International Journal of Engineering and Advanced Technology(TM)
Exploring Innovation| ISSN:2249-8958(Online)| Reg. No.:61902/BPL/CE/2011| Published By BEIESP| Impact Factor: 5.02
Home
Articles
Conferences
Editors
Scope
AUTHOR GUIDELINES
Publication Fee
Privacy Policy
Associated Journals
Frequently Asked Questions
Contact Us
Volume-6 Issue-1 Published on October 30, 2016
04
Volume-6 Issue-1 Published on October 30, 2016

 Download Abstract Book

S. No

Volume-6 Issue-1, October 2016, ISSN:  2249-8958 (Online)
Published By: Blue Eyes Intelligence Engineering & Sciences Publication Pvt. Ltd. 

Page No.

1.

Authors:

Joseph Zacharias, Jayakrishnan S B, Vijayakumar Narayanan

Paper Title:

82 GHz Millimeter-Wave Transmission Over OFDM ROF System

Abstract: Orthogonal Frequency Division Multiplexing (OFDM) based signal transmission over Millimeter-Wave Radio-over-Fiber (mm-Wave RoF) systems is proposed.  For that an external modulator and an optical interleaver are used to generate dual octupling-frequency optical millimeter waves. Simultaneously. The frequency of local oscillator signal is reduced largely due to frequency octupling.  OFDM signal is used as the downlink data for transmission. Most of the advanced systems are using OFDM based signal such as LTE 4G or WiMAX network. So a system that uses RoF technology to transmit OFDM signal by mm-Wave will be effective. In this proposal, the advanced technologies are combined in order to get an effective model to transmit data at higher speed with a reasonable price.

Keywords:
 Orthogonal frequency division multiplexing, Radio over fiber (RoF), Millimeter-wave, wavelegth reuse.


References:

1.       Tam Hoang Thi and Mitsuji Matsumoto, “Transmission Analysis of OFDM Millimeter-Wave Radio-over-Fiber System ”, Fifth International Conference on Ubiquitous and Future Networks (ICUFN), pp. 800- 804, July 2013
2.       J. Armstrong, “OFDM for optical communications ”, J. Lightw. Technol., vol. 27, no. 3, pp. 189204, Feb. 2009.

3.       Guangming Cheng, Banghong Guo, Songhao Liu, Weijin Fang, “A novel full-duplex radio-over-fiber system based on dual octupling-frequency for 82 GHz W-band radio frequency and wavelength reuse for uplink connection ”.

4.       Jianjun Yu, Zhensheng Jia, Ting Wang, Gee-Kung Chang “A Novel Radio- Over-Fiber configuration using optical phase modulator to generate an optical mm-Wave and centralized lightwave for uplink connection ”, IEEE Photonics Technology Letters, vol. 19, no. 3, pp. 140 - 142, February 2007

5.       SPP “Planning of the 7176 GHz and 8186 GHz bands for millimeter wave highcapacity fixed link technology, ”, Australian Communication and Media Authority, 2006

6.       Colombo, M. Cirigliano, “Next-generation access network: a wireless networkusing E-band radio frequency (7186 GHz) to provide wideband connectivity, ”, Bell Labs Tech. J. , vol. 16, no. 1, pp. 187 - 206, 2011.

7.       Zizheng Cao, Jianjun Yu,Minmin Xia, Qi Tang, Yang Gao,  Wenpei Wang, and Lin Chen, “Reduction of Intersubcarrier Interference and Frequency-Selective Fading in OFDM-RoF Systems”, Journal of lightwave technology, vol. 28, no. 16, August 15, 2010

8.       R. Karthikeyan and Dr. S. Prakasam, “OFDM Signal  Improvement Using Radio over Fiber for Wireless System ”, International Journal of Computer Networks and Wireless Communications (IJCNWC), ISSN: 2250-3501 vol. 3, no. 3, June 2013.

9.       Jianjun Yu, Zhensheng Jia,Ting Wang, and Gee Kung Chang, “Centralized Lightwave Radio-Over-Fiber System With Photonic Frequency Quadrupling for High-Frequency Millimeter-Wave Generation ”,  IEEE photonics technology letters, vol. 19, no. 19, Oct 2007

10.    Wake,  C.  R.  Lima  and  P.  A.  Davies,  “Transmission  of  60-GHz Signals over 100 km of Optical Fiber Using a dual mode Semiconductor Laser Source ”, IEEE photonics technology letters, vol 8, no 4, April 1996

11.    C. van den Bos , M. H. L. Kouwenhoven and W. A. Serdijn, “The influence of non-linear distortion on OFDM bit error rate ”, IEEE International Conference on Communications, vol. 2, pp. 1125 - 1129, June 2000

12.    Lin Chen, Hong Wen, and Shuangchun Wen, “A Radio-Over-Fiber system with a novel scheme for Millimeter-Wave generation and wavelength reuse for up-link connection ”, IEEE Photonics Technology Letters, vol. 18, no. 19, pp. 2056 - 2058, October 2006

13.    G.-K. Chang, J. Yu, Z. Jia, J. Yu “Novel optical-wireless access network architecture for simultaneously providing broadband wireless and wired services ”, Proc.OFC, Paper OFM1D, Anaheim, USA, March 2006.

14.    Yoon-Khang Wong, S.M. Idrus, and I.A. Ghani, “Performance Analysis of the OFDM Scheme for Wireless over Fiber Communication Link,”, International Journal of Computer Theory and Engineering , vol. 4, no. 5, October 2012.

15.    Ajay Kumar Vyas, Dr. Navneet Agrawal, “Radio over Fiber: Future Technology of Communication, International Journal of Emerging Trends and Technology in Computer Science (IJETTCS) , vol. 1, no. 2, August 2012.


1-4

www.blueeyesintelligence.org/attachments/File/fee/2checkout_download.html

2.

Authors:

Anila V M, Seena Thomas

Paper Title:

Detection of Diabetic Retinopathy from Fundus Images through Local Binary Patterns and Artificial Neural Network

Abstract:  Diabetic retinopathy (DR) is one of the most frequent cause of blindness and vision loss in diabetic patients. The diabetic retinopathy is detected earlier, the better the chance that it can be effectively treated and further vision loss prevented. This condition increases the importance of automated detection of the disease. This work focuses on distinguishing between diabetic retinopathy (DR) and normal fundus images by analyzing the texture of the retina background. Local Binary Patterns (LBP) are used as texture descriptors. They are the powerful grey-scale texture descriptors that is commonly used because of its computation simplicity. Local Binary Pattern is based on looking at the local variations around each pixel, and assigning labels to different local patterns and the labels are evaluated and used in the classification stage. Probabilistic Neural Network (PNN) is the classifier that is used for the classification of abnormal and healthy images. This work suggest that LBP is a robust texture descriptor for retinal images and the proposed method analyzing the retina background directly and avoiding difficult lesion segmentation such as exudates, microaneurysms etc. can be useful for diagnostic aid.

Keywords:
  Diabetic Retinopathy, Local Binary Patterns, Probabilistic Neural Network, Fundus Images.


References:

1.       Sandra Morales, Kjersti Engan, Valery Naranjo and Adri´an ColomerT. “Retinal Disease Screening through
2.       Local Binary Patterns” IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS, VOL. 00, NO. 00, 2015

3.       Frdric Zana and Jean-Claude Klein ,Segmentation of Vessel-Like Patterns Using Mathematical Morphology and Curvature Evaluation IEEE Transactions On Image Processing, Vol. 10, No.7, July 2001

4.       Keith A. Goatman, Alan D. Fleming, Sam Philip, Graeme J.Williams, John A. Olson and Peter F. Sharp, Detection of New Vessels on the Optic Disc Using Retinal Photographs, IEEE Transactions on Medical Imaging, Vol. 30, No. 4, pp. 972 979, 2011.

5.       E. Ricci and R. Perfetti, Retinal blood vessel segmentation using line operators and support vector classification, IEEE Trans. Med. Imag., vol. 26, no. 10, pp. 13571365, Oct. 2007

6.       E. Ricci and R. Perfetti, Retinal blood vessel segmentation using line operators and support vector classification, IEEE Trans. Med. Imag., vol. 26, no. 10, pp. 3571365, Oct. 2007

7.       T. Walter, J.C. Klein, P. Massin, and A. Erginay, A contribution of image processing to the diagnosis of diabetic retinopathy-detection of exudates in colour fundus images of the human retina , IEEE Transactions on Medical Imaging , Vol. 22(10),pp. 1236 1243, 2002.

8.       Jo£o V. B. Soares, Jorge J. G. Leandro, Roberto M. Cesar Jr.,Herbert F. Jelinek, and Michael J. Cree, Retinal Vessel Segmentation Using the 2-D Gabor Wavelet and supervised Classification IEEE TRANSACTIONS ON MEDICALIMAGING, VOL. 25, NO. 9, SEPTEMBER 2006

9.       World Health Organization (WHO), Universal eye health: a global action plan 2014-2019, 2013.

10.    T. Ojala, M. Pietikinen, and T. Menp, A generalized local binary pattern operator for multiresolution gray scale and rotation invariant texture classification, in Advances in Pattern Recognition, 2nd International Conference on, 2001, pp. 397406.

11.    T. Ojala, M. Pietikainen, and T. Maenpaa, Multiresolution gray-scale and rotation invariant texture classification with local binary patterns, Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol. 24, no. 7, pp. 971987, 2002.

12.    M. Heikkil, M. Pietikinen, and C. Schmid, Description of interest regions with local binary patterns, Pattern Recognition, vol. 42, no. 3, pp. 425 436, 2009.

13.    Z. Yang and H. Ai, Demographic classification with local binary patterns, in Advances in Biometrics, ser. Lecture Notes in Computer Science, S.-W. Lee and S. Li, Eds., 2007, vol. 4642, pp. 464473.

14.    L. Nanni, A. Lumini, and S. Brahnam, Local binary patterns variants as texture descriptors for medical image analysis, Artificial Intelligence in Medicine, vol. 49, no. 2, pp. 117 125, 2010.

15.    M. Mookiah, U. R. Acharya, R. J. Martis, C. K. Chua, C. Lim, E. Ng, and A. Laude, Evolutionary algorithm based classifier parameter tuning for automatic diabetic retinopathy grading: A hybrid feature extraction approach, Knowledge-Based Systems, vol. 39, no. 0, pp. 9 22, 2013.

16.    M. M. R. Krishnan and A. Laude, An integrated diabetic retinopathy index for the diagnosis of retinopathy using digital fundus image features, Journal of Medical Imaging and Health Informatics, vol. 3, no. 2, pp. 306313, 2013.

6-9

www.blueeyesintelligence.org/attachments/File/fee/2checkout_download.html






























































































3.

Authors:

Wael Zaghloul ElSayad, Hussein Mahmoud Hussein

Paper Title:

Reducing the Negative Effects of Dust Storms using Solar Energy to Recycle Plastic Waste

Abstract:  A sandstorm is characterized as one that whips up extraordinary loads of sand into the air, forming a dense cloud above the ground in the process. While most of the sand will rise higher than 50 cm, some sand particles can even ascend to the height of 2 meters. According to Wikipedia, the average diameter of the particles carried by such dust storm winds will vary between 0.15 and 0.30 mm. Wind speeds such during sandstorms have been recorded at up to 16 km per hour and more, while most storms continue to blow for between three hours to five hours. The dust unleashed from sandstorms continues to pose severe environmental concerns in certain Arab and Middle East countries, causing great hardships to its citizens in the form of lost income and widespread infrastructure damage. Perhaps more importantly, when it comes to measuring the effects on people's health, it has been well documented that sandstorms have, in many cases, led to both the death and destruction of livestock, crops and even human beings. Based on the above factors, scientific researchers continue to work tirelessly to confront sandstorms in an effort to both prevent and alleviate this dangerous natural phenomenon. This particular study will look to establish a low-cost system of erecting plastic trees built from solar energy and recycled plastic waste in order to reduce the risks of sandstorms.

Keywords:
 Middle East countries, recycled plastic, sandstorms, solar energy.


