The system describes new similarity-based genetic algorithm (GA) and thresholding Strategies (R&SCut variants). GA was designed to give appropriate weights to terms according to their semantic content and importance by using their co-occurrence information and the discriminating power values for similarity computation.  After investigating the existing common thresholding strategies,  design multi-class text categorization in which documents may belong to variable numbers of categories.The proposed System conducted extensive comparative experiments on two standard text collections (the Reuters-21578 and the 20-Newsgroups). The experimental results using a standard evaluation method, F1, for micro and macro-averaged performance. The results show that GA and R&SCut variants work better than other widely used techniques.

Mobile Adhoc Network (MANET) consists of a  collection of wireless mobile hosts without the required intervention of any existing infrastructure or centralized access point such as base station. The dynamic topology of MANET allows nodes to join and leave the network at any point of time. Wireless MANET is particularly vulnerable due to its fundamental characteristics such as open medium, dynamic topology, distributed cooperation and constrained capability. So security in MANET is a complex issue. There are many routing protocols that establish the routes between the nodes in the network. The control towards the management of the nodes in the MANET is distributed. This features does not give assurance towards the security aspects of the network. There are many routing attacks caused due to lack of security.  In this paper, therefore, we attempt to focus on analyzing and improving the security of one of the popular routing protocol for MANET viz. the Adhoc On Demand Distance Vector (AODV) routing protocol. Our focus specifically, is on ensuring the security against the Blackhole Attack. The proposed solution is capable of detecting black hole nodes in the MANET at the initial stage itself. The simulation study is performed using Network Simulator NS-2.34.

 

Intrusion Detection System (IDS) in computer technology is a little bit different than physical intrusion detection system, which detects any physical changes in the protected premises. In computer technology, IDS is used to examine all traffics and activities either in computer unit or network. These IDS could be old technology systems, which we refer in this paper as traditional Intrusion Detection System  (tIDS), or it could be an intelligent system based on AI, machine learning, data mining and other intelligent techniques. In tIDS, which based on errors detection, the system works according to its database. This database is usually predefined by security experts. IDS is used to classify suspicious behaviors as intrusion acts or regular activities. Experts update the database manually [1]. Thus, it is hard to keep track of every single update and hard to analyze an event as a suspicious act with acceptable efficiency and satisfaction. So the need for automated tools became immanent to support security experts. Such a support could be achieved using data mining techniques as one of the possible ways to automate the system. This may handle the problem with high degree of accuracy.
This paper demonstrates the advantage of using data mining techniques in IDS. The system depends on users’ behaviors in order to extract features and then generate rules. The generated rules will be used as a pattern recognition tool. These rules enable the system to classify any irregular activity as an intrusion act.. In this research we hypothesize that, depending on time of a day and location of the activity in the database we could classify a suspicious behavior as an intrusion acts. The experimental results show high level of accuracy, efficiency, robustness where the system can handle errors, scalability where we can use the system in large number of users as well as reliability as the system shows 0% error rate of this technique

This paper proposes a new method of Visual Secret Sharing using Zigzag Scan approach. Non-expanded shares are generated by this scheme. This overcomes the drawback of Hilbert Curve approach, that is, the input should be a square image of size which is an integral power of 2.

Abstract-Although information security is critical for organizations to survive, a number of studies continue to report incidents of critical information loss. To this end, there is a continuous interest to study information security from a non-technical perspective. In doing so, this research focuses on organizational culture and commitment to e-banking security development and management. Even though considerable work has been done in banks in adopting e-banking security, continuous vigilance and management will be essential as the scope of e-banking increases. Two questions motivated this research. First, what is the possible relationship between organizational culture and commitment in e-banking adoption? Second, what is the effect of these organizational perspectives to the success in e-banking security adoption? A case study approach was used to investigate culture and commitment in e-banking security adoption at three banks in Greece. The results have shown that there is indeed a positive interrelation between organizational culture and commitment in e-banking security adoption and this interrelation affects positively e-banking security development through: e-banking project alignment, support from top management, information transparency, project flexibility, e-banking security knowledge and awareness, availability of resources and effective alignment of technology-organizational processes. The paper concludes that banks may need to re-consider their approach to e-banking adoption in favour of the long-term benefits it offers. 

 

Image segmentation denotes a process of partitioning an image into distinct regions. A large variety of different segmentation approaches for images have been developed. Among them, the clustering methods have been extensively investigated and used. In this paper, a clustering based approach using a Self Organizing Map (SOM) algorithm   is proposed for medical image segmentation. This paper describe segmentation method consists of two phases. In the first phase, the MRI brain image is acquired from patient database. In that film artefact and noise are removed. In the second phase (MR) image segmentation is to accurately identify the principal tissue structures in these image volumes. A new unsupervised MR image segmentation method based on fuzzy C-Means clustering algorithm for the Segmentation is presented

Keywords—-Image analysis, Segmentation, HSOM,  Fuzzy C-Means, Tumour detection

 

In this paper the performance evaluation has been done for combinatorial code for different system and code parameters under noisy optical channel conditions for potentially increasing number of users for optical code division multiple access system. It has been observed that code weight and effective power from each user are two main factors to decide the system performance.
Keywords- Optical Code division Multiple Access (OCDMA), Optical Orthogonal Code (OOC), Phase Induced Intensity Noise( PIIN),Signal to Noise Ratio(SNR),Bit error Rate(BER).

