iosr-JCE   Volume-20 ~ Issue-2 ~ Mar-Apr 2018

Abstract: With the mass consumption of digitally interactive multimedia like audio, images and video there is also a considerable rise in the mode and the motive to fabricate digital forgeries. Ubiquitous availability and low cost devices like cameras, camcorders and CCTVs has led to wide spread use of video information and services in our society for various purposes like video surveillances, forensics investigation, entertainment etc. Formerly Video editing techniques were essential used for enhancement of the digital content. However the growth and usage of affordable and effortless video editing software there has been a surge in the consequences and hazards of using such editing techniques. Video Forgery is thus a technique of generating altered or fake videos by combining, altering or creating new video. Thus the authenticity of such digital videos is questionable and needs to be verified. Forgery detection in videos aims at exposing and examining the underlying facts about a video to deduce whether the video contents have undergone any unethical post processing.

Index Terms—Video Forgery, Spatial and Temporal Tampering, Video Forgery Detection

[1] Mrs. J.D. Gavade, M. S. (2015). Review of Techniques of Digital Video Forgery Detection. Advances in Computer Science and Information Technology (ACSIT), Volume 2 .
[2] Sowmya K.N., H. C. (2015). A SURVEY ON VIDEO FORGERY DETECTION. International Journal of Computer Engineering
Chih-Chung Hsu, T.-Y. H.-W.-T. (2008). Video forgery detection using correlation of noise residue.IEEE 10th Workshop on Multimedia Signal Processing. IEEE.
[3] Anderson Rocha, W. S. (2010). Vision of the Unseen: Current Trends andChallenges in Digital Image and Video
[4] Forensics. ACM Digital Library Ashish Kumar Kushwaha, A. P. (2015). Video Forensic Framework for Video
[5] Forgeries. International Journal of Innovative Research in Computer and Communication Engineering..

Abstract: Big data analytics enhance modern healthcare by providing personalized medicine based on predictive prescriptions. A model of three layered data sharing for Big Heart Data is developed which uncovers the scope of cardiac remodelling. Remodelling helps in predicting status of heart health informatics based on existing database and prioritizing patient's recent-past cardiac activities. The concept was found to indicate early stages of heart failure leaving ample time to protect the patient from an acute cardiac arrest. A comparative analysis of Activation States and Rest-Task Pair Connectivity of brain is also conducted. Experimental explanations are also provided by recognition process and it opened the scope of not only detecting but also curing dementia by Body Sensor Networking (BSN). BSN can also aid rural cardiac treatments. Big Health Data leads to explore a new era of remotely testing, diagnosing and even curing particular diseases at an early stage without complex medications.

Keyword—Big Heart Data, Big Brain Data, Cardiac Remodelling, Functional Connectivity, Body Sensor Networks.

[1]. Marcus, Hani, et al. "Surgical robotics through a keyhole: From today's translational barriers to tomorrow's "disappearing" robots." IEEE Transactions on Biomedical Engineering 60.3: 674-681 (2013).
[2]. Holzinger, Andreas, Carsten Röcker, and Martina Ziefle. "From smart health to smart hospitals." Smart health. Springer International Publishing, 1-20 (2015).
[3]. Zao, John K., et al. "Pervasive brain monitoring and data sharing based on multi-tier distributed computing and linked data technology." Frontiers in human neuroscience 8 (2014).
[4]. O‟donoghue, John, and John Herbert. "Data management within mHealth environments: Patient sensors, mobile devices, and databases." Journal of Data and Information Quality (JDIQ) 4.1: 5 (2012).
[5]. Schneeweiss, Sebastian. "Learning from big health care data." New England Journal of Medicine 370.23: 2161-2163 (2014)...

Abstract: The switching of energy mode in duty-cycled wireless sensors network is very critical phase. The mode of switching deals of active mode of node and dormant phase of node. In scenario of switching basically controlled the utilization of energy in idle case and enhanced the life of network. The major issue in duty-cycle network is sink node broadcasting message to all node for the process of communication. In this process used maximum energy and life of network is expire. In this paper proposed cluster based algorithm for the routing of data in wireless sensor network. The cluster based protocol used probabilistic model and measure the flooding condition of sink node and reduces the consumption of energy. The proposed algorithm simulated in MATLAB software and used 200 nodes for simulation process. The proposed algorithm gives better performance instead of HEOT and DEF routing algorithm.

