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Volume-3 Issue-8, January 2014, ISSN:  2278-3075 (Online)
Published By: Blue Eyes Intelligence Engineering & Sciences Publication Pvt. Ltd. 

Page No.



Tapinder Kaur, Ashish Verma

Paper Title:

Structure Extraction from Complex Textures using Gradient based Relative Total Variation

Abstract:  It is universal that expressive arrangements are shaped by or seem over textured exteriors. Extracting them under the difficulty of texture patterns, which could be consistent, near-regular, or uneven, is very challenging, but of great real-worldsignificance. This paper presents a review on texture segmentation and analysis of different techniques. The comparisons among available techniques are also drawn in order to find the best suitable one. To overcome the existing problems of texture extraction a new extended relative total variation technique is proposed. The proposed technique has ability to extract textures from complex background images using gradient based methods and median filtering.  The proposed method has shown accurate results even in highly noisy images. The comparison has shown that the proposed method is quite significant over the available methods.

  Dark regions, gradients, texture, texture patterns, texture segmentation.


1.       Jiao, S., Li, X., & Lu, X. (2006). “An improved Ostu method for image segmentation”.In Signal Processing, 2006 8th International Conference on (Vol. 2).IEEE.
2.       Hu, J. L., Deng, J. B., & Sui, M. X. (2009, August). “Color space conversion model from CMYK to LAB based on prism”. In Granular computing, 2009, GRC'09. IEEE International Conference on (pp. 235-238). IEEE.

3.       Wang, X., Huang, X., & Fu, H. (2010, April). “A Color-Texture Segmentation Method to Extract Tree Image in Complex Scene”. In Machine Vision and Human-Machine Interface (MVHI), 2010 International Conference on (pp. 621-625). IEEE.

4.       Jian, Y. U. (2010, December). “Texture Image Segmentation Based on Gaussian Mixture Models and Gray Level Co-occurrence Matrix”. In Information Science and Engineering (ISISE), 2010 International Symposium on (pp. 149-152). IEEE

5.       Mridula, J., Kumar, K., &Patra, D. (2011, February). “Combining GLCM Features and Markov Random Field Model for Colour Textured Image Segmentation”. In Devices and Communications (ICDeCom), 2011 International Conference on (pp. 1-5). IEEE.

6.       Murugswari, G., &Suruliandi, A. (2011, March). “Comparative analysis of texture models for image segmentation.”In Computer, Communication and Electrical Technology (ICCCET), 2011 International Conference on (pp. 115-118).IEEE.

7.       NagaRaju, C., NagaMani, S., rakesh Prasad, G., &Sunitha, S. (2011). “Morphological Edge Detection Algorithm Based on Multi-Structure Elements of Different Directions”. International Journal of Information and Communication Technology Research© 2010-11 IJICT Journal, 1(1).

8.       Hengqiang, S., & Changji, W. (2012, June). “A new algorithm based on super-green features for ostu's method using image segmentation.” In World Automation Congress (WAC), 2012 (pp. 1-4). IEEE.

9.       Babu, U. R., Kumar, V. V., &Sujatha, B. (2012). “Texture Classification Based on Texton Features”.International Journal of Image, Graphics and Signal Processing (IJIGSP), 4(8), 36.

10.    Kezia, S., Prabha, I. S., & Kumar, V. V. (2013). “A Color-Texture Based Segmentation Method To Extract Object From Background”. International Journal of Image, Graphics and Signal Processing (IJIGSP), 5(3), 19.

11.    Rafael C. Gonzalez, Richard E. Woods. “Image Segmentation,” in Digital Image Processing, 3nd ed., India: Pearson, 2013, pp.689-787.

12.    S SapnaVarshney, NavinRajpal and RavindarPurwar. “Comparative Study of Image Segmentation Technique and Object Matching using Segmentation.” In International Conference on Methods and Models in Computer Science,2009,pp. 120-124.

13.    Xu, Li, Qiong Yan, Yang Xia, and JiayaJia. “Structure extraction from texture via relative total variation.” ACM Transactions on Graphics (TOG) 31, no. 6 (2012): 139.

14.    Wang, Wencheng, and Miao Hua. “Extracting Dominant Textures in Real Time With Multi-Scale Hue-Saturation-Intensity Histograms.” IEEE, 2013.

15.    Arivazhagan, S., and R. Benitta. "Texture classification using color local texture features." In Signal Processing Image Processing & Pattern Recognition (ICSIPR), International Conference on, pp. 220-223.IEEE, 2013.






Mahendraperumal Guruvaiah, Keesoo Lee

Paper Title:

Utilization of Flue Gas from Coal Burning Power Plant for Microalgae Cultivation for Biofuel Production

Abstract: Microalgae have high photosynthetic efficiency that can fix CO2 from the flue gas directly without any upstream CO2 separation, and along with produce biomass for biofuels application and reduce greenhouse gas emissions. Microalgae studies were conducted in a batch mode experiments at Power plant, Jefferson city, Missouri, USA. The experiments were conducted in different period (May to October, 2011) of time. The genus Scenedesmus sp was isolated from power plant habitat and used for this experiments and then comparative study done by flue gas ponds vs non flue gas treatment ponds. The microalga was cultured with different simulated flue gases containing 1% – 4% (volume fraction) of CO2. The results show that Scenedesmus sp were grown very efficient at 2% CO2 content. The maximal biomass productivity and lipid productivity were obtained when aerating with 2% of CO2. The lipids content ranged from 10 to 18 % of dry mass of biomass. Scenedesmus sp has a great potential for CO2 mitigation, environmental tolerance and biodiesel production.

   Biomass, CO2 Sequestration, Microalgae, Lipids.


1.       Amit Kumar, Sarina Ergas, Xin Yuan, Ashish Sahu, Qiong Zhang, Jo Dewulf, F. Xavier Malcata,  Herman van Langen hove 2010. Enhanced CO2 fixation and biofuel production via microalgae: recent developments and future directions. Trends in Biotechnology 28, 371–380.
2.       Chang EH, Yang SS. 2003. Some characteristics of microalgae isolated in Taiwan for biofixation of carbon dioxide. Bot Bull Acad Sin 44:43–52.

3.       Chiara B, Inna Khozin G, Sammy B, Avigad V, Zvi C.2002.Lipid and fatty acid composition of the green oleaginous alga Pariotochloris incises the richest plant source of arachidonic acid. Phytochemistry 2002; 60(5):497–503.

4.       Hanagata N, Takeuchi T, Fukuju Y, Barnes DJ, Karube I 1992. Tolerance of microalgae to high CO2 and high-temperature. Phytochemistry 31: 3345-3348.

5.       Olaizola M 2003. Commercial development of microalgal biotechnology: from the test tube to the market place. Biomolecular Engineering 20: 459-466.

6.       Ono E, Cuello JL. 2004. Design parameters of solar concentrating systems for CO2 mitigating algal photobioreactors. Energy; 29:1651–7.

7.       Sung KD, Lee JS, Shin CS, Park SC, Choi M J 1999. CO2 fixation by Chlorella sp. KR-1 and its cultural characteristics. Bioresource Technology 68: 269-273.

8.       Watanabe Y, Ohmura N, Saiki H 1992. Isolation and determination of cultural- characteristics of microalgae which functions under CO2 enriched atmosphere. Energy Conversion and Management 33: 545-552.






Abdulkadom Alyasiri, Jameel K Abed, Mohannad J Mnati

Paper Title:

Design and Implementation New Saving Energy System by Using Human Motion Sensor

Abstract:  This work presents the design of a new electronic system to save electrical energy. In this design is to focus on the use of low power digital IR motion sensors to perform human motion to voltage conversion .PIC16F84A microcontroller have been used to control the entire system. Three electrical devices (Televisions, Fan and Lump) was controller by this system. PROTEUS 8 professional software was used for simulating the designed system, and MikroC software from MikroElektronika was used to programing the pic16F84A microcontroller. Results of the system design showed how to saving electrical energy by using human motion sensor and PIC16F84A microcontroller.

 saving energy, PIC16f84A and human motion sensor.


1.       Ding Yanchuang , Guo Jinying , “ LED Display Screen Design and Proteus Simulation Based on Single-Chip Microcomputer”, International Conference on Information Engineering and Computer Science, IEEE Publisher, Pages: 1-4,2010
2.       Dr S S Adamu “A Control System Retrofit for a Plastic Bag Making Machine ”, International Journal of Engineering Science and Technology (IJEST), Vol. 3 No. 7 July 2011

3.       Kang Bing, Liu Fu, Yun Zhuo, and Liang Yanlei, “  Design of an Internet of Things-based Smart Home System”,The 2nd International Conference on Intelligent Control and Information Processing, IEEE Publisher ,July 25-28,2011

4.       Yavuz EROL, Hasan H. BALIK, Serkan INAL,Duygu KARABULUT, “Safe and Secure PIC Based Remote Control Application for Intelligent Home” , IJCSNS International Journal of Computer Science and Network  Security, VOL.7 No.5, May 2007

5.       LIU Li-jun, LI Zong-qiang , “Design and Simulation of LED Clock Circuit Based on Proteus”, International Conference on Computer, Mechatronics, Control and Electronic Engineering (CMCE), 2010

6.       Philip A. Adewuyi, Muniru O. Okelola, Adewale O. Jemilehin  , “PIC Based Model of an Intelligent Gate Controller”, International Journal of Engineering and Advanced Technology (IJEAT), Volume-2, Issue-3, February 2013

7.       Ankita Bharaktya, S.G.Reddy, “Energy Efficient Query Optimization in Wireless Sensor Networks”, International Journal of Engineering and Advanced Technology (IJEAT), Volume-1, Issue-6, August 2012

