VOLUME 4, ISSUE 2, FEBRUARY 2015

Abstract: Radiation properties of axially slotted elliptical antenna embedded in anisotropic plasma material are studied theoretically. The fields are expressed in terms of Fourier series with unknown constants. The radiated field constants are obtained using the boundary value method by invoking the boundary conditions at various surfaces. Results are plotted graphically for the radiation patterns for different geometries and electrical parameters.� The results show that the presence of the anisotropic plasma coating has affected the main beam while elliptic antenna beam is less oscillated compared to circular one for the same coating thickness

Keywords: axially slotted circular or elliptic antenna, theoretical analysis, anisotropic plasma material, radiation pattern

Abstract: Future wireless systems will require higher data rates with better coverage for a wide variety of users operating with a large variety of different systems.� To achieve these goals, greater power, interference suppression, and multipath mitigation are needed. Smart antenna gives a promising future for wireless communication systems since it can improve the capacity, extend coverage and provide better quality services by tracking users, switching beams accordingly. In this paper three non-blind adaptive beamforming algorithms, least mean square (LMS), Recursive Least square (RLS) and Sample matrix inversion (SMI) have been studied. Investigation of their performances in tracking a desired user has been made and compared. All the three algorithms direct their beams towards a desired user and place nulls towards interferer. However the rate of their performance differs from each other.

Keywords: � Non-blind adaptive algorithms, beamforming, LMS, RLS, SMI, Desired user, desired signal

Abstract: In recent years, Deep Learning at the latest developed field belonging to soft computing. The Deep learning has been a hot topic in the communities of artificial intelligence, artificial neural networks and machine learning. It tries to mimic the human brain, which is capable of processing the intricate input data, learning various knowledge�s intellectually and intense as well as solving sundry kinds of sophisticated tasks well. The deep learning paradigm tackles problems in which shallow architectures (e.g. SVM) are impressed with the curse of dimensionality. Deep architectures are composed of multiple levels of non-linear operations, such as in neural nets with many hidden layers or in complicated propositional formulae re-using many sub-formulae.� The transformation these characteristics of the human brain to a learning model, we wish the model can deal with the high-dimensional data, support an intense and intellectual learning algorithm and perform well in the inextricable artificial intelligence, real tasks, such as pattern recognition� speech recognition, image classification, computer vision and natural language processing. In this paper, we are discussing the history of deep learning, Deep Learning Architectures, abridge the components of Deep Boltzmann Machines (DBM), Deep Stacking Networks (DSN), Compound Hierarchical Deep Models(CHDM),� Deep Convolutional Neural Network (DCNN) and Deep Belief Network (DBN) their learning algorithms.

Keywords: Soft Computing, Support Vector Machine (SVM), Artificial Intelligence (AI), Deep Boltzmann Machines (DBM), Compound Hierarchical Deep Models (CHDM), Deep Learning.

Abstract: In this digital globe, the need of successful generation and transmission of data in numeric form is highly desirable. Images have always gathered attention as the data can be represented in a more appreciable format as compared to long strings of characters, so is the necessity of excellent image compression. The theory below demonstrates various image compression techniques available and briefly compares them all on the basis of certain parameters like PSNR, Compression Ratio, MSE and Code Energy. We have also proposed an innovative development in the arena of lossy image compression called as Lattice Vector Quantization which is supposed to reduce the average computational time required for image compression as well as the memory requirement for the same.

Keywords: LVQ, PSNR, MSE, Compression ratio.

Abstract: Image denoising is a kind of processing of image which belongs to image restoration, and the ultimate goal of restoration techniques is to improve an image in some predefined sense. In order to improve the power of signal to noise ratio of image, a local adaptive Wiener filter with Two dimensional block least mean square (TDBLMS) algorithm is applied to a 2-D image. Several 1-D windows could be constructed on the direction character of sub-image in the filter window after wavelet transform. To verify the feasibility of this approach, the simulations in the block-adaptation phase with the block sizes of 4 � 4, 8 � 8, 16 � 16, and 32 � 32 are performed. The simulation results show that this approach achieves a higher signal-to-noise ratio in each case of block size.

Keywords: TBLMS, 2-D, 1-D, PSNR, RMSE, Wiener filter, wavelet transform.

Abstract: The Wireless Oscilloscope android application helps one to observe the waveform of the closed circuit. This application is supported by all Smartphone�s and tablet computers (Receiver�s) that work on Android operating system. Hence it is easy portable and easy installation. At the end of the closed circuit, Wireless Fidelity (Wi-Fi) Module is used to transmit the waveform signal over radio frequency and then is received by receiver using Wi-Fi. At last Graphical Waveform is reproduced in receivers

Keywords: Cathode-Ray Oscilloscope, Wireless Fidelity, Voltage Divisions(Voltage Div),Time Divisions(Time Div), Graphical waveform of output waves, Frequency, IEEE, Mobility, Android Application, Linux-Based operating system and Graphical waveform.

Abstract: Due to richness of information in forums, researchers are increasingly interested in mining knowledge from forums. From this observation, the forum posts and replies are clustered and analyzed in order to improve the user knowledge in the field. To harvest knowledge from the forum the contents must be downloaded. Forum board or thread is usually divided into multiple pages which are linked by page flipping links.� The forum sites contain different pages like entry pages, thread pages and page flipping. ����������� The forum mining have three phases: preprocessing, mining the data by applying various data mining strategies such as clustering and post processing. In preprocessing raw data is transformed into a usable format, mainly by parsing and cleaning.� While preprocessing, the pages are downloaded as the html file and the files are invoked into parsing and assign attributes like forum id, forum title, thread count, post count. The parsing process is accomplished; data cleaning process is applied to the downloaded post sets and automatically remove noise data and irrelevant data. Clustering algorithm is applied for the preprocessed data to groups the forums into various clusters.� The clustering is accomplished by using all topics and sub topics of the forum. The four dimensions of clustering are number of posts/topics, average sentiment values/topics, positive percentage of posts/topics and negative percentage of posts/topics. The posts/topics dimension are determined by number of replies for a post, the sentiment values of this topics are identified from user replies, it describe the user opinion, the positive and negative dimensions are determined from user replies, describe the user perception in the posts. The positive and negative dimensions are also used to identifying the user attitude and pros and cons of the specific topics are discussed in the particular forum. In the post processing stage numbers of clusters are obtained. The obtained final clusters are grouped based on the topics with similar sentiment values and user opinions. Based on the sentiment values, the positive and negative posts are clustered for each thread. Information seekers, decision makers can benefit from this clustering. It simplifies the decision making process.

Keywords: Clustering, Forum, Graph, Threads.

Abstract: Today e-mails have become one of the most popular and economical forms of communication for Internet users. Thus due to its popularity, the e-mail is going to be misused. One such misuse is the posting of unwelcome, unwanted e-mails known as spam or junk e-mails. E-mail spam has various consequences. It reduces productivity, takes extra space in mail boxes, extra time, extend software damaging viruses, and materials that contains potentially harmful information for Internet users, destroy stability of mail servers, and as a result users spend lots of time for sorting incoming mail and deleting unwanted correspondence. So there is a need of spam detection so that its consequences can be reduced. In this paper, the focus is on various steps of spam detection such as pre-processing, representation of data, and classification for unmasking spam in e-mail messages. Further, some results, after applying the various spam detection steps have been displayed.

Keywords: Spam, Spam detection algorithm, Spam detection techniques, Email classification

Abstract: Towers of Hanoi is a standard planning problem in the field of computer science. It has applications in various fields of engineering. Solution to Towers of Hanoi is generally provided by method of recursion. Recursion is an functional programming concept widely used to solve variety of problems. Recursion has been providing solution to this problem most efficiently, hence other methods of solving have not been explored. In this paper we study artificial intelligence method of solving the problem.Artificial intelligence is a field of study which aims at creating intelligence in computer systems. Genetic algorithm is a well known algorithm for optimization used in artificial intelligence. In this paper we have studied a method of solving Towers of hanoi using genetic algorithm. Parallelism is achieved through OpenMp.We propose a comparative study of both Genetic agorithm and Recursive algorithm in solving Towers of Hanoi puzzle. Results for the same are presented.

Keywords: Towers of Hanoi, Genetic algorithm, Recursion, Roulette Wheel selection, OpenMp

Abstract: The early identification of leukemia form in cancer patients can greatly increase the likelihood of recovery. Diagnostic methods that distinguish among the disease's many forms are either costly or do not exist. Amongst the existing diagnostic methods are immune- phenotype and cytogenetic abnormality, which require time to obtain results and are costly to perform due to their requirement of well equipped laboratories. Thus, there is a need for fast and cost-effective method that results in the identification of the different leukemia forms or types. Therefore, we propose the use of digital image morphological analysis of microscopic images of leukemic blood cells for the identification purpose. We present in this paper the first phase of an automated leukemia form identification system, which is the segmentation of infected cell images. The segmentation process provides two enhanced images for each blood cell; containing the cytoplasm and the nuclei regions. Unique features for each form of leukemia can then be extracted from the two images and used for identification.

Keywords: Cancer Diagnosis, Leukemia Type, Blood Cell, Image Segmentation, Morphological Analysis.

Abstract: Cloud computing revolutionize IT and business by offering computing as a utility over the internet. The evolution from internet to a cloud computing platform, the emerging development paradigm and technology and how these will change the way enterprise applications should be architected for cloud deployment plays an important role but these enterprise technologies are critical to cloud computing. New cloud analytics and business intelligence (BI) services can help businesses (organizations) better manage big data and cloud applications.Analysing and gathering business intelligence (BI) has never been easy, but today BI is complicated further by overwhelming amounts of data loads and the number of data entry and access points. New cloud analytics advancements may offer BI relief and even profit-increasing predictability for enterprises. These new cloud analytics applications can deliver functional capabilities that can be easily, quickly and economically deployed, producing tangible and measurable benefits far more rapidly than in the past. Many organizations that recognized, effectively analysing their business needs and providing the data they require to make the right business decisions depends on a combination of internally generated data and externally available data.

Keywords: Enterprise clouds, Business Intelligence, Analytics, business models

Abstract: Mobile devices have larger impact in our daily life. The proposed project is concerned with ticketing and identification of the passenger in the public transport service. As seen in various metropolitan cities like Mumbai, Kolkata, Chennai, Bangalore there are various issues and problems related to severe malfunction and security. There are various problems related to public transport like confusion and misunderstanding between the passengers regarding fares, facing the severe problem of traffic jam, having severe security problems in public transport due anti social elements. This proposed project aims to develop a user friendly, interactive automated ticketing system which will deduct the passenger�s fare according to the distance travelled as well as detect the passenger�s identification. This is only possible by use of Near Field Communication (NFC) cards.

