Information Technology and Mobile Communication

This paper proposes an adaptive Fuzzy rule based motion prediction algorithm for predicting the next instance position of a moving object. The prediction algorithm is tested for real-life bench-marked data sets and compared with existing motion prediction techniques. Results of the study indicate that the performance of the predictor is comparable to the existing prediction methods.

Checkpointing using message logging is a very popular technique for fault tolerance in distributed systems. The proposed protocol controls the lost messages, orphan messages and also simplifies garbage collection which is not available in most of existing protocols. In the protocol, all processes take checkpoints at the end of their respective smart interval to form a global consistent checkpoint. Since the checkpointing is allowed only within smart interval, the protocol will minimize various overheads like checkpointing overhead, message logging overhead etc.

The face recognition system is used to create a national database for the purpose of identity cards, voting in an electoral systems, bank transaction, food distribution system, control over secured areas etc. In this paper we propose the Face Recognition System using Discrete Wavelet Transform and Fast PCA (FRDF). The Discrete Wavelet Transform is applied on face images of Libor Spacek database and only LL subband is considered. Fast Principal Component Analysis using Gram-Schmidt orthogonalization process is applied to generate coefficient vectors. The Euclidean Distance between test and database face image coefficient vectors are computed for face recognition based on the threshold value. It is observed that the face recognition rate is 100% and the proposed algorithm for the computation of eigenvalues and eigenvectors improves the computational efficiency as compared to Principal Component Analysis (PCA) with same Mean Square Error (MSE).

Discovering association rules is one of the important tasks in data mining. While most of the existing algorithms are developed for efficient mining of frequent patterns, it has been noted recently that some of the infrequent patterns, such as negative associations and indirect associations, provide useful insight into the data. Existing indirect association mining algorithms mine indirect associations between items and require two join operations. But in this paper, we propose an algorithm for mining the complete set of indirect associations between pair of items and itemsets which require only one join operation.

An attacker produces a sequence of encrypted messages E, each of which has a distinct probability, however small, of decrypting into a valid message and also a probability of decrypting into an invalid message. The smallest modification that an attacker can make to the cipher-text and can still decrypt it correctly, gives information about the private key used to encrypt the message. In this paper we assume that the attacker knows or the gets hold of intermediate text which arises during the process of decryption.

Folding and Interpolating ADC have been shown to be an effective means of digitization of high bandwidth signals at intermediate resolution. The paper designs Folding and Interpolating ADC using cascaded folding amplifier to observe the effect of process variations. The primary circuit effects, resulted from process variations that are liable to degrade the performance of ADC are transistor mismatch, resistor mismatch and amplifier-comparator offsets. The device matching in reference generation, folding amplifier, interpolation and comparator offsets specify overall performance of ADC. Since the mismatches are random, Monte Carlo Analysis is used to estimate the linearity performance. In this paper the design is simulated using 0.35

μ

m, 3.3V to study the effect of process corners.

Image compression, in the present context of heavy network traffic, is going through major research and development. Traditional entropy coding techniques, for their high computational cost is becoming inappropriate. In this paper a novel near-lossless image compression algorithm had been proposed which follows simple tree encoding and prediction method for image encoding. The prediction technique uses a simple summation process to retrieve image data from residual samples. The algorithm had been tested on several gray-scale standard test images, both continuous and discreet tone, and had produced compression comparable to other state-of-the-art compression algorithms. The output compressed file sizes had shown that they are independent of image data, and depends only on the resolution of the image, an unique property that can exploited for networking bandwidth utilization.

Today’s Real Time System (RTS) is characterized by managing large volume of distributed data making real time distributed data processing a reality [1, 2]. The demand for real time data services is increasing in many large scale distributed real time applications. The transaction work load in DRTDBS may not be balanced and the transaction access pattern may be time varying and skewed. Hence, computation workload on large scale distributed system can lead to large number of transaction deadline misses [3, 4]. Hence, efficient database management algorithm and protocol for accessing and maintaining data are required to satisfy timing constraints of transaction supported applications. In this paper, an algorithm has been proposed for admission control in DRTDBS consisting of local controller and global load balancer working at each site, which decide whether to admit or reject the newly arrived transaction. The simulation results show that the new algorithm successfully balances the workload in DRTDBS [5, 6].

Image Registration is a fundamental task in image processing used to match two or more pictures taken, for example, at different times, from different sensors, or from different viewpoints. Image registration is particularly difficult when images are obtained through different sensor, (multi-modal registration). Mutual Information can be used for multimodal image registration. But this method has its own limitations one of it is of speed, method is very slow hence when time is an important constraint one cannot use this method. In this paper an attempt has been made to overcome this limitation.

60 GHz radio channel propagation characteristics in a typical indoor environment are addressed in this paper using a simple deterministic 2-Dimensional model utilizing ray-tracing technique based on geometrical optics (GO) and image principle. Values of the received power, rms delay spread (DS) and power delay profile (PDP) for horn, omni-directional and isotropic antennas are presented.

The back propagation algorithm calculates the weight changes of artificial neural networks, and a common approach is to use a training algorithm consisting of a learning rate and a momentum factor. The major drawbacks of above learning algorithm are the problems of local minima and slow convergence speeds. The addition of an extra term, called a proportional factor reduces the convergence of the back propagation algorithm. We have applied the three term back propagation to multiplicative neural network learning. The algorithm is tested on XOR and parity problem and compared with the standard back propagation training algorithm.

Orthogonal frequency division multiple access (OFDMA) is a emerging standard for broadband wireless access. Synchronization in OFDMA represents one of the most challenging issues and plays a major role in the physical layer design. Aim of this paper is to provide a overview of various frequency and time synchronization errors in OFDM systems. This paper also discusses the effect of timing and frequency errors on system performance. It focuses on time and frequency error estimation algorithms for OFDM based systems in downlink transmission as well.

The work “Cell-ID Based Vehicle Locator and Real-Time Deactivator Using GSM Network” (VLRD) uses GSM network for locating and real-time controlling on the vehicle by using the cell-id sent by guardian software and real time decoding of the encoded commands which are communicated through the circuit switched network. The system gets the command from the user and acts according to a pre-programmed set of instructions in real time to avoid the problems of delayed or undelivered commands in the existing system and improves the assurance of command execution. Removing the GPS usage can be reached through detecting the moments that Cell-ID is providing sufficient accuracy for the envisaged application.

