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Über dieses Buch

The three volume set LNICST 84 - LNICST 86 constitute the refereed proceedings ofthe Second International Conference on Computer Science and InformationTechnology, CCSIT 2012, held in Bangalore, India, in January 2012. The 70 revised full papers presented in this volume were carefullyreviewed and selected from numerous submissions and address all major fields ofthe Computer Science and Information Technology in theoretical, methodological,and practical or applicative aspects. The papers feature cutting-edge developmentand current research in computer science and engineering.

Inhaltsverzeichnis

Frontmatter

Advances in Computer Science and Engineering

Qualitative Optimization of Coupling Parasitics and Driver Width in Global VLSI Interconnects

Analyses of the effects of interconnect wires in deep sub-micron technology is of prime importance in the modern era integrated circuits. The performance parameters such as crosstalk noise and delay are fundamentally dependent on interconnects and driver sizing. The coupling parasitics are the primary source of crosstalk. This paper addresses the optimization of coupling parasitics and driver sizing qualitatively for delay and peak noise. For this study, a pair of distributed

RLC

lines each of 4mm length is considered. These lines are coupled inductively and capacitively. The SPICE waveforms are generated at far end of lines for varying coupling parasitics and width of aggressor driver PMOS while keeping channel width of NMOS half of PMOS. The simulation is carried out at 0.13

μ

m, 1.5 V technology node. Both the cases of simultaneous switching of inputs

i.e

in-phase and out-of-phase are taken into consideration.

Devendra Kumar Sharma, Brajesh Kumar Kaushik, R. K. Sharma

Survey on Optimization Techniques in High Level Synthesis

This paper provides a detailed survey of optimization techniques available in high level synthesis. This survey contemplates on two parts. The first part deals with the applicability of optimization techniques available in high level language compiler into high level synthesis. The second part address the topics such as Area optimization, Resource optimization, Power optimization and Optimization issues pertaining to the notions value-grouping, value to register assignment, Transfer to wire assignment and wire to FU port assignment.

B. Saravanakumaran, M. Joseph

An Adaptive Technique Using Advanced Encryption Standard to Implement Hard Disk Security for Personalized Devices

The main objective of the paper is to develop an efficient and cost effective method for Hard Disk Drive(HDD) Security. The task is implemented using Full Disk Encryption (FDE) with Advanced Encryption Standards(AES) for data security of Personal Computers(PCS) and Laptops . The focus of this work is to authenticate and protect the content of HDD from illegal use. The paper proposes an adaptive methods for protecting a HDD based on Partial Disk Encryption(PDE) which one of the flavor of FDE. The proposed method is labeled as DiskTrust. FDE encrypts entire content or a single volume on your disk. Symmetric key uses same key for encryption as well for decryption. DiskTrust uses these two technology to build cost effective solution for small scale applications. Finally, the applicability of these methodologies for HDD security will be evaluated on a set of data files with different key sizes.

Minal Moharir, A. V. Suresh

Design of Fractional Order Digital Differentiator Using Inverse Multiquadric Radial Basis Function

In this paper, a fractional order digital differentiator is designed by using Inverse multiquadric radial basis function (RBF). First, the RBF interpolation approach is described. Then, the non-integer delay sample estimation is derived by using RBF approach. Next, the Grünwald-Letnikov derivative and non-integer delay sample delay are applied to obtain the transfer function of the proposed method i.e. fractional order digital differentiator. The design accuracy of the proposed method is better then the conventional methods like examples Time domain least squares method, Fractional sample delay method and Frequency response approximation method.

Nitin Kumar, Tarun Kumar Rawat

Cognitive Symmetric Key Cryptographic Algorithm

Today, Cryptographic schemes play a major role in storage, retrieval and transfer of data and code in a secured manner. The major factors which determine the efficiency of a cryptographic system are computational speed, level of security provided, cost effectiveness and key size of the algorithm. Choosing the optimal bit size for keys in encryption and decryption algorithm is necessary for the efficient computation of the algorithm and bit size of the key is directly proportional to the complexity of the algorithm and in turn cost of the encryption and decryption algorithm. In this paper, we propose a novel cost-effective small key size symmetric key algorithm which is suitable to all sizes of data and all kinds of data such as audio and video because of its low key size and high computational speed.

Y. R. A. Kannan, S. Aravind Prasad, P. Varalakshmi

Modeling and Verification of Fiat-Shamir Zero Knowledge Authentication Protocol

Model checking is a multi-purpose, automatic technique for verifying finite-state concurrent systems. Formal verification methods have quite recently become usable by industry. Presently model checking has been widely used in hardware, software validation and security protocol analysis. Fiat-Shamir is one of the many zero-knowledge authentication protocol which is used for security authentication purpose. In this paper, we have proposed a formal model of Fiat-Shamir authentication protocol using Finite State Machine (FSM). Security requirements are represented using Computation Tree Logic (CTL). These security requirements are verified and analyzed using symbolic model checker tool NuSMV. Based on our verification we have identified one of the security flaw of Fiat-Shamir protocol using the NuSMV model checker.

Amit K. Maurya, Murari S. Choudhary, P. Ajeyaraj, Sanjay Singh

Developing Software Metrics for Analysis and Design Artifacts in Unified Process

In this paper we have investigated the unified process workflow from analysis and design perspectives of software development life cycle. There are particular well defined roles to perform the life cycle activities. All these activities are streamed up in a typical capability pattern called workflow. When these activities are performed we need some artifacts as inputs. After the activities are done we receive some output artifacts. We have developed software process and software artifact metrics for the major artifacts and process of analysis and design workflow. We have suggested some metrics pertaining to the input and output artifacts. The metrics that we developed are for analysis and design process, software architecture document artifact, and design model artifact. Also we investigated how to quantify the artifact checklist items and make a decision about the quality for different attributes of the process and artifacts, and finally deciding upon the overall quality.

Meena Sharma, Rajeev G. Vishwakarma

A Novel Approach for Green Computing through Event-Driven Power Aware Pervasive Computing

Green computing is the term used for eco-friendly computing. It utilizes the computing resources in the most efficient way without raising issues to the environment. The goals of green computing are to reduce the use of hazardous materials, maximize energy efficiency during the product’s lifetime, and promote recyclability or biodegradability of defunct products and factory waste. The main purpose of this paper is to use the pervasive computing techniques, the advanced wireless communication strategies and smart hardware for the implementation of green computing. This paper discusses the role of pervasive computing towards achieving green computing by introducing pervasiveness in utilizing computing systems much efficiently in support with environmental well being. And also the paper tries to explore the concept of power aware computing and its implementation using event driven pervasive computing with the support of a handheld device such as a smart phone.

