iosr-JCE   Volume-17 ~ Issue-2 ~ March-April 2015

Abstract: Current information retrieval process concentrate in downloading web content and analyzing and indexing from surface web, exist of interlinked HTML pages. Information retrieval has limitations if the data is behind the query interface. Answer depends on the uncertainty party's circumstance in classify to connect in dialogue and negotiate for the information .in this paper we proposed Approach , resource selection & integration of invisible web and show through our proposed algorithm is effective another algorithm. We show through the experiment result our algorithm more effective. Invisible web searching contributes to the development of a general framework.

Keywords: Invisible web, Information retrieval, resource selection, integration of invisible web.

[1]. Ying Wang, Wanli Zuo, Tao Peng, Fengling He," Domain-Specific Deep Web Sources Discovery" Domain-Specific Deep Web Sources Discovery- 2008 IEEE.
[2]. Jia-Ling Koh and Nonhlanhla Shongwe, Chung-Wen Cho," A Multi-level Hierarchical Index Structure for Supporting Efficient Similarity Search on Tag Sets" 978-1-4577-1938-7/12/-2011 IEEE.
[3]. Bao-hua Qiang, Jian-qing Xi, Bao-hua Qiang, Long Zhang," An Effective Schema Extraction Algorithm on the Deep Web" 978-1-4244-2108-4/08/ 2008 IEEE .
[4]. parul ,Dr. A.K. Sharma," A framework for hierarchical clustering based indexing in search"PGDC-2010.
[5]. J.C. Chuang, C.W. Cho, and A.L.P. Chen, "Similarity Search in Transaction Databases with a Two Level Bounding Mechanism," in Proceeding of the 11th International Conference of Database Systems for Advanced Applications (DASFAA), 2006.
[6]. Jia-Ling Koh and Nonhlanhla Shongwe, Chung-Wen Cho," A Multi-level Hierarchical Index Structure for Supporting Efficient Similarity Search on Tag Sets" 978-1-4577-1938-7/12/ IEEE- 2011.

Abstract: Digital image processing is the use of computer algorithms to perform image processing on digital images. It is a subfield of digital signal processing. Digital image processing has many advantages over analog image processing; it allows a much wider range of algorithms to be applied to the input data, and can avoid problems such as the build-up of noise and signal distortion during processing. Since images are defined over two dimensions digital image processing can be modeled in the form of Multidimensional Systems.

[1]. D. L. B. Jupp, A. H. Strahler and C.E. Woodcock , "Autocorrelation and Regularization In Digital Images - Image Basic Theory", IEEE Transactions on Geosciences and Remote Sensing, Vol. 26, No. 4, pp. 463-473, 1988.
[2]. Amogh Mahapatra and Rajballav Dash, B.Tech Thesis On "Data Encryption And Decryption By using Hill Cipher Technique And Self repetitive Matrix", Department of Electronics & Instrumentation Engineering, National Institute of Technology ,Rourkela,2007.
[3]. B A Forouzan, Cryptography & Network Security , McGraw- Hill, India , 2007.
[4]. Castleman, K.R., Digital Image Processing. Second ed. 1996, Englewood Cliffs, New Jersey: Prentice-Hall.
[5]. Castleman, K.R., Digital Image Processing. Second ed. 1996, Englewood Cliffs, New Jersey: Prentice-Hall.
[6]. Dr. D. M. Shah, "Image Encryption & Decryption model".

Abstract: E-government is getting a positive thrust in view of `Digital India Project` initiatives by the current government in India. At present, information and communication technology (ICT) has become an essential prerequisite in all government`s service delivery mechanisms and the idea of governance becomes 24x7 phenomenon. E-governance tools facilitate citizens an efficient, transparent, flexible and comprehensive service delivery platform. The success of any CCS (Citizen Centric System) is now largely dependent on the implementation of an integrated EAF or web based service delivery model specifically. New technologies influenced the innovations in governance at large scale. The ICDS (Integrated Child Development Services/Schemes) is a very diverse program implemented throughout the country with some specified goals regarding child/woman welfare. At present almost every state of India implements the different programs of ICDS.There are two important instigations of this research paper, first is to study and analyze all short comings of the current and previous works regarding e-governance initiatives taken in implementation of service delivery process in CCS of ICDS throughout the country and second is to explore and outline/design an effective integrated EAF or a web based service delivery model (WBSDM) for the CCS of ICDS in India.

Keywords: E-Governance, E-Governance Tools, CCS, ICDS, EAF, Web Quality Characteristics.

