bluuebunny/crossref_metadata_2025 huggingface dataset:
Metasystemic Re-Engineering
Authors: de la Cerda Osvaldo García , Muermann Renato Orellana
Published: May 2011

In the last decades organizational transformation has become a fundamental strategy for survival. It is a multi dimensional change of relationship patterns among executives, professionals, clients, and providers that define their organizational setting. The main difficulty lies in the persistence of the emotional, experiential, and cognitive “understanding” of the roles people play in the organisation and the dimensions that intervene in the assessments regarding action and strategy. This consideration centres the transformation effort on people. The main question to be answered is what it takes to shift people to work efficiently in a different organizational setting, and how to characterize and prepare for this setting. This article summarises a methodological proposition for organizational transformation centred on the distinction of the “observer” developed by Maturana and Varela (The tree of knowledge) that shows that our biological condition does not allow for an objective perception of reality. This fact brings forth the notion that as a result of culture and personal trajectory each human being has its own perception of the world in which he lives. The characterization of this “uniqueness” is captured by the notion of the human being as an embodied “observer” characterized by a set of distinctions that specifies the dimensions of its perceptions and blindness. An organizational transformation is the process of developing a new “managerial observer.” The fundamental methodological proposition is that an organizational transformation process is possible if, and only if, there is a transformation of the “organizational observer” shared by the community of workers and managers as distinctions in action.
Next Generation Analytics and Dynamic Decision Support
Authors: Langdon Chris Schlueter
Published: May 2011

In 1991 “Terminator 2” revolutionized the use of computers for digital effects or computer-generated imagery (CGI) in movies (Wikipedia.org, 2006). Costs were high and few saw digital effects to grow beyond a niche of few scenes in a few movies (Marr & Kelly, 2006). Fifteen years later, digital effects are widely considered a key success factor. For example, in 2005 all top five grossing movies, including Harry Potter and Star Wars sequels, relied extensively on digital effects (Box Office Mojo, 2006). Many industry observers foresee a similar success of computational methods in business intelligence analytics (BIA) and decision support (Davenport, 2006; Heingartner, 2006; March, 2005; Kimbrough, 2003). Just as CGI has not diminished the value of story telling, so will computational BIA not reduce the value of an experienced decision-maker but it will enhance it. After all, very few decision-makers make the right decision based on gut instinct all the time. Computational BIA and decision support is seen as yet another example of how a rapid increase in processing power and advances in software design have enabled embedding of more and more business activities in software routines. This process has been referred to as “softwarization” (Schlueter Langdon, 2003). Softwarization has expanded far beyond enterprise resource planning, billing, and customer relationship management. Today, few passengers and pilots seem to mind that computers land their jet liners. This article presents two examples of how advanced BIA can improve precision of managerial and executive- level decision-making. Both examples follow a multi-step approach derived from research science that explicitly addresses instrument validation. Both examples are taken from the auto industry, a global, complex, and important industry in developed countries. The first example uses traditional methods but combines them creatively to increase analytical precision. It is focused on lifecycle aging and baseline sales estimation to improve the return on marketing investments (RoMI) using gap analysis and ordinary least squares estimation. While the first example is essentially a backwards-looking analysis, the second one is forwardlooking. The second application simulates the impact of a disruptive event, a recession on profitability of automakers and their suppliers. It takes advantage of complex adaptive system modeling techniques and agent-based software implementation methods.
Qualitative Comparative Analysis
Authors: Beynon Malcolm J.
Published: May 2011

This article concerns itself with qualitative comparative analysis (QCA), introduced in Ragin (1987), it is a technique that attempts to identify the causal relationship between variables and some outcome. QCA is employed in comparative case-oriented research, for studying a small-to-moderate number of cases in which a specific outcome has occurred, compared with those where it has not. Unlike conventional statistical analysis, however, QCA does not ask about the independent effect of a variable on the likelihood of an outcome. Rather, it considers configurations of values on the independent variables as cases (Ragin, 1987; Kitchener, Beynon, & Harrington, 2002). The central goal of QCA is to mimic some of the basic analytic procedures that comparative researchers use routinely when making sense of their cases. The key difference between QCA and traditional case-oriented methods is that with QCA it is possible to extend these basic analytic procedures to the examination of more than a handful of cases (Ragin & Rihoux, 2004).
Supporting Decisional Episodes
Authors: Holsapple C.W.
Published: May 2011

