Scholarly

A Study of the Effectiveness of the Routing Decision Support Algorithm

Year: 2007 Volume: 1 Issue: 7 2159 - 2164 Pages

Abstract: Multi criteria decision making (MCDM) methods like analytic hierarchy process, ELECTRE and multi-attribute utility theory are critically studied. They have irregularities in terms of the reliability of ranking of the best alternatives. The Routing Decision Support (RDS) algorithm is trying to improve some of their deficiencies. This paper gives a mathematical verification that the RDS algorithm conforms to the test criteria for an effective MCDM method when a linear preference function is considered.

Predicting the Three Major Dimensions of the Learner-s Emotions from Brainwaves

Year: 2007 Volume: 1 Issue: 7 2152 - 2158 Pages

Abstract: This paper investigates how the use of machine learning techniques can significantly predict the three major dimensions of learner-s emotions (pleasure, arousal and dominance) from brainwaves. This study has adopted an experimentation in which participants were exposed to a set of pictures from the International Affective Picture System (IAPS) while their electrical brain activity was recorded with an electroencephalogram (EEG). The pictures were already rated in a previous study via the affective rating system Self-Assessment Manikin (SAM) to assess the three dimensions of pleasure, arousal, and dominance. For each picture, we took the mean of these values for all subjects used in this previous study and associated them to the recorded brainwaves of the participants in our study. Correlation and regression analyses confirmed the hypothesis that brainwave measures could significantly predict emotional dimensions. This can be very useful in the case of impassive, taciturn or disabled learners. Standard classification techniques were used to assess the reliability of the automatic detection of learners- three major dimensions from the brainwaves. We discuss the results and the pertinence of such a method to assess learner-s emotions and integrate it into a brainwavesensing Intelligent Tutoring System.

Post Mining- Discovering Valid Rules from Different Sized Data Sources

Year: 2007 Volume: 1 Issue: 7 2145 - 2151 Pages

Abstract: A big organization may have multiple branches spread across different locations. Processing of data from these branches becomes a huge task when innumerable transactions take place. Also, branches may be reluctant to forward their data for centralized processing but are ready to pass their association rules. Local mining may also generate a large amount of rules. Further, it is not practically possible for all local data sources to be of the same size. A model is proposed for discovering valid rules from different sized data sources where the valid rules are high weighted rules. These rules can be obtained from the high frequency rules generated from each of the data sources. A data source selection procedure is considered in order to efficiently synthesize rules. Support Equalization is another method proposed which focuses on eliminating low frequency rules at the local sites itself thus reducing the rules by a significant amount.

The Rank-scaled Mutation Rate for Genetic Algorithms

Year: 2007 Volume: 1 Issue: 7 2140 - 2144 Pages

Abstract: A novel method of individual level adaptive mutation rate control called the rank-scaled mutation rate for genetic algorithms is introduced. The rank-scaled mutation rate controlled genetic algorithm varies the mutation parameters based on the rank of each individual within the population. Thereby the distribution of the fitness of the papulation is taken into consideration in forming the new mutation rates. The best fit mutate at the lowest rate and the least fit mutate at the highest rate. The complexity of the algorithm is of the order of an individual adaptation scheme and is lower than that of a self-adaptation scheme. The proposed algorithm is tested on two common problems, namely, numerical optimization of a function and the traveling salesman problem. The results show that the proposed algorithm outperforms both the fixed and deterministic mutation rate schemes. It is best suited for problems with several local optimum solutions without a high demand for excessive mutation rates.

Issues and Architecture for Supporting Data Warehouse Queries in Web Portals

Year: 2007 Volume: 1 Issue: 7 2134 - 2139 Pages

Abstract: Data Warehousing tools have become very popular and currently many of them have moved to Web-based user interfaces to make it easier to access and use the tools. The next step is to enable these tools to be used within a portal framework. The portal framework consists of pages having several small windows that contain individual data warehouse query results. There are several issues that need to be considered when designing the architecture for a portal enabled data warehouse query tool. Some issues need special techniques that can overcome the limitations that are imposed by the nature of data warehouse queries. Issues such as single sign-on, query result caching and sharing, customization, scheduling and authorization need to be considered. This paper discusses such issues and suggests an architecture to support data warehouse queries within Web portal frameworks.