The goal of future mobile communication systems will be to incorporate and integrate different wireless access technologies and mobile network architectures in a complementary manner so as to achieve a seamless wireless access infrastructure. To support this seamless user mobility across different wireless access technologies it is needed to design reconfigurable multistandard receiver architecture. This paper presents the system-level design of a wireless receiver’s baseband architecture, which supports two wireless access technologies: Wideband Code Division Multiple Access (WCDMA) and Orthogonal Frequency Division Multiplexing (OFDM). In this paper, efficient method of Fast Fourier Transform (FFT) algorithm for OFDM standard and Rake Receiver design for WCDMA standard were implemented. This architecture efficiently shares the resources needed for these two standards while reconfiguring. The proposed architecture is simulated using ModelSimSE v6.5 and mapped onto a Spartan 3E FPGA device (3s5000epq208) using the tool Xilinx ISE 9.2. Simulation results show that the proposed architecture can be efficiently reconfigured in run-time and proved as area efficient.

Two novel long tail pair based CCII are proposed in this paper. The first OTA CCII offer 1.98GHZ current transfer bandwidth and 10MHZ voltage transfer bandwidth. The second proposed design of CCII is independent against bias current variation. The second proposed design offer voltage transfer bandwidth of 10MHZ and current transfer bandwidth of 1.2GHZ with a very accurate voltage and current copy at corresponding x and Z nodes. The none idealities of first CCII are also measured using Spice simulation with TSMC 180nm model parameters.

Communication and concurrency are the major factors needed for the construction of a concurrent system. In concurrent environment systematic testing becomes a complex task. Generating test cases in concurrent environment is a difficult task because of arbitrary meddling of the concurrent thread. The interference of the concurrent thread may lead to a deadlock. In this paper we propose a methodology to generate the test cases for the conformance of deadlock in concurrent systems using UML State Chart Diagram. For system specification we have used the UML State Chart Diagram, from which event tree is generated. Along with a case study an algorithm is proposed to generate the test suite and confirm whether it is free from deadlock.

Most of the resource present in grid are underutilized these days. Therefore one of the most important issue is the best utilization of grid resource based on users request. The architecture of intelligent agent proposed to handle this issue consists of four main parts. We discuss the need and functionality of such an agent and propose a solution for resource sharing which satisfies problems faced by today’s grid. A J2EE based solution is developed as a proof of concept for the proposed technique. This paper addresses issues such as resource discovery, performance, security and decentralized resource sharing which are of concern in current grid environment.

A novel kind of miniaturized wideband patch antenna is designed and comparative analysis is presented. The antenna is having size of 2.1cm X 2.1cm X 1.25cm and patch is having area of 153mm

2

. Single or dual bands frequency response can be obtained by varying the feed location, height of the substrate and the geometric specifications of the antenna. This proposed antenna is very small in size although it provides good impedance behavior, return loss S11 behavior and VSWR which is very much nearer to 1 at each band. Bandwidths up to more than 56% can be obtained. Far-field radiation pattern and field distributions on the coaxial probe feed patch have been analyzed.

Anomaly based DDoS detection systems construct profile of the traffic normally seen in the network, and identify anomalies whenever traffic deviate from normal profile beyond a threshold. This deviation in traffic beyond threshold is used in the past for DDoS detection but not for finding zombies. In this paper, two layer feed forward neural networks of different sizes are used to estimate number of zombies involved in a DDoS attack. The sample data used to train the feed forward neural networks is generated using NS-2 network simulator running on Linux platform. The generated sample data is divided into training data and test data and MSE is used to compare the performance of various feed forward neural networks. Various sizes of feed forward networks are compared for their estimation performance. The generalization capacity of the trained network is promising and the network is able to predict number of zombies involved in a DDoS attack with very less test error.

The lifting wavelet transform (LWT) is a recent approach to wavelet transform, and singular value decomposition (SVD) is a valuable transform technique for robust digital watermarking. While LWT allows generating an infinite number of discrete biorthogonal wavelets starting from an initial one, singular values (SV) allow us to make changes in an image without affecting the image quality much. This paper presents an approach which tries to amalgamate the features of these two transforms to achieve a hybrid and robust digital image watermarking techniques. Certain performance metrics are used to test the robustness of the method against common image processing attacks.

Nowadays phishing attacks are increasing with burgeoning rate which is highly problematic for social and financial websites.Many antiphishing mechanisms currently focused to verify whether a web site is genuine or not. This paper proposes a novel anti-phishing approach based on Dynamic watermarking technique. According to this approach user will be asked for some additional information like watermark image, its fixing position and secret key at the time of user’s registration and these credentials of particular user will be changed at per login. During each login phase a user will verify the authentic watermark with its position and decide the legitimacy of website.

In the current business scenario, with explosive growth of the amount of information resources available over the Internet and Intranets in any organization, the retrieval of the required information at the spot and time of requirement is very essential, for the effective performance of the organization, by reducing the process time and meeting customer satisfaction of meeting delivery schedule. When the number of document collection and users of the document go beyond an extent, an efficient search tool for the retrieving the information from the collection of documents becomes vital. Actual information retrieval means searching for keyword within documents. This study investigates the various stages of information retrieval, selection of best method for implementation at each stage and optimizing the solution using of genetic algorithm with different parameters. The method is tested with a training data of document collections, where more relevant documents are presented to users in the genetic modification. In this paper a new fitness function is presented in the genetic algorithm for appropriate information retrieval which is found to be efficient than other fitness functions.

Today the concept of Data Mining services is not alone sufficient. Data mining services play an important role in the field of Communication industry. Data mining is also called knowledge discovery in several database including mobile databases and for heterogeneous environment. In this paper, we discuss and analyze the consumptive behavior based on data mining technology. We discuss and analyze different aspects of data mining techniques and their behavior in mobile devices. We also analyze the better method or rule of data mining services which is more suitable for mobile devices. In this paper, we propose a novel DAM (Define Analyze Miner) Based data mining approach for mobile computing environments. In DAM approach, we first propose about the environment according to the requirement and need of the user where we define several different data sets, then DAM analyzer accept and analyze the data set and finally apply the appropriate mining by the DAM miner on the accepted dataset. It is achieved by CLDC and MIDP component of J2ME.

View selection is concerned with selecting a set of views that improves the query response time while fitting within the available space for materialization. The most fundamental view selection algorithm HRUA uses the view size, and ignores the query answering ability of the view, while selecting views for materialization. As a consequence, the view selected may not account for large numbers of queries. This problem is addressed by the proposed algorithm, which aims to select views by considering query frequency along with the size of the view. The proposed algorithm, in each iteration, computes the profit of each view, using the query frequency and size of views, and then selects from amongst them, the most profitable view for materialization. The views so selected would be able to answer a greater number of queries resulting in improvement in the average query response time. Further, experimental based comparison of the proposed algorithm with HRUA showed that the proposed algorithm was able to select views capable of answering significantly greater number of queries at the cost of a slight increase in the total cost of evaluating all the views.