Keyword—WSN, Duty- Cycle, HEOT, Switching, MATLAB

[1] Shaobo Wu, JianweiNiu, Wusheng Chou, Mohsen Guizani "Delay-Aware Energy Optimization for Flooding in Duty-Cycled Wireless Sensor Networks" IEEE Transactions On Wireless Communications, Vol-15, 2016. Pp 8449-8462.
[2] Guodong Sun, Bin Xu "Dynamic Routing Algorithm for Priority Guarantee in Low Duty-Cycled Wireless Sensor Networks" WASA 2010, Pp 146–156.

[3] MessaoudDoudou, Djamel Djenouri, and NadjibBadache "Survey on Latency Issues of Asynchronous MAC Protocols in Delay-Sensitive Wireless Sensor Networks" IEEE Communications Surveys & Tutorials, VOL. 15. 2013. Pp 582-551.
[4] Koen Langendoen "Medium Access Control in Wireless Sensor Networks" Delft University of Technology, 2007.
[5] Hang Shen, Guangwei Bai "Routing in wireless multimedia sensor networks: A survey and challenges ahead" Journal of Network and Computer Applications, 2016. Pp 30-49...

Abstract: For Sustainable development of any country , electricity is the basic need for current civilization. With out hampering the environment , generation of electricity is very essential. Solar energy is completely natural, it is considered as clean energy source. In this work , an automation system for solar panel cooling is proposed on the use of a commercial sensor with RISC based micro-controller. An electro mechanism was designed and developed to enhance solar panel life time under different sunlight peak hours to evaluate it's voltage efficiency. The impact on the over all performance of solar PV panel caused by different temperatures at sunlight peak hours are analyzed. The developed cooling system is innovative in relation to the unusual cooling system already existing in commercial units. A mini prototype model was designed and experimented, field results have proven good enhancement. With this automation cooling technique, voltage efficiency is improved from 3% to 5%..

Keyword—automation cooling technique, solar energy, solar PV panel , temperature, voltage efficiency, sunlight peak hours

[1] Michaela Schmidt, Ilya Astrouski, Marcus Reppich, Miroslav Raudensky ," Solar panel cooling system with hollow fibres" , Applied Solar Energy ,April 2016, Volume 52, Issue 2, pp86–92
[2] Xiao Tang, ZhenhuaQuan, Yaohua Zhao , " Experimental Investigation of Solar Panel Cooling by a Novel Micro Heat Pipe Array", Energy and Power Engineering, 2010, 2, 171-174
[3] MohdEhtishaan, MdRizwanSaifee, "Simulation Based Intelligent Water Cooling System For Improvement-The Efficiency Of Photo- Voltaic Module" , International Journal of Computer Science and Mobile Computing, Vol.5 Issue.7, July-2016, pg. 535-544
[4] SandeepKoundinya, Dr. A S Krishnan, " Computational Study Of Cooling Of Pv Solar Panel Using Finned Heat Pipe Technology ", International Journal Of Mechanical Engineering And Technology (Ijmet), Volume 5, Issue 4, April (2014), Pp. 216-223.
[5] B.Koteswararao, K.Radha Krishna, P.Vijay ,N.Rajasurya, "Experimental Analysis of solar panel efficiency with different modes of cooling ", International Journal of Engineering and Technology (IJET), Vol 8 No 3 Jun-Jul 2016,pp 1451-1456..

Abstract: In new aspects at different computing environment as a worthy new direction for computer architecture research: personal mobile computing, where portable devices are used for visual computing and personal communications tasks. Such a device supports in an integrated fashion all the functions provided today by a portable computer, a cellular phone, a digital camera and a video game. The requirements placed on the processor in this environment are energy efficiency, high performance for multimedia and DSP functions, and area efficient, scalable designs. We examine the architectures that were recently proposed for billion transistor microprocessors. While they are very promising for the stationary desktop and server workloads, we discover that most of them are unable to meet the challenges of the new environment and provide the necessary enhancements for multimedia applications running on portable devices.