8.       Motion Sensor Board Manual. http://www.mikroe.com/downloads/get/1218/motion_manual_v100.

9.       Jasio,L,D, Wilmshurst,T , Ibrahim,D,(2008), “PIC Microcontrollers: Know    It All” , 1st ed, UK, Elsevier Inc.

10.    PIC16F84A Data Sheet.http://biltek.tubitak.gov.tr/gelisim/elektronik/dosyalar/9/pic16f84A

11.    LM78XX / LM78XXA Positive Voltage Regulator Datasheet http://www.fairchildsemi.com/ds/LM/LM7805.pdf

12.    mikroC PRO for PIC http://www.mikroe.com/downloads/get/30/
13.    Introduction to Proteus VSM (Part I) http://faculty.uoh.edu.sa/alutaibi/teaching/coe305/lab/01-Introduction%20to%20Proteus%20VSM%20Part%20I.pdf






Yogesh Kumar, Ashish Kumar Khandelwal, Sharda Pratap Shrivas

Paper Title:

A Study of Integrated Supply Chain Model

Abstract:   The purpose of this paper is to present the relationship between firm integration and supply chain orientation and supporting technology as moderating that relationship. The term can be used to describe either functional management or project management- leading technical professionals who are working in the fields of product development, manufacturing, construction, design engineering, industrial engineering, technology, production, or any other field that employs personnel who perform an engineering function. This paper concludes that trust, serious relationships, and good communication between tour operators and other SC members could lead to more efficiency and effectiveness in tourism business.

  development, manufacturing, construction, design engineering, industrial engineering, technology,


1.       Marcel W., “Supply Chain Analysis Thinking- Systems,” in Proceedings of the IEEE International Conference on Man and Cybernetics, 2003.
2.       Ganeshan R. and Harrison T., “An Introduction to Supply Chain Management,” http://silmaril.smeal.psu.edu/supply_chain_intro.html.

3.       M.H. Hugos, Essentials of Supply Chain Management, John Wiley and Sons, 2006.

4.       N.H. Moin and S Salhi, “Inventory Routing Problems: a Logistical Overview”, Journal Operational Research Society advance online publication, August 2006.

5.       Wikner, J., Towill, D.R. and Naim, M., Smoothing supply chain dynamics, International Journal of Production Economics, 1991, 22(3), pp. 231-248.

6.       Norrman, A, and Jansson, U., Ericsson’s proactive supply chain risk management approach after a serious sub-supplier accident, International Journal of Physical Distribution & Logistics Management, Vol. 34, No. 5, 2004, pp. 434-456.

7.       Gaudenzi, B., and Borghesi, A., Managing risks in the supply chain using the AHP method, The International Journal of Logistics Management, Vol. 17, No. 1, 2006, pp. 114-136.

8.       Wu, T., Blackhurst, J., and Chidambaram, V., A model for inbound supply risk analysis, Computers in Industry, Vol. 57, 2006, pp. 350–365.






Nirmala. M, Palanisamy. V

Paper Title:

An Efficient Framework for Exploring Personal Pattern Mining and Prediction in Mobile Commerce

Abstract:  With the rapid advance of wireless communication technology and the increasing popularity of powerful portable devices, mobile users not only can access worldwide information from anywhere at any time but also use their mobile devices to make business transactions easily, e.g., via digital wallet. Meanwhile, the availability of location acquisition technology, e.g., Global Positioning System (GPS), facilitates easy acquisition of a moving trajectory, which records a user movement history. We propose a novel framework namely, Mobile Commerce Prediction (MCP) framework consists of three major components: 1) Similarity Model (SM) for measuring the similarities among stores and items, which are two basic mobile commerce entities 2) Mobile Commerce Pattern Mine (MCPM) algorithm for efficient discovery of mobile users’ Personal Mobile Commerce Patterns 3) Mobile Commerce User Behavior Predictor (MCUBP) for prediction of possible mobile user behaviors. We perform an extensive experimental evaluation by simulation and show that our proposals to produce excellent results.

Association rule mining, Data mining, Mobile commerce, Pattern mining and prediction.


1.       R. Agrawal , T. Imielinski, and A. Swami, “Mining Association Rule between Sets of Items in Large Databases,” Proc. ACM SIGMOD Conf. Management of Data, pp. 207-216, May 1993.W.-K. Chen, Linear Networks and Systems (Book style).       Belmont, CA: Wadsworth, 1993, pp. 123–135.
2.       R. Agrawal and R. Srikant, “Fast Algorithm for Mining Association Rules,” Proc. Int’l Conf. Very Large Databases, pp. 478-499, Sept 1994.

3.       J. Han, J. Pei, and Y. Yin, “Mining Frequent Patterns without Candidate Generation,” Proc. ACM SIGMOD Conf. Management of Data, pp. 1-12, May 2000.

4.       V.S. Tseng and W.C. Lin, “Mining Sequential Mobile Access Patterns Efficiently in Mobile Web Systems,” Proc. Int’l Conf. Advanced Information Networking and Applications, pp. 867-871, Mar. 2005.

5.       R. Agrawal and R. Srikant, “Mining Sequential Patterns,” Proc.Int’l Conf. Data Eng., pp. 3-14, Mar. 1995.

6.       D. Xin, J. Han, X. Yan, and H. Cheng, “Mining Compressed Frequent-Pattern Sets,” Proc. Int’l Conf. Very Large Data Bases,pp. 709-720, Aug. 2005.

7.       S. C. Lee, J. Paik, J. Ok, I. Song, and U.M. Kim, “Efficient Mining of User Behaviors by Temporal Mobile Access Patterns,” Int’l J. Computer Science Security, vol. 7, no. 2, pp. 285-291, Feb. 2007.

8.       V.S. Tseng, H.C. Lu, and C.H. Huang, “Mining Temporal Mobile Sequential Patterns in Location-Based Service Environments,”Proc. Int’l Conf. Parallel and Distributed Systems, pp. 1-8, Dec. 2007.






Majid S. Naghmash, Hazim Salah Abdulsatar, Tahseen Flaih Hasan

Paper Title:

Reconfigurable Down Sampling Channelizer for SDR Receiver Using FPGA

Abstract:   This paper presents, the design and implementation of reconfigurable down sampling the IF band frequency to baseband in Software Defined Radio (SDR) receiver. To enhance both the integration and adaptation of multiple communication standards like GSM, CDMA and WCDM systems, the selection of channel in SDR technology require to achieve relaxing on chip at baseband. The wireless and mobile systems classically utilize a channelizer to extract the desired band for more processing in baseband. Down conversion in frequency domain requires less computation and complexity to provide the idea of minimum power consumption as current user demand.  In the low power design and efficient FPGA area implementation, the cascaded digital filter structure is required to convene multi standards specifications in wide and narrow band systems. Many type of digital filter has been decomposition to implement this filter as well as a lot of software from Mathworks and Xilinx is used. A number of experiments and investigation are given to estimate the results of FPGA design for filter structure.  The nonappearance of error in the design steps shows an important improvements in the filter implementation results to enhance the conventional design.

 Reconfigurable filter, Down Sampling, SDR Receiver, FPGA


1.          Rajesh and Pattnaik, “ Reconfigurable Design of GSM Digital down Converter for Enhanced Resource Utilization”,  International Journal of Computer Applications (0975 – 8887) Volume 57 – No.11, November 2013
2.          Santhosh Y. N., et al., “Design and VLSI Implementation of interpolators/decimators for DUC/DDC”, Third International Conference on Emerging Trends in Engineering and Technology, IEEE,  978-0-7695-4246-1/10, 2010

3.          Rajesh Mehra, Swapna Devi’ “Efficient Hardware Co-Simulation of Down Convertor for Wireless Communication Systems” International Journal of VLSI Design & Communication Systems (VLSICS), pp. 13- 21, Vol.1, No.2, June 2010.

4.          Majid Salal Naghmash and Mohd Fadzil Ain “Design of minimum error digital down-converter (DDC) for GSM mask requirements”, Journal of Engineering and Technology Research Vol.1 (5), pp.091-101, August, 2009.

5.          Kyung-ho Hwang and Dong-ho Cho, “Software Defined Radio Technology,” Telecommunications Review, vol . 10, no. 1, pp. 130-143,  Jan/Feb. 2000,

6.          Rajesh Mehra, Dr. Swapna Devi, “FPGA Based Design of an Optimized Digital Down Converter for Software Radio Wireless Applications” Innovative Conference on Embedded Systems, Mobile Communication and Computing, pp. 43-51, ICEMC2-2010.

7.          Young-bum Chang, “A Block FIR Filtering Architecture for IF Digital Down Converter,” Journal of IEEK, vol. 37, no. 9, , pp. 465-473. Sept. 2000

8.          LIN Fei-yu1, QIAO Wei-ming, WANG Yan-yu, LIU Tai-lian1, FAN Jin, HANG Jian-chuan, “Efficient WCDMA Digital Down Converter Design Using System Generator”. Proceeding of International Conference on Space Science and Communication, pp.89-92, IEEE-2009.

9.          S. Im, W. Lee, C. Kim, Y. Shin, S.H. Lee, and J. Chung, “Implement of SDR-Based Digital IF Channelizer / De channelizer for Multiple CDMA Signals,” IEICE Trans. Communications, vol . 83, no. 6,  pp. 1282-1289. June 2000

10.       Alan Y. Kwentus, “Application of Filter Sharpenning to Cascaded Integrator-Comb Decimation Filters,” IEEE, vol . 45, no. 2, pp. 457-467. Feb. 1997

11.       Emad S Malik, Khaled A. Shehata, Ahmad H. Madian, “ Design of Triple Mode Digital Down Coverter for WCDMA, CDMA 2000 and GSM of Software Defined Radios” International Conference on Microelectronics, pp. 272-275, IEEE-2009.

12.       Hyuk J. Oh, Sunbin Kim, and Ginkyu Choi, “On the Use of Interpolated Second-Order Polynomials for Efficient Filter Design in Programmable Downconversion,” IEEE J. Select. Areas Commun., vol. 17, no. 4, , pp. 551-560., Apr. 1999

13.       G. Mazzini, G. Setti, and R. Rovatti, “Chip pulse shaping in asynchronous chaos-based DS-CDMA,” IEEE Trans. Circuits Syst. I, vol. 54, no. 10, pp. 2299–2314, Oct. 2007.