Jeeva Susan Jacob, K. G. Preetha

Coloured Petri Net for Modelling and Validation of Dynamic Transmission Range Adjustment Protocol in an Ad-Hoc Network

The IEEE 802.11 standard defines two operational modes for WLANs: infrastructure-based and infrastructure-less or ad-hoc. With constrained resources and limited computational capability, it may not be able for a node to serve more number of neighbours at the same time. The Dynamic Transmission Range Adjustment Protocol provides a mechanism for adjusting transmission range of the ad-hoc nodes to register or de-register a communicating node as its neighbour by dynamically varying the transmission range. Coloured Petri Nets is the modelling tool which provides a framework for design, specification, validation and verification of systems. In this paper, this tool is used to model and validate Dynamic Transmission Range Adjustment Protocol.

Lopamudra Mohapatra, Debansu Panda

Security Analysis of Proxy Blind Signature Scheme Based on Factoring and ECDLP

Proxy blind Signature is a digital signature where an original signer delegates his/her signing capability to a proxy signer who performs message signing blindly, on behalf of original signer but he cannot make a linkage between the blind signature and the identity of the message’s owner. Recently, Qi et al proposed an improved proxy blind signature scheme based on factoring and elliptic curve discrete log problem (ECDLP). In this paper we show that Qi et al’s scheme does not hold the identifiability and unlinkability properties. Moreover, we also point out that their scheme is not secure against universal forgery attack. Furthermore, we propose an improved proxy blind signature scheme to remedy the weaknesses of Qi et al.’s scheme. The security and performance of the improved scheme are also analyzed.

Namita Tiwari, Sahadeo Padhye

Dynamic Enterprises Architecture for One or More Clouds

Cloud computing goal is to support the IT organizations to integrate their services globally. It can help enterprises to improve their creation and delivery of IT solutions by providing them to access services in a cost effective and flexible manner. Cloud applications have different compositions, configurations, and deployment requirements. Quantifying the performance of scheduling and allocation policies in a real Cloud environment is extremely challenging due to several reasons like, variety of demands, supply patterns, and system size, heterogeneous and meeting the requirements of users competitively. To simplify this process, we develop a Dynamic Enterprise Architecture- (DEA) through industry collaboration to enable interoperability among various clouds and service providers. The Dynamic Architecture helps the user to utilize the services and integrate their applications from anywhere in the world by on demand, at competitive costs. Resources can be dynamically adjusted pertaining to the demand. It selects the suitable service provider or the coordination of the service provider according to the requirement of the user.

P. Mangayarkarasi, R. Selvarani

Congestion Control in Distributed Networks - A Comparative Study

Network congestion is characterized by delay and packet loss in the network. Increase in the rate of data transmissions as a result of increase in load, declines the throughput. Controlling congestion in network is an attempt to avoid overloading of any of the link capabilities of the intermediate nodes in the network by incorporating measures as reducing the rate of transmission or window size. This paper describes the comparison of different methods used in communication networks for controlling congestion to ensure effective communication. This study shows that the cross layered architecture with stochastic approach is providing an effective control over congestion and the response of the quality parameters is remarkably good in critical traffic situations.

K. Vinodha, R. Selvarani

Adaptive Controller and Synchronizer Design for the Qi-Chen Chaotic System

This paper investigates the design problem of adaptive controller and synchronizer for the Qi-Chen chaotic system (2005) with unknown parameters. First, adaptive control laws are derived to stabilize the Qi-Chen chaotic system to its unstable equilibrium at the origin. Then adaptive control laws are also derived to achieve global chaos synchronization of identical Qi-Chen chaotic systems with unknown parameters. The results derived for adaptive stabilization and synchronization for the Qi-Chen chaotic system are established using Lyapunov stability theory. Numerical simulations are presented to demonstrate the effectiveness of the adaptive control and synchronization schemes derived in this paper.

Sundarapandian Vaidyanathan

Opinion Mining from Weblogs and Its Relevance for Socio-political Research

This paper presents our experimental work on mining of opinions from a large number of blog posts and its relevance for socio-political research. The experimental work involves collecting blog data on three interesting topics, transforming the collected blog data into vector space representation, and then performing opinion mining using both a machine learning text classifier and an unsupervised semantic orientation approach. We implemented Naïve Bayes and SO-PMI-IR algorithms for opinion mining. We obtained interesting results, which have been evaluated for correctness and also cross-validated with the outcomes of multiple techniques employed. The paper concludes with a short discussion of the results and relevance of the experimental work.

Vivek Kumar Singh, Mousumi Mukherjee, Ghanshyam Kumar Mehta, Shekhar Garg, Nisha Tiwari

Generalized Projective Synchronization of Three-Scroll Chaotic Systems via Active Control

This paper investigates the generalized projective synchronization (GPS) of identical Wang 3-scroll chaotic systems (Wang, 2009) and non-identical Dadras 3-scroll chaotic system (Dadras and Momeni, 2009) and Wang 3-scroll chaotic system. The synchronization results (GPS) derived for the 3-scroll chaotic systems have been derived using active control method and established using Lyapunov stability theory. Since the Lyapunov exponents are not required for these calculations, the active control method is very effective and convenient for achieving the general projective synchronization (GPS) of the 3-scroll chaotic systems addressed in this paper. Numerical simulations are presented to demonstrate the effectiveness of the synchronization results derived in this paper.

Sarasu Pakiriswamy, Sundarapandian Vaidyanathan

Switching Algorithms in Peer to Peer Networks - Review

The peer-to-peer (P2P) network is heavily used for content distribution and is popularly used for internet file sharing. In a peer to peer network the average time to download a given file becomes a key metric for performance measure. The common approach of analyzing the average download time based on average service capacity is fundamentally flawed, and shown that the spatial heterogeneity of service capacities of different source peers and temporal fluctuations in service capacity of a single source peer have significant impact on increasing the average download time in P2P networks. This paper gives a comparative study of various downloading algorithms to effectively remove these negative factors thereby reducing the average download duration of a file.

M. Padmavathi, R. M. Suresh

Proposed Software Development Model for Small Organization and Its Explanation

Software Development is the process to illustrate the overall mechanism involved in the progress of software during different stages of development. To moderate the computational efficiency of earlier and later phases of development often occurred in small scale software developing organization we have proposed a new software development model for small organization. Through this model we can elicit the software requirement and we can also compute the functionality and risk in each and every phase of the software development.

Vinish Kumar, Sachin Gupta

A Comparative Analysis of Reduction Algorithms in Picasso Tool for Cost Based Query Optimizers of Relational Databases

Query optimization is a process of selecting an optimal Query Execution Plan from a number of plans available for execution of query which is very critical to the performance of a relational database. Picasso is a Query Optimizer analysis tool developed in the Database lab of Indian Institute of Science [24]. Using Picasso we can visualize the query execution plans and can implement a technique known as Plan Diagram Reduction [15][16][17] which can effectively increase the Query Optimizer performance. In this paper we briefly introduce the query optimization concept and then perform an exhaustive analysis of the reduction algorithms and try to establish some hard fact about their relative performance and reduction efficiency.