Keywords: �NFC cards, NFC card reader, Android mobile, Digital bus ticket

Abstract: Mobile ad hoc Networks (MANETs) is an autonomous assortment of mobile nodes that type form network with none existing network infrastructure or central access point. Since MANETs need a novel, distinct, and protracted identity per node so as for his or her security protocols to be viable, Sybil attacks cause a heavy threat to such networks. Sybil attacker will lawlessly claim multiple identities on single node and violate one-to-one mapping. Masquerading is an active attack where one node pretends to be another and giving false impersonation. Here by using RSS (Received Signal Strength) of nodes to find Sybil and masquerading identities on network with good accuracy even in the presence of mobility. This scheme detect Sybil identities while not exploitation centralized trusty third party or any further hardware, like directional antennae or a geographical positioning system.

Keywords: Mobile Ad hoc Networks (MANET), Received Signal Strength, Sybil Attack, Masquerading Attack, Security.

Abstract: An intrusion detection system is used to find the malicious activities in the network and reports to the management. It can be done in two ways. One is host based intrusion detection system and another one is network based intrusion detection system. There are two types of detection methods one is anomaly detection and another one is misuse detection. In this paper classification algorithm is used to detect the malicious activities in the network. Support vector machine concept is used to find the optimal hyper plane. Initially classification is done to classify the data whether it is normal or an attack. Then clustering concept is applied to group the similar attacks. After grouping multiple class batch processing is done.

Keywords: Intrusion detection system, Detection types, data mining, classification, Support vector machine, Multiclass batch algorithm.

Abstract: An intrusion detection system is used to find the malicious activities in the network and reports to the management. It can be done in two ways. One is host based intrusion detection system and another one is network based intrusion detection system. There are two types of detection methods one is anomaly detection and another one is misuse detection. In this paper classification algorithm is used to detect the malicious activities in the network. Support vector machine concept is used to find the optimal hyper plane. Initially classification is done to classify the data whether it is normal or an attack. Then clustering concept is applied to group the similar attacks. After grouping multiple class batch processing is done.

Keywords: Intrusion detection system, Detection types, data mining, classification, Support vector machine, Multiclass batch algorithm.

Abstract: A large number of cloud services require users to share private data like electronic health records for data analysis or mining, bringing privacy concerns. Unavowed data sets via generalization to satisfy certain privacy requirements such as k-anonymity is a widely used category of privacy conserving techniques. At present, the tensile of data in many cloud applications increases tremendously in accordance with the big data trend, thereby making it a challenge for frequently used software tools to capture, manage, and process such vast-scale data within a tolerable pass by time. As a result, it is a challenge for existing unavowed approaches to achieve privacy preservation on privacy-sensitive large-scale data sets due to their insufficiency of scalability. In this paper, we put forward a scalable two-phase top-down specialization (tds) approach to anonymize large-scale data sets using the mapreduce framework on cloud. In both phases of our start to deal with, we consciously design a group of innovative mapreduce jobs to concretely accomplish the specialization computation in a highly scalable way.

Keywords: Data anonymization, top-down specialization, mapreduce, cloud, privacy preservation

Abstract: �The demand for cross platform mobile development is constantly growing in the market. The basic need for programmers on any platform is compatibility. There are various cross-browser tools that will take any developer a long way in creating flexible apps that stand the compatibility test such as Whoop, Mosync, Phonegap, Appcelator etc. Phonegap is one of the most developer friendly tools present in the market which provide a good range of native APIs and platforms. This paper deals with the available approaches of building a cross-platform application using phonegap.

Keywords: PhoneGap, PhoneGap APIs, native APIs.

Abstract: Handwritten digit recognition is one of the important problems in computer vision these days. There is a great interest in this field because of many potential applications, most importantly where large number of documents must be dealed such as post mail sorting, bank cheque analysis, handwritten form processing etc. So a system should be designed in such a way that it is capable of reading handwritten digits and provide appropriate results. This paper presents a survey on various neural network approaches to recognize handwritten digits.

Keywords: Artificial Neural Network (ANN), Handwritten Digit Recognition, Back-propagation (BP), Single Layer Perceptron (SLP), Hopfield Neural Network (HNN).

Abstract: This Paper presents an overview of the clustering and its methods used in Data Mining. Firstly, different measures that are used for determining whether two clusters are similar or dissimilar are defined. Then different methods of clustering are presented and are divided into: �hierarchical, partitional and evolutionary algorithms. Finally clustering is performed in large data sets and subsequently their challenges are discussed.

Keywords: Clustering, similarity measures, clustering analysis, k-means.

Abstract: Detection and segmentation of faces from an image is a crucial problem that has gained importance, face detection and segmentation play the main role in the face recognition systems. There are many difficulties should be solved to make the face detection and segmentation algorithm successful. The face skin has special colors range as well as special textures that can be detected by using texture recognition algorithms which recognized skin from the background. In this paper we introduced a new method for face detection and segmentation based on face color, we uses the YCbCr color space as a method to segment image to many regions. Gray level co-occurrence matrix used to extract the important features represent the skin, and then Tamura texture used to remove all the non skin blobs which is recognized as skin by GLCM. The proposed algorithm tested with many images and it was successfully recognize the images with faces from images without faces. The proposed algorithm has high efficient in detected faces and segmented faces from the background. The accuracy of this algorithm more than 99% in detection faces and also segment its. The proposed algorithm forms a prerequisite for any practical verification system using face as the main attribute.

Keywords: segmentation, face detection, GLCM, skin color, Tamura.

Abstract: The most important challenge faced by a public cloud is hacking or data intrusion. If an attacker hack the cloud they can manipulate the information or disable the services. We all know that a Biometric system can ensure that rendered services can only accessed by a registered user only. It can identify an authorized user by checking the physiological features of that person. Here I wish to propose a new approach based on biometric encryption for to improve the security of data sharing in public cloud. In this approach we combine the digital key with the biometric image to create bioscrypt. These digital keys can be used as the cryptographic key. During the verification the biometric image is combining with bioscrypt to retrieve the key for the encryption and decryption of the data. The cipher text is then uploading to the public cloud. And an authorized user can retrieve data by his digital key. This approach ensures the data integrity and confidentiality.

Keywords: Biometric Encryption, Bioscrypt, Attack, Public Cloud

Abstract: Image processing has a very big potential to do virtually anything. This project comes to the extent of development details on Recognition of osteoporosis through CT images. The objective of the recognition of osteoporosis is to identify and distinguish between a normal bone image and osteoporotic bone image with its case as severe or non-severe. Osteoporosis is due to the following two phenomena: a reduction in bone mass and a degradation of the micro architecture of bone tissue. Osteoporosis is a disease in which the quality of bone is reduced, leading to weakness of the skeleton and increased risk of fracture and change is observed in micro architecture. In this project we propose a methodology to build a system to identify the normal bone image and affected bone image with the case severe or non severe. We use contrast feature of the grey level co-occurrence matrix and apply thresholding to detect the normal or osteoporotic bone image.

Keywords: Osteoporosis, Computer Vision, Bone Images, Endocrine, Rule Based Classification

Abstract: This paper aims at studying the various techniques and algorithms available in literature for the cancellation of various types of artifacts occurring out of the noise present in the Electrocardiogram (ECG) signal. It further aims at the enhancement of the ECG signal for proper monitoring and diagnosis of the patient. In the process of the transfer of the signal information from the location of the patient to a remote location, certain kind of noise is introduced in the signal that results in the disturbance as well as interference of the signal. Hence, the information cannot be predicted accurately. Thus, it is important to remove the resulting noise and the artifacts in order to enhance the ECG signal for proper treatment of the patient.

Keywords: artifacts, Electrocardiogram (ECG), enhancement, remote location, interference.

Abstract: Software organizations often need to migrate applications from one platform or technology to another for a variety of reasons. The software engineering research community is trying to find out techniques by which such migration projects can be carried out efficiently. The present paper proposes a technique called e-Splitter, to address the challenge of testing of migrated web application by enhancing an approach called Splitter. The paper attempts to draw on the power of genetic algorithms in addressing complex problems. Through an empirical study, we show that e-Splitter performs better than Splitter in testing of migrated web applications.

Keywords: Splitter, e-Splitter, Web Application migration, Testing

Abstract: The problem of online multitask learning for solving multiple related classification tasks in parallel, aiming to classify every sequence of data received by each task accurately and efficiently. First, to meet the critical requirements of online applications which is highly efficient and scalable classification, this solution can make immediate predictions with low learning cost is needed. Second, classical classification methods, it is the batch or online, often encounter a dilemma when applied to a group of tasks i.e., a� process of single classify model trained on the entire collection of data from all tasks may fail to capture characteristics of individual task; on other process, a model trained independently on individual tasks may suffer from the insufficient training data. To overcome these kinds of challenges we have proposed a collaborative online multitask learning method, which will learn a global model over the entire data of all tasks.  

Keywords: �Multitask learning, Global Model, collaborative Model, Scalable Classification.

Abstract: This paper discusses Cloud Computing is rising as a replacement machine paradigm shift. Hadoop-MapReduce has become a robust Computation Model for process giant knowledge on distributed commodity hardware clusters like Clouds. Studies describe that Hadoop implementations, the default first in first out scheduler hardware is accessible wherever jobs are scheduled in FIFO order with support for different priority primarily based schedulers also other defaulter schedulers� . During this paper we have studied numerous scheduling enhancements in a scheduling techniques a brand new with Hadoop like Fair4s scheduling algorithm with its extended functionalities allows processing large as well small jobs with effective fairness without starvation of small jobs. Majority of small jobs are available till date so Job scheduling algorithm must take in consideration of small jobs first with effective major to process these jobs.

Keywords: Cloud Computing, Hadoop, HDFS, MapReduce, Schedulers

Abstract: Introducing the new knowledge of Big Data for belief apprehension of large-volume, complex, growing data sets with several autonomous sources. HACE theorem that characterizes the features of big data revolution and �perform the operation in data mining perspective. Big Data e-Health Service application has promised to transform the whole healthcare heart disease process to become more efficient, less expensive and higher quality. This application involves data-driven model demand-driven aggregation of information sources. Big Data is transforming healthcare, business, as e-Health heart disease becomes one of key driving factors during the innovation process. Look into BDeHS (Big Data e-Health Service) to fulfil the Big Data applications in the e-Health service domain. Existing Data Mining technologies such cannot be simply applied to e-Health services directly. Our design of the BDeHS for heart disease that supplies data operation management capabilities and e-Health meaningful usages.