References:

1.    Sultan Ayoub Meo, Mohammad Fahad A Al-Kheraiji, Ziyad Fahad AlFaraj, Nasser abdulaziz Alwehaibi, and Ahmad Adnan Aldereihim. “ Respiratory and general health complaints in subjects exposed to sandstorm at Riyadh, Saudi Arabia”. (2013, April). Pakistan Journal of Medical Sciences. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3809255/
2.    Miller, Ron and Tegan, Ina. “Desert Dust, Dust Storms and Climate”. National Aeronautics and Space Administration Goddard Institute for Space Studies, (1997, April). http://www.giss.nasa.gov/research/briefs/miller_01/

3.    Buttiker, N & Krupp (Eds). Climatologically features of Saudi Arabia, in Fauna of Saudi Arabia, a, No.6, Meteorological Environmental Protection Administration, Saudi Arabia

4.    Ayoub Meyo, Sultan, Fahad A Al-Kheraiji, Mohammed et al. 'Respiratory and general     health complaints in subjects exposed to sandstorm at Riyadh, Saudi Arabia.' Pakistan Journal of Medical Sciences, April 29, 2013, 642–646.

5.    Regional Master Plan for the prevention and control of Dust and Sandstorms in Northeast Asia. Volume No. 1. March 2005.

6.    Deserts and Desertification Seminar. (2006). “Danger of dust storms leads to the transfer of germs that cause for «anthrax»” http://archive.aawsat.com/details.asp

7.    Al Turki, Ali bin Mohammed, Al Maghrbi, Salem al-Azab and Ghazi Algamd, Abdul Aziz. "Properties and the amount of soil losing by wind drift in the Riyadh region."

8.    "High-density polyethylene." Wikipedia. July 6, 2016. https://en.wikipedia.org/wiki/High- density polyethylene.

10-13

www.blueeyesintelligence.org/attachments/File/fee/2checkout_download.html


































4.

Authors:

Safia Yasmeen, G. Manoj Someswar

Paper Title:

Design & Development of a Suitable Model to Validate New Estimation Approaches for Effective Performance

Abstract: As COCOMO is a non-proprietary model, its details are available in the public domain, encouraging researchers and practitioners in the software engineering community to independently evaluate the model. There have been many extensions independently reported where machine learning techniques are used to generate effort models from the original COCOMO model. In our research work, we proposed a calibration method by transforming the model equation into a linear form and estimating the model parameters using standard linear regression techniques. This calibration method has been adopted by the COCOMO development team in their calibration work.  COCOMO has also been a model used to validate new estimation approaches such as fuzzy logic and neural networks. The COCOMO development team continues to calibrate and extend the model using different calibration approaches on more augmented data sets and our research work is mainly based upon these approaches wherein we have evolved newer and better approaches over the existing approaches and gave a realistic outlook to the very purpose of achieving the best performance.

Keywords:
Calibration Technique, Maintenance Function Point (MFP), Maintenance Impact Ratio (MIR), Developed for Reusability (RUSE), Required Development Schedule (SCED), Required Software Reliability (RELY)


References:

1.       Abran A., Silva I., Primera L. (2002), "Field studies using functional size measurement in building estimation models for software maintenance", Journal of Software Maintenance and Evolution, Vol 14, part 1, pp. 31-64
2.       Albrecht A.J. (1979), "Measuring Application Development Productivity," Proc. IBM Applications Development Symp., SHARE-Guide, pp. 83-92.

3.       Albrecht A.J. and Gaffney J. E. (1983) "Software Function, Source Lines of Code, and Development Effort Prediction: A Software Science Validation," IEEE Transactions on Software Engineering, vol. SE-9, no. 6, November

4.       Banker R., Kauffman R., and Kumar R. (1994), "An Empirical Test of Object-Based Output Measurement Metrics in a Computer Aided Software Engineering (CASE) Environment," Journal of Management Information System.

5.       Basili V.R., (1990) "Viewing Maintenance as Reuse-Oriented Software Development," IEEE Software, vol. 7, no. 1, pp. 19-25, Jan.

6.       Basili V.R., Briand L., Condon S., Kim Y.M., Melo W.L., Valett J.D. (1996), "Understanding and predicting the process of software maintenance releases," Proceedings of International Conference on Software Engineering, Berlin, Germany, pp. 464-474.

7.       Basili V.R., Condon S.E., Emam K.E., Hendrick R.B., Melo W. (1997) "Characterizing and Modeling the Cost of Rework in a Library of Reusable Software Components". Proceedings of the 19th International Conference on Software Engineering, pp.282-291

8.       Boehm B.W. (1981), "Software Engineering Economics", Prentice-Hall, Englewood Cliffs, NJ, 1981.

9.       Boehm B.W. (1988), "Understanding and Controlling Software Costs", IEEE Transactions on Software Engineering.

10.    Boehm B.W., Royce W. (1989), "Ada CCCOMO and Ada Process Model," Proc. Fifth COCOMO User's Group Meeting, Nov.

11.    Boehm B.W., Clark B., Horowitz E., Westland C, Madachy R., Selby R. (1995), "Cost models for future software life cycle processes: COCOMO 2.0, Annals of Software Engineering 1, Dec, pp. 57-94.

12.    Boehm B.W. (1999), "Managing Software Productivity and Reuse," Computer 32, Sept., pp.111-113

13.    Boehm B.W., Abts C, Chulani S. (2000), "Software development cost estimation approaches: A survey," Annals of Software Engineering 10, pp. 177-205.

14.    Boehm B.W., Horowitz E., Madachy R, Reifer D., Clark B.K., Steece B., Brown A.W., Chulani S., and Abts C. (2000), "Software Cost Estimation with COCOMO II," Prentice Hall.

15.    Boehm B.W., Valerdi R. (2008), "Achievements and Challenges in Cocomo-Based Software Resource Estimation," IEEE Software, pp. 74-83, September/October

16.    Bradley E., Gong G. (1983), "A leisurely look at the bootstrap, the jack-knife and cross-validation", American Statistician 37 (1), pp.836-848.

17.    Briand L.C., Basili V., Thomas W.M. (1992), "A pattern recognition approach for software engineering analysis", IEEE Transactions on Software Engineering 18 (11)931
942.

18.    Briand L.C. & Basili V.R. (1992) "A Classification Procedure for an Effective Management of Changes during the Software Maintenance Process", Proc. ICSM '92, Orlando, FL.

19.    Briand L.C, El-Emam K., Maxwell K., Surmann D., and Wieczorek I., "An Assessment and Comparison of Common Cost Estimation Models," Proc. 21st International Cor ference on Software Engineering, pp. 313-322, 1999.

14-21

www.blueeyesintelligence.org/attachments/File/fee/2checkout_download.html

5.

Authors:

M Veera Chandra Kumar, K. Satyanarayana, M.N.V.V. Brahmam

Paper Title:

An SMC based RZVDPWM Algorithm of Vector Controlled Induction Motor Drive for Better Speed Response with Reduced Acoustical Noise

Abstract:  In this paper, an sliding mode controller (SMC) based Random Zero vector Distribution PWM (RZVDPWM) algorithm of vector controlled induction motor drive for better speed response with reduced Acoustical Noise is analyzed. In order to mitigate the difficulty faced in the conventional Space Vector PWM (SVPWM) approach, the proposed RZVDPWM algorithm is created by taking the concept of Simplified PWM sequence. This algorithm is developed by using the concept of random number generation technique. Simulation studies are carried out to validate proposed RZVDPWM algorithm, the results obtained are presented and compared. The simulation results shows that the overall performance of SMC based RZVDPWM drive is better when compared to SVPWM technique under different conditions of operation.

Keywords:
 Simplified PWM sequence, SVPWM, RZVDPWM, Vector control, SMC


References:

1.    F. Blaschke “The principle of field orientation as applied to the new transvector closed loop control system for rotating-field machines," Siemens Review, 1972, pp 217-220.
2.    Heinz Willi Vander Broeck, Hnas-Christoph Skudelny and Georg Viktor Stanke, “Analysis and realization of a pulse width modulator based on voltage space vectors” IEEE Trans. Ind. Applicat., vol. 24, no. 1, Jan/Feb 1988, pp. 142-150.

3.    Michael M.Bech, Frede Blaabjerg, and John K. Pedersen, “Random modulation techniques with fixed switching frequency for three-phase power converters” IEEE Trans. Power Electron., vol.15, no.4, pp. 753-761, Jul, 2000.

4.    S-H Na, Y-G Jung, Y-C. Lim, and S-H. Yang, “Reduction of audible switching noise in induction motor drives using random position space vector PWM” IEE. Proc. Electr. Power Appl., vol.149, no.3, pp. 195-200, May, 2002.

5.    Andzrej M. trzynadlowski, Konstantin, Yuin Li, and Ling Qin, “A novel random PWM technique with low computational overhead and constant sampling frequency for high-volume, low-cost applications” IEEE Trans. Power Electron., vol. 20, no.1, pp.116-122, Jan, 2005.

6.    Dae-Woong Chung, Joohn-Sheok Kim and Seung-Ki Sul, “Unified voltage modulation technique for real-time three-phase power conversion” IEEE Trans. Ind. Applicat., vol. 34, no. 2, Mar/Apr 1998, pp. 374-380.

7.    T. Brahmananda Reddy, J. Amarnath and D. Subbarayudu, “Improvement of DTC performance by using hybrid space vector Pulse width modulation algorithm” International Review of Electrical Engineering, Vol.4, no.2, pp. 593-600, Jul-Aug, 2007.

8.    K. Satyanarayana1, J. Amarnath2, and A. Kailasa Rao1, “Hybrid PWM Algorithm with Low Computational Overhead for Induction Motor Drives for Reduced Current Ripple” ICGST-ACSE journal, vol.10, isuue.1, pp. 29-37, Dec, 2010.

9.    N Subba rao, K. Satyanarayana, K.Siva Prasad “Performance Improvement of Sliding Mode Controller based Indirect Vector Controlled Induction Motor Drives” International Journal of Engineering and Advanced Research Technology (IJEART)  ISSN: 2454-9290, Volume-2, Issue-1, January 2016.


22-28

www.blueeyesintelligence.org/attachments/File/fee/2checkout_download.html

6.

Authors:

Thamizharasi A, Jayasudha J.S

Paper Title:

Face Recognition of Enhanced Contrast Limited Adaptive Histogram Equalization using Feature Extraction Method

Abstract:  Face recognition is most widely useful for social networks and surveillance applications. Face recognition is complex if there are variations in light. The proposed work is to develop an illumination invariant face recognition system by enhancing Contrast Limited Adaptive Histogram Equalization (CLAHE). The face recognition of Enhanced CLAHE is done using feature extraction method. The features extracted are DWT statistical features, moments, texture, regional features, shape ratios, Fourier descriptors and facial features from Enhanced CLAHE images. These features are combined to create a feature vector. The feature vector is classified using Support Vector Machine (SVM) classifier and Multilayer Perceptron (MLP) neural network. The efficiency of feature vector is tested with three public face databases AR, Yale and ORL. The testing result proves that feature vector has high recognition accuracy rate.

Keywords:
  face recognition, CLAHE, Enhanced CLAHE, feature vector, illumination invariant, SVM and MLP classifier.


References:

1.       R. Chellappa, C.L. Wilson, and S. Sirohey, “Human and machine recognition of faces: A survey,” Proceedings of. IEEE, vol. 83, pp. 705–740, 1995.
2.       Franco Scarselli and Ah Chung Tsoi, “Universal Approximation Using Feed forward Neural Networks: A Survey of Some Existing   Methods, and Some New Results”, Neural Networks, Vol 11, No 1, pp15-37, 1998

3.       Thamizharasi  and J.S. Jayasudha, “An Illumination invariant face recognition by enhanced contrast limited adaptive histogram equalization”, ICTACT Journal on Image and Video Processing, May 2016, Vol. 06, Issue: 04, ISSN: 0976-9102

4.       Rafael C.Gonzalez and Richard E.Woods, "Digital Image Processing", Addison-Weseky, 1993.

5.       Taiping Zhang, Yuan Yan Tang, Bin Fang and Xiaoyu Liu, "Face Recognition Under Varying Illumination using Gradientfaces," IEEE Transactions on Image Processing, Vol. 18, No. 11, pp. 2599-2606, 2009.

6.       H.Wang, S.Z.Li and Y.Wang, "Face Recognition under varying lighting conditions using self-quotient image," in Proceedings of IEEE International Conferencec on Automatic Face and Gesture Recognition, pp. 819-824, 2004

7.       Zhang Y., Tian J., He X. and Yang X., "MQI Based Face Recognition under Uneven Illumination," Advances in Biometircs, Vol. 4642, pp. 290-298, 2007

8.       D.J.Jobson, Z.Rahman and G.A.Woodell , "A multiscale retinex for bridging the gap between color images and the human observation of scenes," IEEE Transactions on Image Processing, Vol. 6, pp. 965-976, 1997

9.       D.J.Jobson, Z.Rahman and G.A.Woodell , "Properties and Performance of a Center/Surround Retinex," IEEE Transactions on Image Processing, Vol. 6, No. 3, pp. 451-462, 1997.

