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International Review on Computers and Software - March 2011 (Vol. 6 N. 2) - Papers

One Improved Kind of l-Resolution for Medium Predicate Logic
Evolutionary-Generated Watermark for Robust Digital Image Watermarking in DCT_SVD Domain
Face Detection using Fuzzy and Wavelet Neural Network
A Hybrid Electrocardiogram Denoising Technique based on Continuous Wavelet Transform and Forward Wavelet Transform Translation Invariant
Monolingual Dictionary Semantic Capturing using Concept Lattice
Statistical and Template Matching Features for Persian Handwritten Postal Code Recognition
Development of a Constraint based Sequential Pattern Mining Tool
Ontological Representation Models for Adaptive Hypermedia Construction
A Repair-less Genetic Algorithm for Scheduling Tasks onto Dynamically Reconfigurable Hardware
A New Nanometric Reversible Full Subtractor Gate
H∞ Fuzzy Variable Structure Control for T-S Model Based Induciton Motor Drive System
Hardware Architectures & Designs for Projective Elliptic Curves Point Addition Operation using Variable Levels of Parallelism
New Approach Multicriteria MPLS Networks: Design and Implementation
Error Concealment using Joint Multiple Description Coding and Zero Padding
Managing Software Project Risks with Proposed Regression Model Techniques and Effect Size Technique
Accelerating the BEMD by reducing the Number of Extrema Points to Interpolate in the SP
An Overview of Artificial Immune System Algorithms for Industrial Monitoring
Multi-Objective Minimization of Test Suite and its Cost Associates using Swarm Intelligence
Real-Time Management System for Airline Operations

International Review on Computers and Software - Papers

One Improved Kind of l-Resolution for Medium Predicate Logic
by Sheng-li Zhang, Zheng-hua Pan

Vol. 6. n. 2, pp. 150-154

Abstract - For the medium predicate logic system MF, Pan proposed the infinite valued semantic interpretation which showed the variable procedure of two opposite concepts. However, this sort of infinite valued semantic interpretation never reflects “~A true when A fuz”. On which based, this paper further investigates and gives out one improved kind of infinite valued semantic interpretation as the truth value range is [0, λ)U(λ,1] (λ Î (0.5, 1)) for MF, and redefines the notion of the literal in MF. In this paper, one improved kind of λ-resolution for MF is proposed and the completeness of which is proved. From this paper, it is easy to obtain that the situation which is “~A true when A fuz” is better reflected in terms of the new infinite valued semantic interpretation of MF.

Keywords: Medium Predicate Logic,Resolution Principle, λ-Interpretation, λ-Resolution Principle.

Evolutionary-Generated Watermark for Robust Digital Image Watermarking in DCT_SVD Domain
by F.Golshan, K.Mohammdi

Vol. 6. n. 2, pp. 155-161

Abstract - In this paper, a novel intelligent watermarking algorithm for digital images has been proposed. In digital image watermarking, robustness and imperceptibility compete with each other. We applied a DCT_SVD based intelligent algorithm to make a tradeoff between these two functions. The algorithm initially transforms some special 8×8 blocks of original image into DCT domain. Then SVD decomposition is applied to coefficients and a binary watermark image is embedded into the singular values of DCT coefficients. The novelty of our proposed method is that the binary watermark image is obtained from an evolutionary algorithm such as Genetic Algorithm to solve the optimization problem between robustness and imperceptibility. So the watermark is variable and image adaptive. The proposed method is robust and the final watermark can survive on several attacks such as filtering, noise contaminating, JPEG compression and some geometrical attacks like rotation, cropping and rescaling .Experimental results show improvement in imperceptibility and robustness in comparison with a recently similar existing work.

Keywords: Digital Image Watermarking, DCT, SVD, Genetic Algorithm.

Face Detection using Fuzzy and Wavelet Neural Network

by Mohammad Hassan Safavi Pour, Mohammad Ali Doostari, Javad Askari

Vol. 6. n. 2, pp. 162-167

Abstract - This paper presents a new method for face detection in color images. In the proposed method, the regions with skin color of color images are identified using tuning a filter by means of fuzzy logic theory. In fact, the accuracy of the filter is improved using fuzzy logic in order to set a parameter in the filter. Then, the face is extracted from the obtained areas by means of using wavelet neural network.

Keywords: Face Detection, Skin Color, Fuzzy Logic, Wavelet Neural Network.

