Jörg Roth University of Applied Sciences Nuremberg, Nuremberg, Germany Researcher

Location-based applications and services become increasingly important for mobile users. They take into account a mobile user's current location and provide a location-dependent output. To support developers of location-based services, the Nimbus framework hides specific details of positioning systems and provides uniform output containing physical as well as symbolic location information, which often are more suitable for applications and users. One basic problem is the Distributed Location Resolution Problem: given a location; which identifiable areas cover th is location, if area information is distributed among different servers? This paper presents an algorithm that solves this problem and runs in the dis- tributed, self-organizing Nimbus infrastructure.

Asaf Shupo, Miguel Vargas Martin University of Ontario Institute of Technology

Child pornography is an increasingly visible problem in society today. Methods currently employed to combat it may be considered primitive and inefficient, and legal and technical issues can exacerbate the problem significantly. We propose a network-based de tection system that us es a stochastic weak estimator coupled with a linear classifier, which is a ppropriate in this context due to the non-stationarity of the input data. Our experiments show that the sy stem is capable of distinguishing child pornography images from non-child pornography images even when the obscene image is redu ced to only 20% of its representation. This method for identifying offensive material is potentially attractive to law enforcement and can be accomplished with acceptable overhead. We believe our approach, with minor adaptations, is of independent interest for use in a number of network applications which benefit from packet classification beyond detecting child pornography. These include securi ty applications such as detecting malicious packets, and network anom alies consisting of dangerous tra ffic fluctuations, abusive use of certain services, and distributed denial-of-service attacks.

Mohammad Hassan Shirali-Shahreza Computer Engineering Department, Yazd University, Pejoohesh Street, Safa-ieh Researcher, P.O.Box 89195-, Yazd Researcher, IRAN Researcher

Nowadays, many daily human activities such as education, trade, talks, etc are done by using the Internet. In such things as registration on Internet web sites, hackers write programs to make automatic false registration that waste the resources of th e web sites while it may al so stop it from functioning. Therefore, human users should be distinguished fro m computer programs. To this end, this paper presents a method for distinction of Persian and Arabic-language users from computer programs based on Persian and Arabic texts. In th is method, the image of a Persian or Arabic word chosen from a dictionary is shown to the user and he is asked to type it. Considering that the presently available Persian and Arabic OCR programs cannot identify these words, the word can be identified only by a Persian or Arabic-language user. The proposed method has been implemented by the Java language.

Omar Flores Sánchez, Vicente E. Vidal Gimeno1 1Universidad Politécnica de Valencia, Departamento de Sistemas y Computación—DSIC, Camino de Vera s/n, Valencia Researcher, España 2Instituto Tecnológico de Tuxtepec, Departamento de Sistemas y Computación—DSC, Av. Dr. Victor Bravo Ahuja s/n, Col. 5 de Mayo, A.P., C.P. Researcher, Tuxtepec Researcher, Oaxaca Researcher, México Researcher

This paper discusses how High Performance Computi ng can help to solve Engineering problems, where it is necessary to reduce the execution time spent in the solution of sparse linear systems. We have chosen three free-distribution numeri cal parallel libraries called PETSc (Portable, Extensible Toolkit for Scientific Computation) [Satish2001], pARMS (Parallel Algebr aic Recursive Multilevel Solver) [Saad2003], and one direct sparse solver named SuperLU [Demmel2003]. These libraries have been applied to a realistic test case of Nuclear Engineering where it is necessary to solve efficiently very-large sparse linear systems to study steady-state neutr on diffusion processes. Nume rical experiments have shown the effectiveness of using parallel and distributed computing.

Kollayut Kaewbuadee Department of Computer Science.Thammasat University, Thailand Researcher

Functional Dependency (FD) is an important feature for referenc ing to the relationship between attributes and candidate keys in tuples. It also sh ows the relationship between entities in a data model (Calvanese et al. 2001). In research areas of data cleaning (Arenas et al. 1999; Bohannon et al. 2005), the FD is used for improving the data quality. In a data mining research, an FD discovery technique has been studied (Savnik and Flach 1993; Huhtala et al. 1999) . However, an FD discove ry could find too many FDs and, if use directly in a cl eaning process, could cause it to NP time (Bohannon et al. 2005). In this research, we have developed a cleaning engine by combining an FD discovery technique with data cleaning technique and use the feature in query optimization called “Selectivity Value” to decrease the number of discovered FDs. Testing results showed that this work can identi fy duplicates and anomalies with high recall and low false positive.