Neeraj Sharma, Yogendra Kumar Jain

Tele-control of Remote Digital Irrigation System Performed through Internet

There are two aspects of this project concerning to remote sensing and control related to electronic plantation and irrigation system. First part is dealing with the remote sensing of desired parameters in an unknown location as to decide and establish possibly an appropriate electronic plantation unit. Here, the desired parameters are sensed through appropriate transducers and live data are uploaded into the website automatically. In a remote station, by accessing the website the parameters conveyed are gathered and saved in memory. After collecting the data for a considerable period of time an analysis is made to decide the suitability of the area for establishing a plantation unit. The second part of the project is running an already established irrigation system by monitoring the desired parameters in the remote station and issuing control signals to switch ON or OFF the selected appliances as to maintain the irrigation automatically and efficiently. The methodologies used are presented with an analysis.

Akin Cellatoglu, Balasubramanian Karuppanan

A Fuzzy Rule Based Expert System for Effective Heart Disease Diagnosis

This is a general method that combines the soft computing techniques like genetic algorithms and fuzzy rule based expert system for effective heart disease diagnosis. It is very important to diagnose the disease in the early stage itself. Prompt and correct diagnosis of the disease by selecting the important and relevant features will help to discard irrelevant and unimportant ones. Genetic algorithms help in feature subset selection. After the subset selection the fuzzy rule based expert system provides the classificatory knowledge. The proposed system generates the rules from the instances and narrows down the limit of the rules using degree of the memberships. The system is designed in Matlab software. The system can be viewed as an alternative method for effective diagnosis of heart disease presence.

E. P. Ephzibah, V. Sundarapandian

Moving Object Detection Using Incremental Statistical Mean Technique

We propose a new approach for moving object detection. Moving object detection is low-level, important task for any visual surveillance system. The aim of this paper is to, to describe traditional approach of moving object detection techniques such as background subtraction, temporal difference, as well as pros and cons of these techniques. Finally, we propose the statistical mean technique to overcome the problem in traditional techniques. Since, simple statistical mean technique having disadvantages, to defeat those, we propose incremental statistical mean technique. Incremental statistical mean technique have need of computation to perform simultaneously, that requires parallel computation to speed up and reduce the computation complexity.

Safvan A. Vahora, Narendra C. Chauhan, Nilesh B. Prajapati

Classification of Moving Vehicles in Traffic Videos

In this paper, we propose a model for classification of moving vehicles in traffic videos. We present a corner-based tracking method to track and detect moving vehicles. The detected vehicles are classified into 4 different types of vehicle classes using optimal classifiers. The proposed classification method is based on overlapping the boundary curves of each vehicle while tracking it in sequence of frames to reconstruct a complete boundary shape of it. The reconstructed boundary shape is normalized and a set of efficient shape features are extracted. Vehicles are classified by k-NN rule and the proposed weighted k-NN classifier. Experiments are conducted on 23.02 minutes of moderate traffic videos of roadway scenes taken in an uncontrolled environment during day time. The proposed method has 94.32% classification accuracy which demonstrates the effectiveness of our method. The proposed method has 87.45% of precision with 79% recall rate for classification of moving vehicles.

Elham Dallalzadeh, D. S. Guru, S. Manjunath, M. G. Suraj

Use of Augmented Reality in Serious Game for Training Medical Personnel

Serious games are games focused on learning other than pure entertainment. The potential of serious games for training of personnel is considered in many fields. The serious games differ from regular games, by helping the player to learn from the game rather than only entertainment. This paper focuses on the potential of serious game to train medical personnel and the use of augmented reality to enhance the training process. We also prove that the use of augmented reality in the serious games can improve the training of medical personnel and give them real world experience. This paper elaborates the use of serious game for training medical personal and the efficiency of using augmented reality in serious games.

Arun Kumar Karthikeyan, Praveen Kumar Mani, Suresh Kumar Balasubramaniyan, Praveen Jelish Panneer Selvam

Encouraging the Usage of Neural Network in Video Text Detection Application

The video text detection is an expert system in which we study how the performance can be enhanced by adding neural network. The implementation of video text detection using algorithm based approach [9] is taken and compared with the neural networks based implementation [11]. A standard protocol [10] for evaluating the video text detection approach is taken and its metrics are used for the comparative study. With this comparison, the evaluation of both the systems for better performance can be done. The conclusions necessary for enhancing the usage of neural network is drawn based on the comparison study. The paper is about encouraging the use of neural network in an expert system (Video Text Detection Application).

Suresh Kumar Balasubramaniyan, Praveen Kumar Mani, Arun Kumar Karthikeyan, Ganesh Shankar

A Novel Face Recognition Method Using PCA, LDA and Support Vector Machine

Here an efficient and novel approach was considered as a combination of PCA, LDA and support vector machine. This method consists of three steps: I) dimension reduction using PCA, ii) feature extraction using LDA, iii) classification using SVM. Combination of PCA and LDA is used for improving the capability of LDA when new samples of images are available and SVM is used to reduce misclassification caused by not linearly separable classes.

U. Raghavendra, P. K. Mahesh, Anjan Gudigar

Contextual Strategies for Detecting Spam in Academic Portals

The emergence of social networking platforms in online space and its ever increasing user base has opened up a new arena for the spammers to exploit. Spam, in these kinds of platforms and such other interactive tools like forums, instant messaging, could be created easily and difficult to stop it from spreading, which necessitates the development of better detection strategies. In this paper, we present a contextual strategy for detecting spam in a restricted domain such as an academic portal. The proposed method uses the relationship between the concepts of the domain and the concepts of the individual message fragments to determine the relevancy of the message to the given context and marks the outliers. The strategy has been tested using a prototype system which had networking and interactive features for the participants to share information, and the results indicated that the contextual strategy was fairly successful in detecting spam.

Balaji Rajendran, Anoop Kumar Pandey

Hybrid Synchronization of Hyperchaotic Chen Systems via Sliding Mode Control

This paper investigates the hybrid synchronization of hyperchaotic Chen systems (Jia, Dai and Hui, 2010) via sliding mode control. The stability results for the sliding mode control based synchronization schemes derived in this paper are established using Lyapunov stability theory. The sliding mode control method is very effective and convenient to achieve global chaos synchronization of the identical hyperchaotic Chen systems because the Lyapunov exponents are not required for these calculations. Numerical simulations are presented to demonstrate the sliding mode control results derived in this paper for the hybrid synchronization of identical hyperchaotic Chen systems.

