bluuebunny/crossref_metadata_2025 huggingface dataset:
Support of Online Learning through Intelligent Programs
Authors: Hamdi Mohamed Salah
Published: May 2011

Distance learning through the Internet is changing educational paradigms. Learning approaches, teaching methods, students’ expectations with instructional activities, and financial expectations are issues that challenge professionals and educational institutions (O´Donoghue, Singh & Dorward, 2001; Parikh & Verma, 2002). The growing availability of Internet access at working places and residences, in addition to a global market where education is a competitive advantage, are reasons for keeping the growth of investments in information technology for distance education. The distance education commercial arena currently involves universities, governments, and general educational institutions. Individuals and companies keep investing in educational programs for professional qualification, or even for keeping employees up to date with new technologies and market opportunities.
Supporting Online Collaborative Learning in Mathematics
Authors: Nason Rod , Woodruff Earl
Published: May 2011

Most school math problems do not require multiple cycles of designing, testing and refining (Lesh & Doerr, 2003), and therefore, do not elicit the collaboration between people with different repertoires of knowledge that most authentic math problems elicit (Nason & Woodruff, 2004). Another factor that limits the potential of most school math problems for eliciting knowledgebuilding discourse is that the answers generated from school math problems do not provide students with much worth discussing (Bereiter, 2002a). Another factor that has prevented most students from engaging in ongoing discourse and other mathematical knowledge-building activity within CSCL environments is the limitations inherent in most computerbased mathematical representational tools (Nason et al., 1996). Most of these tools are unable to carry out the crucial knowledge-building functions of: 1) generating multiple representations of mathematical concepts, 2) linking the different representations, and 3) transmitting meaning, sense and understanding.
Ten Scalability Factors in Distance Education
Authors: Laws R. Dwight , Howell Scott L. , Lindsay Nathan K.
Published: May 2011

The institutional decision about how much technology should be used to scale distance education enrollments, reduce costs, maximize profits, and protect course and program quality is both institutional specific and complex. Guri-Rosenblit (1999) noted that “many conventional universities worldwide operate as largescale universities and are in a continuous search to find the right balance between massification trends, quality education, and the catering to the individual needs of students” (p. 289). This research is an outgrowth of the authors’ own efforts to identify relevant scalability factors and their interrelationship one to another in a traditional university’s distance education program. This article identifies 10 additional factors beyond information technology (IT) or information communications technology (ICT) that merit careful consideration by decision makers as they define their own institutions’ degrees of scalability. Each institution’s level of scalability is determined or characterized in part by the interrelationship of these 10 factors within their given technological context or infrastructure: interaction, learning levels, student class standing, faculty tenure or continuing status, completion rates, cohort versus noncohort settings, degree- versus nondegree- seeking programs, market type, tuition costs, and profitability. The authors briefly examine their own distance education program and others, including those of mega-universities, across these 10 scalability factors.
Towards a Personalized E-Learning System
Authors: Leung Elvis Wai Chung , Li Qing
Published: May 2011

To cope with the increasing trend of learning demand and limited resources, most universities are taking advantage of Web-based technology for their distance education or e-learning (Montelpare & Williams, 2000). One of the reasons is due to the significant price drop of personal computers in recent decades; the Internet and multimedia have penetrated into most households. Moreover, most students prefer to learn from an interactive environment through a self-paced style. Under the Web-based learning model, students can learn anytime, anywhere because they are not required to go to school on schedule (Appelt, 1997). Meanwhile, universities also enjoy the economic benefit due to the large student base that can share the development cost of course materials and other operational expenses. Gradually, more and more universities follow this similar way to provide online education.
Using Intelligent Tutoring Technologies to Enhance Online Learning Environments
Authors: Wijekumar Kausalai Kay
Published: May 2011

Online and distance learning environments have changed dramatically over the last 20 years and are now sophisticated interactive learning environments. However, much more improvement is possible, and some of that improvement might come from mining some of the technologies developed as part of intelligent tutoring systems. Intelligent tutoring systems combine the best of human tutoring by capturing one on one tutoring interactions between a teacher and student on all topics for a learning module and converting them to a computerized version. The computerized version is designed to gauge the understanding of the student and adapt the instruction, modeling, hints, interactions, and activities to particular students. The systems are usually designed to assess the student’s learning continuously and scaffold the learning of the student. Ideally, these interactions will mimic human tutoring that has been shown to significantly improve learning beyond large group instruction.
Vicarious Learning
Authors: Lee John R.
Published: May 2011

