International Journal of Technical Research And Applications(IJTRA)

www.ijtra.com

Edited by : A.K. Pandey R.Srivastava E-mail: [email protected]

ABOUT THE PUBLICATION

IJTRA is the online/print publication with e-ISSN 2320-8163 and p-ISSN 2321-7332 which gives opportunity to technical Authors to publish their paper (Research/Review/Case study etc). IJTRA give high indexing with the help of Google Scholar, Research Gate, WikiCFP, Scribd, SlideShare, Open Research, Wepapers, issuu etc . We aim to cover the latest outstanding developments in the field of science, technology and other educational sectors. We also aim to reach authors and researchers world-wide which enable them to express their work and development comprehensively. Sure that our journal will act as a scientific platform for all researchers to publish their works online. We invite all authors to submit their manuscripts to publish with us. We request all authors to send only original and genuine work for review if our team found any fake or copy work then the paper will be rejected. Under the copyright claim section people can calm if they found fake and unauthorized work by any other author. This is a platform where authors represents there work globally. It has been observed that some authors/researchers have depth knowledge in their working field and they work hard from certain time. But they fail to express their work internationally. IJTRA is an online publication which promotes their work globally with the help of high indexing websites. In this way authors’ work reaches to the target audience. We also welcome your suggestions in our official email address is [email protected] for the improvement of our online journal. . We know that your suggestions will be very helpful for us and we will implement it as soon as possible. Thank you for your kind wisdom.

Regards Team IJTRA www.ijtra.com Email: [email protected] Follow us: www.facebook.com/ijtra

INTERNATIONAL JOURNAL OF TECHNICAL RESEARCH AND APPLICATIONS (IJTRA) (IJTRA is a high-quality scientific journal devoted to fields of Science, Technology & Engineering. It is publish online/print format with the e-ISSN 2320-8163 & p-ISSN 2321-7332.) .

Introduction: The Editorial Board is very committed to build the Journal as one of the leading international journals in The field of sciences in the next few years. With the support of our member of editorial board and Team IJTRA, it is expected that a heavy resource to be channelled into the Journal to establish its international reputation. The Journal's reputation will be enhanced from arrangements with several organizers of international conferences in publishing selected best papers of the conference proceedings. Aims and Scope: International Journal of Technical Research and Applications (IJTRA) is a refereed international journal to be of interest and use to all those concerned with research in various fields of, or closely related to, Science, Technology & Engineering disciplines. : International Journal of Technical Research and Applications (IJTRA) aims to provide a highly readable and valuable addition to the literature which will serve as an indispensable reference tool for years to come. The coverage of the journal includes all new theoretical and experimental findings in the fields of Science, Technology & Engineering or any closely related fields. The journal also encourages the submission of critical review articles covering advances in recent research of such fields as well as technical notes. Guide for Authors Manuscript Submission High-quality submissions to this new journal are welcome now and manuscripts may be either submitted online or mail. Online: For online submission upload one copy of the full paper including graphics and all figures at the online submission site, accessed via E-mail. [email protected]. The manuscript must be written in MS Word Format. All correspondence, including notification of the Editor's decision and requests for revision, takes place by e-mail and via the Author's homepage, removing the need for a hard-copy paper trail. By Mail: Manuscripts (1 original and 3 copies) accompanied by a covering letter may be sent to the Editor-in-Chief. However, a copy of the original manuscript, including original figures, and the electronic files should be sent to the Editor-in-Chief. Authors should also submit electronic files on disk (one disk for text material and a separate disk for graphics), retaining a backup copy for reference and safety. Note that contributions may be either submitted online or sent by mail. Please do NOT submit via both routes. This will cause confusion and may lead to delay in article publication. Online submission is preferred. Submission address and contact: A K Pandey, Editor-in-Chief International Journal of Technical Research and Application (IJTRA), 13/28 Vikas Nagar, Lucknow U.P. 226022 (INDIA) Types of contributions: Original research/review papers Corresponding author: Clearly indicate who is responsible for correspondence at all stages of refereeing and publication, including post-publication. Ensure that telephone and fax

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Text Layout: Title should be in fount size 24, name of the author etc should be in font size 12. Remaining paper show have font size 10. Use shortcut “Fig.” while labelling the figures in bold . heading of table should also in bold font . Corresponding author: Clearly indicate who is responsible for correspondence at all stages of refereeing and publication, including post publication. The corresponding author should be identified with an asterisk and footnote. Ensure that telephone and fax numbers (with country and area code) are provided in addition to the email address and the complete postal address. Full postal addresses must be given for all coauthors. Please consult a recent journal paper for style if possible. Abstract: A self-contained abstract outlining in a single paragraph the aims, scope and conclusions of the paper must be supplied. Keywords: Immediately after the abstract, provide a maximum of six keywords (avoid, for example, 'and', 'of'). Be sparing with abbreviations: only abbreviations firmly established in the field may be eligible. Symbols: All Greek letters and unusual symbols should be identified by name in the margin, the first time they are used. Units: Follow internationally accepted rules and conventions: use the international system of units (SI). If other quantities are mentioned, give their equivalent in SI. Maths: Number consecutively any equations that have to be displayed separately from the text (if referred to explicitly in the text). References: All publications cited in the text should be presented in a list of references following the text of the manuscript. Text: Indicate references by number(s) in square brackets in line with the text. The actual authors can be referred to, but the reference number(s) must always be given. List: Number the references (numbers in square brackets) in the list in the order in which they appear in the text. Examples: Reference to a journal publication: [1] Divya James Bhattachrya S K, Bhattacharya D, Sairam K, Ghosal S (2002) Effect of Withania somnifera glycowithanolides on a rat model of tardive dyskinesia. Phytomedicine 9:167-170 [2] Chopra R N, Chopra I C, Handa KL, Kapur, LD (1958) Indigenous drugs of India UN Dhur and Sons, Calcutta, pp. 436-437 [3] Dewir YH, Chakrabarty D, Lee SH, Hahn EJ, Paek KY (2010). Indirect regeneration of Withania somnifera and comparative analysis of withanolides in in vitro and greenhouse grown plants. Biologia Plantarum 54:357-360

Reference to a chapter in an edited book: [4] Mettam GR, Adams LB. How to prepare an electronic version of your article. In: Jones BS, Smith RZ, editors. Introduction to the electronic age, New York: E-Publishing Inc; 1999, p. 281-304

Free Online Color: If, together with your accepted article, you submit usable color and black/white figures then the journal will ensure that these figures will appear in color on the journal website electronic version. Tables: Tables should be numbered consecutively and given suitable captions and each table should begin on a new page. No vertical rules should be used. Tables should not unnecessarily duplicate results presented elsewhere in the manuscript (for example, in graphs). Footnotes to tables should be typed below the table.

EDITORIAL PREFACE It is my great pleasure to publish the Vol-2 ISSUE-5 of the International Journal of Technical Research and Applications (IJTRA). IJTRA is a refereed, peer reviewed quarterly international journal issued by the Team IJTRA. The journal covers a wide range of research and development concerning science, engineering and technology. Through the publication, we hope to establish and provide an international platform for information exchange in different fields of science, engineering and technology. International Journal of Technical Research and Applications (IJTRA) recently achieves the Impact factor: 4.39 (sjif); and IC Value: 5.79 which is the great achievement for us. We aims to provide a highly readable and valuable addition to the literature, which will serve as an indispensable reference tool for years to come. We are also organizing International conference on :  3-5 November , 2014 Kuala Lumpur  6-9 November, 2014 Singapore Interested author may register themselves at www.grdsweb.org The coverage of the journal includes all new theoretical and experimental findings in all aspects of concerning science, engineering and technology or any closely related fields. The journal also encourages the submission of critical review articles covering advances in recent research of such fields as well as technical notes. The Editorial Board is very committed to build the Journal as one of the leading international journals in concerning science, engineering and technology in the next few years. it is expected that a valuable resource to be channelled into the Journal to establish its international reputation. We have received an excellent response to the previous issues of IJTRA from both academics and practitioners. We are pleased by this response and proud to report that IJTRA is achieving its mission of promoting research and applications in science, engineering and technology. IJTRA will bring you top quality research papers from an international body of contributors and a team of distinguished editors from the world's leading institutions engaged in all aspects of mechanical and industrial engineering. Now, the IJTRA invites contributions from the entire international research community. The new journal will continue to deliver up to date research to a wide range of science, engineering and technology professionals. We would like to thank all members of the editorial board and the international advisory board members for their continued support to IJTRA with their highly valuable advice. Additionally, we would like to thank the manuscript reviewers for providing valuable comments and suggestions to the authors that helped greatly in improving the quality of the papers. My sincere appreciation goes to all authors and readers of IJTRA for their excellent support and timely contribution to this journal. We would be delighted if the IJTRA could deliver valuable and interesting information to the worldwide community of science, engineering and technology. Your cooperation and contribution would be highly appreciated. More information about the IJTRA guidelines for preparing and submitting papers may be obtained from www.ijtra.com Regards Editor_in_Chief www.ijtra.com Email: [email protected] Follow us: www.facebook.com/ijtra

Members of Editorial Board Dr P.K. Trivedi CSIR Scientist(NBRI, Lucknow,India) Post Doc University of Maryland, USA

Dr. Virendra Kumar Scientist UP Remote Sensing Application Centre Land Use and Land Cover Divisional Head

Prof (Dr.) Amarika Singh Dean Institute Of Engineering & Technology, Lucknow A Constituent College Of G.B. Technical University, Lucknow

Prof (Dr.) S. Qamar Abbas Director And Professor; AIMT Department of Computer Science Engineering

Silvia Riva Department of Health Sciences Interdisciplinary centre for Research and Intervention on Decision (IRIDe Centre). Via Festa del Perdono,7 20122 Milan (Italy)

Prof (Dr.) M. I. Khan (IITK) (IITK) Professor; Integral University,India Previously; Assistant Professor University of Basrah, IRAQ Professor Univ. of Garyounis, Libya

Prof(Dr.) Mohamed Hussein Director/Professor; Jahangirabad Institute of Engineering & Technology Department of Computer Science Engineering

Ali I.Al-Mosawi Lecturer in Technical Institute-Babylon,Machines Depart, IRAQ M.Sc. in Materials Engineering

Prof.(Dr.) Vikas Misra Dean / Director / Principal Allen House Institute of Technology Department of Mechanical Engineering

Dr. Abdulrahman S. Alanazi Consultant Clinical Pharmacist Saudi Arabia

Dr. Neelam Pathak Professor; Integral University,India Department Of Bio-Technology Post-Doc University of Maryland, USA

Prof (Dr.) Vinodini Katiyar Professor & Dean at Shri Ramswaroop Memorial Group of Professional Colleges Department of Computer Science & Engineering

Dr. Taghreed Hashim Al-Noor Professor; Chemistry Department, Faculty of Science of Ibn-Al-Haitham Education College University of Baghdad, Baghdad

Dr. K. M. Moeed Associate Professor Integral University, India Department of Mechanical Engineering

Dr. Sudhish Kumar Shukla (IIT;BHU) Professor; Manav Rachna College of Engineering,Faridabad Department of Applied Science Post-Doc North West University, South Africa.

Dr Ravi Shankar Mishra Professor,HOD;Sagar Institute Of Science & Technolgy Bhopal Department of electronics and communication Engineering Maulana Azad National Institute of Technology, Bhopal, India

Prof Yudhishthir Raut Department of electronics and communication Engineering Professor;Sagar Institute of Research & Technology Bhopal Ph.D ;Rajiv Gandhi Proudyogiki Vishwavidyalaya Bhopal, India

Mr. Pyie Phyo Maung Department of Biotechnology, Technological University Kyaukse, Kyaukse Township, Mandalay Division, Myanma Mrs Ritu Gulati Faculty of Architecture GBTU, Lucknow. Specialization in Environment and Energy CEPT University Ahemdabad, India *

Mr Faizan Sayed Ali Asst. Manager Bureau of Research on Industry & Economic Fundamentals Specialization in Department of CIM Engineering Visvesvaraya Technological University, Karnataka

Dr. Maneesh Kumar Srivastav Asst. Prof V. L. College of Pharmacy, Raichur- Karnataka Department of Medicinal Chemistry

CONTENTS SL.NO.

Page No.

Manuscript Title IDENTIFICATIONS OF ELECTRICAL AND ELECTRONIC EQUIPMENT

1.

01-03

POLYMER WASTE TYPES USING MFI, DENSITY AND IR (Anas Mohammed Elhafiz Dafa Alla, Ahmed Ibrahim Seedahmed) ASSESSMENT OF HEAVY METALS CONCENTRATION IN INDIAN AND

2.

04-08

PAKISTANI VEGETABLES (Osama Sarwar Khan, Farooq Ahmad, Adnan Skhawat Ali, Rana Muhammad Kamal, Umar Ashraf) ENERGY AWARE INFORMATION DISSEMINATION STRATEGIES TO

3.

09-11

IMPROVE LIFETIME OF A WSN (Madhu G.C, J. Jhansi) A NETWORK DATA AND COMMUNICATION ANALYSIS BASED COMBINED

4.

12-15

APPROACH TO IMPROVE VIDEO TRANSMISSION IN MANET (Madhu G.C, J. Jhansi) DIFFUSER ANGLE CONTROL TO AVOID FLOW SEPARATION

5

16-21

(Vinod Chandavari, Mr. Sanjeev Palekar) SYNTHESIS, PHYSICO-CHEMICAL AND ANTIMICROBIAL PROPERTIES OF

6.

SOME METAL (II) -MIXED LIGAND COMPLEXES OF TRIDENTATE SCHIFF

22-28

BASE DERIVES FROM Β-LACTAM ANTIBIOTIC {(CEPHALEXIN MONO HYDRATE)-4-CHLOROBENZALDEHYDE} AND SACCHARIN (Taghreed. H. Al-Noor, Amer. J. Jarad, Abaas Obaid Hussein) CAUSES AND EVALUATION OF CRACKS IN CONCRETE STRUCTURES 7.

29-33

(Syed Mohd Mehndi, Prof. Meraj Ahmad Khan & Prof. Sabih Ahmad) DEVELOPMENT OF A FRAMEWORK FOR PRESERVING PRIVATE DATA IN

8.

34-36

WEB DATA MINING (Sabica Ahmad, Shish Ahmad, Jameel Ahmad) RELATIONSHIP BETWEEN HEAVY METAL AND TRANSFER FACTOR FROM

9.

SOIL TO VEGETABLE GROWN IN WASTE WATER IRRIGATED AREA OF

37-41

REWA (M.P.) INDIA (Geetanjali Chauhan & Prof. U.K. Chauhan) STRESS AND COPING STYLE OF URBAN AND RURAL ADOLESCENTS 10.

42-45

(Samata Srivastava, Dr. J. P. Singh, Dr. Om Prakash Srivastava) THE EFFECT OF SPERM PARAMETERS AND BOTH MATERNAL AND

11.

PATERNAL

AGE

ON

OUTCOME

OF

INTRACYTOPLASMIC

INJECTION (Milat Ismail Haje, Christopher Barrett, Kameel M Naoom)

SPERM

46-51

BIO-REMEDIATION OF HEAVY METALS FROM DRINKING WATER BY THE 12.

52-60

HELP OF MICROORGANISMS WITH THE USE OF BIOREACTOR (Arpit Srivastava, Dr. Pradeep Srivastava, Ms. Rupika Sinha, Sarada P. Mallick) KINETIC AND STATIC STUDY ON BIOSORPTION OF HEXAVALENT

13.

CHROMIUM USING TAMARIND POD SHELL AND CARBON AS ADSORBENT

61-66

(Sudhanva.M.Desai, NCLN Charyulu, Satyanarayana V. Suggala) ANAEROBIC DIGESTION OF MUNICIPAL SOLID WASTE USING FUNGI 14.

67-70

CULTURE (ASPERGILLUS FLAVUS ) WITH METHANOGENS (Mahesh Kumar Shetty, Ravishankar R, Ramaraju H K, Jagadish H Patil, Sunil H, Mamatha B.Salimath) AN

15.

EXPERIMENTAL

STUDY

OF

PERFORMANCE

AND

EMISSION

CHARACTERISTICS OF CI ENGINE FUELLED WITH HYBRID BLENDS OF

71-74

BIODIESELS (Shankarappa Kalgudi, K V Suresh) ADAPTIVE FUZZY PID CONTROLLER FOR SPEED CONTROL OF PMSM 16.

75-77

DRIVE SYSTEM (Rajnee Bala Minz, Rajesh Thinga, Supriya Tripathi) MINIMUM DELAY BASED ROUTING PROTOCOL IN MANET

17.

(Abhishek Jain, Ashish Jain, Rohit Thete, Akshay Shelke, Harshada Mare, Prof. S.A.

78-81

Jain) SPLIT BLOCK SUBDIVISION OMINATION IN GRAPHS 18.

82-86

(M.H. Muddebihal, P.Shekanna, Shabbir Ahmed) MONITORING FIXTURES OF CNC MACHINE

19.

87-88

(Pingale Namrata Namdev, Prof. Hate S.G) FUELS FROM PLASTIC WASTES

20.

89-90

(Prajakta Sontakke) MEDICAL DECISION MAKING IN SELECTING DRUGS USING COMPUTER-

21.

91-93

GENERATED VIRTUAL ENVIRONMENTS (Silvia Riva, Gabriella Pravettoni) PRODUCTION OF HARD SHEETS FROM MUNICIPAL SOLID WASTE

22.

94-96

(Mohamed Magzoub Garieb Alla, Amel G. Elsharief) THROUGHPUT ANALYSIS OF MOBILE WIMAX NETWORK UNDER

23.

97-99

MULTIPATH RICIAN FADING CHANNEL (Sunil Kumar Gupta, Jyotsna Sengupta) ANALYSIS

24.

OF

GROUNDWATER

QUALITY

USING

STATISTICAL

TECHNIQUES: A CASE STUDY OF ALIGARH CITY (INDIA)

100-106

(Khwaja M. Anwar, Aggarwal Vanita) HOCSA: AN EFFICIENT DOWNLINK BURST ALLOCATION ALGORITHM TO 25.

ACHIEVE HIGH FRAME UTILIZATION (Rabia Sehgal, Maninder Singh)

107-112

TRACKING AND CHECKING CARGO CONTAINERS PILFERAGE USING 26.

113-116

ELECTRONIC LOCK (Sandeep Singh R, Feroz Morab, Sadiya Thazeen, Mohamed Najmus Saqhib) RESEARCH FRONTS OF WEB PERSONALIZATION: A SURVEY

27.

117-121

(Deepti Sharda, Sonal Chawla) MULTIPATH ROUTING PROTOCOLS FOR MOBILE AD HOC NETWORK

28.

A 29.

122-125

(Amit Sharma, kshitij shinghal, Pushpendra Vikram Singh, Himansu Verma) WEB-BASED

EDUCATIONAL

SYSTEM

FOR

LEARNING

DATA

STRUCTURES (Valentina S. Dyankovaa, Stoyan N. Kapralovb, Milko I. Yankovc and Yumit N. Ismailovd)

126-132

International Journal of Technical Research and Applications e-ISSN: 2320-8163, www.ijtra.com Volume 2, Issue 5 (Sep-Oct 2014), PP. 01-03

IDENTIFICATIONS OF ELECTRICAL AND ELECTRONIC EQUIPMENT POLYMER WASTE TYPES USING MFI, DENSITY AND IR Anas Mohammed Elhafiz Dafa Alla1, Ahmed Ibrahim Seedahmed2 1, 2

Department of Plastic Engineering, College of Engineering, Sudan University of Science and Technology, Khartoum P. O. Box: 72, Sudan [email protected] Abstract:- The main objective of this work is to reduce polymer Waste from Electrical and Electronic Equipment (WEEE) disposal to landfill and hence reduce their negative impacts to environment, and to produce useful products suitable for demanded application using WEEE waste as raw materials and to reduce virgin materials used in production of Electrical and Electronic equipment by using WEEE through Identifications the materials used in manufacturing of the EEE. Four type of (EEE) (Keyboard, colored and Black printer and Mouse) were chosen and the analytical result (Density, Melt Flow Index and Infer Red) showed that the polymer type was used in manufacturing of this samples was ABS material for three type and the forth one Mouse is recycled material. This result emphasizes and achieves the three goals of this paper that the recycling processes can solve the problem of polymer waste. Keywords: Waste from Electrical and Electronic Equipment, IR, MFI, ABS.

I. INTRODUCTION According to modern systems of waste management, waste may be classified to different types including: 1. Municipal waste includes: households waste, commercial waste, and demolition waste 2. Hazardous waste includes industrial waste 3. Bio-medical waste includes clinical waste 4. Special hazardous waste includes radioactive waste, explosives waste, electrical and electronic waste. Considering the fourth type, electric and electronic equipment including personal computers, Compact Disks, TV sets, refrigerators, washing machines, and many other dailylife items is one of the fastest growing areas of manufacturing industry today. This rapidly advancing technology together with the increasingly short product life cycles have led to huge volumes of relatively new electronic goods being discarded. This has resulted in a continuous increase of Waste of Electric and Electronic Equipment (WEEE) with estimates of more than 6 million tones annual production or up to 10 kg per person per year in 2005. It has been estimated to be as high as 12 million tons in 2015. Since 1980, the share of plastics in Electrical and Electronic Equipment (EEE) has continuously increased from about 14% to 18% in 1992, 22% in 2000 and estimated 23% in 2005. In 2008, the plastics share from European waste electrical and electronic equipment (WEEE) over all categories was estimated to amount to 20.6 %.