Sundarapandian Vaidyanathan, Sivaperumal Sampath

Design and Implementation of Efficient Viterbi Decoders

Viterbi decoders are used for forward error correction, but the algorithm demands more hardware, memory and computational time, hence researchers have come up with other alternatives like fangled viterbi decoder, modified fangled viterbi decoder, but these methods lack error correction capabilities. In this work an innovative method is used to improve error correction capabilities. The results shows it can correct two bit error with less computational time and hardware requirement.

K. S Arunlal, S. A Hariprasad

Classification of MRI Brain Images Using Cosine-Modulated Wavelets

This paper presents technique for the classification of the MRI images of human brain using cosine modulated wavelet transform. Better discrimination and low design implementation complexity of the cosine-modulated wavelets has been effectively utilized to give better features and more accurate classification results. The proposed technique consists of two stages, namely, feature extraction, and classification. In the first stage, the energy features from MRI images are obtained from sub-band images obtained after decomposition using cosine modulated wavelet transform. In the classification stage, Bays classifier is used to classify the image as normal or abnormal. Average Classification accuracy with a success rate of 100% has been obtained.

Yogita K. Dubey, Milind M. Mushrif

A Novel Approach for Email Login System

In real time world password will be compromise by some adversaries is common for different purpose. In ICC 2008 Lei et al. introduced a new user authentication system based on the virtual password system methodology. In virtual password methodology they have used function based on the linear randomization approach, to be secure against identity theft attacks, phishing attacks, keylogging attack and shoulder surfing system. At ICC 2010 Li’s given a security attack which compromised the user on the Lei’s work. The proposed approach gives modification on Lei’s work to prevent the Li’s attack with reducing the server overhead. This paper also discussed the problems with current email password recovery system and gives the better approach.

Bhavesh Patel, Dipak Patel, Shakti Patel, Rajendra Patel, Bhavin Tanti, Nishant Doshi

A Non-revisiting Genetic Algorithm with Adaptive Mutation for Function Optimization

Genetic Algorithm (GA) is a robust and popular stochastic optimization algorithm for large and complex search spaces. The major disadvantages of Genetic Algorithms are premature convergence and revisits to individual solutions in the search space. In other words, Genetic algorithm is a revisiting algorithm that leads to duplicate function evaluations which is a clear waste of time and computational resources. In this paper, a non-revisiting genetic algorithm with adaptive mutation is proposed for the domain of function optimization. In this algorithm whenever a revisit occurs, the underlined search point is replaced with a mutated version of the best/random (chosen probabilistically) individual from the GA population. Moreover, the suggested approach is not using any extra memory resources to avoid revisits. To test the power of the method, the proposed non-revisiting algorithm is evaluated using nine benchmarks functions. The performance of the proposed genetic algorithm is superior as compared to simple genetic algorithm as confirmed by the experimental results.

Saroj, Devraj

xScribble: A Generalized Scheme for String-Encoding Graphical Data in Multiuser Graphical Chat

Multiuser graphical chat enables two or more users to communicate user generated graphical data in real time. It is most commonly used in online whiteboards where users can interact simultaneously. In this paper, we introduce xScribble: a generalized scheme for encoding graphical data for real time network communication. The paper discusses how to encode graphical data from various drawing tools into string format flexible enough to be used with any text chat system. The memory efficiency and performance of the xScribble scheme is also analysed.

Rahul Anand, Joshy Joseph, P. Dipin Dev, Hegina Alex, P. C. Rafeeque

Analysis of IG DV Protocols in MPLS Network for Quality of Video Conference

This paper analyzes the different Interior Gateway (IG) Distance Vector (DV) protocols like Routing Information Protocol (RIP), Interior Gateway Routing Protocol (IGRP) and Enchanced Interior Gateway Protocol (EIGRP) for MultiProtocol Label Switching (MPLS) network in video conference application. In telecommunication networks, delay is one of the major problems which leads the network to discard packets and in turn having a negative impact on a quality. The combination of MPLS prominent execution packet carrying technology along with IG protocol can reduce the packet delay in the network. The simulation results show that Enchanced Interior Gateway Routing Protocol (EIGRP) can be used for achieving better quality.

Swarnalatha Mannar Mannan, Arunkumar Jayaraman, Kolachina Srinivasa Kranthi Kiran

A Comparative Analysis of Watermarking Techniques for Copy Protection of Digital Images

Digital watermarking is the process of embedding information into a digital signal, i.e. audio, pictures, video, etc. Embedded marks in the message are generally imperceptible but can be detected or extracted. By imperceptibly hiding information into the video content it is possible to provide copy protection .The embedding takes place by manipulating the content of the digita l data, which means the information is not embedded in the frame around the data. If the signal is copied, then the embedded information is also in the copy. So, Watermarking is an emerging technology that is claimed to have an important application in copy protection. A variety of watermarking techniques have been proposed by researchers for the copy-protection. This paper presents an extensive review of the prevailing literature in watermarking for copy protection.

Dolley Shukla, Manisha Sharma

Unique-Minimum Conflict-Free Coloring for a Chain of Rings

An optimal algorithm is presented about Conflict-Free Coloring for connected subgraphs of chain of rings. Suppose the length of the chain is |

C

| and the maximum length of rings is |

R

|. A presented algorithm in [1] for a Chain of rings used

O(log

|

C

|

.log

|

R

|

)

colors but this algorithm uses

O(log

|

C

|

+log

|

R

|

)

colors. The coloring earned by this algorithm has the unique-min property, that is, the unique color is also minimum.

Einollah Pira

Enhanced Ad Hoc on Demand Distance Vector Local Repair Trial for MANET

Ad hoc On-demand Distance Vector (AODV) is a routing schema for delivering messages in a connected Mobile Ad hoc Network (MANET). Connectivity between any sources to destination pair in the network exists when they are in radio range of each other. Local Repair is an important issue in routing protocol which is needed for minimizing flooding and performance improvement. Routes can be locally repaired by the node that detects the link break along the end to end path. In this paper, the existing Local Repair Trial method in AODV is extended to achieve broadcasting and minimizing the flooding. The enhanced protocol first creates the group of mobile nodes then broadcasting can be done and if the link breaks then local repair technique can be applied. In the network the numbers of intermediate nodes are increased by using Diameter Perimeter Model. Enhanced AODV-Local Repair Trial (EAODVLRT) protocol is implemented on NS2 network simulator. Simulations are performed to analyze and compare the behavior of proposed protocol (EAODVLRT) for varying parameters such as size of network, node load etc. Proposed protocol has been compared with the existing AODV-LRT in terms of routing load, Data delivery ratio.