[1]. K. Keeton, D.A. Patterson, Y.Q. He, and Baker W.E. Performance Characterization of the Quad PentiumPro SMP Using OLTPWorkloads. In the Proceedings of the 1998 InternationalSymposium on Computer Architecture (to appear), June 1998.
[2]. G. Grohoski. Challenges and Trends in Processor Design: Reining in Complexity. IEEE Computer, 31(1):41–42, January 1998.
[3]. P. Rubinfeld. Challenges and Trends in Processor Design: Managing Problems inHigh Speed. IEEE Computer, 31(1):47–48, January 1998.
[4]. R. Colwell. Challenges and Trends in Processor Design: Maintaining a Leading Position. IEEEComputer, 31(1):45–47, January 1998.
[5]. E. Killian. Challenges and Trends in Processor Design: Challenges, NotRoadblocks. IEEEComputer,31(1):44–45, January 1998.
[6]. K. Diefendorff and P. Dubey. How Multimedia WorkloadsWill Change Processor Design. IEEComputer, 30(9):43–45, September 1997...

Abstract: One of the important task in pattern detection and recognition is object localization. This important task is performed to reduce the searching time to the interest object. In this research we demonstrate our novel method of object localization based on color feature. Our novel method is a combination of histogram of s-RGB and histogram of Hue. In the training phase, we use these histograms to determine the color dominant in the initial Region of Interest (ROI). Then this information is used to label the interest object. We apply the row and column density function of pixels to reduce noise and localize the interest object. The comparison result with some processes, our system gives a best result and takes a short computation time of 48.37 ms, in the video rate of 15 frames per second (fps).

Keyword—color feature; histogram of s-RGBH; object localization; pattern recognition

[1]. M. Ozuysal, V. Lepetit, P. Fua. Post Estimation for Category Specific Multiview Object Localization. Proceeding of Computer Vision and Pattern Recognition (CVPR2009), (Florida, USA. 2009) pp. 1-8.
[2]. D. Li, J.B. Huang, Y. Li, S. Wang, M.H. Yang. Weakly Supervised Object Localization with Progressive Domain Adaptation. Proceeding of Computer Vision and Pattern Recognition (CVPR 2016), (Las Vegas, USA. 2016) pp. 3512-3520.
[3]. M. Marszalek, C. Schmid. Accurate Object Localization with Shape Masks. Proceeding of Computer Vision and Pattern Recognition (CVPR 2007), (Minnesota, USA. 2007) pp. 1-8.
[4]. E. Bostanci, B. Bostanci. Object Localization and Spatial Analysis Using Computer Vision. International Journal of Machine Learning and Computing, Vol. 1, No. 2, June 2011. Pp. 1-5.

[5]. L. Bazzani, A. Bergamo, D. Anguelov, L. Torresani. Self-Taught Object Localization with Deep Networks. Proceeding of Winter Conference on Applications of Computer Vision (WACV 2016), (New York, USA, 2016) pp. 1-9..

Abstract: The study investigates the causes of aggressive behavior among secondary school students in Ilorin East of Kwara State. Data for the study was collected from secondary school teachers through structured interviews. Twelve research questions were consequently raised, survey was carried out in ten (10) secondary schools which represented single sex and co-educational schools. Data were obtained through judicious use of questionnaires on teachers their responses were analyzed in percentages. The result obtained indicates that students home background and up-bringing take the lead in influencing the character of children. Other causes of aggression are that; Students behaved aggressively when their needs are not met (66); and are influence by School cliques-groups with conflicting ideas and values causes indiscipline among students thus ;Students do what is expected of them by the group to which they belong; at homes Parents constant indiscipline and quarreling at home influence the..........

Keyword—Agressiveness, Behaviour, Emotions, Adolescence and Peer-Group

[1] Alfred, A. (2003). Learning and environment. Chicago: University Press.
[2] Bellow, J.Y. (2005). Educational Psychology of learning. Nigeria: Havey Publication Company.
[3] Derek, W. (2004). The psychology of morale behaviour. Harmonds. Middlesex England: Penguin Books Limited.
[4] Dollard, Doab, Muller, Mower and Sears (2005). Economics and Educational Policy. New York. Longman.
[5] Donn, Bryne and Kathryn, K. (2003). Psychology, personal and social adjustment. New York: Haper and Rowe Publishers...

Abstract: The bacterium treponema pallidum, which is a subspecie of pallidum, is the primary cause of syphilis. Syphilis is a contagious disease which is mostly transmitted through sex either anal or oral sex. The approach on ground of the classification of syphilis is too precise proving a sharp contraction between bondaries. In addressing this precise approach a fuzzy approach was adopted to provide non-precise boundaries overlapping classes in classifying Secondary syphilis into "Mild", "Moderate" and Severe". This approach is objective with the aim of quick and objective recognition, based on available objective decision variables, parameters or criteria.