Figure1: Wasted Electronic Devices such as computer Monitors

Figure2: A collection of WEEE Waste Despite of all advantages of Plastic in different uses, but wastes represent a significant environmental impact necessitate some measures to get rid of it. Although, a variety of techniques have been developed for the recycling of polymers in general and particularly for WEEE, the high cost associated with these methods usually leads to a disposal of plastics from WEEE to sanitary landfills. The main drawback that obstructs material recovery from plastics contained in WEEE is the variety of polymers that are being used, resulting to a difficulty in sorting and recycling. Another relevant drawback in dealing with treatment of WEEE is that very often they contain brominated aromatic compounds, used as fire retardants. So there are many procedures to recycle polymer waste one of it is thermal treatment of such chemicals is likely to produce extremely toxic halogenated dibenzodioxins and dibenzofurans. During last years some work has been carried out on the development of different methods to recycle or give added-value to WEEE. II. Materials A. WEEE materials Four different samples of WEEE viz.: keyboard, mouse, colored printing cartridge and black printing cartridge were selected based on the rate of their consumption. 1|Page

International Journal of Technical Research and Applications e-ISSN: 2320-8163, www.ijtra.com Volume 2, Issue 5 (Sep-Oct 2014), PP. 01-03 was measured. The pycnometer was emptied and filled it with distilled water only. Filter paper was used to dry the spare water again and weight was measured. The experiment was then repeated for all samples 3. MFI (Melt Flow Index): Approximately (6 gm) of sample was loaded into the barrel of the melt flow apparatuses, which has been heated to a temperature 190 . A weight specific for the material was applied to a plunger and the molten material was forced through the die. Melt flow rat values were calculated in 8 mg/10 min using the following model: Figure3: Selected WEEE samples B. Preparations of samples Selected samples were cleaned with soap and water, then dismantled to separate polymer materials from the other materials ,then crushed and grinded for a laboratory analysis to determine and identify the type of the polymer and additives used in the samples under question.

Figure4: Preparation of Samples C. Testing and Identification Methods: The type of polymers was determines using relevant chemical and instruments. 1. IR Spectrophotometer Finely crushed solid samples were and grinded with KBr, then pressed to make a disc, the disc was used as background in the IR spectrophotometer. Then the device was operated as required for the intended test.

Figure 6: MFI apparatus III. Results The results for both MFI and density were shown in table 2 and the results of the IR analysis where shown in figures 812: Melt Flow Index Sample Density MFI 1 1.053 17.82 2 1.129 21.23 3 0.538 18.05 4 0.649 16.91

Figure 5: Shimatzu IR Spectrophotometer device 2. Density Samples densities were tested using Pycnometer the empty weight of the pycnometer was determined . , then filled to about 1/3 with sample and measure the weight . Water was then added to pycnometer as well as capillary hole in the stopper was filled with water. Water that leaked through the capillary hole was dried with a filter paper and total weight

Figure 7: MFI Keyport sample 2|Page

International Journal of Technical Research and Applications e-ISSN: 2320-8163, www.ijtra.com Volume 2, Issue 5 (Sep-Oct 2014), PP. 01-03 (1.04). This means the material used is not one of these materials because the density is lower than the range of all materials used in manufacturing EEE. MFI According to literature the MFI of PE, PC and ABS is range from (2 – 60), the Results show that the MFI of all samples in the range of (16.908 -21.228) for all samples (Keyboard, Colored and Black printer and Mouse) compared to (2 – 60) in the literature. This means the material used in manufacturing is not one of these materials because the cutting time for all samples was confirmed with standard 15 second but Mouse sample has cutting time 10 second even the MFI in the range. Figure 8: MFI colored printer IR Results show that the IR of all samples in the range of (459.7 3892.48) for three samples (Keyboard, Colored and Black printer) and (555.52 – 3042) for Mouse, that means there was some bands or groups not available in material used in manufacturing Mouse or it was cracking in re- process.

Figure 9: MFI kcalB printer sample

Figure 10: MFI Mouse sample IV. Discussions Density According to the current work results the density of all samples in the range of (1.1 -1.05) for three samples (Keyboard, Colored and Black printer) and 0.64 for Mouse. Compared to literature which points the main polymer used to manufacturing EEE is PE with density range (0.88 – 0.94), PC with density range (1.2 – 1.22) and ABS with density of

V. Conclusions The analytical results confirmed that the material used in manufacturing three samples (Keyboard, Colored and Black printer) have similar properties and the fourth one Mouse has different properties; this results confirmed by re-analysis for allsamplesandrepeatitseveraltimesforthefourthoneMouse. Mentioned results confirm that the material used in the manufacture of the three samples was ABS material according to similarity obtained between the properties of samples with the properties of ABS material, but sample of Mouse showed a difference results for all materials used in the manufacture of EEE, suggesting that the material may be recycled material. REFERENCES [1] http://en.wikipedia.org/wiki/Waste Definitions. [2] Wäger, P., Schluep M. and Müller, E. Substances in Mixed Plastics from Waste Electrical and Electronic Equipment. Swiss Federal Laboratories for Materials Science and Technology September 17, 2010. [3] D.S. Achilias et al. / Journal of Hazardous Materials (2007). [4] Electric And electronic waste, Received 3 September 2008; accepted 2 March 2009 DOI 10.1002/app.30533 Published online 2 June 2009. [5] Dimitris S. Achilias et al.* Laboratory of Organic Chemical Technology, Department of Chemistry, Aristotle University of Thessaloniki, Thessaloniki Greece.Recent Advances in the Chemical Recycling of Polymers (PP, PS, LDPE, HDPE, PVC, PC, Nylon, PMMA) [6] Chemical recycling of plastic wastes made from polyethylene (LDPE and HDPE) and polypropylene (PP) D.S. Achilias a,∗, C. Roupakias a, P. Megalokonomosa, A.A. Lappas b, E.V.Antonakou b Available online 29 June 2007. [7] Facts and Figures on E‐Waste and Recycling February 21, 2012. [8] Recycling of acrylonitrilebutadiene styrene from used refrigerator material,Aminu, Omar ArokeAhmadu Bello University, ZariaFebruary, 2012. [9] Recycling and disposal of electronic waste Health hazards and environmental impacts report 6417 march 2011.

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International Journal of Technical Research and Applications e-ISSN: 2320-8163, www.ijtra.com Volume 2, Issue 5 (Sep-Oct 2014), PP. 04-08

ASSESSMENT OF HEAVY METALS CONCENTRATION IN INDIAN AND PAKISTANI VEGETABLES Osama Sarwar Khan, *Farooq Ahmad, Adnan Skhawat Ali, Rana Muhammad Kamal and Umar Ashraf Sustainable Development Study Centre, GC University, Lahore, Pakistan. [email protected] ABSTRACT: The current research was conducted to quantify the heavy metals accumulation in vegetables imported from India and compared with same vegetables collected from vegetable market in Pakistan. Green chili, capsicum, tomato and ginger were selected to analyze their heavy metal contents by atomic absorption spectrophotometer. Samples were prepared by dry ash method and wet digestion method to find out the efficient method for heavy metals analysis. Maximum concentration of heavy metals detected by dry ash method in Indian vegetables were of Cu (0.34ppm) in capsicum, Cd (0.0ppm) in capsicum, Cr (0.22ppm) in Ginger, Pb (0.22ppm) in ginger and Ni (0.14ppm) in Ginger while in Pakistani vegetables, it were of Cu (0.62ppm) in Tomato, Cd (0.04ppm) in Capsicum, Cr (0.17ppm) in Tomato, Pb (0.36ppm) in Ginger. Heavy metal contents determined by wet digestion method were of Cu (0.57ppm) in Ginger, Cd (0.01ppm) in capsicum, Cr (0.17ppm) in Ginger, Pb (0.27ppm) in capsicum while in Pakistani vegetables these were of Cu (0.19ppm) in Ginger, Cd (0.04ppm) in green chili, Cr (0.09ppm) in Tomato, Pb (0.25ppm) in Ginger. It was found that the concentrations of these heavy metals in vegetables of both the countries were within WHO/FAO permissible limits so at present these are not hazardous but long term use of these vegetables can magnify heavy metals contents in human body. For statistical analysis two factor ANOVA was run, which indicated that almost all the vegetables had accumulated heavy metals but there was a difference in the uptake of Indian and Pakistani vegetables. Keywords: Heavy metals, Vegetables, Green chili, Capsicum, Ginger.

I. INTRODUCTION In Pakistan industrial effluent and untreated sewage are being discharged into surface water bodies. The water deficiency in country, forces the farmers to use wastewater for irrigation of their crops and vegetables fields. Sewage water disposal in big cities of Pakistan and its hazardous effects are worsen with the passage of time because untreated sewage water is used for growing crops in the surroundings of urban areas [1]. Sewage and industrial wastewater contains high level of organic matter and nutrients along with heavy metals like Fe, Mn, Cu, Zn, Pb, Cr, Ni, Cd and Co. Plants have high capacity for accumulation of the heavy metal contents, some species accumulate specific heavy metals while other accumulate all heavy metals, which cause detrimental effects on human health. Leafy vegetables accumulate more concentration of heavy metals when grown in contaminated soil and water [2].It has been widely reported that health problems occurred due to heavy metals contamination of soil [3]. Metals such as iron, copper, zinc and manganese are essential metals but they may produce toxic effects when their levels exceed certain limits in organisms. High level of copper may produce toxic effects such as dermatitis and liver cirrhosis when consumed in excessive amounts in foods [4]. The objectives of this study

were to estimate heavy metal concentration in vegetables imported from India and to compare the heavy metal contents of Indian vegetable with Pakistani vegetables collected from vegetable and fruit market. II. MATERIALS AND METHODS The present study was carried out to analyze the contamination of the heavy metals concentration in vegetables imported from India and compared with vegetables grown in Pakistan. A. Collection of samples: The samples of vegetables i.e. Tomatoes (lycopersicon esculentum), Ginger (Zingiber officinale), Green chilli (Capsicum frutescens), Capsicum (capsicum annum) that imported from India to Pakistan were collected from trucks which were shifting the vegetables from Wagha border to vegetable market. Same Pakistani vegetable samples were collected from Lari Adda Mandi and Iqbal Town market Lahore. The samples were taken in winter season in the month of December. B. Pretreatment of vegetable samples: The vegetables that collected from different sites coming from Wagha border were individually washed by distilled water to remove dust particles and non-edible parts were removed from them. After washing and cutting, the vegetables were dried in open air and then these vegetables were placed in an oven for 2-3 days at 80 °C. The hard dried vegetables were broken into small pieces by hammer and then these pieces were grinded into a fine powder (80 mesh) using a commercial blender (TSK-West point, France). The powdered material was stored in polythene bags and placed aside until further procedure was done. C. Heavy metal analysis: Samples were prepared for the analysis of heavy metals by dry ash method and wet digestion method to measure the process efficiency. D. Dry ash method: Electronic balance was used to weigh 1g powered sample of each vegetable in boron free silica crucibles then these samples were placed in the muffle furnace at 450 0C for at least two hours until ash was formed. Furnace was left for some time to get cool. Samples were removed from furnace and added 10ml of 0.7N H2SO4. Mixed the samples thoroughly and left the samples for one hour. A conical flask of 500ml was used to filter the samples with Whatmann filter paper no.42 and washed two to three times by using 5.0ml of 0.7N H2SO4. Samples were filtered again in volumetric flasks were used for heavy metal analysis.

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International Journal of Technical Research and Applications e-ISSN: 2320-8163, www.ijtra.com Volume 2, Issue 5 (Sep-Oct 2014), PP. 04-08

II. RESULTS AND DISCUSSION Deposition of heavy metals are associated with a wide range of sources such as brick kilns, small level industries (metal smelting, metal products, battery production, cable coating industries), suspended road dust, vehicular emission, diesel generators and coal combustion. Indian coal has poor quality and high concentration of heavy metals. These are all important contributor of heavy metals present in vegetables. Another source of heavy metal contamination in vegetables is the wastewater produced from domestic and industrial areas and used for irrigation purpose. This wastewater not only contaminates soil but also contaminate crops and vegetables grown in those fields containing contaminated soil. Other sources include excessive use of pesticides, fertilizers and sewage sludge. Industrial wastewater used for irrigation could be the major reason of heavy metal accumulation in vegetables. Cadmium can easily be taken up by the food crops especially leafy vegetables. Different vegetable species contain different heavy metals concentration depending on environmental conditions such as plant availability, metal species and type of irrigation practice. Heavy metal concentrations of plants is directly associated with their concentrations in soils, but their levels significantly differ with plant species [5]. A. Comparison of Pakistan and Indian Vegetables by Dry Ash Method: 1. Heavy metal concentration in Green chili The heavy metal concentration of Cu and Pb obtained by dry ash method in Indian vegetables was 0.29ppm and 0.11ppm respectively and value of Cd, Cr and Ni were below detection limit. The value of Cu and Pb obtained in Pakistani vegetables by dry ash method was 0.07ppm and 0.18ppm and value of Cd, Cr and Ni were below detection limit (Fig. 1). It have been reported that local residents of an area near a smelter in Nanning, China have been exposed to Cd and Pb through consumption of vegetables but no risk was found for Cu and Zn [6, 7].

Heavy metal concentration

Pak dry ash method

India dry ash method

0.35 0.28 0.21 0.14 0.07 0 Cu

Cd

Cr

Pb

Ni

Heavy metals in Green chilli

Fig. 1: Heavy metal concentration in Indian and Pakistani Green chili by dry ash method. 2. Heavy metal concentration in Capsicum: The heavy metal concentration of Cu, Cd, Cr, Pb and Ni obtained by dry ash method in Indian vegetables was 0.34ppm, 0.01ppm, 0.09ppm, 0.12ppm and 0.13ppm respectively and values of Cu, Cd, Cr, Pb and Ni obtained in Pakistani vegetables by dry ash method were 0.08ppm, 0.04ppm, below detection limit, 0.07ppm and below detection limit respectively (Fig. 2). It have been studied the heavy metal contents in different vegetables grown in the lands irrigated by wastewater and noted the concentration of Cr to be within the safe limits [8]. Pak dry ash method Heavy metal concentration

E. Wet digestion method: In wet digestion method, 0.5g sample of each vegetable was weighed by weighing balance and 5ml of concentrated HNO3 was added into digestion flasks. Same quantity of HNO3 was also added into empty digestion flask to run the blank sample. Kjeldahl digestion unit was used to digest samples at 80-90ºC for two hours. Temperature increased to 150ºC (boiling point) and 3 to 5ml of 30%H2O2 along with concentrated HNO3 were added to start and continued the digestion until the clean solution obtained. Samples were cooled at room temperature. Solutions were filtered by Whatmann filter paper no. 42. Final volume was made to 25ml by using distilled water. Samples of both dry ash method and wet digestion method were put in an analyzer for the analysis of heavy metals by Atomic Absorption Spectrophotometer (FAAS, Shimadzu AA-7000F). F. Statistical Analysis: Concentrations of metals in various vegetables dry ash method and wet digestion method were compared by SPSS version-19.

India dry ash method

0.35 0.3 0.25 0.2 0.15 0.1 0.05 0 Cu

Cd

Cr

Pb

Ni

Heavy metals in Capsicum

Fig. 2: Heavy metal concentration in Indian and Pakistani Capsicum by dry ash method. 3. Heavy metal concentration in Tomato: The heavy metal concentration of Cu, Cd, Cr, Pb and Ni obtained by dry ash method in Indian vegetables was 1.27ppm, below detection limit, 0.18ppm, 0.13ppm and 0.05ppm respectively and values of Cu, Cd, Cr, Pb and Ni obtained in Pakistani vegetables by dry ash method were 0.62ppm, below detection limit, 0.17ppm, 0.23ppm and below detection limit respectively (Fig. 3). It have been analyzed various vegetables (cucumber, tomato, green pepper, lettuce, parsley, onion, bean, eggplant, pepper mint, pumpkin and okra) and reported that the Zn concentration (3.56–4.592 mg kg-1) was within the recommended international standards[9].

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International Journal of Technical Research and Applications e-ISSN: 2320-8163, www.ijtra.com Volume 2, Issue 5 (Sep-Oct 2014), PP. 04-08 India dry ash method

Pak wet method

Heavy metal concentration

Heavy metal concentration

Pak dry ash method 1.2 1 0.8 0.6 0.4 0.2 0 Cu

Cd

Cr

Pb

Indian wet method

0.3 0.25 0.2 0.15 0.1 0.05 0 Cu

Ni

Cd

Cr

Pb

Ni

Heavy metals in Green chilli

Heavy metals in Tomato

Fig. 3: Heavy metal concentration in Indian and Pakistani Tomato by dry ash method.

Fig. 5: Heavy metal concentration in Indian and Pakistani Green chili by wet digestion method.

4. Heavy metal concentration in Ginger: The heavy metal concentration of Cu, Cd, Cr, Pb and Ni obtained by dry ash method in Indian vegetables was 1.13ppm, below detection limit, 0.22ppm, 0.22ppm and 0.14ppm respectively and values of Cu, Cd, Cr, Pb and Ni obtained in Pakistani vegetables by dry ash method were 0.39ppm, below detection limit, 0.09ppm, and 0.36ppm and below detection limit respectively (Fig. 4).

2. Heavy metal concentration in Capsicum: The heavy metal concentration of Cu, Cd, Cr, Pb and Ni obtained by wet digestion method in Indian vegetables was 0.43ppm, 0.01ppm, below detection limit, 0.27ppm and below detection limit respectively and values of Cu, Cd, Cr, Pb and Ni obtained in Pakistani vegetables by wet digestion method were 0.10ppm, 0.01ppm, 0.08ppm, 0.17ppm and below detection limit respectively (Fig. 6). Pak wet method

India dry ash method Heavy metal concentration

1.2 1 0.8 0.6 0.4

Indian wet method

0.5 0.4 0.3 0.2 0.1 0 Cu

Cd

0.2

Cr

Pb

Ni

Heavy metals in Capsicum

0 Cu

Cd

Cr

Pb

Ni

Heavy metals in Ginger

Fig. 4: Heavy metal concentration in Indian and Pakistani Ginger by dry ash method. B. Comparison of Pakistan and Indian Vegetables by wet digestion Method: 1. Heavy metal concentration in Green chili: The heavy metal concentration of Cu, Cd, Cr, Pb and Ni obtained by wet digestion method in Indian vegetables was 0.24ppm, below detection limit, below detection limit, 0.13ppm and below detection limit respectively and values of Cu, Cd, Cr, Pb and Ni obtained in Pakistani vegetables by wet digestion method were 0.06ppm, 0.02ppm, 0.07ppm, 0.20ppm and below detection limit respectively (Fig. 5). The estimated intake rates of Cu and Zn suggested that the contribution of vegetables to the intake of these heavy metals is low and does not pose potential health risk to consumers of vegetables [10].

Fig. 6: Heavy metal concentration in Indian and Pakistani Capsicum by wet digestion method. 3. Heavy metal concentration in Tomato: The heavy metal concentration of Cu, Cd, Cr, Pb and Ni obtained by wet digestion method in Indian vegetables was 0.28ppm, below detection limit, 0.10ppm, 0.15ppm and below detection limit respectively and value of Cu, Cd, Cr, Pb and Ni obtained in Pakistani vegetables by wet digestion method were 0.14ppm, 0.01ppm, 0.09ppm, 0.25ppm and below detection limit respectively (Fig. 7). Pak wet method Heavy metal concentration

Heavy metal concentration

Pak dry ash method

Indian wet method

0.3 0.25 0.2 0.15 0.1 0.05 0 Cu

Cd

Cr

Pb

Ni

Heavy metals in Tomato

Fig. 7: Heavy metal concentration in Indian and Pakistani Tomato by wet digestion method. 6|Page

Dry Ash Method

International Journal of Technical Research and Applications e-ISSN: 2320-8163, www.ijtra.com Volume 2, Issue 5 (Sep-Oct 2014), PP. 04-08 4. Heavy metal concentration in Ginger: Table 2: Relationship of copper, cadmium, chromium, lead The heavy metal concentration of Cu, Cd, Cr, Pb and Ni and nickel uptake in various vegetables of India and obtained by wet digestion method in Indian vegetables was Pakistan by dry ash method. 0.57ppm, below detection limit, 0.08ppm, 0.15ppm and below Concentration SS df MS F P-value F crit detection limit respectively and values of Cu, Cd, Cr, Pb and of metals in Ni obtained in Pakistani vegetables by wet digestion method vegetables were 0.14ppm, 0.02ppm, 0.17ppm, 0.25ppm and below Copper 0.901938 3 0.300646 8.489822 0.056199 9.276628 detection limit respectively (Fig. 8). Heavy metals determined in different vegetables showed that the concentrations of Cu, Cadmium 0.00015 3 0.00005 2.77 1.17 9.276628 Zn and Cd have often exceeded the safe limits of both Indian Chromium 0.043338 3 0.014446 7.687361 0.063962 9.276628 and FAO/WHO standards [11- 13]. However the concentration of Cu, Cd, Cr, Pb and Ni were lowered than Lead 0.039438 3 0.013146 4.412587 0.127078 9.276628 given standard of WHO by both dry ash method and wet digestion methods but consumption of contaminated Nickel 0.0067 3 0.002233 1 0.5 9.276628 vegetables may pose risk to human health. Heavy metal concentration

Pak wet method

Indian wet method

0.6 0.5 0.4 0.3 0.2 0.1 0 Cu

Cd

Cr

Pb

Ni

Heavy metals in Ginger

Fig. 8: Heavy metal concentration in Indian and Pakistani Capsicum by wet digestion method. A. Statistical Analysis: It was analyzed that the F value of Cu, Cd, Cr, Pb and Ni in vegetables were less than F Crit hence there were no difference in the uptake of Cu, Cd, Cr, Pb and Ni in different vegetables which means that all the vegetables contained Cu, Cd, Cr, Pb and Ni in it but the F value among the countries was more than F Crit value so there was a significant difference of concentration of Cu, Cd, Cr, Pb and Ni in vegetables of India and Pakistan (Table 1& 2).