P. Priya Naidu, Meenu Chawla

Multi-class SVM for EEG Signal Classification Using Wavelet Based Approximate Entropy

In this paper, we have proposed a novel wavelet based approximate entropy for feature extraction and a novel Multi-Class Support Vector Machine (MSVM) for the multi-class electroencephalogram (EEG) signals classification with the emphasis on epileptic seizure detection. The aim was to determine an effective classifier and features for this problem. Wavelets have played an important role in biomedical signal processing for its ability to capture localized spatial-frequency information of EEG signals. The MSVM works well for high dimensional, multi-class data streams. Decision making was performed in two stages: feature extraction by computing the wavelet based approximate entropy and classification using the classifiers trained on the extracted features. We have compared the MSVM with Probabilistic Neural Network (PNN) by evaluating with the benchmark EEG dataset. Our experimental results show that the MSVM with wavelet based approximate entropy features gives high classification accuracies than the existing classifier.

A. S. Muthanantha Murugavel, S. Ramakrishnan

Hybrid Intrusion Detection with Rule Generation

This paper reports a new experimental hybrid intrusion detection system (HIDS). This hybrid system combines the advantages of Misuse-based intrusion detection system (IDS) having low false-positive rate and the ability of anomaly detection system (ADS) to detect novel unknown attacks. This is done by mining Internet connections records for anomalies. We have built ADS that can detect attacks not detected by Misuse-based systems like Snort or Bro systems. Rules are extracted from detected anomalies and then are added to Misuse-based system’s rule database. Thus Misuse-based intrusion detection system can detect new attacks. The system is trained and tested using Massachusetts Institute of Technology/ Lincoln Laboratory (MIT/LL) DARPA 1999 dataset respectively. Our experimental results show a 69 percent detection rate of the HIDS, compared with 47 percent in using the Snort. This increase in detection rate is obtained with around 0.08 percent false alarms. This approach provides a better way to deal with novel attacks using ADS along with a trustworthy misuse-based Intrusion detection system.

V. V. Korde, N. Z. Tarapore, S. R. Shinde, M. L. Dhore

Tele-Operation of Web Enabled Wireless Robot for Old Age Surveillance

This paper discusses the system design and implementation of web-enabled wireless robotic system for old age surveillance. In societies, surveillance holds valuable importance for aging population. The system presented is meant for surveillance of elder citizens, who might face physical problems and could be potential site of criminal activities. As a solution to this problem, a prototype of a wireless robot mounted with a wireless camera and microphone is developed, which proved to be quiet effective to test various abnormal events occurring with elder ones. The system works using audio-video information that triggers message to remote client if any abnormality is detected. The remote client can receive live feed of the place where elder people are present using media streaming over and the same can also control the motion of the wireless robot over internet. This helps in restraining the felicity of elder citizens.

Yatin Wadhawan, Sajal Gupta

DSP Implementation of Wavelet Transform Based Embedded Block Coder Using Quadtree Partitioning Method

This paper work describes the implementation of embedded block coder for still image compression using only quad-tree partitioning method. This technique is based on Discrete Wavelet Transform. The motivation behind this work is from SPECK (Set Partitioning Embedded bloCK) algorithm. It uses a recursive set-partitioning procedure to sort subsets of wavelet coefficients by maximum magnitude with respect to thresholds that are integer powers of two. The proposed method simplifies the complexity of the embedded wavelet image coding algorithm by combining both sorting pass and refinement pass. In comparison with other methods, this is simpler to be realized on hardware and has higher compression efficiency. This paper work also explains the software and hardware implementation by using TMS320C6713 DSK board. The statistical analysis is done with profile statistic available in Code Composer Studio (CCS) environment. The MATLAB simulation results show that PSNR values are quite improved by lowering threshold values.

Deepali P. Ladhi, Richa R. Khandelwal

Calculation of the Minimum Time Complexity Based on Information Entropy

In order to find out the limiting speed of solving a specific problem using computer, this essay provides a method based on the entropy of information. The relationship between the minimum time complexity and the information entropy change is illustrated. Several examples are served as evidence of such connection. Meanwhile some notices of modeling these problems are proposed. Finally, the nature of solving problems with computer programs is disclosed to support the theory and a redefinition of the information entropy in this field is proposed. This will develop a new field of science.

Xue WU

Enhancing E-Learning through Cognitive Structures for Learning Sports

Enhancing e-Learning through understanding and taking into account the cognitive structures of learner and trainer in learning sports is a new avenue of research. E-Learning has made its steps into all disciplines, while sports domain remains a discipline that involves physiological variables in learning. Learning sport is incomplete until a learner is trained physically and is ready to actually play the sport. The curiosity to know how e-Learning methods can be utilized for learning sports has led the work to look into the learning theories. The behaviorist approach can be efficient at the initial level. The cognitive approach has been identified as an efficient approach in advanced level learning. Cognitive theory of learning also proposes feedback mechanism, contiguity, repetition, and reinforcement. This research is to explore the possibility of enhancing e-learning using cognitive theoretical approach in learning sports.

S. MuthuLakshmi, S. Nagasundari, S. P. Surender Nath, G. V. Uma

Speaker Independent Connected Digit Recognition Using VQ and HMM in Additive Noise Environment

The main objective of this paper is to discuss the effectiveness of concatenated perceptual features and the noise reduction technique based on wavelet transform and Recursive least square filtering in getting the good recognition rate for the peculiar combination of connected digits in additive noise environment. The proposed concatenated perceptual features are captured and code book indices are extracted. Expectation maximization algorithm is used to generate discrete HMM models for the connected digits. Speech recognition system is evaluated on clean and noisy test speeches and the selection is based on which model gives maximum log likelihood value. Speeches for this work are randomly chosen from “TI Digits_1”, “TI Digits_2” databases. This concatenated perceptual feature yields the accuracy of 81.4% and 73% for the combination of connected digits (10 - 19) and (12- 19,21,31,41,51,61,71,81,91). Pink noise, white noise, babble noise and factory noise are considered in this work.

A. Revathi, Y. Venkataramani

Decomposition+: Improving ℓ-Diversity for Multiple Sensitive Attributes

In this paper, we analyse existing privacy-transformation techniques in the field of PPDP that anonymize datasets with Multiple Sensitive Attributes (MSA). Of these, we present an analysis of Decomposition, an algorithm which generates a dataset with distinct ℓ-diversity over MSA using a partitioning approach. We discuss some improvements which can be made over Decomposition: in the realms of its running time, its data utility, and its applicability in the case of Multiple Release Publishing. To this effect, we describe

Decomposition+

an algorithm that implements some of these improvements and is thus more suited for use in real-life scenarios.

Devayon Das, Dhruba K. Bhattacharyya

Radix-4 Modified Interleaved Modular Multiplier Based on Sign Detection

Data Security is the most important issue nowadays. A lot of cryptosystems are introduced to provide security. Public key cryptosystems are most common cryptosystems used for securing data communication. Modular multiplication is the basic operation of a lot of public key cryptosystems such as RSA, Diffie-Hellman key agreement (DH), ElGamal, and ECC. Abd-el-fatah et al. introduced an enhanced architecture for computing modular multiplication of two large numbers X and Y modulo given M. In this paper, a modification on that architecture is introduced. The proposed design computes modular multiplication by scanning two bits per iteration instead of one bit. The proposed design for 1024-bit precision reduced overall time by 38% compared to the design of Abd-el-fatah et al.