Public key cryptography is widely used in the establishment of secure communication. An important issue in the use of public key cryptography is to ensure that a public key actually belongs to its owner. This problem is referred to as the key validation problem. One solution to this key validation problem is the centralized public key infrastructure (PKI) model ([1]). A second alternative is the decentralized Web of Trust model ([2]). In this model a user depends on digital certificate introduced by other users, who may be trustworthy or otherwise, to establish the binding between a public key and its owner. In this work we propose to model the trust relationship between users as weighted edges. We propose an algorithm to find trusted paths and thus validate public keys. The proposed algorithm is simple and has a low complexity both in terms of time and space.

In this paper, a novel architecture suitable for Field Programmable Gate Array (FPGA) implementation of an adaptive color image enhancement based on Hue-Saturation-Value (HSV) color space is presented. The saturation feedback is used in order to enhance contrast and luminance of the color image. The saturation component is enhanced by stretching its dynamic range. Hue is preserved in order to avoid color distortion. The adaptive luminance enhancement is achieved by using a simple arithmetic mean filter. An efficient architecture for histogram equalization is also developed in order to evaluate the performance of proposed algorithm. The algorithm is implemented on Xilinx Vertex II XC2V2000-4ff896 FPGA device. The pipelining and parallel processing techniques have been adapted in order to speed up the enhancement process. The experimental results show that the color images enhanced by the proposed algorithm are clearer, vivid and efficient.

The functions of transmembrane proteins are attributed by kinks (bends) in helices. Kinked helices are believed to be required for appropriate helix-helix and protein-protein interaction in membrane protein complexes. Therefore, knowledge of kink and its prediction from amino acid sequences is of great help in understanding the function of proteins. However, determination of kink in transmembrane

α

-helices is a computationally intensive task. In this paper we have developed signal processing algorithms based on discrete Fourier transform and wavelet transform for prediction of kink in the helices with a prediction efficiency of ~80%. The numerical representation of the protein in terms of probability of occurrence of amino acids constituted in kinked helices contains most of the necessary information in determining the kink location, and the signal processing methods capture this information more effectively than existing statistical and machine learning methods.

This paper presents a cascaded H-bridge multilevel boost inverter for electric vehicle (EV) and hybrid EV (HEV) applications implemented without the use of inductors. Currently available power inverter systems for HEVs use a dc–dc boost converter to boost the battery voltage for a traditional three-phase inverter. A cascaded H-bridge multilevel boost inverter design for EV and HEV applications implemented without the use of inductors is proposed in this paper. The proposed design uses a standard three-leg inverter (one leg for each phase) and an H-bridge in series with each inverter leg which uses a capacitor as the dc power source. Experiments show that the proposed dc–ac cascaded H-bridge multilevel boost inverter can output a boosted ac voltage without the use of inductors.

The enhancing bandwidth and size reduction mechanism that improves the performance of a conventional micro strip patch antenna on a relatively thin substrate (about 0.006

λ

), is presented in this research. The design adopts meandered patch structure. Introducing the novel meandered square patch, offer a low profile, broadband, high gain, and compact antenna element. The proposed patch has a compact dimension of 0.384

λ

× 0.384

λ

(where

λ

is the guided wavelength of the centre operating frequency). The design is suitable for applications with respect to a given frequency of 750-1100 MHz. The simulated bandwidth of the proposed antenna is about 39%.

Moving cast shadows are a major concern for foreground detection algorithms. Processing of foreground images in surveillance applications typically requires that such shadows have been identified and removed from the detected foreground.. It is critical for accurate object detection in video streams since shadow points are often misclassified as object points, causing errors in segmentation and tracking. Processing of foreground images in surveillance applications typically requires that such shadows have been identified and removed from the detected foreground. We have implemented a novel pixel based statistical approach to model moving cast shadows of non-uniform and varying intensity by modelling each pixel as a mixture of Gaussians and using an on-line approximation to update the model.

Active Queue Management is a solution to the problem of congestion control in Internet routers. The problem of congestion degrades the overall performance of Internet routers. As data traffic is bursty in routers with varying flows, burstiness must be handled intelligently without comprising the overall performance. A congested link leads to many problems such as large delay, unfairness among flows, underutilization of the link and packet drops in burst. In this paper, we propose an AQM scheme that considers the characteristics of queue length based AQMs and uses the flow information to increase the overall performance and to satisfy the QOS requirements of the network.

This paper shows that not every scan cell contributes equally to the power consumption during scan based test. The transitions at some scan cells cause more toggles at the internal signal lines of a circuit, which have a larger impact on the power consumption during test application than the transitions at other scan cells. They are called power sensitive scan cells. A verilog based approach is proposed to identify a set of power sensitive scan cells. Additional hardware is added to freeze the outputs of power sensitive scan cells during scan shifting in order to reduce the shift power consumption.

In this paper we propose a scheme for rate adaptive lossless distributed source coding scheme for wireless sensor network. We investigate the distributed source-channel coding of correlated sources when correlation parameter is not fixed or may change during sensor network operation. For achieving rate adaptability we propose the puncturing and extension of IRA code depending on the value of correlation between two sources and the quality of channel. In our scheme we need to transmit only incremental redundancy for decreased correlation or fall in channel quality to meet energy constraints and reducing computation cost.

This paper proposes a method for detecting the motion of a particular object being observed. The Motion tracking Surveillance has gained a lot of interests over past few years. The Motion tracking surveillance system is brought into effect providing relief to the Normal video surveillance system which offers time-consuming reviewing process. Through the study and Evaluation of products and methods, we propose a Motion Tracking Surveillance system consisting of its method for motion detection and its own Graphic User Interface. Various methods are used in Motion detection of a particular interest. Each algorithm is found efficient in one way. But there exits some limitation in each of them. In our proposed system those disadvantages are omitted and combining the usage of best method we are creating a new motion detection algorithm for our proposed Motion Tracking Surveillance system. The proposed system in this paper does not have its effect usage in office alone. It also offers more convenient, effective and efficient usage in home.

In this paper, we present ‘RTS-Mirror’, an attempt to transform the overall usage and functioning of rear vision mirror to an entire stage of compliance in accordance to the automated technology of rear mirror that will leverage the present technology of movement of the rear vision mirror by a joystick or rather by a human hold. ‘RTS-Mirror’ is an intelligent system running on RTOS that tracks the face of driver in real-time and will apparently adjusts the rear mirror in a contiguous synchronized manner. This project explores the use face tracking algorithm like Haar-Classifier cascade algorithm [3], [5], Lucas- Kanade algorithm [14], [15], and joystick mechanism of rear mirror can develop a fully automated digital Rear vision mirror.