A Hybrid Electrocardiogram Denoising Technique based on Continuous Wavelet Transform and Forward Wavelet Transform Translation Invariant
by Salah Hadji, Mourad Talbi, Akram Aouinat, Noureddine Ellouze, Adnène Cherif

Vol. 6. n. 2, pp. 168-172

Abstract - In this paper, we propose a denoising scheme of ECG signal based on smoothing of continuous wavelet transform coefficients. To evaluate the proposed technique, we compare it to Smoothing Translation Invariant Denoising Procedure recTI. Performance evaluation uses parameters like signal to noise ratio (SNR) and mean square error (MSE). The preliminary tests of the two denoising techniques application were made on the ECG signals of MIT-BIH database. The obtained results from the SNR and MSE computations show that the proposed technique outperforms the denoising technique based on recTI.

Keywords: Recti, Wavelet Transform, Denoising, Thresholding, ECG Signal.QRS Complex.

Monolingual Dictionary Semantic Capturing using Concept Lattice
by A. Meštrović, M. Čubrilo

Vol. 6. n. 2, pp. 173-184

Abstract - This paper proposes an approach for retrieving semantic relationships between semantic units in a monolingual dictionary. The presented approach is based on the usage of formal concept analysis (FCA) technique for determining semantic relations and hierarchy in a set of words extracted from dictionary. In the first phase the formal grammar for words and the extraction of their attributes from Croatian language monolingual dictionary is defined. In our approach grammar rules include graphical properties of dictionary text. In the second phase a technique of using formal concept analysis for the capturing of semantic overlapping is modeled. The models are represented in F-logic language and implemented using FLORA-2 system. The focus of this paper is on the whole transformation process of a set of words from the dictionary into the concept lattice. The concept lattice as the final result shows semantic relationships and overlapping in a set of words.

Keywords: Formal Concept Analysis, Concept Lattice, F-Logic, Formal Grammar, Synonym Extraction, Dictionary, Semantic.

Statistical and Template Matching Features for Persian Handwritten Postal Code Recognition
by Z. Kamranian, S. A. Monadjemi, N. Nemat Bakhsh

Vol. 6. n. 2, pp. 185-190

Abstract - Postal code recognition can be an important step in the post offices automation. In this paper, a recognition system based on statistical and template matching approaches to recognize Persian handwritten postal codes on postal envelopes is presented. The system consists of pre-processing, feature extraction, and classification stages. Pre-processing is fully automated for envelopes with a postcode frame. For feature extraction, we use statistical and template-matching features. Moreover, a MLP neural network with one hidden layer is trained using back-propagation algorithm as the classifier. Furthermore, we propose a voting algorithm employing several neural networks results to develop the classification performance. Evaluating the proposed system with approximately 2100 test samples, the recognition rate of 97.75% is achieved.

Keywords: Persian OCR, Statistical features, Template matching, MLP Neural Network, Voting Algorithm, Postal Code, Handwritten.

Development of a Constraint based Sequential Pattern Mining Tool
by G. Yılmaz, B. Y. Badur, S. Mardikyan

Vol. 6. n. 2, pp. 191-198

Abstract - Sequential pattern mining is an important data mining task with wide applications. In traditional sequential pattern mining, the purpose is to discover sequences that are frequent. The main disadvantages of the traditional algorithms such as Generalized Sequential Patterns (GSP) are the lack of focus on user expectations and the high number of discovered patterns. Constraint based data mining technique is an efficient solution as it limits the patterns within a set of conditions based on the requirements of the user. Despite the importance of constraint based sequential pattern mining, a constraint based data mining tool that handles many of the user-specified constraints simultaneously does not exist in the literature. The aim of this study is to develop a constraint based sequential pattern mining algorithm and a new constraint based sequential pattern mining tool named as CBSPM (Constraint Based Sequential Pattern Mining) which handles a set of user-specified constraints simultaneously. A data generator facility is also developed for generating artificial sequential datasets. The verification test is conducted and the sensitivity of execution times on various parameters is examined. Performance tests showed that the execution time increases with the number of sequences and the number of items in sequences. On the other hand, increasing the minimum support threshold and adding the user specified constraints increase the performance of the tool.

Keywords: Data Mining, Sequential Pattern Mining, Constraint Based Mining, Sequential Pattern Mining Tool.

Ontological Representation Models for Adaptive Hypermedia Construction
by Amel Behaz, Mahieddine Djoudi

Vol. 6. n. 2, pp. 199-205

Abstract - The objective of the works presented in this article is to study how we can integrate models from cognitive theories and ontologies for the construction of adaptive hypermedia. The goal is to provide the system capacity enabling it to carry out reasoning on descriptions obtained in order to automatically adapt resources and services offered to a learner based on preferences learning styles. We present ontology of domain. A learner ontology based on the theory of psychological types of MBTI (Myers-Briggs Type Indicator). Finally, we present a model of adaptation that generates personalized content by applying rules of structure and presentation.
Copyright © 2011 Praise Worthy Prize S.r.l. - All rights reserved

Keywords: Adaptive Hypermedia, Knowledge Engineering, Semantic Web, Ontology, Learner Modeling, MBTI.