14.       Amir Beygi, Ali Mohammadi, Adib Abrishamifar. “AN FPGA-BASED IRRATIONAL DECIMATOR FOR DIGITAL RECEIVERS” in 9th IEEE International Symposium on Signal Processing and its Applications, pp. 1-4, ISSPA-2007.

15.       Ming Jian, Weng Ho Yung, and Bai Songrong, “An Efficient IF Architecture for Dual-Mode GSM/W-CDMA Receiver of a Software Radio,” IEEE Int’l Workshop on Mobile Multimedia Communications, vol. 87932, , pp. 21-24.  Nov. 1999

16.       M. Cummings, S. Haruyama, “FPGA in the Software Radio”. IEEE Communications    Magazine, v37, pp.108-112. Feb. 1999.

17.       Rabiner, Crochiere, Optimum FIR Digital Filter Implementations for Decimation , Interpolation, and Narrow-Band Filtering, IEEE  Transactions on Acoustics,
Speech, and Signal Processing, October 1975.

18.       Rajesh Mehra, Dr. Swapna Devi, “FPGA Based Design of an Optimized Digital Down Converter for Software Radio Wireless Applications” Innovative Conference on Embedded Systems, Mobile Communication and Computing, pp. 43-51, ICEMC2-2010.

19.       Xilinx Corp., Virtex-4 Xtreme DSP Design Considerations User Guide,2008               

20.       Xilinx Corp., DDS Compiler v2.1, 2008

21.       Xilinx Corp., System Generator User Guide,2008

22.       Xilinx Corp., Xilinx ISE 10.1 Software Manuals, 2008.






Arjan Fakhraldin Abdullah, Mazin Burhan Adeen, Alya'a Abbas Al-Attar

Paper Title:

Studying Flexural Behavior of Reinforced Fibrous Self- Compacted Concrete T- Beams Strengthened with CFRP SHEETS

Abstract: This research Studies the possibility of producing self-compacting concrete (SCC) containing Pozzolanic materials and reinforced with different types of fibers , 11% (by weight of cement) of silica fume were used and two types of fiber (Steel, Nylon) with different volume fraction , also  it studies the structural behavior of the self-compacted  reinforced T-section beams. The current study includes a practical program considers the effect of adding steel and nylon fibers to structural behavior of T- section self-compacting concrete such as compressive and tensile strength and flexural behavior represent by load-deflection curves, variables that which studied after obtaining the self-compacting was the volumetric ratios of fibers which used (0.2, 0.3 and 0.4) % ratios for steel and nylon and hybrid fiber. Also Rehabilitate the T- beams after failure in bending by strengthened it with carbon fiber strips (CFRP), and find out the effect of external strengthening by CFRP on the flexural resistance of concrete & reinforced concrete beams. The practical results of the current study indicated that when adding steel fiber to the self-compacted concrete it has shown a good effect of the increase in compressive, tensile and flexural strength, also it has effect of reducing deflection, this effect increasing by increase of the volumetric ratio of steel fiber. while adding of nylon fibers lead to a slight increase in compressive strength and this effect decrease  by fiber content increasing  and the addition of these fibers lead to a small increase in the tensile and bending strength , also adding hybrid fiber in all ratios lead to an improvement in hardened properties of self-compacted concrete .The results of repair by strengthening the beams with carbon sheets indicated that the carbon fibers had a noticeable effect in increasing the ultimate load in all beams and testing results showed that the flexural strength increased between (6.42% - 29.62%) for concrete beams, and between (9%-33%) for rehabilitated damaged concrete beams.

  Fibers self-compact Concrete, Flexural Strength, CFRP, and Epoxy.


1.       Nagamoto N., Ozawa K., Mixture properties of Self-Compacting, High-Performance Concrete, Proceedings, Third CANMET/ACI International Conferences on Design and Materials and Recent Advances in Concrete Technology, SP-172, V. M. Malhotra, American Concrete Institute, Farmington Hills, Mich. 1997, p. 623-637.
2.       Khan A. R., "Repair and Strengthening of Reinforced Concrete Structures using CFRP Plates", FEST Hamadard University, India, 2002. (eprints.kfupm.edu.sa).

3.       Schanerch D., Standford, K. and Lanier, B., "Use of High Modulus Carbon Fibre Reinforced Polymer (CFRP) for Strengthening Steel Structures", Department of Civil Construction and Environmental Engineering, North Carolina State University, U.S.A., 2001.

4.       Al-Mahaidi, R.; Lee, K.; and Taplin, G., 2001, “Behavior and Analysis of RC T Beams Partially Damaged in Shear and Repaired with CFRP Laminates,” Structures Congress, ASCE, Washington DC.

5.       Hasan, Q. F., 2007, “Behavior of CFRP Strengthened Reinforced Concrete Beams under Cyclic Loading,” PhD thesis, University of Al-Nahrain.

6.       Limit of Iraqi specification No.5/1984

7.       Limits of the Iraqi specification No.45/1984 zone (3).
8.       ASTM C 33-01, "Standard specification for concrete Aggregates".
9.       M. Mazloom, A.A. Ramezanianpour, J.J. Brooks, "Effect of Silica Fume on Mechanical Properties of High-Strength Concrete", Elsevier Science Publishing Ltd., Cement & Concrete Composites 26 (2004) 347–357.

10.    EFNARC: Specification and guidelines for self-compacting concrete, February 2002.






Annu Pandey, Y.K.Bind

Paper Title:

Effects of Oil Contamination on Geotechnical Properties of Alluvial Soil Naini, Allahabad

Abstract:  Soil contamination by engine oil basically takes place due to spilling from vehicles or discarding of used engine oil in areas near garages or service stations. This contamination causes huge damage to the environment. The hydrocarbons present in the oil influences the quality and physical properties of oil contaminated soil. These hydrocarbons infiltrate into the soil through pore spaces and collect at the top of the ground level. A fraction of this hydrocarbon gets trapped and clog within pore space, which is cumbersome to remove and costly to clean .Some major tasks need to be performed for remediation and reclamation of contaminated area .Also, in connection with the clean-up works, and for any possible application of contaminated soil, a knowledge of the geotechnical properties and behavior of contaminated soils is required. This study aimed to investigate the compaction characteristics of engine oil-contaminated alluvial soil. The amount of oil added to soil was varied at 0%,4%,8% and 12% of the dried weight of samples. Results showed that the oil contamination decreased the liquid limit , plastic limit and shrinkage limits. The compaction characteristics were also affected to a great extent. The MDD value was found to be decreasing as a result of increasing amount of added engine oil into the soil. A similar behavior was observed with the value of OMC with increasing engine oil content, which means that the addition of oil has adverse effects to the geotechnical properties of the studied soil. Contaminated residual soils might be used for geotechnical purposes and these results will be used for geotechnical purposes and will benefit engineers or researchers in recycling or re-using of contaminated soils

   Hydrocarbons, oil contaminated soil, petroleum products, remediation, reclamation.


1.       American Petroleum Institute(1991).Sampling and analysis of gasoline range organics in soils.American Petroleum Institute Publication.No.45 16.
2.       In Situ Bioreclamation: Application and Investigations for Hydrocarbon and Contaminated Site Remediation. Ed. by Hinchee, R.E. and O1 fen bu ttel, R.F. Butterworth-Heinemann. London. pp. 125- 142.

3.       Dineen. D., Slater, J.P., Jicks, P. and Holland, 1. (1990). In situ biological remediation of petroleum hydrocarbons in unsaturated soils. Hydrocarbon Contaminated Soil and Ground Water : Analysis, Fate, Environmental and Public Health Effects, Remediation. Ed by Kostecki, P.T. and Calabrese, E. J. Vol. 1. Lewis Publishers, Chelsea, Mich., pp. 177- 187.

4.       Custance, S. and Ruth, M.P. ( 1992). Environmental fate of the chemical mixtures: crude oil, JP-5, mineral spirits, and diesel fuel. Journal of Soil Contamination. 1 (4): 379-386.

5.       O. Samira, G. Gerard, and R. Waleed, "Types and extent of soil contamination in greater Al-Burqan oil field, Kuwait", Kuwait: s.n:2006, Kuwait Journal of Science and Engineering, vol. 33, pp. 89-99.

6.       Gr&, K. and Kriston, E. (1995). In situ bioremediation of hydrocarbon in soil. Journal of Soil Contamination . 4(2): 163- 173.

7.       Wroth, C. P. and Wood, D. M. (1978).”The correlation of Index Properties with Some Basic Engineering Properties of Soils.” Canadian Geotechnical Journal, 15, 137-145.

8.       Blight, G.E. 1997. Mechanics of Residual Soils: A guide to the formation, classification and geotechnical properties of residual soils, with advice for geotechnical design. Rotterdam, The Netherland: Balkema Publishers.

9.       ASTM. (1996a). Standard test method for particle size analysis of soils (D422-63). In 1996 Annual book of ASTM stondardî. Sec. 8, Vol. 4, ASTM, Philadelphia, pp. 10-20.

10.    Rahman,Z.A., U.Hamazah, M.R.Taha  ,N.S.Ithnain and Ahmad,2010.”Influence of oil contamination on Geotechnical Properties of Basaltic soil.”Am.J.applied sci.,&:7

11.    Khamehchiyan, M., Charkhabi, A.M. & Tajik, M. 2007. Effects of crude oil contamination on geotechnical properties of clayey and sandy soils. Eng. Geol. 89: 220-229.

12.    Mercer J.W.,Cohen R.M.(1990):”A review of immiscible fluids in the subsurfaces:Properties; models;characterization and remediation.J.contamin.Hydrogeol.6,107-163.

13.    ASTM. (1996b). Test method for laboratory compaction characteristics of soi1 using standardeffort (D689-91). In 1996 Annual book of ASTM standards. Sec. 8, Vol. 4, ASTM,Philadelphia, pp.75-82.