Software Effort Estimation is the most important activity in project planning for Project Management. This Effort estimation is required for estimation of resources, time to complete the project successfully. Many models have been proposed, but because of differences in the data collected, type of projects and project attributes, no model has been proven successful at effectively and consistently predicting software development effort due to the uncertainty factors. The Uncertainty in effort estimation controlled by using fuzzy logic and the parameters of the Effort estimation are tuned by the Particle Swarm Optimization with Inertia Weight. We proposed three models for software effort estimation using fuzzy logic and PSO with Inertia Weight. The valuated effort is optimized using the incumbent archetypal and tested and tried on NASA software projects on the basis of three touchstones for assessment of software cost estimation models. A comparison of the all models is done and it is found that the incumbent archetypal cater better values.

Mobile Ad hoc routing is challenging issue due to dynamic and distributed nature of mobile nodes required frequent observed updations of node information to route the packets appropriately, there are several proactive and reactive routing methods and geographical hierarchical routing techniques to route the packets from source to destination effectively. Based on the characteristics of Mobile Ad Hoc Network (MANET) routing protocols the routing techniques should address the distributed, dynamic topology, periodic updates and physical security. We proposed a novel mechanism concentrating to minimize the existing DSDV routing limitations; it is originated from computational geometric concepts. Fortune’s Algorithm (Sweep line method) which address the characteristic complexities of MANET routing and representing the route information in binary search method which minimizes the searching for optimal route.

The Zone Routing Protocol (ZRP) is a hybrid routing protocol that proactively maintains routes within a local region of the network (which we refer to as the routing zone). Here, we describe the motivation of ZRP and its architecture also the query control mechanisms, which are used to reduce the traffic amount in the route discovery procedure. In this paper, we address the issue of configuring the ZRP to provide the best performance for a particular network, at any time. Through NS2 simulation, we draw conclusions about the performance of the protocol.

Multi-Channel transmitter Controller is designed on ARINC 429 Protocol. Its new architecture shows better performance and saves high percentage of total power i.e. static power and dynamic power. It is specially designed for providing a dedicated transmission link between processor and various equipments placed in aircraft by selecting the particular transmitter for transmitting the data to many equipments like Microwave Landing system, Tire Pressure Measuring Systems etc. Also, an efficient VLSI implementation of proposed system on PROASIC 3 plus ACTEL FPGA device is described.

Technology is proliferating. Many methods are used for medical imaging .The important methods used here are fast marching and fast level set in comparison with the watershed transform .Since watershed algorithm was applied to an image has over clusters in segmentation . Both methods are applied to segment the medical images. First, fast marching method is used to extract the rough contours. Then fast level set method is utilized to finely tune the initial boundary. Moreover, Traditional fast marching method was modified by the use of watershed transform.The method is feasible in medical imaging and deserves further research. In the future, we will integrate level set method with statistical shape analysis to make it applicable to more kinds of medical images and have better robustness to noise.

Time synchronization for wireless sensor networks (WSNs) has been studied in recent years as a fundamental and significant research issue. Time synchronization in a WSN is a critical for accurate time stamping of events and fine-tuned coordination among the sensor nodes to reduce power consumption. This paper proposes a reference based, tree structured multi-hop time synchronization service for WSNs in which sensor nodes synchronize by collecting reference points with reference to Root node of the logically constructed tree structure of the network. Proposed approach is lightweight as the number of required broadcasting messages is restricted to one broadcasting domain.

In recent time, routing remains a major concern in Mobile adhoc networks (MANETs) due to the mobility of nodes. In particular, the link stability remains a major concern in existing protocols. In this paper, we propose a Markov Chain based Cost Evaluation Metric (MCCE) which is an extension of existing WCETT metric with an enhancement of link stability. The proposed routing metric is capable of providing better link stability and higher packet delivery fraction than the other proposed metrics in this category.

The texture analysis plays an important role in image processing and image classification field. Texture is an important spatial feature useful for identifying objects in an image. The local binary pattern and entropy are the most popular statistical methods used in practice to measure the textural information of images. Here, we proposed new statistical approach for the classification of texture images. In this method, the local texture information for a given pixel and its neighborhood is characterized by the corresponding texture unit and the global textural aspect of an image is revealed by its texture spectrum. The proposed method extracts the textural information of an image with a more complete respect of texture characteristics.

IEEE802.11i is the standard designed to provide secured communication of wireless LAN. The IEEE802.11i specification contains WPA-GPG authentication protocol. It allows a wireless station to gain access to a protected wireless network managed by access point. This paper models the WPA-GPG authentication protocol by formal verification using CasperFDR and analyzes the output. A few attacks are found in this protocol. The specifications through which these attacks are found are presented.

The steganography is a covert communication to transfer confidential information over an internet. In this paper we propose Adaptive Steganography based on Covariance and Discrete Cosine Transform (ASCDCT) algorithm. The Average Covariance of the Cover Image (ACCI) is computed. The ACCI of 0.15 is considered as the threshold value. The cover image is segmented into 8*8 cells and DCT is applied to derive coefficients. The payload Most Significant Bits (MSBs) are embedded into the cover image based on ACCI and DCT coefficients. It is observed that the capacity, Peak Signal to Noise Ratio (PSNR) and security is better compared to the existing algorithm.

In the paper, the difficulty in image segmentation based on the popular level set framework to handle an arbitrary number of regions has been addressed. There is very few work reported on optimized segmentation with respect to the number of regions. In the proposed model, first the image is classified using type-2 fuzzy logic to handle uncertainty in determining pixels in different color regions. Grey scale average (GSA) method has been applied for finding accurate edge map to segment the image that produces variable number of regions.

The modern day software industry has seen an increase in the number of software projects .With the increase in the size and the scale of such projects it has become necessary to perform an accurate requirement analysis early in the project development phase in order to perform a cost benefit analysis. Software cost estimation is the process of gauging the amount of effort required to build a software project. In this paper we have proposed a Particle Swarm Optimization (PSO) technique which operates on data sets which are clustered using the K-means clustering algorithm. The PSO generates the parameter values of the COCOMO model for each of the clusters of data values. As clustering encompasses similar objects under each group PSO tuning is more efficient and hence it generates better results and can be used for large data sets to give accurate results. Here we have tested the model on the COCOMO81 dataset and also compared the obtained values with standard COCOMO model. It is found that the developed model provides better estimation of the effort.

Genetic Algorithms (GAs) are commonly used today worldwide. Various observations have been theorized about genetic algorithms regarding the mutation probability and the population size. Basically these are the search heuristics that mimic the process of natural evolution. This heuristic is routinely used to generate useful solutions for optimization and search problems. GAs belong to the larger class of evolutionary algorithms (EAs), which generate solutions to maximize problem solving by using techniques inspired by natural evolution, such as inheritance, mutation, selection, and crossover. In this paper we study of a simple heuristic in order to control the crossover probability of a GA. We will also explain how stress factors in on the crossover probability and why it is an important phenomenon in case of a GA and how it can be controlled effectively. Experimental results show that, for reaching lower probability from higher probability, we can get faster optimal solutions for any problem. These experimental values are derived by taking the values at the high probability and then slowly yet steadily decreasing them.

