bluuebunny/crossref_metadata_2025 huggingface dataset:
Distance Learning Techniques in University Courses
Authors: Frignani Paolo
Published: May 2011

Distance learning (DL) is not, and must not become, a surrogate for traditional learning with the teacher (Trentin, 1998). For this reason, alongside virtual classroom technologies such as chat and video-audio conferences and methods typical of synchronous DL which requires the simultaneous presence of lecturers, tutors and students online, it is important to implement asynchronous interaction tools for: • Accessing content; • Self-testing; • Distance dialogue between students, tutors and teachers. Asynchronous DL therefore offers an important innovative possibility for classroom teaching (whether it be real or virtual): automatic link between content and structure. From this it is easy to deduce that DL is characterized by three types of activity: 1. Transmission of content prepared by the teacher (configured as content expert); 2. Test and self-test of learning through the use of online interactive tools; 3. Dialogue between students, tutors and teachers. This complex structure which generates articulated processes designed to create environments favourable to teaching but above all to learning, also requires to be considered, and above all defined, in the light of the roles and professional figures involved (Frignani, 2003).
Dynamic Reconstruction of Concept Maps
Authors: Pedroni Marco
Published: May 2011

Within the e-learning context, the importance of developing concept maps—and, therefore, of developing software tools that support their design and utilization phases—clearly derives from their connection with the theme of the ontological structure of knowledge, which is founded on graph theory and which determines, according to rules defined by Joseph Novak (Novak & Gowin 1984), the node elements and the relationships with the arcs. However, concept maps cannot be described simply as a product of the evolution of the concept of content indexing, since their role encompasses not only the organizational function of knowing but also the vehiculatory function, assuming that there is a specific clarificatory task within the cognitive context that is different from, and additional to, the navigational support. Research into concept maps takes its cue from the world of education (Novak, 1998), in which their significance is clearly recognized. On the one hand, the characteristic representation of the tissue of relationships that links the concepts together constitutes an extremely interesting expressive approach in terms of its capacity to focus attention of learners, whereas on the other hand—and mainly within the framework of constructivist didactics—the environments used for the ontological mapping of disciplines can be deployed as a locus for collaboration in exploring the cognitive and negotiative context. Both of these aspects are further promoted by e-learning (Canas, Hill, & Lott, 2003; Canas, Hill, Carff, Suri, Lott, & Eskridge, 2004), which uses concept maps not only in the representation of knowledge within a range of structural Learning Object models (Information Maps, Generative Learning, Workflow-based Learning) but also in the indexing of communication flows (Barabasi, 2004), and within interactive environments geared towards the collaborative construction of knowledge.
An Edutainment Framework Implementation Case Study
Authors: Embe Zarina Che , Hussain Hanafizan
Published: May 2011

The convergence of information technology, particularly multimedia applications, has made it possible to create electronic games with characters that come alive on the screen. From its original use just for entertainment, electronic games now can be used for educational purposes. Thus, the term ‘edutainment’ is created from a combination of the two areas: education and entertainment. Exploring the edutainment environment has become an interesting research area and understanding its application to suit various learning environments or teaching models is a crucial issue.
E-Learning Function Integration with Corona 2
Authors: Pedroni Marco
Published: May 2011

The aim of the Corona project, which was launched in 2003 in the context of methodological-technological research on the subject of e-learning carried out in collaboration with CARID (“Centro di Ateneo per la Ricerca, l’Innovazione Didattica e l’Istruzione a Distanza”, the research center of the University of Ferrara which studies e-learning methods and techonologies and applies them in real learning contexts) and the Omniacom Consortium, is to facilitate the integration of functional modules (synchronous, such as chat rooms and virtual classrooms, and asynchronous such as the production and provision of Learning Objects, forums, assessment and tracking tools), originating from different development environments, in a single online interactive environment.
Electronic Loyalty Programs Comparative Survey
Authors: Ozcelik Yasin
Published: May 2011

Loyalty is defined as the repeated satisfaction of a customer with purchases of products from a specific firm or brand. Firms have been developing customer loyalty programs because it is generally less expensive for firms to retain existing customers than to attract new ones (Reichheld & Schefter, 2000). Although the correlation between customer loyalty and long-run firm profitability is under discussion, there is a consensus on positive effects of customer loyalty programs on firm sales (Reinartz & Kumar, 2002). Loyalty programs are also attractive for customers since they receive special offers or discounts. The notion of loyalty on the Internet, coined as electronic loyalty (e-loyalty), is a relatively new concept. However, because of their potential to increase sales and reduce online customer retention costs, e-loyalty programs have received much attention from both businesses and academic researchers. In what follows, we first summarize major theoretical results and empirical evidence on customer loyalty in the literature. We then analyze different types of popular e-loyalty programs on the Internet.
Evaluating Usability to Improve Efficiency in E-Learning Programs
Authors: Lastrucci Emilio , Infante Debora , Pascale Angela
Published: May 2011

