iosr-JCE   Volume-19 ~ Issue-1 ~ Jan-Feb 2017

Abstract: The purpose of the study is to explore web security status of the E-Governance websites and web applications. The central theme of the paper is to study and analyze the security vulnerabilities in the technologies utilized for E-Governance website and web application development. The study was conducted in the State of Gujarat,India. The data related to web development technologies, vulnerabilities affecting those technologies, vulnerability severity, and vulnerability type were gathered from 26 E-Governance website/Web application for detail analysis. The outcome of the study depicts the relationship between technology vis-a-vis vulnerability type and vulnerability severity.

Keyword: Web Security, Vulnerability, Risk, E-Governance

[1]. UNESCO, "E-Governance," UNESCO, 2001. [Online]. Available: http://portal.unesco.org/ci/en/ev.php-URL_ID=3038&URL_DO=DO_TOPIC&URL_SECTION=201.html. [Accessed 14 July 2016].
[2]. Sans. Institute, "Information Security Resource," SANS, [Online]. Available: https://www.sans.org/information-security/. [Accessed 14 July 2016].
[3]. P. Mittal and A. Kaur, "E-Governance - A challenge for India," International Journal of Advanced Research in Computer Engineering & Technology (IJARCET), vol. 2, no. 3, March 2013.
[4]. "Guidelines for Indian Government Websites," Department of Administrative Reforms and Public Grievances, Government of India, 2009.
[5]. "Guidelines for Registration, Hosting and periodic security audit of Government Websites," Science and Technology Department of Government of Gujarat, Gandhinagar, 2014.

Abstract: The purpose of the study is to explore and find a research gap in E-Governance Information Security (InfoSec) domain in Indian Context. The study identifies the research gap in E-Governance InfoSec domain and substantiates given research gap with relevant literature review. The study outcomes clearly depict the requirement of research in the field of InfoSec in e-governance domain in a country like India.

Keywords: E-Governance, Information Security, Risk Assessment, Vulnerability, Threat

[1]. UNESCO, "E-Governance," UNESCO, 2001. [Online]. Available: http://portal.unesco.org/ci/en/ev.php-URL_ID=3038&URL_DO=DO_TOPIC&URL_SECTION=201.html. [Accessed 14 July 2016].
[2]. SANS Institute, "Information Security Resource," SANS, [Online]. Available: https://www.sans.org/information-security/. [Accessed 14 July 2016].
[3]. M. Wimmer and B. v. Bredow, "A Holistic Approach for providing security solutions in E-Government," in 35th Hawaii International Conference on System Sciences, Hawaii, 2002.
[4]. S. Alfawaz, L. May and K. Mohanak, "E-Governace Security in developing countries:A managerial conceptual framework," International Research Society for Public Management, 2008.
[5]. P. Mittal and Amandeepkaur, "E-Governance - A challenge for India," International Journal of Advanced Research in Computer Engineering & Technology (IJARCET), vol. 2, no. 3, March 2013

Abstract: Big data problem in intrusion detection system is mainly due to the large volume of the data. The dimension of the original data is 41. Some of the feature of original data are unnecessary. In this process, the volume of data has expanded into hundreds and thousands of gigabytes(GB) of information. The dimension span of data and volume can be reduced and the system is enhanced by using K-NN and BA. The reduction ratio of K-DD datasets and processing speed is very slow so the data has been reduced for extracting features by Bees Algorithm (AB) and use K-nearest neighbors as classification (KNN). So, the KDD99 datasets applied in the experiments with significant features. The results have gave higher detection and accuracy rate as well as reduced false positive rate.

Keywords: Big Data; Intrusion detection system; K-NN method; Bees algorithm; feature selection

[1]. A.Suebsing, N. Hiransakolwong "Euclidean-based Feature Selection for Network Intrusion Detection" 2009 International Conference on Machine Learning and Computing IPCSIT vol.3 (2011) IACSIT Press, Singapore.
[2]. R.-Ching Chen and K.Fan Cheng "Using Rough Set and Support VectorMachine for Network Intrusion Detection" International Journal of NetworkSecurity & Its Applications (IJNSA),Vol 1, No 1, April 2009.
[3]. K. Rufai, R.Chandren "Improving Bee Algorithm Based Feature Selection in Intrusion Detection System Using Membrane Computing" Journal of Networks, vol. 9, no. 3, March 2014.
[4]. A. Sabry and E. Zeynep " A new feature selection model based on ID3 and bees algorithm for intrusiondetection system"Turkish Journal of Electrical Engineering & Computer Sciences Turk J Elec Eng & Comp Sci(2015) .
[5]. A. Amin, M. Bin Ibne Reaz "A novel SVM-kNN-PSO ensemble method for intrusion detection system" Department of Electrical, Electronic & Systems Engineering, Faculty of Engineering & Built Environment, National University of Malaysia, 43600 UKM Bangi, Selangor Darul Ehsan, Malaysia 2016.