Keywords: Big data, Data mining, HACE theorem, Cloud storage, Hadoop map reduce.

Abstract: The flaw detection will detect data objects that are inconsistent with normal dataset. In additional to normal data, there exist negative outliers in many applications and data will be imperfectly labeled. This paper represents an outlier detection approach to address data with imperfect data labels into learning. Our past approach works in two steps. In the first step, we develop a pseudo training dataset by computing possible values of each example based on its local action. We introduce kernel k-means clustering method and kernel Local Outlier Factor-based method to compute the likelihood values. In the next step, we introduce the obtained possible values and limited abnormal examples into SVDD-based learning to produce a more accurate classification for global outlier detection. The proposed system has three approaches. They are Naive Bayes approach, Logistic regression and . For classification of dataset we go for these two approaches which makes easy to find outliers.

Keywords: �Flaw detection, abnormal data, local outlier factor

Abstract: Shadow will occur by sunlight or any light sources. We cannot get clear and quality picture for obtain the shadow in the images. The objective of this paper is detect and removal of shadows play an important role in application of urban high resolution remote sensing images. Object oriented shadow detection and removal methods are used in this paper.� Shadow detection is used during the image segmentation. The suspected shadow are extracted by the statistical features. For shadow removal, support vector machine and adaboost classifier based on IOOPL matching could effectively remove the shadow. According to the homogeneous section shadow removal will be performed. Our method can accurately detect shadows from urban high-resolution remote sensing images and can effectively restore shadows with a rate of over 95%.

Keywords: Object oriented, IOOPL, shadow detection, homogeneous section, shadow removal

Abstract: In cloud computing and services, virtual machine powers with its features by providing resources and various infrastructure which is actually expected by large businesses and organizations. A challenging problem yet cannot be solved is the storage file system of a virtual machine instance. The existing deduplication concepts to reduce the VM storage are under DEDE and SAN clusters. In case of extensive VM hosting, all the existing techniques are unable to convince since they have inadequacy to cost. Our proposed system addresses accessible deduplication storage exclusively for Extensive VM implementation. Design of this system offers rapid creation of instances of VM including transmission of data in peer-to-peer networks. A wide range of features like very less utilization of VM storage, cloning of VM instances quicker and using copy on read techniques peer caches are managed to avoid bottlenecks.  

Keywords: �Deduplication, Cloud computing, virtual machine, storage, peer to peer, Copy-on-Read.

Abstract: Mobile wireless sensor network is a subset of mobile ad hoc network. Therefore independent nods mobility is an essential property of network. Due to limited radio range the communication is also performed in ad hoc manner. In these networks the routing protocol played important role in route discovery between communicating nodes. Due to this the network suffers from the performance issues. Among them security is main area of concern in the presented work. Therefore different routing based attacks are investigated and a serious resources consumption attack is addressed. This attack using false messaging, or by modifying routing information network performance is affected. Thus an improved routing solution is suggested. This paper is proposed routing protocol is implemented and simulated in NS2 network simulation environment. In order to simulate the routing performance using two different network scenarios the performance is compared. And the comparative performance study is performed in terms of packet delivery ratio, throughput, end to end delay and energy consumption. The obtained results demonstrate the effective performance with respect to the traditional routing protocol.

Keywords: DOS attack, flooding attack, Routing Protocols, Security

Abstract: In today�s digitized environment, information has become a vital part of our day to day activities. Sharing of information becomes a drastic need in order to carry out business specific operations. Several mean of convenience has been brought forward to accomplish this task. Both security and privacy are the major concern while sharing information. Hiding of data i.e. steganography and encryption of data i.e. cryptography are the two familiar approaches in case of sharing of highly confidential data. Both approaches have efficient features and the collaboration of these two can yield optimum result. This paper suggests a modified approach that brings up both cryptography and steganography together in order to enhance the sharing of highly vital information using audio file.

Keywords: Confidential, Cryptography, Encryption, Steganography, RSA.

Abstract: Raising the number of services is emerging on the Web Development to get the relevant service-relevant data become too big to be effectively processed by traditional approaches. So Arise the Big Data Knowledge for challenge environment in the Mash ups. Clustering-based Collaborative Filtering approach (Club CF) is planned recruiting similar services in the same clusters to recommend services collaboratively (Recommender Service System).Technically this approach is enacted around two stages: In first stage, the available services are divided into small-scale clusters in logic for further processing. In second stage, a collaborative filtering algorithm is imposed on one of the clusters. The number of the services in a cluster is much less than the total number of the services available on the web, it is used to reduce the online execution time of collaborative filtering.

Keywords: �Big data application, clustering, mash up techniques, collaborative filtering

Abstract: Image inpaiting is the process of reconstructing or modifying the deteriorated or damage part of the image, just like in world of museum or valuable paintings the process of the inpainting is done by skill expert conservator. This inpainting process is focuses on to reduce the computational complexity of image structures. In this paper we introduced two algorithms that is diffusion based and super resolution algorithm. By comparing two algorithms we concluded that the super resolution algorithm is more superior than the diffusion based algorithm in the cases of clarity and time. In one survey, the innovative Digital photography is changing the way we communicate, socialize, and document events around us but they face some problem like blur image or some damaged part in the valuable image so it is need some new application software that help to solve these problems hence in this paper we introduced SR algorithms.

Keywords: Image inpainting, Blur image, Diffusion based algorithm, SuperResolution algorithm.

Abstract: Now a days Android mobiles are everywhere in the world, but if we consider the area such as IT industry, Organisations, Educational, Business in these sectors all the employee with their Android mobile phones performs much activities. Every company, organisation having their own policies, rules, future projects so in such cases the privacy, security and confidentiality must be maintain by the employee of the organisation. So it�s very important to track their mobile phones whether they are leaking the confidential data or they are doing wrong call, wrong SMS, or crossing out the organisation�s geographical area in working hours. Another thing there are so many criminal cases happening like child kidnaping so in order to avoid this all cases we need to track the location of child�s mobile [10]. After considering all these factors we implemented the system �Mobile Activity Monitoring System Using Android Spy� This system is implemented for tracking the daily activity of the users with their android mobiles. The information such as missed call, incoming call, outgoing call, call duration, incoming SMS, outgoing SMS along with its date and time will be tracked and updated to the server this server will be monitored by the administrator. This information can be maintained for security purpose of the organization such as leaking the confidential data and maintaining policies of organisation.

����� Another thing this system consists of an alert of location if any of user crosses the specified geographical area of the organization instantly an alert will be sent to the manager�s mobile phone in the form of E-mail [6]. This is very helpful system to the administrator to monitor any user in the organization with their personal data and location they exist through GPS .Through tracking such information organization can improved their performance in working hours.

Keywords: Android, GPS, SMS, Tracking, E-mail;

Abstract: The ischemic myocardium and coronary heart disease which occur due to abnormality in firing of the electrical impulses from the ventricles are causing an unanticipated death. This is most commonly referred to as Acute Myocardial Infarction (AMI). The value of ST-segment duration is not always easy to determine if the electrocardiograms (ECGs) are often spoiled by different types of artefacts. Occasionally it is not likely to recognize the exact end of the ��S wave and the accurate commencement of the T wave. Even if the Holter monitoring systems is useful to detect ST segment elevation or ST depression with good accuracy, there is no stringent technique of measuring an ischemic ST episode. This paper is intended to detect automatically ST-segment deviations and transient ST episodes which will help us in identification of Myocardial Infarction and also to categorize major cardiac arrhythmia. Our system has been tested and yielded an accuracy of 94.5% for the ST episode detection on the Long Term ST Database and 97.4% on MIT-BIH Arrhythmia Database.

Keywords: ST segment, MI, FIR filter, QRS, QT interval

Abstract: In today�s era, internet is the mean of convenience for sharing information over distance. Our day to day transactions completely relies on sharing of information and digital media. The sharing of confidential data can be done by using digital media such as images, audio and video etc. Certain technique has been brought forward to accomplish this sharing scenario. The enormous developments in the field of multimedia and internet technology easily let us do the distribution of digital media and data. Nowadays sharing of confidential data over network is a major issue, as there is a possibility of having threat to the information that we are delivering in terms of privacy and security. Hence it is necessary to find appropriate solution because the information that we are delivering needs to be delivered securely and safely. Considering this aspect, here we have implemented a system that hides the vital data behind an image in encrypted format by using multi-carrier/signature iterative generalized least-squares (MIGLS) algorithm, considering the fact that the quality of the image should not be differed, deflected or reduced.

Keywords: Digital media, Embedding, Encryption, MIGLS, Spread spectrum, Transaction

Abstract: Design of an algorithm for vehicle identification by recognizing the number plate is presented. Automatic Vehicle Identification (AVI) has many applications in traffic systems (highway electronic toll collection, red light violation enforcement, border and customs checkpoints, etc.).The proposed algorithm consists of three major parts: Number plate recognition, vehicle size detection and recognition of plate characters. For extracting the plate region, edge detection algorithms and smearing algorithms are used. In segmentation part, smearing algorithms, filtering and some morphological algorithms are used. And finally genetic algorithm is used for recognition of plate characters. For vehicle size detection blob detection method is used and for theft detection number plates are matched. Experiments have been conducted with images taken from various scenes and conditions and the detection rate is found to be 92.5 %. Experiments have conducted for recognition with LPR images taken at different conditions and the recognition rate is found to be 91 %. Detection time is linear function of number of objects in the input image. Potential applications include provisioning of vehicle parking facilities and campus security system for permitting authorized vehicles into the premises.

Keywords: Number Plate Recognition, Genetic algorithm, plate region extraction, segmentation, thinning, vertical and horizontal projection.