Wet Digestion Method

Table 1: Relationship of copper, cadmium, chromium, lead and nickel uptake in various vegetables of India and Pakistan by wet digestion method. Concentrati on of metals in vegetables Copper Cadmium Chromium Lead Nickel

SS

d MS f

F

Pvalu e

F crit

0.059 5 3.75

3 0.01 9833 3 1.25

3.48 9736 1

0.16 6006 0.5

1.06 4 0.18 0212 6553 5

0.48 03 0.90 3481 ----

9.27 6628 9.27 6628 9.27 7 9.27 6628 9.27 6628

0.010 8 0.002 55 0

3 0.00 36 3 0.00 085 3 0

III. Conclusions This research was conducted to quantify the heavy metals concentration in Pakistani and Indian vegetables. Samples were collected from the market. Pakistani vegetables were collected from vegetable market of Iqbal Town. Samples of Indian vegetables were collected from “lari adda mandi” from the trucks coming from Wagha Border. Samples of Indian and Pakistani vegetables were analyzed by using dry ash and wet digestion method. Heavy metals were analyzed both in Pakistani and Indian vegetables by using atomic absorption spectrophotometer. It was found that both Pakistani and Indian vegetables were contaminated with heavy metals but the concentration of these metals was not higher than WHO/FAO standards limits. As the long term usage of these contaminated vegetables may cause their accumulation in human body which can cause hazardous effects later in their lives. It was noted from the results that heavy metal contents were detected to be similar with both dry ash and wet methods except few in which concentration was detected to be more by dry ash method. IV. Acknowledgements The authors acknowledge Government College University Lahore for providing funding for the current study. The complete research work was done in laboratories of Sustainable Development Study Centre and Department of Chemistry, GC University Lahore which were equipped with all the materials necessary for this study. The authors also acknowledge Muhammad Tariq, Scientific Officer of PCSIR laboratories Lahore, Pakistan. REFERENCES [1] Yamin M T, Ahmed N (2007). Influence of hudiara drain water irrigation on trace elements load in soil and uptake by vegetables.Journal of Applied Science Environmental Management 11(2): 169-172 [2] Farooq M, Anwar F, Rashid U (2008). Appraisal of heavy metal contents in different vegetables grown in the vicinity of an industrial area.Pakistan Journal of Botany40(5): 2099-2106 [3] Singh A, Sharma R K, Agrawal M, Marshall F M (2010). Risk assessment of heavy metal toxicity through contaminated vegetables from waste water irrigated area of Varanasi,India.Tropical Ecology51: 375-387 [4] Aktan N,Tekin-Özan S (2012). Levels of some heavy metals in water and tissues of chub mackerel (Scomberjaponicus) compared with physico-chemical parameters, seasons and size

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[5]

[6]

[7]

[8] [9]

[10]

[11]

[12]

[13]

of the fish. The Journalof Animal & Plant Science 22(3): 605613 Öztürk E, Atsan E, PolatT, Kara K (2011). Variation in heavy metal concentrations of potato (Solanum tuberosum L.) cultivars.The Journal of Animal & Plant Science 21(2): 235-239 Cui Y J, Zhu Y G, Zhai R H, Chen D Y, Huang Y Z, QiuandY, Liang J Z (2004). A comparative evaluation of heavy metals in commercial wheat flours sold in calabar-Nigeria. Environment International 30: 785-791 Begum H S,Abida I K (2009).Analysis of heavy metal in water ,sediments and fish samples of madivala lake of Bangalore, Karnataka. International Journal of Chemical Technology Research 1(2): 245-249 Sharma R K, Agrawal M, Marshall F (2008).Transport and fate of copper in soils.Environmental Pollution 154: 254-263 Demirezen D, Ahmet A (2006).Seasonal changes of metal accumulation and distribution in shining pondweed (potamogetonlucens). Journal of Food Quality 29: 252-265 Mapanda F, Mangwayana E N, NyamangaraJ, Giller K E (2007). Uptake of heavy metals by vegetables irrigated using wastewater and the subsequent risks in Harare, Zimbabwe. Physical Chemical and Earth Sciences Parts A/B/C, 32(15-18): 1399–1405 Awashthi S K (2000). Prevention of Food Adulteration Act No. 37 of 1954. Central and State Rules as Amended of 1999.3rdEdition. Ashoka Law House, New Delhi Wei M, Yanwen Q, BinghuiZ, Lei Z (2008).Heavy metal pollution in Tianjin Bohai Bay. Journal of Environmental Science 20: 814-819 Rahman A K M R, HossainS M, Akramuzzaman M M (2010).Distribution of heavy metals in rice plant cultivated in industrial effluent receiving soil. Environment Asia 3(2): 15-19

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International Journal of Technical Research and Applications e-ISSN: 2320-8163, www.ijtra.com Volume 2, Issue 5 (Sep-Oct 2014), PP. 09-11

ENERGY AWARE INFORMATION DISSEMINATION STRATEGIES TO IMPROVE LIFETIME OF A WSN Madhu G.C1, J. Jhansi2 1

Assistant Professor, Dept.of EConE 2 Dept.of ECE Sree Venkatesa Perumal College of Engineering and Technology, Puttur, India [email protected], [email protected] Abstract— The wireless sensor node can only be equipped with a limited power source. In some application scenarios, replenishment of power resources might be impossible. Sensor node lifetime, therefore, shows a strong dependence on battery lifetime. Hence, power conservation and power management take on additional importance. The main task of a sensor node in a sensor field is to detect events, perform quick local data processing, and then transmit the data. Power consumption can hence be divided into three domains: sensing, communication, and data processing. One of the most commonly used Power management techniques is to allow a node to follow sleep-wake up-sample-compute-communicate cycle. Based on the amount of the battery availability, by adopting the proper information dissemenitation schemes, the network life time can be extended. This process relies on hardware support for implementing sleep states, permits the power consumption of a node to be reduced by many orders of magnitude. Keywords—WSN, Energy Consumption, Information Dissemination Schemes, Mobile Sensor Node.

I. INTRODUCTION A wireless sensor network consists of thousands of sensor nodes, deployed according to some predefined pattern, over a region of interest. A sensor node has many stringent resource constraints, such as limited battery power, signal processing, computation and communication capabilities, and a less amount of memory. Group of sensor nodes are collaborated with each other to achieve a bigger task efficiently. A sensor node is made up of four basic components: a sensing unit, a processing unit, a transceiver unit and a power unit. Sensing units are composed of two subunits: sensors and analog to digital converters (ADCs). The analog signals produced by the sensors are converted to digital signals by the ADC, and then fed into the processing unit. A transceiver unit connects the node to the network. One of the most important components of a sensor node is the power unit. There are also other subunits, which depends on the application. In many applications, the sensor nodes are often difficult to access, the lifetime of a sensor network depends on the life time of the power resources of the nodes. However, designing energy efficient and low duty cycle radio circuits is still technically challenging task. The main task of a sensor node in a sensor field is to detect events, perform quick local data processing, and then transmit the data. The total power will be consumed to perform the three important tasks: sensing, data processing and communication.

Figure 1.0 The functional blocks of a Sensor Node

Sensing power varies with the nature of applications. The complexity of event sensing also plays an important role in determining energy expenditure. A sensor node consumes maximum energy in data communication. This involves both data transmission and reception. It can be shown that for shortrange communication with low radiation power, transmission and reception energy consumption are nearly the same. A sensor node consists of a short range radio which is used to communicate with neighbouring nodes and the outside world. Radios can operate under the Transmit, Receive, Idle and Sleep modes. It is important to completely shut down the radio rather than put it in the idle mode when it is not transmitting or receiving because of the high power consumed in this mode. A sensor node must have computational abilities and be capable of interacting with its surroundings. The limitations of cost and size lead us to choose complementary metal oxide semiconductor (CMOS) technology for the micro-processor. A CMOS transistor pair draws power every time it is switched. This switching power is proportional to the switching frequency, device capacitance. Reducing the supply voltage is hence an effective means of lowering power consumption in the active state. When a micro-processor handles time-varying computational load, simply reducing the operating frequency during periods of reduced activity results in a linear decrease in power consumption. Communicating one bit over a wireless medium at short ranges consumes more energy than processing that bit. With the current technology, the energy consumption for communication is several magnitudes higher than the energy required for computation. One of the power management strategies is to practice the energy aware information dissemination.

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International Journal of Technical Research and Applications e-ISSN: 2320-8163, www.ijtra.com Volume 2, Issue 5 (Sep-Oct 2014), PP. 09-11 II. INFORMATION DISSEMINATION SCHEMES base node should consist of the amount of the battery power remained and the temperature value. There are four established techniques for information If the available battery power of static node is greater than dissemination in WSNs: 50% but less than 75%, it transmits the averaged value of the Continuous/periodic dissemination: The sensor node sensed samples for every 2 seconds. During the processing continuously reports data in a periodic manner. In this way, time of the data, the transceiver of the base node and the packets are pushed from the network even when the sensed mobile node should be maintained in sleep state. parameter has not significantly changed, hence containing Event driven Data Dissemination: little useful information since the previous transmission. If the available battery power of the mobile node is Query-driven dissemination: The user initiates data transfer greater than 25% but less than 50%, the temperature sensor by querying data from the network. Qualifying nodes reply to continuously sense the temperature values and it will be stored these queries with packets. in the controller and the present sensed value will be compared Event-driven dissemination: The sensor node decides for with the previously stored value in the microcontroller. If there itself what data are worth reporting to a sink node. In that way, occurs a significant deviation in temperature, say 20 C then the redundant transmissions can be minimized. In continuous mobile node will transmit the information to the base node. If reporting, the choice of period duration has a considerable the present temperature is 280 C, let us suppose the present effect on network performance. If a short period is chosen, a sensed value is 290C, the transceiver of the mobile node will large proportion of the packets are likely to be redundant not transmit this information to the base node. It has to containing little useful information, while still consuming transmit only when the temperature is 300C or greater values. energy. If a long period is chosen, the network is likely to When the microcontroller recognized a deviation, an interrupt suffer from the missing of events. While the missing of events will be generated to awaken the transceiver of the mobile can be avoided by locally aggregating the average sensed node. During this time the transceiver of the mobile node is values. In this paper we designed an experiment to implement maintained in sleep state. all the above strategies by using the two mobile sensor nodes Query driven Strategy: which are used to transmit the sensed information from the If the available battery power of the mobile node is greater region of interest to the base station. Recent progress in low than 5% but less than 25%, a request will be sent from the power embedded systems has led to the creation of mobile base node directly to the mobile node to transmit the sensor nodes. Autonomous node mobility brings with it its temperature present at that time. Based on the request own challenges, but also alleviates some of the traditional generation only, the mobile node has to sense the temperature problems associated with static sensor networks. Mobility is and should be transmitted to the base node. Along with the the ability of a sensor node to move intentionally, and without request an interrupt awakens the transceiver and the human assistance. Methods have been suggested to use mobile microcontroller of the mobile node from sleep state to the sensor nodes to physically transport energy in the network active state. If the available battery power of the node is less from areas where it is available in plenty to other regions than 5%, the redundant mobile node has to move towards the where energy availability is scarce. present mobile node to sense the temperature from the region. This mobile node continues the temperature sensing and can III. PROPOSED SYSTEM also be operated in all the above specified strategies. Mean A system is designed to sense a temperature in a region and while the first mobile node battery can be recharged for the will be transmitted to the base node by using a WSN having further use. two manually deployed mobile nodes and one base node. To optimize the power consumption of a WSN, depending upon the available amount of the battery, this system is free to be operated in one of the three strategies. Periodic data Dissemination: If the available battery power of the mobile node is greater Power IC

Temperature Sensor

Microcontroller & Mobilizer platform

IV. RESULTS If the available battery power of the mobile node is greater than 75%, it will transmit the data to the base node in a periodic manner. The information received by the base node should consist of the level of the battery power and the temperature value.

Zigbee

IR Sensor Fig.2.0 Construction of a Mobile Sensor Node than 75%, it will transmit the data to the base node in a periodic manner. The temperature sensor connected to the mobile node senses the temperature from a region and it will be processed by using the microcontroller and will be transmitted to the base node. The information received by the

Figure 3.0 Continuous transmissions of data from the static node to the base node. 10 | P a g e

International Journal of Technical Research and Applications e-ISSN: 2320-8163, www.ijtra.com Volume 2, Issue 5 (Sep-Oct 2014), PP. 09-11 If the battery power of mobile node is greater than 50% but REFERENCES less than 75%, it transmits the averaged value of the sensed [1] Akyildiz, W. Su, Y. Sankarasubramaniam, and E. Cayirci, samples for every 2 seconds.If the battery power of the mobile “A survey on sensor networks,” IEEE Commun. Mag., node is greater than 25% but less than 50%, the sensor vol. 40, no. 8, pp. 102–114, Aug. 2002. continuously sense the temperature and it will be stored in the [2] C. Y. Chong and S. Kumar, “Sensor networks: Evolution, controller. If there occurs a deviation of 20 C then the mobile opportunities, and challenges,” Proc. IEEE, vol. 91, no. 8, node will transmit the information to the base node. pp. 1247–1256, Aug. 2003.

Figure 3.2 Event driven data transmission strategy If the available battery power of the mobile node is less than 5%, the redundant mobile node has to move towards the sensing field and present node has to move away from the field. The new mobile node can also be operated in a similar manner as the previous node.

[3] Ren C.Luo, Ogst Chen,”Mobile sensor node deployment and asynchronous power management for wireless sensor networks” IEEE Transactions on Industrial Electronics, Vol. 59, No. 5, May 2012. [4] G. T. Sibley, M. H. Rahimi, and G. S. Sukhatme, “Robomote: A tiny mobile robot platform for large-scale ad-hoc sensor networks,” in Proc.IEEE Int. Conf. Robot. Autom. 2002, vol. 2, pp. 1143–1148. [5] K. Dantu, M. Rahimi, H. Shah, S. Babel, A. Dhariwal, and G. S. Sukhatme, “Robomote: Enabling mobility in sensor networks, “Center Robot. Embedded Syst., Viterbi School Eng., Univ. Southern California, Los Angeles, CA, Tech. Rep. CRES-04-006, 2004. [6] Nojeong Heo and Pramod K. Varshney,” EnergyEfficient Deployment of Intelligent Mobile Sensor Networks” IEEE Transactions on systems, man and Cybernatics—Part A: Systems and Humans, Vol. 35, No. 1, January 2005.

Figure 3.3 Switching of the data transmission task to the second mobile node.

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International Journal of Technical Research and Applications e-ISSN: 2320-8163, www.ijtra.com Volume 2, Issue 5 (Sep-Oct 2014), PP. 12-15

A NETWORK DATA AND COMMUNICATION ANALYSIS BASED COMBINED APPROACH TO IMPROVE VIDEO TRANSMISSION IN MANET Reena Boora#, Veepin Kumar* # M. Tech Scholar, CSE Deptt. Om Institute of Technology &Management, Guru Jambheshwar University, Hisar (Haryana), India * H.O.D. In CSE Deptt. Om Institute of Technology &Management, Guru Jambheshwar University, Hisar (Haryana), India #[email protected],

Abstract –Video transmission over wireless network requires link reliability. Videos are having more data to be transmitted during communication. The criticality and load of the network increases when some video data is communicated over the network. Firstly, describes the characteristics of Mobile Ad hoc Networks and their Routing protocol, and second a mobile ad hoc network (MANET) which consists of set mobile wireless nodes and one fixed wireless server are design using ns-2. In this research we will simulate three MANET routing protocols such as AODV against three different parameters i.e. delay, network load, throughput and retransmission. Keywords- Multi-media Communication, MANET, QOS, MANET routing protocol (i.e. AODV), NS-2(Network Simulator-2).

I. INTRODUCTION Wireless networks are getting popular due to their convenience of use. Consumer or user is no more dependent on wires where he or she is, easy to move and enjoy being connected to the network. One of the great features of wireless network that makes it fascinating and distinguishable amongst the traditional wired network is its mobility. This feature gives the ability to move freely, while user being connected to the network. The Wireless networks comparatively easy to install, on other hand wired network don’t. Video transmission over wireless networks to multiple mobile users has remained a challenging problem due to potential limitations on bandwidth and the time-varying nature of wireless channels. Video transmission is one of the part in multimedia communication system. As we know that the multimedia has become an essential part of any presentation. The evolution of internet has also increased the demand for multimedia content. Multimedia is the media that uses multiple forms of information content and information processing (e.g. text, audio, video, graphics, animation, interactivity) to inform or entertain the user. Mobile ad hoc networks (MANETs) consist of multiple wireless mobile nodes which dynamically exchange data among themselves. MANETs nodes are distinguished by their memory resources, processing as well as high degree of mobility.[1] I. MANETS ROUTING PROTOCOLS Routing protocols in MANETs (Murty and Das, 2011) are a challenging and attractive tasks, researchers are giving tremendous amount of attention to this key area (Bouke, 2011). MANETs routing protocols are categorized into three different categories according to their functionality. 1. Reactive protocols (i.e. AODV,DSR and DYMO)

*[email protected]

2. Proactive protocols (i.e. DSDV,OLSR,FSR) 3. Hybrid protocols (i.e. ZRP) 1. Reactive protocols - Reactive routing protocols are only search for a route to a destination when they need to send data to that host. 1(a). AODV - AODV is an on-demand routing protocol used in ad hoc networks. This algorithm facilitates a smooth adaptation to changes in the link conditions. 1(b). DSR - Dynamic Source Routing is a reactive routing protocol for manet ad hoc wireless network. Its characteristics has also on-demand like AODV but it’s not table driven. It based on source routing. A node wishing to send a packet specifies the route for that packet. 1(c). DYMO – DYMO is a routing protocol that was created for situations where clients are mobile and communications will be transported through several different clients over a wireless medium Mobile ad-hoc Network (MANET). When a node initiates communication with another host a routing path is found, on demand, and this will result in a bidirectional unicast communication path, if a path is found to the destination. DYMO was created to dynamically handle changes in the network. II. RELATED WORK Extensive research work has been done in the field of MANET routing protocols. Different routing protocols were simulated in different kind of simulators. Here we will discuss different research papers about MANET routing protocols performance. In this we will simulate three MANET routing protocols such as DSR, DYMOUM and AODV against three different parameters i.e. delay, network load, throughput and Retransmission. Due to this characteristic (Keshtgary and Babaiyan, 2012), there are some challenges that protocol designers and network developers are faced with. These challenges include routing, service and frequently topology changes. Therefore routing discovery and maintenance are critical issues in these networks. There are also limited battery power and low bandwidth available in each node. In this paper, we evaluate the performance of four MANET routing protocols using simulations: AODV, OLSR, DSR and GRP.[2] Our evaluation metrics are End-to-End delay, network load, throughput and media access delay. Most of the papers consider the first three parameters, but here we also consider MAC delay. Path routing and protocol selection are the primary strategies to design any wireless network. In Mobile Ad hoc Network 12 | P a g e

International Journal of Technical Research and Applications e-ISSN: 2320-8163, www.ijtra.com Volume 2, Issue 5 (Sep-Oct 2014), PP. 12-15 (MANET) the selected protocol should have best in terms of third stage, the route optimization is done, by analyzing the data delivery and data integrity (Mohapatra and Kanungo, participation of each node in network communication. The 2011). nodes having the heavy participation are ignored for The throughput performance in Mobile Ad Hoc Networks communication whereas the nodes having the lesser (Fazeli and Vaziri, 2011) and compares emulated tested communication participation are considered to perform the results with simulation results from OPNET (Optimized communication over the network. The network design for the Network Engineering Tool). presented work is given here in figure 3.1. This paper presents a performance analysis of two Mobile Ad The presented work is about to provide the effective Hoc Network (Hosek, 2011) routing protocols - Ad Hoc On communication in case of congested network or the DOS Demand Distance Vector (AODV)[8] and Optimized Link infected network. The frame analysis provide the work to State Routing (OLSR). take the earlier decision so that the effective communication. They address the on-demand routing protocols by focusing The effective route generation provides the dynamic analysis on dynamic source routing (DSR) protocol and ad hoc on on network traffic to provide effective network demand distance vector (AODV) routing protocol in WMNs communication. (Guo and Peng, 2010).