10.    T.Chen, W.Yin, X.S.Zhou, D.Comaniciu and T.S.Huang, "Total Variation Models for variable lighting face recognition," IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 28, pp. 1519-1524, 2006.

11.    X.Tan and B.Triggs , "Enhanced local texture feature sets for face recognition under difficult lighting conditions," IEEE Transactions on Image Processing, Vol. 19, pp. 1635-1650, 2010

12.    A.S.Georghiades , P.N.Belhumeur and D.J.Kriegman , "From few to many: Illumination cone models for face recognition under variable lighting and pose," IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 23, No. 6, pp. 643-660, 2001

13.    Dao Qing Dai and Hong Yan, Wavelets and Face Recognition.: ISBN 978-3-902613-03-5, I-Tech, Austria, pp. 558, 2007

14.    X.Xie, W.Zheng, J.Lai, P.C.Yuen and C.Suen , "Normalization of face illumination based on large and small-scale features," IEEE Transactions on Image Processing, Vol. 20, pp. 1807-1821, 2011.

15.    Zhenhua Chai, Heydi Mendez Vazquez, Ran He and Tieniu Tan, "Gabor Ordinal Measures for Face Recognition," IEEE Transactions on Information Forensics and Security, Vol. 9, No. 1, 2014.

16.    Jiwen Lu and Yap-Peng Tan, "Cost-Sensitive Subspace Analysis and Extensions for Face Recognition," IEEE Transactions on Information Forensics and Security, Vol. 8, No. 3, pp. 510-519, 2013

17.    Weiping Chen and Yongsheng Gao, "Face Recognition using Ensemble String Matching," IEEE Transactions on Image Processing, Vol. 22, No. 12, pp. 4798-4808, 2013.

18.    Jiwen Lu, Venice Erin Liong, Gang Wang  and Pierre Moulin, "Joint Feature Learning for Face Recognition," IEEE Transactions on Information Forensics and Security, Vol. 10, No. 7, pp. 1371-1383, 2015

19.    Luciano da Fontoura Costa and Roberto Marcondes Cesar Jr., "Shape Classification and Analysis:Theory and Practice", 2nd Edition, Pages. 674, 2009

20.    Christican Walck , "Hand-book on Statistical Distributions for experimentalists", Internal Report, University of Stockholm, Pages.190, 1996

21.    Shailendrakumar M.Mukane , Dattatraya S.Bormane , and Sachine R.Gengaje , "Wavelet and Co-occurence Matrix based Rotation Invariant Features for Texture Image Retrieval Using Fuzzy Logic," International Journal of Computer Applications, ISSN 0975-8887, Vol. 24, No. 7, 2011

22.    Dengsheng Zhang and Guojun Lu , "A Comparative Study on Shape Retrieval Using Fourier Descriptors with Different Shape Signatures," Journal of Visual Communication and Image Representation, Vol.14, No. 1, pp. 39-57, 2003

23.    Mark Nixon and Alberto Aguado, "Feature Extraction and Image Processing for Computer Vision", Third Edition,  Academic Press, Pages. 350, 2012

24.    V.Vapnik , "The Nature of Statistical Learning Theory", Springer-Verlag, Newyork, Pages.39, 1995

25.    Franco Scarselli and Ah Chung Tsoi , "Universal Approximation Using Feed Forward Neural Networks: A Survey of Some Existing Methods and Some New Results," Neural Networks, Vol. 11, No. 1, pp. 15-37, 1998

26.    A.M.Martinez and R.Benavente, "The AR Face Database," 24, CVC Technical Report, 1998.

27.    (Checked on 10th September 2016) ORL Face database. [Online]. http://www.cl.cam.ac.uk/research/dtg/attarchive/facedatabase.html

28.    P.N.Belhumeur, J.P.Hespanha and D.J Kriegman, "Eigenfaces vs Fisherfaces: Recognition using class specific linear projection," IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 19, No. 7, 1997.

29.    Rafael C.Gonzalez , Richard E.Woods  and Steven L.Eddins, "Digital Image processing with MATLAB", 2nd Edition, 2009

30.    (Checked on 10th September, 2016) Weka Software. [Online]. http://www.cs.waikato.ac.nz/ml/weka/

31.    Amany Farag and Randa Atta , "Illumination Invariant Face Recognition Using the Statistical Features of BDIP and Wavelet Transform," International Journal of Machine Learning and Computing, Vol. 2, No. 1, 2012

32.    Kai Li, Zhen Liu and Peng Tang , "On Linear Discriminant Analysis and its Variants in Face Recognition," International Journal of Artificial Intelligence and Mechatronics, Vol. 4, No. 1, 2015.

33.    Jamal Husain Shah , Muhammad Sharif, Mudassar Raza and Aisha Azeem, "A Survey: Linear and Nonlinear PCA Based Face Recognition Techniques," The International Arab Journal of Information Technology, Vol. 10, No. 6, 2013.

34.    Liu N., Wang H. and Yau W., "Face Recognition with Weighted Kernel Principal Component Analysis," in Proceedings of the nineth International Conference on Control, Automation, Roboticcs and Vision, pp. 1-5, 2006.

35.    Gautham Sitaram Yajia, Sankhadeep Sarkara, K Manikantana  and S Ramachandran, "DWT feature extraction based face recognition using intensity mapped unsharp masking and laplacian of Gaussian filtering with scalar multiplier," in Second International Conference on Communication, Computing and Security (ICCCS-2012), Procedia Technology, Vol.6, pp. 475-484, 2012

36.    Zahraddeen Sufyanu, Fatma S.Mohamad, Abdulganiyu A.Yusuf and Mustafa B.Mamat, "Enhanced Face Recognition Using Discrete Cosine Transform," Engineering Letters, Vol. 24, No. 1, pp. 52-61, 2016

37.    M.H Yang, "Kernel Eigenfaces vs Kernel Fisherfaces: Face Recognition using Kernel Methods," in Proceedings of fifth IEEE International Conference on Automatic Face and Gesture Recognition (RGR'02), pp. 215-220, 2002


29-34

www.blueeyesintelligence.org/attachments/File/fee/2checkout_download.html

7.

Authors:

K. Murali Krishna, S. Ashok Reddy, K. Siva Shankar

Paper Title:

MPPT for Standalone PV System under Partially Shaded Condition using Genetic Algorithm

Abstract:   sun oriented vitality is spotless, renewable and its decentralized character is suitable well at the scattered State of the zones with low thickness of populace. The expense of Electricity from the sun oriented cluster framework is more costly than the power from the utility network. In this way, it is important to work the PV framework at most extreme proficiency by following greatest force point at any natural condition. In this work, the Genetic algorithm is utilized to control the operation of the PV exhibit keeping in mind the end goal to separate the most extreme force. The outcomes acquired are looked at and talked about.

Keywords:
PV System, Maximum Power Point Tracking (MPPT), Genetic algorithm, P&O algorithm.


References:

1.       Bidyadhar Subudhi and Raseswari Pradhan, “A Comparative Study on Maximum Power Point Tracking Techniques for Photovoltaic Power Systems” IEEE Transactions on Sustainable Energy, 2013, Vol. 4, No. 1
2.       Moacyr Aureliano Gomes de Brito, Luigi Galotto, Jr., Leonardo Poltronieri Sampaio, Guilherme de Azevedo e Melo, and Carlos Alberto Canesin, Senior Member, “Evaluation of the Main MPPT Techniques for Photovoltaic Applications” IEEE Transactions on Industrial Electronics, 2013, Vol. 60, No. 3.

3.       M. A. S. Masoum, H. Dehbonei, and E. F. Fuchs, “Theoretical and experimental analyses of photovoltaic systems with voltage and current based maximum power point tracking,” IEEE Trans. Energy Conv., 2002, Vol. 17, No. 4, pp. 514–522

4.       Subudhi and R. Pradhan, “Characteristics evaluation and parameter extraction of a solar array based on experimental analysis,” in Proc. 9th IEEE Power Electron. Drives Syst., Singapore, 2011

5.       T. Esram, J. W. Kimball, P. T. Krein, P. L. Chapman, and P. Midya, “Dynamic maximum power point tracking of photovoltaic arrays using ripple correlation control,” IEEE Trans. Power Electron.,2006, Vol. 21, No.5, pp. 1282–1291

6.       K. Ishaque, Z. Salam, and H. Taheri, “Simple, fast and accurate two diode model for photovoltaic modules,” Solar Energy Mater. Solar Cells, 2011, Vol. 95, pp. 586–594.

7.       LI Chun, ZHU Xin, SUI Sheng and HU Wan, "Maximum Power Point Tracking of a Photovoltaic Energy System Using Neural Fuzzy Techniques", J Shanghai Univ (Engl Ed), 2009, 13(1), pp.29-36.

8.       Abdulaziz M, S. Aldobhani and Robert John, " Maximum Power Point Tracking of PV System Using ANFIS Prediction and Fuzzy Tracking", Procs. Of the Inter. Multi Conf. of engineers and Computer  cientists 2008, vol. II, IMECS 2008, 19-21 March,Hong Kong.

9.       K. Abdelsalam, A. M. Massoud, S. Ahmed and P. N. Enjeti, “Highperformance adaptive perturb and observe MPPT technique for photovoltaic-based microgrids,” IEEE Trans. Power Electron., vol. 26, no. 4, pp. 1010–1021, Apr. 2011

10.    D.G. Lorente, S. Pedrazzi, G. Zini, A. Dalla Rosa, P. Tartarini, Mismatch losses inPV power plants, Sol. Energy 100 (2014) 42–49.

11.    Y.Shaiek, M.Ben Smida, A.Sakly, M.F.Mimouni“Partial Shading Impact on MPPT Methods of Solar PV Generator’ ,Solar Energy ,2013

12.    S. Silvestre, A. Boronat, A. Chouder, Study of bypass diodes configuration on PVmodules, Appl. Energy 86 (2009) 1632–1640.

13.    S.Daraban, D. Petreus, C. Morel“A novel MPPT (maximum power point tracking) algorithm based on a modified genetic algorithm specialized on tracking the global maximum power point in photovoltaic systems affected by partial shading”,Energy,2014


35-41

www.blueeyesintelligence.org/attachments/File/fee/2checkout_download.html

8.

Authors:

Preethi W, Binu Rajan M R

Paper Title:

Atomic Web Service Reliability Prediction

Abstract:  Web service is one of the main supporting underlying technologies in Service Oriented Architecture (SOA). This work is focused on atomic web service reliability, as one of the most important non-functional properties. Service reliability can be defined as the probability that a service invocation gets retrieved successfully, i.e. correct response to the service invocation gets successfully retrieved under the specified conditions and the time constraints. A model-based collaborative filtering approach CLUS (CLUStering) is used to estimate the reliability of an ongoing web service. It considers user, service and environment specific parameters to provide a more accurate description of the service invocation context. Incorporating K-Strings clustering algorithm is highly prominent for clustering of high dimensional data rather than using K-Means algorithm. This aims to generate higher accuracy and efficiency to the prediction model.

Keywords:
 reliability prediction, K-Strings, atomic web services, QoS prediction, K-Means

References:

1.       M. P. Papazoglou, “Service-oriented computing: Concepts, characteristics and directions,” in Web Information Systems Engineering, 2003. WISE 2003. Proceedings of the Fourth International Conference on. IEEE, 2003, pp. 3–12.
2.       Hongbing Wang, Haixia Sun and Qi Yu, “Reliable Service Composition via Automatic QoS Prediction”, IEEE 2013.

3.       L. Zeng, B. Benatallah, A. Ngu, M. Dumas, J. Kalagnanam, and H. Chang, “Qos-aware middleware for web services composition,” Software Engineering, IEEE Transactions on, 2004.

4.       D. Wang and S. T. KISHOR, “Modeling user-perceived reliability based on user behavior graphs,” International Journal of Reliability, Quality and Safety Engineering, 2009.

5.       V. Cortellessa and V. Grassi, “Reliability modeling and analysis of service-oriented architectures,” pp. 339–362

6.       Z. Zheng and M. R. Lyu, “Collaborative reliability prediction of service-oriented systems,” in ACM/IEEE International Conference on Software Engineering - Volume 1, ACM, 2010.

7.       Z. Zheng, H. Ma, M. R. Lyu, and I. King, “Qos-aware web service recommendation by collaborative filtering,” IEEE Transactions on Services Computing, 2011.