DTN is an emerging research area that takes a different approach to (inter)networking and allows working in stressed as well as in highly heterogeneous environments.DTN features a number of unique properties which make this concept applicable to challenging environments in which traditional communication paradigms would fail or perform poorly. In DTN intermediate nodes takes the responsibility to store-and-forward delivery as well as physical data carriage using deterministic and/or probabilistic routing. In this paper we present a comprehensive up to date survey of different routing protocols as well as perform qualitative comparison of different routing strategies with respect to important issues in DTN. Further we highlight some of the upcoming issues related to design of DTN routing strategy.

In this paper, MOSFET modeling for millimeter wave integrated circuits is discussed. High frequency MOSFET is built using BSIM3v3 as intrinsic core and the parasitics due to HF are designed as extrinsic subcircuit. The proposed methodology is then used in designing a low power, mm-wave CMOS low noise amplifier. The operation of the circuit is simulated using a circuit simulator. The wideband characteristics are verified by implementing the LNA circuit with and without composite model.

Next generation Business Intelligence web application development uses integrated and intensified technologies like Web 2.0 architectures, Agile Modeling, and Service-orientation (or Web Services). Applying Web Services Mining strategies to Agile Modeled Web architectures will eventually provide valuable insights to Business Intelligence users, Operational Business Decision makers, and more importantly Web application architects. These insights are important in maintenance of these developed applications and also in their scalability purposes. Our research focuses on applying Mining for Software (or Web) Engineering for designing dependable solutions for these integrated technologies, which will eventually improve the Web Engineering process in terms of architecture, its security, requirements etc. In this paper, we discuss about our Mining approach for Business Intelligence to improve insights of Web Engineering applications. We validate our approach with a suitable exemplar.

A continuous version of particle swarm optimization (CPSO) is employed to solve uncapacitated facility location (UFL) problem which is one of the most widely studied in combinatorial optimization. The basic algorithm had already been published in the Research Article “A Discrete Particle Swarm Optimization Algorithm for Uncapacitated Facility Location Problem” [1]. But in addition to that, the algorithm is slightly modified here to get better result in a lesser time. To make a reasonable comparison, the same benchmark suites that are collected from OR-library [6] are applied here. In conclusion, the results showed that this modified CPSO algorithm is slightly better than the published CPSO algorithm.

Evolutionary algorithms are used to obtain the optimal solutions for varieties of engineering problems. The performance of evolutionary algorithms can be enhanced by integrating them with local search methods. The idea is to combine the best of both global and local optimization approaches to perform a better exploration of search space. This paper presents a preferential hybrid evolutionary algorithm, where the gradient descent method is integrated into the NSGA-II. This new algorithm has been verified on a set of multiobjective benchmark problems using four different performance metrics. The results show that the proposed algorithm brings out the optimal solutions with better diversity and closeness to the known optimal solutions than NSGA-II and also consumes less time than traditional hybrid algorithm.

This paper discusses about the synergy of multi-agent coordination technique with different optimization techniques viz. integer programming optimization with Lagrangian Relaxation and a simple heuristic approach with experience based learning effect in case of patient scheduling problem. The objective is to achieve good reduction in waiting time of the patients in hospital while achieving better resource utilization. The proposed methods have been implemented in JADE and the results are compared with the traditional scheduling techniques. The performance of the proposed methods based on total weighted waiting time of the patient increases by 15% to 52% when compared to traditional scheduling techniques. The waiting time of the patient is further reduced by 5%, when experience based learning effect is incorporated. Optimization based on simple heuristic method shows that it gives near optimal solution with drastic reduction in the execution time ie. 90.84% when compared to integer programming approach.

World Wide Web has become the largest repository of information because of its connectivity and scalability. With the increase in number of web users and the websites, the need for website classification gains attraction. The website classification based on URLs alone plays an important role, since the contents of web pages need not be fetched for classification. In this paper, a soft computing approach is proposed for classification of websites based on features extracted from URLs alone. The Open Directory Project dataset was considered and the proposed system classified the websites into various categories using Naive Bayes approach. The performance of the system was evaluated and Precision, Recall and F-measure values of 0.7, 0.88 and 0.76 were achieved by this approach.

This paper proposes a new technique for the efficient selection of test cases from the large suite. The main aim of selection of test cases is that the fewer test cases may reduce the testing time and project cost. And also test case selection may increase a test suite’s rate of fault detection. An increased rate of fault detection during testing provides earlier feedback on the system under test, allowing debugging to begin earlier, and supporting faster strategic decisions about release schedules. Further, an improved rate of fault detection can increase the likelihood that if the testing period is cut short, test cases that offer the greatest fault detection ability in the available testing time will have been executed.

The main problem in a distributed cooperative mobile robots when they navigate to a target is that fixing the degree of freedom in movement for an individual robot without breaking the communication link with other robots. In this paper an agent based approach to intelligently coordinate the group members in a cooperative robots are done. Initial steps of optimized link state routing algorithm is used to get the information of other members. And a fuzzy based decision can be taken regarding the movement without breaking the communication link. So this technique ensure , each and every time all the robots are in communication with at least one robot in the group, at the same time system provides maximum degree of freedom for movement.

Low rate Denial-of Service, DoS, attack recently emerged as the greatest threat to enterprise VoIP systems. Such attacks are difficult to detect and capable of discovering vulnerabilities in protocols with low rate traffic and it noticeably affects the performance of Session Initiation Protocol, SIP, communication. In this paper, we deeply analysis the resilience of SIP server against certain low rate DoS attacks. For this purpose we define performance metrics of SIP server under attack and non-attack scenarios. The performance degradation under attacks gives a measure of resilience of the SIP server. In order to generate normal SIP traffic and the attacks, we defined our own XML scenarios and implemented them using a popular open source tool known as SIPp. The system under evaluation was an open source SIP server.

Stereo vision systems determine the depth from two or more images which are taken at the same time, but from slightly different viewpoints. A novel approach for depth map generation is proposed for a multi-window stereo algorithm on a cluster computing setup using Message Passing Instructions (MPI) to overcome the speed limitations.

Mobile ad hoc network(MANET) is the latest application of telecommunication. This is one of the most innovative and challenging area of wireless networking. Ant Colony Algorithm has been used in Mobile Network since long because of isomorphism between them. Pheromone graph and stigmergic architecture of ant colony algorithm are comparable with structure & constraints of communication network. In this paper, A literature survey about the application of ACO is given. In this paper we review ANT algorithm and different approaches proposed by researchers for the improvement of routing performance. In this proposed work, ACO will be used in case of link failure. Path will be discovered by reactive routing, and maintained by periodically generating HELLO messages by all the nodes in the link. All nodes in the link will also find an alternate route for next to next node proactively. By using this method, throughput, and end to end delay parameters can be improved probably the on the cost of increase in the overhead. Overhead will increases in proactive route finding at the same time number of route failure reduces so the bits required in alternate route finding will reduce.