A Phenomic Algorithm for Reconstruction of Gene Networks

Year: 2007 Volume: 1 Issue: 7 2128 - 2133 Pages

Abstract: The goal of Gene Expression Analysis is to understand the processes that underlie the regulatory networks and pathways controlling inter-cellular and intra-cellular activities. In recent times microarray datasets are extensively used for this purpose. The scope of such analysis has broadened in recent times towards reconstruction of gene networks and other holistic approaches of Systems Biology. Evolutionary methods are proving to be successful in such problems and a number of such methods have been proposed. However all these methods are based on processing of genotypic information. Towards this end, there is a need to develop evolutionary methods that address phenotypic interactions together with genotypic interactions. We present a novel evolutionary approach, called Phenomic algorithm, wherein the focus is on phenotypic interaction. We use the expression profiles of genes to model the interactions between them at the phenotypic level. We apply this algorithm to the yeast sporulation dataset and show that the algorithm can identify gene networks with relative ease.

A File Splitting Technique for Reducing the Entropy of Text Files

Year: 2007 Volume: 1 Issue: 7 2123 - 2127 Pages

Abstract: A novel file splitting technique for the reduction of the nth-order entropy of text files is proposed. The technique is based on mapping the original text file into a non-ASCII binary file using a new codeword assignment method and then the resulting binary file is split into several subfiles each contains one or more bits from each codeword of the mapped binary file. The statistical properties of the subfiles are studied and it is found that they reflect the statistical properties of the original text file which is not the case when the ASCII code is used as a mapper. The nth-order entropy of these subfiles are determined and it is found that the sum of their entropies is less than that of the original text file for the same values of extensions. These interesting statistical properties of the resulting subfiles can be used to achieve better compression ratios when conventional compression techniques are applied to these subfiles individually and on a bit-wise basis rather than on character-wise basis.

An Intelligent Human-Computer Interaction System for Decision Support

Year: 2007 Volume: 1 Issue: 7 2113 - 2122 Pages

Abstract: This paper proposes a novel architecture for developing decision support systems. Unlike conventional decision support systems, the proposed architecture endeavors to reveal the decision-making process such that humans' subjectivity can be incorporated into a computerized system and, at the same time, to preserve the capability of the computerized system in processing information objectively. A number of techniques used in developing the decision support system are elaborated to make the decisionmarking process transparent. These include procedures for high dimensional data visualization, pattern classification, prediction, and evolutionary computational search. An artificial data set is first employed to compare the proposed approach with other methods. A simulated handwritten data set and a real data set on liver disease diagnosis are then employed to evaluate the efficacy of the proposed approach. The results are analyzed and discussed. The potentials of the proposed architecture as a useful decision support system are demonstrated.

Implementing Authentication Protocol for Exchanging Encrypted Messages via an Authentication Server Based on Elliptic Curve Cryptography with the ElGamal-s Algorithm

Year: 2007 Volume: 1 Issue: 7 2107 - 2112 Pages

Abstract: In this paper the authors propose a protocol, which uses Elliptic Curve Cryptography (ECC) based on the ElGamal-s algorithm, for sending small amounts of data via an authentication server. The innovation of this approach is that there is no need for a symmetric algorithm or a safe communication channel such as SSL. The reason that ECC has been chosen instead of RSA is that it provides a methodology for obtaining high-speed implementations of authentication protocols and encrypted mail techniques while using fewer bits for the keys. This means that ECC systems require smaller chip size and less power consumption. The proposed protocol has been implemented in Java to analyse its features and vulnerabilities in the real world.

Tracking Activity of Real Individuals in Web Logs

Year: 2007 Volume: 1 Issue: 7 2101 - 2106 Pages

Abstract: This paper describes an enhanced cookie-based method for counting the visitors of web sites by using a web log processing system that aims to cope with the ambitious goal of creating countrywide statistics about the browsing practices of real human individuals. The focus is put on describing a new more efficient way of detecting human beings behind web users by placing different identifiers on the client computers. We briefly introduce our processing system designed to handle the massive amount of data records continuously gathered from the most important content providers of the Hungary. We conclude by showing statistics of different time spans comparing the efficiency of multiple visitor counting methods to the one presented here, and some interesting charts about content providers and web usage based on real data recorded in 2007 will also be presented.