8.       L. Baresi and S. Guinea, “Event-based multi-level service monitoring,” in ICWS, pp. 83–90, 2013.

9.       Marin Silic, Goran Delac, and Sinisa Srbljic, “Prediction of Atomic Web Services Reliability for QoS-aware Recommendation”, IEEE 2014.

10.    G. Delac, M. Silic, and S. Srbljic, “A reliability improvement method for soa-based applications,” Dependable and Secure Computing, IEEE Transactions on, vol. PP, no. 99, pp. 1–1, 2014.

11.    V.GrassiandS.Patella,“Reliability prediction for service-oriented computing environments,” IEEE Internet Computing, 2006.

12.    W. T. Tsai, D. Zhang, Y. Chen, H. Huang, R. Paul, and N. Liao, “A software reliability model for web services,” in International Conference on Software Engineering and Applications, 2004.

13.    J. Ma and H.-p. Chen, “A reliability evaluation framework on composite web service,” in IEEE International Symposium on Service-Oriented System Engineering, IEEE Computer Society, 2008.

14.    B. Li, X. Fan, Y. Zhou, and Z. Su, “Evaluating the reliability of web services based on bpel code structure analysis and runtime information capture,” in Asia Pacific Software Engineering Conference 2010, IEEE Computer Society, 2010.

15.    X. Su and T. M. Khoshgoftaar, “A survey of collaborative filtering techniques,” Adv. in Artif. Intell., vol. 2009.

16.    B. Sarwar, G. Karypis, J. Konstan, and J. Riedl, ‘‘Item-Based Collaborative Filtering Recommendation Algorithms,’’ in Proc. 10th Int’l Conf. World Wide Web, 2001, pp. 285/295.

17.    Z. Zheng and M.R. Lyu, ‘‘Collaborative Reliability Prediction of Service-Oriented Systems,’’ in Proc. 32nd ACM/IEEE Int’l Conf. Softw. Eng., New York, NY, USA, 2010, vol. 1, pp. 35/44, ACM.

18.    Klein, F. Ishikawa, and S. Honiden, ‘‘Towards NetworkAware Service Composition in the Cloud,’’ inProc. 21st Int’l Conf. World Wide Web, 2012, pp. 959/968.

19.    N.B. Mabrouk, S. Beauche, E. Kuznetsova, N. Georgantas, and V.Issarny,‘‘QoS-AwareServiceCompositioninDynamicService Oriented Environments,’’ in Proc. 10th ACM/IFIP/USENIX Int’l Conf. Middleware, 2009, pp. 123/142.

20.    Y. Wang, W.M. Lively, and D.B. Simmons, ‘‘Web Software Traffic Characteristics and Failure Prediction Model Selection,’’ J. Comput. Methods Sci. Eng., vol. 9, no. 1, pp. 23-33, Apr 2009.

21.    “Service Selection for Web Services with Probabilistic QoS” , IEEE transactions on services computing, vol. 8, no. 3, may/june 2015.

22.    Mingdong Tang et al., “Collaborative Web Service Quality Prediction via Exploiting Matrix Factorization and Network Map”, IEEE 2015.

23.    Xin Luo et al., “Generating Highly Accurate Predictions for Missing  QoS Data via Aggregating Nonnegative Latent Factor Models”, IEEE 2015.

24.    Y. Xu, J. Yin, and W. Lo, “A unified framework of QoS-based web service recommendation with neighborhood-extended matrix factorization,” in Proc. 6th IEEE Int. Conf. Service Oriented Computing and Applications (SOCA 2013), 2013, pp. 198–205.

25.    X.Luo,Y.-N.Xia,andQ.-S. Zhu, “Incremental collaborative filtering recommender based on regularized matrix factorization,” Knowl. Based Syst., vol. 27, pp. 271–280, 2012.

26.    Jianlong Xu, Zibin Zhen, and Michael R. Lyu, “Web Service Personalized Quality of Service Prediction via Reputation-Based Matrix Factorization”, IEEE transactions on reliability, vol. 65, no.1, march 2016.

27.    Xin Luo et al., “Generating Highly Accurate Predictions for Missing QoS Data via Aggregating Nonnegative Latent Factor Models”, IEEE 2015.

28.    R.XuandI.Wunsch,D.,“Survey of clustering algorithms”, Neural Networks, IEEE Transactions on, 2005.

29.    Marin Silic, Goran Delac, and Sinisa Srbljic, “Prediction of Atomic Web Services Reliability for QoS-aware Recommendation”, IEEE, 2015.

30.    Y. Wang, W. M. Lively, and D. B. Simmons, “Web software traffic characteristics and failure prediction model selection,” J. Comp. Methods in Sci. and Eng., 2009.

31.    Y. Baryshnikov, E. Coffman, G. Pierre, D. Rubenstein, M. Squillante, and T. Yimwadsana, “Predictability of web-server traffic congestion,” Web Content Caching and Distribution, International Workshop on, 2005.

32.    M. Andreolini and S. Casolari, “Load prediction models in web based systems,” in International conference on Performance evaluation methodolgies and tools, ACM, 2006.

33.    Y.-T. Lee and K.-T. Chen, “Is server consolidation beneficial to mmorpg? a case study of world of warcraft,” in Cloud Computing, 2010 IEEE 3rd International Conference on, pp. 435–442, 2010.

34.    Viet-Hoang Le and Sung-Ryul Kim, “K-strings algorithm, a new approach based on Kmeans”, ACM 2015.


42-46

www.blueeyesintelligence.org/attachments/File/fee/2checkout_download.html

9.

Authors:

Hameed R. M. Al-Mishmish, H. S. Al-Raweshidy

Paper Title:

Interface and Traffic Handover Mechanism in Multi-homed Mobile IP Node

Abstract:  Network Mobility is a relatively new networking concept aimed at improving the reliability and scalability of data communications within vehicles moving at high speed. The growing use of IP devices in portable applications has created the demand for mobility support for entire networks of IP devices. Users are expected to be connected to the internet from anywhere at any time this facilities will provide to own user to more than mobile devices, there are several mobile devices such as mobile phone, laptop and PDA and other type, all these devices could have multiple network interfaces, these interfaces enable mobile devices to maintain ongoing communication while its moving from one point to another.

Keywords: Mobile IP, IETF, Network Mobility, Network Simulator (NS2), Multi-homed node, Interface selection mechanism, Throughput, Delay, Jitter.


References:

1.       Hesham Soliman, “Mobile IPv6, mobility in wireless internet,” April 2004.
2.       C. Perkins, Ed. Internet Engineering Task Force (IETF), RFC 5944, 2010.

3.       Nicolas Montavont and Thomas Noel and Thierry Ernst, “Multihoming in Nested Mobile Networking”, IEEE Jan 2004.

4.       “Introduction to Mobile IP” Cisco IOS IP. 2001.

5.       Albert Cabellos-Aparicio, Jordi Domingo Pascual, “Load Balancing in Mobile IPv6’s Correspondent Networks with Mobility Agents” IEEE 2007.

6.       M. Suthar, A. Ranavadiya, and S. Patel "A survey paper on mobile IP,"International Journal for Scientific Research and Development. IJSRD,Vol. 2, pp. 655-658, 2014.

7.       Esraa Hassan Abdelhafiz Alsaied, Sayda Maowia Alshareef Modatheir “Performance Evaluation of Mobile IP with DSDV Routing Protocol using NS2” IEEE 2015.

8.       Noureen, Z. llyas, 1. Shahzadi, M. Iqbal, M. Shafiq and A. Irshad "Mobile IP issues and their potential solutions: an overview," Advances in Computer Science: an International Journal. ACSlJ, Vol. 3, No. 07, pp. 106-114,2014.

9.       Younghwan Choi, Bongsoo Kim, Sang-Ha Kim, Minkyo In, and Seungyun Lee. “A Multihoming Mechanism to Support Network Mobility in Next Generation Networks”, IEEE Aug 2006.

10.    Hiroshi Esaki, “Multi-Homing and Multi-Path Architecture Using Mobile IP and NEMO Framework”, IEEE, 2004.

11.    Christer Åhlund, Robert Brännström and Arkady Zaslavsky, “A Multihoming approach to Mobile IP”, Luleå University of Technology, Skellefteå Campus, SE-931 87 Skellefteå, Sweden.


47-50

www.blueeyesintelligence.org/attachments/File/fee/2checkout_download.html

10.

Authors:

M Indu, Kavitha K V

Paper Title:

A Varied Efficient Approach on Sketch Based Image Retrieval System

Abstract:   Especially with the vogue of touch screen devices, retrieval of images that match with a hand-drawn query sketch became a highly desirable feature. Since 1990s, query-by sketch has been an extensive study. Due to the lack of effective and efficient matching solutions they are still very challenging. Compared to face recognition, face photo recognition using face sketch is relatively a younger area. The exceptional triumph of search techniques have encouraged to revisit the problem and focused at solving the problem of sketch based image retrieval. To this end, a novel method is presented here which is as follows: for each image in the database feature extraction is carried out and edge correspondence metric is computed which will be stored. Similarly for the query sketch the same steps are repeated. For each value the query sketch searches for a match score. The database image with highest match score is the retrieved match against the query sketch from the face photo database. An optimized algorithm is also incorporated for images that are corrupted by various types of noises. This method can handle non-facial factors such as such as hair style, hairpins, and glasses. During investigation results show that the proposed method outperforms several state of-the-arts in terms of accuracy and running time.

Keywords:
 Face sketch synthesis, Feature vector, Edge correspondence metric, Sketch based image retrieval.


References:

1.       W. Zhao, R. Chellappa, A. Rosenfeld, and J. Phillips, “Face recognition: A literature survey,” ACM Comput. Surv., vol. 35, no. 4, pp. 399–458, 2003.
2.       Chalechale, G. Naghdy, and A. Mertins, “Edge image description using angular radial partitioning,” IEEE Proc.-Vis., Image Signal Process., vol. 151, no. 2, pp. 93–101, Apr. 2004.

3.       R. Uhl, N. da Vitoria Lobo, and Y. Kwon, “Recognizing police sketches of faces,” in Proc. IEEE Workshop Appl. Comput. Vis., 1994, pp. 129–137.

4.       J. W. Brahan, K. P. Lam, H. Chan, and W. Leung, “AICAMS—Artificial intelligence crime analysis and management system,” Applications and Innovations in Expert Systems V, J. Knowl. Based Syst., pp. 143–153, 1997.

5.       Turk, M. and Pentland, A., “Eigenfaces for recognition," Journal of Cognitive Neuroscience 3(1), 71-86 (1991).

6.       Phillips, P., Scruggs, W., OToole, A., Flynn, P., Bowyer, K., Schott, C., and Sharpe, M., “Frvt 2006 and ice 2006 large-scale results," in [NISTIR 7408], (2007).

7.       Gross, R., Baker, S., Matthews, I., and Kanade, T., “Face recognition across pose and illumination," in [Handbook of Face Recognition], Li, S. Z. and Jain, A. K., eds., Springer-Verlag (2004).

8.       Wright, J., Yang, A. Y., Ganesh, A., Sastry, S. S., and Ma, Y., “Robust face recognition via sparse representation," IEEE Trans. Pattern Analysis & Machine Intelligence 31(2), 210-227 (2009).

9.       Tang, X. and Wang, X., “Face sketch synthesis and recognition," in [Proc. of IEEE International Conference on Computer Vision], 687-694 (2003).

10.    Tang, X. and Wang, X., “Face sketch recognition," IEEE Trans. Circuits and Systems for Video Technology 14(1), 50-57 (2004).

11.    Liu, Q., Tang, X., Jin, H., Lu, H., and Ma, S., “A nonlinear approach for face sketch synthesis and recognition," in [Proc. of IEEE Conference on Computer Vision & Pattern Recognition], 1005-1010 (2005).

12.    Wang, X. and Tang, X., “Face photo-sketch synthesis and recognition," IEEE Trans. Pattern Analysis & Machine Intelligence 31, 1955-1967 (Nov. 2009).

13.    W. Konen, “Comparing facial line drawings with gray-level images: A case study on PHANTOMAS,” in Proc. Int. Conf. Artif. Neural Netw., 1996, pp. 727–734.

14.    Y. Gao and M. K. H. Leung, “Face recognition using line edge map,” IEEE Trans. Pattern Anal. Mach. Intell., vol. 24, no. 6, pp. 764–779, Jun. 2002.