[1]. Gupta A., Gupta S.K., Baridalyne N.,"ICDS:A journey of 37 years", Indian Journal of Community Health,Vol. 25,Jan-Mar 2013
[2]. Bhudeb Charavarti, M.Venugopal,"Citizen Centric Service Delivery through E- government Portal-Present scenario in India", White Paper NiSG, 2008.
[3]. E-Governance: http//www.iadb.org/ict4dev/ Governance-html
[4]. Marawar, T. Kale, S. Araspure, K. ""E Governance": IEEE Data Storage and Data Engineering (DSDE)", 2010 International Conference on : 9-10 Feb. 2010 Dept. of Computer . Technology. RTM Nagpur Univ.Nagpur, India.
[5]. Brian H. Cameron and Eric McMillan "Analyzing the Current Trends in Enterprise Architecture Frameworks " Journal of Enterprise Architecture – February 2013
[6]. Bhudeb Chakravarti, Senior Member IEEE and Vasudeva Varma, Member, IEEE "An Enterprise Architecture Framework for Building Service Oriented e-Governance Portal"

Abstract: An ad-hoc network is a collection of mobile hosts with wireless network interfaces that may form a temporary network without the aid of any established infrastructure of centralized administration. In such environment, the nodes operate both as hosts as well as routers. Due to mobility, the topology of the network may change randomly, rapidly and unexpectedly. The objective of the work is to present effective decision algorithm that improves network performance. In the proposed technique, we defuzzyfy the values of delay, packet success rate, bandwidth and find out the threshold for these parameters for current session. In the path selection each node checks for its suitability with respect to the threshold corresponding to the parameters. If a node satisfies the condition then only it is included in the path otherwise node is omitted from the path.

Keywords: Adhoc Network, Fuzzy Logic, AODV, Routing, MANET

[1]. Samarth H. Shah, Kai Chen, Klara Nahrstedt, Available Traffic condition Estimation in IEEE 802.11-based Wireless Networks,,Department of Computer Science University of Illinois at Urbana-Champaign.
[2]. Lei Chen, and Wendi B. Heinzelman, QoS-Aware Routing Based on Traffic condition Estimation for Mobile Ad Hoc Networks, IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, VOL. 23, NO. 3, MARCH 2005
[3]. S. Chen and K. Nahrstedt, "Distributed quality-of-service in ad hoc networks,"IEEE J. Sel. Areas Commun., vol. 17, no. 8, Aug. 1999.
[4]. Fethi Filali," QoS Issues and Solutions in Wireless Networks", CNRS- GDR – ARP – QoS Day :Paris, June 4, 2004
[5]. R. S. Prasad M. Murray_ C. Dovrolis K. Claffy,"Traffic condition estimation: metrics, measurement techniques, and tools"

Abstract:An important approach to text mining involves the use of natural-language information extraction. Information extraction (IE) distils structured data or knowledge from unstructured text by identifying references to named entities as well as stated relationships between such entities. IE systems can be used to directly extricate abstract knowledge from a text corpus, or to extract concrete data from a set of documents which can then be further analyzed with traditional data-mining techniques to discover more general patterns. Here is the methods and implemented systems for both of these approaches and summarize results on mining real text corpora of biomedical abstracts, job announcements, and product descriptions. Challenges that arise when employing current information extraction technology to discover knowledge in text are considered. Additionally, latest IEP which is accumulated in database can be used for the offline working. The system fetches content of current web page, stores and updates data to database, so that user can browse data online as well as offline.
Keywords-Indicative Extraction Patterns (IEP), Information Extraction (IE)

[1]. Shasha Li, Chin-Yew Lin, Young-In Song and Zhoujum Li. 2013.Comparable Entity Mining From Comparative Questions. National University of Defense Technology, Changsha, China
[2]. ZornitsaKozareva, Ellen Riloff, and Eduard Hovy. 2008. Semantic class learning from the web with hyponym pattern linkage graphs. In Proceedings of ACL-08: HLT, pages 1048–1056.
[3]. Nitin Jindal and Bing Liu.2006a.Identifying comparative sentences in text documents. In Proceedings of SIGIR "06, pages 244–251.
[4]. Ellen Riloff.1996 Automatically Generating Extraction Pattern from Untagged Text
[5]. Ellen Riloff and Rosie Jones. 1999. Learning dictionaries for information extraction by multi-level bootstrapping. In Proceedings of AAAI "99 /IAAI "99, pages 474–479.
[6]. Guoping Hu1, Jingjing Liu2, Hang Li, Yunbo Cao, Jian-Yun Nie3, and Jianfeng Gao. A Supervised Learning Approach to Entity Search. Microsoft Research Asia, Beijing, China..