Keyword—Fuzzy Classifier, Fuzzy Logic, Fuzzy Cluster, Syphilis, Set theory

[1] Angelov P., Zhou X. (2008), Evolving Fuzzy-Rule-based Classifiers from Data Streams, IEEE Transactions on Fuzzy Systems, ISSN 1063-6706, special issue on Evolving Fuzzy Systems, December 2008, vol. 16, No6, pp.1462-1475.
[2] Babuska R. (1998), Fuzzy Modeling for Control, Kluwer Academic Publishers, Boston, USA.

[3] CDC: Centre for Disease Control and prevention (2015), Syphilis, retrieved from CDC.com, 2 June, 2017.
[4] Christos S. and Dimitros S. (2008) "Neural Network", retrieved from http://www.docstoc.com/docs/15050/neural-networks.
[5] Cordon O., Jesus M. J., Herrera F. (1999), "A proposal on reasoning methods in fuzzy rule-based classification systems", International Journal of Approximate Reasoning, 20 (1), 1999, pp.22-45, 1999.

Abstract: Due to the availability of documents in the digital form becoming enormous the need to access them into more adjustable way becoming extremely important. In this context,document management tasks based on content is called as IR or Information Retrieval. Thishas achieved a noticeable position in the area of information system.For faster response time of IR,it is very important and essential to organize,categorize and classify texts and digital documents according to the definitions,proposed by Text Mining experts and Computer scientists.Automatic text Categorization or Topic Spotting,is a process to sorta document set automatically into categories from a predefined set.According to researchers the superior access to this problem depends on machine learning methods in which,a general posteriori process builds a classifier automatically by learning pre-classified documents given and the...........

Keyword—Text Classification, Text Mining, Machine Learning, Support Vector Machine.

[1] Anurag Sarkar, Saptarshi Chatterjee, Writayan Das, Debabrata Datta, "Text Classification using Support Vector Machine", International Journak of Engineering Science Invention, volume 4, Issue 11, November 2015.
[2] Istvan Pilaszy, "Text Categorization and Support Vector Machine",Department of Measurement and Information System Budapest University of Technology and Economics.
[3] Fabrizio Sebastiani, "Machine Learning in Automated Text Categorization",ACM computing survey, Consiglio Nazionale delle Ricerche, Italy, 26th October 2001.
[4] Mojgan Farhoodi, Alireza Yari, "Applying Machine Learning Algorithm for Automatic Persian Text Classification", Iran Telecommunication Research Center.
[5] Pradnya Kumbhar, Manisha Mali, Dr. Mohammad Atique, "A Genetic-Fuzzy Approach for Automatic Text Categorization", IEEE 7th International Advance Computing Conference, 2017.

Abstract: Check in perspective of passwords is used, all things considered, in applications for PC security and insurance. In any case, human exercises, for instance, picking terrible passwords and contributing passwords shakily are seen as statement the weakest association quote in the check chain. Rather than optional alphanumeric strings, customers tend to pick passwords either short or noteworthy for straightforward recognition. With web applications and adaptable applications stacking up, people can get to these applications at whatever point and wherever with various contraptions. This advancement brings remarkable settlement also extends the probability of exhibiting passwords to endure surfing strikes..........

Keyword—Graphical Passwords, Authentication, Shoulder Surfing Attack, PassMatrix, Security and protection, Login Indicator, Encryption, Decryption

[1] Rohan Rao, Ajay Tambe, Rama Khude and Digambar Patil, Image-Based System to Resist ShoulderSurfing Attack Over Web,International journal of emerging technology and computer science(Volume: 1 Issue: 4),2017.
[2] S. Wiedenbeck, J. Waters, J. Birget, A. Brodskiy, andN. Memon,"Passpoints: Design and longitudinalevaluation of a graphicalpassword system," International Journal of Human-Computer Studies, Vol 64

[3] M. Kumar, T. Garfinkel, D. Boneh, and T. Winograd, "Reducing shoulder-surfing by using gaze-basedpassword entry, in Proceedings of the 3rd symposium on Usable privacy and security. ACM, 2007
Theses:
[4] Xiaoyuan Suo, ADesign andAnalysis of Graphical Password, Ying Zhu., College of Arts and Sciences, GeorgiaStateUniversity, August 2006
Proceedings Papers:
[5] Hung-Min Sun, Shiuan-Tung Chen, Jyh-Haw Yeh and Chia-Yun Cheng,A Shoulder Surfing Resistant Graphical Authenticatio System, IEEE Transactions on Dependable and Secure Computing (Volume:PP , Issue: 99 ),09 March 2016.