The history of usability began almost 20 years ago when computers were about to be used outside the designer and programmer environment. Until the 1980s software was mostly produced and used by designers so usability was taken for granted. In 1983, the first computers providing a graphic interface and a mouse were produced by Apple for distribution on a large scale. The gradual introduction of computers to offices and houses began creating usability problems. The development of computers was guided mainly by the technology available at that time. Gradually, the impact of training costs, errors in the interaction between user and computer, and the evolution of studies regarding the “human factor”, carried out by psychologists and ergonomics experts, led to a reflection on the importance of the target users.
Information Communication Technology Tools for Software Review and Verification
Authors: Wong Yuk Kuen
Published: May 2011

While information communication technology (ICT) can be considered a well-established discipline, software development projects are still prone to failure. Even if a software project is not classified as a failure, the general level of software quality leaves room for much improvement. It has been suggested that one of the most prevalent and costly mistakes made in software projects today is deferring the activity of detecting and correcting software problems until the end of the project. Hence, the cost of rework in the later stages of a project can be greater than 100 times the project costs. About 80% of avoidable rework comes from 20% of defects. As a result, techniques such as software review for improving software quality are important. Software review (inspection/verification) was originally introduced by Fagan (1976). The review process essentially includes six major steps: 1. Planning: Organize and prepare the software review, typically for preparing the review materials and review procedure, forming review team and scheduling review meeting, selecting review participants, and assigning roles. 2. Overview: Author explains overall scope and the purpose of the review. 3. Individual preparation: Individual reviewers analyze and review the software artefact. 4. Group review meeting: Find errors, sometimes also called “logging meeting.” Review teams correct and the reader summarizes the work. 5. Rework: Defect correction, which involves the author in resolving problems by reviewing, revising, and correcting the identified defect or by decreasing the existence of errors of the software artefact. 6. Follow-up: Validate the correction quality and decide if re-inspection is required
Intelligent Multi-Agent Systems
Authors: Krcadinac Uros , Stankovic Milan , Kovanovic Vitomir , Jovanovic Jelena
Published: May 2011

Since the AAAI (http://www.aaai.org) Spring Symposium in 1994, intelligent software agents and agentbased systems became one of the most significant and exciting areas of research and development (R&D) that inspired many scientific and commercial projects. In a nutshell, an agent is a computer program that is capable of performing a flexible, autonomous action in typically dynamic and unpredictable domains (Luck, McBurney, Shehory, & Willmott, 2005). Agents emerged as a response of the IT research community to the new data-processing requirements that traditional computing models and paradigms were increasingly incapable to deal with (e.g., the huge and ever-increasing quantities of available data). Agent-oriented R&D has its roots in different disciplines. Undoubtedly, the main contribution to the field of autonomous agents came from artificial intelligence (AI) which is focused on building intelligent artifacts; and if these artifacts sense and act in some environment, then they can be considered agents (Russell & Norvig, 1995). Also, object-oriented programming (Booch, 2004), concurrent object-based systems (Agha, Wegner, & Yonezawa, 1993), and human-computer interaction (Maes, 1994) are fields that have constantly driven forward the agent R&D in the last few decades.
Modeling Business Actions
Authors: Rittgen Peter
Published: May 2011

The effective use of information and communication technology, or ICT (Barua, Kriebel, & Mukhopadhyay, 1995; Burn & Szeto, 2000; Mahmood & Mann, 2005; Mukhopadhyay, Kekre, & Kalathur, 1995; Sircar, Turnbow, & Bordoloi, 2000; Zammuto, 1982), requires a careful design of information systems and the business processes they support from a communicative perspective (language-action perspective). The literature on language action provides a broad spectrum of frameworks for modeling business processes, for example, business action theory (BAT; Goldkuhl, 1996, 1998; Goldkuhl & Lind, 2004), dynamic essential modeling of organizations (DEMO; Dietz, 1999; Dietz & Habing, 2004; Liu, Sun, Barjis, & Dietz, 2003; van Reijswoud, 1996; van Reijswoud & Dietz, 1999), action workflow (Denning & Medina-Mora, 1995; Kethers & Schoop, 2000; Medina-Mora, Winograd, Flores, & Flores, 1992), action-based modeling (Lehtinen & Lyytinen, 1986), and conversation for action (Winograd & Flores, 1986). Among these frameworks, BAT can be seen as the most general because it does not commit the modeler to any specific methodology allowing for a free choice of the most appropriate one in the context. A possible choice would be that of the situation-adaptable work and information systems modeling method (SIMM; Goldkuhl, 1996).
Modelling Wireless Local Area Networking in Higher Education Institutes
Authors: Väänänen Ossi
Published: May 2011