The Worldwide Interoperability of Microwave Access (WiMAX) technology has become popular nowadays and has been receiving growing acceptance as a Broadband Wireless Access (BWA) system. Below 11 GHz frequency in its line-of-sight (LOS) and non line-of-sight (NLOS) conditions where it operates, WiMAX has potential success. For the deployment of WiMAX networks there are going to be a surge all over the world. In initial deployment of wireless network and cell planning estimation of path loss is very important. In this paper we explain the WiMAX propagation in LOS and NLOS environment.
Keywords: WiMAX, LOS, NLOS propagation

Medical images (X-ray, CT, MR or PET) of human organs are widely used in the everyday clinical praxis. The paper presents methods which allows the user to analyze, model and adjust the total knee contour detection procedure during a preoperative planning which eliminating the need of using expensive and sophisticated commercial software tools, which procedures are not familiar to the natural user, the surgeon. It has based on a observation which is affects the global saliency of the contour from the local context of a edges. Here we have  propose the scheme consists of first find the edge in which response all points in an image using gradient computation and in the second one adapted the edge response at a point by the response in its  border. Here we also apply the canny edge detection technique to present the results of implementing the scheme followed by a mask operation for the border manipulation. We have examined on a large set of images which is tested successfully. This scheme is computationally and qualitatively favorably in comparison with another human knee contour detector technique which is also based several influence. The proposed scheme can provides a little expenditure preprocessing step for high level tasks such shape based human knee contour detection.

 Keywords: Biological models, image analysis, reconstruction, Contour detection, Surround suppression, Human visual system.

This paper presents the designing of a rectangular microstrip antenna using Multi Layer Preceptron (MLP) neural network model. The model was trained for 40 set of input-output (length of patch-resonant frequency) parameters. The output error and time delay (no. of epochs) were optimized by changing the learning rate and momentum term. In case of testing the output of the present model (resonant frequency) is found in good agreement with theoretical results.
Index terms: MLP, microstrip antenna, neural network

This paper gives case study of   Vehicle Tracking System using GPS technology. The system presently available uses GSM technology for transmitting the information like Longitude, Latitude, Altitude and Speed through SMS /GPRS. It is having several limitations because of dependency on GSM service provider. The practical observations made on VTS are discussed here. Probable modifications in the present systems are suggested with addition of mobile Wi-Max and DGPS (Differential Global Positioning System). With DGPS, accuracy of positions will be around 1 to 3 meters and Wi-Max gives more bandwidth/ data rate of 3 Mbps or more, enabling transmission of video files. The system accuracy will be improved and the system is expected to function more efficiently and effectively. The modified VTS system may be effectively used for applications like Theft Tracking System, Electronic Parking system and curbing the crime along with its intended applications of positioning and navigation.

Keywords— Differential Global Positioning System (DGPS), General packet radio service (GPRS), Worldwide Interoperability for Microwave Access (Wi-MAX), Vehicle Tracking System (VTS).

A fabric defect is any abnormality in the fabric that hinders its acceptability by the consumer. Quality assurance of textile materials depends on the quality of a fabric when it is received as a roll. Even the most outstanding manufacturing methods cannot compensate for defective materials. Presently, the inspection is done manually after a significant amount of fabric is produced. The optimal solution would be to automatically inspect fabric as it is being produced to change process parameters automatically to improve product quality. In this paper, the problem of fabric defect detection using image distance difference algorithm is investigated. The approach is experimented and evaluated with a set of images of fault free and faulty images with satisfactory results. Experimental results confirm the reliable and reasonable defect detection ability of the proposed system.

Keywords- Fabric inspection, image distance difference algorithm, Quality assurance, region prop, threshold.

Fractal Image compression is a ground-breaking image compression technique in the area of image processing. This technique is based on fractals rather than pixels.  It is   advantageous in compression ratio, decompression speed, bit-rate and resolution independence. But in conjunction with above advantages, the encoding phase of this technique consumes huge time, which is a major drawback and restricts its area of applications. A lot of theories have been proposed to overcome this limitation.  This paper represents a study of Kick-Out Condition based speedup techniques in fractal image compression.
Index Terms—Fractal image coding, zero contrast, conventional full search, kick-out rule, DCT inner product, normalized one-norm.

