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Volume-4 Issue-6: Published on January 05, 2015
14
Volume-4 Issue-6: Published on January 05, 2015
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S. No

Volume-4 Issue-6, January 2015, ISSN: 2231-2307 (Online)
Published By: Blue Eyes Intelligence Engineering & Sciences Publication Pvt. Ltd. 

Page No.

1.

Authors:

Aginam C. H, Nwakaire Chidozie, Nwajuaku A.I

Paper Title:

Engineering Properties of Lateritic Soils from Anambra Central Zone, Nigeria

Abstract: This study was carried out to investigate the geotechnical properties of lateritic soils from Anambra Central senatorial zone of Nigeria. Four samples were collected from four different locations in the zone, namely, Neni, Nimo, Obeledu and Enugwu Ukwu and were designated as LAT-1, LAT-2, LAT-3 and LAT-4, respectively. The tests carried out on the soil samples include the Atterberg limit tests, particle size distribution analysis, specific gravity, compaction test using the British Standard Light (BSL) Compactive effort, and California Bearing Ratio (CBR) test as specified by the West African Standard (WAS). The tests revealed that all the samples are poorly graded. The liquid limits ranged from 28.85% to 35.7% while the plasticity indices ranged from 9.18% to 14.55%. The Maximum dry densities (MDD) and Optimum moisture contents (OMC) ranged from 1.77g/Cm3 to 1.98g/Cm3 and 9.5% to 14.6% respectively. The CBR values obtained were 28%, 27%, 25% and 22% respectively. Apart from the Neni sample which was classified as A-2-4 with the AASHTO classification, the other soils were classified as A-2-6 soils. All the samples were classified as SC (Clayey sands) according to USCS classification system.  It was concluded that the four lateritic soil samples were suitable for sub-grade and sub-base type 2, but should not be used in road construction as a base material. Stabilization of the soil was equally recommended.

Keywords:
California bearing ratio, compaction, Geotechnical properties, lateritic soil

References:

1.              Abebaw, Z., (2005). Basic Engineering Properties of Lateritic Soils Found in Nejo – Mendi Road Construction Area, Welega. Pp. 1-11.
2.              Adekoya, J.A.(1987). Preliminary Geological and Geotechnical Study of Lateritic Weathering Profiles Derived from Banded Gneiss in the Ibadan Area, Southwest Nigeria. Proceedings of 9th Regional Conference for Africa on Soil Mechanics and Foundation Engineering, Lagos, Nigeria. Pp:21-30.

3.              ASTM (2004). Standard Test Method for Liquid limit, Plastic Limit, and Plasticity Index of Soils. D 4318 – 00. Annual Book of ASTM standards. Section 4, Construction. Soil and Rock (I); Baltimore, Md, U.S.A. volume. 04.08.

4.              Bayewu, O.O., (2012).Petrographic and geotechnical properties of Lateritic Soils developed over different parent rocks in Ago-Iwoye area, Southwestern Nigeria. Int. Journal of Applied Sciences and Engineering Research, 1(4):584-594.

5.              BS 1377 (1990). Methods of Test for Soil for Civil Engineering. British Standard Institution, London.

6.              Buchanan, C.(1807).  Laterite Bauxite. Elsevier, Amster-dam, Oxford, New York.

7.              Federal ministry of works and housing, (1997). “General specifications for roads and bridges.” volume II. Federal highway department: Lagos Nigeria. Pp.145.

8.              Gidigasu, M.D. (1976). Laterite Soil Engineering Pedogenesis and Engineering Principles; Elserier Scientific Publishing company, Amsterdam, New York.

9.              Hamilton, R.(1964). Microscopic Studies of Laterite Formation. A.Jungerius(Editor), Elserier, Amsterdam, Pp:269-278.

10.           Ikiensinma, A. G., (2005). Slope Stability Analysis of Laterite Soil Embankments. Pp.7-15.

11.           Jiregna, D., (2008). Detail Investigation on Index Properties of Lateritic Soils: The Case of Nedjo-Mendi-Assosa. Pp.5-14.

12.           Malomo, S. (1989). Micro structural Investigation on Lateritic Soils. International Association of Engineering Geology, Bullettin 39:105-109.

13.           Nnadi, G. (1987). Geotechnical Predictions from Hydraulic Conductivity Tests. 19th Annual Conference of Nigerian Society of Agric Engineers, Owerri Nigeria.

14.           Northmore, K. J., Culshaw M.G., Hobbs P. R. N., Hallam J. R., Entwisle D. C., (1992). Engineering geology of tropical red clay soils. U.K.: British geological survey. Pp 1-3.

15.           Ogunsenwo, O. (1989). CBR and Shear strengths of Compacted Lateritic Soils from Southwestern Nigeria. Quarterly Journal, Engineering Geology, London. Vol 22:317-328.

16.           Osinubi, K.J. (1998) “Influence of Compactive Efforts and Compaction Delays on Lime-treated Soil”. Journal of Transport Engineering, ASCE, 124(2), 149-155.

17.           Proctor, R.R. (1933). Design and Construction of Rolled Earth Dams. English News Record, Aug.31, Sept. 7, Sept.21, and Sept.28, Pp 245-248, 286-289, 341-351, and 372-376, respectively.

18.           Rahardjo, H., Aung, K.K., Leong, E.C., and  Rezam, R.B.(2004). Characteristics of Residual Soils in Singapore as Formed by Weathering. Journal of Engineering Geology, 73:157-169.

19.           Rowe, K. (2000). Geotechnical and Geoenvironmental Engineering Handbook; Kluver Academic Publishers.

20.           Sergeya, Y.M., Grebowsaka-Oleszawka, B., Osipov, V.I., and Sokolov, V.N. (1978). Types of Microstructure of Clayey Soils. Proceedings III International Conference IAEG, Madrid.

21.           Tuncer, E.R., and Lohnes, R.A. (1977). An Engineering Classification for Certain Basalt-derived lateritic Soils. Engineering Geology, 11:319-339.

22.           Venkatramaiah, C. (2006). Geotechnical Engineering, Revised 3rd Edition, New Age International Publishers, New Delhi.


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2.

Authors:

Ammar Saddik Dahlan, Mahmoud Ahmad Eissa

Paper Title:

The Impact of Day Lighting in Classrooms on Students' Performance

Abstract:       The study examines daylight and other features of indoor environment of classrooms on students' learning over an academic year at selected faculties at King Abdul-Aziz University campus at Jeddah, Saudi Arabia. Correlation analysis is used to compare the performance of 400 students in 20 classrooms at the selected faculties. The classrooms were on different floors of educational buildings. A statistical model was used to investigate the link between Daylight in classrooms and students’ performance in their classrooms, despite the fact of existence of traditional descriptive learning variables. Other elements including, thermal comfort, Indoor air quality, acoustics and artificial light are examined to indicate any possible effect to students’ performance. Further investigation was made which include interviews with teaching staff to examine the effect on classroom daylight on students’ academic performance.

Keywords:
  Daylight, classrooms, educational buildings, artificial lighting, indoor environment, energy


References:

1.              Alpin Yener, “Daylight Analysis in Classrooms with Solar Control”, Architectural Science Review, Volume 45, Issue 4, 2002
2.              Kibert CJ. Sustainable construction; Green building design and delivery. 2nd ed. New Jersey: John Wiley & Sons, Inc., 2008.

3.              Liberman J. Light medicine of the future. New Mexico: Bear & Company Publishing, 1991.

4.              Collins BL. Windows and people: A literature survey. Washington, DC: U.S. Government Printing Office, 1975.

5.              Drews D. Zimmerman Design Group. Personal communication, 29 June, 2001.

6.              Grocoff, P. Avant-Garde Lighting Design. Personal communication, 5 July, 2001.

7.              McCreey, John; Hill, Timothy E. School Planning and Management, February 1, 2005.

8.              Patricia P, Conway S, and Epstein K. Daylighting in schools: Improving student performance and health at a price schools can afford. Paper presented at the American Solar Energy Society Conference Madison, WI, June 2000.

9.              Creating quality cities. The Official Newsletter of the Association of Idaho Cities, March 2004.

10.           Degro J. School experiments with a luxmeter. Institute of Physics and IOP Publishing May 2007; 3.


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3.

Authors:

Kaveri Jagtap, Chandraprabha. A. Manjare

Paper Title:

An Ancient Degraded Images Revamping Using Binarization Technique

Abstract:        Revamping of ancient degraded document images is a grueling task due their foreground text and background which is degraded due to uneven illumination, dust, water marks, smear, strain, ink bleed and low contrast etc. The proposed Binarization technique addresses this problem by using adaptive image contrast which is a combination of the local image gradient and local image contrast that is stoic to text and background variation. In the proposed technique, for an input ancient degraded document image an adaptive contrast map is first constructed. The contrast map is then binarized and combined with Canny’s edge map to recognize the text stroke edge pixels. The text of document is further segmented by a local threshold that is concluded based on the intensities of detected text stroke edge pixels within a local window. Dataset of different languages like Modi, Marathi and English are used as input in handwritten and printed form. Modi, Marathi, English database are from year 1908, 1957, 1922.The proposed system is simple, required minimum parameter tuning, and give the superior performance compared with other techniques.

Keywords:
   Document Image Processing, Document Analysis, Pixel Classification, Degraded Document Image Binarization, Adaptive Image Contrast.


References:

1.              J. Sauvola and M. Pietikainen, “Adaptive document image binarization,” Pattern Recognition, vol. 33, no. 2, pp. 225–236, 2000.
2.              C. Wolf and D. Doermann, “Binarization of Low Quality Text using a Markov Random Field Model,” International Conference on Pattern Recognition, pp. 160–163, 2002.

3.              S. Kumar, R. Gupta, N. Khanna, S. Chaudhury, and S. D. Joshi, “Iterative multimodel subimage binarization for handwritten character segmentation,” IEEE Transactions on Image Processing, vol. 13, pp. 1223–1230, September 2004

4.              S. Nicolas, J. Dardenne, T. Paquet, and L. Heutte, “Document image segmentation using a 2D conditional random field model,” International Conference on Document Analysis and Recognition, pp. 407–411, September 2007.

5.              T. Lelore and F. Bouchara, “Document image binarisation using markov field model,” International Conference on Document Analysis and Recognition, pp. 551–555, July 2009.

6.              Patvardhan, C., A. K. Verma, and C. Vasantha Lakshmi. "Document image denoising and binarization using Curvelet transform for OCR applications."Engineering (NUiCONE), 2012 Nirma University International Conference on. IEEE, 2012.

7.              Papavassiliou, Vassilis, et al. "A Morphology Based Approach for Binarization of Handwritten Documents." Frontiers in Handwriting Recognition (ICFHR), 2012 International Conference on.IEEE, 2012.

8.              Su, Bolan, Shijian Lu, and Chew Lim Tan. "A learning framework for degraded document image binarization using Markov random field." Pattern Recognition (ICPR), 2012 21st International Conference on.IEEE, 2012.

9.              Rabeux, V., et al. "Quality evaluation of ancient digitized documents for binarization prediction." Document Analysis and Recognition (ICDAR), 2013 12th International Conference on.IEEE, 2013.

10.           Wagdy, M., Ibrahima Faye, and DayangRohaya. "Fast and efficient document image clean up and binarization based on retinex theory." Signal Processing and its Applications (CSPA), 2013 IEEE 9th International Colloquium on.IEEE, 2013

11.           KEFALI, Toufik SARI, Mokhtar SELLAMI, “Evaluation of several binarization techniques for old Arabic documents images”

12.           Gatos, K. Ntirogiannis, and I. Pratikakis, “ICDAR 2009 document image binarization contest (DIBCO 2009),” in Proc. Int. Conf. Document Anal. Recognit., Jul. 2009, pp. 1375–1382.

13.           Pratikakis, B. Gatos, and K. Ntirogiannis, “H-DIBCO 2010 handwritten document image binarization competition,” in Proc. Int. Conf. Frontiers Handwrit. Recognit., Nov. 2010, pp. 727–732.

14.           S. Lu, B. Su, and C. L. Tan, “Document image binarization using background estimation and stroke edges,” Int. J. Document Anal. Recognition, vol. 13, no. 4, pp. 303–314, Dec. 2010.

15.           Bolan Su, Shijian Lu Member and Chew Lim Tan, “A Robust Document Image Binarization Technique for Degraded Document Images”, in IEEE Transaction on Image Processing, Vol. 22 No. 4, April 2013.

16.           Manju Joseph, Jijina K.P, “An Improved Contrast Image Based Document Imaged Binarization Technique for Degraded Document Images”, Vol. 04, Issue 04, April 2014.

17.           Prashali Chaudhary and B.S. Saini, “An Effective and Robust Technique For The Binarization Of Degraded Document Images”, vol. 03, Issue. 06, June 2014.

18.           L. Eikvil, T. Taxt, and K. Moen, “A fast adaptive method for binarization of document images,” in Proc. Int. Conf. Document Anal. Recognit., Sep. 1991, pp. 435–443.

19.           J. Parker, C. Jennings, and A. Salkauskas, “Thresholding using an illumination model,” in Proc. Int. Conf. Doc. Anal. Recognit., Oct. 1993, pp. 270–273.

  

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4.

Authors:

Prakash Jadhav, G. K. Siddesh

Paper Title:

Near Lossless Compression of Video Frames Using Soft Computing Technologies in Immersive Multimedia

Abstract:   Compression of Video Frames is a heavily researched domain in Digital TV Technology and Multimedia applications and hundreds of researchers have experimented with various techniques of transform coding and quantization mechanisms with varied results. Despite this fact, there is still a tremendous amount of scope for better compression schemes that seek to reduce the utilized band of the spectrum. In real time applications such as Digital TV and streaming Multimedia applications, time plays a crucial role and a successful implementation usually makes a compromise between factors such as (1) quality of reconstructed frames, (2) amount of utilized band owing to compression and (3) ability of the system to cope with increasing frame rates and advanced video profiles that are creeping into Digital TV Standards. It is important to observe that methodologies employed in achieving successful compression based on both inter and intra-frame redundancies rely very heavily on the frequency-domain redundancies generated by transform coding techniques and it is imperative that compression techniques place a great amount of emphasis on the correlation that can generated on a sub-image basis. Noise in images tends to decrease the correlation and noisy frames tend to compress less. Our objective in this research program is to focus on ways and means of increasing the redundancies by employing Linear Neural Network techniques with feed-forward mechanisms. Since quantization plays a major role in the amount of compression generated and the quality of the reconstructed frames, adaptive quantization based on a PSNR threshold value is employed so that best compression with a guaranteed reconstructed quality is obtained. Our research program targets to achieve the objectives: (1) better compression ratios with even fairly noisy frames (2) better quality of reconstructed frames in terms of very large PSNR and RMS Error tending towards values extremely small and nearer to 0 and (3) honoring the time constraints imposed by frame rates.