This article is partly based on the research being done by Turku University of Applied Sciences in Turku, Finland. The research was started in spring 2006 and is backed by the Ministry of Education in Finland. The aim of the research is to do the basic information collation of the current implementations and the use of wireless local area networking in Finnish universities of applied sciences (former polytechnics). Based on certain models and best practices for WLAN (wireless local area networking), networking is created.
Multimedia Integration in Active Online Learning Environments
Authors: Song Holim , Kidd Terry T.
Published: May 2011

The terms distance learning, online learning, and Webbased instruction have become buzzwords and catch phrases for the new phenomenon of learning. These terms used to describe an ever-changing environment represent approaches that focus on opening the access to education and training provision for adult learners, freeing the adult learners from the traditional constraints of time and place. Online learning is one of the most rapidly growing fields of education around the world, and its potential impact on all education delivery systems has been greatly emphasized through the development of Web-based information technologies, multimedia, communication technologies, and, more importantly, the Internet.
Product Evaluation Services for E-Commerce
Authors: Guan Sheng-Uei
Published: May 2011

Despite the rapid growth of e-commerce and the hype surrounding it, the potential of the Internet for truly transforming commerce is largely unrealized to date is because most electronic purchases are still largely nonautomated. User presence is still required in all stages of the buying process. According to the nomenclature of Maes’ group in the MIT Media Labs (Guttman, 1999; Maes, 1994), the common commerce behavior can be described with consumer buying behavior (CBB) model, which consists of six stages, namely, need identification, product brokering, merchant brokering, negotiation, purchase and delivery, and product service and evaluation.
Technology Enhanced Learning in Continuing Medical Education
Authors: Trentin Guglielmo
Published: May 2011

The traditional training programs will be increasingly intended as the early stages of a learning process designed to last over time under the direct responsibility of the individual. This is true particularly in cases where professional knowledge is prone to rapid obsolescence. Such is the case of the medical profession where, besides an initial university education and professional development based on direct experience, there is the need for a process of continuous education on scientific research results and best professional practice carried out by colleagues (Manning & DeBakey, 2001; Wyatt, 2000). It is precisely due to this requirement that many educational institutions and agencies in Italy have set up specific continuing medical education (CME) programs.
Comparing Approaches to Web Accessibility Assessment
Authors: Martín Adriana , Cechich Alejandra , Rossi Gustavo
Published: May 2011

Web accessibility is one facet of Web quality in use, and one of the main actors upon which the success of a Web site depends. In spite of these facts, surveys repeatedly show that the accessibility at the Web for people with disabilities is disappointingly low. At the Web, most pages present many kinds of accessible barriers for people with disabilities. The former scenario encouraged research communities and organizations to develop a large range of approaches to support Web accessibility. Currently, there are so many approaches available that comparisons have emerged to clarify their intent and effectiveness. With this situation in mind, this chapter will discuss the importance of Web accessibility assessment and compare 15 different approaches found in literature. To do so, we provide an evaluation framework, WAAM, and instantiate them by classifying the different proposals. The aim of WAAM is to clarify from an evaluation and classification perspective the situation at the accessibility arena.
Handling Usability Aspects for the Construction of Business Process Driven Web Applications
Authors: Torres Victoria , Fons Joan , Pelechano Vicente
Published: May 2011

Users consider usability aspects as a key factor when using Web applications. For this reason, in this work we take a special care in this very important issue. In particular, we are centred on usability aspects regarding business process driven Web applications. Therefore, in this work we gather a set of guidelines provided by experts in Web usability and present the solution designed in a particular Web engineering method that follows a model driven development approach. The provided solution bases on the introduction of these guidelines following two different approaches. The former implies handling usability guidelines at the modeling level. The latter implies using them for the definition of the transformation rules that generate the corresponding usable Web applications.
The Use of Metamodels in Web Requirements to Assure the Consistence
Authors: Escalona M.J. , Aragón G.
Published: May 2011

The increasing complexity and the many different aspects that should be treated at the same time require flexible but powerful methodologies to support the development process. Every day, the requirements treatment in Web environments is becoming a more critical phase because developers need suitable methods to capture, define, and validate requirements. However, it is very important that these methods assure the quality of these requirements. The model-driven engineering is opening a new way to define methodological approaches that allow control and relate concepts that have to be treated. This chapter presents a Web methodological approach to deal with requirements, NDT (navigational development techniques) based on model-driven engineering. As it is presented, NDT proposes a set of procedures, techniques, and models to assure the quality of results in the Web requirements treatment.
A Quality-Aware Engineering Process for Web Applications
Authors: Castro Cristina Cachero , Calero Coral , García Yolanda Marhuenda
Published: May 2011