A Repair-less Genetic Algorithm for Scheduling Tasks onto Dynamically Reconfigurable Hardware

by Morteza Mollajafari, Hadi Shahriar Shahhoseini

Vol. 6. n. 2, pp. 206-212

Abstract - Current reconfigurable systems suffer from a significant overhead due to the time it takes to reconfigure their hardware. In order to deal with this overhead, it is important to develop scheduling algorithms to minimize the execution time of a set of dependent tasks in a dynamically reconfigurable hardware. Many heuristic methods exist which find suboptimal schedules for multiprocessor systems but for dynamically reconfigurable devices it is more complicated to find such schedules because there are configurations other than tasks that need to be scheduled. GA has demonstrated considerable success in providing efficient solutions to many NP-hard optimization problems.
In this paper a new genetic algorithm approach to reconfigurable hardware problems is introduced. This method uses a novel genotype to phenotype conversion instead of direct genotype decoding of the problem so that not only always produces valid solutions and eliminates repairing phase, but also allows neutrality and results further fitness improvement. To prove the efficiency of the proposed method we compared it with standard GA and List Scheduler and the Exhaustive Search method was taken as a criterion. The performance of these methods is validated using a number of random task graphs. Experimental results show that he proposed method, standard GA and List Scheduler’s average error in comparison with Exhaustive Search are 0.75%, 8.01% and 22.95% respectively and as the execution time point of view; our method is 41% faster than the standard GA.

Keywords: : Genetic Algorithm, Genotype to Phenotype Mapping, Reconfigurable Systems, Scheduling.

A New Nanometric Reversible Full Subtractor Gate
by Majid Haghparast, Ghasem Sheikh Jabbari

Vol. 6. n. 2, pp. 213-218

Abstract - Reversible circuits have large application in communication, computer graphics, signal processing, cryptography and so on. It’s play special role in quantum computing and systems need energy saving. In designing circuits’ base on nanotechnology and low power VLSI technology, reversibility is very important. In this circuits number of input vectors is equal output vectors. Due to one to one relationship between inputs and outputs, this gates (circuits) save energy. In this paper we propose a new Reversible Gate, GHNG. The proposed GHNG is a 4*4 Reversible gate and can be used as a full subtractor. As we know designing of reversible gates is important and useful for quantum computer designing. In this paper a new design of Half Subtractor using from one FG and one NTG proposed. We also offer a full subtractor based on the proposed GHNG gate. A 4 bit parallel full subtractor is also suggested. The GHNG gate can implement all Boolean functions.

Keywords: Reversible Logic Gates, Reversible Full Subtractor, Quantum Computing, Reversible Computing, Nanotechnology.

H∞ Fuzzy Variable Structure Control for T-S Model Based Induciton Motor Drive System
by Yongjian Li, Xizheng Zhang, Yaonan Wang

Vol. 6. n. 2, pp. 219-226

Abstract - An H∞ fuzzy variable structure control (HFVSC) scheme based on T-S models was proposed in this paper for the Induction Motor (IM) in order to solve speed tracking problem. A T-S fuzzy model was firstly formed to represent the nonlinear system of IM. For converting the tracking control into a stabilization problem, a new control design was proposed to define the internal desired states. Then, the HFVSC controller for IM system with parameters variation and load disturbances was designed based on this fuzzy model, where the derivations of feedback gains were formulated in terms of linear matrix inequalities (LMIs). The HFVSC scheme can drive the dynamics of IM into a designated sliding surface in finite time and guarantee the H∞ performance. Simulation results, associated with versatile command profiles and load conditions, show that the proposed system achieves satisfactory performance from the viewpoint of tracking accuracy and disturbance rejection.

Keywords: Induction Motor, Uncertain T-S Nonlinear Systems, Variable Structure Control, H∞ Control, Linear Matrix Inequalities (Lmis).