 Wireless Ad Hoc Networks Han L mentioned [3] that the wireless ad hoc networks were first deployed in 1990’s Mobile Ad-hoc networks have been widely researched for many years. Mobile Ad-hoc Networks are collection of two or more devices equipped with wireless communications and networking capability. These devices can communicate with other nodes that immediately within their radio range or one that is outside their radio range.

 An Analytical Model Of Tcp Performance Debessay Fesehaye Kassa mentioned [4] that the Transmission Control Protocol (TCP) is the dominant transport layer protocol for the end-to-end control of information transfer. Accurate models of TCP performance are a key and basic step for designing, dimensioning and planning IP (Internet Protocol) networks.

 TCP Performance Over Mobile Ad Hoc Network B. Sikdar et. al. described [5] that TCP is a transport protocol that guarantees reliable ordered delivery of data packets over wired networks. Although it is well tuned for wired networks, TCP performs poorly in mobile ad hoc networks (MANETs). This is because TCP’s implicit assumption that any packet loss is due to congestion is invalid in mobile ad hoc networks where wireless channel errors, link contention, mobility and multi-path routing may significantly corrupt or disorder packet delivery.

 TCP Performance Over Multipath Routing In Mobile Ad Hoc Networks Haejung Lim Kaixin Xu, at all mentioned [6] that in mobile ad hoc networks (MANET), TCP performance is not as stable as in wired networks. TCP performance over a multipath routing protocol is given. Multipath routing can improve the path availability in mobile environment. Thus, it has a great potential to improve TCP performance in ad hoc networks under mobility. III. PROPOSED WORK The presented work is about to perform the effective video communication over the mobile network by performing the three stage work. The first stage of this work is to analyze the video frames so that the frame type of route diversion will be performed. The high quality frames will be transferred from different route. In second stage, the contention window decision is taken by analyzing the network parameters. In

Define Network with N Mobile Nodes

Initialize the video transmission with source and destination node specification Divide the video in smaller frames Perform frame analysis to provide route diversion based on frame analysis Optimize the contention window size to optimize the communication

Analyze the node participation vector to prioritize the nodes

Perform multipath communication on low participating nodes

Analyze the communication under different parameters Figure 3.1: Flow of Work A. ALGORITHM Algorithm(Nodes,N) /*A Mobile Network is defined with N Number of Nodes*/ { Define as Source Node Src and Destination Node Dst Set curNode=Src [Set Src as Current Node] While curNodeDst [Process All Nodes, till Destination Node not occur] { NNodeList=FindNeighbors(Nodes,CurNode) [Identify the Neighbor Node List for CurNode] For i=1 to N NodeList.Length [Process all Neighbor List] { if(Communication(CurNode,NNodeList(i))>0) [If the Neighbor Node is Communicating Node] {

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International Journal of Technical Research and Applications e-ISSN: 2320-8163, www.ijtra.com Volume 2, Issue 5 (Sep-Oct 2014), PP. 12-15 CommuCount=CommuCount+1 Load=Load+DataCount [Perform the Communication Analysis on NeighborNode }} AvgComm=CommCount/NNodeList.length [Find the Average Communication Analysis on neighbor node list] For i=1 to NNodeList.Length [Process all Neighbor List] { if (CommuCount(curNode,NNodeList(i))>AvgComm) { set Participation(i)=1 }else if (CommuCount(curNode,NNodeList(i))>AvgComm*2) { set Participation(i)=2 } else { Set Participation(i)=0 }} Disable All Nodes for Communication having Participation Value 2 nextHop=FindPartipentNode(NNodeList,1) [Identify the Effective Neighbor having Partipation value 1 and set it as Effective Neighbor] Set curNode=nextHop [Set Effective communication node as Next communicating Hop] }} IV. SIMULATION RESULTS The work mainly defines an effective video communication routing in energy effective mobile network. The possible outcomes are the simulation results obtained from NS2 which shows the performance parameters such as transmission rate, loss rate, end-to-end delay, packets send and packets received for the both proposed solution and existing network with attack. The simulation results also provide graphical comparison of the networks.The parameters taken in this work for network generation are given here under Table 4.1. Table 4.1 : Simulation Parameters Parameters

Values

Communication channel

Wireless

Number of Nodes Area

10 800x800

Routing Protocol

AODV

MAC Protocol

802.11

Topology

Random

Communication Delay Energy Adaptive

50 MicroSec Yes

Here figure 4(a) is showing the simulation scenario for mobile network. The figure is showing the network with 10 nodes. The communication is here performed between a node pair and the large circles here shows the communication range of each mobile node.

Figure 4(a): Network Design Here figure 4(b) shows the outcome of data packet transmission in video file communication. Here X- axis represents simulation time and Y-axis represents packet transmission over the network. It shows, the presented work has improved the network throughput.

Figure 4(b) : Packet Transmission Analysis (Existing Versus Proposed Approach) Here figure 4(c) is showing the packet loss analysis as the video data is communicated. Here X-axis represents simulation time and Y-axis represents number of packet lost over the network.

Figure 4(c) : Packet Loss Analysis (Existing Versus Proposed) 14 | P a g e

International Journal of Technical Research and Applications e-ISSN: 2320-8163, www.ijtra.com Volume 2, Issue 5 (Sep-Oct 2014), PP. 12-15 Here figure 4(d) is showing the communication delay VI. FUTURE WORK The presented work is to provide the effective video analysis as the video data is communicated. Here X-axis communication over mobile network by using three stage represents simulation time and Y-axis represents packet delay analysis. The work can be improved under different aspects over the network.  The presented work is about to optimize the network communication by performing the dynamic analysis over the network nodes. The work can be improved by using some session based approach to save the path so that the path identification work will be reduced.  The work is based on the statistical analysis. The work can be improved by using some optimization approach.

[1] [2] [3] [4]

Figure 4(d): Communication Delay Analysis (Existing Versus Proposed Approach) Here figure 4(e) is showing the packet lossrate analysis as the video data is communicated. Here X-axis represents simulation time and Y-axis represents packet delay over the network.

[5]

[6]

[7] [8]

[9]

[10]

[11]

Figure 4(e) : Packet lossrate analysis (Existing Versus Proposed Approach) V. CONCLUSION The presented work is about to provide the video communication over the mobile network. The work is divided in three main stages. In first stage, the video frame analysis is done. In second stage, the optimized contention window specification is performed. At third stage, the route optimization is done by observing the node participation dynamically. In this work a multipath communication is defined to generate the effective route over the network. The work is implemented in NS2 environment. The obtained results show the effective route generation in congested video communication over the mobile network. The results shows that the work has reduce the communication loss and improved the network communication. The results are here shown using XGraph.

[12]

REFERENCES http://www.isi.edu/nsnam/ns/tutorial http://www.isi.edu/nsnam/ns/ns-documentation.html http://dev.scriptics.com/scripting V. C. Frias, G. D. Delgado, and M. A. Igartua, “Multipath routing with layered coded video to provide qos for video streaming over manets," in Proceedings - 2006 IEEE International Conference on Networks, ICON 2006 Networking-Challenges and Frontiers 1, vol. 1, pp. 1-6, September 2006. Fahim Maan, Nauman Mazhar, “Analysis of Performance of widely used MANET routing protocols DSDV, AODV, OLSR , DYMO and DSR with mobility models”{978-1-45771177-0/11/©2011 IEEE} Asad Amir Pirzada, Ryan Wishart and Marius Portmann, “an Congestion-Aware Routing In Hybrid Wireless Mesh Network “{ 1-4244-1230-7/07/© 2007 IEEE} Uyeng trang and Jin Xu,”Fundamental approaches to multicast routing “{0163-6804/07/$20.00 © 2007 IEEE}. Youiti Kado, Azman Osman Lim, and Bing Zhang, “Analysis Of Wireless Mesh Network Routing Protocol For Push-to-Talk Traffic “{1-4244-1251-X/07/©2007 IEEE}. Chen Lijuan, “Research On Routing protocol Applied To Wireless Mesh Network”{ 978-0-7695-3989-8/10© 2010 IEEE}. G. A. Pegueno and J. R. Rivera, “Extension to MAC 802.11 for performance Improvement in MANET”, Karlstads University, Sweden, December 2006. C.Parkins, E.B.Royer, S.Das, A hoc On-Demand Distance Vector (AODV) Routing. July 2003, [Online]. Available: http://www.faqs.org/rfcs/rfc3561.html. [Accessed: April. 10, 2010] C.M barushimana, A.Shahrabi, “Comparative Study of Reactive and Proactive Routing Protocols Performance in Mobile Ad-Hoc Networks”, Workshop on Advance Information Networking and Application, Vol. 2, pp. 679-684, May, 2003.

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DIFFUSER ANGLE CONTROL TO AVOID FLOW SEPARATION Vinod Chandavari1, Mr. Sanjeev Palekar2 M.Tech (APT), Department of Aerospace Propulsion Technology Visvesvaraya Technological University - CPGS Bangalore, Karnataka, India 1 [email protected], [email protected] Abstract— Diffusers are extensively used in centrifugal compressors, axial flow compressors, ram jets, combustion chambers, inlet portions of jet engines and etc. A small change in pressure recovery can increases the efficiency significantly. Therefore diffusers are absolutely essential for good turbo machinery performance. The geometric limitations in aircraft applications where the diffusers need to be specially designed so as to achieve maximum pressure recovery and avoiding flow separation. The study behind the investigation of flow separation in a planar diffuser by varying the diffuser taper angle for axisymmetric expansion. Numerical solution of 2D axisymmetric diffuser model is validated for skin friction coefficient and pressure coefficient along upper and bottom wall surfaces with the experimental results of planar diffuser predicted by Vance Dippold and Nicholas J. Georgiadis in NASA research center [2]. Further the diffuser taper angle is varied for other different angles and results shows the effect of flow separation were it is reduces i.e., for what angle and at which angle it is just avoided. Keywords: Planar Diffuser, CFD, Taper angle, Flow Separation.

I.

INTRODUCTION

Diffusers are integral parts of jet engines and many other devices that depend on fluid flow. Performance of a propulsion system as a whole is dependent on the efficiency of diffusers. Identification of separation within diffusers is important because separation increases drag and causes inflow distortion to engine fans and compressors. Diffuser flow computations are a particularly challenging task for Computation Fluid Dynamics (CFD) simulations due to adverse pressure gradients created by the decelerating flow, frequently resulting in separation. These separations are highly dependent on local turbulence level, viscous wall effects, and diffuser pressure ratio, which are functions of the velocity gradients and the physical geometry. The diffuser is before the combustion chamber that ensures that combustion flame sustenance and velocities are small [2]. 1.1 What is the meaning of Separation or Reverse Flow? The designing of an efficient combustion system is easier if the velocity of the air entering the combustion chamber is as low as possible. The natural movement of the air in a diffusion process is to break away from the walls of the diverging passage, reverse its direction and flow back in the direction of the pressure gradient, as shown in figure 1.1 air deceleration causes loss by reducing the maximum pressure rise [4].

Fig: 1.1 Diffusing Flow

Buice, C.U. and Eaton, J.K [1], was carried out the Experimental work using a larger aspect ratio experimental apparatus, paying extra attention to the treatment of the endwall boundary layers. They are titled as “Experimental Investigation of Flow through an Asymmetric Plane Diffuser,” The results of this experiment are compared to the results of different calculations made for the same diffuser geometry and Reynold number. One of the calculation is Large Eddy Simulation (LES). The other is a Reynold Averaged Navier Stokes (RANS) calculation using v2-f turbulence model. Both calculations captured the major features of the flow including separation and reattachment. Vance Dippold and Nicholas J. Georgiadis[2], they have been performed “Computational Study of Separating Flow in a Planar Subsonic Diffuser” in National Aeronautics and Space Administration is computed with the SST, k-ε, SpalartAllmaras and Explicit Algebraic Reynolds Stress turbulence models are compared with experimentally measured velocity profiles and skin friction along the upper and lower walls. Olle Tornblom[3], repeated the experimental work of Buice, C.U. and Eaton, J.K, “Experimental study of the turbulent flow in a plane asymmetric diffuser”, the flow case has been concentrated on in an uniquely composed wind-tunnel under overall controlled conditions. A similar study is made where the measured turbulence data are utilized to assess an explicit algebraic Reynolds stress turbulence model (EARSM) and coefficient of pressure is measured. In this study diffuser gives an idea of choosing the turbulence model and to avoid separation flow by varying the taper angle (7º, 8º, 9º and 10º). The diffuser model and Fluent 14.5 are used, to study the diffuser characteristics with the effect of various factors like Pressure coefficient and Skin friction coefficient. Obtained results are validated against the known experimental results carried out by Vance Dippold and Nicholas J. Georgiadis [2]. II.

PHYSICAL MODEL AND MESH

Diffuser geometric configuration with the height of the inlet channel H = 0.015 meters and the diffuser has a 10ᴼ expansion taper angle and is 21H in length. At the end of the expansion, the diffuser channel is 4.7H in height. Figure 2.1 shows the schematic diagram of diffuser [1]. 16 | P a g e

International Journal of Technical Research and Applications e-ISSN: 2320-8163, www.ijtra.com Volume 2, Issue 5 (Sep-Oct 2014), PP. 16-21 study because the flow through the diffuser user is steady in the mean. In this study, SST-K-ω turbulence models were used with varying complexities and formulations. Understandably, the increased complexity (i.e., increased number of equations) requires more computational time. Thus, the selection of turbulence models with varying complexities provides the opportunity to observe a correlation between modeling accuracy and computational time [4]. Identical boundary conditions were used for all turbulence models. In particular, the inlet conditions were specified as a constant velocity profile corresponding to the bulk inlet velocity, Ub = 20 m/s. Fig: 2.1 Shows the schematic diagram of Diffuser

Figure 2.2 shows the computational domain of 2D that mimics the physical model. The diffuser apparatus can be divided into three sections: an inflow channel, the asymmetric diffuser, and an outflow channel. Figure 2.3 shows the 2D structured mesh for computational domain. Mesh having 41511 nodes and 41000 elements. Mesh Quality: Orthogonal Quality is ranges from 0 to 1, where values close to 0 correspond to low quality. Hence the  Minimum Orthogonal Quality = 0.945334629648056  Y plus value= 1.03

All turbulence models implemented a COUPLED scheme to couple the pressure and velocity. Furthermore, the spatial discretization was accomplished by a second-order accurate upwind scheme for the momentum and a FLUENT standard scheme for the pressure. Any additional closure equations for the various turbulence models were spatially discretized by second-order accurate upwind schemes. In all cases, the corresponding calculation residuals were monitored to convergence at 1*10-05. These residuals included continuity, xvelocity, and y-velocity for all turbulence models. Beyond these generic residuals, any additional closure equations gave additional terms to monitor. The fluid properties were carefully chosen to ensure a matched Reynolds number with the experimental data. Specifically, the fluid density was chosen to be 1.225 kg/m3 and the dynamic viscosity was selected to be 1.789*10-05 kg/m-s. The combination of these values yields the appropriate Reynolds number based on inlet channel height, ReH = 20,000. IV.

Fig: 2.2 Computational domain

VALIDATION

The suitability of solver selection, turbulence model, numerical scheme, discretisation method and convergence criteria used in the present study is validated by comparing the skin friction coefficient and pressure coefficient along the X/H with the experimental data of Vance Dippold and Nicholas J. Georgiadis[2]. Among various turbulence models available in the fluent code, SST-k-ω model are tested with different taper angle (7º, 8º, 9º and 10º). The figures 4.1.1 and 4.1.3 shows skin friction coefficient is 0.006 of Bottom_wall and Top_wall respectively, figure 4.2.1 shows the Pressure coefficient and the figure 4.1.2, 4.1.4 and 4.2.2 shows computational results obtained are in better agreement with the known experimental results as follows. Table: 4.2 Comparison of Experimental Results with Computational Results

Fig: 2.3 Computational Domain with Mesh

III.

NUMERICAL PROCEDURE

This project implemented steady Reynolds Averaged NavierStokes equations (RANS) in the ANSYS FLUENT flow simulation program. For all cases, a two-dimensional, doubleprecision flow solver was used. It was assumed that the application of steady RANS equations was sufficient for this

Parameters

Experimental

Taper Angle

10 º

7º

8º

9º

0.73 to 0.85

0.882

0.880

0.873

0.85

0.006 to 0.0063

0.0064

0.0065

0.0066

0.006

Pressure coefficient Skin friction coefficient Velocity (m/s)

Computational 10 º

Min

-1.156

0

-0.146

-0.723

-1.156

Max

22.845

22.845

22.845

22.845

22.845

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International Journal of Technical Research and Applications e-ISSN: 2320-8163, www.ijtra.com Volume 2, Issue 5 (Sep-Oct 2014), PP. 16-21 Table 4.2 demonstrates the correlation distinctive parameters of experimental results with computational results. This table demonstrates the how the taper angle decreases pressure coefficient expands and skin friction coefficient diminishes this implies the flow separation is bit by bit diminishes.

Fig: 4.1.4 Comparison of Computational Results with Experimental Results of Top_wall skin friction along with the X/H using the SST model at 10ᴼ taper angle

Fig: 4.1.1 Experimental results of Bottom_wall skin friction along with the X/H using the SST model at 10ᴼ taper angle [2]

Fig: 4.2.1 Experimental results of pressure coefficient (Cp) at 10ᴼ taper angle along with the X/H

Fig: 4.1.2 Comparison of Computational Results with Experimental Results of Bottom_wall skin friction along with the X/H using the SST model at 10ᴼ taper angle

Fig: 4.2.2 Computational Results of Pressure Coefficient, bottom and Top wall at 10ᴼ taper angle

V.

Fig: 4.1.3 Experimental results of Top_wall skin friction along with the X/H using the SST model at 10ᴼ taper angle [2]

RESULTS AND DISCUSSION

The results are obtained from the CFD by applying the experimental condition to the computational model with variation of taper angle 7ᴼ, 8ᴼ, 9ᴼ, and 10ᴼ, were measured for different contours plots, figure 5.1.1, 5.1.2, 5.1.3, and 5.1.4 shows the contours of velocity, figure 5.2.1, 5.2.2, 5.2.3, and 5.2.4 shows the separation for streamline functions and figure 5.2.5, 5.2.6, 5.2.7, and 5.2.8 shows contours of separation flow.

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Fig: 5.1.1 Contours of Velocity at 10ᴼ taper angle

Fig: 5.1.4 Contours of Velocity at 7ᴼ taper angle

Fig: 5.2.1 Separation for Streamline Function at 10ᴼ taper angle Fig: 5.1.2 Contours of Velocity at 9ᴼ taper angle

Fig: 5.1.3 Contours of Velocity at 8ᴼ taper angle

Fig: 5.2.2 Separation for Streamline Function at 9ᴼ taper angle

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Fig: 5.2.3 Separation for Streamline Function at 8ᴼ taper angle

Fig: 5.2.6 Contours of Separation at 9ᴼ taper angle

Fig: 5.2.4 Separation for Streamline Function at 7ᴼ taper angle Fig: 5.2.7 Contours of Separation at 8ᴼ taper angle

Fig: 5.2.8 Contours of Separation at 7ᴼ taper angle Fig: 5.2.5 Contours of Separation at 10ᴼ taper angle

Identification of separation within diffusers is important because separation increases drag and causes inflow distortion to engine fans and compressors. Figure 5.1.1, 5.1.2 and 5.1.3 shows the contours of velocity 10ᴼ, 9ᴼ and 8ᴼ taper angle respectively, blue color shows the negative value. Figure 5.1.4 taper angle at 7ᴼ contours of 20 | P a g e

International Journal of Technical Research and Applications e-ISSN: 2320-8163, www.ijtra.com Volume 2, Issue 5 (Sep-Oct 2014), PP. 16-21 velocity doesn’t shows negative value it means that the separation flow is avoided at 7ᴼ taper angle. VI.

CONCLUSION

From the present study it is evident that when the taper angle is decreased, the skin friction coefficient drops & pressure coefficient rises, as result the flow separation follows a diminishing trend The optimum taper angle is 7ᴼ below which there is no flow separation at all but going beyond it gives rise to flow separation VII.

SCOPE FOR FUTURE WORK

The proposed next work for the present configuration is, simulating for 3D structured mesh configuration to these taper angle varieties and as in the present work the contrast in 2D taper angle we can figure it for variety taper angle, and 3D configuration simulation is possible for the impact of expectation taper angle. REFERENCES [1] Buice, C.U. and Eaton, J.K., “Experimental Investigation of Flow Through an Asymmetric Plane Diffuser,” 1997 [2] Vance Dippold and Nicholas J. Georgiadis., “Computational Study of Separating Flow in a Planar Subsonic Diffuser,” NASA, October 2005 [3] Olle Tornblom., “Experimental study of the turbulent flow in a plane asymmetric diffuser,” 2003 [4] Reid A. Berdanier., “Turbulent flow through an asymmetric plane diffuser”, Purdue University, April-2011 [5] Arthur H Lefebvre and Dilip R. Ballal., “Gas Turbine Combustion-Alternative Fuels and Emissions”, CRC Press Taylor & Francis Group, Third Edition pp.79 – 112 – 2010 [6] Gianluca Iaccarino., “Predictions of a Turbulent Separated Flow Using Commercial CFD Codes,” 2001 [7] Obi, S., Aoki, K., and Masuda, S., “Experimental and Computational Study of Turbulent Separating Flow in an Asymmetric Plane Diffuser,” Ninth Symposium on Turbulent Shear Flows, Kyoto, Japan, August-1993. [8] Dheeraj Sagar, Akshoy Ranjan Paul Et al., “Computational fluid dynamics investigation of turbulent separated flows in axisymmetric diffusers,” 2011 [9] E.M. Sparrow and J.P. Abraham., Et al. “Flow separation in a diverging conical duct: Effect of Reynolds number and Divergence angle,” 2009.