Abstract: Effective traffic management is the need of the hour to solve issues related to transportation of vehicles on roads considering the environment, technology, government policies, etc. Vehicles either two or four wheeler has been increasing at very phenomenal rate year by year leading to congestion, pollution and wastage of man-hours waiting at signal lights for a longer period leading to loss of productivity, reduced quality of life. This ever growing problem has to be controlled by having an efficient solution. Hence traffic survey and analysis is required to be done to introspect the traffic density............

Keywords: Traffic Congestion, Traffic density, Traffic Signal Controller

[1]. Deepti Srinivasan, Min Chee Choy, and Ruey Long Cheu, "Neural Networks for Real-Time Traffic Signal Control", IEEE Transactions On Intelligent Transportation Systems, Vol. 7, No. 3, September 2006, pp. 261-272.
[2]. S. Chiu and S. Chand, "Self-organizing traffic control via fuzzy logic," in Proc. 32nd IEEE Conf. Decision Control, 1993, pp. 1987–1902.
[3]. G. Nakamiti and F. Gomide, "Fuzzy sets in distributed traffic control," in Proc. 5th IEEE Int. Conf. Fuzzy Syst., 1996, pp. 1617–1623.
[4]. S. Mikami and Y. Kakazu, "Genetic reinforcement learning for cooperative traffic signal control," in Proc. 1st IEEE Conf. Evol. Comput., vol. 1, 1994, pp. 223–228.
[5]. W. Wei and Y. Zhang, "FL-FN based traffic signal control," in Proc. FUZZ-IEEE, May 12–17, 2002, vol. 1, pp. 296–300

Abstract: As we probably aware now a days networks are broadly dispersed so administrators relies on upon different devices, for example, pings and follow course to troubleshoot the issue in network. So we proposed a robotized and orderly approach for testing and troubleshooting network called "Automatic Test Packet Generation"(ATPG). ATPG first peruses switch arrangement and produces a gadget free model. The model is utilized to produce least number of test packets to cover each connection in a network and every control in network. ATPG is equipped for researching..............

Keywords: Fault Localization, Test Packet Selection, Network Debugging, Automatic Test packet Generation (ATPG), Forwarding Information Base (FIB).

[1]. Zeng, Kazemian, Varghese,and Nick "Automatic Test Packet Generation",VOL. 22, NO. 2, APRIL 2014
[2]. Y. Bejerano and R. Rastogi, "Robust monitoring of link delays and faults in IP networks," IEEE/ACM Trans Netw., vol. 14, no. 5, pp. 1092–1103, Oct. 2006
[3]. N. Duffield, "Network tomography of binary network performance characteristics," IEEE Trans. Inf. Theory, vol. 52, no. 12, pp. 5373–5388, Dec. 2006.
[4]. N. Duffield, F. L. Presti, V. Paxson, andD.Towsley,"Inferringlink loss using striped unicast probes," in Proc. IEEE INFOCOM, 2001, vol. 2, pp. 915–923.
[5]. Y. Bejerano and R. Rastogi, "Robust monitoring of link delays and faults in IP networks," IEEE/ACM Trans. Netw., vol. 14, no. 5, pp. 1092–1103, Oct. 2006.

Abstract: Cervical cancer is the highest rate of incidence after breast cancer, gastric cancer, colorectal cancer, thyroid cancer among all malignant that occurs to females ; also it is the most prevalent cancer among female genital cancers. Manual cervical cancer diagnosis methods are costly and sometimes result inaccurate diagnosis caused by human error but machine assisted classification system can reduce financial costs and increase screening accuracy. In this research article, we have developed multi class cervical classification system by using Pap Smear Images according to the WHO descriptive Classification of Cervical Histology...............

Keywords: Cervical Cancer, Pap Smear Images, Feature Extraction, Classification

[1] S.Athinarayanan, Dr.M.V.Srinath & R.Kavitha " Computer aided diagnosis for detection and stage identification of cervical cancer by using pap smear screening test images" ictact journal of image and video processing, ISSN: 0976-9102 vol. 6, no.4, May 2016. pp. 1244 – 1251.
[2] S. Aswathy, M. A. Quereshi, B. Kurian, and K. Leelamoni, "Cervical cancer screening: current knowledge & practice among women in a rural population of Kerala, India," Indian Journal of Medical Research, vol. 136, no. 2, pp. 205–210, 2012.
[3] S.Athinarayanan, Dr.M.V.Srinath, "Classification of Cervical Cancer Cells in Pap Smea Screenig Test" ictact journal of image and video processing, ISSN: 0976-9102 vol. 6, no.4, May 2016. pp. 1234 – 1238.
[4] B. L. Craine, E. R. Craine, J. R. Engel, and N. T. Wemple, "A clinical system for digital imaging Colposcopy," in Medical Imaging II, vol. 0914 of Proceedings of SPIE, pp. 505–511, Newport Beach, Calif, USA, June 1998.
[5] H. Doornewaard, Y. T. van der Schouw, Y. van der Graaf, A. B. Bos, and J. G. van den Tweel, "Observer variation in cytologic grading for cervical dysplasia of Papanicolaou smears with the PAPNET testing system," Cancer, vol. 87, no. 4, pp. 178–183, 1999.