This chapter introduces the necessity to consider quality management activities as part of the Web engineering (WE) process to improve the final quality of Web applications with respect to creative practices. We explore principles and achievements that, uncovered in different Web quality lines of research, provide insights into how to deal with quality in each of the different workflows that a typical WE process defines, from requirements to implementation. Also, in order to preserve the semiautomatic nature of WE processes, we propose the definition of measurable concepts, measures, and decision criteria in a machine-readable way that facilitate the automation of the quality evaluation process, thus preserving the model-driven engineering (MDE) nature of WE processes. In this way, we are providing the user of a WE methodology with the advantages associated with managing quality from the early stages of development with little extra development costs.
WSRP-O
Authors: Moraga Mª Ángeles , García-Rodríguez de Guzmán Ignacio , Calero Coral , Piattini Mario
Published: May 2011

The use of Web portals continues to rise, showing their importance in the current information society. Specifically, this chapter focuses on portlet-based portals. Portlets are Web components, and they can be thought of as COTS but in a Web setting. Recently, the Web service for remote portlets (WSRP) standard has come into existence. Its aim is to provide a common interface in order to allow the communication between portal and portlets. Bearing all that in mind, in this chapter we propose an ontology for this standard. This ontology offers an understandable summary of the standard. Thus, the ontology leads both portlet and portal developers to focus their effort on developing the portlet domain logic instead of implementing its communication.
Improving the Quality of Web Search
Authors: Hamdi Mohamed Salah
Published: May 2011

Conventional Web search engines return long lists of ranked documents that users are forced to sift through to find relevant documents. The notoriously-low precision of Web search engines coupled with the ranked list presentation make it hard for users to find the information they seek. Developing retrieval techniques that will yield high recall and high precision is desirable. Unfortunately, such techniques would impose additional resource demands on the search engines which are already under severe resource constraints. A more productive approach, however, seems to enhance post-processing of the retrieved set. If such value-adding processes allow the user to easily identify relevant documents from a large retrieved set, queries that produce low precision/high recall results will become more acceptable. We propose improving the quality of Web search by combining meta-search and self-organizing maps. This can help users both in locating interesting documents more easily and in getting an overview of the retrieved document set.
Adaptive Neural Algorithms for PCA and ICA
Authors: Mutihac Radu
Published: May 2011

Artificial neural networks (ANNs) (McCulloch & Pitts, 1943) (Haykin, 1999) were developed as models of their biological counterparts aiming to emulate the real neural systems and mimic the structural organization and function of the human brain. Their applications were based on the ability of self-designing to solve a problem by learning the solution from data. A comparative study of neural implementations running principal component analysis (PCA) and independent component analysis (ICA) was carried out. Artificially generated data additively corrupted with white noise in order to enforce randomness were employed to critically evaluate and assess the reliability of data projections. Analysis in both time and frequency domains showed the superiority of the estimated independent components (ICs) relative to principal components (PCs) in faithful retrieval of the genuine (latent) source signals. Neural computation belongs to information processing dealing with adaptive, parallel, and distributed (localized) signal processing. In data analysis, a common task consists in finding an adequate subspace of multivariate data for subsequent processing and interpretation. Linear transforms are frequently employed in data model selection due to their computational and conceptual simplicity. Some common linear transforms are PCA, factor analysis (FA), projection pursuit (PP), and, more recently, ICA (Comon, 1994). The latter emerged as an extension of nonlinear PCA (Hotelling, 1993) and developed in the context of blind source separation (BSS) (Cardoso, 1998) in signal and array processing. ICA is also related to recent theories of the visual brain (Barlow, 1991), which assume that consecutive processing steps lead to a progressive reduction in the redundancy of representation (Olshausen and Field, 1996). This contribution is an overview of the PCA and ICA neuromorphic architectures and their associated algorithmic implementations increasingly used as exploratory techniques. The discussion is conducted on artificially generated sub- and super-Gaussian source signals.
Adaptive Neuro-Fuzzy Systems
Authors: Esmahi Larbi , Williamson Kristian , Badidi Elarbi
Published: May 2011