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International Journal of Technical Research and Applications e-ISSN: 2320-8163, www.ijtra.com Volume 2, Issue 5 (Sep-Oct 2014), PP. 22-28

SYNTHESIS, PHYSICO-CHEMICAL AND ANTIMICROBIAL PROPERTIES OF SOME METAL (II) -MIXED LIGAND COMPLEXES OF TRIDENTATE SCHIFF BASE DERIVES FROM Β-LACTAM ANTIBIOTIC {(CEPHALEXIN MONO HYDRATE)-4CHLOROBENZALDEHYDE} AND SACCHARIN Taghreed. H. Al-Noor, Amer. J. Jarad, *Abaas Obaid Hussein Department of Chemistry. Ibn -Al-Haithem College of Education Baghdad University [email protected], *[email protected] Abstract— A new Schiff base 4-chlorophenyl)methanimine (6R,7R)-3-methyl-8-oxo-7-(2-phenylpropanamido)-5-thia-1azabicyclo[4.2.0]oct-2-ene-2-carboxylate= (HL)= C23H20 ClN3O4S) has been synthesized from β-lactam antibiotic (cephalexin mono hydrate(CephH)=(C16H19N3O5S.H2O) and 4chlorobenzaldehyde . Figure(1) Metal mixed ligand complexes of the Schiff base were prepared from chloride salt of Fe(II),Co(II),Ni(II),Cu(II),Zn(II) and Cd (II), in 50% (v/v) ethanol –water medium (SacH ) .in aqueous ethanol(1:1) containing and Saccharin(C7H5NO3S) = sodium hydroxide. Several physical tools in particular; IR, CHN, 1H NMR, 13C NMR for ligand and melting point molar conductance, magnetic moment. and determination the percentage of the metal in the complexes by flame(AAS). The ligands and there metal complexes were screened for their antimicrobial activity against four bacteria (gram + ve) and (gram -ve) {Escherichia coli, Pseudomonas aeruginosa, Staphylococcus aureus and Bacillus}. The proposed structure of the complexes using program, Chem office 3D(2006). The general formula have been given for the prepared mixed ligand complexes Na2[M(Sac)3(L)], M(II) = Fe (II), Co(II) , Ni(II), Cu (II), Zn(II) , and Cd(II). HL= C29H24 ClN3O4S, L= C29H23 ClN3O4S -. Key words— (Cephalexin antibiotics, Saccharin, Schiff base, Spectral studies drugs mixed ligand complexes, and antibacterial activities.

containing hetero atoms like O,N ,S and P are found to work as very effective corrosion inhibitors [2-3] Schiff bases have been studied extensively because of their high potential chemical permutation. Magnetic susceptibility, absorption spectra, elemental analysis, molecular weight determination, conductivity, thermal analysis of many Schiff bases and their complexes have been reported.[4–5]Several workers also studied their biological properties, such as antibacterial, antifungal, activities.[6–7] Saccharin (C7H5NO3S), also called o-sulfobenzoimide, is widely used as an artificial sweetening agent. Saccharin is a weak acid [8]. The structures of Co(II) [7], Ni(II) [8], Cu(II) [9] and Cd(II) [10] imidazole saccharinates were reported. In this paper we present the synthesis and study of Fe(II),Co(II),Ni(II), Cu(II), Zn(II),and Cd(II) complexes with tridentate Schiff base derives from β-lactam antibiotic { (cephalexin mono hydrate)4-chlorobenzaldehyde } as a primary ligand and Saccharin as secondary ligand. Their structures were confirmed by Uv-Vis . IR and NMR spectral analysis. Further, their antibacterial activity towards some clinically important bacteria was evaluated. II. EXPERIMENTAL

Figure(1):structural of the HL (3D)

A. Chemicals All chemical reagents and solvents used were of analytical grade and were used without further purification and were used as received, CuCl2.H2O, CdCl2.H2O, ZnCl2, FeCl2.9H2O.MnCl2.2H2O, CoCl2.6H2O,NiCl2 .6H2O, NaOH (supplied by either Merck or Fluka) ethanol, methanol dimethylforamaide, and KBr, acetone , benzene, 4chlorobenzaldehyde, and chloroform from (B.D.H).Cephalexin powder DSM (Spain).

I. INTRODUCTION Metal complexes of the Schiff bases are generally prepared by treating metal salts with Schiff base ligands under suitable experimental conditions. However, for some catalytic application the Schiff base metal complexes are prepared in situ in the reaction system. [1].Generally the organic compounds

B. Instrumentals Elemental micro analysis for the ligands was performed on a (C.H.N.) Euro EA 3000. In Ibn Al-Haitham College of Education, University of Baghdad, Iraq. 1H NMR spectra were recorded using Brucker DRX system 500 (500 MHz) and 13 C-1H hetero nuclear 2D correlation 22 | P a g e

NaOH

MeOH

Stirring 2hours

International Journal of Technical Research and Applications e-ISSN: 2320-8163, www.ijtra.com Volume 2, Issue 5 (Sep-Oct 2014), PP. 22-28 spectroscopy (COSY), HETCOR), in the Department of complexes precipitated were filtered and washed with distilled Chemistry Sharif University, Tehran, Iran. water, then with methanol and recrystallized using acetone solvent. Na2 [M (L)(Sac)3] (Scheme 2) . Yields: 82-90%. UV-Vis spectra were recorded on a (Shimadzu UV- 160A) Ultra Violet-Visible Spectrophotometer. IR- spectra were taken O OH H H NNa + MCl on a (Shimadzu, FTI R- 8400S) Fourier Transform Infrared S + 3 2 N S O 1 N CH3 Spectrophotometer (4000- 400) cm-1 with samples prepared as N O O KBr discs. Metal contents of the complexes were determined O HO by atomic absorption (A.A) technique using a Shimadzu AA Cl 620G atomic absorption spectrophotometer. The Chloride contents of complexes were determined by potentiometric titration method using (686-Titro processor-665. Dosimat Metrohn Swiss). Conductivities were measured for 10-3M of H complexes in DMSO at 25оC using (conductivity meter, O H HS N Jewnwary, model 4070). Magnetic measurements were N CH N

Farady’s method. In addition melting points were obtained using (Stuart Melting Point Apparatus). The proposed molecular structure of the complexes were drawing by using chem. office prog 3DX (2006). C. SYNTHESIS OF SCHIFF BASE (HL) The Schiff base ligand was prepared by condensation of (2.92 gm,8mmol) of Cephalexin mono hydrate in (15ml) methanol and of (1.12 g m , 8mmol) of 4-chlorobenzaldehyde in (15ml) methanol was refluxed on water bath for 3-4 hours in presence of few drops of glacial acetic acid. The yellow coloured solid mass formed during refluxing was cooled to room temperature, filtered and washed thoroughly with methanol, washed with hot acetone and recrystallized from acetone to get a pure sample. Yield: 83%, m p: 205-210o C. M.W= 469. 94, (C23H20N3 ClO4 S). see scheme (2-1) . % Calculated: 58. 78 , H: 4.92, N: 8;94 % Found: C: 57.55, H: 5.093, N: 8.627. S H

HN

H2O +

N

Cl

OH O O

drop acetic acid

O

O

methanol

H2N

Reflux 3-4h S H HN

O

N

O

OH O

N Cl

(6R,7R)-7-(2-((Z )-4-chlorobenzylideneamino)-2-phenylacetamido)-3-methyl-8-oxo-5-thia-1-azabicyclo[4.2.0]oct-2-ene-2-carboxylic acid

Scheme (1): The synthesis route of ligand (HL) D. General preparing of the mixed ligands metal complexes The complexes were prepared by a similar method of synthesis using the reagents in molar ratio of 1:3:1. Of M: L: 3Sac. A methanolic solution (15 mL, 1m mol) of the appropriate FeCl2.6H2O. (0.180gm, 1mmol), CoCl2.6H2O (0.237gm, 1mmol), NiCl2.6H2O (0.238gm, 1mmol), CuCl2.2H2O (0.176gm, 1mmol), ZnCl2(0.136gm, 1mmol),CdCl2 (0.183gm, 1mmol); was added to a methanolic solution (15ml) of the Schiff base, primary ligand [HL] (1m mol) and methanolic solution (0. 549g, 3mmol) ) of the secondary ligand sodium saccharinate was added to the previous solution and the reaction mixture was refluxed for about 2-3 h on a water bath and then aqueous alcoholic solution of Na OH (V: V) was added to the mixture to adjust the pH 6 to 8 and further refluxed for about an hour with constant stirring . The

3

O

O

O M

Cl

O N

O

Na2

N S

O O

O S

O O

O

N S

O

M(II) = Fe (II),Co(II),Ni(II),Cu(II), Zn(II), and Cd (II)

Scheme (2): The synthesis route of Metal(II) -(Schiff base HL –Sac) Mixed Ligand Complexes III. RESULTS AND DISCUSSION The data obtained from analytical and physico-chemical studies have been correlated in a logical way to explain the properties, bonding and structures of the compounds. A. Characterization of the ligand, Generally, the complexes were prepared by reacting the respective metal salts with the ligands using 1:1:3 mole ratios.[M: L3 :3(Sac)], i.e. one mole of metal salt : one mole of Schiff base(HL) and three moles of sodium Saccharinate The synthesis of mixed ligand metal complexes may be represented as follows 3SacH +3NaOH→ 3 Sac Na + 3H2O 3 SacNa + HL+ MCL2 .n H2O → [M(Sac)3(L)]+ n H2O + NaCl (where HL is Schiff base derives from selected β-lactam antibiotic (cephalexin monohydrate) with 4chlorobenzophenone, and Sac H is Saccharin). M (II) = Fe (II), Co(II),Ni(II),Cu(II), Zn(II), and Cd (II) B. Physical properties The formula weights and melting points, are given in table (1).Based on the physicochemical characteristics, it was found that all the complexes were non- hygroscopic, All complexes are insoluble in most organic solvent, but soluble in ethanol, DMF and DMSO. The complexes were dissolved in DMSO and the molar conductivity values of 10-3 M solution at 25 o C of the complexes are in the range 63.55-77.36 ohm–1mol-1 cm2. It is obvious from these data that complexes are electrolytes types 1: 2 [11]. The test for halide ion with AgNO3 solution was negative indicating that halide ion is inside the coordination sphere of the central metal [12]. The ligand, HL was yellow in color with a melting point of 162oC. The analytical data showed closed agreement with the suggested formula of C23H20 ClN3O4S. It was further characterized by 1H NMR,13C NMR and FT-IR 23 | P a g e

International Journal of Technical Research and Applications e-ISSN: 2320-8163, www.ijtra.com Volume 2, Issue 5 (Sep-Oct 2014), PP. 22-28 C. spectral data all the metal complexes indicates that, these groups are not involved in coordination. Some new bands of weak intensity The (FT-IR) spectrum for the starting material saccharin observed in the regions around (526-474)cm-1 and (418-486) (Sac H) Table(3). In saccharin the bands for stretching cm-1 may be ascribed to M-N and M-O vibrations, respectively vibration of N-H and (CNS) are found at 3402 and 966 cm-1 [14-15].It may be noted that, these vibrational bands are absent respectively. The absorption band for stretching vibration of in the spectra of the ligands.[15-16] (C = O) appeared at 1705 cm-1 .The absorption bands in the (U.V-Vis) Spectral data for the Schiff bases mixed ligands region 1333 to 1553 cm-1 is for C = C in the aromatic ring, complexes [Fe(L)(Sac)3], [Co (L)(Sac)3], [Ni (L)(Sac)3], [Cu 1292 cm-1 for C-N single bond, and at 1692 cm-1 for C-O (L)(Sac)3 , [Zn (L)(Sac)3] and [Cd (L)(Sac)3]. single bond. The two SO 2 stretching vibrations appear at The UV-Vis spectrum of the ligand (saccharin) shows similar frequencies(1292 and 1178 cm-1 for υ asmy(SO2) asym peaks at 275 nm (36363 cm-1)(εmax=142 molar-1.cm-1), 340 and υ smy (SO2) sym, respectively. [13-14] The (FT-IR) nm (21422 cm-1) (εmax=168 molar-1.cm-1) assigned to (π–π*) spectrum for the ligand (HL), displays bands at (3211, 3045) and (n–π*) electronic transitions. [17] cm-1 due to υ (N–H) secondary amine stretching vibration, and The UV-Vis spectrum of the ligand (HL) shows peaks at disappeared the band for the υ (N–H) primary amine stretching 300 nm (33333 cm-1) (εmax=880 molar-1.cm-1), assigned to vibration. (n–π*) electronic transitions within the organic ligand, [17- 18] The spectrum displays a new band at (1689) cm-1 is due υ The absorption data for complexes are given in Table (5). (HC=N-) group of the azomethine stretching vibrations of the Na2[Fe(L)(Sac)3] ligand [125] .Where The band at (1759) cm-1 is due to Stretch The magnetic moment table (3-27) of the Fe (II) d6 grouping υ(C=O) for (COOH) and strong _ (OH) stretching at complex is 4.72 B.M. 3423cm-1 corresponding to carboxylic group. The (U.V- Vis) Fe (II) spectrum, exhibits four peaks. The The band at (1689) cm-1 stretching vibration is due to υ assignment of the electronic spectral bands, their positions, and (C=O) for β-Lactam group overlapping with υ (-HC=N-); The the spectral parameters for Fe (I1) which is in agreement with bands at (1593) and (1398) cm-1 were assigned to stretching data reported by several research workers [24,7], the first high vibration (COOH) asymmetric and symmetric stretching intense peak at (273 nm)( 36630 cm-1)(εmax =1189 molarvibration, respectively. , Δυ = [υ asym (COO-) - υsym (COO-)] 1.cm-1) is due to the (L.F), while the second peak at (299nm)( is (195 cm-1) .These values are quite agreeable with the values 334442 cm-1)(εmax =1208 molar-1.cm-1) and third peak at reported earlier [124-125]. (345 nm)( 28985 cm-1)(εmax =1208 molar-1.cm-1) are due to The bands at (1502), (3045), (1163), and (2813) were the (C-T) .The fourth peak at (757 nm)( 13210 cm-1) (εmax assigned to υ(C=C) aromatic, υ(C–H) aromatic,( υ(C–C) aliphatic., and υ (C–C) aromatic ) stretching vibration =42 molar-1.cm-1) is due to the 5T2g→5Eg transition. respectively. The band at (1315) cm-1 is due to υ(C–N) cm-1 [5,18].These results reveal the distorted octahedral geometry stretching vibration. The band at (1282) cm-1 was assigned to for these complex.[17] υ(C–O) stretching vibration [123]. The band at (582) cm-1 was Na2[Co(L)(Sac)3] assigned to υ(C–S) stretching vibration [13-14]. The electronic absorption spectrum of Co (II) d7 complex The assignment of the characteristic bands (FT-IR) spectra showed five absorption bands as shown in table (5). The for the free ligand (HL), are summarized in Table (2) and (3) assignment of the electronic spectral bands, their positions, and respectively. the spectral parameters for Co (I1) which is in agreement with FT-IR of Na2 [Fe( L)(Sac)3] (1), Na2[Co ( L)(Sac)3] (2), data reported by several research workers [124,127], the first Na2[Ni ( L)(Sac)3](3), Na2[Cu( L)(Sac)3] (4) ,Na2[Zn( high intense peak at (273 nm)( 36630 cm-1)(εmax =1340 L)(Sac)3] (5) and Na2[Cd ( L)(Sac)3] (6) complexes: molar-1.cm-1) is due to the (L.F) , while the second peak at The FT-IR spectra for complexes (1) , (2) , (3) , (4) , (5), (299 nm)( 334442 cm-1) (εmax =1379 molar-1.cm-1) and and (6), are summarized in table (4) . The spectrum of the (HL) third peak at (345 nm)( 28985 cm-1)(εmax =1383 molardisplays a new band at (1689) cm-1 is due to υ (HC=N-) group 1.cm-1) are due to the (C-T). The fourth peak at(862nm)( of the azomethine stretching vibrations of the ligand [125,128]. 11600 cm-1)(εmax =28 molar-1.cm-1) and fifth peak at (981 on complexation these band has been shifted to lower nm)( 10193 cm- 1)(εmax =145 molar-1.cm-1) are due to frequencies (1620), (1629, (1629), (1585), (1629) and (1585) the4T1g→4T1g (P) (ν3) and 4T1g → 4A2g (ν2) cm-1for complexes (1), (2), (3), (4), (5) and (6).This bands respectively. The magnetic moment table (3-26) of the Co (II) gets shifted to lower frequency in the complexes, complex is 3.51B.M suggesting octahedral geometry for the Co indicating the coordination through azomethine nitrogen to (II) complexes. [5,17] metal atom. [5, 14, 15]. Na2[Ni(L)(Sac)3] The bands at (1593), and (1398) cm-1 were assigned to The electronic absorption spectrum of Ni (II) d8 complex stretching vibration (COOH) asymmetric and symmetric showed five absorption bands as shown in table (5).The stretching vibration, respectively. on complexation these bands assignment of the electronic spectral bands, their positions, and have been shifted to lower frequencies [(1581), (1587), the spectral parameters for Ni (I1) which is in agreement with (1527), (1527), (1587) and (1558) cm-1 for Δ (-COO)asy], and data reported by several research workers[124,127],the first [(1336), (1334), (1394), (1380), (1334), and (1358) cm-1,for Δ high intense peak at (272 nm)( 36764 cm-1)(εmax =1188 (-COO) sy] for the compounds (1) , (2) , (3) , (4) ,(5) and (6), molar-1.cm-1) is due to the (L.F) , while the second peak at that the coordination with metal was occurred through the (344 nm)( 29069 cm-1)(εmax =2073 molar-1.cm-1) and third oxygen atom of carboxylate ion. Moreover, Δ(aυs (COO–)peak at (358 nm)( 27932 cm-1) (εmax =1383 molar-1.cm-1) υs(COO–) values of complexes below 200 cm−1 would be are due to the (C-T).The fourth peak at(885 nm)( 11299 cmexpected for bridging or chelating carboxylates but greater than 1)(εmax =12 molar-1.cm-1) and fifth peak at (980 nm)( 200 cm−1 for the monodentate bonding carboxylate anions 10204 cm-1)(εmax =104 molar-1.cm-1) are due to the 3A2g [6,13]. The un altered position of a band due to ring υ(C-S) in 24 | P a g e

International Journal of Technical Research and Applications e-ISSN: 2320-8163, www.ijtra.com Volume 2, Issue 5 (Sep-Oct 2014), PP. 22-28 (C6; C7; C8; β-lactam);135 .65; 131. 63; 130.18).The (F) → 3T1g (P) (ν3) and 3A2g(F) → 3T1g(F) four resonance at (δ=140.87, δ= 140.42, δ= 140.12, δ= 139.92 (ν2)respectively . The magnetic moment table (3-2276) of ppm) assigned to carbon atoms of aromatic ring (C1, C2, C4, the Ni (II) complex is 2.77 B.M suggesting octahedral C3) respectively. (–HC=N); 146.14. geometry for the Ni (II) complexes.[ 17 , 19]. Na2[Cu (L)(Sac)3] F. The proposed molecular structure forNa2[M The electronic absorption of Cu(II) d8 complex showed (L)(Sac)3] three absorption bands as shown in table (5). The first high Studying complexes on bases of the above analysis, the intense peak at (271 nm)( 36900 cm-1)(εmax =1039 molarexistence of Hexa coordinated [M( L) (Sac) 3] were, M= 1.cm-1) is due to the (L.F) , while the second peak at (348 Fe(II),Co(II),Ni(II),Cu(II),Zn(II),and Cd(II).proposed models nm) (28735 cm-1)(εmax =485 molar-1.cm-1) and third peak is of the species were built with chem.3D shows in figure(2 ) observed multiple absorption band at 11682 cm-1 – 16500 cm1 but they are overlapped. Because, octahedral complexes of Cu(II) are observable distorted by Jahn-Teller effect and the structure of complex is to name pseudo-octahedral. It was to taken notice of top of the peak as absorption band and d–d transition at about 11682 cm-1 (2Eg→2T2g) for Cu(II) complex. The complex has a room temperature magnetic moment of 1.71 B.M. which corresponds to distorted octahedral structure for the Cu (II) ion,[ 19-.20]. Na2[Zn (L)(Sac)3] and Na2[C d (L)(Sac)3] The electronic spectra of d10[Zn(II) and C d(II)]complexes do show the charge transfer . The magnetic susceptibility shows that two complexes have diamagnetic moments., because d-d transitions are not possible hence electronic spectra did not give any fruitful information. in fact this result is a good Figure (2): 3D molecular modeling proposed complexes agreement with previous work of octahedral geometry Na2[M(L)(Sac)3] [16,19,21]. M= Fe(II),Co(II),Ni(II),Cu(II),Zn(II) and Cd(II) D. Magnetic susceptibility The observed magnetic moment values of the prepared complexes are summarized in table (6).Examination of these data reveals that magnet moment of 0.0 B.M for Cd (II) and Zn complexes confirms that the complexes are essentially diamagnetic. The magnetic moment found for Fe(II),Co (II), Ni (II), Cu (II), 4.72, 3.51, 2.77, 1.71 B.M respectively these values suggest octahedral geometry which is in good agreement with data of electronic transition . The electronic spectra and the magnetic moments support the stereochemistry of the complexes [12-120] E. NMR Spectral studies The integral intensities of each signal in the 1HNMR spectrum of ligand was found to agree with the number of different types of protons present. In the 1H NMR spectrum of the ligand, the formation of Schiff base is supported by the presence of a singlet at (δ 8.21) ppm corresponding to the azomethine proton (–N=CH–).The signal obtained in range (δ 7.77-7.92) ppm was assigned for doublet due one proton of aromatic ring of phenyl. Three groups of double peaks given by (CO–CH) and (N–CH) on the beta-Lactam ring and (NH sec.) amide appeared at (δ 4.48), (δ 5.06) and (δ 8.08) ppm, respectively. This confirms the formations of imine ligand. This observation was also supported by the FTIR data of the ligand discussed earlier. One group of four resonance signals attributed to (S-CH) on the dihydrothiazine ring was observed in the (δ 2.92-3.27) ppm. and 9.53 ppm (1H, s, –NH–CO); This observation was also supported by the FTIR data of the ligand discussed earlier. [23, 24].The NMR spectral data of HL was compared with the spectral data for the similar ligands reported in literatures [23, 24]. The 13C NMR spectrum of the ligand [HL] in DMSO-d6 solvent shown