Abstract: Digital resume provides insights about a candidate to the organization. This paper proposes a system where digital resumes of candidates are generated by extracting data from social networking sites like Facebook, Twitter and LinkedIn. Data which is relevant to recruitment is obtained from unstructured data using Data Mining algorithms. Candidates are evaluated based on their digital resumes and ranked accordingly. Ranking is done based on the requirements specified by an organization for a key position................

Keywords: Recruitment, Digital Resume, Digital Profile, Digital Footprint, Candidate Ranking.

[1]. Digital Footprints: Pros, Cons and Future by Prof. Anjana R. Arakerimath, Pramod Kumar Gupta MCA Department.Pimpri Chinchwad College of Engineering, Savitribai Phule Pune University Pune, Maharashtra 411044, India.
[2]. A Twitter-based smoking cessation recruitment system by Ahmed Abdeen Hamed, Xindong Wui and James R Fingar.
[3]. Social Media Mining, an ebook by Reza Zafarani, Mohammad Ali Abbasi, Huan Liu.
[4]. A framework to identify educational relevance in social networking posts by Muhammad Fahim Uddin, University of Bridgeport.
[5]. Recruiting with Social Media: Social Media's Impact on Recruitment and HR, an ebook by Raj Anand.

Abstract: Data mining means to the process of collecting, searching through, and analyzing a large amount of data in a database. Classification in one of the well-known data mining techniques for analyzing the performance of Naive Bayes, Random Forest, and Naïve Bayes tree (NB-Tree) classifier during the classification to improve precision, recall, f-measure, and accuracy. These three algorithms, of Naive Bayes, Random Forest, and NB-Tree are useful and efficient, has been tested in the medical dataset for diabetes disease and solving classification problem in data mining. In this paper, we compare the three different algorithms, and results indicate the Naive Bayes algorithms are able to achieve high accuracy rate along with minimum error rate when compared to other algorithms.

Keywords: Data mining, Classification, Naive Bayes, Random Forest, NB-Tree, Weka

[1]. Joachims T., 1998, "Text categorization with support vector machines: Learning with many relevant features," ECML'98. pp.137-142.
[2]. Quinlan J., 1993, "C4.5:Programs for Machine Learning, ". The Morgan Kaufmann.
[3]. AI-hegami A. "Pruning Based Interestingness of Mined Classification Patterns.
[4]. International Arab Journal of Information Technology. Vol. 6, No. 4, pp. 336-343, 2009.
[5]. Manish M., Rakesh A., and Jorma R., 1996, "SLIQ: A Fast Scalable Classifier for Data Mining," Int. Conference on Extending Database Technology(EDBT'96), Avignon, France.

Abstract: Cloud processing is turning into an inexorably mainstream endeavor demonstrate in which figuring assets are made accessible on-request to the client as required. The one of a kind incentivized offer of distributed computing makes new chances to adjust IT and business objectives. Distributed computing utilizes the web advancements for conveyance of IT-Enabled abilities 'as an administration' to any required clients i.e. through distributed computing we can get to anything that we need from anyplace to any PC without agonizing over anything like about their stockpiling, cost............

Keywords: Cloud Computing, Cloud Services, Scalability, Vertical Scaling, Virtualization

[1]. Onur , E., Sfakianakis, E., Papagianni, C., Karagiannis, G., Kontos, Intelligent End-To-End Resource Virtualization Using Service Oriented Architecture Delft Univ. of Technol., Delft, Netherlands, GLOBECOM Workshops, IEEE, 28 December 2009.
[2]. Buyya R, "Market-Oriented Cloud Computing: Vision, Hype, and Reality of Delivering Computing as the 5th Utility," 9th IEEE/ACM International Symposium on Cluster Computing and the Grid, pp. 1, 2009.
[3]. G. Gruman, "What cloud computing really means", InfoWorld, Jan. 2009.
[4]. R. Buyya, Y. S. Chee, and V. Srikumar, Market-Oriented Cloud Computing: Vision, Hype, and Reality for Delivering IT Services as Computing Utilities, Department of Computer Science and Software Engineering, University of Melbourne, Australia, pp. 9, July 2008.
[5]. C. Braun, M. Kunze, J. Nimis, and S. Tai. Cloud Computing, Web-based Dynamic IT-Services". Springer Verlag, Berlin, Heidelberg, 2010

Abstract: Time To Market isspeed at which the company can transform product ideas into saleable product. Customers are ready to pay premium price for short response time, consequently timeliness in present times translates into revenue .

