VOLUME 5, ISSUE 12, DECEMBER 2016

Abstract: Pervasive computing is a new technology which will be integrated into all the objects that interact with peoples, to enhancement and make people's routine lives easier through making the process of those objects interactive automatically to anything and everything in every place and at any moment of time in their environment without human intervention as possible. Security is very important element in pervasive computing environment to protect data that is transferred between devices connected with each other via (Wi-Fi or Bluetooth �etc.). This papers proposed a new secure method called HDOTP which is determine on Diffie-Hellman key exchanging to exchange and establish secret key and use this secure key as an initial key in One-Time pad algorithm with new algorithm for steam key generator to generate a random key and compared it with RSA and ElGamal according to parameter performance (runtime, memory usage, avalanche Effect, throughput) and concluded that HDOTP is more efficient than RSA and ElGamal.

Keywords: Pervasive computing environment, cryptography, RSA, ElGamal, Diffie-Hellman Key Exchange, One Time Pad, key stream.

Abstract: With the advancement in networking services, network security has become the key facet in our digital world. The term network security constitutes prevention of network and network resources by ceaseless monitoring and thereby denying the services like user access to network resources and modification of network configuration details from unauthorized users. Firewalls are one such network security system that monitors the inbound and outbound traffic of the network, this observation relies on two principal factors, Stateless and Stateful firewalls. The Stateless firewalls track the source and destination address of every incoming and outgoing data packets whereas the Stateful firewalls track each packet in the network by reading the entire header and thus it can read the type of data being transmitted. �PLUTO � A home office firewall� is a stateless firewall which can be used in Linux environment. The main motto behind developing the PLUTO as real time firewall is to demonstrate a real-time application for home office users through which they can secure their network.

Keywords: Pluto, home office firewall, firewalls, network perimeter security.

Abstract: Ranking of site pages is for showing important web pages to client inquiry it is a one of the essential issue in any web search index tool. Today�s need is to get significant data to client inquiry. Importance of web pages is depending on interest of users. There are two ranking algorithm is utilized to demonstrate the current raking framework. One is page rank and another is BM25 calculation. Reinforcement learning strategy learns from every connection with dynamic environment. In this paper Reinforcement learning (RL) ranking algorithm is proposed. In this learner is specialist who learns through interactopm with dynamic environment and gets reward of an activity performed. Every site page is considered as a state and fundamental point is to discover score of website page. Score of website pages is identified with number of out connections from current website page .Rank scores in RL rank as considered in recursive way. Along these lines we can enhance outcomes with help of RL method in ranking algorithm.

Keywords: Ranking, Search engine, Agent, Value function, Reinforcement Learning, Artificial intelligence.

Abstract: In this paper we consider the design issues in IoT and find that single heuristics cannot be used to optimize multiple objectives .So, we prefer a multi objective genetic algorithm approach to solve this design issues. We particularly consider the Pareto optimal solution which cannot be dominated by any other solution in solution space. We formulate 4 objectives for IoT design and try to minimize or maximize them as per the need in hand. The main aim is to obtain a refined IoT architecture. In a refined IoT architecture, design parameters are same but the input values to this parameters are within a boundary as specified by the Pareto solution set. This paper will help the IoT designer to consider the objective function in terms of IoT design factor and obtain a justifiable solution set to enhance the design ability of the IoT architecture.

Keywords: IoT, Genetic Algorithm, Pareto Optimal Solution, Multiobjective Optimization.

Abstract: Question Answering (QA) Systems are systems that attempts to answer questions posed by human in natural language. As a part of the QA system comes the question processing module. The question processing module serves several tasks including question classification and focus identification. Question classification and focus identification play crucial role in Question Answering systems. This paper describes and evaluates the techniques we developed for answer type detection based on question classification and focus identification in Arabic Question Answering systems. Question classification helps in providing the type of the expected answer and hence directing the answer extraction module to apply the proper technique for extracting the answer. While focus identification helps in ranking the candidate answers. Consequently, that has increased the accuracy of answers produced by the QA system. Question processing module involves analysing the questions in order to extract the important information for identifying what is being asked and how to approach answering it, and this is one of the most important components of a QA system. Therefore, we propose methods for solving two main problems in question analysis, namely question classi?cation and focus extraction.

Keywords: Question classification, Question focus extraction, Question Answering Systems, Information Retrieval, Natural Language Processing.

Abstract: In today�s highly developed word every person in society are express themselves via various number of medium on the internet every minute. At the every minute the large number of heterogeneous data is generated. This data may be in text format which are retrieved from forums and the social media websites. This data is also called as unstructured data. The thought of users related to the particular application or the topics like politics, economics, social affairs and products. These are extract from various type of technologies for the highly importance to make the forecast for one-to-one consumer marketing. In this paper we propose the analysis of the �Is selected android application genuine or fraud by android application users through their in order to mine what they think. Hence we are using hadoop framework for sentimental analysis which will process the large amount of data on a hadoop cluster faster.

Keywords: Sentiment analysis, Information extraction, Big Data, Hadoop, Stemming Algorithm, Tokenization, NLP.

Abstract: Hadoop provides distributed file system and a framework for the analysis and transformations of very large data sets using MapReduce. In a large cluster, thousands of servers both host directly attached storage and execute user application tasks. By distributing storage and computation across many servers, the resource can grow with demand while remaining economical at every size .Over the last few years; organizations across public and private sectors have made a strategic decision to turn big data into competitive advantage. The challenge of extracting value from big data is similar in many ways to the age-old problem of distilling business intelligence from transactional data. At the heart of this challenge is the process used to extract data from multiple sources, transform it to fit your analytical needs, and load it into a data ware house for subsequent analysis, a process known as �Extract, Transform Load�. The nature of big data requires that the infrastructure for this process cost-effectively. Apache Hadoop has emerged as the de facto standard for managing big data. In past few years Hadoop Distributed File System (hdfs) has been used by many organizations with gigantic data sets and streams of operations on it. HDFS provides distinct features like, high fault tolerance, scalability; etc. The Name node machine is a single point of failure (SPOF) for a HDFS cluster. If the name node machine fails the system needs to be re-starting manually the system less available.

Keywords: Big data, Hadoop, HDFS.

Abstract: Wireless sensor networks provide a significant contribution to the emerging field such as ubiquitous computing and ambient intelligence. Due to the inherent property of WSN, it is most vulnerable for reliability. In literature, most of the authors concern about network longevity and ignore fault tolerance. In this dissertation, we present an energy-efficient fault tolerable routing protocol (EEFT) mechanism for WSN. The major novelty of this work is that sensor nodes can send their data to alternate path during a fault. The energy efficient can be achieves using clustering protocol for routing. The subordinate for each cluster help to tolerate faults occurred in the proximity. The cluster head nodes in proximity propagate aggregated data to base station. The simulation results show that the proposed approach yields better performance than the existing methods. It has observed that the proposed protocol EEFT has better energy utilization than existing EE-LEACH and FTREEP protocols. The EEFT protocol also has better packet delivery ratio than FTEERP; it increased up to 53.60%.

Keywords: Energy efficiency; wireless sensor network; cluster head selection; fault tolerance.

Abstract: Electronics is the diverse field of engineering finding applications in almost all areas of human life. One of the most important applications is in biomedical engineering. Recent medical sciences and association claims that the number of the patients suffering from heart diseases increasing day by day. This might be due to changing life style, work load, over tension, competition, lack of exercise etc. So timely monitoring of such a patient�s heart activities like heartbeat, ECG is in demand now days. This further increases rush in the hospitals and increases patient expenditure also. This encourage us to design such a system which can monitor patient at his home place continuously or whenever required and all the body parameters could be shared by the doctor at hospital in real time. Whenever any parameter value exceeds normal range then SMS is also sent to the doctor thereafter rapid treatment can be provided to the patient. This project used ARM 7 LPC 2148 development board. Patients body temperature, heart beat and ECG are acquired from body through various sensors, processed it and displayed on LCD as well as on NI LabVIEW through HC 05 Bluetooth module. It is then transmitted to doctors PC using team viewer which provides connectivity in both sides. SIM 900 GSM/GPRS Module is used for sending the SMS. The objective of this project is to design a configuration system which will require optimum power for its operation and should be cost efficient.

Keywords: SIM 900, GSM/GPRS, NI LabVIEW, ECG, LUT.

Abstract: In the Smt. Chandaben Mohanbhai Patel Institute of Computer Applications, Charusat, allocation of subjects to faculties at the start of each new semester of academy year is a complex and tedious process. We propose a decision support system that attempts to maximize satisfactions for the overall faculty group. The system is able to improve the satisfaction level to 80%, even though some of the subjects may be heavily prioritized by faculty. Concept of Data Mining is used and it is shown to be effective. Results of subject allocation by the system have been positive. The system will greatly reduce the complex manual work of Principal/HoD for subject allocation. In addition, it will result in significant time saving for the Institute�s Subject Allocation Committee.

Keywords: Subject Allocation, Decision Support System, Faculty Members.

Abstract: Cryptographic algorithms are used as fundamental techniques for assuring confidentiality and integrity of data used in financial transactions and for authenticating entities involved in the transactions. Secure data transmission via Internet or any public network, there is no alternative to cryptography. It is widely used by governmental and intelligence agencies around the world to safe transmission of any format of messages-online or offline. No data online is secure unless use any type of cryptography to send your messages. Cryptographic algorithm development is a never-ending race as the cryptanalysts are also getting smatter with the advent of higher computer power of decoding secret codes.. This research will concentrate on increasing the complexity of block cipher encryption. Secure key based Treble Data Encryption Standard algorithm (STDES) is based on secure keys of Static IP address. STDES algorithms ensure the improved encryption performance, high secure and less encryption, decryption time. STDES algorithm is highly secure while improving the efficiency of cryptography algorithm.

Keywords: Secure key, Static IP address, Encryption, Decryption, Permutation, S-box.

Abstract: India is an agricultural based country. In recent trends knowledge are upgraded by mobile enabled information services. Farmers need advice to take decision during their farming activities. Application of required amount of fertilizer at proper time and proper proportion will help in increasing the overall productivity of the farm and also safe guards the soil health and microbial biodiversity. This paper expresses the idea about the creation of Fertilizer Apps( F Apps) an android application that helps in delivering the rice crop specific fertilizer quantity to be applied. The idea is to calculate the amount of NPK fertilizers to be applied based on the blanket recommendation for the villages in Manikandam Block in Tiruchirappalli district. This application works based on the rice crop, village selected by the farmer and that is taken as input, thus providing the farmers with the blanket recommendation of the NPK fertilizers and the amount of Urea, SSP and MOP to be applied for selected village.

Keywords: NPK, Urea, SSP, MOP, Android App, NPK, Manikandam Block.

Abstract: In recent year, technology development has taken place in communication standards such as fourth generation (4G) or fifth generation (5G) and we are experiencing a rapid growth in information and communication technologies. Moreover, the demand of higher data rates has been increasing with development in technology. Free Space Optic (FSO) connections are becoming an enchanting alternative for copper, RF and fiber optic communication techniques, in terms of speed, costing, distance and mobility. Higher data rate demands higher data security as well as reliability. Optical communication security is important not only at the management layer but also at the physical layer. The following article focuses on enhancements in FSO communication techniques to improve the reliability of the FSO link and data security. Line of Sight (LOS) is maintained using Fine Tracking System which uses 4-quadrant detector (4QD), the user data security can be achieved by implementing quantum cryptography, and a secure physical network can obtained by using Acousto-optic Deflectors (AOD).

Keywords: Acousto-optic deflector; Free space optic; Physical layer security; Data link layer security; User data security; quantum cryptography; Fine tracking system.

Abstract: The proper functioning of a grid depends mainly on the efficient management and use of grid resources to carry out the various jobs that users send for execution. In grid computing system management of resources and scheduling of jobs are the most crucial problem, a lot of effort had been made to efficiently schedule and manage resource in computational grid systems, scheduling policies such as, First Come First Serve which is a simple policy used to improve efficiency of the scheduler, even though it have been widely used, it therefore end up with invoking low system utilization of both global and local scheduler as a result of the gaps that exists in between the jobs submitted in the waiting queue. To improve system utilization and efficiency of both main and local schedulers back filling approach is used, this approach allows tasks or jobs in the waiting queue to fill in those gaps that exist. This paper proposes an efficient scheduling algorithm based on multi-gap elimination approach. The proposed algorithm uses intelligent agents in the scheduler to perform scheduling in a collaborative and coordinated way. The algorithm uses gap filling strategy to optimize priority rule algorithms in grid scheduling system by considering the available gaps in both global and local schedulers.