Antibacterial Activities studies: [25-26] The effectiveness of an antimicrobial agent in sensitivity is based on the zones of inhibition. The synthesized metal complexes were screened for their antimicrobial activity by well plate method in nutrient agar . The invitro antibacterial activity was carried against 4 hold cultures of pathogenic bacteria like gram (+) and gram (-) at 37o C. In order to ensure that solvent had no effect on bacteria, a control test was performed with DMSO and found inactive in culture medium. Antimicrobial activity was evaluated by measuring the diameter of the inhibition zone (IZ) around the hole. Most of the tested compounds showed remarkable biological activity against different types of gram positive and gram negative bacteria. The diameter of the susceptibility zones were measured in mm and the results are presented in Table (7) [2627]Compounds were considered as active when the (IZ) was greater than 6 mm. The zone of inhibition of the complexes against the growth of bacteria were given In table (6), figure(3 ) *The antibacterial activity results revealed that the ligand (HL) and its complexes shown weak to good activity. Complexes Na2[M (L)(Sac)3], M =Co(II) ,Ni(II) ,Cu(II) and Zn(II) show negative against all bacteria. *The complex Na2[Fe (L)(Sac)3] show very good antibacterial activity agains towards 3- organisms except pseudomas. *The complex Na2[Cd(L)(Sac)3] show good antibacterial activity against towards 4- organisms. The inhibition antibacterial property of complexes can be explained as follows. The positive charge of the metal ion is shared antibacterial between the donor atoms of the ligand. There is the possibility of delocalization of the π electron density of aromatic ring also. These two factors positively contribute to increase the lipophilic character. Upon complexation , polarity of metal ion get reduced due to the overlap of ligand orbital and 25 | P a g e

International Journal of Technical Research and Applications e-ISSN: 2320-8163, www.ijtra.com Volume 2, Issue 5 (Sep-Oct 2014), PP. 22-28 [14] Silverstein R. M., Spectrophotometric Identification of Organic the sharing of positive charge of the metal ions with donor Compounds, 2009.John Wiley, New York, NY, USA. groups. [5,16] REFERENCES [1] Cozzi. P.G, Chemical Society Reviews, 33 (2004) 410-421. [2] Blanc C., Gastaud S., J. Electrochem.Soc. 150, 396, 2003. [3] Ebenso E. E,. Okafo P. C r, U. J. Eppe,Anti Corr. Meth. and Mat, 50,414,2003. [4] Taghreed H. Al-Noor, Sajed. M. Lateef and Mazin H. Rhayma, J.Chemical and Pharmaceutical Research,( 2012), 4(9):41414148 [5] Taghreed H. Al-Noor, Ahmed. T. AL- Jeboori , Manhel Reemon , J. Chemistry and Materials Research ,( 2013), Vol.3 No.3, 114124 [6] Taghreed H.Al-Noor,Ahmed T.AL- eboori , Manhel Reemon,( 2013 ) J. Advances in Physics Theories and Applications Vol.18, 1-10. [7] Zhang,. J. Li, Y. Lin, W. Liu, S., J. Huang, Polyhedron, (1992), 11, 419. [8] Zhang, J. Li Y., Lin, W. Liu, J. S. Huang, J. Cryst. Spec. Res. (1992)., 22, 433 [9] Liu, J. Huang, J. Li, W. ., Lin, J. Acta Crystall ogr. (1991), C47, 41. [10] Ke, J. Li, Y. Wang, Q. Wu X., J. Cryst. Res. Technol. (1997), 32, 481. [11] Geary, W. J. Coord. Chem. Rev. 1971, 7, 81-122. [12] Vogel A. (1978).Text Book of Quantitative Inorganic Analysis (Longman, London). 3Ed th 694. [13] Nakamoto; K. (1996).Infrared spectra of Inorganic and coordination compounds “4Ed th ; J. Wiely and Sons, Newyork.

[15] Sharma, R.C Giri P.P, Devendra Kumar and Neelam, J. Chem. Pharm. Res(.2012), 4(4): 1969-1973. [16] Fayad N.K., Taghreed H. Al-Noor and Ghanim F.H, Journal of Advances in Physics Theories and Applications, (2012) , Vol. ( 9), 1-12. [17] Lever A.B.P., “Inorganic Electronic spectroscopy“,2rd Ed Elsevier, New York. (1984). [18] Taghreed H. Al-Noor, Manhel Reemon Aziz and Ahmed T. ALJeboori, Journal of Chemistry and Materials Research, 2013 Vol.3 No.3, 114-124. [19] Taghreed H. Al-Noor, Ahmed. T. AL- Jeboori, Manhel Reemon, Journal Advances in Physics Theories and Applications ( 2013) Vol.18, 1-10. [20] Dutta. R. L and Syamal A., Elements of Magnatochemistry , 2nd Ed., East west press, New Delhi, (1996). [21] Manchand W. ConardFernelius W., Journal of Chemical Education (1961). 38 (4) 192-201, [22] Fouziarafat M. Y. Siddiqi and Siddiqi., k. S. J. Serb. Chem. Soc.(2004), 69 (8–9) 641–6649 [23] Chohan, ZH.Daniel L.M. Aguiak DE, Rosane A.S. San GIL, Leandro B. Borre, Monica R.C. Marques, Andre L. Gemal , J. Appl Organomet Chem, (2011) 20: 112- 118. [24] Reddy V., Patil N. and. Angadi S.D, E-J. Chem., (2008), 5(3), 577-583. [25] Seely H.W ,and Van Demark P J, Microbes in Action, Laboratory of Microbiology, 3rd Ed., W H Freeman and Co. U.S.A, 1981, 38 [26] Awetz J., Melnick, And Delbrgs A,( 2007), “Medical Microbiology” 4th ed McGraw Hil-USA.

Table (1): The physical properties of the Schiff base mixed ligand Na2 [M(L)(Sac)3]complexes M. wt = Molecular Weight, Lm = Molar Conductivity, dec. = decomposition

Table(2):Data from the Infrared Spectrum for the Free Ligand Ceph (cm-1) and Schiff base HL

Table (3): Infrared spectral data (wave number ύ) cm-1 for the Saccharin (Sac H) Sym: symmetric, asy: asymmetric, am: amide, v.s: very strong, s: strong, m: medium, w: week, sh: shoulder , arom. = aromatic, aliph = aliphatic

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International Journal of Technical Research and Applications e-ISSN: 2320-8163, www.ijtra.com Volume 2, Issue 5 (Sep-Oct 2014), PP. 22-28

Table (4): Infrared spectral data (wave number ύ) cm-1 for the ligand HL, and their complexes

Table (5): Electronic Spectral data, magnetic moment, of the mixed ligands complexes

Table (6): The magnetic measurements data of the prepared complexes

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International Journal of Technical Research and Applications e-ISSN: 2320-8163, www.ijtra.com Volume 2, Issue 5 (Sep-Oct 2014), PP. 22-28

Table (7): The antibacterial activity (Zone of inhibition) (mm) data of Schiff base (HL) and its complexes Na2 [M(L)(Sac)3]

Figure(3) :Chart of biological effects of the Na2[M( L)(Sac)3]

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CAUSES AND EVALUATION OF CRACKS IN CONCRETE STRUCTURES Syed Mohd Mehndi Prof. Meraj Ahmad Khan & Prof. Sabih Ahmad (Guide) Dept. of Civil Engineering Integral University Lucknow, India [email protected], [email protected], [email protected] Abstract-This research work focused on checking the cause and evaluation of cracks at every stage in R.C.C structures. This paper will describe how to find out cracks size and cause of cracks. Cracks generally occur both in plastic and elastic state of concrete. I have selected this topic because less work is being done in this area in India. The repair materials and repair technique are different depending upon forms of cracks according to their positions in structure. Good crack repair methods depends on knowing the cause of cracks and selecting appropriate repair method that take these causes into account otherwise the repair would not last long. This report serves as a tool in process of cracks evaluation and causes of cracks in concrete structures. So we can say if crack repair is assumed to be building of structure than this report can be assumed as foundation of it. Keywords— Thermal expansion, alkali-silica reactions, alkalicarbonate reactions, corrosion; cracking; drying shrinkage, heat of hydration, mass concrete, plastic & precast concrete, prestressed concrete, reinforced concrete, shrinkage.

II. REASONS OF CRACKING A. CRACKING WHICH OCCUR IN PLASTIC CONCRETE 1. PLASTIC SHRINKAGE CRACKING It arise when the rate of evaporation of water from top layer of freshly laid concrete is greater than bleed water provided by underlying concrete due to this surface concrete contracts. Due to the restraint shown by the concrete below the drying surface concrete layer the tensile stresses are develop in the weak and stiffening plastic concrete. Due to this shallow crack of variable depth are formed at different locations whose shape can be random, polygonal pattern, or be essentially parallel to one another. These cracks may be fairly wide and can be observed the surface. The size of these cracks would vary from few inches to feet in length. Plastic shrinkage cracks begin as narrow cracks, but can become full-depth cracks later on.

I. INTRODUCTION Concrete encompasses certain type of cracks in prehardening stage and develops some other types of cracks in post hardening stage in life of structure due to various reasons, even with our extreme care in prevention of cracks. When concrete becomes older cracks become causes of leakages and seepages and give entree to the moisture, oxygen, chloride, carbon dioxide etc. and other aggressive chemicals and gases into the concrete causing serious degradation of the structure and causing corrosion of steel and damage in the concrete and at a same time causing structural failure of the member. Cracking are early indications of failure of structure. Lightweight concrete shrinks more. It is vital to note that concrete does crack and this is usual. What is not normal is too much of cracks. “Cracks can be treated as cancer in R.C.C structure, as cancer which in its primary stage is curable to a certain extent but becomes danger to life in later stage; same happens with cracks” Depending on types and importance cracks can be of two types:-

Structural Cracks Non Structural Cracks

Structural cracks are of more important and have to be dealt more carefully because neglect to this leads to un-safe structure. Non-structural cracks are not of so much significance as far as safety is considered but it deals more with aesthetic point of view.

Fig.1 Above Presenting Typical View of Plastic Shrinkage Crack Plastic shrinkage cracking occur due to: When temperature of air above concrete is high. When there is low relative humidity When wind velocity above concrete is high. Preventive measures of plastic shrinkage include use of: to saturate the air above concrete Fog nozzles Plastic sheeting to cover concrete to decrease the wind velocity Windbreaks to decrease the surface temperature Sunshades 2. SETTLEMENT CRACKING Concrete has general tendency to settle down after initial placing of concrete and when this settlement are blocked by reinforcement, framework etc. then settlement cracks will develop. Due to restraints; cracks develops in structure which are adjacent to restraining element. Settlement cracking increase with increase in bar size, inadequate vibration and increase in slump and decreases with increase in size of cover and addition of fibers in concrete.

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International Journal of Technical Research and Applications e-ISSN: 2320-8163, www.ijtra.com Volume 2, Issue 5 (Sep-Oct 2014), PP. 29-33 concrete can be due to water filled inside water retaining structure, foundation that came in contact with soil or due to air pollutant which react with concrete. Concrete get cracked when concrete react with aggregate containing active-silica and alkalis resulting from cement hydration. When the alkalis in cement react with aggregate particles a reaction film of alkalisilica gel is produced around the aggregate. If this gel is exposed to moisture it will expands causing an increase in the volume of the concrete mass which finally results in cracking. Remedial measures include use of aggregates which do not take part in reaction. Certain carbonates rocks take part in reactions with alkalis produce expansion and cracking. Sulfates from soil when react with cement paste Calcium Sulfoaluminate is formed, which may be root cause in increase in volume of concrete. This increased in volume of concrete causes development of closely spaced cracks and ultimately deterioration of the concrete. Sulfate- resistant cements are very beneficial in reducing this problem. Using concrete with a low w/c ratio is important to have adequate protection against severe sulfate attack. 4: WEATHERING Weathering is wear and tear of structures caused by freezing, drying and wetting of concrete. Concrete can be easily get damaged by freezing of water both in elastic stage and plastic stage. Freeze water inside concrete result in increase in volume of concrete. The increased volume of concrete results in cracking of concrete. Concrete can be protected against weathering by use of the Fig above Presenting Typical View of Settlement Crack low w/c ratio, tough aggregate and adequate curing of concrete. 5: CORROSION OF REINFORCEMENT B: CRACKING OF HARDENED CONCRETE Corrosion to reinforcement is signs rather than reason for 1: DRYING SHRINKAGE concrete damage. Corrosion occurs due to electrochemical Concrete has greater volume when it is in dried form and it oxidation of reinforcement bars in existence of moisture and volume decreases on drying; decrease in volume is due to loss electron flow inside metal. After corrosion the volumes of of water. When decrease in volume of concrete is restrained by reinforced bars get increased. Due to increase in volume of reinforcement bars then cracks is established called Plastic reinforced bars a bursting radial stresses are produced around shrinkage cracks. Tensile stresses are developed within structure bars which result in local radial cracks around bars. due to combination of shrinkage and restraint provided by Remedial technique comprises of epoxy coating of bars, use another part of the structure. As we know that concrete are of richer grade of concrete and by use of corrosion inhibitors. weak in tension so when tensile stress which is developed 6: POOR CONSTRUCTION PRACTICES during restraint exceeds tensile strength of concrete then cracks When construction is not done correctly cracks started to started to develop. These cracks are detected at the surface originate in structure called cracks due to wrong construction which go deep later on as time passes. Factors which affect practice. In this the most common is additional of water to drying shrinkage are type of aggregate and W/C ratio. Stiff increase workability. Addition of water plays an important role aggregate offer more resistance to shrinkage. Contraction in decreasing concrete strength, increasing concrete settlement joints and correct detailing of the reinforcement reduces and increasing drying shrinkage of concrete. Another problem shrinkage cracking. which comes under this is when less curing is done or curing is 2: THERMAL STRESS eliminated early stages. Thermal stresses are produced when there is normal 7: STRUCTURAL OVERLOADS expansion and contraction of concrete due to surrounding Concrete gets damaged due to structural overload which are change in air temperature. It was observed that concrete length very easy to detect. Precast member like beam and are variations is about 0.5 inch per 1000 linear feet at an generally subjected to this type of load. Most unfortunate atmospheric temperature of about 80 °F. When there is no things about cracks is due to structural overload are that cracks provision of thermal expansion concrete will crack. This type are detected at early stages. of cracks forms as a source of seepage in water retaining These types of cracks can be prevented if designer limit the structures. Cracks developed from tensile stresses get load on structure. accelerated by consumption of Portland cement. 8: ERRORS IN DESIGN AND DETAILING Method to reduce thermal induced cracking involve Errors in detailing & designing result in cracking of concrete. practice of jute bags to cover concrete and keep watering it at These problems are mostly seen in re-entrant corners near door least three times a day in hot countries like India. and windows opening in building. Problems which also came in 3: CHEMICAL REACTION consideration include incorrect detailing of reinforcement steel Chemical reactions which occur due to reaction of concrete bars and others problems like restraint of members, lack of in its firm state with materials used to make concrete or by materials that came in contact with it. Chemical reaction inside 30 | P a g e

International Journal of Technical Research and Applications e-ISSN: 2320-8163, www.ijtra.com Volume 2, Issue 5 (Sep-Oct 2014), PP. 29-33 adequate contraction joints and incorrect design of foundations the surface. A hollow sound specifies one or more cracks below etc. and parallel to the surface being hammered. Infrared imaging equipment although expensive but found effective in III. EVALUATION OF CRACKING recognizing regions in which concrete has cracks. The presence of reinforcement bars can be determined using a pachometer A: DIRECT AND INDIRECT OBSERVATION (Fig. 3.2.1). In this method first we note thickness of crack on a sketched of structure. Then grid are marked on the surface of the structure and crack widths are measured by this instrument to an accuracy of about 0.025 mm .This instrument comprises of a small hand-held microscope with a scale on the lens closest to the surface being viewed as shown in (Fig. 3.1.1) below. However it is generally more convenient to estimate crack thicknesses using a clear card which have lines of specified thickness marked on it, as shown in (Fig. 3.1.2) below.

Fig. 3.1.1—Comparator for measuring crack thicknesses

Fig. 3.1.2—Card used to measure crack thickness Any movement of the surface across the crack should also be documented. Observations such as reinforcement which exposed to environment, surface wear and tear and rust mark on reinforcement bars should be noted down on the sketch. Internal conditions of the crack at definite locations can be observed with the use of flexible shaft fiber- scopes or rigid bore scopes. B: NON-DESTRUCTIVE TESTING Nondestructive tests can be performed to estimate the presence of internal cracks and voids and the depth of penetration of cracks detectable at the surface. Tapping the surface with a hammer is simple method to recognize laminar cracking near

Fig. 3.2.1—Pachometer reinforcing bar indicator Pachometers show the presence of steel bars and allow the experienced user to determine depth and the size of reinforcing steel. In some cases however it required to remove the concrete cover to pinpoint the bar sizes or to measure cover especially in areas of congested reinforcement. Results of Pachometers are observed by use computer algorithms and magnetic fields to provide a visual picture of the reinforcing bars layout in the scanned area. This device is very useful in detecting reinforcement bars, measure concrete cover, and estimate the position and reinforcement size. If cracking is due to Corrosion then concrete above bars are removed and bars are saw directly. Corrosion potential of steel bars is measured by half-cell. Generally copper-copper sulfate half-cell is used to measure extent of corrosion in reinforcing steel. By use of ultrasonic non-destructive test equipment it is possible to detect cracks. A mechanical wave is transmitted to one face of the concrete member and received at the opposite face as shown in (Fig. 3.2.2). The time taken by wave to travel through the member is measured electronically. Pulse velocity can be evaluated if the distance between the transmitting and receiving transducers is known. When it is not possible to place transducers on opposite face then it can be placed on the same face (Fig. 3.2.2(a)). In this technique analysis of results is not so easy. If more time is taken by wave to travel from transducer to receiver then section is said to be cracked one. Higher the wave velocity shows the good quality of the concrete. The interpretation of result can be improved to great extent by use of an oscilloscope that provides a visual representation of the received signal (Fig. 3.2.2(b)).In fully flooded crack section interpretation of result is difficult hence this instrument is of no use. 31 | P a g e

International Journal of Technical Research and Applications e-ISSN: 2320-8163, www.ijtra.com Volume 2, Issue 5 (Sep-Oct 2014), PP. 29-33 concrete can be find out from compressive strength tests but cores containing cracks should not be used to conclude concrete strength. Photographic test result of cracked concrete can tell us about material that causes cracking, w/c ratio relative paste volume and distribution of concrete components, age of cracks, secondary deposits on fracture surfaces. D: REVIEW OF DRAWINGS AND CONSTRUCTION DATA Construction drawing and detailing of reinforcement bars should be studied to confirm that the concrete thickness and quality. Serviceability requirement check is also necessary so that non-structural cracks are evaded in structure. The actual loads which are coming on structure should be checked against designed load. If actual loads coming on structure exceeds design load then we have to either re-design section or look in the direction of restoration of structure. IV. PROPOSED FILTRATIONS AND SUGGESTIONS

Fig. 3.2.2—Ultrasonic testing: through-transmission C: TESTS ON CONCRETE CORES Concrete cores give necessary information about cracks which are taken at different positions. It also gives correct information about thickness and depth of cracks. Strength of

The first step involves visual observation of cracks. In second step we find location and pattern of cracks. In third we find out root cause of cracks. Fourth steps involves cracks measurements for which different instruments are used such as Ultrasonic Pulse Velocity—To identify Void and measure Cracks depth, Cracks Microscope and Digital Crack Measuring Gauge—To locate and find width of cracks, Crack Monitor, Concrete Endoscope and Fiber Scope—To monitors the changes in cracks, Petrography—Evaluate crack due to fire damage, and Thermal imaging camera—To detect leakage and voids inside concrete. In all the technique mentioned above Cracks Compactor is most efficient in measuring small cracks. Ultrasonic testing is more costly than Crack Compactor and used for measuring all types of cracks.