Fuzzy logic became the core of a different approach to computing. Whereas traditional approaches to computing were precise, or hard edged, fuzzy logic allowed for the possibility of a less precise or softer approach (Klir et al., 1995, pp. 212-242). An approach where precision is not paramount is not only closer to the way humans thought, but may be in fact easier to create as well (Jin, 2000). Thus was born the field of soft computing (Zadeh, 1994). Other techniques were added to this field, such as Artificial Neural Networks (ANN), and genetic algorithms, both modeled on biological systems. Soon it was realized that these tools could be combined, and by mixing them together, they could cover their respective weaknesses while at the same time generate something that is greater than its parts, or in short, creating synergy. Adaptive Neuro-fuzzy is perhaps the most prominent of these admixtures of soft computing technologies (Mitra et al., 2000). The technique was first created when artificial neural networks were modified to work with fuzzy logic, hence the Neuro-fuzzy name (Jang et al., 1997, pp. 1-7). This combination provides fuzzy systems with adaptability and the ability to learn. It was later shown that adaptive fuzzy systems could be created with other soft computing techniques, such as genetic algorithms (Yen et al., 1998, pp. 469-490), Rough sets (Pal et al., 2003; Jensen et al., 2004, Ang et al., 2005) and Bayesian networks (Muller et al., 1995), but the Neuro-fuzzy name was widely used, so it stayed. In this chapter we are using the most widely used terminology in the field. Neuro-fuzzy is a blanket description of a wide variety of tools and techniques used to combine any aspect of fuzzy logic with any aspect of artificial neural networks. For the most part, these combinations are just extensions of one technology or the other. For example, neural networks usually take binary inputs, but use weights that vary in value from 0 to 1. Adding fuzzy sets to ANN to convert a range of input values into values that can be used as weights is considered a Neuro-fuzzy solution. This chapter will pay particular interest to the sub-field where the fuzzy logic rules are modified by the adaptive aspect of the system. The next part of this chapter will be organized as follows: in section 1 we examine models and techniques used to combine fuzzy logic and neural networks together to create Neuro-fuzzy systems. Section 2 provides an overview of the main steps involved in the development of adaptive Neuro-fuzzy systems. Section 3 concludes this chapter with some recommendations and future developments.
Adaptive Technology and Its Applications
Authors: Neto João José
Published: May 2011

Before the advent of software engineering, the lack of memory space in computers and the absence of established programming methodologies led early programmers to use self-modification as a regular coding strategy. Although unavoidable and valuable for that class of software, solutions using self-modification proved inadequate while programs grew in size and complexity, and security and reliability became major requirements. Software engineering, in the 70’s, almost led to the vanishing of self-modifying software, whose occurrence was afterwards limited to small low-level machinelanguage programs with very special requirements. Nevertheless, recent research developed in this area, and the modern needs for powerful and effective ways to represent and handle complex phenomena in hightechnology computers are leading self-modification to be considered again as an implementation choice in several situations. Artificial intelligence strongly contributed for this scenario by developing and applying non-conventional approaches, e.g. heuristics, knowledge representation and handling, inference methods, evolving software/ hardware, genetic algorithms, neural networks, fuzzy systems, expert systems, machine learning, etc. In this publication, another alternative is proposed for developing Artificial Intelligence applications: the use of adaptive devices, a special class of abstractions whose practical application in the solution of current problems is called Adaptive Technology. The behavior of adaptive devices is defined by a dynamic set of rules. In this case, knowledge may be represented, stored and handled within that set of rules by adding and removing rules that represent the addition or elimination of the information they represent. Because of the explicit way adopted for representing and acquiring knowledge, adaptivity provides a very simple abstraction for the implementation of artificial learning mechanisms: knowledge may be comfortably gathered by inserting and removing rules, and handled by tracking the evolution of the set of rules and by interpreting the collected information as the representation of the knowledge encoded in the rule set.
Automated Cryptanalysis of Classical Ciphers
Authors: Grošek Otokar , Zajac Pavol
Published: May 2011

Classical ciphers are used to encrypt plaintext messages written in a natural language in such a way that they are readable for sender or intended recipient only. Many classical ciphers can be broken by brute-force search through the key-space. Methods of artificial intelligence, such as optimization heuristics, can be used to narrow the search space, to speed-up text processing and text recognition in the cryptanalytic process. Here we present a broad overview of different AI techniques usable in cryptanalysis of classical ciphers. Specific methods to effectively recognize the correctly decrypted text among many possible decrypts are discussed in the next part Automated cryptanalysis – Language processing.
Behaviour-Based Clustering of Neural Networks
Authors: Castro-Bleda María José , España-Boquera Slavador , Zamora-Martínez Francisco
Published: May 2011