Abstract:Steganography is an art and a science of communicating in a way, which hides the existence of the communication. It is also called as "covered writing", because it uses a "cover" of a message for sending any important secret message. In the steganographic scenario, the secret data is first concealed within another object which is called "cover object", to form "stego-object" and then this new object can be transmitted or saved. Using different techniques, we can send secret data in the form of an image, a music file or even a video file by embedding it into the carrier, forming a stego-signal. At the receiver's end, the secret data can be recovered from the stego-signal using different algorithms. The main goal of Steganography is to communicate securely in a completely undetectable manner and to avoid drawing suspicion to the transmission of a hidden data. It is not only prevents others from knowing the hidden information, but it also prevents others from thinking that the information even exists. If a Steganography method causes someone to suspect there is secret information in a carrier medium, then the method has failed.

[1] "Information Hiding: A survey" (pdf). Proceedings of the IEEE (special issue) 87 (7): 1062–78. doi:10.1109/5.771065. Retrieved 2008-09-02.
[2] A New Text Steganography Method By Using Non-Printing Unicode Characters, Akbas E. Ali, Eng. & Tech. Journal, Vol.28, No.1, 2010
[3] B.r., Roshan Shetty; J., Rohith; V., Mukund; Honwade, Rohan; Rangaswamy, Shanta (2009). Steganography Using Sudoku Puzzle. pp. 623–626. doi:10.1109/ARTCom.2009.116.

Abstract: In daily use of internet, when searching information we face lots of difficulty due to the rapid growth of Information Resources. This is because of the fact that a single search engine cannot index the entire web of resources. A Meta Search Engine is a solution for this, which submits the query to many other search engines and returns summary of the results. Therefore, the search results receive are an aggregate result of multiple searches. This strategy gives our search a boarder scope than searching a single search engine, but the results are not always better. Because the Meta Search Engine must use its own algorithm to choose the best results from multiple search engines. In this paper we proposed a new Meta Search Engine to overcome these drawbacks. It uses a new page rank algorithm called modified ranking for ranking and optimizing the search results in an efficient way. It is a two phase ranking algorithm used for ordering the web pages based on their relevance and popularity. This Meta Search Engine is developed in such a way that it will produce more efficient results than traditional search engines.

Keywords: Metacrawler, Meta Search Engine, Ranking, Search Engine, Web Crawler

[1]. What Is A Search Engine? Digitallearn.Org a PLA Initiative, http://digitallearn.org/sites/default/files/clas
s/Basic%20Search/supplemental-materials/basicsearchhandout.pdf
[2]. Subarna Kumar Das, "Role Of Meta Search Engines In Web- Based Information System: Fundamentals And Challenges", 4th Convention Planner -2006, Mizoram Univ, Aizawl, 09-10 November, 2006
[3]. D.Minnie, S.Srinivasan, "Meta Search Engine With An Intelligent Interface For Information Retrieval On Multiple Domains", International Journal of Computer Science, Engineering and Information Technology (IJCSEIT), Vol.1, No.4, October 2011
[4]. Minky Jindal , Nisha Kharb, "K-Means Clustering Technique On Search Engine Dataset Using Data Mining Tool", International Journal of Information and Computation Technology. ISSN 0974-2239 Volume 3, Number 6 (2013), pp. 505-510
[5]. Sonali Kushwah, Avdhesh Singh, Indu Gupta, "Analysis on Meta Search Engine"
[6]. Trupti V. Udapure, Ravindra D. Kale, Rajesh C. Dharmik, "Study Of Web Crawler And Its Different Types", IOSR Journal of Computer Engineering (IOSR-JCE) e-Volume 16, Issue 1, Ver. VI (Feb. 2014), PP 01-05

Abstract: There have been enormous number of attacks recorded during electronic transmission of information between the source and intended receiver and indeed this has called for a more robust and efficient method for secured data transfer and making it more credible. Cryptography and Steganography are the widely used techniques that manipulates and conceal the information in order to cipher and hide their existence. These two techniques share the common goals and services of shielding the confidentiality, integrity andprevent the access of information by unauthorized users. In this project, a data hiding system which is grounded on audio steganography and cryptography is proposed for authenticateddata transfer. Steganographic medium used in this project is the audio medium. The encryption and decryption methods of cryptography used in developing this system make the surety of the proposed system more efficient in securing the data from unauthorized access. The system thus proposed is therefore recommended for use by the Internet users for founding a more safe and secure system. In this project, an audio medium is used as the steganographic and an advanced algorithm is applied for encoding the private data into the audio file.The goal of this research is to combine both cryptography and steganography in order to develop a better and credible communication in this unsecured open network.

Keywords: cryptography, decryption, encryption, Internet, steganography.