Abstract: Man interacts with computer in a number of ways, the interface between humans and computers they use is important in facilitating this interaction. New methods of Human Computer Interaction (HCI) has been developed in recent years, such as interaction with machine using hand movements, head movements, facial expressions, voice, touch etc. HCI aims to improve the interactions between users and computers by making computers more user friendly .The paper presents a system for eye blink detection and head movements for communication between man and machine. Facial features (eyes and nose) are detected based on which actions such as head movements and eye blinks are performed so that cursor can carry out appropriate functions on screen. Our system provides a comprehensive solution to control computer mouse cursor movement with eye-blinks and head movement for people with special needs. The user may perform the clicking of mouse through eye-blinks. For detection of face candidates our basic strategy is use of Six-Segmented Rectangular Filter (SSR) along with a support vector machine (SVM) for face verification. The patterns of between-the-eyes are tracked with update template matching in face tracking

Keywords: HCI, SSR, SVM, VOG

Abstract: In this digital world, where huge amount of information is available online, illegitimate access to sensitive information is on the increase. This information is accessed using online password guessing attacks like brute force and dictionary attacks. In this paper we depict the inadequacy of existing protocols and we propose the Password Guessing Resistant Protocol (PGRP) which can effectively prevent these attacks. The system is very stringent for attackers and at the same time is very user friendly for legitimate users.� The system prevents cookie theft related issues as it uses IP addresses to track known and unknown machines. It also makes use of ATTs to conquer the guessing attacks

Keywords: Online password guessing attacks, brute force attacks, dictionary attacks, ATT, CAPTCHA

No abstract available.

Abstract: Clustering is a useful exploratory technique for the analysis of gene expression data. In particular, model-based clustering considers that the data is generated by a finite mixture of underlying probability distributions such as multivariate normal distributions. The issues of selecting a �good� clustering method and determining the �correct� number of clusters are reduced to model selection problems in the probability framework. This paper presents an attribute clustering method which is able to group genes based on their interdependence so as to mine meaningful patterns from the gene expression data. It can be used for gene grouping, and classification. Using clustering attributes, the search dimension of a data mining algorithm is dense. It is for the aforementioned reasons that gene grouping and selection are important preprocessing steps for many data mining algorithms to be effective when applied to gene expression data. This project defines the problem of attribute clustering and introduces a methodology to solving it. Our proposed method group�s interdependent attributes into clusters by optimizing a criterion function derived from an information measure that reflects the interdependence between attributes. By applying our OFS algorithm to gene expression data, important clusters of genes are exposed. The grouping of genes based on feature interdependence within group helps to capture different aspects of gene association patterns in each group. Important genes selected from each group then contain useful information for gene expression classification and identification.

Keywords: Feature Selection, Online Learning, Large-scale Data�� Mining, Classification.

Abstract: Gesture recognition is the mathematical interpretation of a human motion by a computing device.It can originate from any bodily motion or state but commonly originate from the face or hand. It focuses in the field include emotion recognition from the face and hand gesture recognition. It presents a vision-based user interface designed to achieve computer accessibility for disabled users with motor impairments. Recognizing gestures as input allows computers to be more accessible for the physically-impaired and makes interaction more natural in a gaming or 3-D virtual world environment. Therefore, it is necessary to develop easily accessible systems for computers to achieve their inclusion within the new technologies. These applications involving hidden Markov models, particle filtering and condensation, are discussed in detail. Hidden Markov models (HMMs) and related models have become standard in statistics, with applications in areas like speech and other signal processing, bioinformatics etc. Markov chain Monte Carlo (MCMC) is great stuff. MCMC revitalized Bayesian inference and frequents inference about complex dependence.

Keyword: gesture recognition, particle filtering, HCI

Abstract: Mobile underwater networks with acoustic communications are confronted with several unique challenges such as long propagation delays, high transmission power consumption, and node mobility. In particular, slow signal propagation permits multiple packets to concurrently travel in the underwater channel, which must be exploited to improve the overall throughput. To this end, we propose the delay-aware opportunistic transmission scheduling (DOTS) protocol that uses passively obtained local information (i.e., neighbouring nodes� propagation delay map and their expected transmission schedules) to increase the chances of concurrent transmissions while reducing the likelihood of collisions. Our extensive simulation results document that DOTS outperforms existing solutions and provides fair medium access even with node mobility.

Key Words: Underwater, AUV, medium access control, opportunistic transmission, CSMA

Abstract: �MANET is one of the acts as routing. Routing main work is exchange information from one host to other host in the network. Multipath routing can be used to improve the efficiency of wireless links in Manet when sending multiple copies of data from one source to multiple group of receiver. In this paper BeeIP present multipath routing in Manet. BeeIP is swarm intelligence based new honeybee inspired routing protocol. It is based on the collective behavior of honeybee forager and able to actively detect multiple paths between Source and destination also distributes traffic across them. The simulation result show that proposed work achieves able to delivery of packet faster and average end to end delay and packet delivery ratio better than other routing protocol and this protocol maintains balanced control overhead during mobility changes.

Keywords: �Swarm intelligence, Mobile ad hoc network, Ant-colony, Bee-colony,� routing protocol.

Abstract: Uncertain reasoning which is from artificial intelligence community, a unified trust management scheme that enhances the security in MANETs is proposed. In the proposed trust management scheme, the trust model has two components: trust from direct observation and trust from indirect observation. In direct observation from an observer node, the trust value is derived using Bayesian inference, when the full probability model can be defined. On the other hand, with indirect observation that is obtained from neighbour nodes of the observer node, the trust value is derived using the Dempster-Shafer theory (DST), which is another type of uncertain reasoning when the proposition of interest can be derived by an indirect method. Combining these two components in the trust model, we can obtain more accurate trust values of the observed nodes in MANETs. Evaluating our scheme under the scenario of MANET routing is also done. The number of nodes used as� an intermediary can also be reduced by using beacon messages between them.

Keywords: Security, Trust Management, MANETs, Uncertain Reasoning.

Abstract: Cloud used as a standalone operating system, where the hardware required is relatively low. Cloud OS manages the user account and the Cloud OS include simple Text editor, Paint application, spreadsheet and a presentation viewer that we usually use in daily life. It also includes Calendar, Contacts manager, and simple games. The Web OS is also used for Remote application management. An OS provide an interface for user�s to manage the applications running on the system. Cloud computing is the technology that helps in reducing the usage of time, cost and resources which is now-a-days used widely by the companies. There are several cloud approaches to store data files and synchronize file versions.

Keywords: Cloud OS, GUI Interface, Chrome OS, Virtual Desktop, SaaS, PaaS, IaaS.

No abstract available.

Abstract: Text and strings in images will be used to provide more informations. Extracting text directly from natural scene images or videos is a challenging task because of diverse text patterns and variant background interferences. Text recognition from natural images can be made using discriminative character descriptor and character structure. But there is a chance of false recognition and low text accuracy. In this paper, the accuracy rate of text detection and adding lexicon analysis is done to extend our system to word-level recognition in natural videos. To improve the accuracy and practicality of scene text extraction, designing more representative and discriminative features to model text structure will be made. This can be achieved by collecting a database of specific scene text words as stronger training set, for example, a set of word patches �EXIT� or �SALE� cropped from scene images. In addition, we will combine scene text extraction with other techniques like content-based image retrieval to develop more useful vision based assistant system.

Keywords: Scene text detection, scene text recognition, mobile application, character descriptor, text understanding, text retrieval.

Abstract: Mobile ad-hoc networks are temporary wireless networks. Network resources are abnormally consumed by intruders. Intrusion detection techniques are used for the network attack detection process. The receiver collision, low transmission power and misbehave report authentication attacks are generated in the routing process.� The acknowledgement scheme is used to control the routing based attacks. Service level based attacks are raised using service requests. Classification methods are used to discover the service level based attacks. The nodes are grouped into clusters. The leader nodes are assigned for the clusters. Cluster Dependant Leader Election (CDLE) and Cluster Independent Leader Election (CILE) schemes are used in the system. The system optimizes the leader election and intrusion detection process. The system uses the Enhanced Adaptive ACKnowledgment (EAACK) scheme for routing based attack detection process. RSA and Secure Hash Algorithms are used to secure the EAACK scheme.� The Bayesian Classification algorithm is used for service level attack detection process. Node mobility is managed by the system.

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Keywords: Mobile ad-hoc networks, Intrusion detection, CDLE, CILE, EAACK, Bayesian classification algorithm.

Abstract: Web-based image search engines mostly rely on surrounding textual features.� It becomes very difficult for them to interpret users� search intention only by query keywords and this leads to ambiguous and noisy search results which do not satisfy users perspective. In order to solve this ambiguity in text based image retrieval we used visual information of query image. In this project, we are implementing a novel Internet image search approach where user is asked to click on one query image with less effort and visually relevant images from a huge database are retrieved. Our main perspective is to capture the users� search intention from this one-click query image in following steps. In this system, the user first submits query keyword. A pool of images is retrieved by text-based search. Then the user is asked to select a query image from the image pool. Images in the pool are re-ranked based on their color and texture similarities to the query image. These similarities are computed using Euclidean distance method. A query-specific color similarity metric and a query specific textual similarity metric are learned from the selected examples and used to rank images. These similarity metrics reflect users� intention at a finer level since every query image has different metrics.

Keywords: Content based image retrieval (CBIR), Color Coherence Vector (CCV), Texture Element Feature Characterization (TEFC), Pixels, Image, Cluster.

Abstract: The paper is based on concept of smart database which deals with formal student guidance throughout his four years of engineering. The older versions made use of static assessment to generate generic student report on the other hand Academic Advisor makes use of various smart algorithms to generate a dynamic student guidance support system which help students to keep a track of their progress and helps them to make informed decisions throughout their academic session and also in their future job endeavors. It helps the IT firms to shortlist students for interview based on the criteria provided by Academic Advisor based on a special and smart grading system. Hence Academic Advisor will provide student with a virtual personalized tutor.

Keywords: Educational Data Mining(EDM); Guidance Support System; Adaptive Hypermedia System; Academic Analytics.

Abstract: With the tremendous growth of the usage of computers over network and development in application running on various platform captures the attention toward network security[1]. Intrusion detection system has become an important component of a network infrastructure protection mechanism. The Intrusion Detection System (IDS) plays a vital role in detecting anomalies and attacks in the network [5]. In this work, data mining concept is integrated with an IDS to identify the relevant, hidden data of interest for the user effectively and with less execution time. In proposed system, we first preprocess dataset (KDD 99 cup).� Then we study different types of decision tree algorithms (C4.5 and its extension) of data mining for the task of detecting intrusions and compare their relative performances. Based on this study, it can be concluded that even extended C4.5 is complex but decision tree obtained is the most suitable with high true positive (correct detection of attacks) and low false positive (Incorrect detection) with high accuracy.