14.    Shin, E.C. and Das, M.D. (2001). “Bearing capacity of unsaturated oil-contaminated sand.International Journal of Offshore and Polar Engineering, Vol. 11, No. 3.






Haque Nawaz, Himat Ali

Paper Title:

Gear Measurement Using Image Processing in Matlab

Abstract:   In this paper gear Measurement has been carried out by focusing two features of gear image object. The problems are to measure the gear features of gear image object, in the sense the measurement of the Area of the gear image object and as well the teeth of the gear will be counted. We have used Matlab tool and development code which overcome these problems and measured the area as well as teeth of the gear image object counted. To accomplish this task we have measured five different gear image objects area and counted the teeth by using image processing. The experimental results and statistics have been shown in this paper.

Gear, Measurement, Image Processing


1.    Zhang Jing “The Research on the Application to Digital Image Technology in Hypoid Gear Contact Zone Detection”, College of Computer Science & Technology, Henan Polytechnic University, Jiaozuo, China.
2.    Fred B. Oswald and Dennis P. Townsend “Dynamic Forces in Spur Gears  Measurement, Prediction, and Code Validation” Lewis Research Center Cleveland, Ohio Brian Rebbechi DSTO, Aeronautical and Maritime Research Laboratory Melbourne, Australia

3.    Joel M. Esposito, Matthew G. Feemster, and John M. Watkins” Role of a  MATLAB Real-time Hardware Interface With in a Systems Modeling Course” United States Naval Academy Weapons & Systems Engineering department, Mail Stop 14A, 105 Maryland Ave., Annapolis, MD 21402-5034

4.    Sören Sjöberg “On the running-in of gears” Department of Machine Design Royal Institute of Technology SE-100 44 Stockholm TRITA – MMK 2010:03

5.    Shrikant J. Honade “Height, Weight and Body Mass index measurement using Matlab”  Dept. of Electronics & Telecommunication, G. H. R. C. E. M., Amravati. S. G. B. A. U., Amravati, India

6.    J. Caja, E. Gómez, C. Barajas, P. Maresca, M. Berzal “Alternative Method for the Metrological Characterization of Spur Gears in the Sub- Millimeter Range Using Optical Equipment” Departament of de Mecánica Industrial - Universidad Politécnica de Madrid Ronda de Valencia, 3 - 28012 Madrid – España

7.    Arashiro, Maiko, and David Leith. "Precision of PM measurements with the UNC passive aerosol sampler", Journal of Aerosol Science, 2013.






M. Shahjahan, N. A. Ahmed, S. N. Rahman, S. Islam, N. Khatun, M. S. Hossain

Paper Title:

Structural and Electrical Characterization of Li-Zn Ferrites

Abstract: Four ferrite samples of Li0.5xFe0.5xZn1-xFe2O4, where x= 0.6, 0.7, 0.8, 0.9 were prepared by conventional ceramic method. The dc electrical resistivity as a function of temperature has been studied and found to decrease with the increase in temperature. The Curie temperature (Tc) has been found to increase as the Zn content decreases from x=0.6 to x=0.8. But for the sample where x=0.9 the Curie temperature is less than that of the sample where x=0.8. The ac electrical conductivity (ac), dielectric constant (), the dielectric loss tangent (tan) and quality control factor (Q-factor) as a function of frequency have also been studied. The experimental results indicate that for the first three samples the ac electrical conductivity (ac) decreases with the increase in frequency up to 200 KHz and afterwards it increases with the increase in frequency. But for the sample where x=0.9 the ac conductivity (ac) increases with the increase in frequency. It has been found that with the increase in frequency the dielectric constant () and dielectric loss tangent (tan) decrease while the quality factor (Q-factor) and ac conductivity increases.      

 Conventional Ceramic, Electrical Properties, Lithium Zinc, Surface Morphology.


1.       Abdullah M H , Yusoff AN, “Frequency dependence of the complex impedances and dielectric behaviour of some Mg-Zn ferrites” Journal of Materials Science Vol. 32, Issue.21, 11-1997, pp 5817-5823.
2.       El Hitti M A, “Dielectric behavior and ac electrical conductivity of Zn substituted Ni-Mg ferrites” Journal of Magnetism and Magnetic Materials, Vol.164, issue 1-2, 11-1996, pp.187-196

3.       Suryavanshi S. S, Kabbur S. M, Deshmukh U.B, Sawant S.R “Complex permeability studies of Li1+ substituted Cu-Zn ferrites” Journal of Electronic Materials,Vol.29, No.7, Jul 2000, pp. 979-983

4.       R.K. Puri, R. Mitra, and R.G. Mendiratta, Proc. ICF-6, New Delhi, India, 1989, pp. 353-357.

5.       N. Rezlescu, E. Rezlescu, P. D. Popa, M. L. Craus, and L. Rezlescu, “Copper ions influence on the physical properties of a magnesium-zinc ferrite,” Journal of Magnetism and Magnetic Materials, vol. 182, no. 1-2, 1998, pp. 199–206.

6.       Sumitra Phanjouban & Chandra prakash “Structural properties and d.c resistivity of Li- Zn-Ti Ferrites” Condensed Matter Physics; Statistical Physics and Applied Physics” Vol. 16, No. 27 (2002),pp. 1027-1030.

7.       Venugopal Reddy P. and Schsagiri Rao T, “Dielectric behaviour of mixed Li-Ni ferrites at low frequencies “Journal of the Less Common Metals ,vol.86, july 1982,pp.255-261.

8.       Young-Yeal Song, Michael S, Grinolds,Pavol Krivosik and Carl E, Ptton, “Pulsed laser-deposited single-crystal LiZn-ferrite films with low microwave loss” Journal of Applied Physics ,Vol. 97,  Issue.10 , May 2005, pp.103516(5).

9.       N. Rezlescu & E. Rezlescu “The Influence of Additives on the Material Parameters of Li-Zn Ferrites” physica status solidi (a) Vol. 147, Issue.2.1995, pp-553-562.

10.    Good enough, John.B “Chemical Inhomogeneities and Square BH Loops”  Journal of Applied Physics ,Vol. 36 , 1965, pp.2342-2346

11.    D Ravinder & K Vijay Kumer  “Dielectric behaviour of erbium substituted Mn-Zn ferrites” Bulletin of Materials Science , Vol.5,2001,pp.505-509.

12.    Radha K and Ravinder D “Frequency and composition dependence of dielectric behavior of mixed Li-Cd ferrites” Indian Journal of Pure and Applied Physics, Vol. 33, 1995, pp.74-77.

13.    Iwauchi.K “Dielectric Properties of Fine Particles of Fe3O4 and Some Ferrites”Japanese Journal of Applied Physics, vol. 10, 1971, pp. 1520–1528.

14.    A.A.Sattar, H.M.El-Sayed, W.R.Agami, and A.A.Ghani, “Magnetic properties and electrical resistivity of [Zr.sup.4+] substituted Li-Zn ferrite” American Journal of Applied Science, vol. 4 Issue.2 Feb, 2007, pp 89-93.






R. S. Pawar, S. H. Sawant

Paper Title:

An Overview of Vibration Analysis of Cracked Cantilever Beam with Non-Linear Parameters and Harmonic Excitations

Abstract:  A beam is an elongated member, usually slender, intended to resist lateral loads by bending. These beam-like structures are typically subjected to dynamic loads.  Therefore, the vibration of beams is of particular interest to the engineer. This paper tries to focuses in the study of the vibration analysis of cracked cantilever beam subjected to free and harmonic excitation at the base. The objective of the study is to identify the effect of non-linearities namely material, geometric, and damping on the natural frequency and mode shapes of cracked cantilever beam by theoretical, numerical and experimental methods.

  Cracked simply supported beam, Cracked Cantilever Beam with Non-linear Parameters and Harmonic Excitation, Free Vibration and Elastic Buckling beams, Modal Analysis of beams with different materials, Rotating Cantilever Beam, Non-linearities in Cracked cantilever beam, Vibrations of axially moving  beam.


1.       Cook, R.D., and Young, W.C., Advanced Mechanics of Materials, Prentice Hall, New Jersey, 1999
2.       Nayfeh, A.H., and Pai, P.F., “Linear and Nonlinear Structure Mechanics”, John Wiley & Sons, New York, 2003.

3.       D. Ravi Prasad and D.R. Seshu,  "A study on Dynamic Characteristics of Structural Materials Using Modal Analysis", Asian Journal of Civil Engineering, Volume 9, Number 2, Pages 141-152, 2008.

4.       Tarsiciobeleândez, Cristianneipp and Augusto beleândez, “Numerical and Experimental Analysis of a Cantilever Beam: a Laboratory Project to Introduce Geometric Nonlinearity in Mechanics of Materials”, International journal of Engineering, Vol. 19, No. 6, pp. 885±892, 2003.

5.       H HYoo and S H Shin, “Vibration Analysis of Rotating Cantilever Beams", Journal of Sound & Vibration, Pages 807-828, 12 Dec.1997.

6.       Mousa Rezaee and Reza Hassannejad, "Damped Free Vibration Analysis of a Beam with a Fatigue Crack using Energy Balance Methods”, International Journal of the Physical Sciences, Pages 793-803, Volume 5(6), June, 2010.

7.       Chih Ling Huang, Wen Yi Lin, Luo Mo Hsio, "Free Vibration Analysis of Rotating Euler Beams and High Angular Velocity", Dept. of Mechanical Engineering; National Chiao Tung University,, HsinchuTiawan 14 Nov. 2005.

8.       H. Ding, G.C. Zhang, LQ Chen, "Supercritical Vibration of Non-linear Coupled Moving Beams based on Discrete Fourier  Transform", International Journal of Nonlinear Mechanics , 2011.

9.       Liao- Liang Ke, Jie Yang, Sritawat Kitipornchai, Yanghh Xiang, "Flexural Vibration and Elastic Buckling of a Cracked Timoshenko Beam made of Functionally Graded Materials", Journal of Advanced Materials and Structures, Volume 16, Page 488-502, 2009.





