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International Review on Computers and Software - July  2010 - Papers



         Special Section on "Advanced Artificial Neural Network Approaches with Applications to System Management"





International Review on Computers and Software - Papers


go to top   A Computer Aided Lexicography Tool for Making Dictionaries on Historical Principles
         by Saad Harous, Sane M. Yagi, Jim Yaghi

         Vol. 5. n. 4, pp. 363-369


Abstract - Despite the long standing tradition of lexicography that Arabic prides itself on, the language does not have a dictionary that states the origin of words and that traces their development across time. Several attempts have been made at it recently but failed, resulting in frustration and in the conclusion that the task is daunting. The main reason for failure is the sheer volume of work required. In this paper, we present a computational tool that would facilitate the compilation of an Arabic dictionary on historical principles. There are no openly available tools for Arabic dictionary making; if they do exist, they are jealously guarded for their commercial value; hence, they are unavailable to scholars who might want to take part in the grand endeavor of building an etymological Arabic dictionary. This research shall make its tool available to the open source community to encourage further development and refinement. The computational tool can also be used in the development of computer-assisted language learning software. Concordances, for example, are by-products of this research, yet they are invaluable to the teaching of grammar and morphology; they encourage learning by discovery.
Copyright © 2010 Praise Worthy Prize S.r.l. - All rights reserved


Keywords: Arabic, Dictionary, Computational Lexicography, Morphology, Computational Tool, CALL.



go to top   The Sound Compression Model Using a Discrete Wavelet Transform and a Dynamic Gammachirp Psychoacoustic Model
         by Khalil Abid, Kais Ouni, Noureddine Ellouze
         Vol. 5. n. 4, pp. 370-383


Abstract - Audio compression algorithms are used to obtain compact digital representations of high-fidelity audio signals for the purpose of efficient transmission over larger distances and storage.This paper presents an audio coder for real-time mutimedia applications. This coder applies a discrete wavelet transform to decompose audio test files into subbands to eliminate redundant data using spectral and temporal masking properties. This architecture is combined with a psychoacoustic model characterised by an external and middle ear model as a first part and a dynamic Gammachirp filter as a second part whose connections are selected in order to come close to the critical bands of the ear . Experimental results show the best performance of this architecture.

Copyright © 2010 Praise Worthy Prize S.r.l. - All rights reserved


Keywords: Audio Compression, Discret Wavelet Transform, Psychoacousic Model, External and Middle Ear Model, Dynamic Gammachirp Filter Bank, MUSHRA Test.



go to top   A New PCA-based Face Authentication Approach for Smart-Card Implementation
         by  A. Sehad, N. Bessah, I.Touari, Y.Benfattoum, H.Khali, M.Cheriet

         Vol. 5. n. 4, pp. 384-389


Abstract - In this paper, we present a new PCA-based face verification approach for smart cards implementation. In fact, our scheme deals with the reduced storage space of smart cards. First of all the DCT2 and then the self Eigen face, are respectively applied for the training step and in the decision step, a new similarity index based on the weighted distance by the representation quality of individuals is used. Experimental results, using AR face database, show a better recognition rate compared to popular distances such as Euclidian, Manhattan and Mahalanobis.

Copyright © 2010 Praise Worthy Prize S.r.l. - All rights reserved


Keywords: Biometrics, Face recognition, PCA, Eigen faces, Smart card, Similarity index.



go to top   Telerobotic on Internet - Case Study: Mobile Robot
         by F. Moutaouakkil, A. Sayouti, H. Medromi

         Vol. 5. n. 4, pp. 390-395


Abstract - Telerobotics actually result from the merger of two originally separate areas that are teleoperation and robotics. Indeed, autonomous robotics are not yet fully developed, the robot must now be operated remotely by a human operator. We must therefore take into account the principles developed in teleoperation. However, as the robot can perform basic tasks independently, it is called telerobotics rather than teleoperation. Telerobotics has applications wherever man has difficulty working directly (hostile environment, too far or too small places) and the tasks are sufficiently complex or unpredictable to be an obstacle to full automation. The main condition for the development of telerobotics is the ability to compete with the direct intervention of humans or the use of an automated highly specialized. In the first case, the advantage of telerobotics is firstly the replacement of human labor painful or dangerous by another, more secure and more comfortable. In the second case, we must show the interest of a material more versatile than the automatic system dedicated to the proposed application.