Keywords: Intrusion detection system, KDD 99 cup, Data Mining, Decision Tree Algorithms, C4.5 and its extensions

Abstract: Timetable creation is a very arduous and time consuming task. To create timetable it takes lots of patience and man hours. Time table is created for various purposes like to organize lectures in school and colleges, to create timing charts for train and bus schedule and many more. To create timetable it requires lots of time and man power .In our paper we have tried to reduce these difficulties of generating timetable by Genetics Algorithm. By using Genetic algorithm we are able to reduce the time require to generate time table and generate a timetable which is more accurate, precise and free of human errors. The first phase contains all the common compulsory classes of the institute, which are scheduled by a central team. The second phase contains the individual departmental classes. Presently this timetable is prepared manually, by manipulating those of earlier years, with the only aim of producing a feasible timetable.

Keywords: Genetic algorithm, timetable, constraints, chromosomes.

Abstract: As the Joint Photographic Experts Group (JPEG) has become an international standard for image compression; we present techniques that allow the processing of an image in the �JPEG-compressed� domain. The goal is to reduce memory requirements while increasing speed by avoiding decompression and space domain operations. In each case, an effort is made to implement the minimum number of JPEG basic operations. Techniques are presented for scaling, previewing, rotating, mirroring, cropping, recompressing, and segmenting JPEG-compressed data. While most of the results apply to any image, we focus on scanned documents as our primary image source

Keywords: �JPEG, DPCM, RLE, CWT

Abstract: When using the secure cloud storage services on resources limited Mobile Devices, the confidentiality of sensitive data must be ensured before uploading the data on cloud storage servers. The complex security operations to ensure security are restricted to execute due to the resource constrained mobile devices. The huge volume of complex security operations are offloaded remotely on cloud storage. By literature review of existing security frameworks focus on reducing the complexity of cryptographic algorithms or methods to offer confidentiality and security. By keep in view the requirements of security and privacy of confidential data of users with resource restricted mobile devices, in this paper, We present a proposed security framework for mobile cloud computing. In this framework the cryptographic methods as well as algorithms are used for encryption and decryption of mobile user data. This Framework ensures the additional security and confidentiality of user�s sensitive or significant data. This paper introduces the scheming flow of proposed security framework. This proposed Security framework is for the purpose to secure and provide privacy and integrity to user�s confidential data in Mobile Cloud Environment.

Keywords: Mobile Cloud Computing; Cloud Computing; security; confidentiality; cryptography.

Abstract: The basic idea behind the ontology is to conceptualize information that is published in electronic format. The problem of ontology alignment is defined as identifying the relationship shared by the set of different entities where each entity belongs to separate ontology. The amount of similarity between two entities from two different ontologies takes part into the ontology alignment process. There are several similarity measuring methods available in the existing literature for measuring the similarity between two discrete entities from different ontologies. To obtain a comprehensive and precise result, all the similarity measures are integrated. One of the ways to combine the various similarity measures is weight-based similarity aggregation. Usually the weights with respect to various similarity measures are assigned manually or through some method. But most of the existing techniques suffer from lack of optimality. Also many evolutionary based approaches are available to find the optimal solution for weight-based similarity aggregation but they are designed as single objective optimization problem. This fact has inspired us to develop a multiobjective particle swarm based optimization algorithm for generating optimal weight based similarity aggregation to get a optimal alignment. In this article, two objectives precision and recall are simultaneously optimized. Moreover a local search is conducted for replacing the worst population in the new generation by best population acquired from the history. The proposed study is evaluated using an artificial data set and performance of the proposed method is compared with that of its single objective versions.  

Keywords: ontology alignment, particle swarm optimization, multiobjective optimization, f-score.

Abstract: Communication is an integral part of human life. But for people who are mute & hearing impaired, communication is a challenge. To understand them, one has to either learn their language i.e. sign language or finger language. The system proposed in this project aims at tackling this problem to some extent. In this paper, the motivation was to create an object tracking application to interact with the computer, and develop a virtual human computer interaction device. The motivation behind this system is two-fold. It has two modes of operation: Teach and Learn. The project uses a webcam to recognize the hand positions and sign made using contour recognition [3] and outputs the Sign Language in PC onto the gesture made. This will convert the gesture captured via webcam into audio output which will make normal people understand what exactly is being conveyed. Thus our project Sign Language to Speech Converter aims to convert the Sign Language into text and audio.

Keywords: Gesture recognition, image processing, Edge detection, Grey scale image

Abstract: Data clustering which is also called as Cluster Analysis is the unsupervised classification of data into various clusters. Clustering is a method of unsupervised learning which is generally implemented by various machine learning techniques. In this paper a specific comparison of three kinds of clustering is introduced and finally the cost function and loss function are calculated. For evaluating any clustering methods, calculation of the error percentage of the concerned method play an important factor. In this paper comparison is carried out on k-means clustering algorithms, hierarchical algorithms and density based algorithms. The main criteria where focus is given while comparing the clustering algorithms are: Scalability, Classes for dealing with noise and extra deposition, different dimensions of high levels etc.

Keywords: Clustering, K means, Hierarchical algorithms, Density based algorithms, Cluster.

Abstract: Cloud storage is a model of data storage, whose demand is greatly increasing. The data sharing is one of the concerning functionality in today�s world of information as it involves security, efficiency and flexibility as their important aspects. Various schemes and methodologies are implemented to make data sharing more effective. With the introduction of encryption and decryption schemes, the storing, sharing and securing of data became rampant. The storing of these ciphertexts and the decryption keys is one of the major issues. There is a need for a mechanism which can minimize the cost of storing these ciphertexts and keys in a secured way. In this paper, we explore the various encryption schemes which were proposed to solve this problem. In this era of information, where there is presence of rich data, the true value lies in sharing, securing and storing them. Protecting users�s data privacy is one of the critical goal of cloud storage. The present research efforts concentrates more on aggregation of these keys into a single aggregate key which will in turn reduce the burden on the network overhead.

Keywords: Cloud storage, data sharing, ciphertexts, encryption schemes

Abstract: Displaying information is an important part in day to day life, so that we are trying to display the message through the LCD in every area and the message will be send through the mobile phones and the priority base information can be displayed on the LCD screen. The authentication purpose we are using the GSM technology which improves security in displaying message. A hi-tech wireless display board use for displaying anywhere.The project is built around the AT89C51 micro controller from Atmel.

Keywords: Global System for Mobile (GSM), SMS, PC, LCD, AT 80c51

Abstract: The hasty e-commerce development has made equally trade community and consumers face a novel situation. Due to severe competition on one hand and the customer�s option to choose from numerous substitutes business community has realized the essential of clever marketing strategies and relationship management. Web usage mining attempts to find out useful facts from the secondary data obtained from the communications of the users with the Web. The paper concerns some Ant Colony Clustering and optimization technique for Web server log file to analyze user�s interest, which is useful for giving suggestion about specific user�s interest.

Keywords: Web Usage Mining, Ant Colony Optimization, ACLUSTER, ACCANTCLUST

Abstract: During the last years, computer-vision-based identification systems are employed in many hospitals and medical specialty clinics, aiming largely at the first detection of carcinoma, and additional specifically, the popularity of melanoma neoplasm. In this paper, we tend to review the state of the art in such systems by initial presenting the installation, the visual options used for skin lesion classification, and therefore the strategies for outlining them. Then, we have a tendency to describe a way to extract these options through digital image process ways, i.e., segmentation, border detection, and color and texture process, and that we gift the foremost outstanding techniques for skin lesion classification. Image segmentation is vital|a crucial|a vital|a very important} task in analysing dermoscopy pictures because the extraction of the borders of skin lesions provides important clues for correct designation. In this paper, we have a tendency to introduce a replacement mean shift based mostly fuzzy c-means formula that needs less machine time than previous techniques whereas providing smart segmentation results. The projected segmentation methodology incorporates a mean field term inside the quality fuzzy c-means objective operate. Since mean shift will quickly and faithfully realize cluster centers, the whole strategy is capable of effectively police investigation regions inside a picture.

Keywords: computer vision, dermoscopy, melanoma, pattern analysis, skin cancer. Dermoscopy, fuzzy c-means, image segmentation, mean shift, melanoma, carcinoma..

Abstract: The challenging issue of defining and implementing an effective law for load balancing in Content Delivery Networks (CDNs). The proposal on a forma study of a CDN system, carried out through the exploitation of a fluid flow model characterization of the network of servers. Starting from such characterization, it derives and proves a lemma about the network queues equilibrium. The result is then leverage in order to devise a novel distributed and time-continuous algorithm for load balancing, which is also reformulated in a time-discrete version. The discrete formulation of the proposed balancing law is eventually discussed in terms of its actual implementation in a real-world scenario. Finally, the overall approach is validated by means of simulations.

Keywords: Load balancing, Content Delivery Network, Cooperative Algorithm

Abstract: Cloud computing is generating lot of interest to provide solution for data outsourcing and high quality data services. More and more institution, organizations and corporations are exploring the possibility of having their applications, data and their IT assets in cloud. As the data and there by the cloud�s size increases searching of the relevant data is expected to be a challenge. To overcome this challenge, search index is created to aid in faster search. However, search Index creation and computation has been complex and time consuming, leading to cloud-down time there by hindering the swiftness in reacting to data request for mission critical requirements.

Focus of this paper is to explain how in the proposed system, reusability of search index is helping to reduce the complexity of search index computation. Search index is proposed to be created using parameters like similarity relevance, user ranking and scheme robustness. User ranking helps to guarantee why a phrase or a sentence or a key word is used frequently in the uploaded data. The proposed system ensures that the reusability of search index concept, highly reduces cloud down time while maintaining the security using searchable symmetric encryption (SSE).The user requested file is retrieved from the cloud, using Two-round searchable encryption (TRSE) scheme that supports top-k multi-keyword retrieval.

Keywords: Cloud, data privacy, search index, ranking, homomorphic encryption

Abstract: Magnetic Resonance Imaging (MRI) is beneficial and effective diagnostic tool in basic analysis, clinical investigation, and unwellness identification since it provides each chemical and physiological info regarding the tissue underneath investigation. however once noise get introduced in mister pictures, it decreases the image quality ,Image analysis and becomes tough to diagnose it accurately. A trade off between noise reduction and preservation of actual image options must build in such manner that enhance the diagnostically relevant image content. so noise reduction remains difficult task. This paper proposes wave domain denoising for removal of Rician noise from MR Image. This methodology heavily depends on alternative of threshold parameter that successively determines the potency of denoising.