This article develops the notion of decisional episodes as a basis for understanding ways in which decisions can be supported. Grounded in and aligned with knowledge management (KM) theory, the resultant perspective on decision support can guide researchers in the generation of research ideas and designs. It can also contribute to practitioners by suggesting architectures and functionalities to consider in the course of developing decision support systems, and by suggesting key issues to resolve in the course of deploying and evaluating a portfolio of decision support systems. Broadly speaking, knowledge management is concerned with efforts to ensure that the right knowledge is available to the right processors at the right time in the right representations for the right cost in order to foster right relationships, decisions, and actions with respect to an entity’s mission. These efforts unfold in various contexts such as designing, communicating, researching, and decision making. Our focus here is on the latter.
ThinkClick
Authors: Yaniv Hanan , Crichton Susan
Published: May 2011

Getting a large audience to actively participate in a lecture is a challenge faced by many lecturers. The value of active participation is well supported in current research with significant contribution made by the introduction of electronic response systems (ERS). ERS allows each member of the audience to participate by using a hand-held device (like a TV remote control), responding to (usually) multiple-choice questions presented on a board. This article is introducing a new approach to the use of ERS, making the audience engage in a decision- making process based on multi-attribute utility theory (MAUT), a commonly used theory in decision making, aiming to: • Help conference participants, in a large group setting, prioritize suggestions and action items developed over the previous days of a conference, drawing on discussions held in concurrent, small group break out sessions. • Organize those suggestions/items into a prioritized list that reflects the discussions and honors individual participant voice. • Generate a list, based on the group organization process that will direct future innovation for conference participants and organizers. • Present the collective knowledge from the conference in a way that participants can see themselves as contributing partners in the conference outcome statements. This article, then, describes a case study of decision making in a large audience, keeping each participant involved in a meaningful process of an elaborated analysis of action items. The technology, the process, and the experiment are presented as a study of the feasibility of using such systems in large audiences. We introduce here the term large group decision support system (LGDSS) to describe the process of using technology to assist a large audience in making decisions.
ThinkTeam
Authors: Yaniv Hanan
Published: May 2011

People make decisions all the time. They make decisions alone; they make decisions together with others. Some fields have been focusing on the process of decision making and have attempted to help people make decisions. Psychologists, trainers, and organizational development consultants are aiming to develop decision- making theories and methodologies and train people to use them in business, economics, urban-planning, and more areas of management and personal life. Computer-based decision support systems emerge in various fields. These fields are mainly interested in the actual process: helping people make better decisions. This article is about an indirect use of decision-making methodology: we use it as a learning task. As technology can process large quantities of integrated information while presenting results in a visualize manner, technology was harnessed to aid decision makers in various ways. Decision support systems (DSS) have been used to present decision makers with all possible relevant knowledge so they can take into account as many variables as they can before making an informed decision.
Uncertainty and Vagueness Concepts in Decision Making
Authors: Peters Georg
Published: May 2011

One of the main challenges in decision making is how to deal with uncertainty and vagueness. The classic uncertainty concept is probability, which goes back to the 17th century. Possible candidates for the title of father of probability are Bernoulli, Laplace, and Pascal. Some 40 years ago, Zadeh (1965) introduced the concept of fuzziness, which is sometimes interpreted as one form of probability. However, we will show that the terms fuzzy and probability are complementary. Recently, in the beginning of the ’80s, Pawlak (1982) suggested rough sets to manage uncertainties. The objective of this article is to give a basic introduction into probability, fuzzy set, and rough set theory and show their potential in dealing with uncertainty and vagueness. The article is structured as follows. In the next three sections we will discuss the basic principles of probability, fuzzy sets, and rough sets, and their relationship with each other. The article concludes with a short summary.
Understanding Non-Decision Making
Authors: Sammon David
Published: May 2011

Non-decision making (NDM) has received limited attention in the research literature. However, this is surprising bearing in mind that the concept of NDM (the impact of the mobilisation of bias upon a latent issue) can indeed be observed and analysed (Bachrach & Baratz, 1963). Notwithstanding this, there is a considerable volume of research literature focusing on power relations and the impact of these relations on group or community decision-making. These research studies have relevance based on the fact that the concept of NDM has emerged through attempts to theorise power relations in society (Kamuzora, 2006). This entry presents some of the important aspects of what has been researched with regards to power relations and the emergence of the concept of Non-Decision Making.
Adult Education and Adult Learning Processes with ICT
Authors: Inoue Y.
Published: May 2011