Copyright © 2010 Praise Worthy Prize S.r.l. - All rights reserved


Keywords: Teleoperation, Telerobotics, Internet, Multi-agent System.



go to top   A Modified DBD System for Scheduling Jobs in a Wafer Fabrication Factory

         by Toly Chen, Chun-Ho Lin

         Vol. 5. n. 4, pp. 396-405


Abstract - Job scheduling (or dispatching) in a wafer fabrication factory is an extremely difficult task. For this reason, a modified dynamic-bottleneck-detection (MDBD) approach is proposed in this study. The MDBD approach is modified from the well-known DBD approach with some innovative treatments. First, for non-bottleneck and bottleneck machines, different scheduling approaches are applied. Second, the remaining cycle time of a job was estimated by applying an advanced data-mining approach to improve the estimation accuracy. Third, the content of the modified DBD approach can be tailored to the wafer fabrication factory. To evaluate the effectiveness of the proposed methodology, production simulation was also applied in this study. According to the experimental results, the proposed methodology outperformed some existing approaches in reducing the average cycle time and cycle time standard deviation.

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Keywords: DBD, Wafer fabrication, Scheduling, Fuzzy, Neural, Tailored, Simulation.



go to top   WAP Based Remote Controlling and Monitoring System

         by Majdi Oraiqat, Mahdi Nisirat, Igried D. M. Al-Khawaldeh, Liyth A Nissirat, Mohammed A. Nisirat

         Vol. 5. n. 4, pp. 406-409


Abstract - General Packet Radio Service (GPRS) has become the most popular system for data communication in mobile phones. Recently, it enables a wide range of engineering applications to be implemented such as remote patient status monitoring. In this application, the ECG signal can be transmitted for monitoring, consulting, and health care. Another area of interest that has a promising application is industrial machine remote monitoring and controlling. This paper presents a new remote industrial machine monitoring and controlling system based on Wireless Application Protocol (WAP) over GPRS technology. This system consists of an interface circuit, internet enabled computer, WAP enabled handheld device (mobile phone). In this paper, the industrial machine is resembled by a data acquisition card. This card is developed and implemented using successive approximation Analogue to Digital Converter (ADC). This converter is used to convert the values of a room temperature and light intensity. The new implemented scheme has the advantages of simplicity and the ability to control the phone functionality using the impeded WML script and WML libraries.

Copyright © 2010 Praise Worthy Prize S.r.l. - All rights reserved


Keywords: GPRS, WAP, WML, XML, Industrial Machine remote controlling.



go to top   Software Protection of Microcontrollers Against EMI - A Case Study
         by R. M. Alaoui, S. Baffreau, E. Sicard,L. Bouhouch

         Vol. 5. n. 4, pp. 410-422


Abstract - This paper deals with different software-based strategies allowing the detection of bit flip errors arising in compact microcomputer-based digital architectures as the consequence of electromagnetic disturbances. A 16-bit microcontroller used in embedded electronic systems for automotive applications is analyzed using a standard immunity method for integrated circuits, namely the IEC 62132 Direct Power Injection method. The failure criteria is the ripple of the nominal output signal delivered by the microcontroller reaching 20% of its nominal voltage level, or by the jitter reaching 20% of the nominal period. Embedded software exploiting the analog-digital conversion, mathematical unit and output ports with and without detection and protection techniques are implemented and their impact on the IC susceptibility from 1 MHz to 1 GHz are investigated. Fault injection experiments demonstrate the software detection capabilities and limitations of the hardware protections and the studied techniques, for almost all the frequency band, with detection sensitivity upto 25 dBm, that is a factor larger than 100 in interference amplitude.

Copyright © 2010 Praise Worthy Prize S.r.l. - All rights reserved


Keywords: EMI, EMC, Microcontroller, Susceptibility, Defensive Software, Detection Algorithm.



go to top   An SVM Based System for Automatic Dates Sorting
         by Djeffal Abdelhamid, Babahenini Mohamed Chaouki, Taleb Ahmed Abdelmalik

         Vol. 5. n. 4, pp. 423-428


Abstract - In this work, we present an automatic sorting dates system based on a statistical learning technique called Support vector machine. This system is developed to be used in factories of the region of Biskra working on dates sorting and packaging. Our system analyses dates images acquired by a camera and builds a features database. The SVM technique uses then this database to search hyperplans which separate better different dates’ classes in features space. Hyperplans are used to classify new dates images. Obtained results show SVM power in dates’ images classification and validate proposed system against similar sorting systems.