In computer-based learning, we often find ourselves addressing our technology to an unexpectedly complex Web of issues in learning and instruction. Understanding what is going on may require us to take a step back and look at some more fundamental theoretical issues. This is the position we find ourselves in with the application of “vicarious learning”. On the face of it, this is the simple concept of accumulating a collection of records of learning experiences, which other learners can also use to learn from. Such a concept is apparently similar to observational learning, or to various notions of re-usable learning knowledge-bases. However, the specific suggestion we address here is that vicarious learning is a distinct idea that may have its own implications, particularly for distance learners and others whose access to normal learning dialogue is limited. In this article, then, we begin with a discussion of the general concept of vicarious learning, and its close relationship to the role of dialogue in learning. We use this understanding to motivate the application of vicarious learning in computer-based learning systems, and argue, against specific objections, that these systems show benefits that will be especially relevant for the groups mentioned above.
Web-Based Course Development Tools
Authors: Wu Hui-Ling
Published: May 2011

Web-based course development tools are software programs that facilitate the creation of online instructional material. These tools have become increasingly important in recent years; advances in technology have made e-learning more popular, but have done so without a parallel rise in the technological proficiency of educators attempting to design online courses. The conveniences of many web-based course development tools remove this problem, and the many types of applications currently in use have broadened the range of functions available to designers. This entry will discuss the major online course development tool innovations that have occurred in the recent years, the types of tools that are in common use among developers today, and the ways in which these tools may be utilized.
Magnetic Resonance Imaging and the Signal-Image Processing Techniques Developed Under the Umbrella of the Unifying Theory
Authors: Ciulla Carlo
Published: May 2011

The forthcoming text of this chapter is intended to raise the debate about the content of the book. To fulfill this purpose, is presented in first instance a section that summarizes on how the literature is reviewed throughout the book and also the MRI database employed to validate the unifying theory. Following this presentation, the chapter introduces to the reader the concept behind the basic issue relating to signal-image interpolation, which is the preservation of the signal (image) energy after processing with interpolation. This concept is strictly related to the approximation properties of the interpolation functions and consequently to the interpolation error. This concept is widely accepted in literature and is viewed in this works with a different and innovative perspective. The discussion undertaken in this chapter then introduces the signal-image processing techniques that were developed under the umbrella of the unifying theory. These are: (i) the SRE-based interpolation functions, (ii) the spectral power evolutions, (iii) a three layered artificial neural network with the added capability to generate its internal architecture during the learning process such to adjust to the given pattern classification task.
The Intuition
Authors: Ciulla Carlo
Published: May 2011

This chapter reports on the initial idea which gave birth to the investigation which subsequently became the unifying theory. The intuition herein illustrated consists of the realization that the following concept might have been supported by reasonable ground of truth after extensive study. The concept is that there exists a region of spatial extent within two nodes (1D), a pixel (2D), or a voxel (3D) where the interpolation function has best approximation properties. Naturally, the adjective best is to be interpreted with its relativity to the potentiality of the specific model interpolation function to determine approximation properties. Such potentiality according to the intuition resides in: (i) the sequel of discrete samples (e.g. the pixel intensities for the two-dimensional case), and (ii) the curvature of the model interpolator as expressed by its second order derivatives. The study in this chapter is initiated for the trivariate linear interpolation function and formalized through a set of definitions, an observation and a theorem.
The Conception of the Sub-Pixel Efficacy Region
Authors: Ciulla Carlo
Published: May 2011

This chapter presents the mathematical deduction of the Sub-pixel Efficacy Region (SRE) for the case of the trivariate liner interpolation function. The questions that the reader may have at this point are: (i) what is the need of defining the Sub-pixel efficacy Region once again? And (ii) why the Sub-pixel Efficacy Region is to be calculated on the basis of the Intensity-Curvature Functional?
Assessment of the Truth Foreseen in the Intuition
Authors: Ciulla Carlo
Published: May 2011