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V. CONCLUSION The paper is divided into three parts. First Part contains different causes of cracks, Second part contains evaluation of cracks and the Last part contains my inference drawn on cracks. This paper on a whole focuses on possible causes and evaluation of cracks in R.C.C structures. Evaluation of cracks can be done by different technique like Crack Compactor and by ultrasonic Testing. In all these mentioned technique Crack Compactor technique is most efficient technique for measuring small cracks, Ultrasonic Testing device is more costly than Crack Compactor and should be used for slightly big evaluation of cracks. Pachomerer is used in determining concrete cover, size and location of reinforcement. In evaluating material causes of cracking Photographic examination is used.

[5]

[6] [7] [8] [9] [10] [11]

REFERENCES [1] Concrete Technology by M. S. Shety, Publication of S.

Chand & Company Ltd, Delhi, 2005 [2] IS 456:2000, “Indian Standard of Plain and Reinforced Concrete Code of Practice. [3] ACI 224.1R-07, “Causes, Evaluation, and Repair of Cracks in Concrete Structures” [4] Pattanaik Suresh Chandra, “Repair of Active Cracks of Concrete Structures with a Flexible Polyurethane Sealant for Controlled Movement” (2011), Proceed of the National Conference on

[12] [13]

Advances in Materials and Structures, ‘AMAS - 2011’, Pondicherry Hand book HB 84-2006: Guide to Concrete Repair and Protection, A joint publication of ACRA, CSIRO and Standards Australia ASTM C881 “Standard Specification for Epoxy-Resin-Base Bonding Systems for Concrete” ACI 224.3R-95: Joints in Concrete Construction (Reapproved 2013) ACI 224.2R-92: Cracking of Concrete Members in Direct Tension (Reapproved 2004) ACI 231R-10 Report on Early-Age Cracking: Causes, Measurement and Mitigation Causes, Mechanism, And Control Of Cracking In Concrete, ACI Publication Cracking, Deflection, and Ultimate Load of Concrete Slab Systems (ACI Publication SP-30) Guide to concrete repair U.S Department of the Interior Bureau of Reclamation Technical service center. Appendix E Avoiding Coating Failures Due to Cracking of Concrete Coating Manual

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DEVELOPMENT OF A FRAMEWORK FOR PRESERVING PRIVATE DATA IN WEB DATA MINING Sabica Ahmad1, Shish Ahmad2, Jameel Ahmad3 Dept. CSE & IT Integral University Lucknow, U.P. 1 [email protected], [email protected], [email protected] Abstract- The main aspire of this research work is, to develop proficient methodology to find privacy preserving association rule mining in centralized environment without infringement of any privacy constraints. The issue of privacy constraints for centralized database environment is entirely different from distributed database environment. The goal of attaining privacy in centralized database environment is, to obtain a distorted database which hides the sensitive item sets. When mining task is performed on distorted database all the sensitive rules should be hidden without any side effects. Based on heuristic approach, a new me-thodology is proposed by incorporating suggested Criteria1 and Criteria2 to identify the victim item and selecting suitable supporting transactions efficiently for sanitization purpose to hide the sensitive item sets. Index Terms — preserving private data, frequent item sets, privacy preserving association rule mining.

I. INTRODUCTION Data mining has been view edasa risk to privacy because of the widespread propagation of electronic data maintained by organizations. This has initiated augmented concerns about the privacy of the under-lying data .The matter of privacy plays a crucial role when several genuine people share their resources in order to obtain mutual profit but no one is interested to reveal their private data .In the process of data mining, how to determine the problem of privacy preserving has become a hot research topic in the field of data mining. Hence, privacy preserving data mining research area is evolved. The privacy preservation data mining algorithms are generally classified into three categories namely reconstruction based, heuristic based and cryptog-raphy based II. PRIVACY PRESERVING ASSOCIA-TION RULE MINING We consider a method for finding privacy pre-serving association rule mining based on heuris-tic approach in centralized environment for dis-covering solution for hiding sensitive rules by fulfilling association rule hiding goals accurately or approximately. A new method is proposed in this paper re-lated to heuristic approach to hide sensitive association rules specified by users with min-imum side effects. The Criteria1 specifies the competent selection of victim item and Criteria2 helps to find the appropriate supporting transactions for victim item in the sanitization process to minimize side effects. Criteria 1: Victim item can be selected based on the follow-ing condition.

If number of times appears in non sensitive frequent item set is greater than number of times appears in non sensitive frequent item sets then Aj be the victim item. If number of times appears in non sensitive frequent item set is less than number of times appears in non sensitive frequent item sets then Ai be the victim item. Criteria 2: The minimum number of transactions required to hide item set is based on the value of .supp – MinTrans +1.. For each support-ing transactions for item set , weight is computed by using the following: W(Tg) = No. of dependant items with victim item number of infrequent item sets associated with victim item. III. PROPOSED FRAMEWORK In this paper a procedure is suggested in which all the sensitive item sets whose length is greater than two are considered to find the pairs of sub patterns. From this pair only significant pair-sub patterns are considered as sensitive to hide sensitive patterns. This procedure is very significant in a way that it avoids the difficulty of forward inference attack. In order to avoid forward inference attack problem, at least one such sub pattern with length of two of the patterns should be hidden. The split pattern procedure helps to accelerate up the hiding process. S.No. 1

Symbols DBASE = {t1,t2,..tN}

Explanatio nA original database consisting of N number of transactions

2

I ={i1,i2,…iM}

3

Lk

An item set of length k

4

Tnm

The n

5

S ={ s1, s2, …sr}

Set of sensitive item sets

6

MinS

7

Supp(J)

User specified Minimum support threshold Number of transactions supporting item set J

8

MinTrans

9

MCT

10

N

11 12

FDBASE L3,… Lk} B

13

FS

14

FNS

An item set of length M

th

th transaction of m item

Based on MinS, number of transactions required to support an item set to be frequent User specified Minimum confidence threshold Size of original database, DBASE ={L1,

L2, A set consists of all frequent item sets Association rule between item sets A and B The set consisting of sensitive item sets The Set consisting of non sensitive frequent item sets

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International Journal of Technical Research and Applications e-ISSN: 2320-8163, www.ijtra.com Volume 2, Issue 5 (Sep-Oct 2014), PP. 34-36 consisting of pairs Consider the victim item (Ai or Aj) based on the Criteria1 by the procedure split Step 8 Find the intersection of supporting transactions for AiAj and AjAk as follows:

15

F2S

The set determined pattern.

16



The sensitive item set pair

17

TAiAj

18

DBASE'

Set of supporting transactions for item set Distorted database which hides all sensitive item sets.

19

Victim item

An item which is selected from the sensitive item pair which produces least side effects or no side effects when modification is done over it.

20

Victim transactions

Selected transactions to modify the victim item value.

21

MinT

22

Count

A set consisting of suitable number transactions, which are to be modified to hide the sensitive item set Count gives number of times the victim item value has to be modified to hide sensitive item set pair.

23

W(Tg)

Weight for transaction Tg

Table 3.1: Symbols Used in Proposed Model

IV. ALGORITHM The algorithm for the proposed model is as fol-lows: Step 1 For a given database DBASE and set of sen-sitive item sets Fs, generate frequent item sets and store with their support values in FDBASE. Step 2 Let the sensitive item sets are stored in Fs then the non sensitive frequent item sets are obtained by subtracting FS from FDBASE. i.e., FNS = FDBASE - FS. Step 3 If any item sets in FS are having more than length of two, call the procedure split pat-tern to identify the prominent pairs which are to be hidden in order to hide all the item sets whose length is greater than two. Step 4 After step 3 a vector F2S is prepared which consists of all two pair sensitive items. Step 5 The generated all pairs sensitive fre-quent item sets with their support values along with their supporting transactions ID’s are stored in a Table TS. Step 6 All the non sensitive frequent item sets that is F- F2S are stored along with their support values in a Table TNS. Step 7 For each item set in F2S If any non overlapping item set exists go to step 12. Else the patterns are chosen

Step 9 Obtain the value for Count1 and Count2 as follows: Count1 for AiAj = .Supp - MinTrans + 1 Count2 for AjAk = .Supp - MinTrans + 1 Step 10 Find minimum number of supporting transactions to be modified by applying Crite-ria2. Select smaller one from both Count1 and Count2 and many transactions are chosen from MinT and the victim item (Aj) values are re-placed with 0 values. By this, item set lower count value will be hidden. To hide the item set, which is having higher count value, Count1 – Count2 no of transactions which are not yet processed will be chosen from MinT for the process of sanitization. To protect this item set, the victim item set can be chosen based on their dependencies with the item sets in non sensitive item set FNS. Accordingly the victim item value will be replaced with zero in the selected trans-actions. After performing this, the item set which is having higher count value is also hidden. Step 11 Modify F2S by removing the pairs and from it. Go to step18. Step 12 For the sensitive item set pair in F2S find victim item by using criteria 1. Step 13 After identifying the victim item, find the supporting transactions for . Step14 Obtain the value for Count1 and Count2 as follows: Count1 for AiAj = .Supp - MinTrans + 1 Step15 Select Count1 no of transactions to be modified from a set MinT obtained by the Crite-ria2. Step 16 The value of victim item in the selected transactions is replaced with value zero. Step 17 Update F2S by removing from it. Step 18 Repeat the above steps from step 7 until no more pair in the F2S to hide. Step 19 Finally distorted database, DBASE´ is obtained in which all sensitive item sets in F2S are hidden. Step 20 Stop the process. V. CONCLUSION This study has been carried out to develop method-ology in centralized as well as in distributed envi-ronment to find privacy preserving association rule mining without revealing any private data or infor-mation. This methodology is proposed in this thesis work to hide the sensitive item sets in centralized database environment. My methodology is related to heuris-tic based approach which utilizes suggested criteria to efficiently find the victim item and its supporting transactions. The proposed methodology efficiently performs sanitization process. REFERENCES [1] Usama Fayyad, Gregory Piatetsky-Shapiro, and Padhraic Smyth, “From Data Mining to Knowledge Discovery in Databases”, American Association for Artificial Intelligence, pp. 37-54,1996. [2] J. Han and M.Kamber, Data Mining Con-cepts and Techniques, Elsevier 2001. [3] R. Agrawal and R. Srikant, “Mining Sequential patterns”, Proc.1995 International Conference on Data Engineering (ICDE‟95), pp 3-14, Taipei, Taiwan, March 1995. [4] Verykios, V.S., Bertino, E., Nai Fovino, I., Parasiliti, L., Saygin, Y., and Theodoridis, Y. “State-of-the-art in privacy

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[5] [6]

[7]

[8]

[9]

[10]

preserving data mining”. SIGMOD Record, 33(1):50– 57,2004. Ahmed HajYasien, “Preserving Privacy In Association Rule Mining”, Ph D.,thesis, Griffith University, June 2007. Ming-Syan Chen, Jiawei Han,Yu, P.S., “Data mining: an overview from a database per-spective”, IEEE Transactions on Knowledge an Data Engineering, Vol. 8 No. 6, pp 866 – 883,1996. Yongjian Fu, “Data mining: Tasks, tech-niques and Applications”, Department of Computer Science”, University of Missouri- Rolla,1997 Michael Goebel, Le Gruenwald, “A Survey Of Data Mining And Knowledge Discovery Software Tools”, SIGKDD Explorations, ACM SIGKDD, Vol: 1, Issue 1, pp 20- 33, June 1999. Thair Nu Phyu ,”Survey of Classifica-tion Techniques in Data Mining”, Proceedings of the International MultiConference of Engineers and Computer Scientists 2009, Vol I,IMECS-2009, Hong Kong, 2009. Yongjian Fu, Distributed data mining: Overview, University of Missouri- Rolla, 2001.

[11] R Agarwal, T Imielinski and A Swamy, “Mining Association Rules between Sets of Items in Large Databases”, Proceedings of the 1993 ACM SIGMOD International Conference on Management of Data, page 207-210, 1993. [12] R. Agrawal and R. Srikant. “Fast, algo-rithms for mining association rules in large data-bases”, Proceedings of the 20th VLDB Conference Santiago, Chile, pp 487-499, 1994. [13] R. Srikant and R. Agrawal, “Mining Generalized Association Rules”, Proc. 21st VLDB Conference, Zurich, Swizerland., 1995. [14] Mohammed J. Zaki, “Parallel and Distrib-uted Data Mining: An Introduction”, Large-Scale Parallel Data Mining Lecture Notes In Computer Science, Vol. 1759, 2000. [15] Qinghua Zou, esley hu, Johnson,Chiu, . A pattern decomposition (PD) algorithm for finding all frequent patterns in large datasets”, International Conference on Data Mining, ICDM 2001, Proceedings IEEE, 673 – 674, 2001

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RELATIONSHIP BETWEEN HEAVY METAL AND TRANSFER FACTOR FROM SOIL TO VEGETABLE COLLECTED FROM WASTE WATER IRRIGATED AREA OF REWA (M.P.) INDIA Geetanjali Chauhan1* & Prof. U.K. Chauhan2 Department of Environmental biology, A.P.S. University Rewa-486003, Madhya Pradesh, India [email protected] Abstract— The study examined the concentration of heavy metals in water, soil and vegetables growing wildly on cement-polluted soil of Rewa city, India. Accumulation of HMs in vegetables occurs by various sources but soil is considered the major one. In this study, soil to vegetable transfer factor (TF) for various HMs were also calculated and data showed that TF values differed significantly between soil and vegetable, the difference in TF values among different vegetables may be attributed to differences in element uptake by different vegetables. However TF values obtained for all vegetables were below (1) at all sites. TF were computed to quantify relative differences in bioavailability of metals to vegetables to identify the efficiency of a vegetables species to accumulate a HM(s). These factors were based on roots uptake of metals and discount the foliar absorption of atmospheric metal deposits. However TF does not present the risk associated with the metal in any form.

I. INTRODUCTION The clean and safe environment is the basic requirement of human existence. Rapid urbanization and industrialization releases enormous volumes of wastewater, which is increasingly utilized as avaluable resource for irrigation in urban and peri-urban agriculture. It drives significant economic activity, supports countless livelihoods particularly those of poor farmers, and substantially changes the water quality of natural water bodies (Marshall et al., 2007). Wastewater from industries may contain various heavy metals including Fe, Zn, Cu, Pb, Cd, Mn, Ni, Cr, Cd, depending upon the type of activities it is associated with. Continuous irrigation of agricultural land with industrial wastewater may cause heavy metal accumulation in the soil and vegetables (Chaney et al., 2000; Sharma et al., 2007; Marshall et al., 2007). Soil to plant transfer of heavy metals is the major path way of human exposure to metal contamination. Food is the major intake source of toxic metals by human beings. Vegetables take up heavy metals and accumulate them in their edible and non-edible parts at quantities high enough to cause clinical problems to both animals and human beings.

main source of human exposure. A convenient way for quantifying the relative differences of bioavailability of metals to plants is the transfer coeficient. The higher transfer coefficient of heavy metal indicates the stronger accumulation of the respective metal by that vegetable. Transfer coeficient of 0.1 indicates that plant is excluding the element from its tissues (Thornton and Farago, 1997). The greater the transfer coefficient value than 0.50, the greater the chances of vegetables for metal contamination by anthropogenic activities will be and so the need for environmental monitoring of the area will be required (Sponza and Karaoglu, 2002). Thus accumulation of heavy metals in consumable vegetables has been well linked with soil heavy metal and irrigation water from long back; atmospheric deposition has now been identified as one of the principal source of heavy metals entering into plants and soil especially around urban-industrial areas (Pandey et al., 2009). Atmospheric heavy metals may deposit by rain and dust, and contributed to elevated metal concentrations in surface layer of soil (Sharma et al., 2008). Atmospheric metals may be absorbed directly on leafy surface, or entered through stomatal openings and accumulated within plant tissue. Metal accumulation in different plant parts depends on chemical form of metals, their translocation potential, and individual species with their stage of maturity (Salt et al., 1995). Heavy metal contamination in agricultural soil and vegetables through industrial wastewater and atmospheric source are of great concern because of metal translocation in soil-plant system and ultimately to the food chain (Khan et al., 2008; Rattan et al., 2005). Thus accumulation of heavy metals in the edible parts of vegetables represents a direct pathway for their incorporation into the human food chain (Florijin et al., 1993); and therefore has drawn the attention of researchers to health risk assessment of population exposed to contaminated foodstuffs. The aim of this research work was to determine the level of some heavy metals from soil that is transferred to the plants collected from waste water as well as clean water irrigated area of Rewa (M.P.), India and to correlate potential health effect of the people those who consumes those vegetables.

Transfer of Heavy Metals from Soil to Vegetables Transfer factor expressed the bioavailability of a metal at a particular position on a species of plants (vegetables). This is however, dependant on different factors such as the soil pH and the nature of plant itself. As the vegetables are the source of human consumption so the soil-to-plant transfer quotient is the

II. MATERIALS AND METHODS A. Experimental Sites Rewa is a city in the northern-eastern parts of the state of Madhya Pradesh, India. It is the administrative centre of Rewa District and Rewa Division. The cities lie about 420 km. (261 mi) north east of the state capital Bhopal, Madhya Pradesh and

Key words— Heavy metal, soil contamination, Transfer Factor (TF), Health Risk (Hazardous), Waste Water.

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International Journal of Technical Research and Applications e-ISSN: 2320-8163, www.ijtra.com Volume 2, Issue 5 (Sep-Oct 2014), PP. 37-41 130 km. (81 mi) south of the city of Allahabad, Uttar Pradesh. It is situated at 24.530 North latitude and 81.30 East longitudes and covers an area of 6,240 km2 (2,410 sq mi). It has an elevation of 304 m. (997 ft) above mean sea level. The average rainfall is 980 mm (39 inches) per year. The average temperature is around 250C (770 F) and the humidity is quite high. Experimental sites of different irrigation sources J.P. Cement Plants Bela, Naubasta (waste water irrigated sites) &, Bhiti village (clean water irrigated site) were selected. Cultivated land of these two industrial areas (Bela & Naubasta) received waste water discharge from industries, manufacturing cement while third site of rural area (Bhiti) received clean (ground) water from deep bore well. Thus all sites of different irrigation sources were selected and the sampling of water, soils and vegetables of the surrounding areas were carried out in May month, to estimate heavy metals contamination from soil to vegetables (TF). Sampling and laboratory analyses B. Collection and digestion of water samples At each site, both waste water and clean water samples collected randomly from different location. As soon as the samples were brought to the laboratory, they were acidified with HNO3 (Merck), filtered and stored in dark at ambient temperature (40C) before analysis. Both waste water and clean water samples were digested according to APHA, (2005); the irrigation water sample, 50 ml. was transferred into beaker and 10 ml. of concentrated nitric acid (HNO3) was added. The beaker with the content was placed on a hot plate and evaporated down to about 20 ml at 800C .The beaker was cool and another 5 ml. concentrated HNO3 was also added. The beaker was covered with watch class and returned to the hot plate. The heating was continued, and then small portion of HNO3 was added until the solution appeared transparent. The beaker wall and watch glass were washed with distilled water and the solution was filtered through whatman NO. 42 filter paper and the total volume were maintained to 50 mL with distilled water. C. Collection and digestion of soil samples Waste Water Irrigated soil samples were collected from the cultivated fields near the J.P. Cement Plant (Bela and Naubasta) along a distance of 100m from the Plants. Soil samples taken from each sites were separately labelled and transferred into air tight polythene bags and brought into laboratory. Before its transported to the research laboratory, care was taken, to the extent possible, to ensure that there were no other sources of contamination at the site of investigation such as motor vehicle emission, dumpsite garbage, sewage water, grey water, domestic waste, slurry, or compost to mask the effect of waste water irrigation. Soils were sieved through a 2 mm sieve to remove coarse particles and stored at ambient temperature prior to analysis. Soil samples were digested according to Allen et al., (1986). To 5g of each of the air dried and sieved soil samples was thoroughly grinded, 1.0g of each of the ground soil samples were placed in 100 ml beaker. 15 ml of HNO, H2SO4 and HCl mixture (5:1:1) of tri-acid were added and the content heated gently at low heat on hot plate for 2 hrs at 800C until a transparent solution was obtained. After cooling, the digested sample was filtered using whatman NO. 42 filter paper. It was then transferred to a 50 mL volumetric flask by adding distilled water.

D. Collection and digestion of vegetable samples Vegetable samples were taken in the agricultural fields around the commune where they were known to be affected by waste water and where they were not (control). Samples of seven different kinds of vegetables; leafy vegetables included

Table 1. Description of vegetable samples analyzed Common Name Spinach

Designation

Scientific Name

Edible Parts

SP

Betavulgaris L. CV.

Leaf

Cabbage

CA

Leaf

Cauliflower

CF

Lady’s Finger Brinjal

LF

Tomato

TO

Radish

RA

Brassica oleracea L. Var. Capatuta Brassica oleracea L. Var. botrytis Abelmoschus esculentus L. Solanum melongena L. Lycopersicon esculentum L. Raphanus sativus L.