[1]. Managing the Global Supply Chain by TajeSkjott-Larsen. [2]. Concurrent Engineering Techniques and Advancement by C.T Leondes .

Abstract: Virtualization and cloud computing is creating a fundamental change in computer architecture, software and tools development, in the way we store, distribute and consume information. In the recent era of autonomic computing it comes the importance and need of basic concepts of having and sharing various hardware and software and other resources & applications that can manage themself with high level of human guidance. Virtualization or Autonomic computing is not a new to the world, but it developed rapidly with Cloud computing. In this paper there give an overview of various types of computing. There will be discussion on Cluster, Grid computing, Utility & Cloud Computing. Analysis architecture, differences between them, characteristics , its working, advantages and disadvantages

Keywords: Cluster computing, Grid computing, Utility computing, Cloud computing, Virtual machine monitor (VMM).

[1]. Comparison between Cloud Computing, Grid Computing, Cluster Computing and Virtualization Rakesh Kumar Department of Information Technology JECRC, Jaipur,
[2]. Comparative study between Cluster, Grid, Utility, Cloud and Autonomic computing 1Samah Mawia Ibrahim Omer, 2Amin Babiker A.Mustafa, 3Fatema Abdallah Elmahdi Alghali
[3]. Seyyed Mohsen Hashemi, Amid Khatibi Bardsiri (MAY 2012) "Cloud Computing Vs. Grid Computing", ARPN Journal of Systems and Software, VOL. 2, NO.5.
[4]. Siddharth Jain, Rakesh Kumar, Sourabh Kumawat, Sunil Kumar Jangir (Novenber, 2014) "An analysis of security and privacy issues, Challenges with possible solution in cloud computing", National Conference on Computational and Mathematical Sciences (COMPUTATIA-IV), Technically Sponsored By: ISITA and RAOPS, Jaipur.
[5]. Rakesh Kumar, Neha Gupta, Shilpi Charu, Somya Bansal, Kusum Yadav (August, 2014) "Comparison of SQL with HiveQL", International Journal for Research in Technological Studies, Vol. 1, Issue 9, ISSN (online): 2348-1439, pg. 28-30.

Abstract: Data mining is a process to extract information from a huge amount of data and transform it into an understandable structure. Data mining provides the number of tasks to extract data from large databases such as Classification, Clustering, Regression, Association rule mining. This paper provides the concept of Classification. Classification is an important data mining technique based on machine learning which is used to classify the each item on the bases of features of the item with respect to the predefined set of classes or groups. This paper summarises various techniques that are implemented for the classification such as k-NN, Decision Tree, Naïve Bayes, SVM, ANN and RF. The techniques are analyzed and compared on the basis of their advantages and disadvantages.

Keywords: Introduction, classification and techniques, Advantages and Disadvantages.

[1]. Manisha Kannvdiya,Kailash Patidar and Rishi Singh Kushwaha , "A Survey On: Different Techniques And Features Of Data Classification", International Journal Of Research In Computer Applications And Robotics, Volume 4 Issue 6, pg 1-6, June 2016.
[2]. Shital H. Bhojani and Dr. Nirav Bhatt, "Data Mining Techniques and Trends – A Review", Global Journal For Research Analysis , Volume -5 , Issue -5 ,pg 252-254, May 2016.
[3]. Supreet Kaur and Amanjot Kaur Grewal, "A Review Paper on Data Mining Classification Techniques for Detection of Lung Cancer", International Research Journal of Engineering and Technology (IRJET), Volume: 03 Issue: 11, pg 1334-1338, Nov 2016.
[4]. Navjot Kaur, "Data Mining Techniques used in Crime Analysis: - A Review", International Research Journal of Engineering and Technology (IRJET), Volume: 03 Issue: 08, pg 1981-1984, Aug-2016.
[5]. Trilok Chand Sharma and Manoj Jain, "WEKA Approach for Comparative Study of Classification Algorithm", International Journal of Advanced Research in Computer and Communication Engineering, Vol. 2, Issue 4,pg 1925-1931, April 2013.

Abstract: Technological Advancement is the mainstay of the Indian economy. Software Development is a primary factor which offers many sources of employment across the state. The major role of Software Company is to provide qualitized product by Managerial Decisions. To improve the Software Quality and Maintenance, Organization concentrates the Programmer's ability and restricts the Placement with various kinds of audiences such as Written test, Personal Interview, Technical Round, Group Discussion etc. Accordingly, Programmer's has to be formed. So Higher Educational institutes have to amend the student's Performance as their expectations............