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Keywords: Image classification, dates sorting, support vector machine.



go to top   Olympics Bidimensional Empirical Mode Decomposition: Using a Novel Approach of Envelope Estimation
         by A. Benkuider, H. Tairi, A. Aarab

         Vol. 5. n. 4, pp. 429-435


Abstract - In this work, we propose a new approach for Bidimensional Empirical Mode Decomposition called the Olympics BEMD (OBEMD). The BEMD is an extension of the Empirical Mode Decomposition (EMD), which can decompose non-linear and non-stationary signals into basis functions called the Intrinsic Modes Functions (IMFs). IMFs are monocomponent functions that have well defined instantaneous frequencies. EMD is a sifting process that is non-parametric and data driven; it does not depend on a priori basis set. BEMD decomposes an image into two-dimension BIMFs. The procedure of decomposition is iterative. The 2D sifting process is performed in two steps: extrema detection by neighbour windows or morphological operators and surface interpolation by Radial Basis Functions (RBF). The RBF interpolation is applied to a set of local maxima (minima) points to form the upper (lower) envelope. But 2D data interpolation methods cause massive computation time and other artefacts in the decomposition. In this context, this paper suggested a new simple, efficient and fast method of envelope estimation that replaces the surface interpolation. In this method, we use an Olympics filter to calculate the mean envelop and he presented the comparison with the BEMD and the Fast and Adaptive BEMD (FABEMD). Moreover, it preserves the totality of information in term of the quality of the constructed image by using the entropy function. The performance of this approach, using the OBEMD, is demonstrated with both synthetic and natural images. The experimental results indicate that our approach is as better than BEMD and the FABEMD.

Copyright © 2010 Praise Worthy Prize S.r.l. - All rights reserved


Keywords: EMD, BEMD, FABEMD, BIMF, IMF, RBF, neighbour windows, morphological, filter Olympics.



go to top   An FPGA-Based Implementation of Fixed-Point Standard-LMS Algorithm with Low Resource Utilization and Fast Convergence
         by Omid Sharifi Tehrani, Mohsen Ashourian, Payman Moallem

         Vol. 5. n. 4, pp. 436-444


Abstract - An FPGA-based fixed-point standard-LMS algorithm core is proposed for adaptive signal processing (ASP) realization in real time. The LMS core is designed in VHDL93 language as basis of FIR adaptive filter. FIR adaptive filters are mostly used because of their low computation costs and linear phase. The proposed model uses 12-bit word-length for input data from analog to digital converter (ADC) chip while internal computations are based on 17-bit word-length because of considering guard bits to prevent overflow. The designed core is FPGA-brand-independent so that it can be implemented on any brand to create a system-on-programmable-chip (SoPC). In this paper, XILINX SPARTAN3E and VIRTEX4 FPGA series are used as implementation platform. Rounding errors were inevitable due to limited word-length and can be decreased by adjusting the dynamic range of input signal amplitude. A comparison is made between DSP, Hardware/Software co-design and pure-hardware implementations. Obtained results show improvements in area-resource utilization, convergence speed and performance in the designed pure-hardware LMS core. Although using a pure-hardware implementation results in high performance, it is much more complex than other structures.

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Keywords: FIR Adaptive Filter, FPGA, LMS Algorithm Core, SoPC.



go to top   Partition-Based Bandwidth Management for Mobile WiMAX IEEE802.16e
         by  D. S. Shu’aibu, S. K. Syed-Yusof, N. Fisal

         Vol. 5. n. 4, pp. 445-452


Abstract - Due to robust wireless channel, bandwidth management has become an important issue in wireless broadband networks such as WiMAX. To ensure an efficient bandwidth management and quality of service achieved to subscriber station (ss) in WiMAX, an efficient admission control is required to monitor the traffics and manages the bandwidth while the SS are continuously entering and leaving the network. In this paper, we present bandwidth partition approach to bandwidth management through call admission control for mobile WiMAX. The bandwidth was partitioned into three, thus; constant partition, variable partition and partition for handover traffics. Simulation results showed that partition-based bandwidth management outperformed the Adaptive bandwidth management.