Keywords:
    Neural Networks, Peak Signal to Noise Ratio (PSNR), Root Mean Square Error (RMS), Quantization, Discrete Cosine Transform (DCT), Burrows Wheeler Transform (BWT), Rosseta Vector, bandwidth.


References:

1.                Ko Nishino, Yoichi Sato and Katsushi Ikeuchi, “Eigen-Texture Method: Appearance Compression and Synthesis Based on a 3D Model” IEEE Transactions On Pattern Analysis And Machine Intelligence, Vol. 23, No. 11, pp 1257-1265, November 2010
2.                Sang-Uok Kum, Ketan Mayer-Patel, Henry Fuchs, “Real-Time Compression for Dynamic 3D Environments” ACM, MM’03, pp – 2-8, November 2003

3.                G. Nur Yilmaz, H.K. Arachchi, S. Dogan, A. Kondoz “3D video bit rate adaptation decision taking using ambient illumination context” Engineering Science and Technology, an International Journal 17 pp 105-115 may 2014

4.                Jacky C.P. Chan, Howard Leung, Jeff K.T. Tang, and Taku Komura, “A Virtual Reality Dance Training System Using Motion Capture Technology”, IEEE Transactions on Learning Technologies, Vol. 4, No. 2, pp- 187-195,  April-June 2011

5.                G Boopathi, Dr.S.Arockiasamy, “An Image Compression Approach using Wavelet Transform and Modified Self Organizing Map” IJCSI International Journal of Computer Science Issues, Vol. 8, Issue 5, No 2, pp- 323-330, September 2011

6.                Dong Zhang, Bin Li, Houqiang Li, “Intermedia-Based Video Adaptation System: Design and Implementation”, TSINGHUA SCIENCE AND TECHNOLOGY, Volume 17, Number 2, pp113-127, April 2012

7.                Chinnusamy.K, Abinaya Preethi.K,” Performance and Analysis of Video Streaming of Signals in Wireless Network Transmission”, IOSR Journal of Electronics and Communication Engineering (IOSR-JECE), Volume 9, Issue 1, Ver. I PP 11-15 Jan. 2014,

8.                Gary J. Sullivan, Jens-Rainer Ohm et,al. “Overview of the High Efficiency Video Coding (HEVC) Standard” IEEE Transactions On Circuits And Systems For Video Technology, Vol. 22, No. 12, Pp 1647-1668, December 2012.

9.                Gulistan Raja1and Muhammad Javed Mirza, “In-loop Deblocking Filter for H.264/AVC Video” Advanced Engineering Research Organization, Wah Cantt.

10.             Mahsa T. Pourazad, Colin Doutre, Maryam Azimi, And Panos Nasiopoulos, “HEVC: The New Gold Standard For Video Compression” IEEE Consumer Electronics Magazine    , Digital Object Identifier 10.1109 / Mce.2012.2192754, pp 36-46  22 June 2012

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5.

Authors:

Lakshmi D Kurup, Chandni Chandawalla, Zalak Parekh, Kunjita Sampat

Paper Title:

Comparative Study of Eucalyptus, Open Stack and Nimbus

Abstract:    Cloud computing is a Service Oriented Architecture which reduces information technology overhead for the end-user and provides great flexibility, reduced total cost of ownership, on-demand services and many other benefits. Hence it delivers all IT related capabilities as services rather than product .Services on cloud are divided into three broad categories: Software as a Service, Infrastructure as a Service & Platform as a Service. Same as services cloud is also classified as Private Cloud, Public Cloud & Hybrid Cloud. Private cloud is gaining popularity, not only among large organizations but also small and medium enterprises. To deploy public or private cloud there are many open source software platforms  available such as Eucalyptus, Nimbus, OpenStack, Open Nebula,  Cloud Stack and Amazon Web Services. In this paper, we provide a comparative study of three open source cloud management platforms: Eucalyptus, OpenStack and Nimbus. We believe that the comparison presented in this paper would benefit enterprises as well as research institutes in selecting best open source platforms to meet their technology demands.

Keywords:
   OpenStack, Cloud computing, Eucalyptus, Nimbus, Private Cloud, Public Cloud, Hybrid Cloud.


References:

1.                Eucalyptus home page, http://open.eucalyptus.com/, march, 2010
2.                Amazon S3 API,

3.                http://docs.amazonwebservices.com/AmazonS3/latest/dev/

4.                Amazon EC2 API,

5.                http://docs.amazonwebservices.com/AWSEC2/2009-04-04/DeveloperGuide/ Ubuntu cloud computing home page,

6.                http://www.ubuntu.com/business/cloud/overview Eucalyptus Enterprise home page, http://www.eucalyptus.com/

7.                D. Nurmi et al., “The Eucalyptus Open-Source Cloud- Computing System,” Cloud Computing and Applications 2008 (CCA 08), 2008;.

8.                Nurmi, d., wolski, r., grzegorczyk, c., obertelli, g., soman, s., youseff, l., and zagorodnov, d. Eucalyptus: a technical report on an elastic utility computing archietcture linking your programs to useful systems . Tech. Rep. 2008-10, university of california, santa barbara, october 2008

9.                P. T. Endo, G. E. Gon¸calves, J. Kelner, and D. Sadok. A Survey on Open-source Cloud Computing Solutions. Brazilian Symposium on Computer Networks and Distributed Systems, May 2010.

10.             Peter Sempolinski, Douglas Thain, "A Comparison and Critique of Eucalyptus, OpenNebula and Nimbus," cloudcom, pp.417-426, 2010 IEEE Second International Conference on Cloud Computing Technology and Science, 2010

11.             M. Chang, J. He, and E. Castro-Leon. Service orientation in the computing infrastructure. In SOSE ’06: Proceedings of the Second IEEE International Symposium on Service-Oriented System Engineering, pages 27–33, Washington, DC, USA, 2006. IEEE Computer Society.

12.             Eucalyptus network configuration,

13.             http://open.eucalyptus.com/wiki/EucalyptusNetworkConfiguration_v2.0

14.             Virtual Distributed Ethernet, http://vde.sourceforge.net RackSpace cloud hosting home page,

15.             http://www.rackspace.com/cloud/ State of the Cloud – January 2011,

16.             http://www.jackofallclouds.com/2011/01/state-of-the-cloud-january-201/

17.             OpenStack Tutorial, IEEE CloudCom, 2010 http://salsahpc.indiana.edu/CloudCom2010/slides/PDF/tutorials/OpenStackTutorialIEEECloudCom.pdf

18.             OpenStack compute home page,

19.             http://openstack.org/projects/compute/ Open Stack Administration Manual home page,

20.             http://docs.openstack.org/openstack-10compute/admin/content/ Nova’s Documentation, http://nova.openstack.org/

21.             Rabbit MQ home page, http://www.rabbitmq.com/ Open Virtual Switch home page, http://openvswitch.org/

22.             CloudAudit home page, http://www.cloudaudit.org/ The Globus alliance home page, http://globus.org/

23.             Keahey, K. “Nimbus: Open Source Infrastructure-as-a-Service Cloud Computing Software”, Workshop on adapting applications and computing services to multi-core and virtualization, CERN, Switzerland, 2009

24.             Nimbus home page, http://www.nimbusproject.org/docs/2.2/faq.html

25.             K. Keahey, T. Freeman. “Science Clouds: Early Experiences in Cloud computing for Scientific Applications,” Cloud Computing and Its Applications 2008 (CCA-08), Chicago, IL. October 2008

26.             W. Allcock, J. Bester, J. Bresnahan, A. Chervenak, L. Liming, and S. Tuecke, “GridFTP: Protocol Extension to FTP for the Grid,” Grid Forum Internet-Draft, March 2001 

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6.

Authors:

Mohammed Abdullah Alghamdi, Sunil G Bhirud, Afshar M. Alam

Paper Title:

Physician's Decision Process for Disease Diagnosis of Overlapping Syndrome in Liver Disease using Soft Computing Model

Abstract:     An understanding towards the overlapping syndromes is essential to cope up the liver disease with the paradigm shift which is underway. Autoimmune hepatitis (AIH), primary biliary cirrhosis (PBC) and primary sclerosing cholangitis (PSC) all belong to the family of autoimmune liver diseases. This can result in a transient phenotypic overlap or a combined syndrome with characteristics of both diseases. It demonstrates mixed clinical presentations of immune-mediated liver injury. Due to overlapping features of AIH, some patients connote such phenotype that leads to a dubious diagnosis of any disease. In some cases, this type of diagnosis system causes the patient’s death in the absence of well-validated diagnostic criteria. Some improvements in diagnosis instrumentation and automation that has become to capture experience of any veteran person, is needed. Simulation of such diagnosis experience is extremely important as it leads to knowledge discovery. In this paper, we gave a soft computing model based disease diagnosis system for overlapping syndrome of liver disease. It helped the in physician’s decision process that comes after long experience in new individual.

Keywords:
    AIH, PBC, PSC, physician’s, diagnostic, phenotypic, cholangitis.


References:

1.              , R.H.: An intelligent model for liver disease diagnosis. Artificial Intelligence in Medicine 47(1), 53–62 (2009)
2.              Lippincott Williams & Wilkins by Schi Eugene R.; Sorrell, M.F.M.W.C.: Schi’s Diseases of the Liver, 11th edition edn. Wiley-Blackwell (2011)

3.              British liver trust, (2009) [online]. available:http://www.britishlivertrust.org.uk/media-centre/facts-about- liver-disease/

4.              Trivedi, P.J., Hirschfield., G.M.: Review article: overlap syndromes and autoimmune liver disease. Alimentary pharmacology & therapeutics 36(6), 517–533 (2012)

5.              De, S.K., Biswas, R., Roy, A.R.: An application of intuitionistic fuzzy sets in medical diagnosis. Fuzzy Sets and Systems 117(2), 209–213 (2001)

6.              Nayak, R., Jain, L., Ting, B.: Artificial neural networks in biomedical engineering: a review. In: Asia-Pacific Conference on Advance Computation (2001). URL http://eprints.qut.edu.au/1480/

7.              Perantonis, S., Virvilis, V.: Dimensionality reduction using a novel neural network based feature extraction method. In: Neural Networks, 1999. IJCNN’99. International Joint Conference on, vol. 2, pp. 1195–1198. IEEE (1999)

8.              Tarr, G.L.: Multi-layered feedforward neural networks for image segmentation. Tech. rep., DTIC Document  (1991)

9.              Machine-learning-databases (last accessed: 7April 2005)

10.           Forsyth, R.S.: Bupa liver disorders dataset:UCI machine learning repository (last accessed: 10 july 2014).URL
https://archive.ics.uci.edu/ml/datasets/Liver+Disorders

11.           Lin, R.H.: An intelligent model for liver disease diagnosis. Artificial Intelligence in Medicine 47, 53–62 (2009)

12.           Liang, F.: Annealing stochastic approximation monte carlo algorithm     for neural network training. Machine Learning 68(3), 201–233 (2007)

13.           Rocha, M., Cortez, P., Neves, J.: Evolution of neural networks for classification and regression. Neurocom-puting 70(16), 2809–2816 (2007)

14.           Liao, Y.: Neural networks for pattern classification and universal approximation (2002)

15.           Cortes, Corinna, and Vladimir Vapnik. "Support-vector networks." Machine learning 20.3 (1995): 273-297.

16.           Neshat, M., Yaghobi, M., Naghibi, M., Esmaelzadeh, A.: Fuzzy expert system design for diagnosis of liver disorders. In: Knowledge Acquisition and Modeling, 2008. KAM’08. International Symposium on, pp. 252–256. IEEE (2008)

17.           Karthik, S., Priyadarishini, A., Anuradha, J., Tripathy, B.: Classification and rule extraction using rough set for diagnosis of liver disease and its types. Adv. Appl. Sci. Res 2(3), 334–345 (2011)

18.           Chaves, A., Vellasco, M.M.B.R., Tanscheit, R.: Fuzzy rule extraction from support vector machines. In:  Hybrid Intelligent Systems, 2005. HIS ’05. Fifth
International Conference on (2005)

19.           Shevked, Z., Dakovski, L.: Learning and classification with prime implicants applied to medical data diagnosis. In: Proceedings of the 2007 international conference on Computer systems and technologies, p. 103. ACM (2007)

20.           Steimann, F.: On the use and usefulness of fuzzy sets in medical ai. Artificial Intelligence in Medicine 21(1), 131–137 (2001)

21.           Friedrich Steimann, K.P.A.: A fuzzy medical data model. In: Proceedings of the 12th European Meeting on Cybernetics and Systems Research(World Scientific, Singapore,, vol. 1, p. 271278 (1994)

22.           Lin, J.J., Chang, P.C.: A particle swarm optimization based classifier for liver disorders classification. In: Computational Problem-Solving (ICCP), 2010 International Conference on, pp. 63–65. IEEE (2010)

23.           Chang, P.C., Lin, J.J., Liu, C.H.: An attribute weight assignment and particle swarm optimization algorithm for medical database classifications. Computer methods and programs in biomedicine 107(3), 382–392 (2012)


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7.

