Next generation wireless communications will likely rely on integrated networks consisting of multiple wireless technologies. Hybrid networks based, for instance, on systems such as WMAN and WLAN can combine their respective advantages on coverage and data rates. WLAN is provided in hotspots, places like coffee bars, airports, shopping centers etc. where the hotspots are covered by access points. As the mobile node moves, it may leave the current wireless network and enter another wireless network; vertical handoff should be taken to the new network so as to maintain the current connection. Existing methods require more time for the vertical handoff process, which causes serious problems for multimedia applications. Vertical handoff delay should be minimum to have seamless vertical handoff communication. To achieve seamless handoff communication a Layer2 handoff method is proposed. In this method, a mobile with two radios of dual-mode capability, and WLAN having the extended region capability is used. The second interface is switched between 802.16 and 802.11 to know ahead to which network it is about to enter. Mobile node comes to know about its nearby network before actually entering the network, thereby reducing vertical handoff delay, making it suitable to seamless vertical handoff Communication.

Keywords-Horizontal handoff, Vertical handoff, IEEE 802.11, WiMax.

Image compression is an important task in medical imaging system and consists of mechanisms that reduce storage requirements while maintaining image quality. Medical image compression can be performed in a lossless or lossy fashion and a method that combines both is the Region of Interest (ROI) techniques. ROI techniques separate relevant and irrelevant details of an image and apply lossy technique to irrelevant part and lossless technique to relevant part. This paper proposes an enhanced active contour based ROI algorithm to separate the image as background and foreground. The foreground is compressed using a lossless JPEG algorithm and the background is compressed using an enhanced lossy JPEG algorithm that uses wavelet neural network followed by a post processing algorithm. Experimental results in terms of Compression Rate, Peak Signal to Noise Ratio and speed of compression show that the proposed scheme is an improved version when compared with the traditional algorithm.
Keywords – ROI based Compression, Enhanced Lossy JPEG Compression, Enhanced Active Contour Model.

Gene expression data usually contains a large number of genes, but a small number of samples. Feature selection for gene expression data aims at finding a set of genes that best discriminate biological samples of different types. Classification of tissue samples into tumor or normal is one of the applications of microarray technology. When classifying tissue samples, gene selection plays an important role. In this paper, we propose a two-stage selection algorithm for genomic data by combining some existing statistical gene selection techniques and ROC score of SVM and k-nn classifiers. The motivation for the use of a Support Vector Machine is that DNA microarray problems can be very high dimensional and have very few training data. This type of situation is particularly well suited for an SVM approach.  The proposed approach is carried out by first grouping genes with similar expression profiles into distinct clusters, calculating the cluster quality and the discriminative score for each gene by using statistical techniques, and then selecting informative genes from these clusters based on the cluster quality and discriminative score .In the second stage, the effectiveness  of this technique is investigated by comparing ROC score of SVM that uses different kernel functions and k-nn classifiers. Then Leave One Out Cross Validation (LOOCV) is used to validate the techniques.  

Key Words - Fisher Criterion, Golub Signal-to-Noise, Mann-Whitney Rank Sum Statistic, Leave One Out Cross Validation (LOOCV), Support Vector Machine(SVM).

Bluetooth provides a way to connect and exchange information between devices like personal digital assistants (PDAs), mobile phones, laptops, PCs, printers, digital cameras and video game consoles via a secure, globally unlicensed short-range radio frequency for multiple users simultaneously. This technology is developed to free end users to allow people access digital information wirelessly. Main idea of this paper is to show implementation for providing internet connection in Bluetooth enabled mobile using IGAP. IGAP is the new Bluetooth profile that solves the problem of accessing (browsing) internet in Mobile phone from a Computer having internet connection. With the IGAP a mobile user can access internet without any GPRS or EDGE provided by the telecommunication companies. This implementation has two parts, a client application and a server application. The server application runs in a normal PC with Bluetooth dongle. This PC acts as the gateway to the internet for the mobile. The mobile will host the client application which will connect to the server application in a hotspot environment and provide the mobile with internet access.
Keywords—IGAP, Bluetooth Hotspot, Bluetooth, Algorithm, Implementation of IGAP.