Cognitive walkthrough (CWT) is a usability inspection method which allows users to learn a system by using it to achieve tasks rather than studying a manual or documentation. It starts with a task analysis that specifies the sequence of steps required by the users to complete a task, and the system responses to those actions. The users then walkthrough the steps as a group and questioning themselves at each step. Data and information are gathered during the CWT and potential problems are identified. However, problems rose if the CWT and user based evaluation were being conducted in the mobile context environment. It became clear that static lab is not ideal for the CWT to be carried Brookfield (1995) has identified four areas as representing unique and exclusive adult learning processes: (1) self-directed learning (which focuses on the process by which adults take control of their own learning—in particular, how they set their own learning goals); (2) critical reflection (which is the idea of the decade for many adult educators who have long been searching for a form and process of learning that could be claimed to be distinctively adult); (3) experiential learning (which is based on the notion that “experience” is the adult’s continuing process of evaluating experiences); and (4) learning to learn (which is the ability of adults to learn how to learn to become skilled at learning in a range of different situations). Brookfield has further noted that one of the trends in the study of adult learning that emerged during the 1990’s, and that promises to exercise influences into the 21st century, might be the ways in which adults learn within the systems of education (distance education, computer assisted instruction, and open learning systems, for instance) that are linked to technological advances.
E-Government Growth Barriers in Sub-Saharan Africa
Authors: Ifinedo Princely
Published: May 2011

E-government, as described by the World Bank, is the use of information and communications technologies (ICT) to transform government by making it more accessible, effective, and accountable to its citizens (InfoDev, 2004). E-government involves the utilization of technologies such as the Internet to improve the services, functions, and processes of governance (Heeks, 1999, 2001, 2002; Moon, 2002). Although, the Internet is vitally important for the process, it has to be pointed out here that e-government is more than establishing a Web server and hosting government sites (Sanchez, Koh, Kappelman, & Prybutok, 2003; Sharma and Gupta, 2003). In fact, Heeks (2001) describes e-government as i-governance or integrated governance, a process that permits the integration of both the processing of information by people and the use of communication technologies in achieving the objectives of governance. The United Nations Division for Public Economics and Public Administration and the American Society for Public Administration (UNDPEPA/ASPA) state “E-government is about opportunity…to provide cost effective services to the private sector…to enhance governance through improved access to accurate information and transparent, responsive, and democratic institutions” (UNDPEPA/ASPA, 2003, p. 6).
Does E-Learning Improve the Communication Among Students and Lecturers?
Authors: Karampotsios Charilaos A. , Kardaras Dimitris K. , Papathanassiou Eleutherios A.
Published: May 2011

This article reports on a survey that investigates the role of e-learning in improving the communication in learning environments. The results are drawn from the analysis of data collected from a sample of 420 university students in Greece. The study focuses on the contribution of e-learning to facilitating the communication among fellow students and the communication among lecturers and students. The results of this article are useful for both practitioners and academics.
From E-Learning to Games-Based E-Learning
Authors: Connolly Thomas M. , Stansfield Mark
Published: May 2011

The emergence of the Internet has had a significant impact on higher education where we have seen elearning evolve from a marginal form of education to a commonly accepted and increasingly popular alternative to traditional face-to-face education. While e-learning has many advantages, there have been problems identified, such as lack of contact leading to feelings of isolation; the need for a motivated, self-disciplined, and mature learner; the monotonous nature of some e-learning materials; and increased drop out rates. If e-learning has developed a reputation for being ‘boring and mindless,’ games have developed the reputation for being engaging and challenging. In recent years, a new form of learning has been developing, namely games-based e-learning, which builds on the successes of e-learning while providing a more stimulating and relevant learning environment for younger people who have been brought up in an environment of powerful home PCs, graphic-rich multiplayer Internet gaming, and mobile phones with ever-increasing functionality. This article will explore the concept of games-based e-learning, discuss some of its pedagogic underpinnings, and examine barriers that may limit the uptake and development of this relatively new approach to learning.
ERP Integration into Existing Courses
Authors: Motwani Jaideep , Akbulut Asli Y.
Published: May 2011

help improve their productivity and customer service while lowering costs and inventory levels. The inherent appeal of ERP has not gone unnoticed in the business curriculum either. Several business schools (Babson College, Louisiana State University, University of Idaho, University of California at Chico, University of North Carolina, and Grand Valley State University, among others) have made systematic changes across their business curriculums to ensure that they graduate students with an integrated understanding of business processes and ERP systems. These schools have mirrored the approach followed by companies in various industries by abandoning the traditional vertical, functional organizational structure in favor of a more horizontal, cross-functional structure (Bailey, Chow, & Haddad, 1999; Gwin & Gwin, 2000; Johnson, Lorents, Morga, & Ozmun, 2004; Ryan & Luthy, 2000; Stover et al., 1997).
E-Tutor
Authors: Ranieri Maria
Published: May 2011