Keywords: Gap filling, Scheduler, Algorithm, Task.

Abstract: Every day twitter receives 500 million tweets with emerged as an invaluable source of news, blogs, unwanted information and more. Continuous tweet cannot show information correctly. Our proposed work consist summarization and opinion mining technique for data analysis. First collect the tweet online and historical from internet, in first technique opinion mining can show fast result and show emotion with score about online tweet by using sentiment analysis. Second technique summarization first cluster the tweet using K-means clustering algorithm ,tweet data structure represent statically known as tweet cluster vector and then formulation of incremental cluster is done. In summarization incremental tweet match with present tweet then add into the specific cluster; if not then declare it is in new cluster. By using summarization evolutes most trending topic very fast. The paper discussed study report of new approach for tweet summarization.

Keywords: Tweet stream, Summarization, Opinion mining, Topic detection.

Abstract: E-commerce (electronic commerce) or EC is the buying and selling of goods and services, or the transmitting of funds or data, over an electronic network, primarily the internet. These business transactions occur either as b to b (business-to-business), b to c (business-to-consumer), c to c (consumer-to-consumer) or c to b (consumer-to-business).It is the trading or in products or services using computer networks like Internet or online social networks. Here the Business conducted through the use of computers, telephones, fax machines, barcode readers, credit cards, automated teller machines (ATM) or other electronic appliances without the exchange of paper-based documents or physically moving to a shopping mall. It includes activities such as procurement, order entry, transaction processing, online payment, authentication, inventory control, order fulfillment, shipment, and customer support. When a buyer pays with a bank card swiped through a magnetic-stripe-reader, he or she is participating in e-commerce. E-commerce Security is a part of the Information Security framework and is specifically applied to the components that affect e-commerce including of Data security and other wider realms of the Information Security framework. E-commerce security is the protection of e-commerce assets from unauthorized access, use, alteration, or destruction. Dimensions of e-commerce security-Integrity, Non-repudiation, Authenticity, Confidentiality, Privacy, Availability. Ecommerce offers the banking industry great opportunity, but also creates a set of new risks and vulnerability such as security threats, hackings. Therefore it is an essential management and technical requirement for any efficient and effective Payment transaction activities over the internet. Due to the constant technological and business change and requires a coordinated match of algorithm and technical solutions. In this paper we discussed with Overview of security for e-commerce, various steps to place an order, Security purpose in E-commerce, various security issues in E-commerce, guidelines for secure online shopping etc.

Keywords: E-commerce, Non-repudiation, Authenticity, Confidentiality, Privacy, Availability.

Abstract: Virtual Learning Systems (VLS) are becoming an increasingly common form of education due to the need for a platform that provides ability to connect people with required sets of skills, regardless of their location in the world. However, user satisfaction has been a major factor in the success of software, regardless of whether the software is proprietary or freeware. Although user-centred designs are gaining recognition among VLS community, many design scenarios still do not incorporate usability as one of their primary goals. Accordingly, many individuals believe that if VLS was more usable, its popularity would increase tremendously. Although there are strong usability models for information systems, there is still potential to improve the usability of virtual learning systems. The usability assessment of VLS is an area where relatively little research has been conducted, and, accordingly, the main contribution of this work is a tool that evaluates the usability maturity of a virtual learning systems.

Keywords: VLS, Usability Maturity, User-Centred Design, Metrics.

Abstract: In recent years a number of studies have been carried out in relation to improvements in control methodologies for induction motors, and due to the great progress achieved in power electronics and microcontrollers, it has been possible to implement advanced Control for this type of electric motors. The purpose of this paper is to achieve the implementation of an advanced control technique, such as vector control for induction motors. Specifically, the methodology is Indirect Field Oriented Control (IFOC) based on the space vector pulse width modulation necessary for the control of the inverter that feeds the motor. The main characteristic of the vector control is that it allows direct control of the stator current according to the desired requirements and improving its efficiency. In this paper project the analysis and the implementation of indirect field oriented control (IFOC) for a three-phase induction motor. This control algorithm makes use of Two PI controllers are available for the currents, and another PI controller for the speed, which together make motor control possible. The main objective of the control is to follow a speed reference and maintain it in spite of the presence of disturbances. In addition, relationship between the reference speed and the reference current, in order to achieve control over a wider range of speeds. The software used to perform the simulations in this paper is MATLAB/ Simulink are used to perform the simulations of the mathematical model and the control algorithm .the components used are presented and the results obtained which shows the behaviour of the currents at different speed levels are high response.

Keywords: indirect field oriented control, PI controllers, space vector pulse width modulation.

Abstract: Mobile ad-hoc network is an infrastructure-less network in which the routing operation play important role in route discovery between communicating nodes. Due to infrastructure-less characteristic of ad-hoc network, it has different issues like routing, MAC layer, security etc. One of them is security issue which needs more concern. Vampire attacks modify targeted packets. It does so by preparing long routes or misguiding the packets. Malicious nodes use false messaging, or modify routing information. This action affects the bandwidth and node battery power. Routing as well as network resources gets protection from vampire attack; an approach is proposed to detect malicious routing packets. Present work gives result for different routing based attacks and discusses the issue of a serious resources consumption attack (Vampire Attack). The proposed approach uses the packet monitoring technique to detect malicious packet in the network. Proposed approach considers different network scenarios when using simulation. The basic principle behind the approach is that nodes check the received route request by comparing the packet header�s information (broadcast id and destination address) during route discovery phase and discard the malicious packets. A comparative performance study is performed in requisites of packet delivery ratio, throughput, routing overhead and energy consumption. It is found that Network performance improves as compared to the existing approaches.

Keywords: Security, Algorithm, Wireless ad-hoc network, Routing, Security Issue, Vampire Attack.

Abstract: Mobile ad hoc networks (MANETs) are highly dynamic in nature. They are used in various critical and urgent situations such as in a conference rooms, virtual lecture rooms, and communication in case of disaster. They do not have a fixed infrastructure and nodes have limited power and bandwidth. Energy aware routing protocols are required for routing packets and choosing an optimal path in terms of energy and bandwidth. This paper presents a literature survey of such energy aware routing protocols. These protocols are modified from existing routing protocols.

Keywords: Routing Protocols, MANETs, Energy efficient, DSR, AODV.

Abstract: Digital video forensics aims at validating the authenticity of videos by recovering information about their history. In a copy-paste forgery, a region from a video is replaced with another region from the same video. Because the copied part come from the same video, its important properties, such as noise, color palette and texture, will be compatible with the rest of the video and thus will be more difficult to distinguish and detect these parts. In this paper DWT is used to compress the frame and optical flow is used to detect the flow of the moving objects and the forgery object. But the sift technique is used to detect the key features of the original frame and the forgery frame..

Keywords: Frame, Video, forgery, DWT and SIFT etc.

Abstract: The most common and first method used to detect breast lesions is mammography. Due to less visibility, poor contrast and noisy nature of mammogram it is necessary to detect the small and non-noticeable cancers in early stage. In order to interpret the changes caused due to mental disorder of the breast the contrast of the images are improved while screening the mammograms. The architectural distortion is found in interpreting breast cancers as well as microcalcification and mass on mammograms. However, it is more difficult to detect architectural distortion than microcalcification and mass. The original mammogram image is decomposed using wavelet decomposition and gabor features are extracted from the original image Region of Interest (ROI). The ability of these features in detecting microcalcification is done using Backpropagation Neural Network (BPNN). The proposed classification approach is applied to a database of 322 dense mammographic images, originating from the MIAS database.This paper presents various techniques used for automatic enhancement and segmentation of microcalcifications in mammographic images. These techniques consists of three different stages which includes preprocessing stage, feature extraction stage and classification stage. The paper represents the proposed system in which these stages can be implemented using histogram equalization, contrast stretching and image segmentation.

Keywords: Mammography, Microcalcifications, Preprocessing, Feature Extraction, Classification, Histogram Equalization, Contrast Stretching, Backpropagation Neural Network and Image Segmentation.

Abstract: The World wide web is the largest collection of statistics in these days and it maintains increasing each day. An web crawler is a program from the huge downloading of web pages from global huge web and this manner is known as web crawling. To gather the web pages from www a search engine makes use of web crawler and the web crawler collects this by using web crawling. Because of barriers of community bandwidth, time-eating and hardware's a web crawler can't down load all the pages, it's miles important to pick out the maximum important ones as early as possible throughout the crawling manner and avoid downloading and touring many beside the point pages. We used web page rank algorithm for powerful searching over internet. This paper opinions help the researches on web crawling techniques used for looking.

Keywords: Crawler, Database, Search Engine, World Wide Web.

Abstract: The Internet-based recruiting platforms become a primary recruitment channel in most companies. While such platforms decrease the recruitment time and advertisement cost, they suffer from an inappropriateness of traditional information retrieval techniques like the Boolean search methods. Consequently, a vast amount of candidates missed the opportunity of recruiting. The recommender system technology aims to help users in finding items that match their personnel interests; it has a successful usage in e-commerce applications to deal with problems related to information overload efficiently. In order to improve the e-recruiting functionality, many recommender system approaches have been proposed. This article will present a survey of e-recruiting process and existing recommendation approaches for building personalized recommender systems for candidates/job matching.

Keywords: Open Source Software; Mining Software Repositories; Developer Expertise; Visualization Tool.

Abstract: Wellbeing Monitoring is more than once specified as one of the fundamental application regions for Artificial Intelligence. Versatile HealthCare is the reconciliation of portable registering and Health Monitoring. It is the utilization of versatile figuring innovations for enhancing correspondence among patients, doctors, attendants, assistant and other medicinal services specialists. As cell phones have turned into an inspirable piece of our life can incorporate medicinal services more flawlessly to our regular day to day existence. It empowers the conveyance of exact restorative data at whatever time anyplace by method for cell phones. The utilization of Electronic Medical Record (EMR) frameworks can resolve some of the long standing therapeutic wasteful aspects regular in creating nations. This paper exhibits the plan and usage of a proposed outpatient administration framework that empowers effective administration of a patient medicinal detail. We exhibit a framework to make meetings with medicinal professionals by incorporating a proposed Android based versatile application with a chosen open source EMR framework. The possibility of this venture is to give an association with a setup that will be useful to that particular association as well as the patient connected with the association also. The patient will have an application particularly intended for them which will push them to contact with a specialist, collaborate with him.

Keywords: Electronic Medical Record, Mobile HealthCare, Mobile Communication.

Abstract: On line social networks (osns) have lately emerged united of the most effective channels for info sharing and discovery due to their potential of permitting users to scan and build new content on the equal time. Whereas this advantage affords customers additional rooms to pick that content material to comply with, it conjointly makes osns fertile grounds for the huge spread of data which may also result in undesirable outcomes. in an effort to make certain the trustiness of content sharing in osns, it is so vital to possess a strategic research at the primary and fundamental problem: the assets of statistics. the usage of thoughts in psychology toguage the unfold of information, incorrect information and information in on-line social networks. Analysing on line social networks to spot metrics to deduce cues of deception can trade the USA to stay diffusion of records. the cognition worried inside the name to unfold information involves respondent 4 major queries viz consistency of message, coherency of message consider capacity of supply and widespread acceptableness of message. we have used the cues of deception to analyse those questions to collect answers for stopping the unfold of records. we've got projected an rule to successfully discover deliberate unfold of fake information which might exchange users to create enlightened choices whereas spreading data in social networks. the computationally within your budget rule makes use of the cooperative filtering property of social networks to live the believability of resources of records.

Keywords: Cognitive psychology, Decryption, Disinformation, Encryption, Misinformation, Online Social Network, spam message.