15.    G. Mackenzie, “Agent-based sketch recognition,” Ph.D. dissertation, Univ. Nottingham, Nottingham, U.K., 2003.

16.    D. Marr and E. Hildreth, Theory of edge detection", Proc. Royal Society, London, 1980, pp.187-217.

17.    E. Argyle. “Techniques for edge detection,” Proc. IEEE, vol. 59, pp. 285-286, 1971.

18.    M Sudarshan, P Ganga Mohan and Suryakanth, V Gangashetty “Optimized Edge Detection Algorithm for Face Recognition”.


51-55

www.blueeyesintelligence.org/attachments/File/fee/2checkout_download.html

11.

Authors:

Gailan Abdul Qadir, Hassan Ali Salman, Sabah Shehd Abdulabas

Paper Title:

Energy Ventilation Air Flow Electronic Meter

Abstract: The measurement of ventilation losses is one of several types in the energy balance of building, depends on nonlinear single slope type analog to digital convertor (NL-ADC), in this papera digital electronics method is described which is useful in measuring the ear flow via leakage per meter of length of windows and doors. The pressure difference signal is provided as an electrical voltage through appropriate transducer, the digital instrument receives the voltage and processes it together with input coming data of the living area geometry, the resulting readout is digital output number representing of the air flow in the building, the energy ventilation meter will be tested in two different room to measure energy conservation in building related to ventilation losses measurement.

Keywords:
 (NL-ADC), measurement, papera digital electronics, measurement. Appropriate transducer


References:

1.    J.F. kreider and F.Kreith,"" Solar energy Handbook", 1981.
2.    Moran M.J. and Shapiro H.N. Fundamentals of Engineering Thermodynamics. Second edition. New York: John Wiley & Sons, 1992.

3.    William H. Hayt , Gerold W. Neudeck " Electronic Circuit Analysis and Design"  2nd Edition, 1989.

4.    J. Chris Stratton, W.J.N Turner, Craig P. Wray, Iain S. Walker,"Measuring Residential Ventilation  System Airflows",2012.

5.    Lian Zhang, Yu Feng Zhang," Research on Heat Recovery Technology for Reducing the Energy Consumption of Dedicated Ventilation Systems: An Application to the Operating Model of a Laboratory", Energies,4 January 2016.

56-58

www.blueeyesintelligence.org/attachments/File/fee/2checkout_download.html
































































































































































































































































































































































12.

Authors:

Vijay Kumar, Rakesh Kumar

Paper Title:

Optimal Analysis of Economic Load Dispatch using Artificial Intelligence Techniques

Abstract:  Applications of artificial intelligence to economic load dispatch problems are discussed in the paper. The fuelcost equation of a thermal plant is generally expressed as continuous quadratic equation. In real situations the fuel cost equations can be discontinuous. Continuous and discontinuous fuel cost equations are explained here as thermal palnts cost equation are continuous which are further a quadratic equation.GA technique used for 30 bus test system have continuous fuel cost equations. Various results compared with conservative quadratic programming methods to analyze superiority of the suggested artificial intelli-gence technique. A 10-generator system each with distributed areas is considered and particle swarm algorithm engaged to reduce the cost of generation. All obtained results compared with other conventional methods.

Keywords:
GA, ELD, PSO, Evolutionary methods


References:

1.       Jiang and S. Ertem, “Economic dispatch with non-monotonically  increasing incremental cost units and transmission system losses”, IEEE Transactions on Power Systems, vol. 10, no. 2, pp. 891-897, May 1995.
2.       H.W. Dommel, “Optimal power dispatch”, IEEE Transactions on Power Apparatus and Systems, PAS93 No. 3, pp. 820–830, 1974.

3.       N. Ramaraj and K. Nagappan, “Analytical method to optimize gen-eration schedule”, Journal of The Institution of Eng-neers (India), vol. 66, p 240, 1987.

4.       C.E. Lin and G.L. Vivianib, “Hierarchical Economic Dispatch of Piecewise Quadratic Cost Functions”, IEEE Transactions of PAS, vol.103, no 6, June, 1984.

5.       N. Ramaraj and R Rajaram, “Analytical approach to optimize genera-tion schedule of plant with multiple fuel options”, Journal of The Institution of Engineers (India), vol. 68, p 106, 1987

6.       N. Ramaraj and R Rajaram, “Analytical approach to optimize genera-tion schedule of plant with multiple fuel options”, Journal of The Institution of Engineers (India), vol. 68, p 106, 1987.

7.       J.V. Guttag, The Specification and Application to Program-ming of Abstract Data Types, Ph.D. Thesis, Dept. of Computer Science, Uni-versity of Toronto (1975).

8.       J.V. Guttag and J.J. Horning, “Formal Specification as a De-sign Tool,”Seventh ACM Symposium on Principles of Program-ming Languages, Las Vegas (1998), pp-2-9.

9.       J.V. Guttag, “Notes on Type Abstraction, Version 2,’’ IEEE Transac-tions on Software Engineering,pp-46-49, vol. SE-6, no. 1 (1980).

10.    C.A.R. Hoare, “An Axiomatic Basis for Computer Pro-gramming,”Communications of the ACM, vol. 12, no. 10 (1985).

11.    A.Igelais, “Proofs of Correctness of Data Representations,” Acta Informatica, pp- 56,vol. 1, no. 4 (2006).

12.    J. H. Holland, Adaptation in Natural and Artficial Systems, Univer-sityof Michigan Press, Ann Arbor, MI, 1975.S. Koziel and Z. Michalewicz, Evolutionary algorithms, homomorphous map-pings, and constrained parameter optimization, Evolutionary Computation 7(1), 19-44, 1999.

13.    T.S. Metcalfe, P. Charbonneau, Stellar structure modeling using a parallel genetic algorithm for objective global optimiza-tion, Journal of Computational Physics 185, 176-193, 2003.

14.    Z. Michalewicz, A Survey of Constraint Handling Tech-niques in Evolutionary Computation Methods, Evolutionary Pro-gramming, Vol.4, pp.135, 1995.Z. Michalewicz, Genetic algo-rithms + data structures =evolution pro-grams,Berlin,Springer,1996


59-63

www.blueeyesintelligence.org/attachments/File/fee/2checkout_download.html




































13.

Authors:

Arathy S. Mohan, M. Nazeer

Paper Title:

Experimental Investigation on the Properties of Gap Graded Aggregate Medium Strength Concrete

Abstract:   Concrete is a mixture of cementations material, aggregate, and water. Aggregate is commonly considered inert filler, which accounts for 60 to 80 percent of the volume and 70 to 85 percent of the weight of concrete. Thus concrete properties are highly affected by physical properties of its aggregate. The particle size distribution of coarse and fine aggregate (grading of aggregate) may have an effect on concrete behaviour. However, due to the inherent difficulties related to the characterization of fine sized particles, little research has been made to evaluate the effect of grading. In the present investigation, packing density of combined aggregate is considered as the criteria for aggregate gradation thus selecting four combinations of gap graded aggregate for making medium strength (M40) concrete mixes. The workability, density and strength results from these concrete mixes are finally compared with conventional concrete to propose a suitable aggregate gradation. Within the premises of this study, it is concluded that gap graded concrete, though of a relatively stiffer and drier mix, can be placed and finished without undue effort for the non-structural, massive construction works demand less workability wherein continuously graded concrete has been customarily used heretofore. A considerable saving in cement content, sand and notable improvements in mechanical properties are the realistically achievable advantages through the use of gap graded concrete. Good control and, above all, care in handling, so as to avoid segregation, are essential.

Keywords:  aggregate, gap graded, gradation, packing density


References:

1.       Quiroga, P. N. (2003)The Effect of the Aggregates Characteristics on the Performance ofPortland Cement Concrete, Doctoral Dessertation,The University of Texas at Austin.
2.       Elices, M. and C.G. Rocco (2008) Effect of Aggregate Size on the Fracture and Mechanical Properties of a Simple Concrete, Journal of Engineering Fracture Mechanics,75, 3839-3851.

3.       Ashraf, W. B. and  M. A. Noor (2011) Performance-Evaluation of Concrete Properties for Different Combined Aggregate Gradation Approaches, The Twelfth East Asia-Pacific Conference on Structural Engineering and Construction, 14, 2627-2634.

4.       Hilf, J. W. (1987) Rolled Concrete Dams Using GapGraded Aggregate, Journal of Construction Engineering and Management, 1, 27-33.

5.       Meddah, M.S., Zitouni, S. and S. Belaabes (2009) Effect of content and particle size distribution of coarse aggregate on the compressive strength of concrete, construction of building materials, 24, 505-518.

6.       Shetty, M. S., Concrete Technology, Ram Nagar, New Delhi, S. ChandPublications,2012.

7.       IS: 12269-1987- Specification for 53 Grade Ordinary Portland Cement, Bureau of Indian Standards, New Delhi, 2000.

8.       IS: 383-1970, Specification for Coarse and Fine Aggregate from Natural Sources for Concrete, Bureau of Indian Standards, New Delhi.

9.       IS: 10262-1982, Recommended guidelines for Concrete Mix Design, Bureau of Indian Standards, New Delhi, 2000.

10.    IS: 2386 (Part 1) –1963, Methods of Test for Aggregates for Concrete Part 1- Particle Size and Shape, Bureau of Indian Standards, New Delhi.

11.    Al-Sahawneh, E. I. (2015) A New Approach for the Determination of Tensile and Shear Strengths of Normal Weight Concrete, International organization of Scientific Research, 05, 38-48.

12.    IS: 516-1959,Method of Tests for Strength of Concrete, Bureau of Indian Standards, New Delhi, India.

13.    IS: 1199-1959, Methods of Sampling and Analysis of Concrete, Bureau of Indian Standards, New Delhi.


64-69

www.blueeyesintelligence.org/attachments/File/fee/2checkout_download.html

14.

Authors:

Ambika P, Binu Rajan M.R

Paper Title:

Link Based Overlapping Community Detection and Medical Data Mining of Social Media for Cancer Prognosis

Abstract: Social media, ranging from personal messaging to live foras, is providing unlimited opportunities for patients to exchange their views on their experiences with drugs and devices. Here the aim is to understand the correlation between user posts and positive or negative judgment on drugs along with its side effects in cancer patients with particular emphasis on analysing the notion of community detection within this social network by analysing link properties. The proposed system is a two-step analysis framework where positive negative user sentiments are evaluated using data mining tools and techniques followed by identifying overlapping community structures (influential user modules) within the user forum. The two-way process utilizes the comments on internet message boards (cancer research forums) to infer the acceptance and effectiveness of a drug in cancer treatment and maps to the influential user within the network. In the first stage of the current study, opinion labels are developed about each drug based on opinion analysis from user posts and each word is given weightage per node using data mining tools. In the second stage, networks are built from the search results of the forum, a network ranking system reflecting the opinion formation about the drug is developed. Different from traditional algorithms based on node clustering, the proposed method is based on link clustering to discover overlapping communities. Since links usually represent unique relations among nodes, the link clustering will discover groups of links that have the same characteristics. The current approach effectively searches for different levels of organization within the networks and uncovers dense modules using partition density factor. Finally, the accuracy of novel link based overlapping community detection method is compared with the traditional network based community detection model using graph benchmark. Thus the experiment is used to determine opinion from consumer and identify influential users within the retrieved modules using information derived from both term occurrence and word frequency of data and network-based properties in an accurate way.

Keywords:
Community detection, Health Informatics, Multi-scale, Markovprocess, Modularity, Overlapping communities, Random walks, Social media, Stability.


References:

1.       Reza Zafarani, Mohammad Ali Abbasi,Huan Liu, “Social Media Mining An Introduction,”, April 2014.J. Cambridge university.
2.       Zhu,F., Patumcharoenpol, P., Zhang, C., Yang, Y., Chan, J., Meechai, A. et al, “Biomedical text mining and its applications in cancer research. “J. Biomed. Inform. 2013;46:200–211.

3.       David F. Nettleton,”Data mining of social networks represented as graphs,” Expert Systems with Application, October 2012

4.       G. Angulakshmi, Dr.R. Manicka Chezian,”An Analysis on Opinion Mining: Techniques and Tools”,Intrn. Journal of Advanced Research in Computer and Communication Engineering Vol. 3,Issue 7, July 2014

5.       Richa Sharma, Shweta Nigam and Rekha Jain,”Oinion mining of movie reviews at document level”, International Journal on Information Theory (IJIT), Vol.3, No.3, July 2014.