[1]. Vivek, J., Lokesh, K., Madhur, M. S., Mohd, S., and KshitizRastogi 2012. Public-Key Steganography Based on Modified LSB Method. Journal of Global Research in Computer Science, 3(4). ISSN: 2229-371X, pp. 26-29.
[2]. AbikoyeOluwakemi, C., AdewoleKayode, S., &OladipupoAyotunde, J. 2012. Efficient Data Hiding System using Cryptography and Steganography. International Journal of Applied Information Systems (IJAIS)–ISSN, 2249-0868,4(11).
[3]. Jayaram, P., Ranganatha, H. R. and Anupama, H. S. 2011. Information Hiding Using Audio Steganography – A Survey. International Journal of Multimedia and Its Application, 3(3), pp. 86-96.
[4]. Raphael, A. J., and Sundaram, V. 2011. Cryptography and Steganography - A Survey. International Journal of Computer Technology Application, 2(3), ISSN: 2229-6093, pp. 626-630.
[5]. Sujay, N. and Gaurav, P. 2010. Two New Approaches for Secured Image Steganography Using Cryptographic Techniques and Type Conversions. Signal & Image Processing: An International Journal (SIPIJ), 1(2), pp 60-73.
[6]. Mohammad, A. A., and Abdelfatah, A. Y. 2010. Public-Key Steganography Based on Matching Method. European Journal of Scientific Research, 40(2). ISSN: 1450-216X. EuroJournals Publishing, Inc., pp. 223-231. Retrieved 21st August, 2012 from http://www.eurojournals.com/ejsr.htm..

Abstract: Character Recognition is a prominent area in the field of image processing. Most of the basic concepts in image processing have been introduced in connection with research carried out in character recognition. Character recognition is still an active field of research and till now it has not acquired sufficient recognition efficiency. Character recognition is used in areas like postal address identification, mail sorting, and bank cheque processing and person identification. In this paper, we have provided a review on existing methods for handwritten character recognition based on geometrical properties of the character. The efficiency of the character recognition is depends on the appropriate preprocessing and feature extraction method. Handwritten character recognition is a difficult task because the handwriting is varying from person to person.

Keywords: Character Recognition, feature, geometrical, handwritten, preprocessing

[1]. Abdul Rahiman M and M.S. Rajasree, Recognition of Handwritten Malayalam Character using Vertical and Horizontal Line Positional Analyzer Algorithm, 3rd International Conference onMachine Learning and Computing, 2013.
[2]. Sumedha B. Hallale and Geeta .D. Salunke, Twelve Directional Feature Extraction for Handwritten English Character Recognition, International Journal of Recent Technology and Engineering, vol. 2, May.2013
[3]. Dayashankar Singh, Sanjay Kr. Singh and Maitreyee Dutta, Handwritten Character Recognition Using Twelve Directional Feature Input and Neural Network, International Journal of Computer Applications, vol. 1,no. 4, 2010.
[4]. Prachi Mukherji and Priti .P. Rege, Shape Feature and Fuzzy Logic Based Offine Devnagari Handwritten Optical Character Recognition, Journal of Pattern Recognition Research 4, June. 2009.
[5]. Parikh Nirav Tushar and Saurabh Upadhyay, Chain Code Based Handwritten Cursive Character Recognition System with Better Segmentation Using Neural Network, International Journal of Computational Engineering Research, vol.3, May. 2013.
[6]. Ved Prakash Agnihotri, Offline Handwritten Devanagari Script Recognition , I.J.Information Technology and Computer Science, pp. 37-48, July. 2012.

Abstract: The Word sense disambiguation approaches contain number of methods such as stacking, voting, in this paper we combined three approaches, Decision List as Master approach and Naïve Bayes, Adaboost a Slaves approaches, for combining models to increase the accuracy and WSD performance.

Keywords: Decision List, Naïve Bayes, Adaboost, Senseval-3, WSD, WordNet, Master-Slave technique, Voting, combination.

[1]. Nitin Indurkhya and Fred J. Damerau "HANDBOOK OF NATURAL LANGUAGE PROCESSING" SECOND EDITION. Chapman & Hall/CRC, USA, 2010.(book style). [2]. Boshra F. Zopon AL_Bayaty, Dr. Shashank Joshi, Conceptualisation of Knowledge Discovery from Web Search, Bharati Vidyapeeth University, International Journal of Scientific & Engineering Research, Volume 5, Issue 2, February-2014, pages 1246- 1248.
[3]. Boshra F. Zopon AL_Bayaty, Dr. Shashank Joshi, Decision List Master Approach to Solve WSD Problem, INTERNATIONAL JOURNAL FOR ADVANCE RESEARCH IN ENGINEERING AND TECHNOLOGY, Webpage: www.ijaret.org Volume 3, III, March 2015 ISSN 2320-6802,pages.29-33. [4]. Arindam Chatterjee, Roll No: 09305905, Under the guidance of Prof. Pushpak Bhattacharyya, Word Sense Disambiguation: Literature Survey, Chapter 1, page 1-2, Department of Computer Science and Engineering, Indian Institute of Technology, Bombay, 2012.
[5]. Boshra F. Zopon AL_Bayaty, Shashank Joshi, , Bharati Vidyapeeth University, Comparative Analysis between Naïve Bayes Algorithm and Decision Tree to Solve WSD Using Empirical Approach, International Conference on Knowledge and Software Engineering, http://www.lnse.org, LNSE 2016 Vol.4( 1), 2016, 82-86.