Keywords: Decision_Making, Association_Rule, Clustering, Classification, Rule Prediction, Preprocessing

[1]. D.Magdalene Delighta Angeline, "Association Rule Generation For Student Performance Analysis Using Apriori Algorithm " ,The SIJ Transactions on Computer Science Engineering and its Applications(CSEA), Vol. ,No. 1,March –April 2013.
[2]. Randa Kh. Hemaid, Alaa M.EL-Halees, "Improving Teacher Performance Using Data Mining", International Journal of Advanced Research in Computer and Communication Engineering Vol. 4, Issue 2, February 2015.
[3]. Charanjit Bambrah, Minakshi Bhandari, Nirali Maniar, Prof. Vandana Munde4, "Mining Association Rules in Student Assessment Data", International journal of Advanced Research in Computer and Communication Engineering Vol. 3,Issue 3, March 2014.
[4]. Mrs.Smita Bhanap, Mrs.Rasika Kulkarni, "Student – Teacher Model for Higher Education System", Current Trends in Technology and Science, ISSN: 2279-0535, Volume: Volume-II, Issue: Issue-III.
[5]. P.Ajith, B.Tejaswi, M.S.S.Sai, "Rule Mining Framework for Students Performance Evaluation", International Journal of Soft Computing and Engineering (IJSCE), ISSN: 2231-2307.Volume-2. Issue – 6, January 2013.

Abstract: Software-Defined Networking(SDN) allows you to have a logical image of the components in the data center, also you could arrange the components logically and use them according to the software application needs. This paper gives an overview about the architectural features of Cisco's Application Centric Infrastructure (ACI) and Vmware's NSX and also compares both the architectures and their benefits.

Keywords: ACI, NCX, Nexus, Vmware, VLAN, VXLAN, NVGRE SDDC.

[1]. Muzzamil Aziz, Sdn-Enabled Application-Aware Networking For Data Center Networks, Electronics, Circuits And Systems (Icecs)

Abstract: Land Cover maps supply information about the physical material at the surface of the earth (i.e. grass, trees, bare ground, asphalt, water, etc.). Usually they are 2d representations so to present variability of land covers in reference to latitude and longitude or other type of earth coordinates. Possibility to link this variability to the terrain elevation is very useful because it permits to investigate probable correlations between the type of physical material at the surface and the relief............

Keywords: 3D visualization, Land Cover Map, GIS, DEM

[1] P. Mileff, K. Nehéz, K., and J. Dudra, Accelerated Half-Space Triangle Rasterization, Acta Polytechnica Hungarica, 12(7), 2015, 217-236.
[2] B. H. McCormick, T. A. De Fanti, and M. D. Brown, Visualization in scientific computing, IEEE Computer Graphics and Applications, 7(10), 1987, 69-69.
[3] P. R. Thota, 3D Visualization of Highway Corridors: The I-77/81 Case Study near Wytheville, doctoral diss., Virginia Polytechnic Institute and State University, 2002.
[4] M. E. Haklay, Virtual reality and GIS: Applications, trends and directions, in P. Fisher, and D. Unwin, Virtual Reality in Geography, 5 (New York: Taylor & Francis, 2002) 47-57.
[5] P. Maglione, C. Parente, R. Santamaria, and A. Vallario, Modelli tematici 3D della copertura del suolo a partire da DTM e immagini telerilevate ad alta risoluzione WorldView-2, Rendiconti Online della Società Geologica Italiana, 30, 2014, 33-40.

Abstract: This paper presents a new investigation for cryptanalysis stream cipher based on Genetic Algorithm(GAs), Particle Swarm Optimization (PSO).GA and PSO utilized for the automatic recovery of the key, and hence the plaintext. Based on a mathematical model, it is shown that such algorithms can be used to reduce the number of trials which are needed to determine the initial state of the attacked generator using ciphertext only attack. Thesealgorithms have been shown to be effective at finding optimal solutions. Experimental results show the ability of GA and PSO in finding the correct secret key which is used to recover the plaintext.

Keywords: Cryptanalysis, Particle Swarm Optimization, Genetic Algorithms

[1]. Schneier, B.1996, Applied Cryptography, Second Edition: Protocols,AlgorithmsandSource Code in C.
[2]. Delman,B.2004,Genetic Algorithm in Cryptography,Doctorol thesis, Rochester Institute of Technology.
[3]. Holland,J.H.1992,Adaptation in Natural and Artificial Systems.
[4]. M.Milanovic,"Solving the generalised vertex cover problem byGenetic Algorithm ", Computing and Informatics,2010.
[5]. H.Bhasin,M.Amini,"The applicability of Genetic Algorithm to Vertex cover", International Journal of ComputerApplication,2015

Abstract: Cooperative communication gains much research attention nowadays to meet the high data rate in cellular networks and wireless ad-hoc networks. User cooperation is promising techniques to improve the performance of wireless networks, where multiple nodes share their resources to achieve transmit diversity. Coded cooperative communication is one of the cooperative system in which cooperation is combined with channel coding there by achieve inherent benefits of spatial diversity and added benefits of channel coding. In coded cooperative communication instead of repeating the codeword each user tries to add some incremental redundancy for its partner. Space time cooperation is an extension to coded cooperative communication in which the second frame itself enjoys the path diversity.