Hardware Architectures & Designs for Projective Elliptic Curves Point Addition Operation using Variable Levels of Parallelism
by Mohammad Khatib, Qasem Abu Al-Haija, Azmi Jaafar

Vol. 6. n. 2, pp. 227-236

Abstract - Although ECC protocol is considered one of the most secure schemes for information security; it also suffers in its arithmetic computations from the modular inversion operation which is known to be time consuming operation. In the addition operation, Many ECC designs that use projective coordinates over GF (p) have not considered a balance between area, hardware utilization, and performance factors which is important in many ECC applications. In this research we proposed to use the projective coordinates systems to compute the ECC point addition operation with no inversion operations due to the ability to convert each inversion to several multiplication operations that can be applied in parallel. We also present several architectures and design choices for point addition operation that will help to build ECC Coprocessor. These architectures consider different levels of parallelism which may give different choices in ECC design in terms of time and space. This paper proposes the different hardware architectures to design ECC Processor by varying the degree of parallelization benefiting from the inherent parallelism for ECC addition operation. It was shown that the throughput of the design with 4 parallel multipliers enhanced the system performance by 400% and 340% for both projections (X/Z, Y/Z), and (X/Z2, Y/Z3) respectively while the design with 5 parallel multipliers is considered the best fit for projection (X/Z, Y/Z2) due its ability to best utilize and parallelize the hardware arithmetic operations. However, the projection (X/Z, Y/Z) when applied using 4 parallel multipliers gave the best results in terms of hardware utilization, parallelization enhancements and cost factor which make it the first choice when you design the ECC Coprocessor using projective coordinates. A trade-off between security, area and performance is which control the ECC Coprocessor design, the more parallelization you make the more area needed the less time required which will lead to a better performance.

Keywords: Elliptic Curves Cryptography, Projective Coordinates, Point Addition.

New Approach Multicriteria MPLS Networks: Design and Implementation
by J. Oubaha, A. Habbani, M. Elkoutbi

Vol. 6. n. 2, pp. 237-243

Abstract - At the time when the evolution of the network and the diversity of Internet applications that require duplication of effort within the supplier to adapt the available resources with the needs and optimize resources. Our research aims to investigate the implication of the improvement of routing protocols over MPLS networks that supports multi-criteria for each package which is designed a percentage weight affected to criteria for each application ensuring the multirouting priority to applications, that require a specific service, This allows a better service differentiation, and provides load balancing. For optimization the base information label of MPLS backbone our proposition is the integration of Distributed Multi Criteria Routing (DMCR) protocol.

Keywords: Optimization, Quality of Service, Label Information Label(LIB), MPLS, Routing Protocol and DMCR.

Error Concealment using Joint Multiple Description Coding and Zero Padding
by Ali Farzamnia, Sharifah Kamilah, Norsheila Fisal

Vol. 6. n. 2, pp. 244-249

Abstract - There has been an increasing usage of Multiple Description Coding (MDC) for error concealment in non ideal channels. This paper attempts to conceal the error and reconstruct the lost descriptions by combining MDC and DCT transform with zero padding. At first DCT is applied to image then zeros are added to rows and columns of the image in the DCT domain. The obtained image from this process has lots of correlation between their pixels. After this process the image is down sampled to 4 sub images and DCT transform is used to map image pixels to transform domain and then by using multiple description scalar quantization (MDSQ) each sub image is quantized and converted to 2 descriptions. So finally there are eight descriptions gained after MDSQ. These data are transmitted into channel. At the receiver side these descriptions are added together but if some of descriptions corrupted or damaged because of channel failure, by taking average of other received descriptions, corrupted descriptions are reconstructed (error concealing method). Then inverse DCT is applied to subimages. By upsampling 4 obtained subimages, reconstructed image is gained. Simulations results show that PSNR values and subjective evaluations are increased as compared to other methods. Since zero padding is used, correlations of image pixels are increased. So quantization variance is low.

Keywords: DCT Transform, Multiple Description Scalar Quantization, Zero Padding.

Managing Software Project Risks with Proposed Regression Model Techniques and Effect Size Technique
by Abdelrafe Elzamly, Burairah Hussin

Vol. 6. n. 2, pp. 250-263

Abstract - Regardless how much effort we put for the success of software projects, many software projects have very high failure rate and Risks are everywhere in life and most assuredly during the life of software projects. Risk is not always avoidable, but it is controllable. The aim of this paper is to present new techniques by which we can study the impact of different control factors and different risk factors on software projects risk and we knew how to deliver good quality solutions. The new technique uses the regression test and effect size test proposed to managing the risks in a software project and reducing risk with software process improvement. Fourteen risk factors and eighteen control factors were used in this paper. The nine of fourteen factors mitigated by using control factors. The study has been conducted on a group of managers. Successful project risk management will greatly improve the probability of project success.

Keywords: Software Project Management, Risk Management, Risk Factors, Risk Controls, Regression model Techniques and Effect Size Technique.