Authors:

M. Karthik, S. Vijayachitra

Paper Title:

Numerical Study on the Detailed Characterization of Ni-MH Battery Model for its Dynamic Behavior using Multi-Regression Analysis - MRA

Abstract:      A numerical study is presented in this paper to examine the dynamic behavior for the detailed characterization of commercially available Ni-MH battery. In the present study, a novel Multi-Regression Analysis (MRA) based model for the D-size HHR650D battery from panasonic is adopted to ascertain the charge and discharge characteristics along with its SoC estimation. Oxygen gas formation at the Ni electrode during charging and overcharging that affects the pressure variations inside the battery is essential to be analyzed for its characterization. Henceforth, the effect of battery charging conditions over the pressure and temperature variations are considered in the developed MRA model and the corresponding performance profiles subjected to recurrent load cycles are reported. Model validation of the steady state behavior is performed based on the benchmark data obtained from a 6.5Ah, 1.2V Nickel-Metal Hydride battery. The result obtained shows that the regression model responses fit well with the benchmark result. Moreover, the model can also predict pressure and temperature dynamics under a sudden change in charging and discharging states. The characterization results show that the proposed regression model of Ni-MH battery could be suited effectively for any kind of model based plug-in or hybrid electric vehicle technologies.

Keywords:
 Interpolation, Multi-Regression analysis, Ni-MH battery, SoC and voltage dynamics


References:

1.             Costlow, T. (2008). Lutz promotes energy conservation, criticizes politicians. Automotive Engineering International, Society of Automotive Engineers, 30-31.
2.             Burke, A. F. (2007). Batteries and ultracapacitors for electric, hybrid, and fuel cell vehicles. Proceedings of the IEEE, 95(4), 806-820.

3.             Gonder, J., Markel, T., (2007). Energy management strategies for plug-in hybrid electric vehicles. In: SAE World Congress & Exhibition.

4.             Markel, A. J., & Simpson, A. (2006). Plug-in hybrid electric vehicle energy storage system design. National Renewable Energy Laboratory.

5.             Barbarisi, O., Canaletti, R., Glielmo, L., Gosso, M., & Vasca, F. (2002, December). State of charge estimator for NiMH batteries. Proceedings of the 41st IEEE Conference on Decision and Control, 2, 1739-1744.

6.             Pierozynski, B. (2011). On the low temperature performance of nickel-metal hydride (NiMH) batteries. International Journal of Electrochemical Science, 6, 860-866.

7.             Quanshi, C., & Chengtao, L. (2005). Summarization of Studies on Performance Models of Batteries for Electric Vehicle. Journal of Automobile Technology, 37(3),,1-5.

8.             Karden, E., Mauracher, P., & Schöpe, F. (1997). Electrochemical modelling of lead/acid batteries under operating conditions of electric vehicles. Journal of power sources, 64(1), 175-180.

9.             Wang, C. Y., Gu, W. B., & Liaw, B. Y. (1998). Micro-Macroscopic Coupled Modeling of Batteries and Fuel Cells I. Model Development. Journal of the Electrochemical Society, 145(10), 3407-3417.

10.          Gu, W. B., Wang, C. Y., Li, S. M., Geng, M. M., & Liaw, B. Y. (1999). Modeling discharge and charge characteristics of nickel–metal hydride batteries. Electrochimica Acta, 44(25), 4525-4541.

11.          Tremblay, O., & Dessaint, L. A. (2009). Experimental validation of a battery dynamic model for EV applications. World Electric Vehicle Journal, 3(1), 1-10.

12.          Chen, M., & Rincon-Mora, G. A. (2006). Accurate electrical battery model capable of predicting runtime and IV performance. IEEE transactions on Energy conversion, 21(2), 504-511.

13.          Salameh, Z. M., Casacca, M. A., & Lynch, W. A. (1992). A mathematical model for lead-acid batteries. IEEE transactions on Energy conversion, 7(1), 93-98.

14.          Chen, M., & Rincon-Mora, G. A. (2006). Accurate electrical battery model capable of predicting runtime and IV performance. IEEE transactions on Energy conversion, 21(2), 504-511.

15.          Valvo, M., Wicks, F. E., Robertson, D., & Rudin, S. (1996, August). Development and application of an improved equivalent circuit model of a lead acid battery. In Energy Conversion Engineering Conference, Proceedings of the 31st Intersociety (Vol. 2, pp. 1159-1163). IEEE.

16.          Ceraolo, M. (2000). New dynamical models of lead-acid batteries. Power Systems, IEEE Transactions on, 15(4), 1184-1190.

17.          Barsali, S., & Ceraolo, M. (2002). Dynamical models of lead-acid batteries: implementation issues. Energy Conversion, IEEE Transactions on, 17(1), 16-23.

18.          Benini, L., Castelli, G., Macii, A., Macii, E., Poncino, M., & Scarsi, R. (2001). Discrete-time battery models for system-level low-power design. Very Large Scale Integration (VLSI) Systems, IEEE Transactions on, 9(5), 630-640.

19.          Jongerden, M. R. (2010). Model-based energy analysis of battery powered systems. University of Twente. CTIT Ph.D.-thesis Series No. 10-183, Netherlands.

20.          Serrao, L., Chehab, Z., Guezennee, Y., & Rizzoni, G. (2005, September). An aging model of Ni-MH batteries for hybrid electric vehicles. In Vehicle Power and Propulsion, 2005 IEEE Conference (pp. 8-pp). IEEE.

21.          Panasonic HHR 650D Ni-MH Battery: Individual Data Sheet for its discharge characteristics, Panasonic Inc.

22.          Kugu, E.; Sahingoz, O.K., "Simulation based multiple regression analysis of fuzzy logic crowd injury model," Application of Information and Communication Technologies (AICT), 2013 7th International Conference on , vol., no., pp.1,5, 23-25 Oct. 2013

23.          R. L. Ott, and M. Longnecker, translated by Z. Z. Zhang, “An introduction to statistical methods and data analysis,” Science Press: Beijing, pp. 583-589

24.          Kalkhajeh, Y. K., Arshad, R. R., Amerikhah, H., & Sami, M. (2012). Comparison of multiple linear regressions and artificial intelligence-based modeling techniques for prediction the soil cation exchange capacity of Aridisols and Entisols in a semi-arid region. Australian Journal of Agricultural Engineering, 3(2), 39.

25.          Ross, M. M. (2001, September). A simple but comprehensive lead-acid battery model for hybrid system simulation. In Proceedings of PV Horizon: Workshop on Photovoltaic Hybrid Systems, Montreal, Canada (Vol. 10).

26.          Ramachandra Maddala, B. E. (2003). Modeling of hybrid electric vehicle batteries (Doctoral dissertation, Texas Tech University).

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8.

Authors:

Abdu Gumaei, Bandar Almaslukh, Nejmeddine Tagoug

Paper Title:

An Empirical Study of Software Cost Estimation in Saudi Arabia Software Industry

Abstract:       Cost estimation of software projects is a very important activity in software process development for shaping how much effort and time software projects required. Successful software projects depends mainly on an accurate cost estimation which is one of the most critical factors of good management decisions. Accurate cost estimation of software projects is not easy to do because it needs more experience and more knowledge about the nature and key features of projects. Especially as there are many cost estimation models available including algorithmic models, expert judgment model, estimating by analogy, and machine learning models. Saudi Arabia is one of the most outsourced country which has employed some methods for cost estimation. Incorrect cost estimations of projects in software development houses of this country prompted us research about the reasons for this problem. In this study, we concentrated on Saudi Arabia software companies and prepared a questionnaire to collect data with goal of exploring the software cost estimation models and analyzing the reasons which effect on the selection of software cost estimation models or methods in Saudi Arabia software industry.

Keywords:
 Software Projects, Cost Estimation, Expert Judgment Model, Algorithmic Models, Estimating by Analogy


References:

1.                D. Sanjeev, “Software Metrics – A Tool for Measuring Complexity”, International Journal of Software and Web Sciences, Vol. 1, No. 2, 2012, pp. 4-7.
2.                Daniel D. Galorath and Michael W. Evans, Software Sizing, Estimation, and Risk Management. Boca Raton, FL :Auerbach Publications, 2006, pp. 149-185. ISBN0849335930.

3.                D. Kashyap, A. Tripathi, A. K. Mishra, “Software Development Effort and Cost Estimation: Neuro-Fuzzy Model”, IOSR Journal of Computer Engineering (IOSRJCE), Vol. 2, Issue 4, July-Aug. 2012, pp. 12-14.

4.                K. K. Rao, G. S. V. P Raju, T. V. M. Rao, “Effort Estimations Based on Lines of Code and Function Points in Software Project Management”, IJCSNS International Journal of Computer Science and Network Security, Vol. 8,  No. 6, 2008, pp. 358-356.

5.                Attarzadeh and S. Hockow,, “Improving the Accuracy of Software Cost Estimation Model Based on New Fuzzy Logic Model”, World Applied Science Journal, Vol. 8, No. 2, 2010, pp. 177-184.

6.                V. BHATTACHERJEE, P. K. MAHANTI,  S. KUMAR, “Complexity Metric for Analogy Based Effort Estimation”, Journal of Theoretical and Applied Information Technology, Vol. 6, No. 1, 2009, pp. 001-008.

7.                M. Jorgensen, S. Grimstad, “Software Development Effort Estimation — Demystifying and Expert Estimation”, Berlin Heidelberg: Springer-Verlag, 2010,  ch. 26, DOI 10.1007/978-3-642-01156-6_26.

8.                Ch. Satyananda Reddy and KVSVN Raju, “An Improved Fuzzy Approach for COCOMO’s Effort Estimation using Gaussian Membership Function”,  Journal Of Software, Vol. 4, No. 5, 2009, pp. 452-459.

9.                P. Poscic, M. Pavlic, N. Vrcek, “Method for Estimating the Complexity of Designing Business Information Systems”, JIOS, Vol. 32, No. 2, 2008, pp. 123-136.

10.             W. Humphrey, Winning with Software: An Executive Strategy, Addison Wesley, 2002.

11.             M. Cohn,  Agile Estimating and Planning, Pearson Education Inc, 2006.

12.             V. Sharma, H. K. Verma, “Optimized Fuzzy Logic Based Framework for Effort Estimation in Software Development”, IJCSI International Journal of Computer Science Issues, Vol. 7, Issue 2, No. 2,  pp. 30-39, 2010.

13.             Idri, A. Zakrani, A. Zahi, “Design of radial basis function neural networks for software effort estimation”, IJCSI International Journal of Computer Science
Issues, Vol. 7, Issue 4, No. 3, July, pp.11-17, 2010.

14.             Information Technology Opportunities in the Kingdom of Saudi Arabia, An Executive Summary, 2002, Available: http://www.egovmonitor.com/reports/SA_ExecSumm.pdf.

15.             Talib and M. Malkawi, “Inward Strategy: An Optimal Solution to Build a Software Industry in Saudi Arabia”, IBIMA Business Review, Vol. 2011 (2011), Article ID 126226, 17 pages.

16.             D. Yang, Q. Wang, M. Li, Y. Yang, K.Ye, J. Du, “A survey on software cost estimation in the Chinese software industry”, In Proceedings of the Second ACM-IEEE international symposium on Empirical software engineering and measurement (ESEM), 2008, pp. 253-262.

17.             Z. Mansor, Z. M. Kasirun, S. Yahya, N. H. H. Arshad, “Current Practices of Software Cost Estimation Technique in Malaysia Context”, In Proceedings of the Springer-Verlag Berlin Heidelberg , ICIEIS , Part I, CCIS 251, 2011, pp. 566–574.

18.             Ali, “A Survey on Software Cost Estimation in the Pakistani Software Industry”, IJCER International Journal of Computer and Electronics Research, Vol.  3, Issue 1, 2014, pp. 13-19.

19.             Khalid, “An empirical investigation into the adoption of Software Engineering Practice in Saudi Arabia”, IJCSI International Journal of Computer Science Issues, Vol. 9, Issue 3, No. 3, 2012, pp. 328-332.

20.             Liming Wu, The Comparison of the Software Cost Estimating Methods, Available:

21.             2014.http://www.compapp.dcu.ie/~renaat/ca421/LWu1.html.


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9.

Authors:

Manish Srivastava, Sunil Agarwal, Ekta Sharma

Paper Title:

Design and Simulation of Perturb and Observe   MPPT Algorithm for 72 Cell Solar PV System

Abstract:        This paper present the design and performance of present stand-alone solar photovoltaic energy system with p and o based mppt algorithm. The system is designed for a solar-PV panels of 72 cell.P and O algorithms is used for efficient tracking of Maximum power point and comparative analysis is done with the conventional model without MPPT algorithm. . In this method, the array terminalvoltage is always adjusted according to the MPP voltage and the duty cycle is adjusted directly in the algorithm. The control loop is simplified, and the computational time for tuning controllergains is eliminated.The system as good dynamic response and good tracking accuracy. The system includes a solar panel, MPPT(maximum power point tracking ) controller, a dc-dc converter, and a single phase VSI(voltage source inverter). The proposed system is simulated using MATLAB/Simulink model.

Keywords:
  Gimbal, Digital Controller, Frequency Domain, Bode Plot, Accuracy.


Refenences:

1.              Azadeh Safari, and SaadMekhilef, “Simulation and Hardware Implementation of Incremental Conductance MPPT With Direct Control Method Using Cuk Converter,” IEEE Trans. Ind. Electron., vol. 58, no. 4, pp. 1154-1161, Apr. 2011.
2.              F. Liu, S. Duan, F. Liu, B. Liu, and Y. Kang, “A variable step size INC MPPT method for PV systems,” IEEE Trans. Ind. Electron., vol. 55, no. 7, pp. 2622–2628, Jul. 2008.

3.              Y.-C. Kuo, T.-J.Liang, and J.-F. Chen, “Novel maximum-power-point

4.              track controller for photovoltaic energy conversion system,” IEEE Trans. Ind. Electron., vol. 48, no. 3, pp. 594–601, Jun. 2009.

5.              B. Liu, S. Duan, F. Liu, and P. Xu, “Analysis and improvement of

6.              maximumpower point tracking algorithm based on incremental conductancemethod for photovoltaic array,” in Proc. IEEE PEDS, 2007, pp. 637–641.

7.              N. Mutoh and T. Inoue, “A control method to charge series-connected ultra electric double-layer capacitors suitable for photovoltaic generation systemscombining MPPT control method,” IEEE Trans. Ind. Electron., vol. 54, no. 1,pp. 374–383, Feb. 2007.

