April 2010, No. 2
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A Data Mashup for Dynamic Composition of Adaptive Courses

Mohammed Al-Zoube and Baha Khasawneh
Princess Sumaya University for Technology, Jordan

Abstract: This paper presents a novel adaptive course composition system that based on mashing up learning content in a web application. The system includes three major components, static course system, data mashup, and adaptive course composer. The first system enables lecturers to build multiple lesson courses that are managed with corresponding APIs including documents stored in Google docs or videos located at YouTube. The data mashup utilizes some web and search engines APIs in which learners can search for relevant web content and display it in a grid layout. The adaptive course composer uses learning object from the data mashup to build adaptive course based on learner preferences. It uses a selected number of the IEEE LOM to sort the learning objects according to their educational role, difficulty level, or rating, and hence, eliminate the use of course domain ontology.

Keywords: Data mashups, adaptive course composition, Google apps, learning objects.

Received November 16, 2008; accepted December 1, 2008

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Applicability of Telemedicine in Bangladesh: Current Status and Future Prospects

Ahasanun Nessa, Moshaddique Al Ameen, Sana Ullah, and Kyung Kwak
Graduate School of IT and Telecommunications, Inha University, Korea

Abstract: Telemedicine refers to the use of information and communication technology to provide and support health care mainly for the purpose of providing consultation. It is also a way to provide medical procedures and examinations to remote locations. It has the potential to improve the accessing to quality health care services and delivery while lowering costs even in the places with scarcity of resources. Understanding the potentiality of telemedicine, many developing countries are implementing it to provide health care facility to remote areas where health care facilities are poor. Bangladesh is not an exception to this either. In this paper we mention the reasons why Bangladesh has to move for telemedicine. We also present the past and on-going telemedicine activities and projects in Bangladesh. Analyzing these projects we have found out some factors which should be assessed carefully for successful implementation of telemedicine application. Considering Bangladesh telecommunication infrastructure, finally we propose a prototype telemedicine network that can improve health facilities through telemedicine by making a connection between rural health facility providers and special hospitals.

Keywords: Telemedicine, information and communication technology, telemedicine implementation.

Received October 4, 2008; accepted November 25, 2008

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Voice Disorders Identification Using Multilayer Neural Network

Lotfi Salhi, Talbi Mourad, and Adnene Cherif
 Signal Processing Laboratory Sciences Faculty of Tunis, University Tunis ElManar, Tunisia

Abstract: In this paper we present a new method for voice disorders classification based on multilayer neural network. The processing algorithm is based on a hybrid technique which uses the wavelets energy coefficients as input of the multilayer neural network. The training step uses a speech database of several pathological and normal voices collected from the national hospital “Rabta - Tunis” and was conducted in a supervised mode for discrimination of normal and pathology voices and in a second step classification between neural and vocal pathologies (Parkinson, Alzheimer, laryngeal, dyslexia…). Several simulation results will be presented in function of the disease and will be compared with the clinical diagnosis in order to have an objective evaluation of the developed tool.

Keywords: Speech processing, pathological voices, classification, wavelet transform, neural networks, energy.

Received August 27, 2008; accepted December 28, 2008
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Enhanced Quicksort Algorithm

Rami Mansi
Department of Computer Science, Al al-Bayt University, Jordan

Abstract:  Sorting is considered as one of the important issues of computer science. Although there is a huge number of sorting algorithms, sorting problem has attracted a great deal of research; because efficient sorting is important to optimize the use of other algorithms. It is also often in producing human-readable output. This paper presents a new sorting algorithm called SMS-algorithm (Scan, Move, and Sort). The SMS algorithm is considered as an enhancement on the Quicksort algorithm in the best, average, and worst cases when dealing with an input array of a large size and when the maximum and the minimum values were small, especially when sorting a list of distinct elements. The SMS algorithm is compared with the Quicksort algorithm and the results were promising.

Keywords: SMS algorithm, Quicksort algorithm, large size array, distinct elements, time complexity, space complexity.

Received August 25, 2008; accepted September 25, 2008
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An Unsupervised Artificial Neural Network Method for Satellite Image Segmentation

Mohamad Awad
National Council for Scientific Research, Center for Remote Sensing, Lebanon

Abstract: Image segmentation is an essential step in image processing. The goal of segmentation is to simplify and/or to change the representation of an image into a form easier to analyze. Many image segmentation methods are available but most of these methods are not suitable for satellite images and they require a priori knowledge. In order to overcome these obstacles, a new satellite image segmentation method is developed using an unsupervised artificial neural network method called Kohonen's self-organizing map and a threshold technique. Self-organizing map is used to organize pixels according to grey level values of multiple bands into groups then a threshold technique is used to cluster the image into disjoint regions, this new method is called TSOM. Experiments performed on two different satellite images confirm the stability, homogeneity, and the efficiency (speed wise) of TSOM method with comparison to the iterative self-organizing data analysis method. The stability and homogeneity of both methods are determined using a procedure selected from the functional model.