This chapter continues the investigation conducted through deduction from the previous three chapters. Chapter II of the book has brought to light an intuition that has allowed the conception of the Sub- Pixel Efficacy Region and its definition. Chapter III outlines the conception of the Intensity-Curvature functional as a measure of the change in energy level of the signal because of the effect of the model interpolation function on the signal (image). Chapter IV studies the Intensity-Curvature Functional (?E) and through the solution of the polynomial system obtained from the first order partial derivatives of ?E, elucidates that a spatial set of points within the voxel is calculated from the Intensity-Curvature Functional and is assigned the name of Sub-pixel Efficacy Region (SRE).
The Results of the Sub-Pixel Efficacy Region Based Bivariate Linear Interpolation Function
Authors: Ciulla Carlo
Published: May 2011

This is the first of the chapters of the book that present results obtained processing the MRI database with both classic and SRE-based interpolation paradigms. The focus of this chapter is on the bivariate linear interpolation function. An overview on the validation paradigm is given along with an explanation of the simulations that were conducted in order to validate the SRE-based bivariate liner interpolation function. Subsequently, results with real MRI are shown quantitatively through plots of the metric called RMSE Ratio which was employed to assess which one between classic and SRE-based interpolation furnishes lower root-mean-square-error (RMSE). Qualitative demonstration of the results with MRI is also given. The chapter also discusses and evaluates the case of interpolation error improvement when the novel re-sampling location within the pixel is placed on the x axis of the coordinate system (i.e. yr0 = 0) and consistently, both quantitative and qualitative results are presented through plots of the RSME Ratio and figures respectively.
The Extension of Theory and Methodology to B-Splines
Authors: Ciulla Carlo
Published: May 2011

The organization of the chapter is similar to that of Chapters VII and X. The methodological approach to extend the unifying theory to the one dimensional quadratic and cubic B-Splines is herein reported along with the most relevant mathematical details. This chapter should be read along with Appendix VI where proofs are given to the assertions herein presented. In either of the two cases: quadratic and cubic B-Spline the math process starts from the calculation of the Intensity-Curvature Functional and continues with the calculation of the Sub-pixel Efficacy Region. Finally, the math process arrives to the calculation of the novel re-sampling locations through the formulas of the unifying theory seen in equations (23) and (33) for the quadratic and the cubic models respectively. The chapter concludes with a section that addresses specifically the theoretical proposition of resilient interpolation for the two classes of B-Splines. This is conducted consistently with Chapters VII and XII of the book choosing to equate the two intensity-curvature terms (before and after interpolation) as the starting point of the math deduction.
Augmentative and Alternative Communication Devices
Authors: Smith Martine , Murray Janice
Published: May 2011

Over the last 30 years, significant advances have been made in the technology supporting augmentative and alternative communication devices. However, technology often brings with it as many problems as solutions. This chapter reports on data collected in interviews with adults who use aided communication. In these interviews, they discuss aspects of their communication world and the opportunities and barriers they face. The chapter highlights some of the diversity of individuals who use, or who choose not to use, aided communication. It also considers the complexity of factors that may critically influence communication experiences and discusses some of these factors within the framework of the International Classification of Functioning, Disability and Health (ICF).
Personal Knowledge Management Skills for Lifelong-Learners 2.0
Authors: Pettenati M. C. , Cigognini M. E. , Guerin E. M.C. , Mangione G. R.
Published: May 2011

In this chapter the authors identify the Personal Knowledge Management (PKM) pre-dispositions, skills and competences of the current effective lifelong-learner 2.0. They derive a PKM-skills model centred on a division into basic PKM competences, associated with social software Web practices of create-organize- share, and Higher-Order skills (HO-skills), which identify enabling conditions and competences which favour the advanced management of one’s personal knowledge (PK). To derive the PKM-skills model we addressed a survey to 16 interviewees who can be defined as expert lifelong-learners 2.0. The HO-skills branch out into four macro competences, identified as connectedness, ability to balance formal and informal contexts, critical ability and creativity.
A Rule-Based and Game-Theoretic Approach to On-Line Credit Card Fraud Detection
Authors: Vatsa Vishal , Sural Shamik , Majumdar A.K.
Published: May 2011