Keywords: Magnetic resonance imaging, Rician noise, Threshold, denoising

Abstract: Database security is a main challenge these days. Companies store sensitive information in databases, however, database security is sometimes not given as much attention and effort as other areas of computer security. These databases can be easily hacked to obtain sensitive information. In this paper, I present two main aspects of Database security- security as most people would understand it (security from outside attacks) and security from the inside (confidentiality policies).

Keywords: Databases, security, confidentiality, technology.

Abstract: Precision irrigation system is basically based on a detailed monitoring of information and data that are necessary for successful decision making in farm production. Wireless Sensor Networks (WSNs) are used for collecting, storing and sharing sensed data. WSN have attracted much attention of researchers in recent years. In past years an extensive research and development work has been done in the field of WSN in the world. WSN have been used for various applications including agriculture, nuclear reactor control, habitat monitoring, environmental monitoring, security and tactical surveillance. WSN have immense potential such that if properly designed and developed can be a solution to a low cost precision irrigation system. The WSN system developed in this paper is for use in precision irrigation system, where real time data of environment and climate are sensed and according to the sensed data a control decisions are taken so that we can modify them. The architecture of WSN consist of a sensor node placed in a field which sends the sensed data to the base station so that a global decision can be taken about the physical environment. This irrigation system promises to give a higher yield and lower input cost by real time monitoring of the field soil and environment conditions using different sensors and thereby improving crop cultivation, reducing time and labor costs.

Keywords: Wireless Sensor Network, Precision Agriculture, ZigBee Network, Soil Moisture Sensor.

Abstract: Cognitive radio network is the promising technology of the next generation communication networks which enables the secondary users (SUs) to use the free spectrum bands which are licensed originally to the primary users (PUs) without causing interference and utilize the spectrum more efficiently. Spectrum sensing should be carried out frequently in order to transmit the data successfully through SU without causing significant interference with the PU and to achieve the maximum throughput. In this paper we propose an artificial neural network model which is known as Levenberg-Marquardt (L-M) algorithm for predicting the propagation. The simulation results show that there is a significant gain in the throughput when compared with both random and HMM methods and it explains the superiority of the algorithm. Also, it is found that the L-M algorithm is faster than the other algorithms.

Keywords: Cognitive Radio Networks, Throughput, Neural Network, Levenberg-Marquardt algorithm

Abstract: This is an era of smartphones. Nowadays Smartphones usage has become quite popular among the masses. There are quite a lot of android applications available in the market almost in every field. So this paper intents to develop an android app� that acts as a smart tourist guide for the users. In Traditional methods, a� problem� is� seen� that� the� travellers� do not� get� exact information while travelling and also the information is not provided on time. The app overcome this drawback by providing convenience to� the� user� while� travelling. The app serves following purposes: User� can find� a� companion to share the vehicle(car-pooling),share GPS location and track location of person in friendlist, decide� between� paths� suggested by� the� application� on� basis� of� time,� distance, find help in case of any emergency, help the user when he/she is in unknown region ,maintain history of travelling.The app aims to provide detailed Maps and GPS location tracking so users� can� understand better� and can� take proper decisions. The travellers can communicate with each other by sending notifications of their GPS location through SMS to other users.�

The� app works based on the principle of Near Neighbor Join algorithm to calculate distance between two nodes and to a given input node finding a set of nearest nodes using a join function.

Keywords: Android, Google Maps, GPS, kNN Join, MapReduce , Near Neighbor Join.

Abstract: Vehicular ad hoc networks (VANETs) are a special form of wireless networks made by vehicles communicating among themselves on roads which includes communications among vehicles and between vehicles and road side units. However, due to the high mobility and the frequent changes of the network topology, the communication links are highly vulnerable to disconnection in VANETs. This paper extend the well-known ad hoc on-demand distance vector (AODV) routing protocol with evolving graph theory to propose reliable routing protocol EG-RAODV. Simulation results demonstrate that EG-RAODV significantly outperforms better packet delivery ratio, lowest routing request ratio, less link failures while maintaining a reasonable routing control overhead and lowest average end to end delay.

Keywords: (AODV) ad hoc on-demand distance vector, (AODV) Vehicular ad hoc network.(MRJ) most reliable journey.

Abstract: Video Surveillance is important as far as security is concerned these days. Commercial spaces, schools and hospitals, warehouses and other challenging indoor and outdoor environments require high end cameras with PTZ. The current technologies require RFIDs which are costly and hence the security domain in all becomes expensive. This paper describes the use of low cost single �board computer Raspberry Pi which follows face detection algorithm written in Python as a default programming environment. This new technology is less expensive and in this paper it is used as a standalone platform for hosting image processing. The paper aims at developing a system which captures real time images and displays them on browser using TCP/IP. The algorithm for face detection is being implemented on raspberry pi which enables live video streaming along with detection of human faces.

Keywords: Raspberry Pi, Video surveillance, IP camera, embedded system

Abstract: This paper describes power harvesting for mobile charging from ambient microwaves. Battery life of mobile phone is always been a problem for manufacturers. People are complaining about their mobile�s battery life, that they don�t have long battery life and they have to charge their phone several times. Portable electronic devices are very popular now a days. As the usage of these portable electronic devices is increasing, the demands for longer battery life are also increasing. This wireless battery charger is expected to eliminate all the hassles with today�s battery technology. In this paper a new proposal has been made so as to make the recharging of the mobile phones is done� automatically as you talk in your mobile phone! This is done by use of microwaves. There are minimal additions, which have to be made in the mobile handsets, which are the addition of a sensor, a �rectenna� and a filter. With the above setup, the need for separate chargers for mobile phones is eliminated and makes charging universal. Thus the more you talk, the mobile phones is eliminated and makes charging universal. Thus the more you talk, the more is your mobile phone charged.

Keywords: Band pass filter,� Global for mobile communications Industrial, scientific and medical ,International telecommunication union, Slotted waveguide antenna

Abstract: In todays era, information security is an important aspect in which data is secure from unauthenticated user. Unsuspected victim attacks the information for economic gain, individual gain and for other illegal activities. Phishing is one of them in which unauthenticated person tries to thieve personal confidential information. To avoid these illegal activities we have projected a new paper �An Anti-Phishing Framework Using Visual Cryptography�. In this, image is generated which after exploit, decomposed into two shares. One share is kept with user and other with server. And when it requires that is at the time of login at particular site two shares are combined together to form original image. The image form by combining two shares will state that current site is not a Phishing site and also identify that user is authenticated one. So data can be secured from unsuspected person.

Keywords: Visual Cryptography, Encryption, Phishing Attack, Shares, Security.

Abstract: The visually impaired face various kinds of problems that normally sighted people don�t. Here a significant help is offered by android application for smartphone equipped with speech synthesizers. In this paper we have mentioned various problems faced by them and currently available solutions. We have used HSV model for more accurate processing of image. For training and recognizing image ANN algorithm is used. ANN facilitates faster training and detection of objects. To separate foreground and background from image sobel edge detection is used.

Keywords: HSV model, ANN and Sobel edge detection

Abstract: Semantic Web is actually an extension of the current one in that it represents information more meaningfully for humans and computers comparable. It is enables the report of contents and services in machine readable form and enables discovering, publishing, promotion and composing services to be mechanical. Ontology classification is the process of establishing partial order on the set of named concepts in ontology using the subsumption tests. Besides answering specific subsumption and satisfiability queries, it is often useful to compute and store the subsumption relation of all the concept names in the ontology. �It was developed based on the Ontology it is measured as the spine of the Semantic Web. In new terminology, the present Web is transformed from being machine readable to machine understandable. One function of the Web is to build a source of reference for information on several subjects, while the Semantic Web is designed to build a web of meaning. The foundation of vocabularies and effective communication on the Semantic Web is ontology. Ontology provides a formal, explicit specification of a shared conceptualization of a domain.

Keywords: Ontology Classification, OWL, Semantic Web, Web Services

Abstract: This paper presents a comprehensive review of Handwritten Character Recognition (HCR) in English language.The handwritten character recognition has been applied in variety of applications like Banking sectors, Health care industries and many such organizations where handwritten documents are dealt with. Handwritten Character Recognition is the process of conversion of handwritten text into machine readable form. For handwritten characters there are difficulties like it differs from one writer to another, even when same person writes same character there is difference in shape, size and position of character. Latest research in this area has used different types of method, classifiers and features to reduce the complexity of recognizing handwritten text.

Keywords: Handwritten database, features extraction, classifiers, HCR system.

Abstract: In most of the university and colleges attendance of students is important factor, checking student attendance is the important issues because all universities evaluate student�s attendance while them giving final grade. Some colleges use paper sheet for student attendance and after that fill all this information manually in college server. This all are time consuming process like calling particular student then fill all information, and student give the proxies of their friends even they absent. By considering all this issue we develop one system which get attendance and update attendance in one place. Our paper presents near field communication technology to get the attendance of students in school and colleges. The system is based on NFC Technology and run on mobile as application, this paper presented details of this system.

Keyword: attendance, near field communication, android OS, embedded mobile camera

Abstract: In this paper, dispersion compensating fibers (DCF) are used to compensate the positive dispersion accumulated over the length of the fiber at 10Gbits/sec and 250 km of optical fiber with 50 km of DCF. Three schemes (Pre-compensation, post-compensation and symmetrical-compensation) of dispersion compensation with DCF are proposed. The simulated transmission system has been analyzed on the basic of different parameters by using OptiSystem 7.0 simulator. The results of three dispersion compensation methods are compared in terms of four parameter, which are Q-factor, BER, Eye height and threshold value, investigated at the receiver end. Further, it has been observed that the system needs proper matching between EDFA gain and the length of the fiber for the optimum performance.

Keywords: Dispersion compensation, Dispersion compensating fiber (DCF), BER, Q-factor, Eye height.

Abstract: �Fiber �Bragg �Grating (FBG) is one of the applicable and important components in optical communication system. In this �paper, chirped �FBG has been studied as a dispersion compensator in an optical communication system for the different lengths of grating and apodization functions. All the simulations are done in OPTISYSTEM 7.0 simulation software at 10 Gbits/sec and 210 km of transmission fiber. The simulated transmission system has been analyzed on the basic of different parameters, which are BER, Q-factor, Output power and Eye height.

Keywords: Fiber Bragg Grating (FBG), eye diagram, BER and Q-factor.