Keywords: Artificial neural network, segmentation, unsupervised, remote sensing, satellite image.

Received August 14, 2008; accepted September 25, 2008
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Impact of CMMI Based Software Process Maturity on COCOMO II’s Effort Estimation

Majed Al Yahya, Rodina Ahmad, and Sai Lee
Department of Software Engineering, University of Malaya, Malaysia

Abstract: The software capability maturity model has become a popular model for enhancing software development processes with the goal of developing high-quality software within budget and schedule. The software cost estimation model, constructive cost model, in its last update (constructive cost model II) has a set of seventeen cost drivers and a set of five scale factors. Process maturity is one of the five scale factors and its ratings are based on software capability maturity model. This paper examines the effect of process maturity on software development effort by deriving a new set of constructive cost model II’s PMAT rating values based on the most recent version of CMM, i.e., capability maturity model integration. The precise data for the analysis was collected from the record of 40 historical projects which spanned the range of capability maturity model integration levels, from level 1 (lower half and upper half) to level 4, where eight data points were collected from each level. We followed the ideal scale factor method in order to withhold the effect of the constructive cost model II’s PMAT scale factor. All prediction accuracies were measured using PRED. The study showed that the proposed model (with the new PMAT rating values) yielded better estimates as compared to the generic , constructive cost model II model’s estimates.

Keywords: Effort estimation, scale factor, cost driver, COCOMO, SW-CMM, CMMI.

Received November 8, 2008; accepted December 15, 2008

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Credit Scoring Models Using Soft Computing Methods: A Survey

Adel Lahsasna, Raja Noor Ainon, and Teh Ying Wah
Faculty of Computer Science and Information Technology, Malaya

Abstract: During the last fifteen years, soft computing methods have been successfully applied in building powerful and flexible credit scoring models and have been suggested to be a possible alternative to statistical methods. In this survey, the main soft computing methods applied in credit scoring models are presented and the advantages as well as the limitations of each method are outlined. The main modelling issues are discussed especially from the data mining point of view. The study concludes with a series of suggestions of other methods to be investigated for credit scoring modelling.

Keywords: Credit scoring, credit risk, soft computing, data mining.

Received August 4, 2008; accepted September 25, 2008
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Deriving Conceptual Schema from Domain Ontology: A Web Application Reverse Engineering Approach

Sidi Benslimane, Mimoun Malki, and Djelloul Bouchiha
Computer Science Department, University of Sidi Bel Abbes, Algeria

Abstract: The heterogeneous and dynamic nature of components making up a web application, the lack of effective programming mechanisms for implementing basic software engineering principles in it, and undisciplined development processes induced by the high pressure of a very short time-to-market, make web application maintenance a challenging problem. A relevant issue consists of reusing the methodological and technological experience in the sector of traditional software maintenance, and exploring the opportunity of using reverse engineering to support effective web application maintenance. This paper presents reverse engineering approach that help to understand existing undocumented web applications to be maintained or evolved, through the extraction from  domain ontology of conceptual schema describing a web application.  The advantage of using ontology for conceptual data modelling is the reusability of domain knowledge. As a result of it the conceptual data model will be made faster, easier and with fewer errors than creating conceptual data model in usual way. We demonstrate the value of the approach by providing an implementation that exhibits appropriate characteristics.

Keywords: Reverse engineering, web application, ontology, conceptual schema, conceptual modeling.

Received July 29, 2008; accepted December 23, 2008

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Hiding Text Information in a Digital Image Based on Entropy Function

Nasser Hamad
Faculty of Information Technology, Arab American University, Palestine

Abstract: The paper is concerned with hiding information into a digital image, specifically, an English text is used to be hidden into a digital grey-scale image. The purpose of this research is to embed a maximum text data size into the most suitable image selected among several images based on the binary entropy function measurements of both the text and image. The embedding process is constrained by minimising the bit error rate. Our results show that the binary entropy function can be considered as a powerful tool to select a proper image for a predetermined text under the BER constrain.

Keywords: Steganography techniques, flipping embedded text, binary entropy function.