Wireless sensor networks afford a new Opportunity to observe and interact with physical Phenomena at an unprecedented fidelity. To fully realize this vision, these networks have to be self-organizing, self healing, economical and energy-efficient simultaneously.  Since the communication task is a significant power consumer, there are various attempts to introduce energy awareness within the communication stack. Node clustering, to reduce direct transmission to the base station, is one such attempt to control energy dissipation for sensor data gathering. In this work, we propose an efficient dynamic clustering algorithm to achieve a network-wide energy reduction in a multihop context. We also present a realistic energy dissipation model based on the results from stochastic geometry to accurately quantify energy Consumption employing the proposed clustering algorithm for various sensor node densities, network areas and transceiver properties.

Index Terms—wireless sensor network, clustering, energy efficient, stochastic geometry.

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The importance of wireless communication is increasing day by day throughout the world due to cellular and broadband technologies. Everyone around the world would like to be connected seamlessly anytime anywhere through the best network. The 4G wireless system must have the capability to provide high data transfer rates, quality of services and seamless mobility. In 4G, there are a large variety of heterogeneous networks. The users for variety of applications would like to utilize heterogeneous networks on the basis of their preferences such as real time, high availability and high bandwidth. When connections have to switch between heterogeneous networks for performance and high availability reasons, seamless vertical handover is necessary. The requirements like capability of the network, handover latency, network cost, network conditions, power consumption and user’s preferences must be taken into consideration during vertical handover. In this paper, we have extracted the requirements of a vertical handover from the literature surveyed. The evaluation of the existing work is also being done on the basis of required parameters for vertical handover. A sophisticated, adaptive and intelligent approach is required to implement the vertical handover mechanism in 4G wireless networks to produce an effective service for the user by considering dynamic and non dynamic parameters.

Index terms: 4G wireless networks, VHO, Requirements, RSS, Parameters, Performance

To reach more  rapidly from one point to another point in a particular network, Surely we must choose the shortest path from several directions .but usually shortest path has problems such as Traffic, damage, ….  .Thus, the node can’t reach to particular target with high speed. Due to the above problems, It  takes more time to reach to goal point rather  other long paths that reach  to goal point.To solve this problem we should bypass the  traffic.To bypass traffic at any moment, the status of nodes, different routes, and node points and other nodes are compared ,then The best route is selected. For inform from the status of nodes at any moment , the GPS system can be used.using  Satellite Systems is another way to know the status of a node.To solve the mentioned  problems , We propose a method that use Dedicated wireless system that with Using the equipment, the information is passed from node to server.After transferring data to the server, it  should be analyzed to determine the shortest path and the node will aware of the path.for analyze the information the Petri graph is used.
Keywords-node, path, traffic, transfer,  Information

Many natural phenomena show that  objects often exhibit some degree of regularity in their movements. However, previous works focus on finding the movement patterns of each single object or all objects. In this paper, we propose an efficient distributed mining algorithm to jointly identify a group of moving objects and discover their movement patterns in wireless sensor networks. As the movements of an object are regular, the object’s next location can be predicted based on its preceding locations. We  model the regularity by using the Variable Length Hidden Markov Model (VLHMM). If a pattern occurs more frequently, it carries more information about the movements of an object. To find out these information patterns, we first define the pattern as a significant pattern by adapting a Prediction Suffix Tree (PST) with improved smoothening factor. Our distributed mining algorithm comprises of Group Trajectory Mine (GTM) and Cluster Ensemble (CE) algorithms. In GTM, we propose a new similarity measure known as minkowski, which is used to compute the similarity of moving objects. In CE phase, our algorithm combines the multiple local grouping results which come from the GTM algorithm. We further leverage the mining results to track moving objects efficiently.
Keywords --- Distributed Clustering, Similarity measure, Object Tracking, WSN, Prediction Suffix Tree

This paper proposes and implements a low cost object tracking system using GPS and GPRS and GIS. The system allows a user to view the present and the past positions recorded of a target object on Google Map through the internet. The key features of the system are an open-source GIS platform, HTTP protocol, A web application is developed using PHP, JavaScript, Ajax and MySQL with the Google Map embedded and a communications server, a web-server, a database server, and a map server. The Monitoring Centre displays the above information on Google Map by means of Internet and sends commands to all the subsystems. The real time availability of all exact locations and speeds of the vehicles enables the system to encompass very clear traffic information
Keywords: GPRS, GPS, GIS, HTTP

This paper investigates the benefits of successive interference cancellation based detectors over linear detectors. low-complexity MIMO receiver with SIC,is simulated using two different modulation schemes namely BPSK and 16 QAM modulation methods. The simulation results obtained at Signal processing lab show that  by combining SIC with MMSE or SIC with ZF provide better BER  performance characteristics than   normal receiver consisting simple MMSE or ZF respectively.

Keywords— Bit error rate(BER), Multiple Input –Multiple Output(MIMO),BPSK,16QAM,Zero Forcing(ZF),Successive Interference Cancellation(SIC),SNR.