Traditional security mechanisms are often found to be inadequate for protection against attacks by authorized users or intruders posing as authorized users. This has drawn interest of the research community towards intrusion detection techniques. The authors model the conflicting motives between an intruder and an intrusion detection system as a multi-stage game between two players, each trying to maximize its payoff. They consider the specific application of credit card fraud detection and propose a two-tiered architecture having a rule-based component in the first tier and a Game-theoretic component in the second tier. Classical Game theory is considered useful in many situations because it permits the formulation of strategies that are optimal regardless of what the adversary does, negating the need for prediction of his behavior. However, the authors use it in a predictive application in the sense that we consider intruders as rational adversaries who would try to behave optimally, and the expected optimal behavior can be determined through Game theory.
A Dimensionality Reduction-Based Transformation to Support Business Collaboration
Authors: Oliveira Stanley R.M. , Zaiane Osmar R.
Published: May 2011

While the sharing of data is known to be beneficial in data mining applications and widely acknowledged as advantageous in business, this information sharing can become controversial and thwarted by privacy regulations and other privacy concerns. Data clustering for instance could be more accurate if more information is available, hence the data sharing. Any solution needs to balance the clustering requirements and the privacy issues. Rather than simply hindering data owners from sharing information for data analysis, a solution could be designed to meet privacy requirements and guarantee valid data clustering results. To achieve this dual goal, this chapter introduces a method for privacy-preserving clustering, called Dimensionality Reduction-Based Transformation (DRBT). This method relies on the intuition behind random projection to protect the underlying attribute values subjected to cluster analysis. It is shown analytically and empirically that transforming a dataset using DRBT, a data owner can achieve privacy preservation and get accurate clustering with little overhead of communication cost. Such a method presents the following advantages: it is independent of distance-based clustering algorithms; it has a sound mathematical foundation; and it does not require CPU-intensive operations.
On the Design of an Authentication System Based on Keystroke Dynamics Using a Predefined Input Text
Authors: Bartmann Dieter , Bakdi Idir , Achatz Michael
Published: May 2011

The design of an authentication system based on keystroke dynamics is made difficult by the fact that the typing behaviour of a person is subject to strong fluctuations. An asymmetrical method able to handle this difficulty by using a long text on enrolment and a short one at login is analysed in this paper. The results of an empirical study based on an extensive field test are presented. The study demonstrates that the advantages of the analysed method remain even if a predefined input text is used. The results also show that the method’s quality highly depends on the amount of text typed on enrolment as well as on login, which makes the system scalable to different security levels. They also confirm the importance of using stable characteristics that are due, that is, to the user’s right- or left-handedness. The method’s learning velocity is shown to be high, which enables enrolment to be kept short. Moreover, the study demonstrates that admitting multiple login attempts significantly ameliorates the recognition performance without sacrificing security.
A Content-Based Watermarking Scheme for Image Authentication Using Discrete Wavelet Transform Inter-Coefficient Relations
Authors: Parameswaran Latha , Anbumani K
Published: May 2011

This chapter discusses a content-based authentication technique based on inter-coefficient relationship of Discrete Wavelet Transform (DWT). Watermark is generated from the first level DWT. An image digest (which is a binary string) is generated from the second level DWT. The watermark is embedded in the mid-frequency coefficients of first level DWT as directed by the image digest. Image authentication is done by computing the Completeness of Signature. The proposed scheme is capable of withstanding incidental image processing operations such as compression and identifies any malicious tampering done on the host image.
Trustworthy Web Services
Authors: Yang Stephen J.H. , Lan Blue C.W. , Hsieh James S.F. , Chung Jen-Yao
Published: May 2011

Web service technology enables seamlessly integration of different software to fulfill dynamic business demands in a platform-neutral fashion. However, the adoption of loosely coupled and distributed services will cause trustworthiness problems. In this chapter, the authors present an experience-based evaluation of service’s trustworthiness based on trust experience (understanding) and trust requirements (policy). The authors utilize ontology to specify past experiences of services and trustworthy requirement of requester. Before invoking found services, the addressed method can help requester evaluate the trustworthiness of the services based on his trustworthy requirements and past experiences of the services. Furthermore, they also present an evaluation method for composite services by taking the structure of the composite services into account. The main contribution of the paper is providing evaluation methods for Web services such that service requester can make better decision in selecting found services in terms of service’s trustworthiness.
Administering the Semantic Web
Authors: Thuraisingham Bhavani , Tsybulnik Natasha , Alam Ashraful
Published: May 2011