Copyright © 2010 Praise Worthy Prize S.r.l. - All rights reserved


Keywords: Admission Control, Blockage Probability, Dropping Probability, Flow Acceptance, Partition Base, Adaptive Base, QoS.



Special Section on “Advanced Artificial Neural Network Approaches with Applications to System Management” - Papers


go to top   Preface to the Special Section
         by Toly Chen

         Vol. 5. n. 4, pp. 453



go to top   Slope Stability During Earthquakes: a Neural Network Application
         by Mert Tolon, Derin N. Ural

         Vol. 5. n. 4, pp. 454-459


Abstract - In this manuscript 170 slopes are analyzed utilizing an artificial intelligence approach. Five neural network architectures including the back propagation neural network architecture, general regression neural network, group method of data handling, Kohonen learning paradigm and probabilistic neural network architectures are used. The back propagation neural network architecture and the general regression neural network demonstrated better applicability to the slope stability problem. Nine input parameters and one output parameter are used in the analysis. The output parameter is the factor of the safety of the slopes, the input parameters are the height of slope, the inclination of slope, the height of water level, the depth of firm base, the cohesion of soil, the friction angle of soil, the unit weight of soil, but the important input parameters are horizontal and vertical seismic coefficients. The importance of the seismic coefficients for a slope stability safety is presented. A sensitivity study is performed to assess the importance of the slope and dynamic input parameters.

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Keywords:  Slope, Stability, Artificial Neural Network, GRNN, Back propagation.



go to top   Fuzzy Logic Algorithm Applied in the Corporate Sustainability: Analysis of an Empirical Study in the Management of Suppliers
         by A. M. Gil Lafuente, L. Barcellos de Paula

         Vol. 5. n. 4, pp. 460-463


Abstract - Diverse scientific studies emphasize that the dialogue with stakeholders is one of the most important points in the area of sustainability in the companies. From the Theory of Stakeholders we will try to analyze the corporate sustainability and the process of suppliers' management of a company that owns the code of conduct in accordance with The Ten UN Global Compact Principles. With the accomplishment of an empirical study one tries to know the degree of fulfillment of the code of conduct on the part of the suppliers and the utility of a tool that facilitates decision making by the employer on the issue. To reach the proposed aim we will resort to the Theory of Affinities, across a model who allows the homogeneous group of variables certain levels. We will use basic elements of decision theory, notably the concepts of relation, as the affinities in the families of Moore and its representation through Galois lattices. The results will provide inputs to the theory of affinities bring to the sustainable management of suppliers.

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Keywords:  supplier management, sustainability, The UN Global Compact, Stakeholder Theory, Logic Fuzzy, Theory of Affinities.



go to top   Developing a Hybrid Forecasting Model for Body Fat
         by Yuehjen E. Shao

         Vol. 5. n. 4, pp. 464-469


Abstract - The measurement of body fat is one of the important assessments of human health. The measuring process of the body fat often required a trained technician and/or expensive equipments. This results in a complicated and inconvenient way of measuring of body fat. This study is motivated to develop a fruitful hybrid forecasting model for the prediction of the body fat. The proposed hybrid model consists of the regression and the artificial neural network components. The regression component of the hybrid model is established for selection of the influential variables, and the artificial neural network component is then designed for generation of the forecasts based on those influential variables. A real data set of the body fat is used for demonstration of the superiority of the proposed hybrid model.

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Keywords:  Hybrid model, Regression, Artificial neural networks, Body fat.



go to top   Swarm Mobile MPLS for Efficient Micro-Mobility Management with QoS in Next Generation Network
         by Merzoug Ghali, Fatima Bendella

         Vol. 5. n. 4, pp. 470-475


Abstract - One of the major challenges for the next generation mobile systems is related to efficient mobility management. Mobile IP (MIP) provides a global framework for IP mobility management; however, it is not suitable for micro-mobility environments. Many domain-based micro-mobility management schemes have been proposed to overcome the limit of MIP. Recently there is a trend to use Multiple Protocol Label Switching (MPLS) to deal with mobility management. At the same time, artificial intelligence has proved its effectiveness in different areas by the use of techniques based on swarm intelligence. In this paper, we propose a new micro-mobility management scheme, called Swarm Mobile MPLS that supports both micro-mobility and quality-of-service (QoS) management in telecommunication networks. Our proposal includes Swarm intelligence technology in order to achieve a fast handoff mechanism with minimum packet loss and a signalling system with minimum registration.