Keywords: Cooperative communication, Coded cooperative communication, Space Time cooperation

[1] Nosratinia, Aria, Todd E. Hunter, and Ahmadreza Hedayat."Cooperative communication in wireless networks." IEEE communications Magazine 42.10 (2004): 74-80.

[2] Hunter, Todd E., and Aria Nosratinia. "Performance analysis of coded cooperation diversity." Communications, 2003. ICC'03. IEEE International Conference on. Vol. 4. IEEE, 2003.

[3] Hunter, Todd E., Shahab Sanayei, and Aria Nosratinia. "Outage analysis of coded cooperation." IEEE Transactions on Information Theory 52.2 (2006): 375-391.

[4] Janani, Mohammad, et al. "Coded cooperation in wireless communications: space-time transmission and iterative decoding." IEEE Transactions on Signal Processing 52.2 (2004): 362-371.

[5] Laneman, J. Nicholas, David NC Tse, and Gregory W. Wornell. "Cooperative diversity in wireless networks: Efficient protocols and outage behavior." IEEE Transactions on Information theory 50.12 (2004): 3062-3080

Abstract: One of the main objectives of data analysis in industrial contexts is prediction, that is, to identify a function that allows predicting the value of a response from the values of other variables considered as potential predictors of this outcome. The large volumes of data that current technology allows to generate and store have made it necessary to develop methods of analysis alternative to the traditional ones to achieve this objective, which allow mainly to process these large amounts of information and to predict the response in real time. Enclosed under the name of Data Mining, many of these new methods are based on automatic algorithms mostly originated in the computer field............

Keywords: CART decision trees; Linear regression; Measurement error; Prediction Error

[1] W.J. Frawley, G. Piatetsky-Shapiro and C. Matheus, Knowledge Discovery in Databases: An Overview, AI Magazine, 13(3), 1992, 57-70.
[2] H-J. Mittag, Measurement Error Effect on Control Chart Performance, Annual Quality Congress, 49(0), 1995, 66-73.
[3] H-J. Mittag, Measurement Error Effects on the Performance of Process Capability Indices, Frontiers in Statistical Quality Control, 5, 1997, 195-206
[4] S. Bordignon and M. Scagliarini, Statistical Analysis of Process Capability Indices with Measurement Errors, Quality and Reliability Engineering International, 18, 200, 321-332.
[5] D. Shishebori and A.Z. Hamadani, The Effect of Gauge Measurement Capability and Dependency Measure of Process Variables on the MCp, Journal of Industrial and Systems Engineering, 4(1), 2009, 59-76.

Abstract: In this paper a new technology of controlling the crowed is presented this technique can be implemented in real events. By this technology the time schedule, security, contingency plans and entry/exit can be maintained. In this technology the application software is utilized to control the crowed. So the title is given as "Soft Crowed Management". The application software uses the PHP Technology and the Maps shown in the software uses the RS/GIS and GPS Technology. Which are used in demarcation of the crowed control points/locations.

Keywords: RS/GIS, GPS, application software, PHP, crowed management.

[1]. K.S. Sudhi, "Crowd management crisis looms large over Sabarimala", The Hindu, KOCHI, December 25, 2015
[2]. Lauren Bradshaw, "Crowd Management Plan for an Existing Outdoor Event research paper", Custom Writing. Com September 30, 2011.
[3]. Spiro G. Doukas, "Crowd Management: Past and Contemporary Issues" The Sport Journal, ISSN: 1543-9518
[4]. Mohd. Fazil Ali, AbulBasharandAsadullah Shah, "SmartCrowd: Novel Approach to Big Crowd Management Using Mobile Cloud Computing", Conference: International Cloud Computing Conference ICCC 2015, At Riyadh Saudi Arabia, DOI: 10.1109/CLOUDCOMP.2015.7149656
[5]. Marine Profile Sweden AB, "Crowed Management", Academia.edu

Abstract: Speech synthesizers based on paramedic methods, still have not achieved the expected naturalness. This is due to less consideration on linear time variant nature between the neighbor phonemes. This paper presents a study to model the phoneme transitions between neighbor phonemes with lesser number of parameters using Auto Regressive Moving Average (ARMA) model, where Steiglitz-McBride algorithm is used to estimate the zeros and poles of the system. The results are compared with an Auto Regressive (AR) model, which show that the correlation between the source signal and the reconstructed signal in ARMA model is higher than that of the AR model.