8.              Sathish Kumar Kollimalla Student Member, IEEE, Mahesh Kumar Mishra Senior Member, IEEE “Novel Adaptive P&O MPPT Algorithm for Photovoltaic System Considering Sudden Changes in Weather Condition” IEEE International conference on ICCEP,2013

9.              Moacyr Aureliano Gomes de Brito, Luigi Galotto, Jr., Leonardo Poltronieri Sampaio,Guilherme de Azevedo e Melo, and Carlos Alberto Canesin, Senior Member, IEEE “Evaluation of the Main MPPT Techniques for Photovoltaic Applications” IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, VOL. 60, NO. 3, MARCH 2013

10.           D. K. Sharma , Purohit G “Advanced Perturbation and Observation (P&O) based Maximum Power Point Tracking (MPPT) of a Solar PhotoVoltaic System”2012 5TH International Conference on Power Electronics

11.           Ali Chermitti, Omar Boukli-Hacene, Bencherif Mohamed “Improvement of the “Perturb and Observe” MPPT Algorithm in a Phot’ovoltaic System under Rapidly Changing Climatic Conditions” International Journal of Computer Applications (0975 – 8887) Volume 56– No.12, October 2012

12.           Yi-Hwa Liu,Rong-Ceng Leou ,Jeng-Shiung Cheng “Design and Implementation of a Maximum Power Point Tracking Battery Charging System for Photovoltaic Applications”power tech, 2012 russia.

13.           Peng Fang, Pu Wang “The Research of Photovoltaic Street Light Control System with MPPT” IEEE 2011 3rd International Workshop on Intelligent Systems and Applications (ISA)

14.           Mohammed A. Elgendy, Bashar Zahawi, and David J. Atkinson, "Assessment of Perturb and Observe MPPT Algorithm Implementation Techniques for PV Pumping Applications" IEEE Transactions on Sustainable Energy, Vol. 3, no. 1, January 2012

15.           Trishan Esram and Patrick L. Chapman, "Comparison of Photovoltaic Array Maximum Power Point Tracking Techniques", IEEE Transactions on Energy Conversion, vol. 22, no.2,June,2007.

16.           Moacyr A. G. de Brito, Luigi G. Junior, Leonardo P. Sampaio, Guilherme A. e Melo, Carlos A. Canes in, "Main Maximum Power Point Tracking (MPPT) strategies intended for Photovoltaics, IEEE Transaction on Energy Conversion, Vol. 22,No. 2,June2007


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10.

Authors:

Gelacio Castillo C, Martha P. Jiménez V, Aurora Aparicio C

Paper Title:

ASIC Thread for Decimal (BCD) Algorithm: A Tutorial on How Create a Thread and to Evaluate ISPMACH4256ZE CPLD

Abstract:         Here it is explained how can be designed by an easy form, and using HDL tool, a thread for implement the algorithm for natural binary format to decimal (BCD) format. In order to achieve that, here is released an explanation of such algorithm in a fast and needed way. In VHDL, structural style will be used for build each one modules for the Arithmetic Unit as well as those modules for Control Unit. The program is the set of instructions. Each instruction is a single operation as a sum, a shift, a comparison and so on. Every those instructions are carried out by a single module in VHDL. The memory to store the program it is implement by array of registers. That array is executed in a sequence by which is driven by a Program Counter (PC). The complete architecture it is explain step by step in order to it can be used as application note or a tutorial, and repeated by teachers, students and hobbyist. The complete processor it is builds in a single CPLD from Lattice Semiconductor. That is the ispMACH LC4256ZE 5TN144C device.

Keywords:
  Binary natural to decimal BCD format, tutorial on how design a thread


References:

1.             Intel. "Tutorial: Intel® Threading Building Blocks". Intel. Document Number 319872-009US. URL: http://www.intel.com/. "TBBtutorial.pdf". Intel: Developer Zone. https://software.intel.com/en-us/articles/intel-threading-building-blocks-tutorial-pdf.
2.             Sajjan G. Shiva, "Computer Organization, Design, and Architecture". Boca Raton, FL, 33487, USA. Ed. CRC Press Taylor and Francis Group 2014, pp. 185-214. International Standard Book Number 13: 978-1-4665-8554-6 (Book: Hardback). Purchased Book. It is not available from web site http://www.taylorandfrancis.com/.
Only referenced.

3.             Lattice Semiconductor. User’s Guide. ispMACH 4256ZE Breakout Board Evaluation Kit. March 2012 Revision: EB65_01.1. http://www.latticesemi.com/. Available from web site: http://www.latticesemi.com/en/Products/DevelopmentBoardsAndKits/ispMACH4256ZEBreakoutBoard.aspx.

4.             Lattice Semiconductor. Data Sheet DS1022. ispMACH 4000ZE Family. 1.8V In-System Programmable Ultra Low Power PLDs. August 2013. http://www.latticesemi.com/. From URL: http://www.latticesemi.com/en/Products/FPGAandCPLD/ispMACH4000ZE.aspx.

5.             Peter Alfke and Bernie New. Application Note. Serial Code Conversion between BCD and Binary. XAPP 029 October 27, 1997 (Version 1.1). Xilinx. Online available as XAPP 029.

6.             Lattice Semiconductor. Habel-HDL Reference Manual (ispLever Classic) 2003. Hillsboro, OR 97124. http://www.latticesemi.com/. Available from URL: http://www.latticesemi.com/en/Products/DesignSoftwareAndIP/FPGAandLDS/ispLEVERClassic.aspx


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11.

Authors:

Abdulameer K. Husain, Ayman A. Rahim A. Rahman

Paper Title:

A New Scheme for Pseudo Random Numbers Generator Based on Secret Splitting

Abstract:     This paper presents a secure scheme for generating a pseudo random numbers. The scheme is based on secret splitting of a piece of secure information which is used as a seed to the generator. In this scheme the procedure of splitting the secure information is performed according to a specified weight in such a way that each segment of the information piece takes a special weight depending on the priority of each part of the random number sequence. Another important concept used in this method is the agreement strategy applied to the secure information. By comparison of this scheme with other methods of generating pseudo random generation, it is found that there are a secure complex relationships among the elements of the random number sequences which are difficult to be discovered by most active attacks.

Keywords:
 Pseudo-Random, secret splitting, Cryptography, Secrecy, agreement.


References:

1.                D. Mathilde, T Jessy, R.Philiippe,” Methodology for the  Fault Analysis end Evaluation of True Random Number  Generator”, hal 00678001 version 1,Monaco , France, 11thMar 2012.
2.                Kinga, F Aline, E Christain,” Generation and Testing  of Random Numbers for Cryptographic Application”, Proceeding of Romania Academy, vol. 13, number 4/2012,pp 368 -377.

3.                D. Dilli, S. Madhu, “Design of a New Cryptography  Algorithm using Reseeding -Mixing Pseudo Random Number Generator”, IJITEE, vol. 52, Is sue 5, 2013.

4.                S. Martain, “Testing of True Random Number Generator Used in Cryptography”, IJCA, vol.2, issue4, 2012.

5.                W. Edward, Q. Christphor, T. Boateng, “ Comparative  Analysis of Efficiency of Fibonacci Random Number Generator Algorithm and Gaussian Random Number Generator Algorithm in Cryptography”, Computer Engineering and Intelligent System, vol. 4, No. 10, 2013.

6.                S. Juan, ” Statistical Testing of Random Number  Generators “, NIST company, 2012.

7.                Klein, “Attacks on the RC4 stream cipher,” Designs, Codes and Cryptography, vol. 48, no. 3, pp. 269–286, 2008.Cryptography, vol. 48, no. 3, pp. 269–286, 2008.

8.                Goldberg and D. Wagner, “Randomness and the Netscape browser,” Dr.Dobb’s Journal, pp. 66–70, 1996.

9.                Z. Gutterman, B. Pinkas, T. Reinman, “Analysis of the Linux Random Number Generator”. Proceedings of the 2006 IEEE Symposium on Security and Privacy, pp. 371–385,  2006.

10.             L. Dorrendorf, Z. Gutterman, B. Pinkas. “Cryptanalysis of the random number generator of the Windows operating system”. ACM T. Inform. System vol. 13(1), pp. 10:1–10:32 ,2009.

11.             L. Blum, M. Blum, and M. Shub, “A simple unpredictable pseudorandom number generator,” SIAM Journal on Computing, vol. 15, pp. 364–383, 1986 .

12.             G. Marsaglia, “A current view of random number generators”. Computing Science and Statistics: Proceedings of the XVIth Symposium on the Interface, pp. 3–10, 1985.

13.             G. Marsaglia, Diehard battery of tests of randomness, The Marsaglia random number CDROM, Department of Statistics, Florida State University, 1995.

14.             G. Marsaglia and W.W. Tsang, "Some difficult-to-pass tests of randomness", Journal of Statistical Software, Vol. 7, Issue 03, 2002.

15.             Claessen, M. Palka (2013) "Splittable Pseudorandom Number Generators using Cryptographic Hashing". Proceedings of Haskell Symposium 2013 pp. 47-58

16.             B. Heike. N., Steffen Scholze,Matthias Voegeler, Method of generating pseudo-random numbers, US 20090150467 A1 , Jun 11, 2009.

17.             E. Mohamed Nageb, R. Mahmud, Pseudo –Random Number Generator Using Deterministic Chaotic System , INTERNATIONAL JOURNAL OF SCIENTIFIC & TECHNOLOGY RESEARCH VOLUME 1, ISSUE 9, OCTOBER 2012 .

18.            B. Sohrab, A. Amir, A. Afshin, A.Samsudin, A novel dynamic model of pseudo random number generator, Journal of Computational and Applied Mathematics –J COMPUT APPL MATH, vol. 235, no. 12, pp. 3455-3463, 2011 .


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12.

Authors:

Ifeoma U. Ohaeri, Obeten O. Ekabua

Paper Title:

Generic Architecture for Biometric and Digital Forensic Analysis

Abstract:      Information Systems and Network Communications has become part of our everyday life. In recent times, there has been a massive growth in computer and electronic devices as well as network-based systems either for e-commerce, e-government or internal processes within organizations. Human beings can no longer be separated from electronic devices and the internet technology. The need for information security is increasing rapidly as a result of the amount of information made available on systems and networks which are connected on the internet. The dependence on information systems and the data that is stored, processed, and transmitted by them has recorded a tremendous increase in the rate of cyber-crimes; rise of information warfare, and threat of cyber terrorism which has even led many companies, organizations and even nations to thoroughly investigate the protection of its critical infrastructures from information, systems, and network based attacks. Therefore, it is very essential to provide an effective security measure and system that ensures the confidentiality, integrity, and availability of information systems, networks, and the services and resources made available. This can be achieved using biometric and digital forensic technology (BDFT).

Keywords:
 About four key words or phrases in alphabetical order, separated by commas.


References:

1.                L. Simson, and V. Garfinkel. “Digital Forensic Research: The next ten years.” Elsevier publications, pp. 64-69, 2010.
2.                D. Mellado, E. Fernández Medina, “A Common Criteria Based Security Requirements Engineering Process for the Development of Secure Information Systems.” International Journal of Computer Standards and Interfaces, vol. 29 (2), pp. 244 - 253, 2007.

3.                L. E Sánchez, A. S.O. Parra, “Managing Security and its Maturity in Small and Medium-sized Enterprises, “Journal of Universal Computer Science, vol. 15 (15), 3038 – 3058, 2009.

4.                Opdahl, A. L. and G. Sindre "Experimental comparison of attack trees and misuse cases for security threat identification." Information and Software Technology. In Press, Corrected Proof, 2008.

5.                B. Fal, A. M. "Standardization in information security management” Journal of Cybernetics and Systems Analysis, vol. 46, 181-184, 2010.

6.                X. Weiguan, W.Houkui, and H. Haoyi, .Donghong. “The Analysis of University Network Information Security System Based on Level Protection Model”, in Proceedings of the eight International Conference on computational Intelligence and Security, 2012, pp.609-614.

7.                N. F. Doherty, and H. Fulford "Aligning the Information Security Policy with the Strategic Information Systems Plan." Journal of Computers & Security, vol. 25(2):vol. 10, pp. 55-63, 2006.

8.                R. S George Weir. “Issues and Perspectives”, in Proceedings of the first International Conference on Cybercrime, Security, and Forensics,” 2011, pp. 720-728.

9.                K. Anil, and A,Ross.”Biometrics: A Tool for Information Security” IEEE Transactions on Information Forensic, and Security, vol. 1, June 2006.

10.             Daniel Mellado, Daniel Mellado.” An Overview of Current Information Systems Security Challenges and Innovations.”International Journal of Universal Computer Science, vol 18, pp.159-1608, 2012.

11.             M.F. Islam, M.I.Nasrul.”A Biometrics-Based Secure Architecture for Mobile Computing.” IEEE Transaction on Biometric Authentication, vol. 8, pp. 520-528, 2009.

12.             H. Singh Lallie. “An Overview of the Digital Forensic Investigation Infrastructure of India, Digital Investigation - Online publication. pp. 1742-2876, March, 2012.
13.             Martin, C. L. Wilson, and M. Przybocki, “An Introduction to Evaluating Biometric Systems,” IEEE publication for National Institute of Standard and Technology, pp. 158-156, 2000.

14.             S. Sargur, C. Huang, S. Harish, V. Shah. ”Biometric and Forensic Aspects of Digital Document Processing,” 2010, pp. 720-728.

15.             W. V. Staden, and M. S. Olivier. “On Compound Purposes and Compound Reasons for Enabling Privacy.” Journal of Universal Computer Science, vol. 17 (3), pp. 426-450, 2011.

16.            G. Pangalos, C. Linoudis, and I. Pagkalos.” The Importance of Cooperate Forensic Readiness in the Information Security Framework,” in Proceedings of the IEEE Workshop on Enabling Technologies infrastructure for Collaborative Enterprise” 2010, pp.12-18.

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13.

Authors:

Akshara Acharekar, Pushkar Adhikari, Pranita Doke, Spurti Shinde

Paper Title:

SABIS-Comparative Studies

Abstract:       S.A.B.I.S. (sEMG Accelerometer based Interactive System) is interactive software that would be used for interfacing compatible hardware systems that would help user have an entirely newer level of experience in the field of Human computer interactions. SABIS would be used to interface and calibrate systems that would be used as input for applications which would support such a system. Many aspects of human interactions can be captured using Accelerometers and surface Electromyogram signals, which give an idea regarding the movement that the user may wish to perform. This data can be sampled and converted as inputs for normal day to day computer applications which would integrate computer usage much more in the flow of human actions. Also, an extra level of research is being done to understand the use of a similar system for the elderly and disabled. This would add into an entirely new field of bioinformatics.