Copyright © 2010 Praise Worthy Prize S.r.l. - All rights reserved


Keywords:  IP Mobility Management, MPLS, QoS, Micro-Mobility, Handoff, Swarm Intelligence.



go to top   Towards Human-like Machine Perception 2.0
         by Rosemarie Velik

         Vol. 5. n. 4, pp. 476-488


Abstract - Machine perception is a research field that is still in its infancy and is confronted with many unsolved problems. In contrast, humans generally perceive their environment without problems. These facts were the motivation to develop a bionic model for human-like machine perception, which is based on neuroscientific and neuropsychological research findings about the structural organization and function of the perceptual system of the human brain. Having systems available that are capable of a human-like perception of their environment would allow the automation of processes for which, today, human observers and their cognitive abilities are necessary. The challenge to be faced is to merge and interpret large amounts of data coming from different sources. For this purpose, an information processing principle called neuro-symbolic information processing is introduced using neuro-symbols as basic information processing units. Neuro-symbols are connected in a modular hierarchical fashion to a so-called neuro-symbolic network to process sensor data. The architecture of the neuro-symbolic network is derived from the structural organization of the perceptual system of the human brain. Connections and correlations between neuro-symbols can be acquired from examples in different learning phases. Besides sensor data processing, memory, knowledge, and focus of attention influence perception to resolve ambiguous sensory information and to devote processing power to relevant features.

Copyright © 2010 Praise Worthy Prize S.r.l. - All rights reserved


Keywords:  Machine Perception, Cognitive Computation, Neuro-cognitive Models, Neuro-symbolic Networks, Supervised Learning, Knowledge Integration, Focus of Attention, Binding Problem.



go to top   Fish Recognition Based on Robust Features Extraction from Size And Shape Measurements Using Back-Propagation Classifier
         by Mutasem khalil Alsmadi, Khairuddin Bin Omar, Shahrul Azman Noah

         Vol. 5. n. 4, pp. 489-494


Abstract - Problem statement: Image recognition is a challenging problem researchers had been research into this area for so long especially in the recent years, due to distortion, noise, segmentation errors, overlap and occlusion of objects in digital images. In our study, there are many fields concern with pattern recognition, for example, fingerprint verification, face recognition, iris discrimination, chromosome shape discrimination, optical character recognition, texture discrimination and speech recognition, the subject of pattern recognition appears. A system for recognizing isolated pattern of interest may be as an approach for dealing with such application. Scientists and engineers with interests in image processing and pattern recognition have developed various approaches to deal with digital image recognition problems such as, neural network, contour matching and statistics. Approach: In this study, our aim is to recognize an isolated pattern of interest in the image based on the combination between robust features extraction. Where depend on size and shape measurements, that are extracted by measuring the distance and geometrical measurements. Result: We presented a system prototype for dealing with such problem. The system started by acquiring an image containing pattern of fish, then the image features extraction is performed relying on size and shape measurements. Our system has been applied on 20 different fish families, each family has a different number of fish types and our sample consists of distinct 610 of fish images. These images are divided into two datasets: 500 training images and 110 testing images. An overall accuracy is obtained using the back-propagation classifier was 86% on the test dataset used. Conclusion: We developed a classifier for fish images recognition. We efficiently have chosen a features extraction method to fit our demands. Our classifier successfully design and implement a decision which performed efficiently without any problems. Eventually, the classifier is able to categorize the given fish into its cluster and categorize the clustered fish into its poison or non-poison fish and categorizes the poison and non-poison fish into its family.

Copyright © 2010 Praise Worthy Prize S.r.l. - All rights reserved


Keywords:  Neural network, ANN, feature extraction, distance and geometrical measurements, digital image recognition and feed forward back propagation classifier, poison and non-poison fish.



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