The Semantic Web is essentially a collection of technologies to support machine understandable Web pages as well as Information Interoperability. There has been much progress made on the Semantic Web including standards for eXtensible Markup Language, Resource Description Framework and Onotlogies. However, administration policies and techniques for enforcing them have received little attention. These policies include policies for security, privacy, data quality, integrity, trust and timely information processing. This chapter discusses administration policies for the Semantic Web as well as techniques for enforcing them. In particular, the authors will discuss an approach for ensuring confidentiality, privacy and trust for the Semantic Web. We will also discuss the inference and privacy problems within the context of administration policies.
Models of Complex-Valued Hopfield-Type Neural Networks and Their Dynamics
Authors: Kuroe Yasuaki
Published: May 2011

This chapter presents models of fully connected complex-valued neural networks which are complex-valued extension of Hopfield-type neural networks and discusses methods to study their dynamics. In particular the authors investigate existence conditions of energy functions for complex-valued Hopfield-type neural networks. Emphasized are the properties of the activation functions which assure the existence of an energy function for the networks. As an application of the energy function, qualitative analysis of the network by utilizing the energy function is shown and a synthesis method of complex-valued associative memories is discussed.
Image Reconstruction by the Complex-Valued Neural Networks
Authors: Lee Donq-Liang
Published: May 2011

New design methods for the complex-valued multistate Hopfield associative memories (CVHAMs) are presented. The author of this chapter shows that the well-known projection rule can be generalized to complex domain such that the weight matrix of the CVHAM can be designed by using the generalized inverse technique. The stability of the presented CVHAM is analyzed by using energy function approach which shows that in synchronous update mode a CVHAM is guaranteed to converge to a fixed point from any given initial state. Moreover, the projection geometry of the generalized projection rule is discussed. In order to enhance the recall capability, a strategy of eliminating the spurious memories is reported. Next, a generalized intraconnected bidirectional associative memory (GIBAM) is introduced. A GIBAM is a complex generalization of the intraconnected BAM (IBAM). Lee shows that the design of the GIBAM can also be accomplished by using the generalized inverse technique. Finally, the validity and the performance of the introduced methods are investigated by computer simulation.
Facial Gesture Recognition
Authors: Kim Daijin , Sung Jaewon
Published: May 2011

From facial gestures, we can extract many kinds of messages in human communication: they represent visible speech signals and clarify whether our current focus of attention is important, funny or unpleasant for us. They are direct, naturally preeminent means for humans to communicate their emotions (Russell and Fernandez-Dols, 1997). Automatic analyzers of subtle facial changes, therefore, seem to have a natural place in various vision systems including automated tools for psychological research, lip reading, bimodal speech analysis, affective computing, face and visual-speech synthesis, and perceptual user interfaces.
Data Mining in Atherosclerosis Risk Factor Data
Authors: Berka Petr , Rauch Jan , Tomecková Marie
Published: May 2011

The aim of this chapter is to describe goals, current results, and further plans of long-time activity concerning application of data mining and machine learning methods to the complex medical data set. The analyzed data set concerns a longitudinal study of atherosclerosis risk factors. The structure and main features of this data set, as well as methodology of observation of risk factors, are introduced. The important first steps of analysis of atherosclerosis data are described in details together with a large set of analytical questions defined on the basis of first results. Experience in solving these tasks is summarized and further directions of analysis are outlined.
Security Issues in Pervasive Computing
Authors: Mohammed Lawan Ahmed , Munir Kashif
Published: May 2011

The change in physical structures of computing facilities into small and portable devices, or even wearable computers, has enhanced ubiquitous information processing. The basic paradigm of such pervasive computing is the combination of strongly decentralized and distributed computing with the help of diversified devices allowing for spontaneous connectivity via the Internet. In general, pervasive computing strives to simplify day-to-day life by providing mobile users with the means to carry out personal and business tasks via mobile and portable devices. This chapter examines the security challenges that are barriers to mainstream pervasive computing and explains why traditional security mechanisms fail to meet the demands of these environments.
What Led Us Here?
Authors: Burgess Stephen , Carmine Sellitto Carmine , Karanasios Stan
Published: May 2011