Abstract: Every organization, whether big or small,has human resource challenges to overcome. Every organization has differentemployee management needs, therefore we design exclusive employee management systems that are adapted to your managerial requirements. This is designedto assist in strategic planning, and will help you ensure that your organization isequipped with the right level of human resources for your future goals.Also, for those busy executive who are always on the go, our systems come withremote access features, which will allow you to manage your workforce anytime,at all times. These systems will ultimately allow you to better manage resources.One of the main features in employee management system is time tracking foremployees. Effective time tracking mechanism saves both time and money for the organization.

Keywords: Information system, Database system, DBMS, employee table, table fields, primary key, foreign key, relationship, sql queries, controls.

Abstract: Text summarisation is largely summarizing the source text into a simplified short version maintaining its actual information content and also the abstract that means. Attributable to apace growing use of internet, the globe is additionally facing drawback to tackle with dangerous quantity of data often facet by facet in kind of text .The bountiful offer of data generally cause time delay within the search of information recovery. In this relative concern automatic text summarisation has a crucial issue concerning data recovery of time. Manually summarizing giant document of text is incredibly troublesome task for individual. For this, extractive summarizing tool supported verified algorithm is required. Therefore supported the analysis of already planned model of extractive text summarisation, We are developing extractive text summarization tool based on genetic algorithm named AETS.. This approach are valid victimization normal information sets and quality measures.

Keywords: Feature extraction, Text summarization, Part of speech, Automatic text, Semantic nets.

Abstract: MapReduce is a framework using which we can write applications to process huge amounts of data, inparallel, on large clusters of commodity hardware in a reliable manner. MapReduce is a model for the data-intensivecomputation. However, despite recent efforts towards designing efficient scheduler to perform MapReduce, the available solutions focuses on scheduling at the task-level offers suboptimal performance in executing jobs. This isbecause tasks can have highly varying resource requirements during their lifetime, which makes it difficult forschedulers to effectively utilize the available resources to reduce job execution time. PRISM-a fine grained phaseand resource aware scheduler was introduce which mainly focuses on designing task level scheduler. The phasebased resource aware scheduler offers high resource utilization and provides improvement in job running time.In my proposed system I have used the virtual memory to overcome the disadvantage of PRISM and using thepausing phase. In this the resource will able to use virtual resource. Instead of going into paused phase it is possibleto use resource virtually till the resource is available. This will surely help the job running significantly reducing the delay.

Keywords: Cloud computing, MapReduce, Hadoop, scheduling, resource allocation.

Abstract: In recent 12 month�s number of community enabled digital devices are gift at homes. With the quick growth of the net the proprietors were asking for remote controlling on in-home gadgets. This android based domestic automation device lets in a couple of users to govern the software the use of android utility or internet site. The system has 3 issue the ones are mobile device to manipulate the home appliances from any area , 2d is server positioned on the cloud which shops statistics associated with home equipment and user and 0.33 device is Wi-Fi router located at home which definitely controls home equipment by sending notification to micro controller.

Keywords: Wi-Fi device, cloud, android device, web server, GCM (Google Cloud Messenger).

Abstract: This paper represents a survey on NAND-type flash memory and FTL algorithms which are used to improve the performance of flash memory. Flash memory is widely used as data storage and various embedded devices nowadays. The most attractive feature of flash memory is that the stored data is non-volatile and can be updated erase/write operation. But, every block in flash memory has a limited write/erase cycle. In order to manage these problems, a software module called FTL (Flash Translation Layer) algorithm is used. Various FTL algorithms have been proposed. This paper surveys the characteristics of those algorithms and their features.

Keywords: Computer Architecture, Embedded system, FTL, NAND flash memory.

Abstract: Cloud service providers and cloud consumers are tightened together via cloud services that are managed under certain constraints and must be abided by cloud consumers. These rules and regulations are referred to as policies that govern the whole process of accessing, storing and sharing data over cloud. Many publications have dealt with various ranges of policies in cloud computing but there is no in-depth exploration of studies that brings a consolidation of factors and requirements involved in cloud policies. Changes and additions in of cloud policies may lead a better success to govern the system in better ways. In this paper, we aim to conduct a systematic review to address these contexts. From the review, we identified seven major classes of policies; they are investigated more than other minor policies. We also found some policies that are relevant to other policies that may carry new policies towards the betterment of cloud computing paradigm.

Keywords: cloud policy; policy classifications; systematic review; policy requirements.

Abstract: A database system must be able to respond to requests for information from the user�i.e. process queries. Obtaining the desired information from a database system in a predictable and reliable fashion is Query Processing. To extract these results in a timely manner is possible with the technique of Query Optimization. For effective query processing the data must not be much fragmented. In this paper we focussed on the poor performance of query when the date fragmentation percentage is more and we have analysed how the fragmentation can be reduced using rebuild and re-organize techniques. In the last section, we have taken a sample data for query processing before rebuild and after that to have a comparative analysis.

Keywords: Indexing, Fragmentation, rebuild, re-organize.

Abstract: In the field of medical image handling, location of brain tumor from Magnetic resonance image (MRI) examine has become to be an active amongst the most dynamic exploration. Detection of the tumor is the fundamental goal of the framework. In this paper, MRI brain image is utilized to tumor recognition process. This framework incorporates test the brain image process, image separating, segmentation, and morphological operation, tumor detection. In recent years many image processing procedures are widely used on medical images to detect tumors at an early and treatment stages. When the images are added with noise the difficulties are primarily associated with the detection of tumors. In such cases the intensity thresholding might fail to identify the tumors. Edges characterize boundaries are the fundamental importance in image processing. The image edge detection reduces the data by filtering and preserving the important structural attributes. So understanding the edge detection algorithms is essential. Here the morphology based region of interest segmentation combined with watershed transform of MRI tumor image is performed and comparative analysis in noisy environment such as Gaussian, salt and pepper, Poisson and speckle is performed. Here different edge detection filters such as average, Gaussian and laplacian, sobel and prewit, unsharp and log in presence of noise. The parameters such as Cross correlation, Peak signal to noise ratio, Mean absolute error for different operators are evaluated. The motivation behind the morphological operators is to separate the tumor part of the image. In this paper, the brain image is considered for examination and recognition. At first the region of interest is found, that recognizes the specific substance of the image and set the boundary of it. Morphological operations are utilized for edge identification. The four parameters, such as Probabilistic Rand Index (PRI), Variation of Information (VOI), Global Consistency Error (GCE), Structural similarity (SSIM) have been utilized to evaluate the performance of segmentation.

Keywords: Magnetic Resonance Image (MRI), Segmentation, Noise, Morphological Operation, Watershed Segmentation, Brain Tumor.

Abstract: Nowadays, the demand of using renewable energy sources increases due to the rising of energy requirement for everyday life. Among renewable energy sources trends, power generation with PV Systems is one of the most demanding. These solar systems provide clean and sustainable energy. In terms of PV systems, grid-connected systems are more advantageous and useful. In that type PV System, the required energy, firstly, is supplied from battery and secondly, from electric grid in case of lack of solar energy to meet. In the article, it is done the optimum sizing with Pv Sol demo software in order to deal with the energy requirement for houses and cars of average family under climate conditions of the city of Istanbul. The designed system is connected to grid and it is just for meeting the energy need of average family�s house and electric car. The PV generator produces 2996 kWh energy annually. The energy requirement for electric car is 3009 kWh. The system works in performance of 81.6 percent annually.

Keywords: Renewable Energy, Solar Energy, Tesla, optimal PV system.

Abstract: In this study, the design of the distance examination system for professional qualification measurement of the Vocational Qualifications Authority, the question bank of this examination system and the methods of forming the questions are given. Possible contributions are being investigated for solutions to problems such as the formation of quality questions, the establishment of question banks, and the creation of examinations consistent with the norms that will be tested during the exams and the creation of exams from the right questions,if the applicant has already entered the examination, the fact that the previous exam questions are not used for the same applicant invocational qualification measurement exams.

Keywords: Vocational Qualification Examination Model, Distance online exam, Consistent Question Bank, Vocational Qualification.

Abstract: A brief summary of Daily meteorology s employed for multiple reasons in many areas like agriculture, transportations, etc. Accuracy of weather shown in forecast reports is very necessary. During this paper, the review is conducted to analyze a higher approach for prediction that is used for various sorts of prediction. Among which Time series with the ARIMA MODEL performs prediction with stripped-down error. For seasonal statistic prediction, Box and Jenkins [5] had projected a comparatively successful variation of ARIMA model, viz. the seasonal ARIMA (SARIMA) .The popularity of the ARIMA model is especially as a result of its flexibility to represent many sorts of statistic with simplicity still because the related Box-Jenkins[5] methodology for optimum model building ARIMA MODEL that is self-adaptive in nature which propose higher efficiency and reliability. It studied by itself in the training data and generates a lot of relative techniques that are helpful for forecasting the weather. This paper reviews varied techniques and focuses mainly on ARIMA MODEL technique for daily meteorology. The technique uses different parameters to forecast the daily weather in terms of rainfall, humidity, temperature, cloud condition, and weather of the day. The prime contribution of this paper is to compare the present meteorology model and to select the precise model to support their predictive ability.

Keywords: Weather forecasting, Time Series, ARIMA (Auto Regressive Integrated Moving Average), Correlation.

Abstract: Due to extensive growth of internet, security of the internet is area of interest for the researchers. An efficient biometric trait these days are sclera blood vessels. Sclera is a white region in the eye, around the eyeball which contains blood vessel patterns that can be used for personal identification. In this paper we present the existing sclera segmentation methods and their working in with their limitations and ideas to enhance them.

Keywords: Sclera, Segmentation, Iris, Feature extraction, Classificiation.

Abstract: The objective of this project is to design the drawing bot using �Fire Bird V ATMEGA2560� microcontroller. Drawing robot is the robot that will draw with a regular marking pen on a piece of paper. The project focuses on drawing a geometric shape. Drawing robot is a application which creates the drawing using firebird V through MatLab. Execution in MatLab yields the result in binary matrix .To move the robot, the program is executed in the AVR studio and result is obtained as Hex file. The Hex file is burn to the robot through USB cable for the movement of robot to draw an image .This project helps us to perform task faster with more accuracy.

Keywords: Binary matrix, Geometric shape, Fire Bird V, Mat Lab, AVR studio.

Abstract: Speech is an ancient field of study and research is being done on it till date. Automatic Speech recognition system deals with analysis and recognition of the input speech signal by the machine or computer in various environments. To enhance the accuracy and capability of the system various feature extraction techniques are implemented. This research paper provides a brief overview of Speech recognition system and its various phases like analysis, feature extraction, modeling and testing or matching. In addition it also includes detailed and comparative study on Linear Predictive Coding (LPC) feature extraction techniques used in Automatic Speech Recognition systems. The main objective of this paper is to briefly summarize speech recognition system and three feature extraction methods that are an integral part of ASR.

Keywords: Automatic Speech Recognition system, Feature Extraction.

Abstract: Autonomous robots are those which move freely without explicit human control. Path planning is done for such robots in order to reach the destination in the shortest possible time. Path planning also helps in obstacle avoidance. Here we are using fuzzy logic algorithm, which is widely used in artificial intelligence to make human like decisions. Fuzzy logic gives an output in the form of degrees of truth rather than just true or false. In this paper we are taking an image and converting it into a bmp file. Image consists of different obstacles which is in black colour and the white colour represents the path. A line joining the source and destination will give us the shortest path. Two different pixel values are set as source and destination. Six inputs such as the distance from the obstacle in front, distance at the front left diagonal, distance at front right diagonal, angle between the heading direction of robot and the goal, distance of the robot from the goal and preferred turn are chosen. The fuzzy system provides single output that will be the motion of the robot towards the destination. We make use of MATLAB software for the execution.

Keywords: Path planning, fuzzy logic, artificial intelligence, image map.

Abstract: Detection of objects in cluttered scenes is a fundamental challenge that has only recently been widely undertaken by computer vision systems. This paper proposes a novel method how to detect a particular object in cluttered scenes, given a reference image of the object. This paper presents an algorithm for detecting a specific object based on finding point correspondences between the reference and the target image. It can detect objects despite a scale change or in-plane rotation. It is also robust to small amount of out-of-plane rotation and conclusion.