Keywords: Auto Regressive (AR) model, Auto Regressive Moving Average (ARMA) model, Correlation Coefficient, phoneme transition, Speech synthesis

[1]. P.Taylor, Text to Speech Synthesis, Cambridge University Press, 2009.
[2]. J. Holmes, W. Holmes, Speech Synthesis and Recognition, Second Edition, Taylor & Francis, 2001. [3]. J.Benesty, M. M. Sondhi, Y. Huang, Springer Handbook of Speech Processing. Springer.2008.
[4]. L. Rabiner, B. Juang, Fundamentals of speech Recognition, Prentice Hall International, 1993
[5]. J. K. Sharma, Business statistics. Pearson Education India. 2007.

Abstract: Modern data sharing mechanisms introduce new opportunities for easier and faster data sharing among mobile devices. Many data sharing mobile applications using these mechanisms have succeeded due to efficient data transfer capabilities. In this work, we explore the possibilities of bringing in an improved sharing scheme that would allow sender devices to serve files to receiver without having to know them in a conventional method like it would in a traditional data sharing scenario; making it possible for mobile devices to receive files from nearby users without their immediate consent.

Keywords: Data sharing; Ad-Hoc network; mobile devices; Server; Client.

[1] SHAREit. Lenovo Apps, n.d. Web. 15 December 2016. http://shareit.lenovo.com/
[2] Xender. Anmobi.Inc, n.d. Web. 15 December 2017. http://www.xender.com/about.html

Abstract: This is the era of huge and large sets of data or can say Big Data. Clustering of Big data plays several important roles for Big Data analytics. In this paper, we are introducing Big Data clustering algorithm by combining Genetic and K-Means algorithm using Hadoop framework. The major aim of this hybrid algorithm is to make clustering process faster and also raise the accuracy of resultant clusters...........

Keywords: Big Data Analytics, Genetic Algorithm, Hadoop, K-Means, MapReduce,

[1] Amr Adel, Esaam ElFakharany and Amr Badr, "Clustering Tweets Using Cellular Genetic Algorithm", Journal of Computer Science, Volume 10, Issue 7, pp 1269-1280, 2014.
[2] Filomena Ferrucci, M-Tahar Kechadi, "A Parallel Genetic Algorithm Framework Based on MapReduce",30th annual ACM symposium on Applied Computing, pp 1785-1793, 2015.
[3] Aditya B. Patel, Manashvi Birla, Ushma Nair, "Addressing Big Data Problem using Hadoop and MapReduce", Nirma University International Conference on Engineering (IEEE) , 2012
[4] Isabel Anger and Christian Kittl, "Measuring Influence on Twitter", 11th international Conference on Knowledge Management and Knowledge Technologies (ACM), 2011.
[5] Akilesh P. chunne , Uddagiri Chandrasekhar , Chetan Malhotra , " Real Time Clustering of Tweets using Adaptive PSO Technique and MapReduce", Global conference of Communication Technologies ( IEEE) , pp 452 – 457 , 2015

Abstract: In this paper, the diversity gains of wireless relay networks were exploited. The proposed cooperative scheme using the first best relay for providing the highest SNR at the destination, whereas the second best relay is used for suboptimal SNR at the destination. The source communicates with the single antenna destination, with the help of multiple AF relays, equipped with a single antenna. Specifically, the BEP and outage probability performance of AF cooperation with the first and second best-relay selection scheme were investigated.............

Keywords: BEP; hybrid relay selection; outage probability.

[1] A. Bletsas, H. Shin, M. Z. Win, and A. Lippman, A simple cooperative diversity method based on network path selection, IEEE J. Sel. Areas Commun., 24(3), 2006, 659-672.
[2] S. Ikki and M. H. Ahmed, Performance of multiple-relay cooperative diversity systems with best relay selection over Rayleigh fading channels, EURASIP J. Adv. Signal Process., 2008, 2008, 1-7.
[3] P. K. Vitthaladevuni and M. S. Alouini, BER computation of 4/M-QAM hierarchical constellations, IEEE Trans. Broadcast., 47(3), 2001, 228-239.
[4] Y. Zhao, R. Adve, and T. J. Lim, Improving amplify-and-forward relay networks: Optimal power allocation versus selection, IEEE Trans. Wireless Commun., 6(8), 2007, 3114-3123.
[5] X. Rui, Decode-and-forward with partial relay selection, International journal of communication systems, 23(11), 2010, 1443-1448.

Abstract: Compact Microstrip antennas have recently received much attention due to the increasing demand of small antennas for personal communication equipment. The problem of achieving impedance bandwidth greater
than or about 10% for present day cellular communication systems for a compact microstrip antenna is becoming an important topic in microstrip antenna design. A study of low cost Microstrip line fed shorted patch
antenna has been presented in this paper. Because both shorted patch and 50Ω microstrip feed line have an air substrate, the material cost is reduced to a minimum. Also a comparative study of the antennas without and
with slots of different geometries has been presented. The proposed antenna without slot has a band width of 18.5%. A Considerable size reduction is obtained with the vertical slots and an enhanced bandwidth of 25.2%
with the inclined slots. The designs are suitable for applications in DCS (Digital Communication Systems) base station.