Mohamed A. Nassar, Layla A. A. El-Sayed

Adapting Temporal Aspects to Static GIS Models

Conventional GIS data models emphasize static representation of real world Geographic features. There are several real world problems where this assumption is not valid. For example the boundary of a lake changes with time depending on the inflow due to rains. The feature’s geometry, its attributes and the topology with respect to its adjacent features are temporal. Current models used in commercial GIS do not support efficient persistence of the temporal history, provide temporal queries and deal with time variant topological changes. Study of current spatio-temporal models has been done and suitable techniques to enhance current spatial models with temporal aspects without breaking existing functionality has been explored. Moving object data model and its variations have been found to be an appropriate candidate for such enhancement. This paper describes the extension of spatial data model and its schema of a commercial GIS tool for supporting moving object data and creation of typical temporal analysis and query commands.

K. C. S. Murti, Viksit Agarwal

A Basic Comparison of Different Memories for Object Oriented Computer Architecture

This position paper is focused on the abstract model of Object Oriented Computer Architecture and specifically the memory unit of such a computing system which would be able to handle the type of object oriented computing proposed in the paper. The memory unit plays a very crucial part because it will have to be radically different from what we call a memory unit in the present contexts. This parallel nature of computing in an OOCA allows it to use different memory architectures both as shared memory and distributed memory. Here we compare the pros and cons of using these types of memories in an OOCA.

Ankit V. Patel, Paresh Mathur

Performance Evaluation of Segmentation of Frog-Eye Spot Lesions on Tobacco Seedling Leaves

In this paper, a new algorithm for segmentation of frog-eye spot lesions on tobacco seedling leaves is proposed. Segmentation algorithm consists of mainly two steps. First step is to approximate lesion extraction using contrast stretching transformation and morphological operations such as erosion and dilation. Second step refines the outcome of first step by color segmentation using CIELAB color model. We have also conducted a performance evaluation of segmentation algorithm by measuring the parameters such as Measure of overlapping (MOL), Measure of under-segmentation (MUS), Measure of over-segmentation (MOS), Dice similarity measure (DSM), Error-rate (ER), Precision (P) and Recall (R). In order to corroborate the efficacy of the proposed segmentation algorithm, an experimentation is conducted on our own dataset of 400 segmented areas of tobacco seedling leaves which are captured in uncontrolled lighting conditions. Experimental results show that our proposed segmentation algorithm achieved best average DSM and MOL accuracy as compared to our previous segmentation algorithm.

P. B. Mallikarjuna, D. S. Guru

Password Authentication Using Context-Sensitive Associative Memory Neural Networks: A Novel Approach

Passwords are the most widely used form of authentication. In many systems the passwords, on the host itself, are not stored as plain text but are encrypted. However, conventional cryptography based encryption methods are having their own limitations, either in terms of complexity or in terms of efficiency. The conventional verification table approach has significant drawbacks and storing passwords in password table is one of the drawbacks.

In the present paper, we propose a cognitive neural model using Context-Sensitive Associative Memory Model(CSAM) for password authentication, which is derived from cognitive domain and vector logic. According to the model, the product of two vectors is an associative memory(context-dependent) that plays critical role in the neural networks domain. In this model the output (encrypted password) is associated with the Kronecker Product of an input (key) and a context (password). The encrypted password is decoded with key and the context-dependent memory (Krnocker product) to get the original password. The proposed system provides better accuracy and quicker response time to authenticate the password but this model requires more space for holding context-dependent associative memory.

P. E. S. N. Krishna Prasad, B. D. C. N. Prasad, A. S. N. Chakravarthy, P. S. Avadhani

A Heuristic Approach for Community Detection in Protein Networks

Protein-protein interactions play a vital role in identifying the outcome of a vast majority of cellular mechanisms. But analyzing these complex data to identify community structures which can explain the activities of protein networks were always been a challenge. This paper reports the use of triangular modularity of protein network as an effective method to identify these community structures.

Sminu Izudheen, Sheena Mathew

Single Reduct Generation by Attribute Similarity Measurement Based on Relative Indiscernibility

In real world everything is an object which represents particular classes. Every object can be fully described by its attributes. Any real world dataset contains large number of attributes and objects. Classifiers give poor performance when these huge datasets are given as input to it for proper classification. So from these huge dataset most useful attributes need to be extracted that contribute the maximum to the decision. In the paper, attribute set is reduced by generating reducts using the indiscernibility relation of Rough Set Theory (RST). The method measures similarity among the attributes using relative indiscernibility relation and computes attribute similarity set. Then the set is minimized and an attribute similarity table is constructed from which attribute similar to maximum number of attributes is selected so that the resultant minimum set of selected attributes (called reduct) cover all attributes of the attribute similarity table. The method has been applied on glass dataset collected from the UCI repository and the classification accuracy is calculated by various classifiers. The result shows the efficiency of the proposed method.

Shampa Sengupta, Asit Kr. Das

Adaptive QoS-Aware Web Service Composition

Service oriented architecture is a challenging area to fervently focus on. In that web service composition plays a vital role. The main crux behind composition lies on the effective selection of available web services in order to provide the value added services on the fly. Quality of Service (QoS) is one of the non functional properties of the web services, which is used to evaluate the degree to which the service can satisfy the service request. In the proposed approach, the composition is handled based on the QoS the web service has provided in its previous attempts towards composition. A separate process of updating the beliefs and reputation is been identified which stores the appropriate belief factor against the candidate web service in the process registry. Instead of having the QoS as a constant provider specified value, our approach assigns the value based on the end users feedback. The paper discusses the approach used in identifying the quality of the web service composition and the efficiency of composing relevant services for the service request.

Deivamani Mallayya, Baskaran Ramachandran

Key Dependent Feature Point Based Image Watermaking Scheme

An approach to a blind discrete Wavelet Transformation (DWT) domain feature point based image watermarking technique is proposed in this paper. The embedding of the watermark is performed into the image feature points defined by the Harris detector and the additional feature points are generated from the existing feature points using a key dependent algorithm. The proposed method is simple and secure. It is also experimentally found to be robust against various geometric and noise attacks.

Ramesh Kumar Surapathi, Kamalika Datta, I. Sengupta

A Survey on ATTACK – Anti Terrorism Technique for ADHOC Using Clustering and Knowledge Extraction

Analyzing and predicting behavior of node can lead to more secure and more appropriate defense mechanism for attackers in the Mobile Adhoc Network. In this work, models for dynamic recommendation based on fuzzy clustering techniques, applicable to nodes that are currently participate in the transmission of Adhoc Network. The approach focuses on both aspects of MANET mining and behavioral mining. Applying fuzzy clustering and mining techniques, the model infers the node’s preferences from transmission logs. The fuzzy clustering approach, in this study, provides the possibility of capturing the uncertainty among node’s behaviors. The results shown are promising and proved that integrating fuzzy approach provide us with more interesting and useful patterns which consequently making the recommender system more functional and robust.