This Appendix provides a brief overview of our PhDs - all of which involved research into small business adoption and use of ICT and Internet technologies. In effect, we felt that this appendix might provide some insights into how this book has evolved and the way that the various chapters have been ordered. In the case of Stephen and Stan’s PhDs, they particularly targeted small businesses, whilst Carmine’s PhD involved research into wineries in Australia – and involved a heavy emphasis on SMEs. More importantly, each of our PhDs involved the development of frameworks which have informed the outline of chapters in this book, and significant background material which have contributed the book’s contents. Each of us will discuss a little of how the PhD has lead us to where we are today.
Adaptation and Congestion in a Multi-Agent System to Analyse Empirical Traffic Problems
Authors: Takama Takeshi
Published: May 2011

This study discusses adaptation effects and congestion in a multi-agent system (MAS) to analyse real transport and traffic problems. Both methodological discussion and an empirical case study are presented in this chapter. The main focus is on the comparison of an analysis of a MAS simulation analysis and an analysis that solely uses discrete choice modelling. This study explains and discusses some important concepts in design empirical MAS in traffic and transportation, including validation Minority Game and adaptation effects. This study develops an empirical MAS simulation model based on real stated-preference data to analyse the effect of a real road-user charge policy and a complimentary park and ride scheme at the Upper Derwent Valley in the Peak District National Park, England. The simulation model integrates a transport mode choice model, Markov queue model, and Minority Game to overcome the disadvantages of a conventional approach. The results of the simulation model show that the conventional analysis overestimates the effect of the transportation and environment policy due to the lack of adaptation affects of agents and congestion. The MAS comprehensively analysed the mode choices, congestion levels, and the user utility of visitors while including the adaptability of agents. The MAS also called as agent-based simulation successfully integrates models from different disciplinary backgrounds, and shows interesting effects of adaptation and congestion at the level of an individual agent.
A Multidimensional Methodology with Support for Spatio-Temporal Multigranularity in the Conceptual and Logical Phases
Authors: Gascueña Concepción M. , Guadalupe Rafael
Published: May 2011

The Multidimensional Databases (MDB) are used in the Decision Support Systems (DSS) and in Geographic Information Systems (GIS); the latter locates spatial data on the Earth’s surface and studies its evolution through time. This work presents part of a methodology to design MDB, where it considers the Conceptual and Logical phases, and with related support for multiple spatio-temporal granularities. This will allow us to have multiple representations of the same spatial data, interacting with other, spatial and thematic data. In the Conceptual phase, the conceptual multidimensional model—FactEntity (FE)—is used. In the Logical phase, the rules of transformations are defined, from the FE model, to the Relational and Object Relational logical models, maintaining multidimensional semantics, and under the perspective of multiple spatial, temporal, and thematic granularities. The FE model shows constructors and hierarchical structures to deal with the multidimensional semantics on the one hand, carrying out a study on how to structure “a fact and its associated dimensions.” Thus making up the Basic factEnty, and in addition, showing rules to generate all the possible Virtual factEntities. On the other hand, with the spatial semantics, highlighting the Semantic and Geometric spatial granularities.
Predictive Models of Cultural Information Transmission
Authors: Upal M. Afzal
Published: May 2011

This chapter will critically review existing approaches to the modeling transmission of cultural information and advocate a new approach based on a new generation of agent-based social simulation systems. It will outline how such systems can be useful for studying the formation of patterns of widely shared cultural beliefs.
The Human Mirror Neuron System
Authors: Newlin David B.
Published: May 2011

Following the discovery in Rhesus monkeys of “mirror neurons” that fire during both execution and observation of motor behavior, human studies have documented a fronto-parietal mirror neuron system (MNS) with apparently similar functions. We discuss some issues related to the human research, including measurement with neuro imaging techniques and recent neuro technologies for manipulating regional brain function. We note the remarkable overlap between several brain systems studied in people: the MNS, the Theory of Mind (ToM), the “self”-system of the brain, and the neural “default mode.” The functional architecture of these systems may have important implications for how the MNS is organized and its functions. We propose that “auto-mirroring” in which self-observation of one’s own motor behavior can be either facilitated or blocked, may be a fundamental aspect of the MNS. Finally, the implications of hemispheric asymmetry in the right and left MNS are discussed. Although MNS research is in its infancy, it bears promise to reveal basic aspects of the brain’s functional architecture.
The Role of Learner in an Online Community of Inquiry
Authors: Cleveland-Innes Martha , Garrison Randy , Kinsel Ellen
Published: May 2011