Abstract: Fingerprint techniques are widely used in authentication systems, therefore its privacy protection becomes an important issue. Securing a stored fingerprint template is very important because once fingerprints are compromised, it cannot be easily revoked. So, we review here a new system for preserving fingerprint confidentiality. In this system, the fingerprint privacy is maintained by combining two different fingerprints into a new identity. In the enrollment phase, two fingerprints are taken from two different fingers. We obtain the minutiae positions of one fingerprint, the orientation of another fingerprint, and the reference points from both fingerprints. Based on the obtained information, a combined minutiae template is generated and stored in a database. In the authentication phase, we use the fingerprints of the same fingers that are already used in enrollment phase. For matching the two query fingerprints against a combined minutiae template, a two-stage fingerprint matching process is used.

[1]. Sheng Li and A. C. Kot, "Fingerprint combination for privacy protection", IEEE Transactions on Information Forensics and Security, vol. 8, no. 2, Feb 2013.
[2]. B. J. A. Teoh, C. L. D. Ngo, and A. Goh, "Biohashing: Two factor authentication featuring fingerprint data and tokenised random number," Pattern Recognit., vol. 37, no. 11, pp. 2245– 2255, 2004.
[3]. N. K. Ratha, S. Chikkerur, J. H. Connell, and R. M. Bolle, "Generating cancelable fingerprint templates," IEEE Trans. Pattern Anal. Mach. Intell., vol. 29, no. 4, pp. 561–72, Apr. 2007.
[4]. K. Nandakumar, A. K. Jain, and S. Pankanti, "Fingerprint-based fuzzy vault: Implementation and performance," IEEE Trans. Inf. Forensics Security, vol. 2, no. 4, pp. 744–57, Dec. 2007.
[5]. S. Li and A. C. Kot, "Privacy protection of fingerprint database," IEEE Signal Process. Lett., vol. 18, no. 2, pp. 115–118, Feb. 2011.

Abstract: Higher learning institutions (HEI) are investing in IT to attain operational excellence. Organizations looking to reduce technology costs typically look for ways to reduce the Total Cost of Ownership (TCO). TCO captures all direct and indirect costs related to deploying a particular system. Understanding life-cycle costs provides opportunity to save scarce resources, improve IT and increase productivity. The study sought to analyze the TCO of university ERP system. The TCO analysis was based on Gartner's TCO model, the Distributed Computing Chart of Account as the theoretical framework. Modified Gartner TCO model was used to determine the total cost of owning Maseno University ERP system. The aim of the study was to create awareness on life-cycle costs of ERP solutions. The results obtained indicate that operations and maintenance account for 51%, end-user usage 23% while technology acquisition costs accounted for 16 %, implementation costs with 7% and the least cost was taken by procurements costs with 3%. Case study was used in gathering both qualitative and quantitative data from Maseno University. Interviews, document analysis, and questionnaires were used to gather the research data. It is hoped that the results of this study will help HEIs improve management of their ERP systems.

Keywords: Enterprise Resource Planning, Information System, IT metrics, TCO, Total cost of ownership

[1]. K. C., Laudon, & J. P. Laudon, (2010). Management Iformation System: Managing the Digital Firm. New York: Prentice Hall.
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[4]. G. Farrell, & I. Shafika,. (2007). Survey of ICT and Education in Africa: A Summary Report, Based on 53 Country Surveys. Retrieved from InfoDev: http://www.infodev.org/en/Publication.353.html
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[7]. M. A. Wouters, & Wynstra, F. (2005). The adoption of Total Cost of Ownership for sourcing decisions -A Structural Equations Analysis. Elsevier.

Abstract: Service-Oriented Architecture (SOA) has changed the way business enterprises get aligned with technology with a very fast pace keeping the demand of re-alignment time very short. Service-oriented architecture (SOA) carries significant commitment to impart an effective version for bias, agile and componentized IT which can be modified quickly. SOA removes the gap between software and business. The service-oriented application can be expensive to test because services are hosted remotely, are potentially shared among many users, and may have cost associated with their invocation. As classical testing approach and tools are not able to fit well, we have evolved a new approach to confront the increased complexity of the software. SV (Service virtualization) is the recent idea in software industry that grasp throughout the SDLC, it grow vigorously due to its artistry to address numerous constraints faced while development and testing. Service virtualization removes system dependency deadlocks by virtualizing or capturing and configuring the objective of the system's dynamic behavior, performance and data which acts and replies in the same manner as live one. The main benefit of using service virtualization is that the cost and time for testing is dramatically reduced, and quality is improved.