BR

Inflorescence Fruit Fruit Fruit Root

Spinach (SP) (Betavulgaris L. CV. All green), and Cabbage (CA) (Brassica oleracea L. Var. Capatuta). Inflorescence vegetable included Cauliflower (CF)(Brassica oleracea L. Var. botrytis), Fruit vegetables included Lady’s Finger (LF) (Abelmoschus esculentus L.), Brinjal (BR)(Solanum melongena L.), Tomato (TO) (Lycopersicon esculentum L.) and Root vegetable included Radish (RA) (Raphanus sativus L.) were taken from the same experimental sites where waters and soils samples were taken . The detailed of the vegetable samples collected from the experimental sites are given in Table 1. Vegetable sample were collected randomly by hand using vinyl gloves carefully packed into polyethylene bags and the whole plant body was brought to the laboratory from each experimental site in order to estimate heavy metals. Cleaning (soil removal) of vegetable plant samples was performed by shaking and also by means of a dry pre-cleaned vinyl brush. Only edible parts of different vegetables were randomly taken from each experimental site. Freshly collected mature vegetable samples from each experimental site were brought to the laboratory and washed primarily with running tap water, then in distilled water and finally rinsed carefully in demonized water to remove any attached dust pollen particles (Burton and Patterson, 1979). Vegetable samples were also digested according to Allen et al., (1986) as described above. E. Analysis of samples Concentrations of Fe, Zn, Cu, Pb, Cd, Mn and Cr in the filtrate of digested soil, water and different kind of vegetables samples were estimated by using an Atomic Absorption Spectrophotometer (AAS, Perkin Elmer analyst 400). The instrument was fitted with specific lamp of particular metal. The instrument was calibrated using manually prepared standard solution of respective heavy metals as well as drift blanks. Standard stock solutions of 1000 ppm for all the metals were obtained from Sisco Research Laboratories Pvt. Ltd., India. These solutions were diluted for desired concentrations to calibrate the instrument. Acetylene gas was used as the fuel and air as the support. An oxidising flame was used in all cases. 38 | P a g e

International Journal of Technical Research and Applications e-ISSN: 2320-8163, www.ijtra.com Volume 2, Issue 5 (Sep-Oct 2014), PP. 37-41 F. Quality Control Analysis Quality control measures were taken to assess contamination and reliability of data. For this Blank samples (zero metal concentration) were analyzed after seven samples. Concentrations were calculated on a dry weight basis. All analysis was replicated three times. The accuracy and precision of metal analysis were checked against NIST (National institute of standard and Technology)-SRM (Standard Reference Material) 1570 for every heavy metal. BIOCONCENTRATION CALCULATION A. Transfer Factor (TF) Metal concentrations in the extract of soils and vegetables were calculated on the basis of dry weight (mg/kg). TF was calculated as follows (Cui et al., 2004):

Where, C (Vegetable) represent the heavy metal concentration (mg/kg) in extract of edible parts of vegetables & C (Soil) represent the heavy metal concentration (mg/kg) in soils from where the vegetable was grown. B. Statistical analysis Statistical analysis of data was done by SPSS 17. For water, soil, vegetable and site, two-way ANOVA was used. Pearson’s Correlations between the vegetable and the soil were also worked out. Statistical significance of means was computed using Pair Samples t-test, with a significance level of P < 0.001 (Steel and Torrie, 1980).

while lowest was in Cd in Cauliflower (0.015) at CWI-Bhiti village. The higher value of TF suggests poor retention of metals in soil and/or more translocation in vegetables. Because metal with high TF are easily transferred from soil to the edible parts of vegetables than ones with low TF. The higher uptake of heavy metals in leafy vegetables may be due to higher transpiration rate to maintain the growth and moisture content of these plants (Gildon and Tinker (1981). The present result agrees with the investigation made by (Zhuang et al. 2009) in the food crops in the vicinity of Dabaoshan mine, South China where the Bioaccumulation factors for heavy metals were significantly higher for leafy than non-leafy vegetables. Similarly high transfer factor value for Cu in Spinach from WWI site of Beijing, China, reported by YongGuan et al., (2004). Due to the high conc. of exchangeable Cu in vegetable soils, the Cu in edible parts of Spinach probably came from the root uptake from soils. The lowest values of the Cu in Cauliflower may be the absence of Cd concentration in soil of CWI-site. Thus a major pathway for Cd to enter the above- ground edible parts of Cauliflower, from vegetable soils, may be through application of fertilisers by farmers.

III. RESULTS AND DISCUSSIONS A. Level of heavy metals in water, soil & vegetables The present study had generated data on heavy metals (Fe, Zn, Cu, Pb, Cd, Mn and Cr) in water, soil and different kind of vegetables (edible parts) from waste water irrigated sites of Rewa, India and associated risk assessment for consumer’s exposure to heavy metals. Pb, Cd, Mn and Cr concentration in waste waters; Cd concentration in waste water irrigated soils and Pb, Cd and Cr concentration in all tested vegetables (from WWI sites) were above the national and international permissible limits. These accumulated heavy metals from Waste Water Irrigated area of Rewa (J.P.Cement Plant of Bela &Naubasta) had affected soil and water for a long time. People living in the contaminated area are at greater risk for health issues than individuals in the reference area. Children are at somewhat higher risk than adults. Heavy metal concentrations were several fold higher in all the collected samples from waste water irrigated sites compared to clean water irrigated ones. B. Transfer Factor of heavy metals from soil to vegetables In all sites of WWI &, CWI, TF of the heavy metals from soil to vegetables are presented in Fig 1, 2 & 3. These factors were based on roots uptake of the metals and discount the foliar absorption of atmospheric metal deposits (Lokeshwari and chandrappa 2006; Awode et al., 2008). The TF values between waste and clean water irrigated soils were not significantly different. The values of TF obtained from each sites were below (1). The TF values of Fe, Zn, Cu, Pb, Cd, Mn and Cr for various vegetables varied greatly between plant species and location. From the results, the highest TF value was observed for Cu in Spinach (0.634) at WWI-Bela site

Fig.1. Transfer Factor of heavy metals for vegetables of WWI site of Bela

Fig.2. Transfer Factor of heavy metals for vegetables of WWI site of Naubasta

Fig.2. Transfer Factor of heavy metals for vegetables of CWI site of Bhiti 39 | P a g e

International Journal of Technical Research and Applications e-ISSN: 2320-8163, www.ijtra.com Volume 2, Issue 5 (Sep-Oct 2014), PP. 37-41 C. Pearson’s Correlation Coefficient for Transfer Factor The Pearson’s correlation coefficient of heavy metals in soils and different kind of vegetables are summarised in table 2. VE G

TFFe

TFZn

SP

-0.389

CA

-0.502**

TFCu

TFPb

TFCd

TFMn

TFCr

FOR WWI SITE OF BELA 0.395*

-0.130

*

-0.499

*

LF

-0.217

*

TO

-0.225*

RA

-0.358

*

SP

-0.382*

CF BR

-0.011 NS -0.643

**

-0.577

**

-0.208

*

-0.211

-0.711**

0.837**

-0.502**

0.972**

0.370*

0.204*

0.947**

-0.226 *

0.942**

-0.005

NS

*

0.362

*

*

-0.144

-0.412* -0.070

NS

*

0.409

*

-0.190

-0.0522 NS *

-0.232*

0.182

*

-0.021 *

-0.207

-1.35

-0.001

-0.570** NS

0.010

NS

NS

0.002 NS -0.009

NS

0.850**

-0.660

**

0.842**

-0.498

*

0.590**

0.758**

0.883**

0.334

*

-0.996**

FOR WWI SITE OF NAUBASTA

-0.710

**

CF

-0.529

**

BR

CA

-0.447*

0.999**

*

**

-0.201

**

0.946

*

-0.988** *

-0.246* **

0.332

1.00 **

**

0.996**

0.315*

0.936

**

-0.760**

**

0.858**

0.535

0.285

-0.511

-0.974

0.972

-0.437*

-0.971**

0.971**

-0.837**

-0.710**

0.789**

0.542**

LF

-0.326*

0.992**

0.169*

-0.989**

0.946**

-0.061 NS

0.356*

TO

**

RA

0.793

-0.094

**

-0. 689 -0.979

**

*

-0. 214

**

-0.572

**

-0. 888

**

-0.954

**

0. 683

**

0.893

-0. 991 -0.239

**

*

-0.751** -0.629**

study area had received minimum rainfall in the recent years. This may also have contributed to the higher concentration of metals in the soil. It may be expected that during the summer season the relatively high decomposition rate of organic matter is likely to release have metals in soil solution for possible uptake by vegetables. Soil to vegetable transfer is one of the key components of human exposure to metals through food chain. In this study, the soil to vegetable transfer factor (TF) for various heavy metals and for most common vegetables consumed by human being were calculated and data showed that the TF values differed significantly between soil and vegetable concentrations the difference in TF values among different vegetables may be attributed to differences in element uptake by different vegetables.**Present studies on uptake of heavy metals through vegetables and the correlation between the heavy metals content in soil and vegetables are necessary to further understand the problem and to plan remedial measures with public participation. ACKNOWLEDGMENT The author would like to place on record their sincere thanks to prof. U.K.Chuahan (Prof. & Head) Dept. of Environmental Biology, A.P.S. University Rewa (M.P.), for so much advice & guidance to complete this research.

NS

FOR CWI SITE OF BHITI

REFERENCES

SP

0.683**

-0.912**

-0.939**

-0.210*

-0.818**

0.971**

0.539**

CA

0.479*

0.845**

-0.569**

-0.236*

-0.972**

-0.318*

0.421*

CF

-1.48

**

**

**

BR

0.970**

LF

-0.169

*

TO

-0.277

*

RA

0.429*

-0.963

**

-0.421* *

**

0.980

0.738** *

0.437

-0.371 **

**

*

0.451

0.516** 0.016

NS **

-0.689

0.656

0.168*

-0.044 NS

0.046 NS

-0.139*

*

0.283

*

**

0.721

**

-0. 999

0. 923

0. 844

0. 283

0. 989

0.956**

0.449*

-0.065

-0.689**

0.257*

0.377* -0.986** -0.884**

NS

Computation of Pearson’s correlation coefficient of heavy metals between soils and vegetables showed that for some vegetables; there were positive but not significantly correlation found while for other vegetables it was positively and significantly correlated. Positive correlation suggested that the metal in different kind of vegetables were translocated efficiently from the soil through root system (Agbenin et al., 2009). However most vegetables showed negatively and significantly while other showed negative but not significantly correlation (Table 2). Negative correlation indicated that higher concentration of heavy metals present in soils but in comparison much lower concentration were found to be in vegetables of that soils. This was due to poor retention capabilities of different edible parts of vegetables. TF values decreases with increasing respective metal concentration in soils, indicating an inverse relationship between transfer factor and metal concentration such inverse relationship were also reported by Wang et al., (2006). IV. CONCLUSIONS/RECOMMENDATION This study indicated that long term and indiscriminate application of waste water or letting of waste water directly to agricultural field without prior treatment which contain heavy metals in association with sludge particles may cause accumulation of toxic metals in surface and sub surface soils. And build up of heavy metals in soil profile may prove not only to plants and animals but also to consumers of harvested crops and vegetables. The vegetable samples were taken in the month of May when the temperature was high and also, the

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International Journal of Technical Research and Applications e-ISSN: 2320-8163, www.ijtra.com Volume 2, Issue 5 (Sep-Oct 2014), PP. 42-45

STRESS AND COPING STYLE OF URBAN AND RURAL ADOLESCENTS Samata Srivastava1, Dr. J. P. Singh2, Dr. Om Prakash Srivastava1 1

Department of psychology, P. G College Gazipur Uttar Pradesh (India) 2 Department of Psychology, Rashtriya P.G. College, Jamuhai (Jaunpur) [email protected] Abstract— This study aimed to assess the nature of stress, and coping styles among rural and urban adolescents. Methods: 200 students in 10+2 and graduation first year of both genders in the age range of 16-19 years were assessed with the Adolescent Stress Scale, and a self-report coping scale. Results: The Result of present study reveals that in both environmental settings male reported more stress than their counterparts girls, however, to utilize coping strategies female adolescents are in higher in number than male adolescents. Conclusions: It is important for research to examine how adolescents suffering from typical stressors such as school examination, family conflict and poor peer relations. Social support is likely one of the most important resources in their coping process. Key words— Adolescents; Stress; Coping; Environmental setting.

I. INTRODUCTION Adolescence is conceptualized as a transitional period, which begins with the onset of puberty and ends with the acceptance of adult roles and responsibilities. Of all life-stages, except childhood, adolescence is the one most marked by rapid and potentially tumultuous transition (Williams, Holmbeck, & Greenly, 2002). This is to be seen in the domain of biological development where the changes are physically externally manifest as well as in the progression of both cognitive and psychosocial maturity from that of childhood to that of the fully functioning adult (Byrne, Davenport, & Mazanov, 2007). While the transition through adolescence is inevitable the speed and magnitude of these changes overtax the capacity of many young people to cope and the resulting phenomenon of adolescent stress is now well recognized (Byrne, et al., 2007). The adolescent period involves a number of different intensities biological, cognitive, and psychosocial changes (Susman & Dorn, 2009). The biological changes involve physical changes in an Individual’s body with extraordinary growth and change in physical appearance and biological functioning. The pubertal changes also affect the adolescents psychologically, in different ways, and with and timing. The cognitive processes are one of the most striking changes to take place during adolescence and involve the development of far more sophisticated thinking abilities and reasoning ability. The rapid development of psychosocial processes during adolescence involve changes in emotions, personality, relationships with others, and social contexts (McElhaney, Allen, Stephenson, & Hare, 2009). A critical task of adolescence is the establishment of a stable sense of identity as a part of achieving autonomy. Adolescents must learn to deal with an expanding social universe and must develop the social skills to find friendship, romance, employment, and social standing within multiple social spheres (Cote, 2009). Adolescents must therefore develop a range of mechanisms, which allow them to function effectively in the face of the stress, which comes about from the transition of adolescence (Byrne et al., 2007).

A. Stress and adolescence period Stress has traditionally been conceptualized in three ways; as a stimulus (an event or accumulation of events); as a response (a psychophysiological reaction); or as a transactional process, in which a person and the environment interact to produce an appraisal of threat or loss (Caltabiano, Sarafino, & Byrne, 2008). “Stress” is used to describe the subjective experience of pressure, implying an evaluation of the outcome of a process. This is in line with the transactional view of stress as a relationship between environmental events or conditions, and the individual’s cognitive appraisals of the degree and type of challenge, threat, harm or loss (Lazarus & Folkman, 1984). The most widely accepted definition of stress is the transactional definition offered by Lazarus and Folkman (1984): “Psychological stress involves a particular relationship between the person and the environment that is appraised by the person as taxing or exceeding his or her resources and endangering his or her well-being” (p. 19). According to this definition, stress is subjective by nature, since it involves an appraisal of individual experiences. Many adolescents today experience numerous potential stressors throughout the process of growth and Development (Compas & Reeslund, 2009). Stressors of both an acute and chronic nature are important in the course of normal as well as disrupted development during adolescence. The types of stressors experienced in adolescence can broadly be divided into three categories. These categories are normative events, non-normative events and daily hassles (Suldo, Shaunessy, & Hardesty, 2008). Normative events refer to events that are experienced by most adolescents, but usually within a relatively predictable timescale. Examples of these includes internal and external changes related to pubertal development, psychosocial changes related to school, family, peers and academically demands. One important aspect here is that these are events, which all young people have to confront, but usually within a relatively predictable timescale (Coleman & Hendry, 1999; Suldo et al., 2008). Non-normative events are different in the way that they are events affecting one adolescent or only a smaller group of adolescents, and can occur at less predictable points in the life course (Grant et al., 2003). Such events can include for example, divorce, illness, injury or natural disasters. The last category is daily hassles. Daily hassles differ from major events in life that they are defined as minor, irritating, and frustrating events that are typical of daily interactions between individuals and their environments. B. Coping style and adolescence period Coping has been defined as the constantly changing cognitive and behavioral effect to manage specific external and /or internal demand that has been evaluated as taking up or exceeding the resources of the person (Lazarus & folkman, 42 | P a g e

International Journal of Technical Research and Applications e-ISSN: 2320-8163, www.ijtra.com Volume 2, Issue 5 (Sep-Oct 2014), PP. 42-45 Materials: - In the present investigation, two tools have been 1984). Research recognizes two functions of coping: regulating used to measure two dependent variable. The detailed stressful emotions and altering the person-environment relation description of these has given below. causing the distress (Folkman, Lazarus, Dunket-schetter, Delongis & Gruen, 1986). I.Psychological stress scale (Prof. A. K. Srivastava)The questionnaire was designed to assess the extended of Coping is thus expending conscious effort to solve personal individual’s feelings of basic components of psychological and interpersonal problems and seeking to master, minimize or stress (such as pressure tension anxiety, conflict, frustration, tolerate the stress of conflict. Psychological coping etc.) resulted from perceived stress situations (such as mechanisms are commonly termed coping strategies or coping adversities, hardships, threats, affliction, failures, constraints skill. The tern coping generally refers to adaptive or excessive demands, conflicting roles etc.) in various spheres of constructive coping strategies, i.e., the strategies reduce stress his social life. The Questionnaire altogether consisted of 40 levels. However; some coping strategies can be considered items representing following seven categories of the social maladaptive, i.e. stress levels increase. Coping response are situation of stress. partly controlled by personality trait, but also by the social contexts of person, particularly the nature of the stressful S.No. Psycho social stressors No. of environment. Coping is also an important mediator of items experience that shapes personality development and influences 1 Tense or strained interpersonal 5 adaptability and resilience in difficult situations (Garmezy, relationship 1987). Conceptualization of children’s/adolescent’s coping was 2 Economic constraints ; Extra 8 derived from the adult coping work. However, growing economic burden evidence indicates that coping abilities of children/adolescents 3 Excessive/ demanding responsibilities 5 may differ from those of adults in some very important ways and Liabilities and expectations of (Arnold, 1990; Compas, Banez, Malcarne, & Worsham, 1991; others Elias, Gara, & Ubriaco, 1985; Omizo, Omizo, & Suzuki, 1988). 4 Marriage related problem (of own or/ 4 Adolescents/Children may be limited in their coping repertoire and of family members) by cognitive, affective, expressive, or social facets of 5 Health related problems (of own or/ 3 development and by lack of experience. The adolescent’s and family member or near relations environments are quite different from adults’ environments, 6 Social situation; legal or property 10 particularly because children have less control over related disputes or problems. circumstances. Adolescents/Children are limited by realistic 7 Perceived or imagined threats to social 5 constraints, such as restricted freedom to actively avoid and economic status or prestige stressors (though restricted freedom also limits their exposure to some stressors), and a state of personal and financial II.Coping Strategies scale (Prof. A.k. Srivastava)dependence on parents. Thus, aspects of development and the The present measure of coping strategies comprises so items, to environment may limit the coping responses, adolescents are be rated on five point scale, 0 to 4 describing varieties of capable of making, and the coping strategies promoting coping behavior underlying following five major categories of adjustment in adolescents may differ from those promoting coping strategies based on the combinations of ‘operation’ and adjustment in adults. Teenagers are also at the stage of ‘Orientation’ of Coping. developing their personal styles of coping. The coping ACTIVE / APPROACH strategies can be reviewed, modified if needed and crystallized COPING (Problem- Focused from one experience of using certain mechanisms of coping coping) with another, during adolescent years. Miller and Kirsch (1987) they found that many studies report differences in how women Behavioral Approach Coping Strategies and men cope with stress, with men tending to deal with stress by problem-focused coping, while women tend to use strategies Cognitive Approach Coping Strategies that modify their emotional response, although these tendencies Cognitive Behavioral coping can change in certain circumstances. Several authors (i.e., Strategies Almeida & Kessler, 1998; Barnett et al., 1987) have suggested AVOIDANCE COPING that the impact of gender on the stress process could be (Emotion Focused coping) conditioned by traditional socialization patterns. The traditional female gender role prescribes dependence, affiliation, Behavioral Avoidance coping Strategies emotional expressiveness, a lack of assertiveness, and the subordination of one’s own needs to those of others. On the Cognitive Avoidance coping strategies other hand, the traditional male role prescribes attributes such as autonomy, self-confidence, assertiveness, instrumentality Procedure: For purpose of the study two groups of subjects and being goal-oriented. . As a summary, we can conclude that were undertaken, one belonging to extreme rural and the other there are some gender differences as well as similarities in from extreme urban environment. To meet the requirement, it adolescents' coping. was decided to adopt schools situated in two entirely different II. METHOD environments giving education to two category of students, one Sample: - The sample consisted of 200 adolescents from rural belonging to very-very poor family background and were less and urban population residing in the eastern district of U.P 100 privileged from the view point of socio-economic status, while adolescents were from rural background (50 male and 50 the other school chosen were from well-developed? female) and 100 were from urban backgrounds (50 male and 50 environment where the student from one of the richest families female). The age ranges of the subjects were 16 to 19 years. were taking education. After selection of the institutions 43 | P a g e

International Journal of Technical Research and Applications e-ISSN: 2320-8163, www.ijtra.com Volume 2, Issue 5 (Sep-Oct 2014), PP. 42-45 researcher contacted to the principle of all institutions for *p