Received July 13, 2008; accepted September 25, 2008

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Fast Cryptographic Privacy Preserving Association Rules Mining on Distributed Homogenous Database

Ashraf El-Sisi
Faculty of Computers and Information, Menofyia University, Egypt

Abstract: Privacy is one of the most important properties of an information system must satisfy, in which systems the need to share information among different, not trusted entities, the protection of sensible information has a relevant role. A relatively new trend shows that classical access control techniques are not sufficient to guarantee privacy when data mining techniques are used in a malicious way. Privacy preserving data mining algorithms have been recently introduced with the aim of preventing the discovery of sensible information. In this paper we propose a modification to privacy preserving association rule mining on distributed homogenous database algorithm. Our algorithm is faster than old one which modified with preserving privacy and accurate results. Modified algorithm is based on a semi-honest model with negligible collision probability. The flexibility to extend to any number of sites without any change in implementation can be achieved. And also any increase doesn’t add more time to algorithm because all client sites perform the mining in the same time so the overhead in communication time only. The total bit-communication cost for our algorithm is function in (N) sites.

Keywords: Association rule mining, Apriori, cryptography, distributed data mining, privacy, security.

Received July 9, 2008; accepted November 25, 2008
 
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A Test Procedure for Boundary Scan Circuitry in PLDs and FPGAs

Bashar Al-Khalifa
Department of Medical Instrumentation Engineering, Technical College, Iraq

 
Abstract: A test procedure for testing mainly the boundary scan cells, and testing partially the test access port controller in programmable logic devices, and field programmable gate array devices, is suggested. The test procedure involves; the configuration of programmable logic devices or field programmable gate array device, the application of test vectors, and finally the verification of the response. These steps are repeated with two different configurations of the device under test, to ensure high faults coverage. Both the configuration, and the application of test vectors, is performed through the joint test access group port of the device under test. The parts of the boundary scan circuit and the type of faults which are covered are mentioned.      

Keywords: Boundary scan circuit test, programmable logic devices, and test procedure.

Received July 1, 2008; accepted September 25, 2008
 
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Left Ventricle Tracking in Isotopic Ventriculography Using Statistical

Deformable Models
Nawres Khlifa, Said Ettaeib, Yosra Wahabi, and Kamel Hamrouni
Research Unit of Single Processing, Image Processing and Pattern Recognition, National Engineering School of Tunis, Tunisia

Abstract: The left ventricle tracking in planar scintigraphic images is an important step to study the coronary state. However, it is not as simple as we thought, because of the bad quality of these images. The study of the related work showed that classic methods based on low level image characteristics failed to localize the ventricle. In this paper, we suggest using a method based on a priori knowledge. Assuming that the human heart can appear in different images as one of a variety of possible shapes, we can incorporate the shape and the texture to delineate the boundaries of the left ventricle.

Keywords: Active shape model, active appearance model, planar nuclear image, tracking, left ventricule.

Received June 30, 2008; accepted February 25, 2009
 
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Leader Election Algorithm in 2D Torus Networks with the Presence of One Link Failure

Mohammed Refai1, Ahmad Sharieh2, and Fahad Alshammari3
1Sciences and Information Technology Collage, Zarqa Private University, Jordan
2King Abdullah II School for Information Technology, University of Jordan, Jordan
3Information Technology and Computer Science College, University of Malaya, Malaysia

Abstract: Leader election algorithms solve the instability problem in the network which is caused by leader failure .In this paper, we propose a new leader election algorithm in two dimensional torus networks. The algorithm aims to elect one node to be a new leader. The new leader is identified by some characteristics not in the other nodes in the network. When the process is terminated, the network is returned to a stable state with one node as leader where other nodes are aware of this leader. The new algorithm solves this problem despite the existence of one link failure.  In a network of N nodes connected by two dimensional torus network, the new algorithm uses O(N) messages to elect a new leader in O( ) time steps. These results are valid for both cases: simple case (when the leader failure is detected by one node) and in the worst case (when the failure is discovered by up to N-1 nodes).

Keywords: Concurrency, leader election, link failure, message complexity, 2D torus networks.
 
Received May 13, 2008; accepted November 25, 2008
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Implementation of Vector Directional Distance Rational Hybrid Filter Using TMS320C6416

 
Anis Boudabous1, Lazhar khriji2, and Nouri Masmoudi1
1Laboratory of Electronics and Information Technology, Tunisia
2Department of Electrical and Computer Engineering,  Sultan Qaboos University, Oman

Abstract: This paper proposes a novel digital signal processing implementation of vector directional distance rational hybrid filter for impulsive, Gaussian and mixed noise suppression and fine-details preservation in color images. The Implementation was done, initially, based on digital signal processing ,  which proves the need to a large execution time for filtering based on vector approach.  Then, we propose efficient optimizations and approximations of the main functions which have no influence on the filtered image quality. Indeed, we could increase the filtering speed compared to the initial vector directional distance rational hybrid filter implementation. Comparative studies of implemented vector directional distance rational hybrid filter with other nonlinear filters are reported. It demonstrates a good color image quality for different noise intensities. This efficient system implementation can perform well in several image processing applications.

Keywords: Color image, DSP, optimization, nonlinear filter.

Received July 3, 2008; accepted November 25, 2008
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