The field of off-line optical character recognition (OCR) has been a topic of intensive research for many years (Bozinovic, 1989; Bunke, 2003; Plamondon, 2000; Toselli, 2004). One of the first steps in the classical architecture of a text recognizer is preprocessing, where noise reduction and normalization take place. Many systems do not require a binarization step, so the images are maintained in gray-level quality. Document enhancement not only influences the overall performance of OCR systems, but it can also significantly improve document readability for human readers. In many cases, the noise of document images is heterogeneous, and a technique fitted for one type of noise may not be valid for the overall set of documents. One possible solution to this problem is to use several filters or techniques and to provide a classifier to select the appropriate one. Neural networks have been used for document enhancement (see (Egmont-Petersen, 2002) for a review of image processing with neural networks). One advantage of neural network filters for image enhancement and denoising is that a different neural filter can be automatically trained for each type of noise. This work proposes the clustering of neural network filters to avoid having to label training data and to reduce the number of filters needed by the enhancement system. An agglomerative hierarchical clustering algorithm of supervised classifiers is proposed to do this. The technique has been applied to filter out the background noise from an office (coffee stains and footprints on documents, folded sheets with degraded printed text, etc.).
Cluster Analysis of Gene Expression Data
Authors: Wee-Chung Liew Alan , Law Ngai-Fong , Yan Hong
Published: May 2011

Important insights into gene function can be gained by gene expression analysis. For example, some genes are turned on (expressed) or turned off (repressed) when there is a change in external conditions or stimuli. The expression of one gene is often regulated by the expression of other genes. A detail analysis of gene expression information will provide an understanding about the inter-networking of different genes and their functional roles. DNA microarray technology allows massively parallel, high throughput genome-wide profiling of gene expression in a single hybridization experiment [Lockhart & Winzeler, 2000]. It has been widely used in numerous studies over a broad range of biological disciplines, such as cancer classification (Armstrong et al., 2002), identification of genes relevant to a certain diagnosis or therapy (Muro et al., 2003), investigation of the mechanism of drug action and cancer prognosis (Kim et al., 2000; Duggan et al., 1999). Due to the large number of genes involved in microarray experiment study and the complexity of biological networks, clustering is an important exploratory technique for gene expression data analysis. In this article, we present a succinct review of some of our work in cluster analysis of gene expression data.
Computer Morphogenesis in Self-Organizing Structures
Authors: Fernández-Blanco Enrique , Dorado de la Calle Julián
Published: May 2011

Applying biological concepts to create new models in the computational field is not a revolutionary idea: science has already been the basis for the famous artificial neuron models, the genetic algorithms, etc. The cells of a biological organism are able to compose very complex structures from a unique cell, the zygote, with no need for centralized control (Watson J.D. & Crick F. H. 1953). The cells can perform such process thanks to the existence of a general plan, encoded in the DNA for the development and functioning of the system. Another interesting characteristic of natural cells is that they form systems that are tolerant to partial failures: small errors do not induce a global collapse of the system. Finally, the tissues that are composed by biological cells present parallel information processing for the coordination of tissue functioning in each and every cell that composes this tissue. All the above characteristics are very interesting from a computational viewpoint. This paper presents the development of a model that tries to emulate the biological cells and to take advantage of some of their characteristics by trying to adapt them to artificial cells. The model is based on a set of techniques known as Artificial Embryology (Stanley K. & Miikkulainen R. 2003) or Embryology Computation (Kumar S. & Bentley P.J 2003).
Configuration
Authors: Anselma Luca , Magro Diego
Published: May 2011

Configuring means selecting and bringing together a set of given components to produce an aggregate (or a set of aggregates) satisfying some requirements. All the component types are predefined and no new component type may be created during the configuration process. The result of the configuration can be physical objects (such as cars or elevators), non-physical entities (such as compound services or processes) or heterogeneous wholes made of both physical and non-physical parts (such as computer systems with their hardware and software components). The configuration process has to take into consideration both endogenous and exogenous constraints: the former pertain to the type of the assembled object(s) (therefore they hold for all the individuals of that type) and mainly come from the interactions among components, whereas the latter usually represent requirements that the final aggregate(s) should satisfy. All these constraints can be very complex and make the manual solution of configuration problems a very hard task in many cases. The complexity of configuration and its relevance in several application domains have stimulated the interest in its automation. Since the beginning, Artificial Intelligence has provided various effective techniques to achieve this goal. One of the first configurators was also one of the first commercially successful expert systems: a production rule-based system called R1 (McDermott, 1982, 1993). R1 was developed in the early Eighties to configure VAX computer systems, and it has been used for several years by Digital Equipment Corporation. Since then, configuration has gained importance both in industry and in marketing, also due to both the support that it offers to the mass customization business strategy and the new commercial opportunities provided by the Web. Configuration is currently an important application field for many Artificial Intelligence techniques and it is still posing many interesting problems to scientific research.
Data Warehousing Development and Design Methodologies
Authors: Yao James , Wang John
Published: May 2011