Hend S. Al-Khalifa, Hugh C. Davis Learning Technology Group- ECS- Southampton

Semantic Metadata, which describes the meaning of documents, can be produced either manually or else semi-automatically using information extraction techniques. Manual techniques are expensive if they rely on skilled cataloguers, but a po ssible alternative is to make use of community produced annotations such as those collected in folks onomies. This paper reports on an experiment that we carried out to validate the assumption that folksonomies contain hi gher semantic value than

Wolfgang Golubski Zwickau University of Applied Sciences, FB Physikalische Technik /

Mobile computing is one of the fast -growing fields of the current computer era. In this paper we present a middleware appropriated to the development of applic ations for mobile ad-hoc peer-to-peer networks. The proposed middleware implemen ts a communication service and an host respectively service discovery in fully decentralized networks. The design and the function of the middleware will be discussed. To argue the quality of the middleware we sketch the development of two services, a distributed card game and a chat application.

Deniss Kumlander Department of Informatics, Tallinn University of Technology, Raja St., Tallinn, Estonia Researcher

In this paper a practical algorit hm for finding the maximum clique is proposed. The maximum clique problem is well known to be NP-hard and is a core problem for a lot of applications in artificial intelligence systems, data mining and many others. The presented algorithm contains some additions to its earlier publications, which makes it much faster. It is based on colour classes and the backtracking technique. This paper includes a description of the algorithm, an example of its work and some analytical discussion topics. The algorithm is tested on DIMA CS graphs to compare it with other well-known algorithms. It has shown very good performance and is more than 1000 times faster than others best known algorithms on some graph types. Moreover certa in modifications of the heuristic colouring strategies described in the article produce even better algorithms for some graph types introducing a need for an artificial intelligence approach in the maximum clique finding algorithms’ implementations. The described algorithm is fast and easy to implement, which makes it very pr actical to apply in a plenty of areas.

Neda Abdolvand, Nasrollah Moghadam Charkari, Reza Mohammadi IT Eng.

Mobile telecommunications companies face the i ssues, including sever competition, and market saturation. Increasing customer loyalty has been introduced as a key solution, to guarantee the success of the business. Several researchers have explored th at customer satisfaction and switching barriers are influential elements of customer loyalty. They intr oduced several factor, which are essential to satisfy customers, and form switching barri ers. This study introduces m-co mmerce as a new opportunity that causes more loyalty of customers. In order to rationalize the use of m-commerce in the mobile telecommunication industry, a soluti on is proposed. This solution is based on the process of knowledge discovery in database, which descri bes phases of data gathering, data preprocessing, data transforming into profiles, and finally knowledge extracting. In a ddition, it is discussed how the solution can help enterprises to achieve the introduced factors. Therefore, the solution tends to an increase in customer satisfaction, and switching barrier, a nd hence customer loyalty. Finally, in order to present an applicable implementation of the solution, phase of data transforming is realized by using the XML.

Carlos Cano, Armando Blanco, Fernando García

Microarray Technology allows us to measure the expression of thousa nds of genes simultaneously, and under specific conditions. Clustering is the main tool used to analyze gene expression data obtained from microarray experiments. By grouping together genes with the same be havior across samples, resultant clusters suggest new functions for some of the gene s. Non-exclusive clustering algorithms are required, as a gene may have more th an one biological function. Gene Shaving (Hastie et al. 2000) is a clustering algorithm which looks for coherent clusters with high variance acro ss samples, allowing clusters to overlap. In this paper we present two Evolutionary Algorithm approaches, based on Genetics Algorithms (GA) and Estimation of Distributi on Algorithms (EDA), whose aim is to find clusters of similar genes with large between-sample vari ance. We apply our methods GA-Shaving and EDA-Shaving to S. cerevisiae cell cycle dataset outperforming Gene-Shaving results in terms of quality and size of obtained clusters. Furthermore, we use GO Term Finder (Boyle et al. 2004) to evaluate the biological interpretation of the results. It computes the most st atistically significant biological processes associated to every cluster by means of the annotations of the Gene Ontology (Gene Ontology Consortium 2004).

Balbir Barn, Hilary Dexter, Samia Oussena, Jim Petch

Improving business processes and services is a challenge that can be met by a model-driven approach to service design and development. Th is approach rests on defining refe rence models of the enterprise business processes that will become the drivers of se rvice frameworks. As part of a national program for developing such models within a Service Oriented Architecture (SOA) framework for e-learning and research in higher education, a canonical reference model for course validation was used to demonstrate the feasibility of the approach. Course validation processes in four UK Highe r Education Institutions (HEIs) were analysed and modell ed using interviews and process documentation. Each institution’s process was modelled with UML Activity Diagrams and its domain information with Class Diagrams. The four models were synthesized into a single canonical reference model of the validation process. This required resolving process model structures and elem ent granularity. Synthesi s of the canonical model demonstrated a methodological basis for developing service specifications, within a SOA framework that could serve all institutions in the sector.

Pedro Isaías

Editorial preface for Volume 1, Issue 2 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.