In recent years, there have been extensive discussions in the information system (IS) community on how to best respond to developments in the information and communications technology (ICT) industry. Some of these discussions have focused on the changing skills of IS graduates and have identified the need for graduates to have an integrated understanding of business processes and the ability to work effectively in teams to solve key business problems in the ICT industry. To better respond to the ICT changes, many firms have implemented companywide information systems called enterprise resource planning (ERP) systems to Many scholars believe that e-tutor support in a virtual learning environment is critical for the success of a student’s learning experience. Several reasons support this belief: “practical reasons such as reduction of drop-out rates, theoretical reasons such as mitigating student isolation, and moral reasons such as the obligation to help students succeed” (Denis, Watland, Pirotte, & Verday, 2004). Notwithstanding, the e-tutor profile is still uncertain and calls for deeper investigation and analysis. This paper aims to present a framework of competencies for specific e-tutor roles, through a literature review and personal experience.
GIS Use in Landscape Archaeology
Authors: Corsi Cristina
Published: May 2011

Information technologies (ITs) entered and irreversibly changed the discipline of archaeology during the last 20 years of the second millennium. The first experiments involved databases and alphanumeric data processing, then in the late 1980s GPS technologies, associated with spatial data processing, were first tested to locate archaeological objects in the geographical space. Computer-aided design (CAD) software has progressively replaced the traditional procedures of topographical and architectural design, while “New Archaeology” and “Processual Archaeology” focusing their attention on the quantitative aspects of phenomena (Binford, 1989; Binford & Binford, 1968; Clarke, 1968; Clarke, 1977) adopted “spatial technologies”, consisting of computer-based applications concerned with the acquisition, storage and manipulation of spatial information (Wheatley & Gillings, 2002).
ICT Investment Evaluation Practices in Large Organizations
Authors: Lin Chad , Huang Yu-An
Published: May 2011

Business-to-business electronic commerce (B2BEC) represents the largest growth sector, that is, 80% of revenues—in e-commerce (Pires & Aisbett, 2003). IDC predicts that Australian B2BEC spending will grow at 70% annually and is likely to reach $166.25 billion by 2006 (Pearce, 2002). ICT investments in B2BEC are used to assist in the interorganization acquisition of goods into the value chain and to provide interfaces between customers, vendors, suppliers, and sellers (Barua, Konana, & Whinston, 2004). Although B2BEC provides organizations a wealth of new opportunities and ways of doing business, it is extremely difficult to evaluate and therefore, have yet to prove enduring sources of profit (Laudon & Laudon, 2004). Research studies and practitioner surveys report contradictory findings on the effect of the ICT expenditures on organizational productivity (Thatcher & Pingry, 2004). In particular, measurement of the business value of ICT investment has been the subject of considerable debate among academics and practitioners (Brynjolfsson & Hitt, 2003; Sugumaran & Arogyaswamy, 2004). Although some ICT productivity studies have produced inconclusive and negative results (Zhu, 2004), other research indicated that spending in ICT is directly related to organizational performance (e.g., Hu & Quan, 2005). Some researchers (e.g., Brynjolfsson & Hitt, 2003; Zhu, 2004) suggested that the confusion over ICT productivity is due to, among other things, the lack or inappropriate use of ICT evaluation and benefits realization methodologies or processes.
Information Environments of Middle Managers in Higher Education
Authors: Kettunen Juha , Hautala Jouni , Kantola Mauri
Published: May 2011

The importance of middle managers is frequently noted in the context of strategic management and other key decisions (Floyd & Wooldridge, 1996; Gold, 1998; Kettunen, 2002). The role of the middle managers can, however, be much greater because they are responsible with other creative individuals for the innovations of their subunits. They assume the responsibility for developing many information systems to serve the processes of the organisation. There has been some criticism of the limited scope of information system innovation research (Lyytinen & Rose, 2003a, 2003b). The purpose of this article is to show that the information systems of an education institution can be classified according to the information environments (IEs) and other characteristics such as the organisational levels. The analysis reveals the creative class of a higher education institution (HEI) which assumes responsibility for developing the information systems in cooperation with the other units of the institution and networks. The empirical case of this article illustrates the information environments and information systems of the Turku University of Applied Sciences (TUAS). It is argued that technology and behaviour are not dichotomous in an information environment; they are inseparable. The analysis helps education management to develop the institution’s information systems in an innovative way.
Linking E-Assessment to Student's Use of Online Learning Content
Authors: Lee Kar-Tin , Pillay Hitendra , Chandra Vinesh
Published: May 2011