Every day an enormous amount of data is stored, processed and transferred digitally. Expenditure of these processes is very much related with amount of data. In order to minimize the processing cost if same information can be presented by reducing amount of bits. In case of image this can be achieved by image compression. In this paper an attempt has been made to present an approach of image compression using DNA sequence. Here two techniques have been presented which compresses an image by more than 99%.    

 

 

 

This paper presents the results of an experimental program conducted for evaluating the performance of corrosion damaged HSC beams strengthened with GFRP laminates. Five Beam specimens of size 150x250x3000 mm were caste and tested for the present investigation. One beam specimen was neither corroded nor strengthened to serve as reference. Two beams were corroded to serve as corroded control. A reinforcement mass loss of approximately 10 and 25% were used. The remaining two beams were corroded and strengthened with GFRP. The study parameters included first crack load, first crack deflection, yield load, yield load deflection, service load, service load deflection, ultimate load and ultimate deflection. Based on the results it was found that the UDCGFRP laminated beams showed distinct enhancement in ultimate strength and ductility.

Keywords—Corrosion, high strength concrete, strengthening, UDCGFRP laminates

 

Decision Trees are extensively used in classification, pattern recognition and Data Mining.  Classical decision tree building algorithms Iterative Dichotomiser 3 (id3) [3] uses one attribute to test at each internal node, resulting in the decision boundaries being parallel to the axis and builds the tree one node at a time. In this paper a new method is proposed where at each internal node a hyperplane is selected based on all attributes, this hyperplane partitions the training set into two disjoint sets. Our method also tries to build most of the tree in a single optimization problem. Genetic Algorithm is used as the optimization methods. The resulting tree using the proposed algorithm may be more compact and accurate in the classification problems.

Keywords : Decison Tree, Genetic algorithm, classifier, Optimization

 

This paper deals with the design of unbalanced power loading problem in a power distributed systems and optimal switching capacitor placement based on Extreme Learning Machine.  The recent studies reveal that the problem of optimal switching capacitors placement have been solved through various non-traditional optimization techniques,  which are less accurate and time consuming.  In this paper, we introduce Extreme Learning Machine (ELM) concept to design and implement an intelligent, automated ELM based switchable capacitor placement control unit. This control unit will periodically get the input from the feeders along with the other inputs called the power loss index and voltage.  Based on the power flow (unbalanced) and other calculations, this control unit will automatically determine the candidate sites and size of the capacitors to activate switchable capacitors dynamically. For quick decision making, the centralized control unit requires less computational time to evolve the site and size of the capacitors and it is achieved through ELM, because its computational time is comparatively less than  other methods.  Finally, the results are compared using a standard 70-bus test system with other models, with respect to the capacitor placement on the networks, savings and the computational time.  It is finally proved that the proposed model performs better than other models

Keywords: Optimal Capacitor Placement, Fuzzy Logic, Artificial Neural Networks (ANN), Particle Swarm Optimization, Fuzzy Expert Systems, Optimal power flow.

 

Cloud computing is one of the today’s most arising and needed technology and became popular for its flexibility, sharing resources, ease of maintenance, cost-efficiency etc., In very recent times, the cloud computing technology will have all its implementation in all ICT commodities and it became procurement model. In this paper, we characterize the problems in controlling the data and throw a keen limelight on the information security and various models that are proposed. Many existing research thrusts/systems has their own importance and same time drawbacks on maintaining the data security in cloud. The paper deals with much research advances in the area of data security concerns as information - centric security architecture over the cloud. The architecture deals for trusted computing, computation support encryption, advantageous of security over the cloud, which can be most benefitable in the vast area of Business Intelligence.