6.       WalaaM edhat a, Ahmed Hassan b, HodaKorashy,” Sentiment analysis algorithms and applications: A survey”, Ain Shams Engineering Journal (2014) ,Volume:5,Issue:4,pp: 1093–1113

7.       Vishal Shrivastava, Rajesh Boghey, BhupendraVerma,"A Framework for Improving Target Marketing Using Collaborative Data Mining Approach", IJICT Journal, Volume 1 No. 2, June 2011

8.       LiseGetoor,” Link Mining: A New Data Mining Challenge,”UMIACS, 415- 444,Volume 4, Issue 2,2013

9.       Mohammad Al Hasan , Mohammed J. Zaki,”A Survey of Link Prediction in Social Networks”,Springer,March,2011

10.    P.Ambika, M.R BinuRajan, “Multi-scale Community Detection in Complex Networks,” IEEE International Conference on research Advances in Integrated Navigation System,2016.

11.    V.R. Nagarajan, Monisha.P.M” Extracting Knowledge from Social Media toImprove Health Informatics”IJARCC,Vol. 4, Issue 7, July 2015.

12.    Akay, A. Dragomir, and B. E. Erlandsson, “A novel data-mining approach leveraging social media to monitor consumer opinion of sitagliptin,” J. Biomed Health Inform. Vol: PP, Issue: 99.

13.    Akay, A. Dragomir, and B. E. Erlandsson, “Network-Based Modeling and Intelligent DataMining of Social Media for Improving CareVol:19, 2015

14.    J. Vesanto, J. Himberg, E. Alhoniemi, and J. Parhankangas, “Self-Organizing Map in MATLAB: The SOM Toolbox,” in Proc. Matlab DSP Conf., Espoo, Finland, 1999, pp. 35–40.

15.    Chuan Shi, Yanan Cai, Di Fu, Yuxiao Dong, Bin Wu, “A link clustering based overlapping community detection algorithm,” Data & Knowledge Engineering, Elsevier, vol. 87, pp. 394–404, May 2013.

16.    Le Yu,BinWu,Bai Wang,“LBLP :Link-Clustering-Based Approach for Overlapping Community Detection,” ISSN, Volume 18, pp387-397, Number 4, August 2013.

17.    Erwan Le Martelot , Chris Hankin, “Multi-scale community detection using stability optimisation,” International Journal of Web Based Communities, v.9 n.3, p.323-348, June 2013

18.    E. Le Martelot and C. Hankin, “Multi-scale community detection using stability as optimization criterion in a greedy algorithm,” Proceedings of the 2011 International. Conf. erence on Knowledge Discovery and Information Retrieval (KDIR 2011), Paris, France: SciTePress, Oct. 2011, pp. 216–225.

19.    Esuli ,A., Sebastian,F.,” SENTIWORDNET: A Publicly Available Lexical Resource for Opinion Mining, ”In: Proceedings of 3rd Conf. on Intrn. Language Resource and Evaluation,pp.417-422(2006)

20.    Design and Analysis of Computer Algorithms1,David M. Mount, CMSC 451

21.    Y.Y. Ahn, J.P. Bagrow, S. Lehmann, Link communities reveal multi-scale complexity in networks, Nature 466 (2010) 761–764.

22.    Fei Zhu, Preecha Patumcharoenpol, Cheng Zhanga, Yang Yang b, Jonathan Chan ,Asawin Meechai , Wanwipa Vongsangnak , Bairong Shen ,”Biomedical text mining and its applications in cancer research ,” Journal of Biomedical Informatics 46 (2013) 200–211


70-75

www.blueeyesintelligence.org/attachments/File/fee/2checkout_download.html







































































































15.

Authors:

Ambika Omana Menon, Sakuntala S. Pillai

Paper Title:

A Paradigm Shift from OFDM to WPMCM as the Preferred Multi-Carrier Modulation Technique

Abstract: As of now, Multi-Carrier modulation (MCM) is considered an effective technique for both wired and wireless communications. Studies have been done by different researchers in this area and analysis of the comparative advantages and disadvantages of the different options for multi-carrier modulation have been extensively done. The place of OFDM, which was once considered as a very strong candidate for multi-carrier modulation technique, has almost been taken over by its successor, WPMCM. This paper reviews the paradigm shift from OFDM to WPMCM as the preferred multi-carrier modulation technique.

Keywords:
 Multicarrier modulation, WPMCM, OFDM, Discrete Wavelet Packet Transform.


References:

1.       A multicarrier primer- John M.Cioffi
2.       D. Karamehmedović, M.K. Lakshmanan, H. Nikookar, “Performance Evaluation of WPMCM with Carrier Frequency Offset and Phase Noise”, Journal of communications, vol. 4, no. 7, August  2009

3.       Ove Edfors -Magnus Sandell Jan-jaap Van De Beek, Daniel Landstrom, Frank Sjoberg, “An introduction to orthogonal frequency division multiplexing”

4.       H. Umadevi, K.S. Gurumurthy, “OFDM Technique for Multi-carrier Modulation (MCM) Signaling” Journal of Emerging Trends in Engineering and Applied Sciences (JETEAS)
2 (5): 787-794

5.       D. Karamehmedović , Dr. H. Nikookar, M. K. Lakshmanan, “A Study of Synchronization Issues of Wavelet Packet based Multicarrier Modulation”

6.       S.Haykin, “Cognitive Radio: Brain-Empowered Wireless Communications‖”, IEEE JSAC, Vol.23, No.2, pp.201-220, February 2005

7.       J.Mitola, G.Q.Maguire, “Cognitive Radio: Making Software Radios More Personal”, IEEE Personal Communications, Vol.6, No.4, pp.13-18, August 1999

8.       Sobia Baig, Fasih-ud-Din Farrukh and M. Junaid Mughal, “Discrete Wavelet Multitone Modulation for ADSL & Equalization Techniques”, Intech Open Access Publisher, pp. 3-24

9.       A.Lindsay, “Wavelet Packet Modulation for Orthogonally Transmultiplexed Communications”, IEEE Transactions on Signal Processing, Vol.45, pp.1336-1339, May 1997

10.    Haleh Hosseini, Norsheila Fisal, Sharifah K. Syed-Yusof, “Wavelet Packet based Multicarrier Modulation for Cognitive UWB Systems”, Signal Processing – An International Journal (SPIJ), Volume (4): Issue (2)


76-78

www.blueeyesintelligence.org/attachments/File/fee/2checkout_download.html





























16.

Authors:

M. Sghiar

Paper Title:

Turbulent Functions and Solving the Navier-Stokes Equation by Fourier Series

Abstract: I give a resolution of the Navier-Stokes [2] equation by using the series of Fourier. Résumé: Je donne une résolution de l'équation de Navier-Stokes [2] par les séries de Fourier.

Keywords:
 Navier-Stokes, Fourier, Séries de Fourier.

References:

1.    Joseph Fourier, Théorie analytique de la chaleur, Firmin Didot Père et Fils (Paris-1822). Réédition Jacques Gabay, 1988 (ISBN 2-87647-046-2)
2. http://www.claymath.org/sites/default/files/navierstokes.pdf

79-80

www.blueeyesintelligence.org/attachments/File/fee/2checkout_download.html














17.

Authors:

Alaa Ibrahim, Ibrahim Marouf

Paper Title:

Methods and Techniques of Conservation Process for the Heritage Building Walls

Abstract: The issue of the conservation of architectural heritage has been given much attention on the political, cultural and academic level due to the heritage values for being cultural wealth for the nations. However the remains and ruins of these properties come under threat due to the propagation of structural work resulting from industrial development and urbanization. Hence, it has become the responsibility of government institutions to ensure the protection and conservation of humanity’s cultural heritage. That's in a manner which strikes a balance and ensures harmony between the preservation of cultural heritage and the changes required by social and economic developments. All efforts have to be exerted to fulfill these two objectives in a spirit of understanding, in a planned timely manner and employing efficient technologies. Therefore, the main aim of the research is to enhance and highlight the new techniques and methods that used for maintaining the heritage building's walls that could achieve the execution of temporary and definitive works. The most used methods that have been successfully implemented for several years for conserving walls are wall grouting injection, Cintec anchoring system, Fiber reinforced polymers, using prestressed steel in buildings consolidation and scaffolding systems .The research methodology is following a qualitative approach through first, defining each technique and it's details (eg, characteristics, way of execution ,advantages , disadvantages and case study) . Second, by analyzing, evaluating the techniques and ensure its efficiency. The implementation of these techniques requires skilled labors, not only at the execution process, but also in the planning stages. The main mission of the conservators of the restoration process is to select the technique that keeps the heritage value of the building without deteriorating the building characteristics, elements or historical materials. To sum up using these techniques with accurate and suitable implementation methods, resulted in conserving the values of the heritage buildings and could safely transform them to the next generations. (The researcher 2016)

Keywords:
Grouting injection, Cintec anchoring system, Fiber reinforced polymers, prestressed steel, Scaffolding systems.


References:

1.       Kate Clark. (2005). Conservation Planning Methodology search, Developing policies for the conservation of historic places. Columbia: Heritage branch.
2.       Asamer Ahmed. (2005). Master Thesis: Contemporary techniques in restoration of historical buildings. Cairo: Cairo University.

3.       Jack Gillon. (2001). CONSERVATION CHARTERS AND STANDARDS. Retrieved from http://ihbc.org.uk

4.       Webber Nodro.(2009). Cultural heritage and the law search. Africa: ICCROM.

5.       WORLD HERITAGE CENTRE. (2013). Operational Guidelines for the Implementation of the World Heritage Convention. France: UNESCO World Heritage Centre.

6.       Intergovernmental Committee.(2013). Operational Guidelines for the Implementation of the World Heritage Convention. France: UNITED NATIONS EDUCATIONAL, SCIENTIFIC AND CULTURAL ORGANISATION.

7.       ICOMOS. (2001). International Council on Monuments and Sites. Retrieved from http://www.icomos.org.

8.       The parliament. (2006). قانون رقم 144. Cairo: The parliament publishing center.

9.       Ashraf Ali. (2012). Master Thesis: Restoration of historic Islamic buildings and its compliance with international standards. Egypt: Faculty of engineering, Cairo University.

10.    Adel Saad. (2002).Master Thesis: اسس وقواعد ترميم المباني الاثريه بين النظريه والتطبيق. Cairo: Faculty of archaeology, Restoration department.

11.    Lisandra Miranda. (2014). DEFINITION AND EVALUATION OF A GROUT FOR CONSOLIDATION OF ANCIENT MASONRY . SEISMIC VULNERABILITY OF A "PLACA" BUILDING. Portugal: DECivil, Instituto Superior Técnico, Universidade de Lisboa.

12.    PJ materials Consultants, 2009, Restoration of a National Historic Site Building, Fredericton City Hall, New Brunswick. Retrieved from http://www.pjmc.org.

13.    Faloon.F Construction. (2015). Scientific paper:Cementitious Sock Anchors. United States: Faloon Construction Center.

14.    Ian Hume. (1997). Scaffolding and Temporary Works for Historic Buildings. Retrieved from http://www.buildingconservation.net

15.    Cestelli Guidio. (2015). Strengthening of buildings structures – therapy search  . Berlin: ETH Zürich, Rämistrasse 101, 8092 Zürich.

16.    Lorenzo Jurina. (2003). The structural consolidation of old massive structures search . Italy: Department of Structural Engineering.

17.    Federico M. Mazzolani. (2009). Refurbishment by steelwork search .: Department of Structural Analysis and Design, University of Naples, Naples, Italy “Federico II”

18.    Peter Cox. (2012).Scientific paper:Wall Stabilization, Aniseed Park, Manchester,  Broadway Business center.


81-87

www.blueeyesintelligence.org/attachments/File/fee/2checkout_download.html

18.

Authors:

Md. Lutfor Rahman, Najmus Saquib Sifat, Md. Zakaria Rahman, M. Ali

Paper Title:

Thermal Performance Analysis of a Closed Loop Pulsating Heat Pipe without Insert and with Insert

Abstract:  In this paper, thermal performance of a Closed Loop Pulsating Heat Pipe (CLPHP) without insert and with insert inside the tube has been investigated. The effect of different parameters like working fluid, the filling ratio, inclination angle and the input heat load on the thermal performance has been analyzed thoroughly. In this study, CLPHP is made from long capillary copper tubes with inner diameter of 2.0 mm and outer diameter of 3.0 mm. The heat pipe is bent into eight U-turns and divided into three sections: evaporator section (50 mm), adiabatic section (120 mm) and condenser section (80 mm). Adiabatic section is maintained by using aluminum foil surrounded by appropriate insulation. An insert made of copper wire with diameter 0.5mm is used throughout the tube of all three sections. Methanol and Ethanol are used as working fluids with different filling ratio varied from 40% to 60% in steps of 10%. The thermal resistance has been investigated with different inclination angles (viz. 0°, 30°, 45° and 60° from vertical) at various heat input from 10 to 100W in the steps of 10W. The result shows that, the thermal resistance decreases as heat input increases. CLPHP with insert structure shows better performance than the CHPHP without insert structure particularly at 45°inclination angle. CLPHP without insert structure shows better performance than the CHPHP with insert structure at 00inclinations. Methanol with 40% filling ratio and Ethanol with 60% filling ratio shows the best performance at 0° inclination angle for CLPHP without insert structure. CLPHP with insert structure shows better performance than the CLPHP without insert structure at high heat input particularly at 45°inclination angle.