Keywords:
 Human Computer Interaction, Signal Processing, Electromyogram, Accelerometers.


References:

1.              Zhang, Xiang Chen, Associate Member, IEEE, Yun Li, Vuokko Lantz, Kongqiao Wang, and Jihai Yang “A Framework for Hand Gesture Recognition Based on Accelerometer and EMG Sensors on Accelerometer and EMG Sensors” IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS—PART A: SYSTEMS AND HUMANS, VOL. 41, NO. 6, NOVEMBER 2011.
2.              Zhaojie Ju, Member, IEEE, and Honghai Liu, Senior Member, IEEE “Human Hand Motion Analysis with Multisensory Information” IEEE/ASME TRANSACTIONS ON MECHATRONICS, VOL. 19, NO. 2, APRIL 2014.

3.              Arjan Gijsberts, Manfredo Atzori, Claudio Castellini, Henning Müller, and Barbara Caputo “Movement Error Rate for Evaluation of Machine Learning Methods for sEMG-Based Hand Movement Classification” IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING, VOL. 22, NO. 4, JULY 2014.

4.              Yun Li, Student Member, IEEE, Xiang Chen, Member, IEEE, Xu Zhang, Member, IEEE, Kongqiao Wang, and Z. Jane Wang, Member, IEEE, “A Sign-Component-Based Framework for Chinese Sign Language Recognition Using Accelerometer and sEMG Data” IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, VOL. 59, NO. 10, OCTOBER 2012.

5.              Anders Fougner, Member, IEEE, Øyvind Stavdahl, Member, IEEE, Peter J. Kyberd, Yves G. Losier, and Philip A. Parker, Senior Member, IEEE,” Control of Upper Limb Prostheses: Terminology and Proportional Myoelectric Control—A Review”, IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING, VOL. 20, NO. 5, SEPTEMBER 2012.

6.              Narisa N. Y. Chu, Senior Member, IEEE, Chang-Ming Yang, and Chih-Chung Wu,” Game Interface Using Digital Textile Sensors, Accelerometer and Gyroscope”, IEEE Transactions on Consumer Electronics, Vol. 58, No. 2, May 2012.

7.              Juan Cheng, Student Member, IEEE, Xiang Chen, Member, IEEE, and MinfenShen,” A Framework for Daily Activity Monitoring and Fall Detection Based on Surface Electromyography and Accelerometer Signals”, IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS, VOL. 17, NO. 1, JANUARY 2013.

8.              ZhaojieJu, Member, IEEE, and Honghai Liu, Senior Member, IEEE,” Human Hand Motion Analysis With Multisensory Information”, IEEE/ASME TRANSACTIONS ON MECHATRONICS, VOL. 19, NO. 2, APRIL 2014.

9.             Hairong Jiang, Bradley S. Duerstock, and Juan P. Wachs, Member, IEEE,”A Machine Vision-Based Gestural Interface for People With Upper Extremity Physical Impairments”, IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS: SYSTEMS, VOL. 44, NO. 5, MAY 2014.

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14.

Authors:

Geeta Hanji, M.V. Latte

Paper Title:

Reliable Filters for Impulse Noise Suppression Methods Implementation and Experimental Analysis

Abstract:    Improving the quaity of the noisy digital images is an important concern and a fundamental problem in the field of image processing. For the noisy images, quality improvement via noise suppression (or denoising) can be achieved with linear and nonlinear filters. Nonlinear filters being the winners in the list of denoising filters are more concerned about preserving the edge and other fine details of an image and are popularly used in the field of image restoration applications. In this paper, a simple and effective approach to suppress salt and pepper impulse noise from highly noised digital image is reviewed and implemented. Better modifications are suggested and incorporated to enhance its denoising capability. The presented work is based on X-ray filtering  scheme  used  in  Videoclient3,  one of popular image  processing  algorithms  used  in  PITZ  applications. X-ray filter in videoclient 3 compares the central (suspected to be noisy) pixel with neighbors to see if the central pixel needs replacement, and has a percentage to control how intensive the filtering process is. The estimation of the noisy pixels is obtained by local mean. The essential advantage  of  applying  X-ray filter  is  to  effectively suppress the heavy noise  and preserve  sharp  details  of  the  original  image. The simulation results on standard test images demonstrate the filter’s simplicity and better denoising capability compared to state of art filters.

Keywords:
 X-ray filter, Videoclient3, PITZ applications, noise   suppression


References:

1.             Gonzalez, R. and Woods, R. (1992) Digital Image Processing, Addison Wesley, Reading, MA.
2.             Maria Petrou,  Panagiota  Bosdogianni,  “Image  Processing:  The Fundamental”, John Wiley & Sons Ltd, 2000.

3.             Bovik  A.C, “Handbook  of  Image  and Video  Processing,” Academic Press, 2000.

4.             Weijia Xiong, Marek Otevrel, ”Review on image   processing algorithms used in PITZ applications,” DESY summer  student  program  2013,Tsinghua University,
CHINA.

5.             Stefan Weiße,DESY Zeuthen, “PITZ – Introduction to the Video System .June 10, 2003.

6.             Weisse.S and V.Miltchev.,”Video Client 2 User Documentation” http://adweb.desy.de/mcs/tine/Video System/vsv2doc/Video%20Client%202%20 User%20 Documentation_rev2.pdf., 01-04-2004.

7.             G.Asova et al., "New beam diagnostic developments at the Photo-Injector Test Facility PITZ," Particle Accelerator Conference, 2007. PAC. IEEE, vol., no., pp.3967,3969, 25-29 June 2007, doi: 10.1109/PAC.2007.4439943.

8.             Sonali  R.Mahakale, Nileshsingh V.”A Soft Computing    Approach for Image Filtering”, International Journal of  Engineering   Science  and Technology,Vol.4.
No.07, July 2012.
9.             Manohar Koli,S.Balaji, ”Literature Survey on Impulse Noise  Reduction”,Signal and Image Processing:An International Journal(SIPIJ) Vol.4,No.5,October 2013.
10.          Rohini R. Varade, M. R. Dhotre, Archana  B. Pahurkar, ”A Survey on Various Median   Filtering Techniques for Removal  of  Impulse Noise from Digital Images”, ISSN: 2278 – 1323, International   Journal  of Advanced  Research in Computer Engineering & Technology  (IJARCET). Vol 2, Issue 2, February 2013.

11.          Madhu S. Nair  and  G. Raju , “A  new fuzzy-based decision  algorithm  for  high-density impulse noise  removal”,  Springer-Verlag,  London  Limited. Signal, Image and Video processing.  DOI 10.1007/s11760-010-0186-4, 2010.

12.          Geeta Hanji, M.V.Latte,“A New Threshold Based Median Filtering Technique for Salt and Pepper Noise Removal,” 2nd International  Conference on Digital Image Processing-(ICDIP-2010), 2010 Proceedings of SPIE,Vol.7546, PP754639-75463910, SINGAPUR, 2010,    DOI: 10.1117/12.856333.

13.          Ng  PE,  Ma  KK., “A  switching  median  filter  with boundary  discriminative  noise  detection  for  extremely  corrupted  images”,  IEEE  Trans.  Image Process, l.15(.6): 1506-1516,2006.

14.          A.K.  Tripathi, U.  Ghanekar  and  SMukhopadhyay,  “Switching  median  filter: Advanced  boundary discriminative noise detection algorithm,” IET  Image  Process.,  Vol  5,  issue  7,  pp 598-610, 2011.

15.          A.  Fabijanska   and D.  Sankowski,  “Noise adaptive  switching  median-based  filter  for impulse  noise  removal  from extremely  corrupted images,” IET Image Process., vol. 5,issue5,pp.472-480, 2011.

16.          Geeta Hanji,M.V.Latte, ”A New Impulse  Noise Detection  and  Filtering Algorithm,” Image Processing & Communications (IPC), The Journal of University of Technology and Life Sciences in Bydgoszcz  Vol. 16,no.1-2, pp.43-48,DOI: 10.2478/v10248-012-0004-4,2012.

17.          Dr. G. Venkata Rami Reddy, Dr. B. Sujatha, “Directional Correlation-Dependent FilteringTechnique for Removal of Impulse Noise”,International Journal of Signal Processing, Image Processing and Pattern Recognition,Vol.7, No.4 (2014), pp.85-92,http://dx.doi.org/10.14257/ijsip.2014.7.4.08.

18.          Geeta Hanji, M.V.Latte, “Detail Preserving Fast Median Based Filter,” Journal of Advanced Computer Science and Technology,1(4) (2012) 195-206 © Science Publishing Corporation, www.sciencepubco.com/index.php/JACST article/view/248.

19.           Priyanka Kamboj, Versha Rani,”Brief  Study  Of Various Noise Model and Filtering Techniques”Journal of Global Research in Computer Science,        Volume 4, No. 4, April 2013 ,www.jgrcs.info.

20.         T. Ravi Kishore,K. Deergha Rao, “Efficient Median Filter for Restoration of Image and Video Sequences Corrupted by Impulsive” IETE Journal of   Research, Volume 56, Issue 4, DOI:10.4103/0377-2063.70645,pages 219-226 Published online: 01 Sept 2014.

21.         Geeta Hanji,M.V.Latte, “Novel Median Filter for Impulse Noise Suppression from Digital Images,” International Journal of Computer Applications (  IJCA), (0975 – 8887),Volume 106– No.8, November 2014.

22.         Geeta Hanji, M.V.Latte, “Novel Adaptive Filter (NAF) for  Impulse  Noise    Suppression  from   Digital   Images”, Communicated  to International  Journal on Bioinformatics & Biosciences (IJBB)ISSN 1839-9614  and  accepted  for  publication  in December 2014 issue.


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15.

Authors:

Y.N. Prajapati, M.K. Srivastava, Sandhya Sharma

Paper Title:

Open Source Video Analysis Tool for Motion Detection

Abstract:     We present a fast moving Open Source detection application by extending the functionality of open source tools that are available freely on the Internet. This application can be placed on a cloud infrastructure and performs fast processing so that the costs needed to use the cloud resources can be minimized.

Keywords:
 Open source, Motion Detection, Video Analysis 


References:

1.                Open    Source    Computer    Vision    (OpenCV)    [Online].    Available http://opencv.willowgarage.com/wiki/. Accessed February 21st, 2012.
2.                FFmpeg [Online]. Available http://ffmpeg.org/. Accessed  February 21st,2012.

3.                H. Zen, T. Hasegawa, and S. Ozawa, Moving object  detection from MPEG coded picture, Proc. of 1999 International Conference on Image Processing (ICIP), Vol. 4, 1999, pp. 25-29.

4.                Ashraf M.A. Ahmad, Duan-Yu Chen, and Shu-Yin Lee,  Robust object detection using cascade filter in mpeg videos, Proceedings of the IEEE 5th International Symposium on Multimedia Software Engineering (ISMSE),2003, pp. 196203.

5.                Pereira, R. et al., An Architecture for Distributed High Performance Video Processing in the Cloud, Proc. of 2010 IEEE 3rd International Conference on Cloud
Computing (CLOUD), 2010, pp. 482-489.

6.                The  OpenCV  Video  Surveillance  /  Blob  Tracker   Facility.  [Online].Available: http://opencv.willowgarage.com/wiki/VideoSurveillance/. [Ac- cessed: February 1st, 2012].

7.                Chen, T. et al., ”Computer Vision Workload Analysis:  Case Study ofVideo Surveillance Systems,” Intel Technology Journal,  May 2005, pp.109-1


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16.

Authors:

Abed Saif Alghawli

Paper Title:

Method for Evaluating The Routing Cost in Mpls Network With Regard To Fractal Properties of The Traffic

Abstract:      There has been proposed the method for evaluating the routing cost which is based on the account of fractal properties of the network traffic and pre-set limits for the latency time and the number of lost packets. This method calculates the fractality of the traffic and the value of bursts. Depending on these parameters, the routing costs are recalculated and the optimal one is chosen for transferring. If the traffic is the usual Poisson flow, then the routing is not changed. If the traffic has strong long-term dependence and high bursts, then the routing cost  increases in proportion to the value of Hurst exponent and the extend of bursts.  The proposed method for evaluating the routing cost with regard to fractal properties of the traffic has been tested on an open platform of graphical simulation of HUAWEI networks in the existing network of "Market-port" company. During the experiment the network parameters have been defined (bandwidth, load capacity of the channels, the number of lost data, transmission delays, fractality) in the real "Market-port" network. Then the network similar to a real one has been modelled and configured in such a way that transmission time, the number of lost packets, the average latency time of the packets in the network coincides with the data having been defined in a real network of "Market-port" company.  The source of the implementations of traffic in the experiments was the realization of the real network traffic captured in the network of "Market-port" company and the model implementation generated by these parameters. The studied simulation of the proposed method for evaluating the routing cost in MPLS network has shown that the use of the developed method significantly improves the quality of the service, reduces the transmission losses and permits to load network channels more evenly.

Keywords:
 MPLS network, traffic management control, routing cost, delays, the quality of the service, fractal traffic.


References:

1.              Selin Cerav Erbas , Cagkan Erbas. A Multiobjective Off-line Routing Model for MPLS Networks. IEEE transactions on knowledge and data engineering , 2003. P.1-10.
2.              Петров В. В.  Структура  телетрафика  и  алгоритмобеспечения  качества  обслуживания  при  влиянии эффекта  самоподобия :  дис.  кандидата  технических наук :  05.12.13  / Петров  Виталий  Валерьевич.  –  М.,2004. – 175 с.

3.              Шелухин О. И.  Фрактальные  процессы  в телекоммуникациях / О. И. Шелухин , А. М. Тенякшев,А. В. Осин  // Монография :  под  ред.  О. И. Шелухина.М.: Радиотехника, 2003. – 480 с.

4.              Кириченко Л. О. Влияние методов маршрутизации на качество обслуживания в мультисервисных сетях при самоподобной нагрузке / Л. О. Кириченко, Т. А. Радивилова, Э. Кайали // Восточно-Европейский журнал передовых технологий. – 2011. – 1/2 (49). – С. 15–18.