Two Approaches to Code Mobility in an Agent-based E-commerce System

Year: 2007 Volume: 1 Issue: 7 2094 - 2100 Pages

Abstract: Recently, a model multi-agent e-commerce system based on mobile buyer agents and transfer of strategy modules was proposed. In this paper a different approach to code mobility is introduced, where agent mobility is replaced by local agent creation supplemented by similar code mobility as in the original proposal. UML diagrams of agents involved in the new approach to mobility and the augmented system activity diagram are presented and discussed.

A Web Oriented Watermarking Protocol

Year: 2007 Volume: 1 Issue: 7 2088 - 2093 Pages

Abstract: This paper presents a watermarking protocol able to solve the well-known “customer-s right problem" and “unbinding problem". In particular, the protocol has been purposely designed to be adopted in a web context, where users wanting to buy digital contents are usually neither provided with digital certificates issued by certification authorities (CAs) nor able to autonomously perform specific security actions. Furthermore, the protocol enables users to keep their identities unexposed during web transactions as well as allows guilty buyers, i.e. who are responsible distributors of illegal replicas, to be unambiguously identified. Finally, the protocol has been designed so that web content providers (CPs) can exploit copyright protection services supplied by web service providers (SPs) in a security context. Thus, CPs can take advantage of complex services without having to directly implement them.

A Novel Metric for Performance Evaluation of Image Fusion Algorithms

Year: 2007 Volume: 1 Issue: 7 2082 - 2087 Pages

Abstract: In this paper, we present a novel objective nonreference performance assessment algorithm for image fusion. It takes into account local measurements to estimate how well the important information in the source images is represented by the fused image. The metric is based on the Universal Image Quality Index and uses the similarity between blocks of pixels in the input images and the fused image as the weighting factors for the metrics. Experimental results confirm that the values of the proposed metrics correlate well with the subjective quality of the fused images, giving a significant improvement over standard measures based on mean squared error and mutual information.

Mining of Interesting Prediction Rules with Uniform Two-Level Genetic Algorithm

Year: 2007 Volume: 1 Issue: 7 2076 - 2081 Pages

Abstract: The main goal of data mining is to extract accurate, comprehensible and interesting knowledge from databases that may be considered as large search spaces. In this paper, a new, efficient type of Genetic Algorithm (GA) called uniform two-level GA is proposed as a search strategy to discover truly interesting, high-level prediction rules, a difficult problem and relatively little researched, rather than discovering classification knowledge as usual in the literatures. The proposed method uses the advantage of uniform population method and addresses the task of generalized rule induction that can be regarded as a generalization of the task of classification. Although the task of generalized rule induction requires a lot of computations, which is usually not satisfied with the normal algorithms, it was demonstrated that this method increased the performance of GAs and rapidly found interesting rules.

Application of the Virtual Reality Modeling Language for Design of Automated Workplaces

Year: 2007 Volume: 1 Issue: 7 2072 - 2075 Pages

Authors:
Jozef Novak-Marcincin

Abstract: Virtual Reality Modelling Language (VRML) is description language, which belongs to a field Window on World virtual reality system. The file, which is in VRML format, can be interpreted by VRML explorer in three-dimensional scene. VRML was created with aim to represent virtual reality on Internet easier. Development of 3D graphic is connected with Silicon Graphic Corporation. VRML 2.0 is the file format for describing interactive 3D scenes and objects. It can be used in collaboration with www, can be used for 3D complex representations creating of scenes, products or VR applications VRML 2.0 enables represent static and animated objects too. Interesting application of VRML is in area of manufacturing systems presentation.

A Quantum-Inspired Evolutionary Algorithm forMultiobjective Image Segmentation

Year: 2007 Volume: 1 Issue: 7 2069 - 2071 Pages

Abstract: In this paper we present a new approach to deal with image segmentation. The fact that a single segmentation result do not generally allow a higher level process to take into account all the elements included in the image has motivated the consideration of image segmentation as a multiobjective optimization problem. The proposed algorithm adopts a split/merge strategy that uses the result of the k-means algorithm as input for a quantum evolutionary algorithm to establish a set of non-dominated solutions. The evaluation is made simultaneously according to two distinct features: intra-region homogeneity and inter-region heterogeneity. The experimentation of the new approach on natural images has proved its efficiency and usefulness.