Abstract: CAM (content-addressable memory) is a specialized type of high-speed memory� that searches its entire contents in a single clock cycle. We are designing� generalized CAM using Dual Port RAM (random access memory) structure which will perform match operation in addition to read and write operation .The design has fast search capabilities while consuming least system resources as possible.CAM provides performance advantage over other search algorithms as searching is based on content rather than address unlike RAM. The match time of our CAM� �structure is faster and resources are more effective.CAM is used in application where search time is very critical. content addressable memory� compare input search data against stored data and return address of� matched data. Thus overall function of CAM is to take search word and return matching memory location.

Keywords: Dual Port , RAM (random access memory), CAM (content-addressable memory), match

Abstract: A PN sequence is a reference signal simulating the random samples of discrete digital information and generates the samples in a specific manner so that it follows the correlation property. A correlation and maximal length sequence of pseudo-random signals is the basis of spread spectrum communication systems intern CDMA. In this paper we examine a comparative study of PN sequence with theoretically measured correlation function at different value of total sequence.

Keywords: PN sequence, Autocorrelation Sequence, Cross-correlation Sequence, Spread Spectrum Modulation, LFSR circuit analysis

Abstract: Providing guaranteed Quality of Service in the current internet has become extremely essential to fulfill the requirements of current internet services. With increase in the number of users and demand for real time applications like video streaming, VoIP, audio video conferencing there is high demand for larger bandwidth for these applications. Many schemes have already been put forth and implemented for such real time applications but with some disadvantages. The project proposes integrating of the IP multicast over MPLS with different Quality of Service QoS techniques to guarantee essential QoS parameters like the bandwidth, delay, and through put. The project implements a non-traffic engineered approach using Label Distribution Protocol (LDP) instead of Resource Reservation Protocol (RSVP) as RSVP has scalability issues when it comes to real time video conferencing application. The network so designed has been simulated using the simulation tool OPNET modeler. The results obtained from the simulation clearly show that use of IP multicast over MPLS while using different QoS techniques has better performance in terms of bandwidth, throughput and delay when compared with convention IP data transfer approach.

Keywords: MPLS, IP, Multicasting, QoS, LDP, RSVP, PIM-SM, ASM, SSM

Abstract: The main idea in this research is to design an E-Marketing website that deal with the problems in previous sites.��� Top ten sites in E-Marketing according to the most frequently used search engines �Google and Yahoo� are visited and evaluated according to certain criteria. Advantages and drawbacks are extracted and compared. Researchers built Home delivery website that avoid many negative points in the analyzed sites.

Keywords: Include at least 4 keywords or phrases

Abstract: Software metrics are quantities estimates for software product attributes which guide us in taking managerial and technical decisions [1]. The current used software metrics depend on syntactical source code at the same time they ignore its semantic aspects. This fact motivates us to focus on semantic metrics instead of traditional used metrics. Moreover, semantic metrics are more precise than syntactic ones, they able to capture the semantic defects of the software system development. In this paper, the researcher will make survey of� an existing research on software metrics along with potential research challenges and opportunities.

Keywords: Metrics, Semantic, Synthetic, quality, data mining.

Abstract: Search for the information is not only limited to the native languages of the user, but nowadays it is more extended to other languages. Cross language information retrieval (CLIR), whose goal is to find relevant information written in a language different from the language of query. CLIR can be used to enhance the ability of users to search and retrieve documents in many languages. Different type of translation techniques can be used to achieve Cross Language Information Retrieval. This paper describes the work done in CLIR and translation techniques for CLIR

Keywords: Query translation, Document translation, CLIR, Machine translation, Dictionary

Abstract: Image denoising has become an essential exercise in medical imaging especially the Magnetic Resonance Imaging (MRI).� In the proposed method noisy image is first decomposed into sub-band by wavelet transform and the nonlocal means filter is applied to each sub-band. This proposed method preserves the wavelet coefficients corresponding to the structures, while effectively suppressing noisy ones. Experimental results are also compared with the other different techniques like median, wiener, wavelet, wavelet based wiener, non-local mean. The quality of the output images is measured by the statistical quantity measures such as peak signal-to-noise ratio (PSNR), signal-to-noise ratio (SNR) and Mean square error (MSE) .The quantitative and the qualitative measures used as the quality metrics demonstrate the ability of the proposed method for noise suppression.

Keywords: Denoising, Wavelet, MRI, Wiener filtering, NLM.

Abstract: Speech recognition technology has been a multi-disciplinary research area since many decades and it found wide range of applications in many areas. Speech analysis can be done in time and frequency domain. In this paper, different techniques for speech analysis (feature extraction) such as short time Fourier transform, linear predictive coding, Mel Frequency cepstral analysis etc. are discussed. Also different methods for automatic speaker recognition also have been discussed. Thus this paper gives a technological review on methods involved in feature extraction and automatic speaker recognition implemented so far.

Keywords: Linear Predictive Coding, Mel Frequency, Wavelet, Vector Quantization, Dynamic time warping, Hidden Markov Model, Artificial Neural Network, Support Vector Machine, Gaussian Mixture Model.

Abstract: Network management systems provides an integrated system for sharing device information across management applications, automation of device management tasks, visibility into the health and capability of the network, and identification and localization of network trouble. By using common centralized systems and network-inventory knowledge, a Network management system delivers a unique platform of cross-functional management capabilities that reduces network administration overhead. An element management system (EMS) consists of systems and applications for managing network elements (NE) on the network element-management layer (NEL) of the Telecommunications (TMN) model. The element management system's key functionality is divided into five key areas - fault, configuration, accounting, performance and security (FCAPS). Portions of each of the FCAPS functionality fit into the TMN models. This paper presents a service delivery platform which aims to develop an enterprise web application that manages these 4G network elements through various modules to meet the required Quality of Service (QoS) using RichFaces framework. RichFaces is an open source Ajax enabled component library for JavaServer Faces which allows easy integration of Ajax capabilities into enterprise application development.

General Terms

SDP - Service Delivery Platform

RAM - Resource Assurance Management

KPI - Key Performance Indicator

EMS � Element Management System

NEL � Network Element Management Layer

NE � Network Elements

TMN � Telecommunications model

FCAPS - Fault, Configuration, Accounting, Performance and Security

Keywords

Element management system (EMS), FCAPS (fault, configuration, accounting performance and security) JavaServer Faces (jsf), RichFaces, JavaEE, JBoss.

Abstract: The power consumption is a major concern these days for long operational life. Although various types of techniques to reduce the power dissipation has been developed. One of the most adopted method is to lower the supply voltage. Techniques based on replica circuits which minimize the effect of operating conditions variability on the speed and power. In this paper different static random access memory are designed in order to satisfy low power, high performance circuit and the extensive survey on features of various static random access memory(SRAM) designs were reported.

Keywords: SRAM, Delay, speed and area, stability, Power Consumption.

Abstract: This study examines the factors associated with the assessment of teacher's performance. To improve the teacher performance, good prediction of training course that will be obtained by teacher in one way to reach the highest level of quality in Teacher performance, but there is no certainty if there are accurately determine Teacher advantage and increase its efficiency through this session. In this case the real data is collected for teachers from the Ministry of Education and Higher Education in Gaza City. It contains data from the academic qualifications for teachers as well as their experience and courses. The data includes three years and questionnaire contains many questions about the course and length of service in the ministry. We propose a model to evaluate their performance through the use of techniques of data mining like association, classification rules (Decision Tree, Rule Induction, K-NN, Na�ve Bayesian (Kernel)) to determine ways that can help them to better serve the educational process and hopefully improve their performance and thus reflect it on the performance of teachers in the classroom. In each tasks, we present the extracted knowledge and describe its importance in teacher performance domain.

Keywords: Teachers� Evaluation, Educational Data Mining, Teacher Performance, Classification.

Abstract: This paper presents a survey on CMOS image sensors(CIS) based on active pixel sensors(APS). Due to its properties, the APS is used in low voltage, low power and its applications in portable imaging systems such as disposable cameras and on-chip autonomous security cameras are random access, faster readout and low noise with peripheral circuitry.

Keywords: CMOS image sensors(CIS),Active pixel sensors(APS),Digital pixel sensors(DPS),pulse width modulation(PWM).

Abstract: It is important to develop a �high-performance multiplier architecture to meet the requirements of real-time, low power, low cost and small area in different applications. Vedic multiplier is one such promising solution and its simple architecture coupled with increased speed forms an unparalleled combination for serving any complex multiplication computations. In this paper various types of Vedic sutras are discussed and extensive survey on features of the Vedic multiplier design were reported.

Keywords: Vedic multiplier, Vedic mathematics, high speed and low power.

Abstract: Wireless sensor networks are a current highly developed technology of networks and are employed in many application areas like in military for surveillance purpose. WSN gather data from sensor node and send it to another sensor node. Due to the distributed nature, restricted computing power, memory space and use in some sensitive application, security is a major problem, so security is very important to transfer the data from one node to another node. To provide security in this LiSP protocol is used. This paper include how much energy is consumed for secure communication between sensor nodes and base station. In this paper, encryption and decryption operation use the block cipher rather than stream cipher and key is used to create security protocol. Encryption algorithm contains two inputs, one is the user input another is the key. To produce lightweight security protocol dynamic key is used. In this paper dynamic key is generated by using different types of random number generator like RC4, Blum Blum shub and wichman random number generator. After that find out how much time and energy is consumed by this protocol. This paper contains protocol which provide secure and efficient data transmission withminimum energy and time consumption so it makes it harder and difficult to break the security of data.

Keywords: Wireless sensor networks, dynamic key, RC4, blum blum shub, whichman, encryption, decryption, one time pad, lightweight protocol.

Abstract: We describe data structures and an update strategy for e practical implementation of inverted indexes. The context of our discussion is the construction of a dedicated index engine for a distributed full-text information retrieval system but the results have wider applications. Retrieval operations require a single disk access per query term. The online update strategy guarantees the consistency of on-disk data structures. Index compression integrates smoothly.

Keywords: �NNquery, Inverted Index, Lucene, Elastic Search.