Keywords: Point Feature Matching, Detection of Features, Cluttered Scenes, Computer Vision Systems.

Abstract: This paper focuses on marker based watershed segmentation algorithms. As marker based watershed segmentation algorithm causes over segmentation and cause noise in the image produced. So to reduce these problem different researchers has proposed different solutions, but the best solution is to use bilateral filter. The main objective of this paper is to find the gaps in existing literature. The different segmentation techniques are reviewed and found that marker based is best in most of cases because it marks the regions then segment them. But optimizing the marking regions is still an area of research.

Keywords: External markers, Gradient, Internal markers, Image segmentation, Watershed.

Abstract: Detecting fire and extinguishing is a hazardous job for a fire extinguisher, it often risks the life of that person. This project aims in giving a technical solution to the mentioned problem. A robot is a mechanical design that is capable of carrying out a complex series of actions automatically, especially one programmable by a computer. A fire extinguisher robot is a DTMF tone controlled robot that has a small fire extinguisher unit added on to it. This mobile robot is controlled using a mobile phone through DTMF tones for its movement and reaching the fire, the flame sensor detects the fire and gives the further signal to the extinguisher units to trigger the pump and spray the water. The whole system is programmed using an arduino UNO board (ATmega328P microcontroller) which forms the brain of the system.

Keywords: DTMF technology, DC motors, flame sensor, water pump, arduino.

Abstract: People detection and tracking is one of the important research fields that have gained a lot of attention in the last few years. Although person detection and counting systems are commercially available today, there is a need for further research to address the challenges of real world scenarios. There is lot of surveillance cameras installed around us but there are no means to monitor all of them continuously. It is necessary to develop a computer vision based technologies that automatically process those images in order to detect problematic situations or unusual behavior. Automated video surveillance system addresses real-time observation of people within a busy environment leading to the description of their actions and interactions. It requires detection and tracking of people to ensure security, safety and site management. Object detection is one of the fundamental steps in automated video surveillance. Object detection from the video sequence is mainly performed by background subtraction technique. It is widely used approach for detecting moving objects from static cameras. As the name suggests, background subtraction is the process of separating out the foreground objects from the background in a sequence of video frames. The main aim of the surveillance system here is, to detect and track an object in motion by using single camera. Camera is fixed at the required place background subtraction algorithm is used for segmenting moving object in video. If human entity is detected the tracking lines are formed around human and the object is tracked. The system when realizes the human entry, it is processed in a second and the alert is produced for the security purpose. The main aim is to develop a real-time security system.

Keywords: Video surveillance system, Moving object detection, Tracking, Background subtraction, Producing alarm.

Abstract: The Singular Value Decomposition expresses image data in terms of number of Eigen vectors depending upon the dimension of an image. The psycho visual redundancies in an image are used for compression. Thus an image can be compressed without affecting the image quality. This paper presents one such image compression technique called as SVD. Basic mathematics of SVD is dealt with in detail and results of applying SVD on an image are also discussed. The MSE and compression ratio are used as thresholding, parameters for reconstruction. SVD is applied on variety of images for experimentation. The work is concentrated to reduce the number of eigen values required to reconstruct an image.

Keywords: SVD, Image Compression techniques, Image Processing.

Abstract: Different types of denoising methods are existed in databases. But every method has its own uniqueness. We propose a new method that is adaptive patch based system for image denoising. The approach depends on a pointwise selection of narrow image patches of precise size in the variable neighborhood of each pixel. Our contribution is to engage in each pixel the weighted sum of data points not outside an adaptive neighborhood, in a sense that it balances the efficiency of estimation and the stochastic error, at each contiguous position. In this paper introducing spatial adaptivity, we prolong the work that can be designed as a development of bilateral filtering to image patches. This method is tested by using AWGN and images are taken from databases with different resolutions. The performance of the denoising system is computed in terms of PSNR by taking different noise levels.

Keywords: Image denoising; bilateral filtering; mean-squared-error (MSE) estimator; PSNR; Patch based method.

Abstract: 5G technology is a revolutionary technology in the field of wireless telecommunications implementing the latest networking architecture which provides high quality services. In this paper, an attempt is made to review the existing generations of mobile wireless technology, their evolution and compare them in terms of their features and performances. Efforts are made to shed light on the architecture proposed by far for the implementation of a 5G network. The term 5G is used alternatingly with World Wide Wireless Web (WWWW), which as a platform enables us to connect to any kind of devices, anytime, anywhere.

Keywords: 5G, 5G architecture, Evolution of 5G, 5G design.

Abstract: The recent multiple access technique, known as interleave division multiple access with turbo encoder, is applied in wireless communication, as well as wired (optical) system to upgrade the performance of the system. The simulation has been done using MATLAB Simulink. The simulated results conforms that turbo encoder can be used to enhance the performance of OIDMA based wired (optical) system.

Keywords: ODMA scheme, Turbo encoder, BPSK modulation, Matrix interleavers, Turbo Decoder, Led, Photo diod.

Abstract: Today Information Technology has gained momentum in our day today life. Information Technology means use of computers and internet to store and manipulate the information. So all the organizations, industries and also every individual are using computers to store and share or communicate the information. So here security is much important while storing and communicating the information over internet or through computer and its devices to avoid unauthorized access. For this security various techniques are available. Among them the most common and easy to use is a password. For security purpose every application provides user authentication. From ancient days, secret data or code is used for hiding and this gives security to information. Most traditional approach is in which we have to pass through username and password. Authentication process is divided into Token based authentication Biometric based authentication and Knowledge based authentication. Many web applications provide Knowledge based authentication which includes alphanumeric password and graphical password as well. In today's changing world when we are having number of networks and personal account some sort of easy authentication schema needs to be provided.

Keywords: Password, Graphical password, alphanumeric password, security primitive.

Abstract: The severity of attacks to Textual and Graphical Passwords has become a major threat to security nowadays. The vulnerabilities of this method which may be eves dropping, dictionary attack, social engineering, shoulder surfing etc. are the most difficult problem to defend against internet security. The goal of this paper is to understand various techniques used for authentication in the field of security. It would be necessary to come up with the better solution to solve the stated problem using the combination of existing techniques.

Keywords: Textual Password, Graphical Passwords, attacks, security, vulnerabilities, authentication.

Abstract: A lot of research has been done on city traffic routing mechanisms and congestion analysis using traffic sensors and CCTV cameras in spatio-temporal mining. Developing countries like India face periods of intensive rain for three-four months a year which has a drastic impact on road traffic. In this paper we have worked on creating a model for mining periodic patterns in traffic, which incorporates the fluctuations that occur due to monsoon in three-four months of the year, thereby depicting a holistic picture of traffic analysis in major cities of developing countries. The crucial aspect in Spatio-Temporal Data Mining is investigating temporal and spatial relations simultaneously as individual dimensions. For this reason it is important to choose a clustering algorithm which gives the most optimum performance for multi-dimensional datasets.

Keywords: Periodic patterns, Traffic Analysis, Spatio-temporal data, DB-Scan, Probability Distribution Matrices.

Abstract: Today security is a main issue for protecting private information.Various context-aware applications provide personalized services which collect user�s contexts through sensor-equipped devices to users. Because of shortage of a secure framework in networks has moved them to appropriate goals for different risks. As privacy is susceptible nature of real-time locality context of to users, many locality sharing applications use their strategies for gathering of private context. Adversary can misuse user�s context so there are various privacy preserving techniques which are used to protect user�s context. If the present location related data isprivatethen user�s current location information kept secret. Privacy preserving approaches for location based data are used to hide user�s location related information from adversary.

Keywords: Privacy, Security, Protection, Sensitive context.

Abstract: Data sharing is a very important practicality in cloud storage. This paper generally tend to expose the way to firmly, expeditiously, and flexibly proportion understanding with others in cloud garage. This paper have a tendency to describe new public-key cryptosystems that manufacture steady-length ciphertexts exact reasonably priced delegation of cryptography rights for any set of ciphertexts are workable. The newness is that one will mixture any set of mystery keys and construct them as compact as one key, however encompassing the ability of all the keys being aggregate. In opportunity words, the important thing holder will unharness a constant-length aggregate key for flexible alternatives of ciphertext set in cloud garage, but the contrary encrypted files out of doors the set stay confidential. This compact combination key can be handily sent to others or be preserve on terribly revolving credit with very limited comfy storage. This system offer formal security analysis of schemes inside the common place version. This machine have a tendency to moreover describe opportunity software of this schemes. Mainly, this schemes offer the number one public-key patient managed cryptography for versatile hierarchy,that was although to be legendary.

Keywords: Public key encryption, master key, ABE scheme, cloud computing, web based services, data sharing.

Abstract: Absence of space accessibility has dependably been an issue in urban territories and significant urban communities and to add to it there are autos stopped unfeelingly in the city that further point of confinement the space Car stopping is real sympathy toward metro urban areas. Uniquely, enormous urban areas require administration of space for auto stopping. Stopping of auto is exorbitant process. It expends time and cash of individuals. Keeping in mind the end goal to handle the issue of stopping in occupied spots different sorts of vehicle stopping frameworks are utilized overall to be specific Multi-level Automated Car Parking. The present venture work is meant to build up a diminished working model of an auto stopping framework for stopping. This paper audits diverse Intelligent Parking Services utilized for stopping direction, stopping office administration and gives an understanding into the financial investigation of such undertakings.

Keywords: Dynamic pricing, dynamic resource allocation,mixed integer linear programming (MILP), reservation, smart carparking.

Abstract: The increasing use of internet leads to handle lots of data by internet service providers. MapReduce is one of the goodsolutions for implementing large scale distributed data application. AMapReduce workload generally contains a set of jobs, each of which consists of multiple map tasks followed by multiple reducetasks. Due to 1) that map tasks can only run in map slots and reduce tasks can only run in reduce slots, and 2) the general executionconstraints that map tasks are executed before reduce tasks, different job execution orders and map/reduce slot configurations for aMapReduce workload have significantly different performance and system utilization. Makespanand total completion timeare two key performancemetrics T his paper proposes two algorithm for these two key. Our first class of algorithms focuses onthe job ordering optimization for a MapReduce workload under a given map/reduce slot configuration. Our second class ofalgorithms considers the scenario that we can perform optimization for map/reduce slot configuration for a MapReduce workload.

Keywords: MapReduce, Hadoop, Flow-shops, Scheduling algorithm, Job ordering.

Abstract: The new technologies characterizing the internet of Things permit realizing real sensible environments ready to offer advanced services to the users. Recently, these sensible environments also are being exploited to renovate the users� interest on the cultural heritage, by guaranteeing real interactive cultural experiences. During this paper, we have a tendency to style and validate an inside location-aware design ready to enhance the user expertise during adiposity. Above all, the projected system depends on a wearable device that mixes image recognition and Localization capabilities to mechanically offer the users with cultural contents associated with the determined artworks. The localization data is obtained by a Bluetooth infrastructure put in within the Museum. Moreover, the system interacts with the Cloud to store multimedia system contents created by the user and to share environment-generated events on his/her social networks.

Keywords: Bluetooth, Image recognition, IoT, Tracking system, Location-awareness, SoA, Smart Museum.

Abstract: With the emerging technological innovations, users are looking for automotive system than the manually operated system. As the number of vehicle users increased, the number of accidents and thefts are increasing. Due to a convergence of multiple technologies usage of Internet evolved in the field of networking, which helps objects to be sensed and controlled remotely. Pi based Embedded System for Vehicle Monitoring, tracking and controlling over internet uses mobile or computer device to monitor, track, and control the vehicle. This project is also aimed to monitor the driver activity through the internet from anywhere around the world by the owner of the vehicle. The owner can monitor the different sensors in the vehicle and can also keep track of the vehicle using GPS in the system and can store these datas in the cloud. In case anything goes wrong in the system the owner can get the update and will be able to stop the vehicle by sending a command. This command turns of the motor. until an authentication command is sent by the owner the vehicle cannot restart. The entire activities of the sensors are controlled by the Raspberry Pi which acts as a master controller and Arduino acts as a slave controller.

Keywords: Vehicle Controlling, Monitoring and Tracking, Gmail as Cloud storage.