Keywords:
CLPHP, filling ratio, inclination angle, working fluid, insert structure and without insert structure, PHP, thermal resistance


References:

1.       G. F. Smyrnov and G. A. Savchenkov, (USSR Patent 504065), 1971.
2.       H. Akachi, Structure of a heat pipe, U.S. Patent Number 4921041, 1990.

3.       H. Akachi, F. Polasek and P. Stulc, Pulsating heat pipes, Proc.5th International Heat Pipe Symposium, pp. 208–217, Melbourne, Australia, 1996.

4.       Y. Zhang and A. Faghri, Advances and unsolved issues in in pulsating heat pipes, Copyright Taylor and Francis Group, LLC, Heat Transfer Engineering, 29(1):20–44, 2008, ISSN: 0145-7632 print / 1521-0537 on line DOI: 10.1080/01457630701677114.

5.       S. Maezawa, R. Nakajima, Gi K. and H. Akachi, Cooling of note book PC by oscillating heat pipe, in: 10th Int. Heat Pipe Conf., Vol. 3/4, Session F, Stuttgart, Germany, 1997.

6.       M. B. Shafii, A. Faghri and Y. Zhang, Thermal modeling of un looped and looped pulsating heat pipes, asme journal of heat transfer, Vol. 123, No. 6, pp. 1159- 1172, 2001.

7.       Zhang X. M., Xu, J. L., and Zhou, Z. Q., Experimental study of a pulsating heat pipe using fc-72, ethanol, and methanol as working fluids, experimental heat transfer, vol. 17, no. 1, pp. 47–67, 2004.

8.       P. Meena, S. Rittidech and P. Tammasaeng , Effect of inner diameter and inclination angles on operation limit of closed-loop oscillating heat-pipes with check valves, American Journal of Engineering and Applied Sciences, Vol. 1 (2), pp. 100-103,2008.

9.       P. Meena and S. Rittidech, Comparisons of heat transform performance of a CLOHP and CLOHP with check valves heat exchangers, American Journal of Applied Sciences 1(1): 7-11, 2008, ISSN 1941-7020.

10.    S. Rittidech P. Meena and P. Terdtoon, effect of evaporator lengths and ratio of check valves to number of turns on internal flow patterns of a closed–loop oscillating heat-pipe with check valves, American Journal of Applied Sciences 5 (3): 184-188, 2008 ISSN 1546-9239

11.    P. Meena, S. Rittidech and P. Tammasaeng, Effect of evaporator section lengths and working fluids on operational limit of closed loop oscillating heat pipes with check valves (CLOHP/CV), American Journal of Applied Sciences, Vol.6(1), pp.133-136,  ISSN 1546-9239, 2009.

12.    P. Charoensawan, S. Khandekar, Manfred Groll, and P. Terdtoon, Closed loop pulsating heat pipes, part a: parametric experimental investigations, Applied Thermal Engineering, Vol. 23, No.16, pp. 2009–2020, 2003.

13.    S. Khandekar, N. Dollinger and M. Groll, Understanding operational regimes of closed loop pulsating heat pipes: an experimental study, Applied Thermal Engineering, Vol.23, No.6, pp.707-719, 2003.

14.    Honghai Yang, S. Khandekar, M. Groll, Operational limit of closed loop pulsating heat pipes, Applied Thermal Engineering,  Vol.28 , pp.49–59, 2008.

15.    N. Panyoyai, P. Terdtoon and P. Sakulchangsatjatai, Effects of aspect ratios and number of meandering turns on performance limit of an inclined closed-loop oscillating heat pipe, Energy Research Journal, Vol. 1 (2), pp. 91-95, 2010.

16.    Dharmapal A Baitule1 and Pramod R Pachghare, Experimental analysis of closed loop pulsating heat pipe with variable filling ratio, Int. J. Mech. Eng. & Rob. Res. ISSN 2278 – 0149   www. ijmerr.com, Vol. 2, No. 3, July 2013.

17.    Bhawna Verma, Vijay Lakshmi Yadav and Kaushal Kumar Srivastava, Experimental studies on thermal performance of a pulsating heat pipe with methanol/di methanol, Journal of Electronics Cooling and Thermal Control, pp 27-34, 3 March 2013.

18.    R. Naik, V. Varadarajan , G. Pundarika and K. R. Narasimha, Experimental investigation and performance evaluation of a closed loop pulsating heat pipe, Journal of Applied Fluid Mechanics, Vol. 6, No. 2, pp. 267-275, 2013. ISSN 1735-3572, EISSN 1735-3645.

19.    E. R. Babu and  G. V. Gnanendra Reddy,  Effect of working fluid and filling ratio on performance of a closed loop pulsating heat pipe,  Journal of Engineering Science and Technology Vol. 11, No. 6 (2016) 872 - 880 © School of Engineering, Taylor’s University

20.    ANSI/ASME, Measurement Uncertainty, Report PTC 19.1- (1985, 1986)


88-94

www.blueeyesintelligence.org/attachments/File/fee/2checkout_download.html

19.

Authors:

Rishikesh Mishra, Prashant Thakare, Shreyas Patil, Kartik Kannav, Nikunj Vitalkar

Paper Title:

VC-T Engine An Advancement in 4-Stroke Engine

Abstract: The most important challenge which the car manufacturers are facing today is to offer vehicles that deliver excellent fuel efficiency and superb performance while maintaining cleaner emissions and driving comfort. This paper deals with the VC-T (Variable Compression Turbo) engine technology which is going to be one of the advanced technology in the IC engine, and also deals with it’s working principle and it’s advantages. VC-T is the brand new technology in four cylinder petrol engine family. The VC-T engine is able to maximize it’s efficiency by running a higher compression ratio at idle or low speeds and boost performance by switching over to lower compression ratio under hard acceleration or heavy engine loads. The VC-T is able to adjust it’s compression ratio anywhere between it’s lower limit of 8:1 to higher limit of 14:1. According to Infiniti, the engine intrinsic smoothness allows it to achieve the NVH (Noise vibration & harshness) level similar to that of V6 engine. The paper rounds off with conclusions and an agenda for future research in this area.

Keywords:
 VC-T Engine, Compression ratio, Nissan Infiniti, Efficiency.


References:

1.    Tanaka, Y., Hiyoshi, R., Takemura, S., Ikeda, Y. et al. (2007) “A Study of a Compression Ratio Control
2.    Mechanism for a Multiple-Link Variable Compression Ratio Engine,” SAE Technical Paper 2007-01-3547 doi: 10.4271/2007-01-3547

3.    Hiyoshi, R., Aoyama, S., Takemura, S., Ushijima, K. et al. (2006) “A Study of a Multiple-link Variable Compression Ratio System for Improving Engine Performance,” SAE Technical Paper 2006-01-0616 doi: 10.4271/2006-01-0616

4.    Takahashi, N., Aoyama, S., Moteki, K., and Hiyoshi, R. (2005) “A Study Concerning the Noise and Vibration Characteristics of an Engine with Multiple-Link Variable Compression Ratio Mechanism,” SAE Technical Paper 2005-01-1134 doi: 10.4271/2005-01-1134

5.    M Ayaz Afsar, Mr Prafulla V. Pawar, Mr Prathik Dahule, Mr. S. Papinwar. “ Experimental investigation of direct air injection scavenged two stroke engine”. 2009 International symposium on computing, communication and control (ISCCC). Proc. Of CSIT vol.1 (2001). PP. 21-24.


95-98

www.blueeyesintelligence.org/attachments/File/fee/2checkout_download.html

20.

Authors:

Vivian Brian Lobo, Nazneen Ansari, Annies Minu, Sehba Siddiqui, Flevina D’souza, Jeba Sangeetha Augestin

Paper Title:

Smartphone Selection using Analytic Hierarchy Process

Abstract: Analytic hierarchy process (AHP) is a measurement theory that is used to obtain ratio scales from distinct as well as continuous paired comparisons, and such comparisons can be selected from either tangible measurements or a basic scale that imitates virtual strength of feelings and predilections. AHP is a decision-making process that was developed by Prof. Thomas L. Saaty (1970), and it aims to quantify virtual significances for a given set of alternatives on a ratio scale—based on decision maker’s judgment—and focuses on the importance of instinctive decisions of both a decision maker and the steadiness of comparison of alternatives. AHP has been an instrument at the hands of decision makers since its discovery and is one of the widely used multicriteria decision-making methods. There have been some exceptional works that have been broadcasted based on AHP in various fields such as scheduling, best alternative selection, allocation of resources, conflict resolution, and optimization. AHP’s forte is its suppleness to be integrated with techniques such as linear programming and fuzzy logic that allows a user to excerpt benefits from all techniques and helps to achieve a desired goal. Similarly, we too use AHP to meet our desired goal. That is, in this study, we consider four smartphones (i.e., ph1, ph2, ph3, and ph4) and determine which smartphone is the best by considering numerous criteria such as cost, camera, internal memory, battery life, and style and generate a rank of alternatives using AHP.

Keywords:
analytic hierarchy process, battery life, camera, cost, criteria, internal memory, smartphone, style


References:

1.       T. L. Saaty, “Axiomatic foundation of the analytic hierarchy process,” Manage. Sci., vol. 32, no.7, 1986, pp. 841–855.
2.       B. G. Merkin, Group choice, John Wiley & Sons, 1979, N.Y.

3.       T. L. Saaty, “The analytic hierarchy process,” McGraw-Hill Book Co., 1980, N.Y.

4.       T. L. Saaty, “How to make a decision: The analytic hierarchy process,” Interfaces, vol. 24, 1994a, pp. 19–43.

5.       T. L. Saaty, “Fundamentals of decision making,” RWS Publications, Pittsburgh, 1994b, P.A.

6.       “The analytic hierarchy process—An exposition,” [Online] Available: https://business.highbeam.com/412157/article-1G1-93610861/analytical-hierarchy-process-exposition [Accessed on October 23, 2016].

7.       “The analytic hierarchy process—An exposition [Online] Available: http://www.johnsaunders.com/papers/ahpexpo.pdf [Accessed on October 23, 2016].

8.       E. H. Forman and M. A. Selly, “Decision by objectives: how to convince others that you are right,” World Scientific, 2001.

9.       http://shodhganga.inflibnet.ac.in/bitstream/10603/101833/11/11_chapter%201.pdf [Online] [Accessed on October 23, 2016].

10.    H. W. Brock, “The problem of “utility weights” in group preference aggregation,” Oper. Res., vol. 28, no. 1, 1980, pp. 176–187.

11.    R. L. Keeney, “A group preference axiomatization with cardinal utility,” Manage. Sci., vol. 23, no. 2, 1976, pp. 140–145.

12.    R. L. Keeney and C. W. Kirkwood, “Group decision making using cardinal social welfare functions,” Manage. Sci., vol. 22, no. 4, 1975, pp. 430–437.

13.    P. L. Yu, “A class of solutions for group decision problems,” Manage. Sci., vol. 19, no. 8, 1973, pp. 936–946.

14.    F. Chiclana, E. Herrera-Viedma, F. Herrera, and S. Alonso, “Some induced ordered weighted averaging operators and their use for solving group decision-making problems based on fuzzy preference relations.” Eur. J. Oper. Res., vol. 182, no. 1, 2007, pp. 383–399.

15.    H. Hsi-Mei and C. Chen-Tung, “Aggregation of fuzzy opinions under group decision making.” Fuzzy Set Syst., vol. 79, no. 3, 1996, pp. 279–285.

16.    C. Tan, “A multi-criteria interval-valued intuitionistic fuzzy group decision making with Choquet integral-based TOPSIS,” Expert Syst. Appl., vol. 38, no. 4, 2011, pp. 3023–3033.

17.    T. Tanino, “Fuzzy preference orderings in group decision making,” Fuzzy Set Syst., vol. 12, no. 2, 1984, pp. 117–131.