MANET links have dependency on node mobility and node battery power causes degradation of network’s performance and it could be alleviated by allowing cross layer interaction in the protocol stack. In this paper Route Discovery by Cross Layer Routing Protocol (RDCLRP) is proposed for route discovery and route maintenance and AODV is modified. Instead of periodic hello message of AODV, non periodic hello warning message is used for route maintenance and route discovery in RDCLRP. HELLO warning message is used to give warning when link is going to break before link breakage when it touches the threshold and it is broadcasted whenever it is required and not periodically. With the help of Hello warning message new route can also be discovered before link breakage. In this paper only HELLO warning message interval is optimized with the help of fuzzy logic. This reduces overhead and power consumption, in turn it reduces delay in search of new route. The result illustrates the improvement of optimized RDCLRP over the basic AODV. Network performance such as throughput, delay, jitter, overhead and battery power consumption can be improved significantly with this method.

Fingerprints have always been the most practical and positive means of Identification. Offenders, being well aware of this, have been coming up with ways to escape identification by that means. Erasing left over fingerprints, using gloves, fingerprint forgery; are certain examples of methods tried by them, over the years. Failing to prevent themselves, they moved to an extent of mutilating their finger skin pattern, to remain unidentified. This article is based upon obliteration of finger ridge patterns .In this article, we propose a new classification algorithm GLCCM (

Gray Level Correlation Coefficient Co-occurrence Matrix

) algorithm for altered fingerprints classification. It is based on the fact that altered fingerprint image is composed of regular texture regions that can be successfully represents by co-occurrence matrix. So, we first extract the features based on certain characteristics and then we use these features for classifying altered fingerprints.

This paper proposes a new method of personal recognition based on footprints. In this basis method, an input pair of raw footprints is normalized, both in direction and in position. The foot image is segmented and its key points are located. The foot image is aligned and cropped according to the key points. The footprint image is enhanced and resized. Sequential Modified Haar transform is applied to the resized footprint image to obtain Modified Haar Energy (MHE) feature. The sequential modified Haar wavelet can map integer-valued signals onto integer-valued signals abandoning the property of perfect reconstruction. The MHE feature is compared with the feature vectors stored in database using Euclidean Distance. The accuracy of the MHE feature and Haar energy feature under different decomposition levels and combinations are compared. More than 88.37% accuracy achieved from the proposed MHE feature.

To increase the availability of data and fault tolerance in distributed database, it is better to add a backup server for each primary server in the system. So, the primary server and backup server must be connected to each other. To connect these computers to each other when they are at a long distance, it is necessary to use a leased line which needs to be charged as data is transferred. When packets are transferred between primary and backup server, more money need to be paid for charging this line. So if number of transferred packets between these computers can be reduced, the company can economize in its expenditures. Moreover, the number of transactions which should be performed in the backup server reduces.

In order to achieve this, a new method is introduced which will reduce the number of transferred packets between primary and backup server. In this method, the replicated data of primary server on other computers is used as its backup.

This position paper presents Quality of Service (QoS) routing model in Mobile Ad hoc Networks (MANETs) by using software agents that employ fuzzy logic and neural networks for intelligent routing. It uses Dynamic Source Routing (DSR) in MANETs to find various paths and attributes. Fuzzy static agents decide whether each node on the path satisfies QoS requirement for multimedia application. The static neuro-fuzzy agents are used for training and learning to optimize the input and output fuzzy membership functions according to user requirement, and Q-learning (reinforcement learning) static agent is employed for fuzzy inference instead of experts experience. Mobile agents are used to maintain and repair the paths.

This paper aims to compare performance of some routing protocols for Wireless Sensor Networks(WSNs). A Wireless Sensor Networks (WSN) is a set of hundreds or thousands of micro sensor nodes that have capabilities of sensing, establishing wireless communication between each other and doing computational and processing operations. The efficiency of sensor networks strongly depends on the routing protocol used. Routing protocols are needed to send data between sensor nodes and the base station. In this paper, we analyzed three different types of routing protocols: Fisheye, LANMAR, LAR1. Sensor networks were simulated using Qualnet simulator. Several simulations were conducted to analyze the performance of these protocols on the basis of performance metrices such as hop count, throughput, end-to-end delay.

A mobile adhoc network (MANET) is a network which does not have any centralized control. Security and trust management are paramount concern for these networks for efficient data transfer among the participating nodes. In this paper, we propose an efficient security and trust management based algorithm for MANET. The proposed algorithm consists of three steps: initialization, data transmission, and detection. The time based nonce is generated at different time interval which gives effectiveness to the proposed approach in the sense that it is not easy to detect the generated nonce. The proposed approach is quite effective with the earlier approaches to detect the security threat in MANET.

With ever increasing network traffic, distributed systems can provide higher performance using a typical dynamic load balancing (DLB) algorithm. Dynamic algorithm employs up to date load information of the nodes to make load distribution decisions and therefore, they have potential to outperform static strategies. In this paper, we illustrate the analytical comparative study of existing dynamic algorithms and result gives a thorough overview of various dynamic algorithms, helping designers in choosing the most appropriate approach for a variety of distributed systems. Moreover, researchers can use it as a catalog of available DLB schemes to come up with new design.

In this paper, a wavelet based electrocardiogram (ECG) data compression technique is reviewed. The method employs the discrete wavelet transform (DWT), thresholding, Huffman encoding followed by different quantization levels. A comparative study of performance at the different quantization levels and thresholding is made in terms of Signal-to-noise ratio (

SNR

), Percent root mean square difference (

PRD

) and Mean square error (

MSE

). The simulation results illustrates that good compression ratio can be achieved at lower quantization levels, while at higher quantization levels, all fidelity measuring parameters are enhanced.

In this paper, we propose an efficient technique for content based image retrieval which uses the local color and texture features of the image. Firstly the image is divided into sub blocks of equal size. The color and texture features of each sub-block are computed. Color of each sub-block is extracted by quantifying the HSV color space into non-equal intervals and the color feature is represented by cumulative histogram. Texture of each sub-block is obtained by using gray level co-occurrence matrix. An integrated matching scheme based on Most Similar Highest Priority principle is used to compare the query and target image. The adjacency matrix of a bipartite graph is formed using the sub-blocks of query and target image. This matrix is used for matching the images. Euclidean distance is used in retrieving the similar images. The efficiency of the method is demonstrated with the results.