A Robust LS-SVM Regression

Year: 2007 Volume: 1 Issue: 7 2063 - 2068 Pages

Abstract: In comparison to the original SVM, which involves a quadratic programming task; LS–SVM simplifies the required computation, but unfortunately the sparseness of standard SVM is lost. Another problem is that LS-SVM is only optimal if the training samples are corrupted by Gaussian noise. In Least Squares SVM (LS–SVM), the nonlinear solution is obtained, by first mapping the input vector to a high dimensional kernel space in a nonlinear fashion, where the solution is calculated from a linear equation set. In this paper a geometric view of the kernel space is introduced, which enables us to develop a new formulation to achieve a sparse and robust estimate.

Automatic Clustering of Gene Ontology by Genetic Algorithm

Year: 2007 Volume: 1 Issue: 7 2053 - 2062 Pages

Abstract: Nowadays, Gene Ontology has been used widely by many researchers for biological data mining and information retrieval, integration of biological databases, finding genes, and incorporating knowledge in the Gene Ontology for gene clustering. However, the increase in size of the Gene Ontology has caused problems in maintaining and processing them. One way to obtain their accessibility is by clustering them into fragmented groups. Clustering the Gene Ontology is a difficult combinatorial problem and can be modeled as a graph partitioning problem. Additionally, deciding the number k of clusters to use is not easily perceived and is a hard algorithmic problem. Therefore, an approach for solving the automatic clustering of the Gene Ontology is proposed by incorporating cohesion-and-coupling metric into a hybrid algorithm consisting of a genetic algorithm and a split-and-merge algorithm. Experimental results and an example of modularized Gene Ontology in RDF/XML format are given to illustrate the effectiveness of the algorithm.

An Edge-based Text Region Extraction Algorithm for Indoor Mobile Robot Navigation

Year: 2007 Volume: 1 Issue: 7 2045 - 2052 Pages

Abstract: Using bottom-up image processing algorithms to predict human eye fixations and extract the relevant embedded information in images has been widely applied in the design of active machine vision systems. Scene text is an important feature to be extracted, especially in vision-based mobile robot navigation as many potential landmarks such as nameplates and information signs contain text. This paper proposes an edge-based text region extraction algorithm, which is robust with respect to font sizes, styles, color/intensity, orientations, and effects of illumination, reflections, shadows, perspective distortion, and the complexity of image backgrounds. Performance of the proposed algorithm is compared against a number of widely used text localization algorithms and the results show that this method can quickly and effectively localize and extract text regions from real scenes and can be used in mobile robot navigation under an indoor environment to detect text based landmarks.

Optimal Image Compression Based on Sign and Magnitude Coding of Wavelet Coefficients

Year: 2007 Volume: 1 Issue: 7 2036 - 2044 Pages

Abstract: Wavelet transforms is a very powerful tools for image compression. One of its advantage is the provision of both spatial and frequency localization of image energy. However, wavelet transform coefficients are defined by both a magnitude and sign. While algorithms exist for efficiently coding the magnitude of the transform coefficients, they are not efficient for the coding of their sign. It is generally assumed that there is no compression gain to be obtained from the coding of the sign. Only recently have some authors begun to investigate the sign of wavelet coefficients in image coding. Some authors have assumed that the sign information bit of wavelet coefficients may be encoded with the estimated probability of 0.5; the same assumption concerns the refinement information bit. In this paper, we propose a new method for Separate Sign Coding (SSC) of wavelet image coefficients. The sign and the magnitude of wavelet image coefficients are examined to obtain their online probabilities. We use the scalar quantization in which the information of the wavelet coefficient to belong to the lower or to the upper sub-interval in the uncertainly interval is also examined. We show that the sign information and the refinement information may be encoded by the probability of approximately 0.5 only after about five bit planes. Two maps are separately entropy encoded: the sign map and the magnitude map. The refinement information of the wavelet coefficient to belong to the lower or to the upper sub-interval in the uncertainly interval is also entropy encoded. An algorithm is developed and simulations are performed on three standard images in grey scale: Lena, Barbara and Cameraman. Five scales are performed using the biorthogonal wavelet transform 9/7 filter bank. The obtained results are compared to JPEG2000 standard in terms of peak signal to noise ration (PSNR) for the three images and in terms of subjective quality (visual quality). It is shown that the proposed method outperforms the JPEG2000. The proposed method is also compared to other codec in the literature. It is shown that the proposed method is very successful and shows its performance in term of PSNR.

International Journal of Information, Control and Computer Sciences

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