18.    Y. Dong, Y. Xu, and S. Yu, “Computing the numerical scale of the linguistic term set for the 2-tuple fuzzy linguistic representation model,” IEEE Trans. Fuzzy Syst., vol. 17, no. 6, 2009, pp. 1366–1378.

19.    E. Herrera-Viedma, L. Martinez, F. Mata, and F. Chiclana, “A consensus support system model for group decision-making problems with multigranular linguistic preference relations,” IEEE Trans Fuzzy Syst., vol. 13, no. 5, 2005, pp. 644–658.

20.    R. -C. Wang and S. -J. Chuu, “Group decision-making using a fuzzy linguistic approach for evaluating the flexibility in a manufacturing system,” Eur. J. Oper. Res., vol. 154, no. 3, 2004, pp. 563–572.

21.    Z. Wu and J. Xu, “A concise consensus support model for group decision making with reciprocal preference relations based on deviation measures,” Fuzzy Set Syst., vol. 206, 2012a, pp. 58–73.

22.    E. H. Forman and S. I. Gass, “The analytic hierarchy process—An exposition,” Oper. Res., vol. 49, no. 4, 2001, pp. 469–486.

23.    N. Subramanian and R. Ramanathan, “A review of applications of analytic hierarchy process in operations management,” Int. J. Prod. Econ., vol. 138, no. 2, 2012, pp. 215–241.

24.    O. S. Vaidya and S. Kumar, “Analytic hierarchy process: An overview of applications,” Eur. J. Oper. Res., vol. 169, no. 1, 2006, pp. 1–29.

25.    E. Forman and K. Peniwati, “Aggregating individual judgments and priorities with the analytic hierarchy process,” Eur. J. Oper. Res., vol. 108, no. 1, 1998, pp.
165–169.

26.    R. Ramanathan and L. S. Ganesh, “Group preference aggregation methods employed in AHP: An evaluation and an intrinsic process for deriving members’ weightages,” Eur. J. Oper. Res., vol. 79, no. 2, 1994, pp. 249–265.

27.    T. L. Saaty, “Fundamentals of decision making and priority theory with the analytic hierarchy process,” RWS Publications, Pittsburgh, 1994a.

28.    Y. Xu, K. W. Li, and H. Wang, “Distance-based consensus models for fuzzy and multiplicative preference relations,” Inform. Sciences, vol. 253, 2013, pp. 56–73.

29.    S. M. Lee, “Goal programming for decision analysis,” Philadelphia: Auerbach, 1972.

30.    R. L. Keeney and H. Raiffa, “Decisions with multiple objectives: Preferences and value tradeoffs,” New York: Wiley, 1976.

31.    T. L. Saaty, “A scaling method for priorities in hierarchical structures,” J. Math. Psychol., vol. 15, no. 3, 1977, pp. 234–281.

32.    T. L. Saaty, “Decision making for leaders,” Belmont, CA: Lifetime Learning Publications, Division of Wadsworth, 1982.

33.    K. D. Lawerence and G. Kleinman (Eds.), “Applications of Management Science,” vol. 15, Emerald Group Publishing, 2012.

34.    D. Golmohammadi, “A decision making model for evaluating suppliers by multi-layer feed forward neural networks,” PeoQuest, 2007.

35.    M. J. Liberatore, B. R. Myers, R. L. Nydick, and H. J. Weiss, “Revisiting the ranking of outstanding professional sports records,” J. Sport. Anal., vol. 2, no. 1, 2016, pp. 1–18.

36.    J. S. Dyer, “Remarks on the analytic hierarchy process,” Manage. Sci., vol. 36, no. 3, 1990a, pp. 249–258.

37.    J. S. Dyer, “A clarification of ‘remarks on the analytic hierarchy process,”’ Manage. Sci., vol. 36, no. 3, 1990b, pp. 274–275.

38.    P. T. Harker and L. G. Vargas, “Reply to ‘remarks on the analytic hierarchy process’ by J. S. Dyer,” Manage. Sci., vol. 36, no. 3, 1990, pp. 269–273.

39.    T. L. Saaty, “An exposition of the AHP in reply to the paper ‘remarks on the analytic hierarchy process,”’ Manage. Sci., vol. 36, no. 3, 1990, pp. 259–268.

40.    R. L. Winkler, “Decision modeling and rational choice, AHP and utility theory,” Manage. Sci., vol. 36, no. 3, 1990, pp. 247–248.

41.    Expert Choice, Inc. Expert Choice for Windows, Version 9.0, Pittsburgh, 1995, P.A.

42.    B. L. Golden, E. A. Wasil, and P. T. Harker (eds.), “The analytic hierarchy process,” New York, Springier-Verlag, 1989.

43.    F. Zahedi, “The analytic hierarchy process—A survey of the method and its applications,” Interfaces, vol. 16, no. 4, 1986, pp. 96–108.

44.    L. G. Vargas and F. Zahedi (eds.), “Special issue on the analytic hierarchy process,” Math. Comput. Model., vol. 17, no. 4–5, 1993.

45.    E. A. Wasil and B. L. Golden (eds.), “Public sector applications of the analytic hierarchy process,” Socio. Econ. Plan. Sci., vol. 25, no. 2, 1991, pp. 87–88.

46.    F. A. Lootsma, “Saaty’s priority theory and the nomination of a senior professor in operations research,” Eur. J. Oper. Res., vol. 4, no. 6, 1980, pp. 380–388.

47.    T. L. Saaty and V. Ramanujam, “An objective approach to faculty promotion and tenure by the analytic hierarchy process,” Res. High. Educ., vol. 18, no. 3, 1983, pp. 311–331.

48.    M. D. Trout and S. K. Tadisina, “The analytic hierarchy process as a model base for a merit salary recommendation system,” Math. Comput. Model., vol. 16, no. 5, 1992, pp. 99–105.

49.    V. M. R. Tummala and P. P. Sanchez, “Evaluating faculty merit awards by analytic hierarchy process,” Model., Simulat. Control C: Environ., Biomed., Hum. Soc. Syst., vol. 11, no. 4, 1988, pp. 1–13.

50.    T. L. Saaty and L. R. Rogers, “Higher education in the United States (19852000): Scenario construction using a hierarchical framework with eigenvector weighting,” Socio. Econ. Plan. Sci., vol. 10, no. 6, 1976, pp. 251–263.

51.    Arbel, “A university budget problem: A priority-based approach,” Socio. Econ. Plan. Sci., vol. 17, no. 4, 1983, pp. 181–189.

52.    N. K. Kwak and C. B. Diminnie, “A goal programming model for allocating operating budgets of academic units,” Socio. Econ. Plan. Sci., vol. 21, no. 5, 1987, pp. 333–339.

53.    R. P. Hope and J. A. Sharpe, “The use of two planning decision support systems in combination for the redesign of an MBA information technology programme,” Computers and Oper. Res., vol. 16, no. 4, 1989, pp. 325–332.

54.    S. K. Tadisina and V. Bhasin, “Doctoral program selection using pairwise comparisons,” Res. High. Educ., vol. 30, no. 4, 1989, pp. 403–418.

55.    J. R. Canada, E. H. Frazelle, R. K. Roger, and E. MacCormac, “How to make a career choice: The use of the analytic hierarchy process,” Ind. Manage., vol. 27, no. 5, 1985, pp. 16–22.

56.    D. Anderson, “An introduction to Management Science: Quantitative approaches to decision making,” Publisher: Thomas R. Williams, 2003.

57.    D. R. Anderson, D. J. Sweeney, T. A. Williams, J. D. Camm, and R. K. Martin, “An introduction to Management Science: Quantitative approaches to decision making,” revised. Cengage Learning, 2011.

58.    F. G. M. Al-Azab and M. A. Ayu, “Web based multi criteria decision making using AHP method,” Int. Conf. Info. Comm. Tech. Muslim World (ICT4M), IEEE, 2010, pp. A6–A12.

59.    D. J. Jakóbczak, “Analyzing risk through probabilistic modeling in Operations Research,” October 2015, DOI: 10.4018/978-1-4666-9458-3.

60.    “Analytic hierarchy process [Wikipedia],” [Online] Available: https://en.wikipedia.org/wiki/Analytic_hierarchy_process [Accessed on October 23, 2016].

61.    F. P. G. Márquez and B. Lev (Eds.), Advanced Business Analytics, Springer, 2015.

62.    C. C. Frangos, K. C. Fragkos, I. Sotiropoulos, I. Manolopoulos, and E. Gkika, “Student preferences of teachers and course importance using the analytic hierarchy process model,” In Proc. World Congress on Eng. (WCE 2014), vol. 2, 2014.


99-105

www.blueeyesintelligence.org/attachments/File/fee/2checkout_download.html







































































































































































































































21.

Authors:

Prakash C. Sharma, Narendra S. Chaudhari

Paper Title:

Investigation of Satisfiability Based Solution Approach for Graph Coloring Problem

Abstract: Graph k-colorability (for k ≥ 3) problem (GCP) is a well-known NP-Complete problem. There are many approaches proposed to solve graph coloring problem till date. There is an alternative approach to solve it efficiently by Satisfiability which is first known NP-Complete problem. We can reduce any NP-complete problem to/from SAT. Reduction from graph k-colorability problem to satisfiability is an important concept to solve it using efficient SAT solver. In this paper, we are presenting a polynomial 3-SAT encoding technique for k colorable graph. Our formulation generates total (((k-2)*|V| ) + (k*|E|) ) clauses in 3-CNF for k-colorable graph. We tested our encoding formulation approach on different graph coloring instances of DIMACS[8][9] and then investigated the solution of graph coloring problem as a decision problem based on SAT approach using powerful SAT solver Minisat 2.2.

Keywords:
3-SAT, CNF, DNF, graph coloring, NP-Complete, k-colorable, chromatic number, DIMACS.


References:

1.       Prakash C Sharma and Narendra S Chaudhari, “Polynomial 3-SAT Encoding for K-Colorability of Graph”, IJCA Special Issue on Evolution in Networks and Computer Communications (1): 2011, pp 19-24
2.       Garey, M. R. and Johnson, D. S., Computers and Interactability: A Guide to the Theory of NP-Completeness, Freeman, San Francisco, 1979.

3.       S. A. Cook, “The Complexity of Theorm Proving Procedures,” in Proceeding of the ACM Symposium on the Theory of Computing, 2004, pp 151-158.

4.       Koen Claessen, Niklas Een, Mary Sheeran and Niklas Sorensson, “SAT-solving in practice”, Proceedings of the 9th International Workshop on Discrete Event Systems Goteborg, Sweden, pp 61-67,May 28-30, 2008.

5.       Prakash C. Sharma and Narendra S Chaudhari, “A graph coloring approach for channel assignment in cellular network via propositional satisfiability”, International Conference on Emerging Trends in Networks and Computer Communications (ETNCC) at Udaipur,  22-24 April 2011, pp 23-26

6.       Alexander Tsiatas, “Phase Transitions in Boolean Satisfiability and Graph Coloring”, May 2008, Department of Computer Science, Cornell University,(www.cseweb.ucsd.edu/users/atsiatas/phase.pdf).

7.       L. Adleman and K. Manders, “Reducibility, randomness and intractability (abstract)”, in STOC 77: Proceedings of the ninth annual ACM symposium on Theory of computing. New York NY, USA: ACM Press, 1977, pp. 151-163.

8.       DIMACS Implementation Challenges, http://dimacs.rutgers .edu/Challenges/

9.       Petersen graph, http://en.wikipedia.org/wiki/ Petersen _graph

10.    N. Een and N. Sorensson. An extensible sat solver. In Proc. of the 6th Int. Conference onTheory and Applications of Satisfiability Testing, 2003.

11.    N. Een and N. Sorensson. MiniSat v1.13 - A SAT Solver with Conict-Clause Minimization. System description for the SAT competition 2005.

12.    The MiniSAT page by Niklas Een and N Sorensson. http://minisat.se/

13.    MiniSAT User Guide: How to use the MiniSAT SAT Solver by David A. Wheeler. http://www.dwheeler.com/ essays/minisat-user-guide.html

14.    Computational Series: Graph Coloring and Its Generalizations, http://mat.gsia.cmu.edu/COLOR04.

15.    E. Malaguti, P. Toth, “A survey on vertex coloring problems”, International Transactions in Operational Research 17, 2010, pp 1–34.

16.    W.K Hale, “Frequency Assignment: Theory and Applications”, in IEEE Proceeding, Vol.68, no.12, 1980, pp. 1497-1514.


106-112

www.blueeyesintelligence.org/attachments/File/fee/2checkout_download.html