Abstract: Email has becomes the major source of communication these days. Majority of people are using this mode of communication for their personal or professional use. Email is an effective, faster, secure and cheaper way of communication. The importance and usage for the email is growing day by day. It provides a way to easily transfer information globally with the help of internet. Because of extensive use of emails, spamming is growing day by day. According to the investigation, it is reported that a user receives more spam or irrelevant mails than ham or relevant mails. Spam is an unwanted, junk, unsolicited bulk message which is used to spreading virus, Trojans, malicious code, advertisement or to gain profit on negligible cost. Spam is a major problem that attacks the existence of electronic mails. So, it is very important to distinguish ham emails from spam emails, many methods have been proposed for classification of email as spam or ham emails. Spam filters are the programs which detect unwanted, unsolicited, junk emails such as spam emails, and prevent them to getting to the users inbox. Machine learning techniques, such as Na�ve Bayes, Support Vector Machine, Bagging and decision tree etc. In this paper we introduce a new Hybrid Technique with bagging to enhance the accuracy and performance of classification of emails into spam and ham.

Keywords: Ham, Spam, Email Spamming, Spam Filter, Email Spam.

Abstract: This paper presents a design of measuring system with Metamaterial inspired CSRR (Complimentary Split-Ring Resonator). The device is of portable, cost effective and which gives the accuracy. The theoretical approach of Metamaterial with its different applications is also discussed here. This paper is of high significance as current testing equipment of micro Complimentary Split-Ring Resonators (CSRR) are highly expensive, and therefore rare, but are also extremely bulky. Therefore developing portable, cost-effective, and robust testing equipment operating within the internationally reserved ISM radio frequency band is a main research work.

Keywords: Complimentary Split-Ring Resonators (CSRR), Metamaterial, Sensor, Permeability.

Abstract: In this era, Cloud Computing is gaining more importance. Cloud computing provides different services on demand. Due to this more and more data owners are interested to store data on cloud. Cloud computing is a model for on-demand access to a shared pool of configurable computing resources. However, for storing sensitive information, Encryption should be done. So encryption is performed before outsourcing the sensitive data. The data present in the cloud is in encrypted format so searching for appropriate documents is difficult. In this paper, we present Multi-keyword ranked search scheme over encrypted cloud data. Vector space model and TF X IDF model is used for index construction and query generation. Tree based index structure is constructed and �Greedy Depth-first search� algorithm is used for efficient search results. The Secure kNN is used to encrypt index and query vector.

Keywords: Cloud Computing, Cryptography, Multi-keyword ranked search, Searchable encryption.

Abstract: From few recent years online social network have amazing advance and become a factual gateway for many billions of Internet users. the shortage of multi-party privacy handling gives in existing mechanism of Social Media framework that makes users incapable to manage to whom information share or to whom not. Single policy that merges the privacy preferences of multiple users will facilitate to solve the problem of these kinds. To merge multiple users personal privacy preferences that aren't easy task these security preferences might clashes. These approaches have to get clearly how end users would really agree, in order to provide agreeable solution to the conflict. Preferences of just one party risks need to fixed ways in which privacy preferences. To encourage different users� concessions and agreements, the primary process mechanism that adapts to completely different scenario which is used for the resolution of conflicts for multi-party privacy management in Social Media in order to determine what number of times every approach matched users� behaviour.

Keywords: Online Social network (OSNs), conflict, multiparty access control (MAC), security model, Conflict resolution.

Abstract: Cardiovascular diseases have become the main cause of death in most of the countries of the world. The considerable growing of cardiovascular disease and its effects and complications as well as the high costs of treatment makes medical community seek for solutions to prevention, early identification and effective treatment with lower costs. Thus, valuable knowledge can be established by using artificial intelligence, the discovered knowledge makes improve the quality of service. Heart disease is a term assigned to a large number of medical conditions related to heart. These medical conditions describe the abnormal health conditions that directly influence the heart and all its parts. Heart disease is a major health problem in today�s time. Technically, the ANFIS performs a vital role for prediction of diseases in medical industry. Diagnosis of heart disease by using machine learning methods is one of the challenges in the health field .This project will be provided on a particular dataset using classification and feature selection approach. In this we will use feature ranking on effective factors of disease related to Cleveland clinic database and by using ANFIS, 13 effective factors reduced in terms of cost and accuracy.

Keywords: heart disease diagnosis, ANFIS, classification, feature selection.

Abstract: Call Detail Record (CDR) is a very valuable source of information in telecom industry; it opens new opportunities and option for telecom industry and maximize its revenues as well as it helps the community to raise its standard of living in different ways. However, I need to analyse Call Detail Record in order to extract its big value which helps to find new business opportunities. Real time streaming data processing is became new trends in Call Detail Record processing. It helps to analyse Call Detail Record in real time and helps in finding real time location of any customer and also behaviour of network in real time. But these Call Detail Records has a huge volume, variety of data and different data rate, while current telecom systems are designed without considering these issues in mind. Call Detail Records can be seen as Big Data source, and hence, it is applicable to use Big Data technologies (for storage, processing and analysis) such as Hadoop in Call Detail Record analytics. There are considerable research efforts to address the Call Detail Records analysis challenges face in telecom industry. This project presents the use of Big Data technology in Call Detail Records analysis by giving some Call Detail Record analytics based application examples, highlighting their architecture, the utilized Big Data and Data Mining tools and techniques, and the Call Detail Record use case scenarios. In this project I am processing Call details record and calculating traffic in Erlang and using this I am creating cluster of base stations and checking its performance for different new pricing and bundling can be seen and management decision can be made.

Keywords: Convergent billing, K-means clustering algorithm, machine learning, normalisation, bundling, Hadoop.

Abstract: NowadaysLocation Based Advertisement (LBA) has become today�s world�s most personal and directmarketing channel that provides customer more relevant information, personalized message, targeted offer about products and allows marketers to reach a specific target customersby means of digit advertisement. Location-based advertising (LBA) is a new form of advertising that is use to integratemobile advertising with location based services (LBS) to provide location-specific advertisements using real time location of consumer�s devices. With the help of LBA, it is possible to target population at the right place and the right time. By taking benefit of consumer�s real world position, location based advertising delivers relevant ads for products and services required. The application helps the registered shop owners to introduce the shop with available products to a consumer who is in close proximity to make them take those final steps to enter his store and let the consumer know what is around him with map support. The main feature of this application is for helping people who are new to that area .So that they can shop easily in nearby area only. One more additional feature is that one can find person nearby his location whose contact number is saved in contact list.so user can also take help from his friend to find required place.

Keywords: Android, GPS-Location, Friend-Finder.

Abstract: A new method of Synthesis by Analysis for EMD multi-component signals of fast changing instantaneous attributes is introduced. It makes use of two recent developments for signal decomposition to obtain near mono-component signals whose instantaneous attributes can be used for synthesis. Furthermore, by extension and combination of both decomposition methods, the overall quality of the decomposition is shown to improve considerably summarize the use of Empirical mode decomposition (EMD) for denoising a speech signal. EMD, introduced by Huang et al in gives time-frequency representation of non-linear and non-stationary signals. It decomposes a signal into a sum of finite zero-mean, oscillating components called as intrinsic mode functions based on the local time characteristics of the signal. Main essence of the method is it�s adaptive and data driven nature.

Keywords: Empirical mode decomposition, IMF, Hilbert transform, Denoising technique.

Abstract: The information leak of sensitive data on systems has a serious threat to organization data security. Statistics show that the improper encryption on files and communications due to human errors is one of the leading causes of information loss. So there a need tools to identify the exposure of sensitive data by monitoring the content in storage and transmission. However, detecting the exposure of sensitive data information is challenging due to data transformation in the content. Transformations result in highly unpredictable leak patterns. In this paper, it is utilize sequence alignment techniques used for detecting complex data-leak patterns. This algorithm is designed for detecting long and inexact sensitive data patterns. This detection is paired with a comparable sampling algorithm, which allows one to compare the similarity of two separately sampled sequences. The system achieves good detection accuracy in recognizing transformed leaks. It implement a parallelized version of our algorithms in graphics processing unit to achieves high analysis data. In the case of collective privacy preservation, organizations have to cope with some interesting conflicts. For instance, when personal information undergoes analysis processes that produce new facts about users' shopping patterns, hobbies, or preferences, these facts could be used in recommender systems to predict or affect their future shopping patterns. In general, this scenario is beneficial to both users and organizations. However, when organizations share data in a collaborative project, the goal is not only to protect personally identifiable information but also sensitive knowledge represented by some strategic patterns.

Keywords: Information leak detection, content inspection, sampling, alignment, dynamic programming.

Abstract: In traditional information retrieval system searching operation is performed based on the keywords which result in large amount of data due to this, it becomes to difficult to find out essential data from this large data. In order to overcome this drawback of traditional information system the new web architecture known as semantic web was introduced. In this paper we described the ontology based semantic information retrieval and jena semantic web framework. In this system input query entered by the user is parsed by Standford parser after which we apply triplet extraction algorithm in order to retrieve the desired information.

Keywords: Ontology Based Information Retrieval system: Semantic Web, Jena API, SPARQL, Query Processing.

Abstract: We present our audio fingerprinting system that detects a transformed copy of an audio from a large collection of audios in a database. The audio fingerprints in this system encode the positions of salient regions of binary images derived from a spectrogram matrix. The similarity between two fingerprints is defined as the intersection of their elements (i.e. positions of the salient regions). The search algorithm labels each reference fingerprint in the database with the closest query frame and then counts the number of matching frames when the query is overlaid over the reference. The best match is based on this count. The salient regions fingerprints together with this nearest neighbor search give excellent copy detection results. However, for a large database, this search is time consuming. To reduce the search time, we accelerate this similarity search by using a graphics processing unit (GPU). To speed this search even further, we use a two-step search based on a clustering technique and a lookup table that reduces the number of comparisons between the query and the reference fingerprints. We also explore the trade off between the speed of search and the copy detection performance. The resulting system achieves excellent results on TRECVID 2009 and 2010 datasets and outperforms several state-of-the-art audio copy detection systems in detection performance, localization accuracy and run time.

Keywords: Audio fingerprint, content-based copy detection, fast search, parallel processing, GPU.

Abstract: The best reversible data hiding (RDH) technique is Prediction-error expansion (PEE), and existing PEE-based RDH techniques are primarily based on the modification of one- or two-dimensional prediction-error histogram (PEH). The one-dimensional PEH-based methods do not perform generally as good as those based on two dimensional PEH; in any case, since the PEH modification manner is fixed and independent of image content, their performance is still unsatisfactory. In this framework, new RDH strategy based on PEE for multiple histograms is proposed .In this framework, Unlike the past methods, consider a sequence of histograms and devise a new embedding mechanism based on multiple histograms modification (MHM). For every pixel, as indicated by its context, a complexity measurement is computed and the pixels with a given complexity are gathered together to generate a PEH. By varying the complexity to cover the whole image, a sequence of histograms can be generated. At that point, two expansion bins are selected in each generated histogram and data embedding is acknowledged based on MHM. The expansion bins are adaptively chosen, considering the image content such that the embedding distortion is minimized. The proposed MHM-based RDH strategy works well, with such chosen expansion bins.

Keywords: Reversible data hiding, multiple histograms modification, prediction-error expansion, prediction-error histogram, adaptive embedding.

Abstract: This paper involves in identifying how the team management is done in various Agile Methodologies. Management is a hugely important part of putting together and managing the software project teams. Agile approaches help teams respond to unpredictability through incremental, iterative work cadences and empirical feedback. Agile methodology provides opportunities to assess the direction of a project throughout the development lifecycle to a team. Agile Team Management has brought a revolution to the IT sector after its introduction by which companies are now able to maintain a healthy relationship with all its employees, thereby encouraging them to work efficiently with less stress and achieve desired goal within stipulated time.Many software projects are not successfully completed or cannot meet the user requirements due to lack of proper project management as organizations continue to diversify, the opportunities for workplace problems intensify. Often the underlying causes of these problems are the lack of open, owing communications or using the wrong organizational structure.

Keywords: Agile Methodology, Software Companies, Software Projects, Team Management.