Research, recent and old, payed much attention on reducing the cycle time and increasing the speed of execution of the processor. This lead to the development of multiple core processors that distribute and share load among the many processors. The important question to answer would be, will the shared cache technology for multi-core work as efficiently as it did for uni-core processors? Our analysis in this paper, takes into consideration the impact that caches have on a uni-core environment and in a shared multi-core environment. In order to demonstrate this we use: DINERO IV for analysing the performance of uni-core environment and CACTI (Cache Access Cycle Time Indicator) for analysing the performance of multi-core environment.

Currently, there is great urgency to reduce the cost of wireless telecommunication networks in order to minimize the number and cost of required facilities, and thus adds to search for optimal network designs. One such solution is optimal assignment of cells to switch in wireless telecommunication network. In this paper, we explored three basic wireless telecommunication networks, which share analogous network architecture namely Personal Communication Services (PCS), Cellular Mobile Network and Universal Mobile Telecommunication Services (UMTS). The optimal assignment problem is NP hard Complex Integer Programming problem. In this paper, we explored various issues like network architecture, formulation of objective function, constraints of objective function, algorithm used, optimization strategy, and intensification and diversification methods in algorithms.

Semantic Webservices (SWS) has raised interest in mechanisms for Ontological representation of Web Services. A number of mechanisms most notably WSMO and OWL-S are being developed to represent the same. An important area in description of Web Services is the QoS characterization and discovery which is the focus of research for this paper. A Domain Specific language is being proposed for definition of observable QoS characteristics and conditions. The syntax of this proposed language is being kept closer to WSML considering it the standard modeling language.

In the wireless network, security is a major concern. Bluetooth network is also highly vulnerable to attacks. This paper proposes a protocol called, Modified Auxiliary Channel Diffie Hellman Encrypted Key Exchange authentication Protocol (MACDHEKE), which authenticates the two previously unknown Bluetooth enabled devices. The user inputs a low security, low entropy pins and converts it into high security, high entropy shared key. It also authenticates the public key as being sent by the claimed sources or devices. It also analyzes how secure this protocol is against man in the middle attack as well as passive eavesdropping.

This paper presents a new methodology for the image segmentation and character recognition from standard Indian License number plates. This method first, gets input of the segmented characters that is partitioned by bilateral partitioning method, in which we eliminate similar part from the character and match it by judging template and return identified character. This partitioning may be performed horizontally or vertically. The characters are to be partitioned horizontally or vertically depend on their subgroup, and before this subgroup the characters are grouped on the basis of the number of holes in it. The subgroup is made on the basis of some similar features like | , / , \ , _ , ( , - , etc. Suppose we have alphabet T and I here similar portion is I than both will go to same subgroup and we partition it horizontally. This method eliminates the problem of confusion between similar looking elements like C, G and T, I, 1, J etc by exploiting the small but significant differences among them.

Data Clustering is a descriptive data mining task of finding groups of objects such that the objects in a group will be similar (or related) to one another and different from (or unrelated to) the objects in other groups [5]. The motivation behind this research paper is to explore KMeans partitioning algorithm in the currently available parallel architecture using parallel programming models. Parallel KMeans algorithms have been implemented for a shared memory model using OpenMP programming and distributed memory model using MPI programming. A hybrid version of OpenMP in MPI programming also has been experimented. The performance of the parallel algorithms were analysed to compare the speedup obtained and to study the Amdhals effect. The computational time of hybrid method was reduced by 50% compared to MPI and was also more efficient with balanced load.

As the network traffic is increasing exponentially, the queuing model used in a network decides the degree of congestion that is possible in the network infrastructure. Hence using a suitable queuing model based upon the network infrastructure like buffer size and the type of data traffic flowing through the network will help in better utilization of system resources by minimizing congestion to the best. In this paper, we study the different queuing models that have evolved over time and how they suit the application.

In Synthetic Aperture Radar (SAR) images, texture and intensity are two important parameters on the basis of which classification can be done. In this paper, 20 texture features are analyzed for SAR image classification into two classes like water and urban areas. Texture measures are extracted and then these textural features are further shortlisted using statistical approach, discriminative power distance and principal component analysis (PCA). In this study 30 SAR images are studied for 20 texture features. Finally, most effective 5 texture features are shortlisted for the classification of SAR images and accuracy is calculated by Specificity and Sensitivity test. The results obtained from test images give an accuracy of 95% for image classification.

WiMAX (Worldwide Interoperability for Microwave Access) is the IEEE 802.16 Standards based wireless technology that provides MAN (Metropolitan Area Network) broadband and IP connectivity. WiMAX is promising technology which offers high speed voice, video and data services based on OFDM. It offers both line of sight and non line of sight wireless communication. In this paper performance of WiMAX with different modulation (BPSK, QPSK and QAM) and coding is studied on the basis of Bit Error Rate, Signal to Noise Ratio and error probability.

When computational clusters increase in size, their mean time to failure reduces drastically. We generally use checkpoint to minimize the loss of computation. Most check pointing techniques, however, require central storage for storing checkpoints. This results in a bottleneck and severely limits the scalability of check pointing, while also proving to be too expensive for dedicated check pointing networks and storage systems. We propose a Stair-Case Replication (SCR) Based MPI check pointing facility. Our reference implementation is based on LAM/MPI; however, it is directly applicable to any MPI implementation. We use the staircase method of fault-tolerant MPI with asynchronous replication, eliminating the need for central or network storage. We evaluate centralized storage, a Sun-X4500-based solution, an EMC storage area network (SAN), and the Ibrix commercial parallel file system and show that they are not scalable, particularly after 64 CPUs. We use the staircase MPI method which allows the access point in a lower complexity level to the higher complexity level which improves the efficiency of the previous method.

Cloud computing has gained tremendous consideration recently. In the ‘Era of Tera’ when data sizes are continuously escalating and traffic patterns have become unpredictable; Cloud is a viable alternative for enterprises to serve their consumers with quicker response times. The businesses can rely on service provider to host their applications and can thus focus on their core competencies. However, a large number of Cloud providers have spurred up with their offerings. As the number of Cloud Computing players grows, the run time services provided to the cloud consumers act as key differentiators. In this paper, traditional applications are compared with Cloud applications and metrics relevant to the Cloud services have been identified. Further, the services of five major Cloud providers are compared for fundamental differences that exist in their offerings on the basis of these metrics.

The enormous amount of XML data growing on the Web raises several security issues that current XML standards do not address. The most important security issue in such a distributed environment is the lack of efficient Access Control and authorization for XML data currently. In this paper, we propose a generalized Role Based Access Control (RBAC) model called An Intelligent Agent Based Temporal Action Status Access Control (IATASAC) model which uses temporal and action status constraints for efficient access control. This model addresses certain shortcomings of RBAC model by the use of semi structured data; hence it is more suitable for distributed web environment. Since the proposed model has been developed for XML data and needs smart decision, it heavily relies on XPath and intelligent agents for effective querying and answering. The Experimental results show that the proposed model performs well.