Shubham Srivastava, Pratibha Singh

Paper Title:

Real-Time Object Tracking Using Colour Feature

Abstract:   Video Tracking is the process of locating a moving object over time using a camera. The objective of video tracking is to associate target objects in consecutive video frames. The association can be especially difficult when the objects are moving fast relative to the frame rate. Another situation that increases the complexity of the problem is when the tracked object changes orientation over time. For these situations video tracking systems usually employ a motion model which describes how the image of the target might change for different possible motions of the object. In this paper an algorithm is proposed to track the real time moving objects in different frames of a video.

   Shape Features, Object tracking, Feature Extraction.


1.       Q. Wang and Z. Gao, “Study on a Real-Time Object Tracking System,” in Computer Science and Computational Technology, 2008. ISCSCT’08. International Symposium on, vol.2, 2008.
2.       Alok K. Watve, Indian Institute of Technology, Kharagpur, seminar on “Object tracking in video scenes”, 2005.

3.       C. Lakshmi Devasena, R. Revathi, “   Video surveillance system-A survey”, IJCSI International journal of computer science Issues, vol. 8, issue 4, no.1, July 2011.

4.       K. Wang, Z. Li, Q. Yao, W. Huang, and F. Wang, “An automated vehicle counting system for traffic surveillance,” IEEE Int. Conf., on Vehicular Electronics and Safety, Japan, Dec 2007, pp. 1-6.Books:

5.       Rafael C. Gonzalez, Richard E. Woods. Digital Image Processing, Pearson Education, 2009.

6.       S. Sridhar. Digital Image Processing, Oxford Higher Edition. 2011.






Alnuami W., Buthainah A., Etti C. J., Jassim L. I., Gomes G. A. C.

Paper Title:

Evaluation of Different Materials for Biodiesel Production

Abstract: The challenges of the dwindling supply of fossil fuels and environmental pollutions caused by them are of growing concerns in the world today. Theincrease in world population has resulted in higher consumption of fossil fuel leading to a reduction in petroleum reserves,which are finite and found only in a few regions of the world. Hence, it becomes necessary to look for alternative fuel that is cheap and can be produced from readily available materials. Biodiesel is a renewable energy derived from vegetable oil and animal fats by transesterificationwith methanol and is widely adopted in many countries around the world as an alternative form of energy resource. It has been found to be a very good substitute for petroleum diesel with several advantages such as lower toxicity, higher flash and fire points than the petroleum diesel meaning that they are less flammable hence they are safer to handle, better biodegradable and higher lubricity than the petroleum diesel which means that an engine run on biodiesel will be less prone to wear and will last longer. The high cost of biodiesel is a major setback to its commercialization. And is mainly due to the high cost of raw materialsit’s the production. Therefore, identifying the right and readily available material that will give good biodiesel yield with good fuel properties and performance dynamic efficiency is very important. This Paperevaluates the different materials that are suitable for biodiesel production as an alternative source of fuel.

 Alternative fuel, Biodiesel, Petroleum fuel, Transesterification, Triglycerides


1.        Alcantara, R., Amores, J., Canoira, L., Fidalgo, E., Franco, M. J., & Navarro, A. (2000). Catalytic production of biodiesel from soybean oil, used frying oil and tallow. Biomass Bioenergy, 18, 515-527.
2.        Amish, P. V., Subrahmanyam, N., & Payal, A. P. (2009). Production of biodiesel through transesterification of Jatropha oil using KNO2/Al2O3 solid catalyst.

3.        Antolin, G., Tinaut, F. V., Briceno, Y., Castano, V., Perez, C., & Ramirez, A. I. (2002). Optimization of biodiesel production by sunflower oil transesterification. Bioresour. Technol, 83 (2), 111.

4.        Ayhan, D. (2002). No TitleBiodiesel from vegetable oils via transesterification in supercritical methanol. International Journal of Energy conversion and Management, 43, 2349-2356.

5.        Berchmans, H. J., & Hirata, S. (2008). Biodiesel production from crude Jatropha curcas L. Seed oil with a high content of free fatty acids. Bioresource Technology, 99, 1716-1721.

6.        Bhale, P. V., Deshpande, N. V., & Thombre, S. B. (2009). Improving the low temperature flow properties of biodiesel fuel. Renewable Energy, 34 (3), 6.

7.        Bournay, L., Casanave, D., Delfort, B., Hillon, G., & Chodorge, J. A. (2005). New heterogeneous process for biodiesel production: A way to improve the quality and the value of the crude glycerin produced by biodiesel plants. Catalysis TODAY, 106, 1-4. Doi: 190-192. doi: DOI: 10.1016/j. coated. 2005.07.181

8.        Chang, D. Y. Z., Van Gerpen, J. H., Lee, I., Johnson, L. A., Hammond, E. G., & Marley, S. J. (1996). Fuel properties and emissions of soybean oil esters as diesel fuel. J. Am. Oil Chem. Soc., 7311, 1549.

9.        Chen, Y., Xiao, B., Chang, J., Fu, Y., L v, P., & Wang, X. (2009). Synthesis of biodiesel from waste cooking oil using immobilized lipase in fixed bed reactor. Energy Conversion and Management, 50 (3), 668-673. doi: doi: DOI: 10.1016/j. enconman. 2008.10.011

10.     Demirbas, A. (2005). Biodiesel production from vegetable oil via and non-catalytic supercritical methanol transesterification methods. Progress in Energy and Combustion Science, 31, 466-487.

11.     Demirbas, A. (2009). Biodiesel from waste cooking oil via base-catalytic and supercritical methanol transesterification. Energy Conversion and Management, 50 (4), 923-927. doi: doi: DOI: 10.1016/j. enconman. 2008.12.023

12.     Denker, J.  (2009). Timescale for depletion of fossil energy resources. Retrieved December, 12, 2010from: http://www.av8n.com/physics/fossil-resources.htm.

13.     Di Serio, M., Tesser, R., Pengmei, L., & Santacesaria, E. (2008). Production, Heterogeneous catalysts for biodiesel. Energy and Fuels, 22 (1), 207-217. doi: doi: DOI: 10.1021/ef700250g

14.     GeoSunNrg. (N.d.). Need for renewable energy. 2010. Retrieved from http://www.geosunnrg.com/about-us/resource/need-for-renewable-energy.

15.     Graboski, M. S., & McCormick, R. L. (1998). Combustion of fat and vegetable oil derived fuels in diesel engines. Prog. Energy Combust. Sci., 24, 125.

16.     Gubitz, G. M. (1999). Exploitation of the tropical seed plant Jathropha Curcas L. Boires Technol, 67, 73-82.

17.     Joelianingsih, Meada, H., Hagiwara, S., Nabetani, H., Sagara, Y., Soerawidjaya, T. H., Armansyah, H., et al. (2008). Biodiesel fuels from palm oil via the non-catalytic transesterification in a bubble column reactor at atmospheric pressure: A kinetic study. Renewable Energy, 33, 1629-1636.

18.     Krawczyk, T. (1996). Biodiesel. INFORM, 7 (8), 801-822.

19.     Liu, X., He, H., Wang, Y., Zhu, S., & Xianglan. (2007). Transesterification of soybean oil to biodiesel using CaO as a solid base catalyst. Fuel journal, 87, 216-221.

20.     Liu, X., Piao, X., Wang, Y., Zhu, S., & He, H. (2008). Calcium methoxide as a solid base for the transesterification of soybean oil to biodiesel with methanol. Fuel, 87
(7), 1076-1082. doi: doi: DOI: 10.106/j. fuel. 2007.05.057

21.     Lott, M. (2002). QSS Group Inc., 4500 Forbes Boulevard, Suite 200, Lanham, MD 20706.

22.     Meng, X., Chen, G., & Wang, Y. (2008). Biodiesel production from waste cooking oil via alkali catalyst and engine test. Fuel processing Technology, 89, 851-857.

23.     Moser, B. R., & Vaughn, S. F. (2010). Coriander seed oil methyl esters as biodiesel fuel: Unique fatty acid composition and excellent oxidative stability. Biomass and bioenergy, 34, 550-558.

24.     Nakpong, P., & Wootthikkhan, S. (2010). High free fatty acid coconut oil as a potential feedstock for biodiesel production in Thailand. Renewable Energy, 35, 1682-1687.

25.     Nye, M., Williamson, T., Deshpande, W., Schrader, J., Snively, W., Yurkewich, T., & French, C. (1983). Conversion of used frying oil to diesel fuel by
transesterification: Preliminary tests. Journal of American Oil Chemists’ Society, 60 (8), 1598-1601. doi: doi: DOI: 10.1007/bf02666593

26.     Peng, B., Shu, Q., Wang, J., Wang, G., Wang, D., & Han, M. (2008). Biodiesel production from waste oil feed stocks by solid acid catalysis, 86, 441-447.

27.     Predojevic, Z. J. (2008). The production of biodiesel from waste cooking oils: A comparison of different purification step. Fuel, 87, 3522-3528.

28.     Prokop, T. (2002). Imperial Western Products, 14970 Chandler St., Coachella, CA 91720.

29.     Ramadhas, A. S., Jayaraj, S., & Muraleedhara, C. (2005). Biodiesel production from high FFA rubber seed oil. Fuel, 84, 335-340.

30.     Rice, B., Frohlich, A., & Leonard, R. (1998). Biodiesel production from Camelina oil, waste cooking oil and Fallow Crop Research Centre, Oak park, Carlow.

31.     Samart, C., Chaiya, C., & Reubroycharoen, P. (2010). Biodiesel production from methanolysis of soybean oil using calcium supported on mesoporous silica catalyst. Energy Conversion and Management, 51, 1428-1431.

32.     Shah, S., & Gupta, M. N. (2007). Lipase catalyzed preparation of biodiesel from Jatropha oil in a solvent free system. Process Biochemistry, 42, 409-414.