K. Sudharson, V. Parthipan

SecureWear: A Framework for Securing Mobile Social Networks

With the rising popularity of social networks, people have started accessing social networking sites from anywhere, any time, and from a variety of devices. Exploiting this ubiquity, the social networking data of an individual can be coupled with her geographical location to build different context aware applications. However, the existing infrastructure to share this personalized data forces users to compromise their privacy. In this paper, we present a secure framework, which allows interaction of social network information with location-based services, without compromising user privacy and security. Through exchanging an encrypted nonce ID (EID) associated with a verified user location, our framework allows location-based services to query its vicinity for relevant information without disclosing user identity. We further argue that, this kind of framework should be adopted as a common security framework for mobile-social interaction to meet privacy requirements.

Baishakhi Ray, Richard Han

Throughput Analysis of Next-Hop Forwarding Method for Non-linear Vehicular Ad Hoc Networks

Position based routing plays a significant role in multi-hop Vehicular Ad hoc Networks (VANETs), due to high mobility of nodes. Selection of next-hop node is crucial to improve the performance of routing. In this paper, we have proposed a method for selecting next-hop forwarding node based on the distance between the source and next-hop node and link quality. Next-hop node is selected based on Expected Progress Distance (EPD) criteria. The EPD is estimated in terms of expected distance between the source and next-hop node. The expected delay (E

D

) and throughput (T

h

) are also estimated for the proposed method. The mathematical model derived for calculating EPD, delay, and throughput are simulated in MATLAB and evaluated the performance of the proposed method.

Ram Shringar Raw, D. K. Lobiyal

A Novel Algorithm for Prediction of Protein Coding DNA from Non-coding DNA in Microbial Genomes Using Genomic Composition and Dinucleotide Compositional Skew

Accurate identification of genes encoding proteins in genome remains an open problem in computational biology that has been receiving increasing consideration with explosion in sequence data. This has inspired us to relook at this problem. In this study, we propose a novel gene finding algorithm which relies on the use of genomic composition and dinucleotide compositional skew information. In order to identify the most prominent features, two feature selection techniques widely used in data preprocessing for machine learning problems: CFS and ReliefF algorithm applied. The performance of two types of neural network such as multilayer perceptron and RBF network was evaluated with these filter approaches. Our proposed model led to successful prediction of protein coding from non-coding with 96.47% and 94.18 % accuracy for MLP and RBF Network respectively in case of CFS and 94.94 % and 92.46 % accuracy for MLP and RBF Network respectively in case of ReliefF algorithm.

Baharak Goli, B. L. Aswathi, Achuthsankar S. Nair

User-Centric Situation Awareness in Ubiquitous Computing Environments

The rising popularity of ubiquitous computing has resulted in a paradigm shift from generic to user-centric solutions, requiring seamless integration of heterogeneous devices and sensors in the environment to constantly monitor and perform tasks traditionally performed by the user. There is a considerable push, therefore, to develop systems capable of perceiving user behavior, and adapting to their idiosyncrasies. In this paper, we discuss limitations of the interpretations of context, and extend them for improved context awareness. We discuss a user-centric approach to perception of activity in the environment, and use the obtained knowledge in understanding user activities. We present a system for perceiving situations, and discuss an approach to empower the user to develop complex, yet intuitive, rules. We evaluate the performance of the system in a dynamic ubiquitous environment.

Gautham Pallapa, Sajal K. Das

A Review of QoS Driven Optimal Selection of Web Services for Compositions

Web services technology promises to enable rich, flexible and dynamic interoperation of highly distributed and heterogeneous applications using Web standards. The providers of composite Web services involving composition plan with different flow patterns need to discover and select suitable candidate Web services for each task of the composition plan at runtime. The dynamic nature of Web services prompts a need for the mechanism to enable the frequent editing of QoS offers of composite Web services by the Composite Service Providers (CSP). In this paper, the authors present a detailed survey of literature in QoS based selection for Web service compositions. The paper also presents different architectures for QoS aware Web service compositions and evaluates various QoS aware selection techniques. The authors classify QoS aware selection techniques for composition based on the nature of composition plan, complexity of QoS requirements and nature of techniques/methodology used in the selection and QoS aggregation.

Demian Antony D’Mello, V. S. Ananthanarayana

Location Service Management Protocol for Vehicular Ad Hoc Network Urban Environment

Location based service is used in vehicular ad hoc networks (VANET) to locate a node’s position before the start of any communica- tion. The existing location services proposed for Mobile Ad hoc Networks (MANET) suffer from low scalability in VANET environments. Protocols proposed for VANET do not consider load balance on location servers, and do not consider realistic information for selecting location servers which affect the protocols efficiency. This paper proposes a Quorum- Based Location Service Management Protocol (QLSP) which is designed for urban area topology utilizing specific node information such as the distance to intersection centre point, and speed in selecting main loca- tion server. Formation of quorum location servers is achieved by the main location server through the nomination of other nodes located at the in- tersection based on their direction of movement. QLSP shows excellent performance in reducing overhead of control packets, provides a high de- livery ratio of packets to destination, and reduces the end-to-end delay of routing packets. The performance of the protocol is then compared to other existing location service protocols.

Salim M. Zaki, M. A. Ngadi, Shukor Abd Razak, Maznah Kamat, Johan Mohamad Shariff

CNT Based Channel Interconnect for CMOS Devices

MOSFET device dimensions and dimensions of interconnects have been scaled down to increase density, functionality and performance of a chip. Recently, scaling down of dimensions, that has now reached to the nano regime, have led to various issues like electromigration as in the case of interconnects and hot carrier effects, drain induced barrier lowering and so on in case of MOSFET’s. Researchers are thus trying to find other options for interconnects and also new architectures to replace the conventional MOSFET’s. This paper is a study of Carbon Nanotube which is gaining interest of researchers both as device interconnect and channel-interconnect. The behavior of CNT with length and diameter is considered. A study of various parameters like mobility, conductance etc. of the CNT is done. This paper focuses on CNT based FET’s, that are gaining interest as replacements for conventional CMOS, in many modern circuits and also new devices.