Information systems were developed in early 1960s to process orders, billings, inventory controls, payrolls, and accounts payables. Soon information systems research began. Harry Stern started the “Information Systems in Management Science” column in Management Science journal to provide a forum for discussion beyond just research papers (Banker & Kauffman, 2004). Ackoff (1967) led the earliest research on management information systems for decision-making purposes and published it in Management Science. Gorry and Scott Morton (1971) first used the term ‘decision support systems’ (DSS) in a paper and constructed a framework for improving management information systems. The topics on information systems and DSS research diversifies. One of the major topics has been on how to get systems design right. As an active component of DSS, which is part of today’s business intelligence systems, data warehousing became one of the most important developments in the information systems field during the mid-to-late 1990s. Since business environment has become more global, competitive, complex, and volatile, customer relationship management (CRM) and e-commerce initiatives are creating requirements for large, integrated data repositories and advanced analytical capabilities. By using a data warehouse, companies can make decisions about customer-specific strategies such as customer profiling, customer segmentation, and crossselling analysis (Cunningham et al., 2006). Thus how to design and develop a data warehouse have become important issues for information systems designers and developers. This paper presents some of the currently discussed development and design methodologies in data warehousing, such as the multidimensional model vs. relational ER model, CIF vs. multidimensional methodologies, data-driven vs. metric-driven approaches, top-down vs. bottom-up design approaches, data partitioning and parallel processing.
Different Approaches for Cooperation with Metaheuristics
Authors: Cadenas José M. , Carmen Garrido Ma , Muñoz Enrique , Cruz-Corona Carlos , Pelta David A. , Verdegay José L.
Published: May 2011

Working on artificial intelligence, one of the tasks we can carry on is optimization of the possible solutions of a problem. Optimization problems appear. In optimization problems we search for the best solution, or one good enough, to a problem among a lot of alternatives. Problems we try to solve are usual in daily living. Every person constantly works out optimization problems, e.g. finding the quickest way from home to work taking into account traffic restrictions. Humans can find efficiently solutions to these problems because these are easy enough. Nevertheless, problems can be more complex, for example reducing fuel consumption of a fleet of plains. Computational algorithms are required to tackle this kind of problems. A first approach to solve them is using an exhaustive search. Theoretically, this method always finds the solution, but is not efficient as its execution time grows exponentially. In order to improve this method heuristics were proposed. Heuristics are intelligent techniques, methods or procedures that use expert knowledge to solve tasks; they try to obtain a high performance referring to solution quality and used resources. Metaheuristics, term first used by Fred Glover in 1986 (Glover, 1986), arise to improve heuristics, and can be defined as (Melián, Moreno & Moreno, 2003) ‘intelligent strategies for designing and improving very general heuristic procedures with a high performance’. Since Glover the field has been extensively developed. The current trend is designing new metaheuristics that improve the solution to given problems. However, another line, very interesting, is reuse existing metaheuristics in a coordinated system. In this article we present two different methods following this line.
Disk-Based Search
Authors: Edelkamp Stefan , Jabbar Shahid
Published: May 2011

The need to deal with large data sets is at the heart of many real-world problems. In many organizations the data size has already surpassed Petabytes (1015). It is clear that to process such an enormous amount of data, the physical limitations of RAM is a major hurdle. However, the media that can hold huge data sets, i.e., hard disks, are about a 10,000 to 1,000,000 times slower to access than RAM. On the other hand, the costs for large amounts of disk space have considerably decreased. This growing disparity has led to a rising attention to the design of external memory algorithms (Sanders et al., 2003) in recent years. In a hard disk, random disk accesses are slow due to disk latency in moving the head on top of the data. But once the head is at its proper position, data can be read very rapidly. External memory algorithms exploit this fact by processing the data in the form of blocks. They are more informed about the future accesses to the data and can organize their execution to have minimum number of block accesses. Traditional graph search algorithms perform well as long as the graph can fit into the RAM. But for large graphs these algorithms are destined to fail. In the following, we will review some of the advances in the field of search algorithms designed for large graphs.
E-Learning in New Technologies
Authors: Pedreira Nieves , Ramón Méndez Salgueiro José , Martínez Carballo Manuel
Published: May 2011

E-learning and the impact of new technologies across contemporary life is a very significant field to education. The challenge of the technology to conventional learning patterns cannot be ignored and in itself raises a host of questions: can online learning facilitate deep learning? How well does video conferencing alleviate the challenge of distance? In what ways can collaborative learning communities be developed and sustained using current and new technologies? At the same time, new communications technologies are impacting on the ways in which we understand ourselves and the worlds in which we live. Relating to this, the aim of today’s education is not to learn certain contents, but rather learn to learn in the course of a whole lifetime. The study of the learning process can help us to find the relevant points to set up some interesting characteristics of a really functional e-learning system.
Energy Minimizing Active Models in Artificial Vision
Authors: Bueno García Gloria , Martínez Antonio , González Roberto , Torres Manuel
Published: May 2011