5.              Радивилова Т. А.  Описание модели сети MPLS и методов управления трафиком Т. А. Радивилова, Э. Кайали // Системи управління, навігації та
зв’язку. – 2012. – Вип. 3 (23). – С. 184–189.

6.              Зайченко Е.Ю. Комплекс алгоритмов оптимизации сетей с технологией MPLS// Системні дослідження та інформаційні технології-2007.-№4.-с.58-71.

7.              Abdalla Jr H., Soares A.M, Carvalho P. H. P et al, Performance Evaluation of Shortest Path Computation for IP and MPLS Multi-Service Networks over Open Source Implementation. Proceedings of the 11th International Conference on Telecommunications –SAPIR 2004, Fortaleza, Brazil, August 2004.

8.              P. A. S. M. Barreto, “Uma metodologia de engenharia de trafego baseada na abordagem auto-similar para a caracterizacao de parametros e a otimizacao de redes multimıdia,” Ph.D. dissertation, Universidade de Brasılia, 2007.

9.              Kirichenko L. Comparative analysis for estimating of the Hurst exponent for stationary and nonstationary time series // L. Kirichenko, T. Radivilova, Z. Deineko // International Journal "Information Technologies & Knowledge". – 2011. – Vol.5. – P. 371-388.

10.           Kirichenko L. Modeling telecommunications traffic using the stochastic multifractal cascade process  // L. Kirichenko, T. Radivilova, E. Kayali // Problems of Computer Intellectualization / ed. K. Markov, V. Velychko, O. Voloshin. – Kiev–Sofia: ITHEA. – 2012. – P. 55–63.


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17.

Authors:

Alanoud Al Mazroa, Mohammed Arozullah

Paper Title:

Securing the User Equipment (UE) in LTE Networks by Detecting Fake Base Stations

Abstract:       An LTE network attacker can set up rogue base station easily to make the victim user equipment (UE) connect to such base station. The privacy of the UE will be compromised. In this paper, we propose a protocol to identify fake base stations to protect user privacy. The basic idea is to synchronize to all base stations in range and collect the network IDs. Based on the fact that legitimate base stations have the same network ID that is different from fake ones, the UE can connect to the legitimate base station with the strongest power instead of any base station with the strongest power in traditional design. Our proposed protocol is a UE side solution and no base station modification is required. This property makes our protocol can be gradually deployed in the future. Our protocol is implemented on NS3 LTE module and evaluated with various practical settings. The results indicate our protocol can ensure that the UE can always connect to the legitimate base station with the strongest power.

Keywords:
 LTE network attacker, NS3, UE, IDs, protocol,


References:

1.             M. Arapinis, L. Mancini, E. Ritter, M. Ryan, N. Golde, K. Redon, and R. Borgaonkar. New privacy issues in mobile telephony: _x and verification. In Proceedings of the 2012 ACM conference on Computer and communications security. ACM, 2012.
2.             C.-M. Chen, Y.-H. Chen, Y.-H. Lin, and H.-M. Sun. Eliminating rouge femtocells based on distance bounding protocol and geographic information. Expert Systems with Applications, 2014.

3.             N. Golde, K. Redon, and R. Borgaonkar. Weaponizing femtocells: The effect of rogue devices on mobile telecommunications. In NDSS, 2012.

4.             C.-K. Han, H.-K. Choi, and I.-H. Kim. Building femtocell more secure with improved proxy signature. In Global Telecommunications Conference, 2009. GLOBECOM 2009. IEEE. IEEE, 2009.

5.             N. K. M. Mishra Sandip D. False base station attack in gsm network environment. In International Journal of Advanced Research in Computer Engineering and Technology (IJARCET), 2014.

6.             N. L. module. http://www.nsnam.org/docs/models/html/lte.html.

7.             D. Perez and J. Pico. A practical attack against gprs/edge/umts/hspa mobile data communications.

8.             R. Prasad, J. Laganier, A. Zugenmaier, M. S. Bargh, B. Hulsebosch, H. Eertink, G. Heijenk, and J. Idserda. Mobility and key management in sae/lte. In Wireless Communications 2007 CNIT Thyrrenian Symposium. Springer, 2007.

9.             R. Singh and S. Singh. Detection of rogue base station using matlab. International journal of Soft Computing and Engineering, 2011.

10.          Y. Song, K. Zhou, and X. Chen. Fake bts attacks of gsm system on software radio platform. Journal of Networks, 2012.

11.          D. Strobel. Imsi catcher. 2007.


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18.

Authors:

Vivek Dogne, Anurag Jain, Susheel Jain

Paper Title:

Evolving Trends and its Application in Web Usage Mining: A Survey

Abstract:      With the abundance of information available on the World Wide Web (WWW), the issue of how to extract useful knowledge from the Web has gained significant attention among researchers in data mining and knowledge discovery areas. Web mining is applied to reflect the importance of Webpages and to predict the web domain visits ofvarious users. This article provides a survey of the available literature on Web usage mining and reviews the research and application issues in web usage mining

Keywords:
 web mining, web content mining, web usage mining, web structure mining.


References:

1.             R. Kosala, H. Blockeel, Web mining research: a survey, ACM SIGKDD Explorations Newsletter 2 (1) (2000)pp, 1–15.
2.             F.M. Facca, P.L. Lanzi, Mining interesting knowledge from weblogs: a survey, Data and Knowledge Engineering 53 (3) (2005)pp, 225–241.

3.             Park, Sungjune, Nallan C. Suresh, and Bong-KeunJeong. "Sequence-based clustering for Web usage mining: A new experimental framework and ANN-enhanced K-means algorithm." Data & Knowledge Engineering 65.3 (2008)pp, 512-543.

4.             Zhang, Xuejun, John Edwards, and Jenny Harding. "Personalised online sales using web usage data mining." Computers in Industry 58.8 (2007)pp, 772-782.

5.             Li, Ziang, et al. "An ontology-based Web mining method for unemployment rate prediction." Decision Support Systems 66 (2014)  pp,114-122.

6.             Belk, Marios, et al. "Modeling users on the World Wide Web based on cognitive factors, navigation behavior and clustering techniques." Journal of Systems and Software 86.12 (2013) pp, 2995-3012.

7.             Wu, Mingxing, et al. "An approach of   product usability evaluation based on Web mining in feature fatigue analysis." Computers  & Industrial Engineering 75 (2014) pp, 230-238.

8.             Matthews, Stephen G. et al. "Web usage mining with evolutionary extraction of temporal fuzzy association rules." Knowledge-BasedSystems 54 (2013)  pp, 66-72.

9.             Wang, Yao-Te, and Anthony JT Lee. "Mining Web navigation patterns with a pathtraversal graph." Expert Systems with Applications 38.6 (2011)  pp,7112-7122.

10.          Wang, Xiaozhe, Ajith Abraham, and Kate A. Smith."Intelligent web traffic mining and analysis."Journal of Network and ComputerApplications28.2 (2005)  pp, 147-165.

11.          Castellano, Giovanna, Anna Maria Fanelli, and Maria AlessandraTorsello. "NEWER: A system for NEuro-fuzzy WEb Recommendation." Applied Soft Computing 11.1(2011)  pp,793-806.

12.          Aggarwal, C., Yuchen Zhao, and P. Yu. "On the use of Side Information for Mining Text Data." (2012) pp, 1-1.

13.          Cooley, R., P.-N. Tan, and J. Srivastava, "Discovery of intersting usage patterns from Web data," presented at WEBKDD, (1999) pp,5-32.

14.          Kohavi, R., "Mining e-commerce data: The good, the bad, and the ugly," presented at 7th ACM SIGKDD International Conference on Knowledge Discovery, San Francisco, California,( 2001) pp,8-13.

15.          Cooley, R., B. Mobasher, and J. Srivastava, "Data Preparation for Mining World Wide Web Browsing Patterns," Knowledge and Information Systems, vol. 1, (1999)pp, 5-32.

16.          Fu, X., J. Budzik, and K. J. Hammond, "Mining navigation history for recommendation," In Proceedings of the 2000 Conference on Intelligent User Interfaces, (2000) pp,106-112.

17.          Pazzani, M., J. Muramatsu, and D. Billsus.Syskill&Webert, "Identifying interesting Web sites," In Proceedings of the Thirteenth National Conference on Artificial Intelligence, (1996), pp, 54-61.

18.          Mobasher , B., R. Cooley, and J. Srivastava,"Creating adaptive web sites through usage-based clustering of URLs," In Proceedings of the 1999 IEEE Knowledge and Data Engineering Exchange Workshop (KDEX'99), (1999) pp, 19-25.

19.          Cooley, R.; Mobasher, B.; Srivastava, J.; “Web mining: information and pattern discovery on the World Wide Web”.In Proceedings ofNinth IEEEInternational Conference., 3-8 Nov. (1997)pp, 558 –567.

20.          Peng, Huiping. "Discovery of interesting association rules based on web usage mining." Multimedia Communications (Mediacom), 2010 International Conferenceon.IEEE, (2010) pp, 272-275.

21.          Masseglia, Florent, DoruTanasa, and Brigitte Trousse. "Web usage mining: Sequential pattern extraction with a very low support." Advanced Web Technologies andApplications.Springer Berlin Heidelberg, (2004) pp,513-522.

22.          Varghese, NayanaMariya, and Jomina John. "Cluster optimization for enhanced web usage mining using fuzzy logic." Information andCommunication Technologies (WICT), 2012World Congress on.IEEE, (2012) pp,948-952.

23.          Raghavendra, Prakash S., Shreya Roy Chowdhury, and SrilekhaVedulaKameswari. "Comparative study of neural networks and k-means classification in web usage mining." Internet Technology and Secured Transactions (ICITST), 2010 International Conference for.IEEE, (2010) pp,1-7.

24.          Li, Yan, BoqinFeng, and Qinjiao Mao. "Research on path completion technique in web usage mining." Computer Science and Computational Technology, 2008.ISCSCT'08.International Symposiumon.Vol.1.IEEE,(2008) pp,554-559.


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19.

Authors:

N. P. Joshi, R. B. Kulkarni

Paper Title:

Educational Web Mining System Based on Result Cache Method for Information Retrieval

Abstract:       There were times in the past when it seems harder to find the information on specific topics and now, the same task is just a one click away. In current times, a huge pool of information is available on different topics on World Wide Web (WWW) and the task of finding a specific one becomes a bit tricky. Different techniques are out there for information searching and retrieval, from which one can choose an efficient technique called web mining. Web mining is the technique that is used for the extraction of useful information from across the available information. There are different such a sub-techniques through which a web mining  can be implemented but has some challenges and issues such as network speed, longer fetching time, content availability, lack of information relevance etc. The paper presents the methodology that tries to avoid or minimize the above mentioned problems by the means of result cache approach that reduces the fetching time, increase the availability of the information resource and provides the closely accurate resources to its users.

Keywords:
 Educational Web Mining, Web mining, Information retrieval, Result cache,XML


References:

1.                Liu, Shengjian, and Peiyuan Liu. "Research of Educational Web mining based on XML." Computer Science & Education (ICCSE), 2012 7th International Conference on. IEEE, 2012.
2.                Wei, Qin. "Research and Design of Web-based Teaching Platform." 2010 Second International Workshop on Education Technology and Computer Science. Vol. 3. 2010.

3.                Liechti, Olivier, Mark Sifer, and Tadao Ichikawa. "A metadata based framework for extracting and using Web sites structures." Multimedia Computing and Systems, 1999. IEEE International Conference on. Vol. 2. IEEE, 1999.

4.                Shengjian, Liu, and Wu Xiaoning. "Architecture design of IT education platform based on web mining." Computer Science and Automation Engineering (CSAE), 2011 IEEE International Conference on. Vol. 4. IEEE, 2011.

5.                Lan, Li, and Rong Qiao-mei. "Research of Web mining Technology based on XML." Networks Security, Wireless Communications and Trusted Computing, 2009. NSWCTC'09. International Conference on. Vol. 2. IEEE, 2009.

6.                Liu, Shengjian. "Educational Web Mining Applications in Intelligent Web-Education Systems." Information Technology, Computer Engineering and Management Sciences (ICM), 2011 International Conference on. Vol. 4. IEEE, 2011.

7.                Romero, Cristóbal, and Sebastian Ventura. "Educational data mining: A survey from 1995 to 2005." Expert systems with applications 33.1 (2007): 135-146.

8.                Kumar, M. Kiran, Shaik Rasool, and S. Jakir Ajam. "Web data mining Using XML and Agent Framework." IJCSNS 10.5 (2010): 175


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20.

Authors:

Suhel Ranjan Mondal, Monalisa Bhowmik, Santanu Maity,  Razia Sultana

Paper Title:

Comparative Analysis and Study on 4-bit RCA and CSK using CMOS Logic

Abstract:        Adders are the most basic and essential component used in Digital signal processing and is widely used in the digital integrated circuits. In VLSI application area, delay and power are the important factors which must be taken into account in design of a full adder. In this paper a comparative analysis in terms of  speed, power consumption and area and PDP  for design of 4 bit RCA and CSK is compared by CMOS logic style , quantitatively and qualitatively by performing detailed transistor level simulation using T spice v13.0.

Keywords:
  Ripple carry Adder, Carry Skip Adder, ,full adder, high speed, low power.


References:

1.             Chandrakasan, A., and Brodersen, Low Power Digital Design, Kluwer Academic   Publishers, 1995.
2.             CMOS Digital Integrated Circuits- Analysis and Design : Kang, Third Edition, TMH         Publishers,2010.

3.             R. Zlatanovici and B. Nikolic, “Power-Performance Optimization for Custom Digital Circuits”, Proc. of PATMOS, Sept 2007, pp. 404-414, Leuven, Belgium.

4.             Weste, N., and Eshragian, K., Principles of CMOS VLSI   Design: A Systems Perspective,   Pearson Addison-Wesley Publishers, 2008.

5.             Bellaouar, A., and Elmasry, M. I., Low-Power Digital VLSI Design: Circuits and   Systems, Kluwer, Norwell, MA, 2005.