Keywords: Service-oriented Architecture (SOA); Service virtualization (SV); continuous testing; software dependency; unavailable and inaccessible components; dependency constraints; infrastructure cost reduction; third party system dependency.

[1]. Thomas Erl, "Service-oriented Architecture: Concept; Technology and Design", Pearson Education Publishing, 2nd Edition, 2013.
[2]. Gaurish Vijay Hattangadi, Rajiv Gupta, "Service Virtualization for Modern Application", Infosys White Paper, April 2011.
[3]. John Michelsen, "Key capabilities of a Service Virtualization Solution", ITKO-Infosys White Paper, July 2011.
[4]. Gaursih Vijay Hattangadi, "A Practitioner's Approach to Successfully Implementing Service Virtualization", Infosys White Paper, Sep. 2011.
[5]. CA LISA Virtualization http://itroisolutions.com/wpcontent/uploads/2014/02/acs2717-ca-lisa-servicevirtualization-ds- 08121.pdf
[6]. Dharmalingam Subbuah, Balaji Arulmozhi, Hariharasudhan Maruthamuthu, "Constraint free testing using service virtualization", Internatioanl Journal of Computer Applications, vol. 105- no. 17, November 2014.
[7]. Gaurish Vijay Hattangadi, "A Practitioner's Guide to Modern SOA Testing", Infosys White Paper, July 2011.

Abstract: Cloud computing is set of resources and services offered through the Internet. Cloud services are delivered from data centers located throughout the world. Cloud computing facilitates its consumers by providing virtual resources via internet. General example of cloud services is Google apps, provided by Google and Microsoft SharePoint. The rapid growth in field of "cloud computing" also increases severe security concerns. This paper aims to identify security threats in cloud computing, which will enable both end users and vendors to know about the key security threats associated with cloud computing.

[1]. Cloud Security Whitepaper , A Briefing on Cloud Security Challenges and Opportunities October 2013.
[2]. International Journal of Security and Its Applications Vol. 6, No. 4, October, 2012.
[3]. Security of Cloud Computing Providers Study. April 2011.
[4]. Identifying Cloud Computing Security Risks February 2011 .
[5]. Security Threats in Cloud Computing Environments1 October 2012.
[6]. Cloud Security Alliance, "Top threats to cloud computing", Cloud Security Alliance, March 2010.
[7]. Information Security Briefing 01/2010 Cloud computing .

Abstract: Load balancing is an integrated aspect of cloud computing. Inorder to achieve optimal machine utilization, tasks from overloaded virtual machines have to be transferred to underloaded virtual machines. In this paper, the honey bee foraging mechanism for load balancing is improved by random stealing technique. For finding the state of a virtual machine, the deviation of virtual machine load is calculated and checked for confinement within a threshold condition set. With random stealing method, tasks are stolen from a random Virtual machine when a VM is idle. It thus saves the idle time of the processing elements in the Virtual machine. The performance evaluation is done by using cloudSim. Simulation results show that the modified honey bee foraging technique with random stealing reduces the makespan of algorithm execution together with balancing system load and reduces the idle time of Virtual machine. Keywords: Bee foraging, Load balancing, Random stealing, Task scheduling, Thresholds

[1]. Dinesh Babu L.D, P.Venkata Krishna , "Honey Bee inspired Load Balancing of tasks in cloud computing environments", Applied soft computing 13,2292-2303,2013
[2]. Tejinder Sharma, Vijay Kumar Banga, "Efficient and Enhanced Algorithm in Cloud Computing",IJSCE,ISSN:2231-2301,2013
[3]. Joshua Samuel Raj, Hridya K.S,V. Vasudevan, "Augmenting Hierarchical Load Balancing with Intelligence in Grid Environment", International Journal of Grid and Distributed Computing Vol. 5,No. 2, pp. 9- 8, 2012
[4]. Guopu.Zha, Sam Kwong , "Gbest-guided Artificial bee Colony algorithm for numerical function optimization", Elsevier 3166-3173,2010
[5]. Ayed salman, Imtiaz Ahmad, "Particle swarm optimization for task assignment problem", Microprocessors and Microsystems 26,363-371,2002
[6]. Belabbas Yabougi, Meriem Meddeber, "Distributed Load balancing model", ARIMA journal, Vol 12,pp 43-60,2010
[7]. Erik Cuevas, Daniel Zaldívar, Marco Pérez-Cisneros, Humberto Sossa, Valentín Osuna, "Block matching algorithm for motion estimation based on ABC", Applied soft computing,2012