Ginto Johnson, Vinod Pangracious

Conviction Scheme for Classifying Misbehaving Nodes in Mobile Ad Hoc Networks

A Mobile ad-hoc network (MANET) is a wireless network, self-configuring, capable of self-directed operation, hastily deployable and operates without infrastructure. Nodes cooperate to provide connectivity, operates without centralized administration. Nodes are itinerant, topology can be very dynamic and nodes must be able to relay traffic since communicating nodes might be out of range. The dynamic nature of MANET makes network open to attacks and unreliability. A node may be unsuccessful to cooperate during routing, sometimes may even disturb the routing transaction. The Qos parameters like PDR, throughput and delay are affected directly due to such behavior of nodes and it is termed as misbehaving nodes. A trust-based system can be used to track this misbehaving of nodes, spot them and isolate them from routing and provide reliability. In this paper a trust based reliable AODV protocol is presented which implements a trust value for each node. Every node is defined as reliable node if its trust value is greater than threshold value, if not it’s a misbehaving node. This enhances reliability in AODV routing and results in increase of PDR, decrease in delay and throughput is maintained. This work is implemented and simulated on NS-2. Based on simulation results, the proposed protocol provides more consistent and reliable data transfer compared with normal AODV, if there are misbehaving nodes in the MANET.

S. Sridhar, R. Baskaran

Virtual Interactive Prototyping

In this paper, we introduce a new method of technology enhanced prototyping called Virtual Interactive Prototyping (VIP). Prototype is a model that mimics the static or working behavior of an actual product before manufacturing the product. Prototyping is implemented by displaying the individual components over a physical model constructed using Cardboard or Thermocole in the actual size and shape of the original product. The components of the equipment or product such as screen, buttons etc. are then projected using a projector connected to the computer into the physical model. Users can interact with the prototype like the original working equipment. Computer Vision techniques as well as sound processing techniques are used to detect and recognize the user gestures captured using a web camera and microphone. VIP is a fast, flexible and interactive prototyping method and has many advantages over existing immersive video prototyping methods.

Kurien Zacharia, Eldo P. Elias, Surekha Mariam Varghese

Chaotic Masking of Voice Bitstream Using Mixed Sequences for Authorized Listening

The voice-based communication becomes extensively vital in the application areas of military, voice over IP, voice-conferencing, phone banking, news telecasting etc. It greatly demands to preserve sensitive voice signals from the unauthorized listening and illegal usage over shared/open networks. To address the need, we propose a chaos-based symmetric encryption technique to protect voice bitstreams over insecure transmission channel. The technique utilizes the features of high dimensional chaos like Lorenz and Chen systems to generate highly unpredictable and random-like sequences. The encryption keys are dynamically extracted from the pretreated chaotic mixed sequences, which are then used to mask the voice bitstream for integrity protection of voice data. The experimental analyses like auto-correlation, signal distribution, parameter-residual deviation, key space and key-sensitivity demonstrate the effectiveness of the proposed technique for secure voice communication.

Musheer Ahmad, Bashir Alam, Omar Farooq

A Framework for Transparency in SHGs

A Self Help Group [SHG] is a small homogeneous gathering of persons who join on a voluntary basis in order to undertake some common activity through mutual trust and mutual help. SHG system is conceptualized basically to address the problem of rural unemployment, and empowering people to make them economically self-dependent. But, there is a possibility of it being turned into a commercial unit negating the very thesis it espouses.In the last decade we have seen an increased use of the term “transparency” in different contexts such as business, political affairs, education, administration and government. Transparency is considered an indispensable ingredient in social accountability and necessary for preserving and guaranteeing ethical and fair processes. Transparency is related to visibility of information. Lack of transparency leaves the organization and stakeholders in blind states. The growing importance to the requirement of transparency in businesses was the motivation to study Transparency in SHGs. This paper persents a framework for transparency and also outlines the implementation of transparency through Member Behavioral Model (MBM) and Task Execution Cycle (TEC).

A. B. Sagar

Classification of Text Documents Using B-Tree

In this paper, we propose an unconventional method of representing and classifying text documents, which preserves the sequence of term occurrence in a test document. The term sequence is effectively preserved with the help of a novel datastructure called ‘Status Matrix’. In addition, in order to avoid sequential matching during classification, we propose to index the terms in B-tree, an efficient index scheme. Each term in B-tree is associated with a list of class labels of those documents which contain the term. Further the corresponding classification technique has been proposed. To corroborate the efficacy of the proposed representation and status matrix based classification, we have conducted extensive experiments on various datasets.

B. S. Harish, D. S. Guru, S. Manjunath

Comparison between Different Feature Extraction Techniques to Identify the Emotion ‘Anger’ in Speech

In this paper, three different techniques of feature extraction for identification of emotion in speech have been compared. Traditional feature like LPCC (Linear Predictive Cepstral Coefficient) and MFCC (Mel Frequency Cepstral Coefficient) have been described. Linear features like LFPC which is FFT based have been explained. Finally TEO (Teager Energy Operator) based nonlinear LFPC features in both time and freqnency domain have been proposed and the performance of the proposed system is compared with the traditional features. The comparison of each approach is performed using SUSAS (Speech Under Simulated and Acid Stress) and ESMBS (Emotional Speech of Mandarin and Burmese Speakers) databases. It is observed that proposed system outperforms the traditional systems. Analysis will be carried for identification mainly of the emotion ‘Anger’ in this paper.

Bageshree V. Pathak, Ashish R. Panat

Feature Image Generation Using Energy Distribution for Face Recognition in Transform Domain

In this paper, we propose a feature image generation method for face recognition. Feature extraction is done using three transforms viz. Discrete Cosine Transform, Slant Transform and Walsh Transform. Energy distribution defined as magnitude of effective information is used to create a feature image in transform domain by retaining high energy distribution coefficients. The proposed method consists of three steps. First, the face images are transformed into the frequency domain. Second, transformed coefficient matrix and energy distribution matrix is divided into three equal regions. Thresholds are selected in each region to retain the most significant features. Finally feature image is generated from these coefficients. Recognition is performed on generated feature images using Mahalanobis distance. Experimental results shows that the proposed method improve the face recognition rate as compared to previously proposed methods.

Vikas Maheshkar, Sushila Kamble, Suneeta Agarwal, Vinay Kumar Srivastava

A Comparative Study of Placement of Processor on Silicon and Thermal Analysis

Today when we have stepped into the second decade of this century, the integrated circuits are getting more and more complex with multicore processors. With technology scaling, more devices are being integrated into a small area. As a result, heat dissipation in integrated circuits (ICs) has increased. The processor is one of the highest heat generating components in an IC. The temperature generated in an integrated circuit varies with factors like number of processors, processor modes, their dimensions and arrangement on Silicon. In this paper we are presenting two simulation results. First one was obtained by analyzing how the area occupied by processor affects the temperature distribution. This study is extremely important as the area occupied by processors scales down with technology. The second study was to find out how the processor location and modes can affect temperature distribution in multicore processors. The processors at 2.4GHz frequency were analyzed in both active and idle modes. The highest and lowest temperatures and the location of hotspot in each case were analyzed.

C. Ramya Menon, Vinod Pangracious

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