33.     Sharma, Y. C., Singh, B., & Upadhyay, S. N. (2008). Advancement in development and characterization of biodiesel: A review. Fuel, 87, 2355-2373.Xu, Y. X ., & Hanna, M. A. (2009). Synthesis and characterization of hazelnut oil-based biodiesel. Industrial Crops and Products, 29 (2-3), 473-479.






Chitra Sree. P, Ravi Shankar.J

Paper Title:

Implementation of Digital Cross Connect For Simplex Mode of Communication

Abstract:  DCS available in the market is expensive and bulky and not scalable and reprogrammable. We have simulated various DCS modes, mainly concentrates on developing indigenous SOC architecture that is reprogrammable, scalable and upgradable. The various switching modes of proposed  DCS are round robin, priority and request and acknowledge , The design is simulated using Verilog Hardware Description Language (HDL) in Xilinx ISE9.1i version software and can be  implemented on Xilinx Spartan2 family based FPGA board.

  Telecommunication, Switching, DCS, simplex mode, round robin, priority, request and acknowledge


1.     Vinita Singhal and Robert Le, “High-Speed Buffered Crossbar Switch Design using Virtex -EM Devices” XAPP240 (v1.0) March 14, 2000, pg 1-7.
2.     “Building Crosspoint Switches with CoolRunner-II CPLDs” XAPP380 (v1.0) June 5, 2002, pg 1-5.

3.     J. E. Flood, “Telecommunication Switcing, Traffic and Networks,” Pearson  2011.

4.     Thiagarajan Vishwanathan, “Telecommunication Switching Systems and Networks,” PHI 2012.

5.     GuoweiShi ,“Design and application of SDH digital cross-connect system”, Communications, Circuits and Systems and West Sino Expositions, IEEE 2002 International Conference on communications. vol.2,pg 1293 - 1296

6.     Yuan Yuying, “Design and Realization of SDH Digital Cross-Connect Matrix ”,IEEE Conference Publications, WiCom ,2007 ,pg 692 - 695

7.     Yuan Yuying “The design of the SDH digital cross-connect matrix based on ASIC”, World Automation Congress (WAC), IEEE Conference Publication,2012.pg 1-4






Vikram J. Patel, Hemraj R. Kumavat

Paper Title:

Modelling of Speed- Flow Equations on Four- Lane National Highway-8

Abstract:   The precise determination of relationship between speed and flow is essential for arriving at the capacity of a road. The Principal objective of the present study is to evaluate speed-flow relationships on National Highway-8 for different types of vehicles by developing separate speed-flow equations on NH-8.

   Capacity, Flow, Free speed, Spot speed,  Lane width, Speed-Flow equations.

1.       Errampalli Madhu, S. Velmurugan, K. Ravinder and J. Nataraju, Development of free-speed equations for assessment of road-user cost on high-speed multi-lane carriageways of India on Plain Terrain, Current Science, vol. 100, no. 9, 10 May 2011.
2.       Huafeng Gong, Operating Speed Prediction Models for Horizontal Curves On Rural Four-Lane Non-Freeway Highways, University of Kentucky Doctoral Dissertations.

3.       Speed Prediction for Two-Lane Rural Highways, Publication No. 99-171 August 2000.

4.       Modeling Operating Speed Synthesis Report, Transportation Research Circular, Number E-C151 July 2011.

5.       V. Thamizh  Arasan, and G. Dhivya, Measuring Heterogeneous Traffic Density, World Academy of Science, Engineering and Technology, Vol. 22, 2008.

6.       Richard Dowling et. Al, Urban Arterial Speed-Flow Equations For Travel Demand Models, April 19, 2006.

7.       Kivanc A. Avrenli1 et. Al, Traffic Flow Characteristics and Capacity in Police-enforced and Intelligent Work Zones, International Symposium on Highway Capacity and
Quality of Service Stockholm, Vol. 6, Sweden June 28 – July 1, 2011.

8.       Indonesia Highway Capacity Manual, Part-II Interurban Roads No. 05, January 1995.

9.       Michael Kyte et. Al, Effect of Environmental Factors on Free-Flow Speed.

10.    Lonnie E. Haefner and Ming- Shiun Li, Traffic Flow Simulation for an Urban Freeway Corridor, Transportation Conference Preceedings, 1998.

11.    Ibrahim Hassan Hashim, Analysis of speed characteristics for rural two-lane roads: A field study from Minoufiya Governorate, Egypt, Ain Shams Engineering Journal, 2011, Vol.2, pp. 43-52.

12.    Rahim F. Benekohal, Kivanc Avrenli and Hani Ramezani, Traffic Flow Characteristic and Capacity in Intelligent Work Zones, 2009.

13.    Satish Chandra et. al, Traffic Flow Analysis on Intermediate Lane Roads, Indian Highways,  December-2010.






Hemraj R. Kumavat, Vikram J. Patel

Paper Title:

Factors Influencing the Strength Relationship of Concrete Cube and Standard Cylinder

Abstract: This paper report an experimental study carried out to investigate to influence of addition of different size aggregate and w/c ratio on the mechanical properties of controlled concrete. The standard size cube and cylinder specimens are prepared and cured for period of 7 and 28 days. At the end of each curing period the compressive strength of each specimen are determined. The result indicate that the cement content in mix are increasing, the ratio of cylinder to cube strength is in case of 10mm aggregate than the 20mm aggregate are also increasing. The results also show there is no unique relationship between the strength of cube and strength of cylinder.

 Aggregate size, Compressive strength, Cube and Cylinder specimen, w/c ratio,

1.    M.S.Shetty, Concrete technology-theory and practice, S Chand publication (2005)
2.    Tumidajski P.J. and Gong B., Effect of coarse aggregate size on strength and workability of concrete, Canadian Journal of Civil Engineering, 76-78 (2006)

3.    Aïtcin, P.C., Miao, B., Cook, W. D., and D. Mitchell. 1994. Effects of Size and Curing on Cylinder Compressive Strength of Normal and High- Strength Concretes. ACI Materials Journal 91(4): 349-354

4.    IS 456:2000 Code of practice for plain and reinforced concrete (fourth revision) Aug 2005

5.    IS 383:1970 Specification for coarse and fine aggregates from natural sources for concrete (second revision) Jan 2007

6.    IS 516:1959 Method of test for strength of concrete Feb 2004

7.    IS 2386(Part 1):1963 Methods of test for aggregates for concrete: Part 1 Particle size and shape Jan 2007

8.    SP 24(S&T): 1983 Explanatory handbook on Indian Standard code of practice for plain and reinforced concrete (IS 456:1978)

9.    BS 1881: Part 120:1983- method for determination of compressive strength of concrete cores.






Yashveer Singh, Kriti Arya, A K Malik

Paper Title:

Inventory Control with Soft Computing Techniques

Abstract:  The objective of this paper is the findings a systematic review of existing research papers concern with the application of soft computing techniques to inventory management. In business organization, inventory management is one of the major core competencies to compete in the global market place. The most important purpose served by the stores is to provide the uninterrupted service to the manufacturing divisions. The purpose of inventory in any business is to decrease the cost of set up and shortage cost. Whenever demands of customers are not fulfilled then good-will of the customers may be lost and the cancellations of orders i.e., result may be in the lost of business.

 Inventory Control, Soft Computing, Fuzzy Logic, Genetic Algorithm.


1.       Ghare, P.M., Schrader, G.P., (1963). A model for an exponentially decaying inventory. Journal of Industrial Engineering, 14 (5), 238–243.
2.       Zadeh, L. A. (1965). Fuzzy Sets, Information and Control, 8, 338-353.

3.       Bellman, R. E. & Zadeh, L. A. (1970). Decision-making in a fuzzy environment.  Management Science, 17, B141-B164.

4.       H. J. Zimmermann. (1985) Fuzzy Set Theory and Its Applications. Kluwer-Nijho, Hinghum, Netherlands.

5.       E.A.Silver, R. Peterson, (1985) Decision Systems for Inventory Management and Production Planning, John Wiley & Sons, New York.

6.       H. J. Zimmermann. Fuzzy Set Theory and Its Applications. Kluwer-Nijho®, Hinghum, Netherlands, 1985.

7.       Park, K. S. (1987) Fuzzy-set theoretic interpretation of economic order quantity, IEEE Transactions on Systems, Man and Cybernetics, 17(6), 1082-1084.

8.       J.F. Bard, J.T. Moore. (1990) Production Planning with Variable Demand. Omega, vol. 18, no. 1, pp. 35-42.

9.       Lee, Y. Y., Kramer, B. A. and Hwang, C. L. (1990) Part-period balancing with uncertainty: a fuzzy sets theory approach, International Journal of Production Research, 28(10), 1771-1778.

10.    Yao J.S. and Lee H.M., (1999). Fuzzy inventory with or without backorder for fuzzy order quantity with trapezoidal fuzzy number. Fuzzy Sets and Systems, 105,

11.    Yao J.S. and Lee H.M., (1999). Fuzzy inventory with or without backorder for fuzzy order quantity with trapezoidal fuzzy number. Fuzzy Sets and Systems, 105, 311-337.

12.    W.H. Ip, Y. Li, K. F. Man, K. S. Tang., (2000) Multi-product Planning and Scheduling Using Genetic Algorithm Approach. Computers & Industrial Engineering, vol. 38, no. 3, pp. 283-296.

13.    M. Papadrakakis, N. D. Lagaros. (2003) Soft Computing Methodologies for Structural Optimization. Applied Soft Computing, vol. 3, no. 4, pp. 283-300.

14.    Hsieh, C.H. (2002). Optimization of fuzzy production inventory models. Information Sciences, 146, 29-40.

15.    R. P. Sundarraj, S. Talluri. (2003) A Multi-period Optimization Model for the Procurement of Component-based Enterprise Information Technologies. European Journal of Operational Research, vol. 146, no. 2, pp. 339-351

16.    Y. Yi, D. Wang, (2003). Soft Computing for Scheduling with Batch Setup Times and Earliness-tardiness Penalties on Parallel Machines. Journal of Intelligent Manufacturing, vol. 14, no. 3-4, pp. 311-322.