Abstract: Offline Script and language identification serves as a forerunner for a multi lingual Optical Character Recognizer (OCR). OCR is a software used for digitizing the handwritten or printed document mages. Most of the OCRs are designed for dealing with a single script. So it can't convert a document which contain more than one scripts. A country having multi lingual culture like India, multi lingual OCR is an essential software requirement for automation of handwritten documents processing. Script Identification consists of three steps Pre-processing, Features extraction and Classification. Based on the features extracted from the document images the classifier discriminates the script of the documents. This survey is an overview of different script identification methods for handwritten document images. They are classified into different categories based on the features and classification algorithm used.

Keywords: Handwritten documents, Optical Character Recognition, Script Identification

[1]. Debashis Ghosh, Tulika Dube, and Adamane P Shivaprasad Script recognitiona review, Pattern Analysis and Machine Intelligence, IEEE Transactions on 32 (2010).
[2]. Pal, Umapada and Jayadevan, Ramachandran and Sharma, Nabin Handwriting Recognition in Indian Regional Scripts: A Survey of Offline Techniques, ACM, March 2012
[3]. D GHOSH and AP SHIVAPRASAD, Handwritten script identification using probabilistic approach for cluster analysis, Journal of the Indian Institute of Science 80 (2013)
[4]. Judith Hochberg, Kevin Bowers, Michael Cannon, and Patrick Kelly, Script and language identification for handwritten document images, International Journal on Document Analysis and Recognition 2 (1999)

Abstract: In cloud computing , the following security functions are commonly considered are as follows, Cloud Data confidentiality ensures the owner that the stored data can be accessed only by an intended user and Cloud Data authentication ensures the group member that the data was accessed by a specified owner and the data was not altered en route. To provide these two functions,the Dynamic Group key protocol relies on one trusted entity, KGC (Key Generation Center), to choose the key, which is then transported to involved members. System uses interval based Interval Based algorithm for re-keying which not only reduce the key generation and sharing complexity, but also improves the owner data sharing efficiency and security.The main security goals for dynamic group key based data sharing in cloud to encrypt the data before sharing. Besides, the designated group manager can reveal the identity of the signature's originator when a dispute occurs, which is denoted as traceability.The goal is to secure the data sharing within group members,comparing AES algorithm with other encrypted algorithm and to analysis which algorithm suits for encrypting the data. Keywords: Bit Mangling , Cipher, Cryptanalysis.

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[2]. Xuefeng Liu, Yuqing Zhang, Boyang Wang, and JingboYan,"Mona: Secure Multi-Owner Data Sharing for Dynamic Groups in the Cloud", IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS, VOL.24, NO. 6, JUNE 2013
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Abstract: Images are often corrupted by impulse noise in the procedures of image acquisition and transmission. Here,an efficient denoising scheme and its structure for the removal of random valued impulse noise in images.To achieve the goal at low cost,a low complexity architecture is proposed.I employ a PCA based technique to estimate the noisy pixels, and an edge preserving filter to reconstruct the intensity values of noisy pixels. Furthermore, an adaptive technology is used to enhance the effects of removal of impulse noise. PCA is used to estimate the noise and an edge preserving filter is used to enhance the image. Extensive experimental results demonstrate that the proposed technique can obtain better performance in terms of both quantitative evaluation and visual quality than the previous lower complexity methods.

Keywords: PCA, Edge preserving filter, image denoising, impulse detector

[1]. [1] Chih-Yuan Lien, Chien-Chuan Huang, Pei-Yin Chen and Yi-Fan Lin,"AnE_cientDenoising Architecture for Removal of Impulse Noise in Images"IEEETrans.oncomputers,vol 62,NO 4,April 2013
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Abstract: Main problems of mobile computing are connections setbacks, bandwidth, heterogeneous webs and bottleneck issues. With the advent of the Internet and the plurality and collection of elaborate requests it held alongside it, the demand for extra elevated services on cellular phones is increasingly becoming urgent. Unfortunately, the new enabling technologies did not prosper in boosting new services. The adoption of Internet services has shown to be extra tough due to the difference amid the Internet and the mobile telecommunication system. Many examined the characteristics of the mobile arrangement and to elucidate the constraints that are imposed on continuing mobile services. This paper investigates the Web services for supporting for existing online and cloud based services for Smartphone's using middleware architectures.