6.             Suzuki, M., Ohkubo, N., Yamanaka, T., Shimizu, A., and Sasaki, K., ―A 1.5-ns 32-b CMOS ALU in double pass-transistor logic‖, IEEE Journal of Solid-State Circuits, vol. 28, pp. 1145-1151, 2008.

7.             K. Chirca, M. Schulte, J. Glossner, S. Mamidi, and S. Vassiliadis, “AStatic Low-Power, High-Performance 32-bit Carry Skip Adder”, Euromicro 2004 Symposium on Digital System Design (DSD), August31 – September 3, 2009, Rennes, France.

8.             R. Barnes Earl and G.Oklobdzija Vojin “New Multilevel Scheme for Fast Carry-Skip Addition,” in IBM Technical Disclosure Bulletin, vol.27, April, 2009, pp133-158 27,.

9.             L. Bisdounis, D.Gouvetas,., and O.Koufopavlou., “A Comparative study of CMOS circuit design styles for low power high-speed VLSI circuits,” Int. J. of Electronics, vol.84, no. 6, 1998, pp. 599-613.


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21.

Authors:

T. K Sai, K. A. Reddy

Paper Title:

Neural Network Applications in a  Power Station

Abstract:   The integration of Soft Computing  techniques in traditional real-time systems  is a promising approach to cope with the growing complexity of real-world applications. A  power station is a complicated multivariable controlled plant, which consists of boiler,  turbine, generator, power network and loads. The demands being placed on Control & Instrumentation engineers include economic optimization, practical methods for adaptive and learning control, software tools that place state-of-art methods . As a result, Neural network applications  are explored in   Measurement and Control. In real time systems, Information plays a vital role for the efficient operation and maintenance in a power station. However there are limitations on making available information online due to instrumentation limitation, hazardous environment condition etc. The Furnace Exit Gas Temperature  (FEGT) is an important  design and  operating  parameter. The furnace of a boiler is such a zone where online measurement of temperature is difficult  because of high temperature and adverse conditions. Considering the complexity of power plant operating condition and number of parameters involved, the best solution to this problem lies in adopting the Neural Networks to measure  FEGT in a 500 MW Thermal Power Plant.  Also, Steam temperature Control is one of the most challenging control loops in a power plant boiler because it is highly nonlinear and has a long dead time and time lag. . The Superheated temperature is to be controlled by adjusting the flow of spray water to within +/- 10 deg C during transient states and +/- 5 deg C at the steady state. A neural network based Model Predictive Control ( MPC ) is proposed in this paper

Keywords:
  Neural Networks, Boiler, Superheater temperature, Furnace exit gas temperature, Measurement Control, Power Plant


References:

1.              C. Aurora, L. Magni, R. Scattolini, P. Colombo, F. Pretolani and G. Villa,” Predictive control of thermal Power Plants”, Int. J. Robust Nonlinear Control 2004
2.              Michel Niklou,”Model Predictive Controllers: “A Critical Synthesis of Theory and Industry needs”

3.              Piotr Tatjewski, Maciej Lawrynczuk, “Soft computing in Model–based predictive control”, International Journal of Applied Maths and Computer Science, 2006, Vol. 16, No. 1, PP7–26.

4.              Piotr tatjewski, Maciej ławry ´ Nczuk, “Soft computing in model–based predictive control”, Int. J. Appl. Math. Comput. Sci., 2006, Vol. 16

5.              Prasad, G., Swidenbank, E., Hogg, B. W., “A Plant Performance Monitoring and Optimization System”, Proc. Of the 30th WEC 1995, Greenwich.UK, PP1444-1449      

6.              Industrial Applications of Soft Computing:A Review Yasuhiko dote and Seppo J Ovas

7.              A Tanemura,H. Matsumoto Y. Eki S. Nigawara  “Expert System for startup scheduling and operation support in fossil power plants”

8.              On Soft Computing techniques in various areas bySantosh Kumar Das1, Abhishek Kumar2, Bappaditya Das3 and A.P.Burnwal4

9.              S. Thompson and K. Li, Thermal power plant simulation and control (United Kingdom,The Institution of Electrical Engineers, 2003).”

10.           Preeti Manke, Sharad Tembhurne “ Artificial Neural network based nitrogen oxides emission prediction and optimization in thermal power plant”

11.           G.Prasad, G.W.Irwin, Eswidenbank, B.W.Hogg “Plant-wide predictive control for a thermal power plant based on a physical plant model”, IEEE Proc-Control theory applications vol: 147,No-5, September-2000, PP523-537

12.           G. Prasad, E. Swidenbank, B. W. Hogg, “A multivariable predictive control strategy for economical fossil Power plant operation”, Control '96, UKACC International Conference (Conf. Publ. No. 427)

13.           S. Joe Qina, Thomas A. Badgwell, “A survey of industrial model predictive control technology”, Control Engineering Practice 11 (2003), PP 733–764

14.           Energy Research center, Lehigh university, 610-758-4090

15.           Storm RF and Reilly TJ Coal Fired Boiler performance improvement throughCombustionoptimisation.                                                          

16.           Ilamathi p, Selludurai v,Balamurugan k “Predictive modelling and optimization of power plant nitrogen oxides emission” IAES,2012

17.           Proceedings: " Workshop or Intelligent Soot Blowing Application ' EPRI project Report ,March1 999,TR- 1l163l

18.           Proceedings," Guidelines for lntelligent Soot blowing Control 'EPRI"2000,TR- 1000410

19.           Intelligent Sootblowing and Waterwall Temperature Monitoring- T. Ziegler AmerenUEM. J. Dooley, A. G. Ferry and M. Daur

20.           Expert system for Boiler efficiency deviations assessment I. Arauzo and C.Cortes

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22.

Authors:

S. Y. S. Hussien, H. I. Jaafar, R. Ghazali, N. R. A. Razif

Paper Title:

The Effects of Auto-Tuned Method in PID and PD Control Scheme for Gantry Crane System

Abstract:    Gantry crane system is a mechanism in heavy engineering that moves payload such container from one point to another. Generally, experienced operators or experts are required to control manually the gantry position while minimizing the payload vibration or swing oscillation. Therefore, those manpower has to be trained in order to operate the gantry crane system safely and efficiently. Thus, to overcome this problem, a feedback control scheme has been utilized in the system. In this paper, PID and PD controllers are introduced for controlling the trolley displacement and the swing oscillation in the gantry crane system. PID controller is designed for tracking the desired position of the trolley whereas PD controller is implemented to minimize the payload oscillation. The PID and PD parameters are tuned by the auto-tuning method. Simulation results have demonstrated satisfactory response based on control system performances.

Keywords:
    Auto-tuned, Gantry Crane System, PID and PD Controller, Payload Oscillation, Trolley Position.


References:

1.              H. Butler, G. Honderd, and J. van Amerongen, "Model reference adaptive control of a gantry crane scale model," Control Systems, IEEE, vol. 11, pp. 57-62, 1991.
2.              D. Diep and V. Khoa, "PID-Controllers Tuning Optimization with PSO Algorithm for Nonlinear Gantry Crane System," system, vol. 2, p. 7.

3.              Garrido, Santiago, et al. "Anti-swinging input shaping control of an automatic construction crane." Automation Science and Engineering, IEEE Transactions on 5.3 (2008): 549-557.

4.              Daqaq, Mohammed F., and Ziyad N. Masoud. "Nonlinear input-shaping controller for quay-side container cranes." Nonlinear Dynamics 45.1-2 (2006): 149-170.

5.              Gupta, S., and P. Bhowal. "Simplified open-loop anti-sway technique." India Annual Conference, 2004. Proceedings of the IEEE INDICON 2004. First. IEEE, 2004.

6.              Wahyudi, Wahyudi, and Jamaludin Jalani. "Design and implementation of fuzzy logic controller for intelligent gantry crane system." (2005).

7.              Zawawi, M. A., et al. "Feedback control schemes for gantry crane system incorporating payload." Industrial Electronics and Applications (ISIEA), 2011 IEEE Symposium on. IEEE, 2011.

8.              Ahmad, M. A., et al. "Control schemes for input tracking and anti-sway control of a gantry crane." Australian Journal of Basic and Applied Sciences 4.8 (2010): 2280-2291.

9.              S. Gade, S. Shendage, and M. Uplane, "MATLAB Based Response of Systems Using Auto Tune PID Controller," International Journal of Emerging Technology and Advanced Engineering (ISSN 2250-2459, ISO 9001: 2008 Certified Journal, Volume 2, Issue 12, pp. 157-162, 2012.

10.           O. Katsuhiko, "Modern control engineering," 2010.

11.           M. Ahmad, R. Raja Ismail, A. Nasir, and M. Ramli, "Anti-sway control of a gantry crane system based on feedback loop approaches," in Advanced Intelligent Mechatronics, 2009. AIM 2009. IEEE/ASME International Conference on, 2009, pp. 1094-1099.

12.           M. Gaiceanu and F. Stan, "Motion control of a single-beam gantry crane trolley," in Electrical and Electronics Engineering (ISEEE), 2010 3rd International Symposium on, 2010, pp. 149-152.

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23.

Authors:

Duong Trong Luong, Nguyen Duc Thuan, Nguyen Thai Ha

Paper Title:

New Design of 12-Lead ECG Simulation Signal System with Simulated Noise Added

Abstract:   This paper presents a simulation system design of 12-lead electrocardiogram (ECG) signal.The simulated ECG  signal  is generated in analog form and can  be added to certain  types of noise such as simulated 50Hz power line  noise or  baseline wander.The original 12-lead ECG signal was taken from database on www.phisyonet.org website. Adding noise signals, selecting leads and signal display are performed by our designed software. The accuracy of simulated ECG  signal is estimated by Mean Square Error (MSE) criterion. The proposed system was tested  and showed  the good results . The system can be used for testing designed circuits or can test actual clinical effect ECG devices. The designed system can supply convenient tools for Researchers, Designers in developing ECG products.             

Keywords:
    12-lead ECG signal, simulated signal, baseline noise, Mean Square Erro (MSE).


References:

1.      Frank G. Yanowitz, MD “ Introduction to ECG interpretation”. Intermountain Healthcare, 2012.
2.      Dr. Truong Thanh Huong, “ Normal ECG signal and ECG measuring”. Lecture note, VietNam  cardiovascular hospital, 2007.

3.      http://www.ti.com

4.       http://www.ic-on-line.cn

5.       G.D. Clifford, F. Azuaje, and P. McSharry, “Advanced Methods and

6.        Tools for ECG Data Analysis”. Norwood, MA, USA: Artech House, Inc., 2006.

7.        Jungkuk Kim, Minkyu Kim, Injae Won, Seungyhul Yang, Kiyoung Lee, and Woong Huh,“An ECG signal processing Algorithm based on removal of wave deflections in time domain”. The 31st Annual International Conference of the IEEE EMBS, Minneapolis, Minnesota, USA, September 2-6, 2009.

8.       http://www.physionet.org

9.      http://www.ni.com/pdf/manuals/371303m.pdf

10.      http://halinh-jsc.com/ :  Nihon-Kohden-ECG-1150-851.html


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24.

Authors:

Anil Kumar Suman, Anil Kumar Saxena, T. R. Arora

Paper Title:

Assessment of Concrete Strength using Partial Replacement of Cement for Rise Husk Ash

Abstract:      Concrete  is  being  widely  used for  the  construction  of most  of  the buildings , bridges, etc throughout the  world. Hence it  is the    backbone  to  the  infra  structure development  of  a  nation.  India is taking major initiatives to improve and develop its infrastructure by constructing   express highways, power projects and industrial structures. A huge quantity of concrete is required to meet out this infrastructure development. Rice husk ash (RHA) is the byproduct of burned rice husk at higher temperature. Considerable efforts are being taken worldwide to utilize natural waste and by product as supplementary cementing materials to improve the properties of cement concrete. RHA is a product of paddy industry. Rice husk ash is a highly reactive pozzolonic material produced by controlled burning of rice husk.  Hence currently the entire construction industry is in search of a suitable and effective waste product that would minimize the use of cement and reduce the construction cost. Few of such products have already been identified like Rice Husk Ash. Fly Ash (FA), and Silica Fumes etc.  Rice husk ash globally approximately 600 million tons of rice paddy is produced every year.  On an average 20% of the rice paddy is husk giving an annual total production of 120 million tones. From rice husk the concept of generating energy has great potential. Rice husks are one of the largest readily available but most underutilized bio mass resources being an ideal fuel for electricity generation. In recent years special attention has been devoted to industrial sectors.   

Keywords:
     RHA, Fly Ash, Rice Husk Ash, pozzolonic, Silica Fumes.


References:

1.           Rama Rao   G V Seshgiri Rao MV: High performance concrete mix design using RHA.
2.           Ephraim etal (2012); compressive strength of concrete with RHA as partial replacement of ordinary Portland cement.

3.           Mega h etal (2005); development of appropriate and sustainable construction materials.

4.           Deep g Nair, k s jadish: reactive pozzolons from rice husk ash.

5.           Arpna; rice husk ash concrete February 26-27, 2004 nation conference.

6.           H B Mahmud, B S china; rice husk ash alternative material in producing high strength concrete.

7.           Geema g sansele: strength development of concrete with rice husk ash.


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25.

Authors:

M. S. Omar, H. I. Jaafar, R. Ghazali, S. H. Mohamad, K. A. M. Annuar

Paper Title:

Investigation of Single Cart Gantry Crane System Performance using Scheduling Algorithm

Abstract:  This paper investigates the implementation of two types of scheduling algorithm to obtain the best performances of the Single Cart Gantry Crane System (GCS). In this research, Deadline Monotonic Priority Assignment (DMPA) and Earliest Deadline First (EDF) scheduling algorithm are chosen to be implemented. The main ideas of this approach is to find the schedule that more compatible and provide more stable result for the system. The Cart performances will be analyzed in term of Settling Time (TS) and Overshoot (OS). In this study, a simple PID controller that acts as a basic control structure is used. The application of TRUETIME kernel block also is implemented to be executed in a MATLAB environment. It has been demonstrated that implementation of these two algorithms will help this system to be more stabilized according to appropriate execution time.

Keywords:
  Cart Gantry Crane System, Deadline Monotonic Priority Assignment, Earliest Deadline First, Truetime.


