IADIS Research Contributor

1 This research activity is partially funded by Ministerio de Educación y Ciencia under the project number TSI2005–06413. Next generation services and networks require information and communications systems able to support context-awareness applications and especially pervasive services. This paper present research challenges in context-awareness and context information modelling rules for supporting management operations within pervasive services into the framework of information systems interoperability. Logic-based rules for context information are discussed and studied and then the system architecture for context handling and delivery of context information using logic models is presented. Logic- based information modelling techniques with semantic enrichment are presented as one of the most proper for pervasive applications in the framework of distributed context information handling and delivery for data query-oriented applications. We support the idea of end user‘s applications and the management complexity of such services as well as communications networks, following the states streaked by logic models.

in blind source separation1 David Blanco, Diego P. Ruiz, María C. Carrion, Carlos García- Puntonet+

The steepest descendent is the non-linear optimiza-tion method most used in ICA algorithms. The method is used to fi nd the unmixing matrix, which solves the problem and is a minimum of a non-linear cost function. In this paper the use of quasi-Newton optimization methods, instead of gradient-type ICA methods, is studied. These methods can increase the speed of the method what it is corroborated by simulations.

Method of Images Benabdellah Mohammed, Gharbi Mourad, Zahid Nourddine, Regragui Fakhita, Bouyakhf El Houssine1 1Laboratoire d’Informatique, Mathématiques Appliquées, Intelligence Artificielle et Reconnaissance de Formes, Fa- culté des sciences de Rabat-Agdal, Maroc. 2Laboratoire de Conception et Systèmes, Faculté des scien- ces de Rabat-Agdal, Maroc. Researcher

The transmission and the transfer of images, in free spaces and on lines, must satisfy two objectives which are: the reduction of the volume of information to free, the maximum possible, the public networks of communication, and the protection in order to guaran- tee a level of optimum safety. The standard techniques of encryp- tion are not appropriate for the par ticular case of the images. For this we have proposed a new hybrid approach of encryp- tion-compression (FMT-AES), which is based on the AES encryp- tion algorithm of the dominant coef ficients, in a mixed-scale rep- resentation, of compression by the Faber-Schauder Multi-scale Transformation. The comparison of this approach with other methods of encryption-compression, such as Quadtree-AES and DCT-partial-encryption, showed its good performance.

Regulatory Interactions with the VBEM Algorithm Isabel M. Tienda-Luna, Maria C. Carrion Perez ♣, Diego P. Ruiz Padillo ♣, Yufang Yin, Yufei Huang

In this paper we perform a study of the performance of the VBEM algorithm proposed in [19]. The VBEM is a Bayesian approach for reconstructing gene regulat ory networks (GRNs) based on microarray data. We focus on a variable selection formulation and devel op a solution by a variational Bayes Expecta- tion Maximization (VBEM) learning rule. The major advantag e of the VBEM solution over Monte Carlo sampling based approach is its lower computational complex ity. This makes it appealing for uncovering large networks. The suitability of the proposed algorithm t o infer large networks is studied in terms of its ROC curves.

El MOHAJIR Mohammed, OUBENAALLA Youness

This paper describes the geo-spatial multidimensional database architecture we built to construct a regional air quality decision-support system. The system retrieves data from three main categories of system sources: a numerical atmospheric model, in -situ detectors and satellites. We worked on an idealized case study for which we established spatial multidimensional OLAP cubes on specific measures and dimensions. This sche ma aims to provide original an alysis like deviations of the concentration simulated by the atmospheric model pe r region, per date and pe r pollutant. Cartographic representation of the results is then achieved by using the SOLAP approach. Thematic maps are generated as a response to a particular query that the end user may submit. A range of options are offered to explore these charts in both space and time. Cartographic contours are not based on pre-defined images but are dynamically elaborated from the numerical coordinates stored in the spatial dimension. Qualities of the design and implementation are finally assessed according to recognized criteria established by the OLAP/SOLAP community as scalabi lity, time response a nd data exploration intuitiveness.

Overlapping Data Sets Using Maximum Entropy Principle A. O. Ammor, A. Lachkar

Many validity indexes have been proposed for evaluating clustering results. They usually have a tendency to fail in selecting the right number of clusters when dealing with overlapping clusters such as the IRIS data. To overcome this limitation, we propose in this paper, a new cluster validity index based on Maximum Entropy Principle, named V MEP. VMEP allows finding the correct number of clusters, and can deal successfully with or without the presence of overlap, even when this later is higher between clusters. Many simulated and real examples are presented, showing the superiority of V MEP to the existing indexes.

Faculté d’Electronique et Informatique, Laboratoire de Traitement d’Images et Rayonnement Atmosphérique, BP 32 El Alia Bab-ezzouar, Alger Researcher, Algérie Researcher

This paper presents a new learning algorithm for the fuzzy adaptive resonance theory. The modification allows us to supervise the fuzzy ART and to simplify ARTMAP network. It consists to find network’s parameters (comparison, training and vigilance) which gave the minimum quadratic distances between the output of the training base and those obtained by the network. A comparative study of these two parameterized network and an third modified fuzzy ARTMAP are done. In this last network, learning is done differently. We don’t take account of the eight (08) values of network’s parameters. As application we carried out a classification of the image of Algiers’s bay taken by SPOT XS. The results of this study presented in the forms of curves, tables and images show that modified fuzzy ARTMAP presents the best compromise quality/computing time.

Design Using Advanced CAD Tools1 Said Gaoua (1), Farah A. Mohammadi (2), Mustapha C.E. Yagoub (3)

Because of the increasing demand for ever-higher level of electronic device integration and miniaturization, modern design requires massive computational tasks during simulation, optimization and statistical analyses, requiring robust modeling tools so that the whole process can be achieved reliably. In this paper, the authors developed advanced computer-aided design tools to efficiently model devices such as transistors and succe ssfully predict the overall circuit performance. The proposed tools are demonstrated through examples.

Pedro Isaías

Editorial preface for Volume 4, Issue 1 of the IADIS International Journal on Computer Science and Information Systems (IJCSIS). This issue brings together peer-reviewed original research contributions covering the wide spectrum of Information Systems, Artificial Intelligence, Software Engineering, and Digital Transformation.