Abstract: Sentiment Analysis (SA) and summarization has recently become the focus of many researchers, because analysis of online text is beneficial and demanded in many different applications. One such application is product-based sentiment summarization of multi-documents with the purpose of informing users about pros and cons of various products. This paper introduces a novel solution to target-oriented sentiment summarization and SA of short informal texts with a main focus on Twitter posts known as �tweets�. We compare different algorithms and methods for SA polarity detection and sentiment summarization. We show that our hybrid polarity detection system not only outperforms the unigram state-of-the-art baseline, but also could be an advantage over other methods when used as a part of a sentiment summarization system. Additionally, we illustrate that our SA and summarization system exhibits a high performance with various useful functionalities and features.Sentiment classi?cation aims to automatically predict sentiment polarity (e.g., positive or negative) of users publishing sentiment data (e.g., reviews, blogs). Although traditional classi?cation algorithms can be used to train sentiment classi?ers from manually labeled text data, the labeling work can be time-consuming and ex-pensive. Meanwhile, users often use some different words when they express sentiment in different domains. If we directly apply a classi?er trained in one domain to other domains, the performance will be very low due to the differences between these domains. In this work, we develop a general solution to sentiment classi?cation when we do not have any labels in a target domain but have some labeled data in a different domain, regarded as source domain.

Keywords: Sentiment analysis, label data, sentiment polarity, sentiment classification.

Abstract: Sentiment Analysis (SA) and summarization has recently become the focus of many researchers, because analysis of online text is beneficial and demanded in many different applications. One such application is product-based sentiment summarization of multi-documents with the purpose of informing users about pros and cons of various products. This paper introduces a novel solution to target-oriented sentiment summarization and SA of short informal texts with a main focus on Twitter posts known as �tweets�. We compare different algorithms and methods for SA polarity detection and sentiment summarization. We show that our hybrid polarity detection system not only outperforms the unigram state-of-the-art baseline, but also could be an advantage over other methods when used as a part of a sentiment summarization system. Additionally, we illustrate that our SA and summarization system exhibits a high performance with various useful functionalities and features. Sentiment classi?cation aims to automatically predict sentiment polarity (e.g., positive or negative) of users publishing sentiment data (e.g., reviews, blogs). Although traditional classi?cation algorithms can be used to train sentiment classi?ers from manually labeled text data, the labeling work can be time-consuming and ex-pensive. Meanwhile, users often use some different words when they express sentiment in different domains. If we directly apply a classi?er trained in one domain to other domains, the performance will be very low due to the differences between these domains. In this work, we develop a general solution to sentiment classi?cation when we do not have any labels in a target domain but have some labeled data in a different domain, regarded as source domain.

Keywords: Sentiment analysis, label data, sentiment polarity, sentiment classification.

Abstract: Tremendous popularity of the ecommerce applications increased now days. Numerous amounts of reviews and ratings are available on the sites. Such as comments, reviews description of the local service. This type of information is valuable for the new user who judges the product online to make their decision. Sometimes this information may be having problem to recommend user about product recommendation because of the lack of reviews and rating of particular product. If any product has two rating one 5 and other is 2 they only have two ratings. So while recommending this product just finds average of ratings and show to user. This not provides quality of service of the recommendation. This is not enough to extract public opinions. To provide quality of service to the recommendation have to improve overall evaluation of rating. Find the trust of the user service rating and feature. Extract the overall rating and trust of service by combining the service rating to providing quality of service.

Keywords: Data Mining, Recommendation system, Quality of Service Evaluation, Social Network.m.

Abstract: In recent year, Location based social network provide different user location features and recommendation. In location recommendation provide geographical influence and social influence with spatial item, and temporal data. A newly features stored user visit location. The user-item matrix is very sparse, which creates a big challenge for traditional collaborative filtering-based recommender systems. In Location based service has low sampling rate which existing prediction rate. In proposed system, we implement sequential personalized spatial item recommendation framework which provide user interest personal influence. We calculate the performance of SPORE on two datasets (Foursquare, Twitter) and one large-scale synthetic dataset. The results improvement SPORE ability to recommend spatial items, in terms of both efficiency and effectiveness, compared with the state-of-the-art methods.

Keywords: Location-based service, Location-based Social Network, Temporal data, spatial item.

Abstract: As in every where automation is required to reduce the work so we decided to implement to automatic meter reading using power line communication. AMR is the modern Power measuring device .It is being used in measuring electricity, gas, water consumption in many countries on the world since it has a lot of advantages that the old analogy meters doesn�t have. It has advantages in safety, real time measuring and time saving as well as it has a better user interface and digital data analysis .Data is send over existing carrier that reduces the complexity and cost of system.

Keywords: AMR, PLC, PLCC.

Abstract: Research in the field of medicine suggests that abnormal pressure and glucose levels are a major cause of several critical complaints. A retinal image provides a snapshot of what is happening inside the human body. In particular, the state of the retinal vessels has been shown to reflect the cardiovascular condition of the body. Retinal images provide considerable information on pathological changes caused by local ocular disease which reveals diabetes, hypertension, arteriosclerosis, cardiovascular disease and stroke. Computer-aided analysis of retinal image plays a central role in diagnostic procedures. However, automatic retinal segmentation is complicated by the fact that retinal images are often noisy, poorly contrasted, and the vessel widths can vary from very large to very small. In this paper, we place focus to implement automate segmentation approach based on graph theoretical method. The scope of this paper is to provide blood vessels regional information by the measure of median filter algorithm. We proposed a novel computational approach for the segmented vascular structure as a vessel segment graph and solve the problem to identify vessels as the one of the findings of blood vessels in the graph given a set of constraints such as CRAE and CRVE. These measurements are found to have good correlation with hypertension, coronary heart disease, and stroke. Moreover, these require the accurate extraction of distinct vessels from a retinal image and a classification method is used to reveals the optimization problem and evaluate it on a real-world dataset of retinal images.

Keywords: Automatic segmentation, Computational approach, Classification Data mining.

Abstract: The computing power, communication, information and knowledge radically changed the way we live, work, and think, due to the growth of high speed networks, coupled with the falling cost of computing power. This explosion of technology is changing the banking industry from paper banks to digitized and networked banking services. Digitalization has already changed the internal accounting Process and management of banks. It is now changing the delivery system, banks use to interact with their customers.All over the world, banks are still struggling to find a technological solution to meet the challenges of a rapidly-changing environment. Banks, with the ability to invest and integrate information technology, will become dominate in the highly competitive global market [1]. Service-oriented architecture (SOA) has become a well-known IT infrastructure for business and increases the efficiency of IT [2]. Business operations are exposed as services, the interaction occur in loosely coupled method that operate independently. SOA architecture allows for service reuse, making it unnecessary to start from scratch when upgrades and other modifications are needed. This is a benefit to businesses that seek ways to save time and money [3] [4]. This paper integrates SOA with banking application to reduce the transaction delay and improve the performance of the system [5].

Keywords: SOA, WSDL, HTTP Protocol, Transactions, Batch Processing.

Abstract: The routing protocols are playing very important job in the performance of both IP (Internet Protocol - Infrastructure based) and the mobile Ad-hoc networks (MANET). The Ad hoc On Demand Distance Vector (AODV) Routing Protocol is a reactive-table driven routing protocol for mobile ad hoc networks. The route discovery and maintenance process is based on the balanced energy level in the neighbouring pair of nodes. This research is a modification on the original AODV, a basic routing protocol for its enhancement. This is an attempt to use communication reliability factor prior to establish communication using energy levels. This is examined by simulation study experimented using NS-2 on Ubantu. The performance metrics used for comparison between AODV and new protocol are PDR, routing overhead, energy level and delay.

Keywords: MANET, AODV, Routing Protocols, RREQ and RREP messages.

Abstract: A considerable amount of attention and research has been devoted in recent years to the deployment of Distributed Sensor Networks (DSN) for use in data gathering, healthcare, collaborative information processing and environmental monitoring. This is the Survey paper for study of various Genetic Algorithms to be applied on Distributed Sensor Networks for better performance and results. However these networks are vulnerable to failure eventually due to many reasons. Hence the best suitable GA is to be applied. The main objective of proposed work is to organize such a network which consumes less energy and fault tolerant using Genetic Algorithms. Thus primary stage is to analyze requirements and preliminaries and accordingly plan for solving fault tolerance in Distributed Sensor Networks.

Keywords: DSN, Deployment, Sensor nodes, Genetic Algorithm, Population.

Abstract: The spread and availability of pen-based devices increased the research in free handwriting and hand sketched recognition. Most of systems in hand sketched diagram recognition are limited to a specific application or limited to specific shapes. Complex diagrams recognition requires not only understanding the primitive shapes but also determining relations between these shapes. This work presents a system for recognition of hand-sketched complex diagrams which create active and intelligent relations between different diagram components. A multi-layers framework is developed which consists of stroke layer, shape layer, and diagram layer. A distance function is used to measure the similarity between template shapes and user sketched shapes. In the diagram layer, many adjustments are applied to enhance the positions and sizes of shapes, increasing the harmony and regularity of shapes arrangement. This system has been tested using a set of primitive shapes and a set of complex diagram and high accuracy results have been obtained.

Keywords: Diagram recognition, free hand sketch, feature extraction, pattern recognition.

Abstract: Energy saving is a critical issue in Wireless Sensor Network as they have limited amount of energy. In WSN Sensor node closer to the sink will exhaust their limited energy more rapidly than other sensor nodes, since they will have to forward huge data during multi hop transmission to the base station. Therefore network lifetime will be reduced because of hotspot problem. To cope up with the network lifetime, in this paper, Novel Energy Efficient Unequal Clustering algorithm for clustered wireless sensor network is proposed, the decision of selecting cluster heads by the sink is based on the residual energy and distance to the base station, Besides, the cluster head also selects the shortest path to reach the sink. Simulation results show that our approach enhanced the performance than traditional routing algorithms, such as LEACH & EEUC.

Keywords: Residual energy, Unequal clustering, Routing, Network lifetime, Hot Spot problem.

Abstract: Data is an important asset for any individual or organization and must be protected from intruders or hackers. The need to hide data from hackers has existed since ancient times, and nowadays, there are developments in digital media, such as audio, video, images, and so on. To secure secret information, different media methods are used and steganography is one. Steganography hides the data under other data without any differentiable changes. Many individual steganography tools can be used to transfer data securely and, in this report, a new tool is proposed that decreases time and effort. Using this tool, we hide the text in images in one place, so there was no need to have access to multiple tools. This proposed tool developed using the least significant bit (LSB) approach. Steganography is a method of hiding secret messages in a cover object while communication takes place between sender and receiver. Security of confidential information has always been a major issue from the past times to the present time. It has always been the interested topic for researchers to develop secure techniques to send data without revealing it to anyone other than the receiver. There for from time to time researchers have developed many techniques to fulfil secure transfer of data and steganography is one of them. In this paper we have proposed a new technique of image steganography i.e. Hash-LSB with RSA algorithm for providing more security to data as well as our data hiding method. The proposed technique uses a hash function to generate a pattern for hiding data bits into LSB of RGB pixel values of the cover image. This technique makes sure that the message has been encrypted before hiding it into a cover image. If in any case the cipher text got revealed from the cover image, the intermediate person other than receiver can't access the message as it is in encrypted form.

Keywords: Cryptography, Steganography, LSB, Hash-LSB, RSA Encryption -Decryption.

Abstract: Recently, so many methods have been invented to determine issues with the choice of starting points in K-Means clustering algorithm. The Global K-Means and the Fast Global K-Means algorithms both are basis of such methods. They frequently insert one cluster centre at a time. The Weighted Fuzzy C-Means algorithm is as well extremely admired for fuzzy basis data clustering. However these all clustering methods are immensely influenced through the extreme environment of high dimensional data values. Every data in the dataset has compound characteristics and the cost of some characteristics might be so huge that the significance of additional characteristic costs might be entirely overlooked in the clustering procedure. The complexity of utilizing high dimensional datasets in clustering process is well known. To resolve these difficulties and to get better clustering algorithm for huge high dimensional datasets we proposed an algorithm �an enhanced global k-means (EGKM) algorithm for cluster analysis�. To calculate the performance of the both FGKM and EGKM algorithms we use six datasets: Letter, Car, Iris, Kddcup, Nursery, Ozone and Spambase. Our trial study shows that EGKM performs much better than FGKM for every high dimensional datasets.