References:

1.           H. I. Jaafar, Z. Mohammed, J. J. Jamian, A. F. Z. Abidin, A. M. Kassim, and Z. A. Ghani, “Dynamic Behaviour of a Nonlinear Gantry Crane System,” Procedia Technology, vol. 11, pp. 419-425, 2013.
2.           H. I. Jaafar, N. M. Ali, Z. Mohamed, N. A. Selamat, A. M. Kassim, A. F. Z. Abidin, and J. J. Jamani, “Optimal Performance of a Nonlinear Gantry Crane System via Priority-based Fitness Scheme in Binary PSO Algorithm,” IOP Conference Series: Materials Science and Engineering, Vol. 53, 2013, 012011.

3.           H. I. Jaafar, Z. Mohamed, A. F. Z. Abidin, Z. M. Sani, J. J. Jamian, and A. M. Kassim, “Performance Analysis for a Gantry Crane System (GCS) using Priority-based Fitness Scheme in Binary Particle Swarm Optimization,” Advanced Materials Research, Vol. 903, 2014, pp. 285-290.

4.           Masrur, S. Chakraborty, and G. Farber, “Constant-time Admission Control for Deadline Monotonic Tasks,” Design, Automation & Test in Europe Conference & Exhibition, Dresden, Germany, March 8-12, 2010, pp. 220–225.

5.           R. I. Davis and A. Burns, “Improved Priority Assignment for Global Fixed Priority Pre-emptive Scheduling in Multiprocessor Real-Time Systems”, 2008.

6.           S. Kato and N. Yamasaki, “Semi-partitioned Fixed-Priority Scheduling on Multiprocessors,” 15th IEEE Real-Time Embedded Technology and Application. Symposium, San Francisco, California, April 13-16, 2009, pp. 23–32.

7.           G. Yao, G. Buttazzo, M. Bertogna, S. Superiore, and S. Anna, “Bounding the Maximum Length of Non-Preemptive Regions Under Fixed Priority Scheduling”, no. 216008, 2013.

8.           O. A. Ghiasvand and M. A. Sharbafi, “Using Earliest Deadline First Algorithms for Coalition Formation in Dynamic Time-critical Environment”, Intenational Journal of Information and Education Technology, vol. 1, no. 2, pp. 120–125, 2011.

9.           S. K. Baruah, V. Bonifaci, and G. D. Angelo, “Mixed-Criticality Scheduling of Sporadic Task Systems,” vol. 6942, pp. 555–566, 2011.

10.        Dua, C. Chan, and N. Bambos, “Channel, Deadline, and Distortion (CD 2) Aware Scheduling for Video Streams Over Wireless”, vol. 3, no. 3, pp. 1001–1011, 2010.

11.        M. I. Solihin, Wahyudi, M.A.S Kamal and A. Legowo, “Optimal PID Controller Tuning of Automatic Gantry Crane Using PSO Algorithm,” Proceeding of the 5th International Symposium on Mechatronics and its Applications (ISMA08), Amman, Jordan, May 27-29, pp. 1-5, 2008.

12.        H. I. Jaafar, M. F. Sulaima, Z. Mohamed, and J. J. Jamian, “Optimal PID Controller Parameters for Nonlinear Gantry Crane System via MOPSO Technique”, IEEE Conference on Sustainable Utilization and Development in Engineering and Technology, Selangor, Malaysia, May 30-June 1, 2013, pp. 86-91.

13.        H. I. Jaafar, Z. Mohamed, J. J. Jamian, M. S. M. Aras, A. M. Kassim, M. F. Sulaima, "Effects of Multiple Combination Weightage using MOPSO for Motion Control Gantry Crane System", Journal of Theoretical and Applied Information Technology, vol. 63, no. 3, 2014, pp. 807-813.


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26.

Authors:

Khaleel J. Hammadi, Ahmed R. Ajel, Salam Ibrahim Kadhim

Paper Title:

Characteristic Performance Analysis of Electrical Machine with Faults via Wavelet Transforms

Abstract:  This paper presents a novel approach to electrical machine current signature analysis based on wavelet transform of the stator current by using labview programming. The novelty of the proposed method lies in the fact that by using WT method the inherent non stationary nature of stator current can be accurately considered. The key characteristics of the proposed method are its ability to provide feature representations of multiple frequency resolutions for faulty modes, ability to clearly differentiate between healthy and faulty conditions, and its applicability to non-stationary signals. Successful implementation of the system for rotor bar breakage is demonstrated here .The condition monitoring of the electrical machines can significantly reduce the costs of maintenance by allowing the early detection of faults, which could be expensive to repair. The applied method is the wavelet transform which utilizes the results of the stator current.

Keywords:
   Electrical machine, Mechanical fault, Wavelet transform, NI USB


References:

1.             JEN-HAO, T., SHUN-YU, C., JIN-CHANG, L. & LEE instrument, R. (2000) A LabVIEW based virtual for power analyzers. Power System Technology, 2000. Proceedings. PowerCon 2000. International Conference on.
2.             KOSTIC, M. LabVIEW and data acquisition, retrieved 27 July 2009, from http://www.kostic.niu.edu/DAQ LabVIEW.html

3.             MANOJ EMBRANDIRI, R. K., AND ARAVIND C.V. (2006) Harmonic distortion analysis in LabVIEW 6i.

4.             MUHAMMAD, H. R. (1993) Power electronics (2nd ed.): circuits, devices, and applications, Prentice-Hall, Inc.

5.             OMATA, K., FUJITA, Y., YOSHIKAWA, N., SEKIGUCHI, M. & SHIDA, Y. (1992) A data acquisition system based on a personal computer. Nuclear Science, IEEE Transactions on, 39, 143-147.

6.             PROMMEE, W., SOMCHAIWONG, N. & JEENAWONG, S. (2006) The low-cost instrument with LabVIEW And DB25. SICE-ICASE, 2006. International Joint Conference.

7.             QIU, T., YAONAN, W. & SIYU, G. (2008) Design of Power System Harmonic

8.             BEITAO GUO, J. Z., XIN NIE (2009) Application of LabVIEW for Hydraulic Automatic Test System. Industrial and Information Systems, 2009.

9.             DEVELOPER, N. I. (2009) Advantages of using LabVIEW in academic research, retrieved 27 July 2009,fromhttp://zone.ni.com/devzone/cda/tut/p/id/8534

10.          BRUCE, M. (2001) LabVIEW for data acquisition, Prentice Hall Press.

11.          DEVELOPER, N. I. (2006) Real-time monitoring & analysis of harmonics in single-phase systems, retrieved 27 July 2009, from http://digital.ni.com/worldwide/singapore.nsf/web/all/146D609A8B8C4C00862574D7003F6341

12.          BENTON, J. S. (1995) Virtual instrument measures harmonic filter duty. Computer Applications in Power, IEEE, 8, 43-46.

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27.

Authors:

Ali Yaghoubi, Hamid Reza Ghaffari

Paper Title:

Improved LDA by using Distributing Distances and Boundary Patterns

Abstract: One of the statistical methods of class discriminant is linear discriminant analysis. This method, by using statistical parameters, obtain a space which by using available discriminating information among class means does classification act . By using distributing Distances, extended analysis linear discriminant to its heteroscedastic state. At this state ,to make classes more separating of available separating information among covariance matrix classes including classes mean is using. In this article ,because of using new scattering matrices which are defined based on boundary and non- boundary  patterns, classes overlapping in Spaces which obtains has been  reduced . On the other hand ,using new scattering matrices brings about increasing classification rate so, the done experiments confirm improvement of classification rate.

Keywords:
  boundary linear discriminant analysis, Boundary and non-boundary patterns, CHernoff criteria, linear discriminant analysis.


References:

1.             Fukunaga, Keinosuke. Introduction to statistical pattern recognition. Academic press, 1990.
2.             Duin, R. P. W., and M. Loog. "Linear dimensionality reduction via a heteroscedastic extension of LDA: the Chernoff criterion." Pattern Analysis and Machine Intelligence, IEEE Transactions on 26.6 (2004): 732-739.

3.             Loog, Marco, and Robert PW Duin. "Non-iterative Heteroscedastic Linear Dimension Reduction for Two-Class Data." Structural, Syntactic, and Statistical Pattern Recognition. Springer Berlin Heidelberg, 2002. 508-517.

4.             Zhu, Xinzhong. "Super-class Discriminant Analysis: A novel solution for heteroscedasticity." Pattern Recognition Letters 34.5 (2013): 545-551.

5.             Safayani, Mehran, and Mohammad Taghi Manzuri Shalmani. "Two-Dimensional Heteroscedastic Feature Extraction Technique for Face Recognition."Computing
and Informatics 30.5 (2012): 965-986.

6.             Sugiyama, Masashi. "Dimensionality reduction of multimodal labeled data by local fisher discriminant analysis." The Journal of Machine Learning Research 8 (2007): 1027-1061.

7.             ReinholdHaeb-Umbach, MarcoLoog. "MULTI-CLASS LINEAR DIMENSION REDUCTION BY GENERALIZED FISHER CRITERIA." The Proceedings of the 6~(th) International Conference on Spoken Language Processing (Volume  ). 2000.

8.             Na, Jin Hee, Myoung Soo Park, and Jin Young Choi. "Linear boundary discriminant analysis." Pattern Recognition 43.3 (2010): 929-936.

9.             Shin, Hyunjung, and Sungzoon Cho. "Neighborhood property–based pattern selection for support vector machines." Neural Computation 19.3 (2007): 816-855.

10.          Na, Jin Hee, et al. "Relevant pattern selection for subspace learning." Pattern Recognition, 2008. ICPR 2008. 19th International Conference on. IEEE, 2008.

11.          Sugiyama, Masashi. "Dimensionality reduction of multimodal labeled data by local fisher discriminant analysis." The Journal of Machine Learning Research 8 (2007): 1027-1061.

12.          McLachlan, Geoffrey. Discriminant analysis and statistical pattern recognition. Vol. 544. John Wiley & Sons, 2004.

13.          Masip, David, Ludmila I. Kuncheva, and Jordi Vitrià. "An ensemble-based method for linear feature extraction for two-class problems." Pattern Analysis and Applications 8.3 (2005): 227-237.

14.          Fukunaga, Keinosuke. Introduction to statistical pattern recognition. Academic press, 1990.

15.          Jain, Anil K., Robert P. W. Duin, and Jianchang Mao. "Statistical pattern recognition: A review." Pattern Analysis and Machine Intelligence, IEEE Transactions on 22.1 (2000): 4-37.

16.          Yang, Jian-Yi, et al. "Prediction of protein structural classes by recurrence quantification analysis based on chaos game representation." Journal of theoretical biology 257.4 (2009): 618-626.

17.          Fisher, Ronald A. "The use of multiple measurements in taxonomic problems."Annals of eugenics 7.2 (1936): 179-188.

18.          Friedman, Jerome H. "Regularized discriminant analysis." Journal of the American statistical association 84.405 (1989): 165-175.

19.          D.J. Newman,  S. Hettich, C.L. Blake, C.J. Merz, UCI repository of machine learning databases, 1998  http://archive.ics.uci.edu/ml .

20.          Vapnik, Vladimir, and Olivier Chapelle. "Bounds on error expectation for support vector machines." Neural computation 12.9 (2000): 2013-2036.

21.          Chapelle, Olivier, et al. "Choosing multiple parameters for support vector machines." Machine learning 46.1-3 (2002): 131-159.

22.          Loog, Marco, R. P. W. Duin, and Reinhold Haeb-Umbach. "Multiclass linear dimension reduction by weighted pairwise Fisher criteria." IEEE Transactions on Pattern Analysis and Machine Intelligence 23.7 (2001): 762-766.


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28.

Authors:

Akram Elentably

Paper Title:

The Importance of Benchmarking to Improving Container Terminal

Abstract:          The behavior of natural body simply considering is Benchmarking is a common activity for many people, in its simplest form comparison of Ideal performance against another similar activity, perhaps just to check that we are getting the best results or the best value for a particular item. In addition the reflect of benchmarking on several scopes such as:- High-quality results -Improving efficiency -Meeting or exceeding needs  Adding value -Better tools for enhanced decision making. This happens in all walks of life. There are many different perspectives  here are two examples: “Benchmarking is a continuous systematic process for evaluating the products, services and work processes of organizations that are recognized as representing best practices for the purpose of organizational improvement.” (Spendolini, J.M. The Benchmarking Book. American Management Association. New York 1992, p.2 )Or “Benchmarking is a performance measurement tool used in conjunction with improvement initiatives; it measures comparative operating performance of companies and identifies the ‘best practices. ‘Benchmarking creates value by:• Focusing on key performance gaps;• Identifying ideas from other companies;- Creating a consensus to move an organization forward;• Making better decisions from a larger base of facts.” (Mission Statement for The Procurement And Supply-chain Benchmarking Association (PASBA), Benchmarking is most effective where a large amount of data derived from practical experience, rather than theory, can be drawn together to identify best practice or establish a range of targets. Data accumulated by trade associations or organizations with international experience is often the best basis. But don’t ignore data derived from your own experiences, benchmarking against historical performance of the same activity also has its uses. While direct comparison between identical activities is most straightforward, some lateral thinking can create benchmarks for particular operations or processes in one sector that can, to some extent, be applied to similar operations in different sectors

Keywords:
     benchmarking, Spendolini, PASBA, accumulated, straightforward..


References:

1.             J.M. Spendolini. The Benchmarking Book. American Management Association. New York 1992.
2.             Patrick Fourgeaud. Measuring Port Performance. The World Bank.

3.             Carsten Boll. Measuring and Benchmarking Terminal Productivity ISL Germany TOC Asia 2001.

4.             Drewry. World Container Terminals, 1998.

5.             Drewry. Global Container Terminals, 2002.
6.             Mission Statement for The Procurement And Supply-chain Benchmarking Association (PASBA™).

7.             Department of Transport, Local Government and the Regions. Recent Developments and Prospects at UK Container Ports, July 2001.

8.             International Benchmarking of the Australian Waterfront, Productivity Commission,1998.

9.             Benchmarking Intermodal Freight Transport, OECD, 2002.

10.          Containerisation International Yearbook, 1998 and 2003.

11.          Castalia. Final Report for the Evaluation of the Suape Port Public Private Partnership. 2011. Castalia (Unpublished).


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