Keywords: Microstrip antenna, Compact antenna, Shorted patch, Microstrip line fed

[1]. Kin-Lu Wang, Compact and Broadband Microstrip Antennas, John Wiley and Sons Inc., 2002.
[2]. K. Fujimoto and J.R. James, Mobile Antenna System Handbook, 2nd Edition, Artech House Inc., 2001.
[3]. R.G. Vaughan and J.B. Anderson, "Antenna Diversity in Mobile Communication" IEEE Transactions, Antennas and Propagation, vol. 49, June 1987, pp. 954-960.
[4]. Shun-Yun Lin and Kuang-Chih Huang, "A Compact Microstrip Antenna For GP and DCS Application" IEEE Trans, Antennas and Propag., vol. 53, no 3, March 2005, pp. 1227-1229.
[5]. Su. S.W. and J. H. Chou, "Low cost Flat Metal Plate Dipole Antenna for 2.4/5 GHz WLAN Operation" Microw. Opt. Tech. Lett., vol. 50, 2008, pp. 1686-1687.

Abstract: This paper presents a novel design of two elements rectangular microstrip array antenna with parasitic wire around (TERMAA) for triple band operation and omni directional radiation pattern. Further,
quadruple bands are obtained by simply minimizing the area of ground plane of TERMAA. Later, by truncating the corners of minimized ground plane, the upper two bands are merged together resulting wider triple band
operation. The magnitude of each operating band is found to be 19.1, 15.43 and 79.23% respectively with a maximum gain of 3.9 dB. This enhancement does not affect the nature of radiation characteristics. The proposed
antennas may find applications for microwave systems operating at WLAN (2.4 – 5.2 GHz), HIPERLAN/2 (5.725 – 5.825 GHz) and X to Ku (8 – 18.5 GHz) band of frequencies. Details of antenna design are described
and experimental results are discussed.

Keywords: microstrip antenna, array antenna, minimized ground plane, triple-band, omni directional.

[1]. Wang .W., et. al. (2004), "A dual polarized stacked microstrip antenna sub array for X-band SAR application", IEEE Antennas and
Propag, Soc. Inter. Symp, Vol.2, pp.1603-1606.
[2]. Waterhouse .R.B and Shuley N.V (1992), "Dual frequency microstrip rectangular patches", Electron Lett, Vol.28, No.07, pp.606-
607.
[3]. Richards .W.F., et. al. (1985), "Dual-band reactively loaded microstrip antenna", IEEE Trans Antennas Propag, Vol. 33, No.5,
pp.556-560.
[4]. Wang .J., et. al. (1990), "Multifunctional aperture coupled stack patch antenna", Electron Lett, Vol.26, No.25, pp.2067-2068.
[5]. Salvador .C (1995), "Dual frequency planer antennas at S and X bands", Electron Lett, Vol.31, No.20, pp.1706-1707.

Abstract: Light profile, low weight, low cost fabrication, enhanced patch area reduction with improved bandwidth and gain are the key characteristics for the antenna designed for wireless communication
applications under S and L band frequency spectra. Microstrip patch antenna (MPA) suits the features mentioned except for its narrow bandwidth and low gain. This paper experimentally investigates an approach to
achieve enhanced patch area reduction (of 23 %) without increasing the complexity of MSA too much with improved impedance bandwidth, gain for applications such as WiMax services, UK fixed satellite services,
aeronautical mobile application, maritime mobile services covering the microwave frequency range from 3 - 4 GHz. Experimental results of return loss, impedance bandwidth, radiation pattern, Smith chart characteristics
and gain are discussed and presented..

Keywords:Microstrip antenna, dual frequency, patch area reduction, WiMax, maritime mobile services, antenna gain .

[1]. Gao, S. C., L. W. Li, and M. S. Leong (2002), "Small dual- frequency micro- strip antennas," IEEE Transactions on Vehicular Technology, Vol. 51, No. 1, pp.28-36.
[2]. Lu, J.-H. (2003), "Broadband dual-frequency operation of circular patch antennas and arrays with a pair of L-shaped slots," IEEE Transactions on Antennas and Propagation, Vol. 51, No. 5, pp. 1018- 1023.
[3]. Guo, Y.-X., I. Ang, and M. Y. W. Chia (2003), "Compact internal multi- band antennas for mobile handsets," IEEE Antennas and Wireless Propagation Letters, Vol. 2, pp.143-146.
[4]. Cheng-shong H (1999), "Gain enhanced broadband microstrip antenna", Proc.Natl.Sci.Counc.Roc(A),Vol.23, No.5, pp. 609-611.
[5]. T. S. Laverghetta (1996), Practical Microwaves, Prentice Hall, Englewood Cliffs, N.J.Kumar G., Ray K.P (2003), Broadband Microstrip Antennas, ArtechHouse, Inc, London.