Learners experiencing an online educational community for the first time can explain the adjustment required for participation. Findings from a study of adjustment to online learning environments validate differences found in 3 presences in an online community of inquiry. Using pre- and post-questionnaires, students enrolled in entry-level courses in 2 graduate degree programs at Athabasca University, Canada, describe their adjustment to online learning. Responses were analyzed in relation to the elements of cognitive, social, and teaching presence, defined by Garrison, Anderson, and Archer (2000) as core dimensions of learner role requirements in an online community of inquiry. Five areas of adjustment characterize the move toward competence in online learning: interaction, self-identity, instructor role, course design, and technology. Student comments provide understanding of the experience of first-time online learners, including the challenges, interventions, and resolutions that present themselves as unique incidents. Recommendations for the support and facilitation of adjustment are made.
Cognition, Technology, and Performance
Authors: Lang Teresa , Hall Dianne
Published: May 2011

Development and sale of computer-assisted instructional supplements and course management system products are increasing. Textbook sales representatives use this technology to market textbooks, and many colleges and universities encourage the use of such technology. The use of course management systems in education has been equated to the use of enterprise resource planning software by large businesses. Research findings about the pedagogical benefits of computer-assisted instruction and computer management systems are inconclusive. This study describes an experiment conducted to determine the benefit to students of using course management systems. The effects of cognition, learning styles, and computer attitude were considered and eliminated to better isolate any differences in performance. Student performance did not improve with the use of the technology.
A Paraconsistent Relational Data Model
Authors: Viswanath Navin , Sunderraman Rajshekhar
Published: May 2011

Typically, relational databases operate under the Closed World Assumption (CWA) of Reiter (Reiter, 1987). The CWA is a meta-rule that says that given a knowledge base KB and a sentence P, if P is not a logical consequence of KB, assume ~P (the negation of P). Thus, we explicitly represent only positive facts in a knowledge base. A negative fact is implicit if its positive counterpart is not present. Under the CWA we presume that our knowledge about the world is complete i.e. there are no “gaps” in our knowledge of the real world. The Open World Assumption (OWA) is the opposite point of view. Here, we “admit” that our knowledge of the real world is incomplete. Thus we store everything we know about the world – positive and negative. Consider a database which simply contains the information “Tweety is a bird”. Assume that we want to ask this database the query “Does Tweety fly?”. Under the CWA, since we assume that there are no gaps in our knowledge, every query returns a yes/no answer. In this case we get the answer “no” because there is no information in the database stating that Tweety can fly. However, under the OWA, the answer to the query is “unknown”. i.e. the database does not know whether Tweety flies or not. We would obtain a “no” answer to this query under the OWA only if it was explicitly stated in the database that Tweety does not fly.
Principles on Symbolic Data Analysis
Authors: Nigro Héctor Oscar , González Císaro Sandra Elizabeth
Published: May 2011

Today’s technology allows storing vast quantities of information from different sources in nature. This information has missing values, nulls, internal variation, taxonomies, and rules. We need a new type of data analysis that allows us represent the complexity of reality, maintaining the internal variation and structure (Diday, 2003). In Data Analysis Process or Data Mining, it is necessary to know the nature of null values - the cases are by absence value, null value or default value -, being also possible and valid to have some imprecision, due to differential semantic in a concept, diverse sources, linguistic imprecision, element resumed in Database, human errors, etc (Chavent, 1997). So, we need a conceptual support to manipulate these types of situations. As we are going to see below, Symbolic Data Analysis (SDA) is a new issue based on a strong conceptual model called Symbolic Object (SO). A “SO” is defined by its “intent” which contains a way to find its “extent”. For instance, the description of habitants in a region and the way of allocating an individual to this region is called “intent”, the set of individuals, which satisfies this intent, is called “extent” (Diday 2003). For this type of analysis, different experts are needed, each one giving their concepts.
Database Reverse Engineering
Authors: Hainaut Jean-Luc , Henrard Jean , Roland Didier , Hick Jean-Marc , Englebert Vincent
Published: May 2011