This article will examine the development and implementation of two information and communications technology (ICT) e-assessment tools—a diagnostic assessment system and an intelligent content assessment marking system—for the teaching of secondary science. An e-learning management system (ELMS, see Figure 1) was used with second-year secondary students in science which provided both content and online assessment tools for teachers. By using this system, teachers had the opportunity to modify how they assessed their students by shifting the skills and knowledge being tested and also when and at which stage of the learning they are tested. The use of the ELMS had also assisted teachers to move away from the narrow confines of standardised tests with their discrete and decontextualized ‘items’ towards more complex, holistic, contextualised, and authentic forms of assessment (e.g., Pellegrino, Chudowski, & Glaser, 2001).
A New Algorithm for Subset Matching Problem Based on Set-String Transformation
Authors: Chen Yangjun
Published: May 2011

In computer engineering, a number of programming tasks involve a special problem, the so-called tree matching problem (Cole & Hariharan, 1997), as a crucial step, such as the design of interpreters for nonprocedural programming languages, automatic implementation of abstract data types, code optimization in compilers, symbolic computation, context searching in structure editors and automatic theorem proving. Recently, it has been shown that this problem can be transformed in linear time to another problem, the so called subset matching problem (Cole & Hariharan, 2002, 2003), which is to find all occurrences of a pattern string p of length m in a text string t of length n, where each pattern and text position is a set of characters drawn from some alphabet S. The pattern is said to occur at text position i if the set p[j] is a subset of the set t[i + j - 1], for all j (1 = j = m). This is a generalization of the ordinary string matching and is of interest since an efficient algorithm for this problem implies an efficient solution to the tree matching problem. In addition, as shown in (Indyk, 1997), this problem can also be used to solve general string matching and counting matching (Muthukrishan, 1997; Muthukrishan & Palem, 1994), and enables us to design efficient algorithms for several geometric pattern matching problems. In this article, we propose a new algorithm on this issue, which needs only O(n + m) time in the case that the size of S is small and O(n + m·n0.5) time on average in general cases.
Online Trust in Mobile Commerce
Authors: Wong Yuk Kuen , Hsu C. J.
Published: May 2011

The aim of this study focuses solely on the customer’s perceptions of the m-commerce environment, rather than on trust in intermediaries or in third parties that might mediate between the customer and the store. The focus is on development of a framework to explain mcommerce acceptance in consumers’ decision-making process. The chapter further extends the technology acceptance model (TAM) in mobile commerce, particularly in the context of the consumer’s confidence level in the buying decision making process, rather than only focusing on the users’ acceptance of technology. The chapter provides a theoretical framework for mcommerce adoption and also suggests the importantrelationships between psychological and behavioral factors in the consumer decision-making process.
A Participatory Design Project on Mobile ICT
Authors: Hyrkkänen Ursula , Kettunen Juha , Putkonen Ari
Published: May 2011

The purpose of this article is to describe and assess the participatory development process of a palm computer with special software from the work activity system point of view and analyse the benefits and drawbacks experienced by an employee while testing, implementing, and using a new communication and collaboration tool. This study focuses on the maintenance personnel of Company Alpha (the name has been changed for this study). The workers are responsible for the maintenance and serving of real estate.
Strengthening the Knowledge-Base of Cities Through ICT Strategies
Authors: Yigitcanlar Tan , Velibeyoglu Koray
Published: May 2011

The chapter sets out to explain the KBD processes and challenges and opportunities in information acceptance and use in urban policy making. This chapter draws on providing a clear understanding on policy frameworks and relevant ICT applications of the Queensland Smart State experience.
Virtual Communities and Collaborative Learning in a Post-Graduate Course
Authors: Ranieri Maria
Published: May 2011

In this chapter I will discuss some of the main issues arising from online collaboration, through the presentation of a methodological model of a post-graduate course based on online collaboration. The model was developed over the last ten years, and implemented at the Laboratory of Educational Technology (LTE) of the University of Florence, with the aim of promoting effective online collaborative learning groups.
The Virtual Identity, Digital Identity, and Virtual Residence of the Digital Citizen
Authors: Sorrentino Fortunato
Published: May 2011

Since cyberspace appeared (Gibson, 1984), our existence has been endowed of a new dimension: “the virtual”. This new “space”, open to many interpretations, has been recognized as a philosophical category, becoming a subject of passionate speculation by many thinkers: Deleuze, Lévy, De Kerkchove, Maldonado— to cite just a few of the recent ones, but one could recede even to Aristotle and Plato. However, if we leave the conceptual level, we realize that today “the virtual” exists for us because something very real exists and is surrounding us: technologies. We shall discuss this view and the effect that “the virtual” and the technologies associated with it have produced on us: the birth of three new attributes for any individual living in the digital society, a person’s virtual identity, digital identity and virtual residence.
Anomaly Detection and Quality Evaluation of Web Applications
Authors: Haydar May , Malak Ghazwa , Sahraoui Houari , Petrenko Alexandre , Boroday Sergiy
Published: May 2011