Recently, strategic behavior modeling has attracted much attention of the researchers focusing on designing protocols in the area of social networks. The motivation lies in the fact that the overlay peers of the social networks are selfish in nature and they typically belong to different administrative domains. In this paper, we model the strategic behavior of the selfish peers by leveraging the rich theory of mechanism design using the concept of economic auctions. By considering the bandwidth of the service offered by the origin server as the commodity, we design dynamic auctions in which downstream peers submit their value of bids for each commodity at the upstream peers.

Microsoft Exchange Server supports the deployment of Exchange in a manner that distributes server tasks among front-end and back-end servers. This work includes messaging services such as “

E-Mail”

, “

DiscussionForum”

, “

SearchEngine”

, “

NewsLetters”

, “

GuestBook”

and “

ClassifiedAdverts”

. The E-Mail service that embeds “Exchange Server” as Back-End acts as the primary messaging service. Microsoft Exchange Server supports the deployment of Information exchange that distributes server’s tasks among Front-End and Back-End servers. Front-End server accepts requests from clients and proxies them to the appropriate Back-End server for processing, to optimize the Front-End and Back-End servers using virtualization technology. The Authorized Users are allowed to utilize the messaging services and special authorization is made when the user wishes to join the E-Mail service. After receiving a request, the front-end server uses LDAP (

L

ightweight

D

irectory

A

ccess

P

rotocol) to query the Windows 2003 server Active-Directory-service and determine which back-end server holds the requested resource. This topology reduces complexity.

This paper describes an efficient Blind Source Separation of speech and music, speech and music which are considered as convolutive mixtures. The convolutive mixed signals consist of source signals and same amount of delay or echo of the same source signal. Convolutive BSS of stereo mixtures is the challenging task in the audio signal processing application.BSS is a technique for estimating original source signal from their mixtures of signals. The mixed signals were decomposed by 1D multilevel discrete wavelet decomposition. Decomposition levels are changed and the signals to noise ratio (SNR) are calulated.After that ICA has been performed and the sources are separated.

This paper presents an efficient, digital audio watermarking method based on one dimensional multilevel discrete wavelet transform(MDWT) and discrete cosine transform (DCT) for the application of copyright protection. The proposed scheme also employs informed source separation for the watermark extracted audio signal based on independent component analysis (ICA).In addition, the performance of the proposed algorithm in terms of Signal to Noise Ratio (SNR), Peak Signal to Noise Ratio (PSNR) and Normalized Root Mean Square Error (NRMSE) are also evaluated. The proposed scheme achieved good robustness against most of the attacks such as requantization, filtering, addition and multiplication of noise. The experimental result shows that the SNR value is about 36.12dB for the proposed algorithm, whereas by using only MDWT technique method gives only 30.2dB.

A content based image retrieval system allows the user to present a query image in order to retrieve images stored in the database according to their similarity to the query image. Content based image retrieval method is used as diagnosis aid in medical fields. In this paper content based image retrieval is used for medical applications. The main objective of this paper is to evaluate the retrieval system using Textural features. The texture features are extracted by using wavelet transform. The method is evaluated on Diabetic Retinopathy Database (DRD). Here the precision rate obtained is about 60% for DRD images.

This paper proposes a watermarking scheme for intellectual property (IP) identification based on testing in soc design. The core concept is embedding the watermarking generating circuit (WGC) and test circuit (TC) in to the soft IP core at the behavioural design level. Therefore this scheme can successfully survive synthesis, placement and routing and can identify the IP core at various design levels and IP core does not change at any levels. This method adopts current main system-on-chip (SOC). The identity of the IP is proven during the general test process without implementing any extra extraction flow. After the chip has been manufactured and packaged, it is still easy to detect the identification of the IP provider without the need of microphotograph. This approaches entail low hardware overhead, tracking costs, and processing-time costs. The proposed method solves the IP-identification problem.

Attribute reduction is a necessitated step for the disseminated environment in regard to classification and prediction of the data. Traditional approaches were not efficient for optimal attribute reducts. Current techniques are quiet time consuming and less accuracy. Rough set approach is a mathematical technique to handle attribute reducts through data dependencies and structural methods. This paper discusses a novel algorithm for optimal attribute deduct and also increases the accuracy in predicted results and the distributed decision tree classification techniques was made use of to implement the same in the disseminated environment. Proposed algorithm for Construction of distributed decision trees with rough sets increases the accuracy and also reduces the attributes on the time of the massive data sets handling.

Evolution of wireless access technologies is about to the reach its fourth generation (4G). The adaptation of smart antenna techniques in future wireless systems is expected to have a significant impact on the efficient use of the spectrum and transparent operation across the multi technology wireless networks. With the rapid growth of wireless data traffic operators are anxious to quickly expand the capacity of their wireless networks. To address these 3GPP standards have incorporated powerful techniques for using so-called smart antennas. This paper focuses on the practical aspects of deploying smart antenna systems in the existing Radio Access Systems (RAS). Smart antenna techniques, such as multiple-input multiple-output (MIMO) systems, can extend the capabilities of 3G and 4G systems to provide customers with increased data throughput for mobile high-speed data applications.

Accurate prediction of financial time series, such as those generated by stock markets, is a highly challenging task due to the highly nonlinear nature of such series. A novel method of predicting the next day’s closing value of a stock market is proposed and empirically validated in the present study. The system uses an adaptive artificial neural network based system to predict the next day’s closing value of a stock market index. The proposed system adapts itself to the changing market dynamics with the help of genetic algorithm which tunes the parameters of the neural network at the end of each trading session so that best possible accuracy is obtained. The effectiveness of the proposed system is established by testing on five international stock indices using ten different performance measures.

The paper presents a proactive approach for failure detection. In our previous work [5], we assumed a trustworthy Transaction Manager, TM, amenable to the job of view creation, detection of faulty primary as well as backup replicas and to evacuate them from the transaction processing system. In the end, TM initiates a view in case it detects faulty primary or faulty replica. The TM provides an efficient failure-resiliency in the protocol; however, it also introduces the possibility of single-point failure. To eliminate the reliance on single TM, we propose a protocol that distributes the responsibilities of a transaction manager among 3

f

+1(

f

are faulty) replicas and results in a distributed Transaction Manager (DTM). The article attempts to limit the failure detection time to an optimum value, i.e., single message propagation time between any two nodes.

Spam mails are unsolicited bulk mails which are meant to fulfill some malicious purpose of the sender. They may cause economical, emotional and time losses to the recipients. Hence there is a need to understand their characteristics and distinguish them from normal in box mails. Decision tree classifier has been trained with the major characteristics of spam mails and results obtained with more then 86.7437% accuracy. This classifier can be a valuable strategy for software developers who are trying to combat this ever growing problem.