Abstract: In this paper, the effect of Hybrid Window parameters CG, ICG, ENBW and SL on the SNR values of the MST radar is computed. The six parts of multibeam observations of the lower atmosphere made by the MST radar are utilized for the analysis of results. Prior to the Fourier transformation, the in-phase and quadrature components of radar echo samples are weighted with Hybrid Window functions. It is noted that the increase of adjustable shape parameter �α� of Hybrid windows increases ENBW and SL but decreases the CG and ICG. It helps to improve the SNR of MST radar return samples. Thus it is reported that the �α=6� can be suggested for good results of SNR improvement in MST radar return signals. The optimum window parameters in turn yields optimum Kaiser-Hamming window function parameters are �CG=1.0382, ICG=1.5233, ENBW=1.4134, SL=0.829�, Cosh-Hamming window function parameters are �CG=1.0169, ICG=1.4888, ENBW=1.4397, SL=0.8343�,Hann-Poisson window function parameters are �CG=0.1487, ICG=0.0784, ENBW=3.5467, SL=0.9602� and Kaiser Window function parameters are �CG=0.4991, ICG=0.3660, ENBW=1.4695, SL=0.8410�.This relates to optimum main lobe width and side lobe attenuation to increase the� signal to noise ratio of MST radar noisy data.

Keywords: �Hybrid Windows, CG, ICG, ENBW, SL, SNR, DFT, Spectral Analysis.

Abstract: Modern application demands high throughput and scalability. Achieving high level of throughput and scalability requires deploying applications in computer grids. But this results in intensifying database bottlenecks. Infinispan is a key/value NoSQL data store and it is a data grid solution written in Java. �Infinispan is exceptionally quick even when it deals with a large number of concurrent accesses. Infinispan have an end point called REST endpoint that uses http/web standards for providing services. If you want to connect to Infinispan data grids from non java clients, REST is the solution. Data inserted into the grid is replicated and can be accessed by client application from nearest location. The Open Data Protocol (OData) is an alternative endpoint. It was developed for querying and updating data. OData protocol is built upon technologies like HTTP, Atom Publishing Protocol (AtomPub) and JSON. Accessing Infinispan data store from a wide range of applications is possible using OData protocol. Combining the features of Infinispan and OData provides a distributed cache that is having features like scalability, availability and open access to data.

Keywords: Infinispan, OData, NoSQL, Data grid, REST

Abstract: In MANET routes between nodes changes regularly due mobile nature of all network nodes. It is always challenging task to discover an optimal path. Due to change in network topology some parameters are also effected like network delay, packet drop and throughput etc. There are basically three categories�� of protocols are reactive, proactive and hybrid. But reactive protocols have wide popularity in this field and provide solution to overcome problems (change in parameters) related to adhoc network. This paper evaluates behaviour of reactive protocols (AODV, DSR) using remote login type traffic in MANET. In this paper some parameters like network delay, total packet drop, network load and throughput are calculated with help of OPNET Modeller 14.5.

Keywords: OPNET, MANET, AODV, DSR and Remote login

Abstract: In this paper we present a comprehensive review of text recognition techniques. Character recognition has gained lot of attention in the field of pattern recognition due to its application in various fields. In coming days, character recognition system might serve as a key factor to create paperless environment by digitizing and processing existing paper documents. We believe that the review should prove helpful in identifying and solving problems that are being faced in developing a practical system.

Keywords: Text recognition techniques, Categories , Text Recognition, Segmentation, OCR, ACR, HCR

Abstract: This paper proposes an adaptive framework for a Knowledge Based Intelligent Clinical Decision Support System for the prediction of schizophrenia which is one of the most deadly illnesses that has a monumental effect on the health of people afflicted with it and has for long remained a persistent health problem affecting a significant number of people all over the world. In the framework the patient� information is fed into the system; the Knowledge base of the system stores all the information to be used by the Clinical Decision Support System and the classification algorithm selected after an exhaustive evaluation of relevant classification algorithms for this work is the C5.0 Decision Tree Algorithm with its percentage of correctly classified instances given as 78.4534%; it searches the Knowledge base and matches the patient information with the related rules that match with each case and thereafter gives the� most precise prediction as to whether the patient is likely to develop schizophrenia or not. This approach to the prediction of schizophrenia provides a very reliable solution to the problem of ascertaining if a person is likely to develop this illness or is almost not susceptible to the ailment.

Keywords: �Schizophrenia, Clinical Decision Support System (CDSS), Medical Decision Support System (MDSS), Artificial Intelligence (AI), K Nearest Neighbor (K-NN), Decision Trees (DT), Support Vector Machine (SVM) and Sequential Minimal Optimization (SMO).

Abstract: This paper presents a new methodology for image encryption. The SCAN-CA based image security system �belongs to the stream cipher.� Its encryption is based on permutations of image pixels and replacement of pixel values. The permutation is done with SCAN pattern generated by the SCAN methodology. SCAN patterns are developed based on the encryption specific SCAN language, which has production rule to generate a different SCAN grammar. The SCAN grammar produces a variable length scan key which is used for image encryption with CA substitution. Image pixel values are replaced using the recursive Cellular Automata substitution. Cellular Automata are dynamical systems in which time and space are discrete. The proposed image encryption method is lossless and it uses a very large number of secret keys. The pixel value permutation is key dependent. Thus, this encryption system finds a great scope in the field of security in terms of, grammar based key generation, large key space with time and space.

Keywords: Image security, Stream Cipher,� SCAN methodology, Encryption and Decryption, Cellular Automata

Abstract: India is rapidly advancing in the technological space. With the growing population and increasing Smartphone penetration, India is going mobile and digital. Smartphone and internet is not just for the rich and wealthy but more users are becoming informed by getting access of mobile internet. E-governance is trying its level best to provide e-government services to citizens. But still there is need to reach these services to individual at their doorstep. So� the looking at the current mobile age there is need for transforming E-governance services to M-Governance ,which promise to bring the �anywhere-anytime-anybody� e-government service vision one step closer. This paper presents an current scenario of mobile usage and Smartphone penetration in India. Information on the� current M-Government services and Which e- government services can be transformed to M-Government for a� powerful and transformational capacity to extend access to existing services, to expand the delivery of new services, to increase active citizen participation in government operations and to change the way of working within the public sector.

Keywords: E-Government, Mobile government, G2C, G2E, G2G.

Abstract: In this era of internet, the Online Social Networks (OSNs) are the platform to build social relations among people who share interests, activities, backgrounds or real life connections. OSNs have gained a ubiquitous status and this has led to security issues of posting unwanted messages on user wall. Therefore, in order to make the OSN user wall a secured wall, we are introducing a flexible- rule based system which provides users to control the messages that are posted on their walls and allows user to customise the filtering criteria to be applied on their walls. This system exploits machine learning based soft classifier for automatically labelling messages in support of content based filtering.

Keywords: Online Social Networks, Flexible-rule based system, filtering criteria, Machine � learning based soft classifier, content based filtering.

Abstract: This paper addresses the optical flow analysis and the smoothing effect in Local and Global Differentiation. There are lots of Local and Global methods and their variants available. But in this paper, as a prototype of local methods least-square fit of Lucas and Kanade has been employed, while the Horn and Schunck approach has been considered as the representative for a global method. Each of these methods has their advantages and shortcomings. Which are mentioned in their respective section. As a consequence, the proposed made from the hybridization algorithm incorporates the advantages of both field and possess less disadvantages. Improvement is made in our algorithm using the spatio-temporal approach and appropriate differentiation approximation

Keywords: Optical flow, combined local global method, Spatio-temporal optical flow.

Abstract: �In today�s world there is huge amount use of workstation particularly for web submission. Most of the people do their transaction through web use. So there are chances of personal figures gets hacked then �need to be provide more refuge for both web server and database server. For that purpose double guard system is used. The double guard system is used to indentify & prevent attacks using Intrusion detection system. Double Guard prevents attacks and prevents user account from intruder from hacking his/her account. By using IDS, system can supply security for both database server and web server using map of demand and query. An IDS system that model the network actions of user sessions across together the front-end web server and the back- end database.

Keywords: Session, Session Id, Query String, Ids.

Abstract: A simple technique to secure quantum key distribution relay networks is presented here. The paper introduces the concept of logical channels that uses a random dropout scheme. The paper also presents an enhanced protocol for key distribution in the relay networks. Previous techniques relied on creating distinct physical paths to create shares. Hence the compromise of one relay must compromise the entire channel. The concept of logical channel ensures that an attacker must compromise all the relays in order to access the key.

Keywords: Quantum cryptography, Quantum Key Distribution, Relay networks, Random dropout

Abstract: Now-a-days, many major e-commerce Websites are using recommendation systems to provide relevant suggestions to their customers. The recommendations could be based on various parameters, such as items popular on the company�s Website; user characteristics such as geographical location or other demographic information; or past buying behavior of top customers. In this paper, a book recommendation engine is proposed which uses data mining techniques for recommending books. The proposed recommender system will give its users� the ability to view and search books as well as novels which will be used to draw out conclusions about the stream of a user and the genre of the books liked by that user. The system will analyze the user behavior by using the features of various recommendation techniques such as content based; collaborative and demographic. Thus, in this paper a hybrid recommendation system is proposed which satisfies a user by providing best and efficient books recommendations.  

Keywords: Demographic Technique, Collaborative Technique, Content Based Technique, Recommendation Engine, User�s Interest.

Abstract: In today�s digital world information exchange is been held electronically. This transmission should provide efficiency in factors like transfer speed, cost, transmission errors etc. Image compression is minimizing the size in bytes of an image without reducing the quality of the image to an unacceptable level. It makes the transmission process faster, provides larger bandwidth and security against illicit use of data. This paper addresses the area of image compression as it is applicable to various fields of image processing. So Image compression is used to provide efficient transfer of data. This paper provides a basic introduction about image compression, and various types of image compression techniques.

Keywords: Image, Image compression techniques, Data redundancies, Compression ratio, Coding redundancy, Inter pixel redundancy

Abstract: In this paper, we have presented an overview of the concepts of big data and big data analytics. Furthermore the various types of data analytics have been discussed and popular tools being currently used for data analytics have been comprehensively explained. Lastly we have presented a tabular view of the comparison of the tools on numerous parameters. ��

Keywords: Big data, Data analytics, Analytics tools.

Abstract: Need of wireless sensor network (WSN) is increasing in various application areas. Resource restricted Traditional WSN is not able to satisfy this increase in demands. Many WSN is using unlicensed band (ISM band) so this band become overcrowded. Cognitive radio in WSN with opportunistic behavior and dynamic spectrum access can satisfy increasing demands and utilized spectrum bands effectively and efficiently. In this paper detail study of Cognitive Radio Sensor Network (CRSN) with architecture, hardware structure and challenges are explored.

Keywords: cognitive radio, dynamic spectrum access, spectrum sensing.