This chapter addresses the problem of Web application quality assessment from two perspectives. First, it shows the use of model checking of properties formulated in LTL to detect anomalies in Web applications. Anomalies can be derived from standard quality principles or defined for a specific organization or application. The detection is performed on communicating automata models inferred from execution traces. Second, the chapter explains how probabilistic models (Bayesian networks) can be built and used to evaluate quality characteristics. The structure of the networks is defined by refinement of existing models, where the parameters (probabilities and probability tables) are set using expert judgment and fuzzy clustering of empirical data. The two proposed approaches are evaluated and a discussion on how they complement each other is presented.
Specification of the Context of Use for the Development of Web-Based Applications
Authors: Fernández de Arriba Marta , Díaz Eugenia , Pérez Jesús Rodríguez
Published: May 2011

This chapter presents the structure of an index which serves as support so allowing the development team to create the specification of the context of use document for the development of Web applications, bearing in mind characteristics of usability and accessibility, each point of the index being explained in detail. A correct preparation of this document ensures the quality of the developed Web applications. The international rules and standards related to the identification of the context of use have been taken into account. Also, the functionality limitations (sensorial, physical, or cognitive) which affect access to the Web are described, as well as the technological environment used by disabled people (assistive technologies or alternative browsers) to facilitate their access to the Web content. Therefore, following the developed specification of the context of use, usable and accessible Web applications with their corresponding benefits can be created.
Algorithms for Association Rule Mining
Authors: Bhatnagar Vasudha , Gupta Anamika , Kumar Naveen
Published: May 2011

Association Rule Mining (ARM) is one of the important data mining tasks that has been extensively researched by data-mining community and has found wide applications in industry. An Association Rule is a pattern that implies co-occurrence of events or items in a database. Knowledge of such relationships in a database can be employed in strategic decision making in both commercial and scientific domains. A typical application of ARM is market basket analysis where associations between the different items are discovered to analyze the customer’s buying habits. The discovery of such associations can help to develop better marketing strategies. ARM has been extensively used in other applications like spatial-temporal, health care, bioinformatics, web data etc (Hipp J., Güntzer U., Nakhaeizadeh G. 2000). An association rule is an implication of the form X ? Y where X and Y are independent sets of attributes/ items. An association rule indicates that if a set of items X occurs in a transaction record then the set of items Y also occurs in the same record. X is called the antecedent of the rule and Y is called the consequent of the rule. Processing massive datasets for discovering co-occurring items and generating interesting rules in reasonable time is the objective of all ARM algorithms. The task of discovering co-occurring sets of items cannot be easily accomplished using SQL, as a little reflection will reveal. Use of ‘Count’ aggregate query requires the condition to be specified in the where clause, which finds the frequency of only one set of items at a time. In order to find out all sets of co-occurring items in a database with n items, the number of queries that need to be written is exponential in n. This is the prime motivation for designing algorithms for efficient discovery of co-occurring sets of items, which are required to find the association rules. In this article we focus on the algorithms for association rule mining (ARM) and the scalability issues in ARM. We assume familiarity of the reader with the motivation and applications of association rule mining
ANN Application in the Field of Structural Concrete
Authors: Pérez Juan L. , Martínez Mª Isabel , Herrador Manuel F.
Published: May 2011

Artificial Intelligence (AI) mechanisms are more and more frequently applied to all sorts of civil engineering problems. New methods and algorithms which allow civil engineers to use these techniques in a different way on diverse problems are available or being made available. One AI techniques stands out over the rest: Artificial Neural Networks (ANN). Their most remarkable traits are their ability to learn, the possibility of generalization and their tolerance towards mistakes. These characteristics make their use viable and cost-efficient in any field in general, and in Structural Engineering in particular. The most extended construction material nowadays is concrete, mainly because of its high resistance and its adaptability to formwork during its fabrication process. Along this chapter we will find different applications of ANNs to structural concrete.
Artificial Intelligence in Computer-Aided Diagnosis
Authors: Eduardo Ambrósio Paulo
Published: May 2011