17.    Chang, H., C., Yao, J., S., and Quyang, L.Y., (2004) “Fuzzy mixture inventory model with variable lead-time based on probabilistic fuzzy set and triangular fuzzy number”, Computer and Mathematical Modeling, 39, 287-304.

18.    Chang, H., C., Yao, J., S., and Quyang, L.,Y., (2006) “Fuzzy mixture inventory model involving fuzzy random variable, lead-time and fuzzy total demand”, European Journal of Operational Research, 69  65-80.

19.    Mahapatra, N. K. & Maiti, M.  (2006). A fuzzy stochastic approach to multi-objective inventory model of deteriorating items with various types of demand and time dependent holding cost, Journal of the Operational Research Society of India, 43 (2), 117-131.

20.    Mahata, G. C. & Goswami, A. (2006). Production lot size model with fuzzy production rate and fuzzy demand rate for deteriorating item nder permissible   delay in payments.  Journal of the Operational Research Society of India, 43 (4), 358-375.

21.    Maiti, M.K., and Maiti, M., (2007) “Two-storage inventory model with lot-size dependent fuzzy lead-time under possibility constraints via genetic algorithm”, European Journal of Operational Research, 179, 352-371.

22.    Dutta, P, Chakraborty, D., and Roy, A.R.,(2007) “Continuous review inventory model in mixed fuzzy and stochastic environment”, Applied Mathematics and Computation, 188, 970-980.

23.    Yung, K. L., W.  Ip and D. Wang (2007). Soft Computing Based Procurement Planning of Time-variable Demand in Manufacturing System. International Journal of Automation and Computing, 04 (1), 80-87.

24.    Singh S.R.  and Singh C.  (2008). Fuzzy Inventory Model for finite rate of Replenishment using Signed Distance Method.  International Transactions in Mathematical Sciences and Computer, 1(1), 27-34.

25.    Halim, K.A., Giri, B.C. & Chaudhuri, K.S. (2008). Fuzzy economic order quantity model for perishable items with stochastic demand, partial backlogging and fuzzy deteriorating rate. International Journal of Operational Research, 3, 77-96.
26.    Goni, A. & Maheswari, S. (2010). Supply chain model for the retailer’s ordering policy under two levels of delay payments in fuzzy environment. Applied Mathematical Sciences, 4, 1155-1164.
27.    Singh, S.R., Malik, A.K., (2010). Optimal ordering policy with linear deterioration, exponential demand and two storage capacity, International Journal of Mathematical Sciences, 9(3-4), 513-528.

28.    Halim, K.A., Giri, B.C. & Chaudhuri, K.S. (2010). Lot sizing in an unreliable manufacturing system with fuzzy demand and repair time.  International Journal of Industrial and Systems Engineering, 5, 485-500.

29.    Singh, S.R. and Malik, A.K. (2011), “An inventory model with stock dependent demand with two storages capacity for non-instantaneous deteriorating items, International Journal of Mathematical Sciences and Applications”,1(3), 1255-1260.

30.    Malik,A.K and Singh,Yashveer (2011). An Inventory Model for Deteriorating Items with Soft Computing Techniques and Variable Demand, International Journal of Soft Computing and Engineering, Vol. 1, No. 5, 317-321.

31.    Malik A.K, Singh, Yashveer and Gupta, S. K. (2012). A Fuzzy based Inventory Model for Deteriorating Items, International Journal of Soft Computing and Engineering, Vol. 2, No. 2, 188-192.

32.    Malik, A.K and Singh, Yashveer (2013). A Fuzzy mixture two warehouses Inventory Model with linear demand, International Journal of Application or Innovation in Engineering and Management Vol. 2, No. 2, 180-186.






Buthainah A., Dayang Radiah A. B., Alnuami W., Ethar Y. Salih, Mohammed. A. Jawad

Paper Title:

Gasoline Diffusivity of Polypropylene-Polycarbonate Composites

Abstract: This manuscript explores the effect of polypropylene-polycarbonate composite (PP-PC) on gasoline absorption. Composites were prepared from PP-PC of different ratios with and without carbon black as a stabilizer. Further, the effect of aging gasoline in the presence of carbon black for a period of two months was studied. A single screw extruder was used to produce these composites and form them into 2mm thick sheets. A hydraulic compressor was then used to produce a 4mm sheet. Absorption test was carried out in gasoline at different immersion times and different blends. The results showed that the polycarbonate performance was improved upon addition of polypropylene. The results of absorption show that it obey Fick's second law of diffusion and after the addition of carbon black the absorption decrease. Further, a polymer composite comprised of PP/PC/carbon black at a ratio of 30/70/1 % (V/V/V %) performs best as suitable composite for the manufacture of fuel tanks.

 diffusion, polymer, absorption, composites


1.       M. Bilewicz, J.C. Viana, L.A. Dobrzański, Development of microstructure affected by in-mould manipulation in polymer composites and nanocomposites, (2008),31(1), 71–76.
2.       K. MANNA, P. P. DE, V. N. S. PENDYALA, S. F. XAVIER,  Processability, compatibility, and effects of solvent aging on mechanical properties of polycarbonate-polypropylene blends. Plastics rubber and composites processing and applications, 26(1), 27–31.

3.       J. C. Seferis , L. Nicolas, the role of the polymeric matrix in the processing and structural     properties of composite materials, Plenum Press, (1983), Technology & Engineering - 684 pages.

4.       L. A. Utracki , polymer alloys and blends, thermodynamics and rheology, (1989),  hanser publishers. Munich Vienna new york.

5.       E. M. (n.d.).Mount, 15 Extrusion Processes, Applied Plastics Engineering Handbook (pp. 227–266), Elsevier. doi:10.1016/B978-1-4377-3514-7.10015-7.

6.       L.A. Dobrzański, M. Król, M. Bilewicz, J.C. Viana, Microstructure and mechanical properties of Polypropylene / Polycarbonate blends, (2008),27(1), 19–22.


8.       A.Jawad, Studying the Effect of Addition of Carbon Black on Rheological Properties of Polypropylene and Polycarbonate, (2013), 31(5), 976–991.

9.       G. S.Springer, & A. Arbor, Moisture Absorption and Desorption of Composite Materials, (1975), 2–20.

10.    F.Officer, C. Kourloufas, R. Base, E.Sale, R. Heslehurst, & E.Wilson, A Review of the Effects of Fluid Absorption / Desorption on the Residual Strength of Carbon Fibre Reinforced Composite Materials, (2011), 1–13.

11.    D.Mpr, NPL REPORT Review of Measurement and Modelling of Permeation and Diffusion in Polymers Bruce Duncan , Jeannie Urquhart Review of Measurement and Modelling of Permeation and Diffusion in Polymers Bruce Duncan , Jeannie Urquhart and Simon Roberts, (2005) (January).

12.    M. S. M.Shayuti, M. Z.Abdullah, & P. S. M. M.Yusoff, Compressive Properties and Morphology of Polypropylene / Polycarbonate Blends, (2011), 12, 303–307.

13.    L. Boccacci, Z. Mcgill, Polymer Composite Gasoline Tanks, (2004).

14.    P.Information, chemical and physical information(1990), 3. 3.1.

15.    S.A. Black, B. Pearls & R. Spectra, Exposure Data. , 1995(April 1984).






Radha Pandey, Arpan Herbert, Annu Pandey

Paper Title:

Soil Decontamination by Soil Washing Technique Using Surfactant

Abstract:  Soil contamination is mainly due to uncontrolled release of petroleum products like underground leakage from storage tanks and above ground oil spills. Hydrocarbons not only affect the quality of soil but also changes its geotechnical properties. This paper aims to investigate the effect of geotechnical properties of soil contaminated with engine oil and evaluate decontamination by soil washing technique using surfactant Brij-35. The geotechnical properties of contaminated soil samples by different proportion of engine oil i.e 2%, 4%, 6% & 8% were determined. Then contaminated samples have been decontaminated by soil washing technique using surfactant and geotechnical properties were determined and compared with contaminated & virgin soil samples. Results shows that Percentage restoration of contaminated soil is same as virgin soil , maximum restoration was found at 4%. Higher percentage of oil lesser will be restoration capacity.

  Brij-35, contamination, decontamination, soil washing.


1.       L. Preslo, M. Miller, W. Suyama, M. McLearn,P. Kostecki, E.Fleischer, Available remedial technologies for petroleum contaminated soils, Petroleum contaminated soils, vol. 1, Lewis Publishers, Chelsea, Michigan, 1989.
2.       P.G. Nicholson, P.R. Tsugawa, Stabilization of diesel contaminated soil with lime and fly ash admixtures, in: Proc.of International Symposium on Environmental Geotechnology,vol. 1, Envo. Pub. Inc., Bethlehem, 1996, pp. 805–816.

3.       A.V. Shroff, D.L. Shah, S.J. Shah, Characteristics of fuel oil contaminated soil and remedial measures – a case study, in:Proc. of Indian Geotechnical Conferences, New Delhi, 1998, pp. 49–51.

4.       J.M.W. Mackenzie, Interaction between oil drops and mineral surfaces, Society of Mining Engineers, AIME, Transaction 247 (1970) 202–208.

5.       Rosen M J, Surfactant and Interfacial Phenomenon; 2nd Ed., Wiley Interscience: New    York, 1989.

6.       Al-Tabbaa A and Walsh S, Geotechnical Properties of a Clay Contaminated with an Organic Chemical, 1st International Congress on Environmental Geotechnics;
Edmonton, Alberta, Canada, 1994, 599-604

7.       Jafvert C T, Van Hoof P L and Heath J K, Water Res., 1994, 28(5), 1009-1017.

8.       Dwarkanath V, Rouse B A, Pope, G A. Kostarelos D, Shotts D and Wade W A, J ContamHydrol., 1999, 38, 465-488.

9.       M. K. Gupta, R. K. Srivastavaand A. K. Singh,Bench Scale Treatability Studies of Contaminated Soil Using Soil Washing Technique,2009.