Keywords: GKM, FGKM, K Means, Cluster Analysis.

Abstract: Web based education systems are very popular nowadays. Organizing and evaluating user�s course details along with their proficiency is very important for improving course systems. With an upgrading technology of E-Learning performs a best effect for the student based on the programming language. However, student modeling in many cases deals with uncertainty and it is a difficult process, because the personal skill and ability may vary time to time and person to person. It cannot be exactly said that a learner knows or does not know a particular concept. And also the domain concepts which were previously known by the learner may be completely or partially forgotten. Thus, at present they may be partly known or completely unknown. The teaching process itself changes the status of knowledge of a user. For this problem this paper presents the Weighted Fuzzy intelligence computing for analyzing and helping students about their learning Process and also provides an Adaptive Instruction through E-learning. To accomplish these, the paper introduces a WFIC_KLS (a Weighted Fuzzy Intelligent Computing in Knowledge Learning System), which predicts the relevant course and concepts based on individual proficiency on every concept and suggests best material to improve their skill. The proposed WFIC_KLS helps to find the appropriate tutorial and course link based on individual proficiency. This also effective to guide the learners based on their individual knowledge and interest. The system has successfully implemented using C#.net platform with a real e learning environment. The experiments and results show the impact of the proposed system in e learning guidance system improves the skill of individual users.

Keywords: E-learning system, Data Mining and Survey, Fuzzy Logic, Intelligent Tutoring System, Fuzzy student model, personalization, programming.

Abstract: Most of the existing authentication system has certain drawbacks for that reason graphical passwords are most preferable authentication system where users click on images to authenticate themselves. An important usability goal of an authentication system is to support users for selecting the better password. User creates memorable password which is easy to guess by an attacker and strong system assigned passwords are difficult to memorize. So researchers of modern days gone through different alternative methods and conclude that graphical passwords are most preferable authentication system. The proposed system combines the existing cued click point technique with the persuasive feature to influence user choice, encouraging user to select more random click point which is difficult to guess.

Keywords: Reauthentication, usable security, Behavioural biometrics, graphical passwords, Smartphone.

Abstract: Last few years digital watermarking has facilitated the protection of copyright information through embedding the hidden information into the digital content. Digital image watermarking is one such the technology that has been developed to protect digital images from illegal manipulations. In this paper a new SWT-SVD semi-blind composite images watermarking algorithm that is robust against various attacks is presented .We use SWT transform to obtain 4-diffirent frequency images. Then we apply SVD on each subsection to modifying their singular value, on the basis of MSE & PSNR values Experimental evaluation demonstrates that proposed algorithm is able to withstand variety of attacks as Salt & Pepper noise, Rotation, Median filter, Vertical Mirroring, Horizontal Mirroring, Gaussian noise, Cropping, Contrast etc. Watermark is recovered efficiently.

Keywords: Copyright protection, Blind watermarking, SWT (stationary wavelet transform), Singular value decomposition (SVD), MSE (mean square error), PSNR (peak signal to noise ratio).

Abstract: Security and Privacy are the major concerns in the current trends of cloud environment. Securing the data and applications from the intruders, Hackers and internal attackers has become a challenge. On the other hand Preserving the privacy of users is also became a challenging task. Most of the cloud based service providers are providing high level of security but privacy of user is done only once at the authentication level. Many of the applications such as Salesforce.com, Google, and Amazon etc are using two factor authentications (TOTP). In this paper we have proposed secure cloud authentication architecture to deal with privacy in cloud applications, by using periodic two factor authentication in cloud systems.

Keywords: TOTP, WTP, Two-factor Authentication, Cloud Security.

Abstract: Data Mining can be defined as an activity that extracts some new nontrivial information contained in large databases. Traditional data mining techniques have focused largely on detecting the statistical correlations between the items that are more frequent in the transaction databases. Also termed as frequent itemset mining, these techniques were based on the rationale that itemsets which appear more frequently must be of more importance to the user from the business perspective .In this thesis we throw light upon an emerging area called Utility Mining which not only considers the frequency of the itemsets but also considers the utility associated with the itemsets. The term utility refers to the importance or the usefulness of the appearance of the itemset in transactions quantified in terms like profit, sales or any other user preferences. In High Utility Itemset Mining the objective is to identify itemsets that have utility values above a given utility threshold. In existing system some high utility itemset mining algorithms such as Two-Phase, UP-Growth have been proposed. But there is problem like it requires more execution time and it uses more memory. The new method is memory efficient technique for mining high utility itemsets from transactional databases. This technique requires less memory space and execution time than existing algorithms.

Keywords: : Data Mining, Frequent Itemset, High Utility Itemset, Utility Mining

Abstract: Extreme programming is an agile methodology for software development that performs very well with changing requirements. XP is one of the most commonly used methods among other agile methods. However, it is implemented sequentially on all activities Moreover; classical XP suffers from an architectural design. Therefore, there is a need for a framework that integrates the strengths of component based architecture refinement reusability into the Extreme Programming Methodology. Which gives a clear vision about a current architectural design requirement without any additional features that are not yet needed? And constantly redesigning through refinement and refactoring concept. The design is simple and loosely coupled as possible, thus making future modifications easier, and achieving the XP values i.e. simplicity and feedback. This will result in reusability of component architecture and to reduce the development effort, time and provide quality software.

Keywords: Refinement, Refactoring, Component, architecture reuse, Agile Software Development, Extreme Programming.

Abstract: As the use of mobile devices is expanding and affecting various aspects of human life, the number and smartphone users is dramatically increasing. Consequently, the robustness of interaction between smartphone and human is essential for better system performance. By using the speech synthesizer technology for the android, the application presents the modality of text-to-speech responses on android device. In user mobile device they provided Location Based Services for set of services which originate from the geographic location. Using these services it is possible for the users to finding and locate other area, vehicles, and resources and also to provide location- services, in addition to tracking their own location. The request for location can originate by mobile device. When the mobile device is at any particular location it is possible to automatically trigger Location Based Services. These services can also helpful in the user�s mobile device itself in order to satisfy location-based queries like finding areas of interest, checking traffic conditions, finding our friends, or vehicles, resources, machines and emergency requests. In this paper we will discuss how to implement these location based services in Android after giving introduction to Android and its constituents.

Keywords: Language learning, text �to- speech, speech synthesis.

Abstract: Nowadays the world needs databases to be able to store and process big data effectively and demand for very high-performance when reading and writing. These requirements effects especially in large scale and high concurrency applications such as search engines, hence the traditional database limits itself for such complex requirements. Therefore various types of non-relational databases that are commonly referred to as NoSQL databases which is abbreviation of �Not only Structured Query Language� was emerged. This paper presents a survey on NoSQL and its various data stores. NoSQL (Not Only SQL) is a database which is used to store large amount of data. NoSQL databases are distributed, non-relational, open-source and horizontally scalable. In this paper fundamental concepts like ACID, BASE and CAP theoremwill be described and present a comparison between ACID and BASE properties. Furthermore on the basis ofthe CAP theorem, various forms of data stores in NoSQL like Key/-Value data store, Column family data store, Document data store, Graph database and their characteristics are explained. In addition a taxonomy of NoSQL by various data stores and also the historical trend of popularity of themis presented. At the end, the reasons to consider a NoSQL solution for the Internet of Things data are depicted.

Keywords: NoSQL, ACID, BASE, CAP theorem, Data store, IoT.

Abstract: Internet of Things (IoT) has provided a promising opportunity to build powerful industrial systems and applications by leveraging the growing and wireless, mobile, and sensor devices. A wide range of industrial IoT applications have been developed and deployed in recent years. In an effort to understand the development of IoT in industries, key enabling technologies, major IoT applications in industries, and identifies research Trends and challenges.

Keywords: RFID, WSN, Sensors.

Abstract: Indian Railways is one of the largest railway passenger modes of transport in the world and is the backbone of the Indian transport infrastructure. However in terms of safety parameters and reliability we have not reached the global standards yet. The major rail accidents occur due to derailment of trains which are caused due to fault in the railway tracks. In this paper, we present to you a LASER pulse-EMAT crack detection system. The location and severity of the crack can be easily sent to the server or cloud storage, for necessary action. LASER pulse is incident on the track twice, after sometime on the same location for more precise monitoring of the tracks. This system can save many lives, by preventing major derailments of trains, in a country where rail accidents have become quite frequent.

Keywords: Safety Parameters, Reliability, LASER Pulse-EMAT Crack Detection System, Server, Cloud Storage, Ultrasonics.

Abstract: The neural network approach to generate efficient classification rules. Convolution neural network algorithm is a multilayer perceptron that is the special design for identification of two-dimensional data information. Always have more layers: input layer, convolution layer, sample layer and output layer. Deep learning refers to the shining branch of machine learning that is based on learning levels of representations. Convolutional Neural Networks (CNN) is one kind of deep neural network. To perform classification task of heart disease dataset, the neural network is trained using convolutions algorithm. The experiment is conducted with heart disease dataset by considering the single and multilayer neural network modes. The proposed algorithm gives detailed analysis of the process of CNN algorithm both the forward process and back propagation. Then we applied improved convolutional neural network to implement the typical heartdata recognition using weka tool. The experimental result show the best classification accuracy compare with existing classification algorithm.

Keywords: Data Mining, Classification, Convolutional Neural Networks, Heart dataset.

Abstract: The two noteworthy zones of worry in the testing of VLSI circuits are Test data volume and inordinate test control. Among the various pressure coding plans proposed till now, the CCSDS (Consultative Committee for Space Data Systems) lossless data pressure plan is one of the best. This paper talks about the procedures that test data pressure conspire in view of lossless data pressure Rice Algorithm as suggested by the CCSDS for the lessening of required test data add up to be put away on the analyzer, which will be exchanged amid assembling testing to every center in a system-on-a-chip (SOC). In the proposed plot, the test vectors for the SOC are compacted by utilizing Rice Algorithm, and by applying different parallel encoding methods. Exploratory results demonstrate that the test data pressure proportion for the bigger ISCAS 89 Benchmark Circuits is altogether enhanced in examination with existing techniques.

Keywords: VLSI Circuits, CCSDS, SOC, Adaptive Entropy Coder (AEC).

Abstract: Mining opinion targets and opinion words from online reviews of products (Custom portal) are important tasks for fine-grained opinion mining, the key component of which involves detecting opinion relations among words (target words). In this system user can add their reviews about the product and the system can extract the target words and opinion relation. By using the opinion and targets to find out the sentiment analysis about the reviews. Reviews contains the compound sentence then it will split it into the separate sentence and find the targets and opinion and also sentiment from reviews. The system is then reversing the Negative opinion sentences into Positive. The sentiment can be negative, positive, neutral, vary negative and very positive. Then all the sentiments, targets and the opinion about the product are represented using the graphical format. All comments will be stored in Hadoop and Analysis will be done on comments using Hadoop.

Keywords: Hadoop, Data Mining, Sentiment Analysis.

Abstract: This paper presents a new approach for face recognition of single face,multi faces, and twins faces, based on Convolutional Neural Network (CNN). Analyzing and exploring essential parameters that can influence model performances the approach has been used in this work to recognize face. Furthermore different elegant prior contemporary models are recruited to introduce new leveraging model. Also show how a very large scale dataset (3M images over 3K people) can be assembled. The proposed method has been compared to the most contemporary approaches and conducted on proposed method with LFW, and YTF datasets and it shows an excellent performance with higher accuracy.

Keywords: Deep Face Recognition, Multiscale images.

Abstract: In this study, the higher order vertical and complete lifts of the tensor fields, which are defined on the extended vector bundles has been obtained.

Keywords: The extended vector bundles, The vertical and complete lifts of the tensor fields.