Keywords—Security, Information, Cloud Computing, Environment, Security Architecture

 

Text Document are tremendously increasing in the internet, the hierarchical document clustering has proven to be useful in grouping similar document for large applications.  Still most documents suffer from problems of high dimensionality, scalability, accuracy and meaningful cluster labels. In this paper an new approach fuzzy frequent itemsets based hierarchical clustering is proposed, in which fuzzy association rule mining algorithm is used to improve the clustering accuracy. In this approach firstly the key terms are extracted from the document set and each document is preprocessed into the document representation for the further mining process. Secondly, a fuzzy association rule mining algorithm for text is discover to find the sets, highly related fuzzy frequent itemsets, in which the key terms are regarded as a labels of the candidate clusters. Referring the candidate cluster it has been experimentally evaluated based on classic 30, Classic 4, and tr11 data sets for two methods FIHC and K-means in MATLAB 2009Rb.     
Keywords- Introduction, document clustering approach, document preprocessing, candidate cluster extraction,  F-measure evaluation.

 

Animal Husbandry has become an important source of income for millions of rural families and has taken an important role in providing employment and income generating opportunity. Indian Dairying shows few of the best Statistics. It ranks first with 185.2 million cattle & 97.9 million buffaloes accounting for about 51 percent of Asia’s and about 19 per cent of world’s bovine population. It also ranks first in milk production with a production of 100.9 million tons in 2006-07. Today, India has the world's largest dairy herd, and is second only to the United States in milk production.

Managing this immense number of animals is not an easy task. Often herds of cattle cross boundaries, lose direction and encroach into restricted areas. Also overgrazing is causing a serious problem of soil erosion. Construction of a real physical fence is too expensive and due to large and variable areas of grass lands, it is difficult too.

In order to overcome these shortcomings of traditional ways, we design a Virtual Fence in order to control and manage animals. This is done using sound and electrical stimulations.

 

 

This paper presents a new prototype framework of automated tracking and monitoring system for construction materials. Previous technologies such as RFID and GPS deployed in construction material tracking have been reviewed and signal strength-based localization has been examined. As an emerging network standard for industrial applications, brief specifications of ZigBee™ protocol have been described. We introduce a ZigBee-based tracking system architecture using hybrid techniques of RF and ultrasound to improve positioning accuracy and cost benefit. Finally, feasibility analysis and application scenario have been examined to present the possible deployment framework in construction area.
Keywords: ZigBee, sensor network, tracking, monitoring, construction materials, localization technique.

 

This project focuses on developing a software user interface using Matlab tools that will allow a user to easily execute C, C++ and assembly language code on a Texas Instrument DSP board (TMS320C6713). A signal processing description to be executed on this DSP board will first be implemented using either a Matlab M-file or Simulink block diagrams. The block diagram in Simulink is first converted to C code using the Real-Time Workshop feature in Simulink. The Code Composer Studio software package converts the C code into an executable file, which is downloaded onto the board and displayed on the oscilloscope.
 Keywords: - MATLAB, Simulink, TMS320C6713, DSP, RTW

 

This paper discusses research in developing general and systematic methods for intrusion detection and based on the classification elect the leaders in network for those are classified as high reliability. The key ideas are to use data mining techniques to discover consistent and useful patterns of system features that describe program and user behavior, and use the set of relevant system features to compute classifiers that can recognize anomalies and known intrusions. The performance of the classification algorithms is evaluated under different traffic conditions and mobility patterns for the Black Hole, Forging, Packet Dropping, and Flooding attacks. The obtained experimental results indicate that the Support Vector Machines exhibit high accuracy for almost all simulated attacks and that Packet Dropping is the hardest attack to detect.
Keywords: MANET, Classification algorithm, detection techniques.

 

Compressing and creating index to large database may result into time consuming. In Peer-to-peer framework, network may have millions of nodes, so creating index to large database requires number of index keys. To overcome this disadvantage and to simplify searching process we introduce QueSea algorithm. This algorithm first selects some part of network and then starts searching. In existing system, we have flooding and random Walk approaches to search multidimensional data, these approaches can be used in Peer-to-peer networks.

Key Terms: Searching Algorithm, performance analysis, multidimensional data management, indexing, compression