Professionals of the medical radiology area depend directly on the process of decision making in their daily activities. This process is mainly based on the analysis of a great amount of information obtained for the evaluation of radiographic images. Some studies demonstrate the great capacity of Artificial Neural Networks (ANN) in support systems for diagnosis, mainly in applications as pattern classification. The objective of this article is to present the development of an ANN-based system, verifying its behavior as a feature extraction and dimensionality reduction tool, for recognition and characterization of patterns, for posterior classification in normal and abnormal patterns.
Automated Cryptanalysis
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. One of the pertinent problems arising in automated cryptanalysis is the plaintext recognition. A computer should be able to decide which of many possible decrypts are meaningful. This can be accomplished by means of a text scoring function, based, e.g. on n-grams or other text statistics. A scoring function can also be used in conjunction with AI methods to speedup cryptanalysis.
Bio-Inspired Algorithms in Bioinformatics II
Authors: Seoane Fernández José Antonio , Miguélez Rico Mónica
Published: May 2011

Our previous article presented several computational models inspired on biological models, such as neural networks, evolutionary computation, swarm intelligence, and the artificial immune system. It also explained the most common problems in bioinformatics to which these models can be applied. The present article presents a series of approaches to bioinformatics tasks that were developed by means of artificial intelligence techniques and focus on bioinspired algorithms such as artificial neural networks and evolutionary computation.
Blind Source Separation by ICA
Authors: Ferrer Miguel A. , Tejera Santana Aday
Published: May 2011

This work presents a brief introduction to the blind source separation using independent component analysis (ICA) techniques. The main objective of the blind source separation (BSS) is to obtain, from observations composed by different mixed signals, those different signals that compose them. This objective can be reached using two different techniques, the spatial and the statistical one. The first one is based on a microphone array and depends on the position and separation of them. It also uses the directions of arrival (DOA) from the different audio signals. On the other hand, the statistical separation supposes that the signals are statistically independent, that they are mixed in a linear way and that it is possible to get the mixtures with the right sensors (Hyvärinen, Karhunen & Oja, 2001) (Parra, 2002). The last technique is the one that is going to be studied in this work. It is due to this technique is the newest and is in a continuous development. It is used in different fields such as natural language processing (Murata, Ikeda & Ziehe, 2001) (Saruwatari, Kawamura & Shikano, 2001), bioinformatics, image processing (Cichocki & Amari, 2002) and in different real life applications such as mobile communications (Saruwatari, Sawai, Lee, Kawamura, Sakata & Shikano, 2003). Specifically, the technique that is going to be used is the Independent Component Analysis (ICA). ICA comes from an old technique called PCA (Principal Component Analysis) (Hyvärinen, Karhunen & Oja, 2001) (Smith, 2006). PCA is used in a wide range of scopes such as face recognition or image compression, being a very common technique to find patterns in high dimension data. The BSS problem can be of two different ways; the first one is when the mixtures are linear. It means that the data are mixed without echoes or reverberations, while the second one, due to these conditions, the mixtures are convolutive and they are not totally independent because of the signal propagation through dynamic environments. It is the “Cocktail party problem”. Depending on the mixtures, there are several methods to solve the BSS problem. The first case can be seen as a simplification of the second one. The blind source separation based on ICA is also divided into three groups; the first one are those methods that works in the time domain, the second are those who works in the frequency domain and the last group are those methods that combine frequency and time domain methods. A revision of the technique state of these methods is proposed in this work.
Clustering Algorithm for Arbitrary Data Sets
Authors: Song Yu-Chen , Meng Hai-Dong
Published: May 2011

Clustering analysis is an intrinsic component of numerous applications, including pattern recognition, life sciences, image processing, web data analysis, earth sciences, and climate research. As an example, consider the biology domain. In any living cell that undergoes a biological process, different subsets of its genes are expressed in different stages of the process. To facilitate a deeper understanding of these processes, a clustering algorithm was developed (Ben- Dor, Shamir, & Yakhini, 1999) that enabled detailed analysis of gene expression data. Recent advances in proteomics technologies, such as two-hybrid, phage display and mass spectrometry, have enabled the creation of detailed maps of biomolecular interaction networks. To further understanding in this area, a clustering mechanism that detects densely connected regions in large protein-protein interaction networks that may represent molecular complexes was constructed (Bader & Hogue, 2003). In the interpretation of remote sensing images, clustering algorithms (Sander, Ester, Kriegel, & Xu, 1998) have been employed to recognize and understand the content of such images. In the management of web directories, document annotation is an important task. Given a predefined taxonomy, the objective is to identify a category related to the content of an unclassified document. Self-Organizing Maps have been harnessed to influence the learning process with knowledge encoded within a taxonomy (Adami, Avesani, & Sona, 2005). Earth scientists are interested in discovering areas of the ocean that have a demonstrable effect on climatic events on land, and the SNN clustering technique (Ertöz, Steinbach, & Kumar, 2002) is one example of a technique that has been adopted in this domain. Also, scientists have developed climate indices, which are time series that summarize the behavior of selected regions of the Earth’s oceans and atmosphere. Clustering techniques have proved crucial in the production of climate indices (Steinbach, Tan, Kumar, Klooster, & Potter, 2003). In many application domains, clusters of data are of arbitrary shape, size and density, and the number of clusters is unknown. In such scenarios, traditional clustering algorithms, including partitioning methods, hierarchical methods, density-based methods and gridbased methods, cannot identify clusters efficiently or accurately. Obviously, this is a critical limitation. In the following sections, a number of clustering methods are presented and discussed, after which the design of an algorithm based on Density and Density-reachable (CADD) is presented. CADD seeks to remedy some of the deficiencies of classical clustering approaches by robustly clustering data that is of arbitrary shape, size, and density in an effective and efficient manner.
CNS Tumor Prediction Using Gene Expression Data Part II
Authors: Islam Atiq , Iftekharuddin Khan M. , George E. Olusegun , Russomanno David J.
Published: May 2011