Key Words: API, RESTful, SOA, symmetric and asymmetric cryptography, Mediation framework, Mediation Architecture, Web Services, Heterogeneity

[1]. Papazoglou, M.P., Traverso, P. and Leymann, F., 2003. "Service-oriented computing", International Journal of Cooperative Information Systems (IJCIS), Vol. 17, No. 2, pp. 25-28.
[2]. Fielding, R., 2010. "Architectural styles and the design of network-based software architectures", Ph.D. Dissertation, University of California, Irvine.
[3]. Asif, M. and Majumdar, S., 2008. "Performance analysis of Mobile Web Service Partitioning Frameworks", Proceedings of 16th IEEE International Conference on Advanced computing and Communications (ADCOM 2008), Carleton University, Ottawa, December 2008, pp. 190-197.
[4]. AlShahwan, F., 2010. "Evaluation of Distributed SOAP and RESTful Mobile Web Services", International Journal on Advances in Networks and Services, Vol. 3, No. 3, pp. 447-461.
[5]. Moessner, K. and AlShahwan, F., 2010. "Providing SOAP Web Services and RESTful Web Services from Mobile Hosts," Proceedings of Fifth International Conference on Internet and Web Applications and Services (ICIW 2010), University of Surrey, Guildford, UK, May 2010, pp. 174-179.

Abstract: Brain tumor is serious and life-threatening because it found in a specific area inside the skull. Computed Tomography (CT scan) which be directed into intracranial hole products a complete image of the brain. That image is visually examined by the expert radiologist for diagnosis of brain tumor. This study provides a computer aided method for calculating the area of the tumor with high accuracy is better than technique within CT scan device. This method determines the extracted the position and shape tumor based on morphological operations (dilation and erosion), enhancement filters and thresholding. Then, automatically calculate of tumor area for the area of interest.

Keywords: medical image, brain tumor, morphological processing.

[1]. H. Shum, S. Chan and S. Kang, Image-Based Rendering, (Springer Science-Business Media, LLC, Spring Street, New York, 2007).
[2]. D Chitradevi and M. Krishnamurthy, "A Survey on MRI based automated Brain Tumor Segmentation Techniques", International Journal of Advances in Computer Science and Technology, Vol. 3, No.11, November (2014).
[3]. K. Somasundaram and T. Kalaiselvi, "Automatic Detection of Brain Tumor from MRI Scans using Maxima Transform", National Conference on Image Processing, Vol. 1, (2010).
[4]. Amir Ehsan Lashkari, "A Neural Network-Based Method for Brain Abnormality betection in MR images using Zernike Moments and Geometric Moments", International Journal of Computer Application, vol. 4, issue 7, July (2010).
[5]. S. Patil and V. R. Udupi, "Preprocessing to be considered forMR and CT Images Containing tumors", IOSR Journal of Electrical and Electronics Engineering, Vol. 1, issue 4, July–August (2012).
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Abstract: Congestion control in packet switching networks became a high priority in network design and research due to ever-growing network bandwidth and intensive network applications. Dozens of various congestion control strategies have been proposed, and more are forthcoming. Based on control theory concepts congestion control can be viewed as control policy to achieve prescribed goals (e.g., round-trip delay or throughput) in a distributed network environment. This paper discusses the advantages, disadvantages and the applications of various congestion control protocols for wireless networks. It explores the motivation behind the design of congestion control protocols which is suitable to large scale wireless network and abolish drawbacks of the most widely accepted two algorithms of TCP and RCP.

Keywords: TCP- Transmission Control Protocol, RCP- Rate Control Protocol

[1]. S. Floyd, "HighSpeed TCP for Large Congestion Windows," RFC 3649 ,http://www.icir.org/floyd/hstcp.html, December 2003.
[2]. Dr.AtulGonsai, BhargaviGoswami&UditnarayanKar, "Newly developed Algorithm RCP+ for Congestion Control on large scale Wireless Networks", International Journal of Innovations & Advancement in Computer Science IJIACS ISSN 2347 – 8616 Volume 3, Issue 2Apri 2014
[3]. Dr.AtulGonsai, BhargaviGoswami, UditnarayanKar, "Evolution of Congestion Control Mechanisms for TCP and Non TCP Protocols" Matrix Academic International Online Journal Of Engineering And Technology © MAIOJET. 2013
[4]. NanditaDukkipati& Nick McKeown, "Why Flow-Completion Time is the Right Metric for Congestion Control and why this means we need New Algorithms", ACM SIGCOMM Computer Communication Review, Volume 36,2006
[5]. Chia-Hui Tai, Jiang Zhu, NanditaDukkipati, "Making large scale deployment of RCP practical for real networks" IEEE INFOCOM, 2008
[6]. Mehta Ishani, UditnarayanKar, Dr.AtulGonsai, "Why RCP is better than TCP" International Journal for Scientific Research & Development (IJSRD),Vol. 2, Issue 12, 2015