10.    Al-Tabbaa A and Walsh S, Geotechnical Properties of a Clay Contaminated with an Organic Chemical, 1st International Congress on Environmental Geotechnics;Edmonton, Alberta, Canada, 1994, 599-604.

11.    Pincus, H.J., Meegoda, N.J., and Ratnaweera, P. 1995. Treatmentof oil contaminated soils for identification and classification. Geotechnical Testing Journal, 18(1): 41–49. doi:10.1520/ GTJ10120J.

12.    Singh, S.K. 2005. Characterisation and evaluation of behaviour ofsoil contaminated with petroleum hydrocarbons. Ph.D. thesis, Department of Civil Engineering,Panjab University, Chandigarh,India.

13.    Meegoda N J and Ratanveera P, Geotech Test J., 1995, 18(1), 41-49.

14.    IS: 2720- Part 7 (BIS, 1974), Determination of Water Content- Dry Density RelationUsing Light Compaction.

15.    Wroth , C. P. and Wood, D. M. (1978).”The correlation of Index Properties with Some Basic Engineering Properties of Soils.”CanadianGeotechnical Journal, 15, 137-145.






Aslam P. Memon, M. Aslam Uqaili, Zubair A. Memon, Naresh K. Tanwani

Paper Title:

Time-Frequency and Artificial Neural Network Applications and Analysis for Electrical System Power Quality Disturbances in MATLAB

Abstract:   In recent years due to increasing utilization of nonlinear loads and power electronic equipment, the issue of EPQD (Electrical power quality disturbances) has become the most important apprehension for suppliers and the users of electric power. It is imperative to detect the sources and causes of electrical power quality disturbances in order to improve EPQ problems. Traditional signal processing techniques permit mapping signals from time to frequency domains by decomposing the signals into several frequency components. Due to this transformation time information is lost. EPQ disturbances vary in the wide range of time and frequency, which means these traditional techniques are not suitable for EPQ problems. This problem can be solved with the application of WT (Wavelet transform) and feedforward neural networks as classifier.  Statistical features extraction data is obtained using DWT (discrete wavelet transformation) and MRDA (multiresolution decomposition analysis) utilizing MATLAB/Simulink and Wavelet toolbox. This minimum feature vector data is used for training FFNN as input. Proposed FFNN classifier reduces training. The results obtained show the promising applicability and suitability of WT analysis with neural network for improved and an efficient methodology for automatic diagnosis of EPQ problems.

Detection and classification, discrete wavelet transform, Electrical power quality disturbances, feedforward neural network, wavelet transforms.


1.       M. H. J. Bollen, IEEE Industry Applications Society, IEEE Power Electronics Society, and IEEE Power Engineering Society, “Understanding Power Quality Problems”: Voltage Sags and Interruptions. New York: IEEE Press, 2000.
2.       Roger, C. Dugan., Mark, F. McGranaghan., Santoso, Surya., Beaty, H. Wayne. (2003), Electrical Power Systems Quality, 2nd edition, McGraw-Hill, Book Company,New York, pp. 1-14, 2003.

3.       IEEE Recommended Practice for Monitoring Electric Power Quality,  IEEE Std. 1159-1995.

4.       Solanki Lachman, T., Memon, Aslam P., Mohammad, T.R., and Memon, Zubair, .A. (2010), “Detection Of Power Quality Disturbances Using Wavelet Transform Technique,” International Journal For The Advancement Of Science & Arts, Volume. 1, No. 1, pp. 1-13, Oct. 2010.

5.       Aslam P. Memon., M. Aslam Uqaili, and Zubair Memon “Wavelet Transform and ANNs for Detection and Classification of Power Signal Disturbances”, Mehran University Research Journal of Engineering and Technology, Vol. 31, No. 4, October, 2012.

6.       Aslam P. Memon., M. Aslam Uqaili, and Zubair Memon “Combined Approach of Probabilistic Neural Network and Time-Frequency as the classifier for Power System Transient Problems”, Mehran University Research Journal of Engineering and Technology, Vol 32, No. 4, October 2013.

7.       Bhim Singh,Kamal Al-Haddadf,”A Review of Active Filters for Power Quality Improvement”,IEEE Transactions on Industrial Electronics Vol 46N0.5Oct 1999.

8.       Adly Girgis, Bi Chang and Elham Makram, “A Digital Recursive Measurement for On Line Tracking of Power Systems Harmonics”. IEEE transactions on Power Delivery, vol 6, N° 3 July 1991.

9.       P. Dash, A. Pradham and G. Panda, “Frequency Estimation of Distorted Power System Signals Using Extended Complex Kalman Filter”. IEEE Transactions on Power Delivery, vol 14, N° 3, July 1999.

10.    Flores, R.A, “State of the Art in the Classification of Power Quality Events, An Overview”. Harmonics and Quality of Power, 2002, 10th International Conference on Volume 1, issue, 6-9, pp. 17-20, Oct. 2002.

11.    Aslam P. Memon, M. Aslam Uqaili, Zubair A. Memon and Asif Ali Akhund, “Time-Frequency Analysis Techniques for Detection of Power System Transient Disturbances,” International Journal of Emerging Trends in Electrical and Electronics (IJETEE ISSN: 2320-9569), IRET publication, Vol. 9, pp. 39-44, November 2013.

12.    Primer, “Introduction to wavelets and wavelet transforms” ( Prentice Hall, 1998)

13.    Daubechies I. “orthogonal bases of compactly supported wavelets”, Communications in Pure Applied Math, vol. 41, pp. 909-996, 1988.

14.    Surya Santoso, Edward J. Powers, W. Mack Grady, Peter Hofmann, “Power Quality Assessment via Wavelet Transform Analysis”, IEEE transactions on Power Delivery, Vol. 11, No.2, April 1996.

15.    S. Santoso, J. P. Edward, W. M. Grady, and A. C. Parsons, “Power Quality Disturbance Waveform Recognition Using Wavelet-Based Neural Classifier—Part 1: Theoretical foundation,” IEEE Trans. Power Delivery, Vol.15, pp. 222–228, Feb. 2000.

16.    B. Boashah, Time-Frequency Signal Analysis and Processing- A Comprehensive Reference (Elsevier, London, 2003).

17.    P. Kailasapathi, D. Sivakumar, “Methods to Analyze Power Quality Disturbances”, European Journal of scientific Research, Vol. 47, No. 1, pp. 06-16, 2010.

18.    F. Sharma, A. K. Sharma, Ajay Sharma and Nirmala Sharma, “Recent Power Quality Techniques, A comparative Study”, Canadian Journal of Electrical & Electronics Engineering, Vol. 01, No. 06, pp. 141-148, Oct 2010.

19.    Math H. J. Bollen, Irene Yu-Hua Gu, (2006), Signal Processing Of Power Quality Disturbances, 2nd edition, IEEE Press Series on Power Engineering, Mohamed E. El-Hawary, Series Editor, A John Wiley & Sons, Inc., Publication, May 2006.

20.    G. Viskadouros, G. stavrakakis and E. Ellinakis, “Power Quality Event Recognition and Classification Using a Wavelet Based Neural Network”, Int. Journal of sustainable water and environment Systems, vol. 03, No. 01, pp. 45-52, September 2011.                              

21.    Santoso S., Powers E.J., Grady W.M., Parsons A.C., “Power Quality Disturbance Waveform Recognition Using Wavelet Based Neural Classifier- Part 2: Application”, IEEE Trans. Power Delivery, Volume 15, No. 1, pp. 229–235, 2000.

22.    Aslam P. Memon., M. Aslam Uqaili, and Zubair Memon, “Suitable Feed forward Neural Network Automatic Voltage Regulator for Excitation Control System”, published Jan-Feb 2014, in Universal Journal of Electrical and Electronic Engineering (UJEEE), Horizon Research Publishing, USA, http://www.hrpub.org.

23.    Memon, Aslam P., Uqaili, M. Aslam, and Memon, Zubair A., “Design of Feedforward NNAVR for Enhancement of Power System Stability Using Matlab/Simulink,” Mehran University Research Journal of Engineering & Technology, Volume. 31, No. 3, pp. 1-8, July, 2012.

24.    Borras, D., Castilla, M., Moreno, N., & Montano, J.C. (2001), “Wavelet and Neural Structure: A New Tool for Diagnostic of Power System Disturbances,” IEEE on Industry Applications, Volume. 37, No. 2, pp. 184-190, Jan. 2001.

25.    Zhang, G.P., (2000), “.Neural Networks for Classification: A Survey,” IEEE Trans. on Systems, Man, and Cybernetics—Part c: Applications and Reviews,” Volume. 30, No. 4, pp. 451-462, Nov. 2000.

26.    Gargoom, A.M., Ertugrul, N., & Soong, W.L. “Automatic Classification And Characterization Of

27.    Power Quality Events,” IEEE Trans. on Power Delivery, Volume 23, No. 2, pp. 2417-2425, Oct. 2008.

28.    Aslam P. Memon., M. Aslam Uqaili, and Zubair Memon, “Suitable Feed forward Neural Network Automatic Voltage Regulator for Excitation Control System”, published Jan-Feb 2014, in Universal Journal of Electrical and Electronic Engineering (UJEEE), Horizon Research Publishing, USA, http://www.hrpub.org.

29.    Aslam P. Memon, A. Sattar Memon, Asif Ali Akhund and Riaz H. Memon, “Multilayer Perceptrons Neural Network Automatic Voltage Regulator With Applicability And Improvement In Power System Transient Stability,” International Journal of Emerging Trends in Electrical and Electronics (IJETEE ISSN: 2320-9569), IRET publication, Vol. 9, Issue 1, pp. 30-38, November 2013.