In this chapter, we propose a novel algorithm for characterizing a variety of CNS tumors. The proposed algorithm is illustrated with an analysis of an Affymetrix gene expression data from CNS tumor samples (Pomeroy et al., 2002). As discussed in the previous chapter entitled: CNS Tumor Prediction Using Gene Expression Data Part I, we used an ANOVA model to normalize the microarray gene expression measurements. In this chapter, we introduce a systemic way of building tumor prototypes to facilitate automatic prediction of CNS tumors.
Constraint Processing
Authors: Barták Roman
Published: May 2011

Constraints appear in many areas of human endeavour starting from puzzles like crosswords (the words can only overlap at the same letter) and recently popular Sudoku (no number appears twice in a row) through everyday problems such as planning a meeting (the meeting room must accommodate all participants) till solving hard optimization problems for example in manufacturing scheduling (a job must finish before another job). Though all these problems look like being from completely different worlds, they all share a similar base – the task is to find values of decision variables, such as the start time of the job or the position of the number at a board, respecting given constraints. This problem is called a Constraint Satisfaction Problem (CSP). Constraint processing emerged from AI research in 1970s (Montanary, 1974) when problems such as scene labelling were studied (Waltz, 1975). The goal of scene labelling was to recognize a type of line (and then a type of object) in the 2D picture of a 3D scene. The possible types were convex, concave, and occluding lines and the combination of types was restricted at junctions of lines to be physically feasible. This scene labelling problem is probably the first problem formalised as a CSP and some techniques developed for solving this problem, namely arc consistency, are still in the core of constraint processing. Systematic use of constraints in programming systems has started in 1980s when researchers identified a similarity between unification in logic programming and constraint satisfaction (Gallaire, 1985) (Jaffar & Lassez, 1987). Constraint Logic Programming was born. Today Constraint Programming is a separate subject independent of the underlying programming language, though constraint logic programming still plays a prominent role thanks to natural integration of constraints into a logic programming framework. This article presents mainstream techniques for solving constraint satisfaction problems. These techniques stay behind the existing constraint solvers and their understanding is important to exploit fully the available technology.
Continuous ACO in a SVR Traffic Forecasting Model
Authors: Samuelson Hong Wei-Chiang
Published: May 2011

The effective capacity of inter-urban motorway networks is an essential component of traffic control and information systems, particularly during periods of daily peak flow. However, slightly inaccurate capacity predictions can lead to congestion that has huge social costs in terms of travel time, fuel costs and environment pollution. Therefore, accurate forecasting of the traffic flow during peak periods could possibly avoid or at least reduce congestion. Additionally, accurate traffic forecasting can prevent the traffic congestion as well as reduce travel time, fuel costs and pollution. However, the information of inter-urban traffic presents a challenging situation; thus, the traffic flow forecasting involves a rather complex nonlinear data pattern and unforeseen physical factors associated with road traffic situations. Artificial neural networks (ANNs) are attracting attention to forecast traffic flow due to their general nonlinear mapping capabilities of forecasting. Unlike most conventional neural network models, which are based on the empirical risk minimization principle, support vector regression (SVR) applies the structural risk minimization principle to minimize an upper bound of the generalization error, rather than minimizing the training errors. SVR has been used to deal with nonlinear regression and time series problems. This investigation presents a short-term traffic forecasting model which combines SVR model with continuous ant colony optimization (SVRCACO), to forecast inter-urban traffic flow. A numerical example of traffic flow values from northern Taiwan is employed to elucidate the forecasting performance of the proposed model. The simulation results indicate that the proposed model yields more accurate forecasting results than the seasonal autoregressive integrated moving average (SARIMA) time-series model.