Deformable models are well known examples of artificially intelligent system (AIS). They have played an important role in the challenging problem of extracting useful information about regions and areas of interest (ROIs) imaged through different modalities. The challenge is also in extracting boundary elements belonging to the same ROI and integrate them into a coherent and consistent model of the structure. Traditional low-level image processing techniques that consider only local information can make incorrect assumptions during this integration process and generate unfeasible object boundaries. To solve this problem, deformable models were introduced (Ivins, 1994), (McInerney, 1996), (Wang, 2000). These AI models are currently important tools in many scientific disciplines and engineering applications (Duncan, 2000). Deformable models offer a powerful approach to accommodate the significant variability of structures within a ROI over time and across different individuals. Therefore, they are able to segment, match and track images of structures by exploiting (bottom-up) constraints derived from the image data together with (top-down) a priori knowledge about the location, size, and shape of these structures. The mathematical foundations of deformable models represent the confluence of geometry, physics and approximation theory. Geometry serves to represent object shape, physics imposes constraints on how the shape may vary over space and time, and optimal approximation theory provides the formal mechanisms for fitting the models to data. The physical interpretation views deformable models as elastic bodies which respond to applied force and constraints.
Ensemble of SVM Classifiers for Spam Filtering
Authors: Blanco Ángela , Martín-Merino Manuel
Published: May 2011

Unsolicited commercial email also known as Spam is becoming a serious problem for Internet users and providers (Fawcett, 2003). Several researchers have applied machine learning techniques in order to improve the detection of spam messages. Naive Bayes models are the most popular (Androutsopoulos, 2000) but other authors have applied Support Vector Machines (SVM) (Drucker, 1999), boosting and decision trees (Carreras, 2001) with remarkable results. SVM has revealed particularly attractive in this application because it is robust against noise and is able to handle a large number of features (Vapnik, 1998). Errors in anti-spam email filtering are strongly asymmetric. Thus, false positive errors or valid messages that are blocked, are prohibitively expensive. Several authors have proposed new versions of the original SVM algorithm that help to reduce the false positive errors (Kolz, 2001, Valentini, 2004 & Kittler, 1998). In particular, it has been suggested that combining non-optimal classifiers can help to reduce particularly the variance of the predictor (Valentini, 2004 & Kittler, 1998) and consequently the misclassification errors. In order to achieve this goal, different versions of the classifier are usually built by sampling the patterns or the features (Breiman, 1996). However, in our application it is expected that the aggregation of strong classifiers will help to reduce more the false positive errors (Provost, 2001 & Hershop, 2005). In this paper, we address the problem of reducing the false positive errors by combining classifiers based on multiple dissimilarities. To this aim, a diversity of classifiers is built considering dissimilarities that reflect different features of the data. The dissimilarities are first embedded into an Euclidean space where a SVM is adjusted for each measure. Next, the classifiers are aggregated using a voting strategy (Kittler, 1998). The method proposed has been applied to the Spam UCI machine learning database (Hastie, 2001) with remarkable results.
Evolutionary Approaches to Variable Selection
Authors: Gestal Marcos , Manuel Andrade José
Published: May 2011

The importance of juice beverages in daily food habits makes juice authentication an important issue, for example, to avoid fraudulent practices. A successful classification model should address two important cornerstones of the quality control of juicebased beverages: to monitor the amount of juice and to monitor the amount (and nature) of other substances added to the beverages. Particularly, sugar addition is a common and simple adulteration, though difficult to characterize. Other adulteration methods, either alone or combined, include addition of water, pulp wash, cheaper juices, colorants, and other undeclared additives (intended to mimic the compositional profiles of pure juices) (Saavedra, García, & Barbas, 2000).
Evolutionary Robotics
Authors: Becerra J. A. , Duro R. J.
Published: May 2011

Evolutionary Robotics is a field of Autonomous Robotics where the controllers that implement behaviours are obtained through some kind of Evolutionary Algorithm. The aim behind this technique is to obtain controllers minimizing human intervention. This is very interesting in order to achieve complex behaviours without introducing a “human bias”. Sensors, body and actuators are usually different for a human being and for a robot, so it is reasonable to think that the best strategy obtained by the human designer is not necessarily the best one for the robot. This article will briefly describe Evolutionary Robotics and its advantages over other approaches to Autonomous Robotics as well as its problems and drawbacks.