Accelerating the BEMD by reducing the Number of Extrema Points to Interpolate in the SP
by A. Sabri, S. Senhaji, A. Aarab

Vol. 6. n. 2, pp. 264-268

Abstract - The Bidimensionnal Empirical Mode Decomposition (BEMD) is an auto-adaptive image decomposition. The basic idea is to decompose images into a redundant set of components denoted IMFs; each component has a zero local mean. Researches prove that it is a very powerful tool for multi-scale analysis of non stationary and non linear signals. The Interpolation is regarded as a delicate stage in the decomposition process. The Radial Basis Functions (RBFs) has been presented as the better technique to interpolate scattered data points. But the use of RBFs in the sifting process involves a large number of iterations to compute the two envelopes; which implies a high computation time especially when decomposing large images. To overcome this inconvenient and to accelerate the decomposition, in this paper we propose to reduce significatively the number of iterations in the sifting process based on the proprieties of the IMFs: first we propose to reduce the extrema points to interpolate based on the zero-crossing propriety of the IMFs, and then we will estimate the value of the pixels without interpolation based on the oscillation propriety of the IMFs.

Keywords: BEMD, IMF, Sifting Process, Interpolation, Extrema Points, Rbfs, Computational Time.

An Overview of Artificial Immune System Algorithms for Industrial Monitoring
by A. Abdelhadi, L. H. Mouss

Vol. 6. n. 2, pp. 269-274

Abstract – We describe in this paper an overview of artificial immune system algorithms to solve the classification problem in industrial monitoring. We present artificial immune system algorithms, starting with the negative selection that happens to be a rich source of inspiration. We also, detail the clonal selection algorithm, which is based on the clonal selection theory. Finally, we detail other algorithms based of agent including the immune system and dendritic cell algorithm. In the end, we summarize the differences and similarities of the works discussed and we conclude on the prospects related to the approach of the algorithms of artificial immune systems for industrial monitoring to solve the classification problem.

Keywords: Industrial monitoring, Natural immune system, artificial immune system, antigens, antibodies, B cells, classification.

Multi-Objective Minimization of Test Suite and its Cost Associates using Swarm Intelligence
by S. Selvakumar, N. Ramaraj

Vol. 6. n. 2, pp. 275-285

Abstract – Software testing is particularly expensive for developers of high-assurance software, such as software that is produced for mission critical systems. One reason for this expense is the system requirement that test suites be modified to provide condition or decision coverage completely. Despite its cost, there is evidence that coverage technique is an effective verification method and can help to reduce the size of the test suite. To address the test-suite size problem, researchers have investigated the use of test-suite minimization algorithms, which identify a reduced test suite that provides the same coverage of the software according to some criterion as the original test suite, and test-suite prioritization algorithms, which identify an ordering of the test cases in the test suite according to some criteria or goals. Existing techniques for test suite minimization consider test-case coverage criteria, other criteria such as risk or fault–detection effectiveness, or combinations of these criteria, but ignore the test-execution cost because of the complexity. This paper investigates the use of swarm intelligence called Particle Swarm Optimization over conventional evolutionary approach, for this test-suite minimization problem. Unlike other algorithms, this algorithm uses new criteria, which is a combination of a block based coverage criteria and a test-execution cost criteria, to make decisions about reducing a test suite. Finally, the results generated were studied by comparing with Genetic based Test suite minimization algorithm. The outcome illustrate that this algorithm can significantly reduce the size and the cost of the test-suite for regression testing. This paper focuses on multiple objectives to reduce the test-execution cost and the size of the reduced test suite rather than only the size as done by conventional methods.

Keywords: Test Suite Minimization, Test Suite Reduction, Particle Swarm Optimization, Test-Execution Cost.

Real-Time Management System for Airline Operations
by M. Abd Allah Makhlouf, M. Elsayed Waheed

Vol. 6. n. 2, pp. 286-298

Abstract - Through the day of operations Control Center (OCC) in an airline monitors all the flights checking if they follow the schedule that was previously defined by other areas of the company. Some problems may arise during this stage related with crew members, aircrafts and passengers. OCC includes teams of experts specialized in solving the above problems, seeking for solutions that minimize the negative impact on passengers, at the same time, minimizing the operational costs. This paper proposes a system that represents and handles all the OCC teams’ actions, the coordination and negotiation processes between all OCC members to solve the schedule disruptions allowing them to take faster and better decisions. It shows how such a system can be designed using an object-Oriented and software engineering methodology and presents the implementation of the system in a real airline company, using widely available tools for airline professionals. The proposed system called BAMS (Broadcast Actions and Management System) and its implementation results indicate that real-time operation monitoring can potentially reduce delays and costs occurring from airline operations and measure the robustness of the airline schedule and the reasons of interruptions.

Keywords: Airline Operation, Flight Management, Delay Propagation; Real-Time Management System.