Abstract: VANET is a promising communication technology that enables communication among V2V and V2I for improving driving safety and efficiency. In VANET, data transfer is done with the help of multi-hop communication in which vehicles act as data carrier. Intelligent Transportations System (ITS) has deployed a no of RSU (Road Side Units) along the roads to collect and deliver traffic information from TCC (Traffic Control Centre) to the vehicles. This paper compares six vehicle trajectory-based data forwarding schemes, tailored for vehicular ad hoc networks. Nowadays GPS-based navigation systems are used for providing efficient driving paths for drivers. Subsequently it also discusses the performance of those data forwarding schemes and list the merits and demerits and conclude the challenges facing in the present day research in Vehicular ad hoc Network (VANET).

Keywords: VANET, IVC, ITS, RSU, Vehicle trajectory, VADD, TBD, TSF, TOAF, STDFS, SDFM.

Abstract: In recent decade, ECG signal plays an important role in the prognosis, diagnosis and survival analysis of cardiac diseases. Electrocardiography (ECG) has profound influence on the practice of medicine. The electrocardiogram signal contains important information�s that can be exploited in various manners. The ECG signal allows the analysis of anatomic and physiologic aspects of the whole cardiac system. This research paper proposes an algorithm for analysis of ECG signals for detecting various cardiac diseases .Different ECG signals are used to test the proposed method using MATLAB software.

Keywords: ECG (Electrocardiogram), MATLAB, Cardiac Patients, Critical Diseases, Diagnosis.

Abstract: In these recent years, with the increase in the growth of digital communication, there has been a huge need for high speed data transmission. Likewise, there is a huge demand for the communication systems that support a wide range of services which include video, data and voice. OFDM (Orthogonal Frequency Division Multiplexing) is an efficient method of communication to achieve high speed data rates in mobile environment since it supports multicarrier modulation and has feature of converting frequency selective fading into flat fading channel. However OFDM has its sensitivity against carrier frequency offset which causes Inter Carrier Interference (ICI). In this paper we have tried to give an efficient ICI cancellation method termed as ICI self cancellation.

Keywords: OFDM, Interference, Inter Carrier Interference, Doppler shift, Frequency miss match.

Abstract: Normal language, whether spoken, written, or typed, makes up much of human communication. A colossal quantity of this language describes the visible world either straight around us or in snapshots and video. This paper reviews a system to mechanically generate ordinary language descriptions from the video and a procedure that generates natural language descriptions for video. The framework is divided into two sections known as training and testing part. The training part is used to train the video with its description like pursuits of objects in that video. The testing part is used to experiment the video and retrieve the output as description of video evaluating videos stored into database. Combining Natural-language processing (NLP) with computer vision to generate English descriptions of visual information is an important area of active research.

Keywords: Natural-language processing (NLP), computer vision, video evaluation, language descriptions, Video processing.

Abstract: Data Mining plays an important role in the field of healthcare, because disease diagnosis and analysis have huge size of data. These circumstances create huge number of data handling issues, and that to be handled effectively. The health dataset�s are uncertain and dynamic in nature and it is very tedious to maintain and to manipulate. To overcome the above issues, several studies introduced numerous Machine learning approaches for various disease diagnosis and prognosis. This paper a different data mining and machine learning techniques used in diabetes are analyzed and compared. The task of disease diagnosis and prognosis is a part of classification and prediction. The recent and popular data mining techniques used in clinical data includes Bayesian, Random forest algorithms, Artificial Neural network, SVM and Decision Tree etc. This paper gives the problems and findings about those techniques with various factors.

Keywords: Data Mining, Clinical data, Diabetes Mellitus, classification, Regression.

Abstract: Budget Pre-Owned Cars is built with a vision that there has to be a better way to buy and sell a pre-owned car, A memorable one every customer leaves with. This includes: 1. Better selection of high quality of cars. 2. Low prices and after sales services. 3. A stress free experience. 4. No-obligation deal of purchase or sale. 5. No-pressure customer service. And therefore we intend to make analytics for the following ideas: 1. Price prediction 2. Sales Prediction 3. Customer parameters 4. Payment support 5. Customer segmentation 6. Future services. Data analytics will help in separating useful information from the useless data. Also, it can save the company time and minimize error rates, hence improved accuracy and quality. These insights will hence further help in modifying the products according to the market needs. These predictions are based on the historical data; hence die rent techniques will be used including data mining for the same. The predictions are then evaluated and compared to and the one with best performance.

Keywords: Data mining, Data analytics, Prediction, Information filtering, commercial services.

Abstract: Ad hoc networks are characterized by a lack of infrastructure, and by a random and quickly changing network topology; thus the need for a robust dynamic routing protocol that can accommodate such an environment. To improve the packet delivery ratio of Destination-Sequenced Distance Vector (DSDV) routing protocol in mobile ad hoc networks with high mobility, a message exchange scheme for its invalid route reconstruction is being used. Three protocols AODV, DSDV and I-DSDV were simulated using NS-2 package and were compared in terms of packet delivery ratio, end to end delay and routing overhead in different environment; varying number of nodes, speed and pause time. Simulation results show that I-DSDV compared with DSDV, it reduces the number of dropped data packets with little increased overhead at higher rates of node mobility but still can�t compete with AODV in higher node speed and number of node.

Keywords: DSDV, link breakage, message scheme, ad hoc network.

Abstract: The main objective of our project is detecting the fault of fabric. In textile industry automatic fabric inspection is important to maintain the quality of fabric. In our project horizontal, Vertical and oil spot such defects are detected using neural network tool. These systems are introducing defect detection using histogram and Neural Network Tool for the inspection textured material. The system acquires fabric images by image acquisition device & converts that image into binary image by restoration and thresholding techniques. ARM 7 is used for processing all actions. This system is based on MATLAB 8.0.0.873.

Keywords: GSM, Histogram, Threshold, DWT.

Abstract: Spoken content retrieval refers to directly indexing and retrieving spoken content based on the audio rather than text descriptions. This potentially eliminates the requirement of producing text descriptions for multimedia content for indexing and retrieval purposes, and is able to precisely locate the exact time the desired information appears in the multimedia. Spoken content retrieval has been very successfully achieved with the basic approach of cascading automatic speech recognition with text information retrieval: after the spoken content is transcribed into text or lattice format, a text retrieval engine searches over the ASR output to find desired information. Latent Dirichlet allocation algorithm is used for clustering. It is a generative statistical model that allows sets of observations to be explained by unobserved groups that explain why some parts of the data are similar. Depends on automatic speech recognition output the algorithm will perform clustering on that content and return the expected result. After converting audio to text we apply LDA algorithm for clustering the input data.

Keywords: Spoken content retrieval, spoken term detection, query by example, semantic retrieval, joint optimization, pseudo-relevance feedback, graph-based random walk, unsupervised acoustic pattern discovery, query expansion, interactive retrieval, summarization, key term extraction.

Abstract: The distinctive ID system provides distinctive identification numbers to Indian residents. UID variety which might not simply help the govt. to trace down people, however would create life so much easier for voters as they'd not ought to submit multiple documents on every occasion they require to avail a brand new public, private and government service. This method can contain personal details like name, sex, address, legal status, photo, identification mark and fingerprint biometric. The unique identification number are within the fashioned of twelve digit alphanumeric variety to supply a lot of security. UID system helps to manage persons wants in his/her generation by employing a single UID is employed as license number, Voter ID card variety, identification number in any organization, bank account variety, personal or skilled details. This system can produce government jobs for pc sector within the development, implementation and maintenance of the UID system.

Keywords: Anonymity, attribute-based encryption, Digital Locker.

Abstract: As the secure data transmission has become a very important issue these days, various barcoding techniques have given a lot of relief in encoding the data into barcodes. The various barcodes like 1D Barcode, Line barcode, PDF457, QR Code, which have various data encoding techniques. But the major drawback of the existing barcodes is that the amount of data that can be encoded into barcodes is very small due to which becomes very difficult to encode larger data into these barcodes. So the paper makes a study about the existing barcoding techniques and thereby get a clear picture about what can be done for encoding the large amount of data. The comparative study of the existing systems is analysed in this paper.

Keywords: Barcoding techniques, data encoding, 2d Barcode, data transmission, security.

Abstract: According to originating standards for LTE-A mobile networks, the small cells are expected to be deployed in future mobile and wireless networks to improve coverage in specific areas with low signal quality. By placing additional stations to the network, new cell boundaries are introduced. Since heavy deployment of the small cells with low radius is expected in LTE-A networks, the procedures for the user�s resource allocation becomes more frequently. Therefore, more often scanning of higher amount of entities in UE's neighborhood must be performed. Moreover, each resource allocation generates some management overhead and introduces interruption in user�s communication. All these aspects lead to a drop of user�s throughput and QoS. This is getting more apparent with dense deployment of small cells. Hence, large and efficient deployment of the small cells requires optimizing the principles of user�s service allocation support to ensure continuous high level of service quality.

Keywords: LTE-A mobile networks, QoS, Wireless Networks, Heterogeneous Networks, E- UTRAN.

Abstract: This paper presents the implementation and comparison of high speed multipliers which depends on booth encoding. In this, we compare the performance of Radix-2 and Radix-4 based on booth multipliers. The multipliers are designed for 8X8 bit multiplication operation. We proposed designs of Booth algorithm which is called Modified Booth algorithm using Radix -4 has been designed using VHDL and synthesized, implemented using Xilinx ISE Sparten 3 Board. We compare the terms according to the critical path delay, cost, area and power consumption.

Keywords: Basic Booth Multiplier using Radix-2, Modified Booth Encoding using Radix-4.

Abstract: A mobile ad-hoc network is a cluster of communication nodes which are capable of communicating among each other in the absence of a backbone. Due to increase in the use of wireless communication, minimizing the hindrances in wireless networks is becoming a high priority objective. Mobile ad-hoc wireless networks are vulnerable to wormhole and blackhole attacks. These attacks affect directly the performance of network. Prevention of such attacks on network is a challenging task. These attacks can result in a significant collapse of the wireless communication networks. In this paper, a novel method (LTAWB) based on LTA multipath routing is proposed, which filters the packets of wormhole and blackhole attacks, for reliable communication in MANETs. In the proposed method, LTA is used to identify the order of event and to make synchronization of time clock in network device that reduces the complexity. The simulated results of the proposed algorithm are compared with that of fuzzy logic based secured MANET transmission against wormhole and blackhole attacks (SMTWB)[7]. It is observed that the proposed LTAWB shows better performance as compared to SMTWB [7], in terms of throughput, end-to-end delay and packet delivery ratio.

Keywords: MANET, Wormhole, Blackhole, Lamport Timestamp Algorithm (LTA), AODV routing protocol, NS2 Simulator, Multipath routing, Security attacks.

Abstract: For the communication between human being and in sign language hand gestures plays an important role. Deaf and deam people survive their life communication with hand gestures. Experimental scheme of the course of action uses solid position economical web camera mutually 10 mega pixel resolution mounted on the outstrip of monitor of computer which captures snapshot by Red Green Blue [RGB] enlarge space from tense distance The work is isolated into four stages one as image preprocessing, region extraction, feature extraction, feature matching. First it take the continuous images from the web camera mounted on the top of the machine. At the next level converts captured RGB conception into gray threshold approach with noise removed by the agency of median filter and Guassian filter, followed by morphological operations. At the third stage the features are extracted using HOG and classiffed using SVM algorithm. The paper include some example of dynamic hand gesture recognition related to some actions. Traning dataset consist of 20 samples of differ symbols.

Keywords: Image Preprocessing; Region Extraction; Feature Extraction; Median Filter; Support Vector Machine.

Abstract: Researchers initially have addressed the problem of spam detection as a text classification or categorization problem. However, as spammers� continue to develop new techniques and the type of email content becomes more disparate, text-based anti-spam approaches alone are not sufficiently enough in preventing spam. In an attempt to defeat the anti-spam development technologies, spammers have recently adopted the image spam trick to make the scrutiny of emails� body text inefficient. The main idea behind this project is to design a spam detection system. The system will be enabled to analyse the content of emails, in particular the artificially generated image sent as attachment in an email. The system will analyse the image content and classify the embedded image as spam or legitimate hence classify the email accordingly. This experiment results show this approach can get high recognition ratio and reduce the cost of calculation.

Keywords: Spam Filtering, Content Based Filtering, Spam email detection, Machine Learning, Nearest neighbour classifier, Pattern recognition, Data mining Classification, Na�ve Bayes.