Abstract: Green Information and Communication Technology (ICT) is the study and practice of using computing resources efficiently to achieve economic viability and improved system performance and use while abiding by ethical and social responsibilities. Green ICT frameworks are useful in measuring and evaluating different organizations' Green ICT efforts. Some frameworks make it easier to interpret and measure green ICT than others, while some do not offer guidance on which metrics to use. Features of Green ICT frameworks have not been studied and documented adequately. Furthermore, existing green ICT frameworks are all static, and have one major limitation, that is the inability to address the common guidelines and procedures for evaluating the implementation of greening ICT and ICT...........

Keyword—ICT, Green ICT, Attitude, Technology, Practice and Policy..

[1] Bordens, K. S., & Abbott, B. B. (2011). Research Design and Methods A Process Approach. New York: McGraw-Hill.
[2] Council of European Professional Informatics Societies (CEPIS). (2012). Energy Efficient Enterprise in Europe Green ICT Awareness in Organisations. Retrieved Augast 23, 2013, from http://cepis.org:http://cepis.org/media/GreenICTSurveyReport_v1.20131.pdf
[3] Curtis, D., & Lingarchani, A. (2011). Green ICT System Architecture Frameworks. In B. Unhelkar, Handbook of Research on Green ICT: Technology, Business and Social Perspectives (pp. 446-457). New York: IGI Global.
[4] Dawson, C. (2009). Introduction to Research Methods. Oxford : How To Content. Denscombe, M. (2007). The Good Research Guide for small-scale social research projects. Berkshire: Open University
[5] Jain, H. (2011). Green ICT Organizational Implementations and Workplace Relationships. In B. Unhelkar, Handbook Research on Green ICT: Technology, Business and Social Perspectives (pp. 146-150). New York: IGI Global.

Abstract:The computational cost in terms of computation time and memory utilization of various techniques in the development of face recognition applications is a major challenge. The fundamental properties of high dimension exhibited by face images leads to superfluous information that instigates computational burden in term of processing speed and memory usage.Support Vector Machine despite being a wonderful face recognition technique due its generalization capability and high theoretical background of classification accuracy consumes large amount of time and memory: a major setback in its implementation in real world applications. Consequently, a hybrid cultural algorithm is proposed to reduce the computational cost of SVM in face recognition applications. Cultural Algorithm optimises the parameter of SVM to lessen the computation requirement. The experimental results reveal that the proposed technique does not only improves the efficiency of SVM but also makes it less computationally expensive in terms of both computation time and memory utilization..

Keyword—Computation Cost, Cultural Algorithm, Culture Particle Swamp Optimization, Feature Selection, Support Vector Machine..

[1]. E. O. Omidiora, A. O. Fakolujo, R. O. Ayeni and I. A. Adeyanju, Optimised Fisher Discriminant Analysis for Recognition of Faces
Having Black Features. Journal of Engineering and Applied Sciences, 3 (7), 2008, 524-531.
[2]. A. S. Abdallah, A. L. Abbott and M. A. El-Nasr, A new face detection technique using 2D DCT and self-organizing feature map.
In Proc. of World Academy of Science, Engineering and Technology, 21, 2007, 15-19.
[3]. C. Beumier and M. Acheroy, Automatic Face Recognition, in Proceedings symposium IMAGING. Eindhoven, The Netherlands,
2000, 77-89.
[4]. R. S. Babatunde, S. O. Olabiyisi, E. O. Omidiora and R. A. Ganiyu. Local Binary Pattern and Ant Colony Optimization Based
Feature Dimensionality Reduction Technique for Face Recognition Systems. British Journal of Mathematics & Computer Science,
11(5), 2015, 1-11.
[5]. A. S. Tolba, A. H. El-Baz, and A. A. El-Harby. Face recognition: A literature review. International Journal of Signal
Processing, 2(2), 2006, 88-103..