Database reverse engineering consists of recovering the abstract descriptions of files and databases of legacy information systems. A legacy information system can be defined as a “data-intensive application, such as [a] business system based on hundreds or thousands of data files (or tables), that significantly resists modifications and changes” (Brodie & Stonebraker, 1995). The objective of database reverse engineering is to recover the logical and conceptual descriptions, or schemas, of the permanent data of a legacy information system, that is, its database, be it implemented as a set of files or through an actual database management system.
Imprecise Functional Dependencies
Authors: Deufemia Vincenzo , Polese Giuseppe , Vacca Mario
Published: May 2011

Functional dependencies represent a fundamental concept in the design of a database since they are capable of capturing some semantics of the data strongly connected with the occurrence of redundancy in a database. The development of applications working on fuzzy and multimedia databases has required the extension of the functional dependency notion to these new types of data. Unfortunately, the concept of imprecise functional dependence or fuzzy functional dependence (IFD, for short) has not had a cogent and largely accepted definition yet. In fact, in attempt to capture different aspects of this notion of many proposals of IFD definition exist in literature, all having semantics and objectives somewhat unclear, especially with respect to the concern of redundancy (Bosc, et al., 1994, Cubero & Vila, 1994, Raju & Majumdar, 1988, Tyagi, et al., 2005, Wang, et al., 2000). Moreover, the debate on the definition of the concept of fuzzy functional dependency seems to be still in progress, as shown by the following question: “But the question remains: are these extended notions of functional dependency a natural generalization?” (Tyagi et al., 2005).
Supporting Location-Based Services in Spatial Network Databases
Authors: Huang Xuegang
Published: May 2011

Location-based services (LBSs) utilize consumer electronics, mobile communications, positioning technology, and traditional map information to provide mobile users with new kinds of online services. Examples include location-sensitive information services that identify points of interest that are in some sense nearest and of interest to their users and that offer travel directions to their users. Data management is a core aspect of the provisioning of LBSs. The diversity and complexity of LBSs demand novel and advanced data management techniques. The scenario of network-constrained movement is of particular interest to LBSs as a large amount of users of LBSs are car drivers and mobile users moving in vehicles. We term the transportation networks where LBS users are moving as spatial networks. The databases that manage the spatial network data as well as other relevant data are termed spatial network databases (SNDBs). Data management in SNDBs poses novel challenges to the database research community. Specifically, most existing discussions on spatial databases assume that objects can move arbitrarily in Euclidean space. The fundamental difference between network-constrained space and the Euclidean space is that the distance of two objects cannot be computed by their coordinates but by the shortest path on the network (Jensen, Kolár, Pedersen, & Timko, 2003). This makes it difficult to extend the existing data models, indexing structures, and query processing techniques from spatial databases to SNDBs.
Data Quality Assessment
Authors: Kulikowski Juliusz L.
Published: May 2011

For many years the fact that for a high information processing systems’ effectiveness high quality of data is not less important than high systems’ technological performance was not widely understood and accepted. The way to understanding the complexity of data quality notion was also long, as it will be shown below. However, a progress in modern information processing systems development is not possible without improvement of data quality assessment and control methods. Data quality is closely connected both with data form and value of information carried by the data. High-quality data can be understood as data having an appropriate form and containing valuable information. Therefore, at least two aspects of data are reflected in this notion: 1st - technical facility of data processing, and 2nd - usefulness of information supplied by the data in education, science, decision making, etc.
Measuring Data Quality in Context
Authors: Shankaranarayanan G. , Even Adir
Published: May 2011

Maintaining data at a high quality is critical to organizational success. Firms, aware of the consequences of poor data quality, have adopted methodologies and policies for measuring, monitoring, and improving it (Redman, 1996; Eckerson, 2002). Today’s quality measurements are typically driven by physical characteristics of the data (e.g., item counts, time tags, or failure rates) and assume an objective quality standard, disregarding the context in which the data is used. The alternative is to derive quality metrics from data content and evaluate them within specific usage contexts. The former approach is termed as structure-based (or structural), and the latter, content-based (Ballou and Pazer, 2003). In this chapter we propose a novel framework to assess data quality within specific usage contexts and link it to data utility (or utility of data) - a measure of the value contribution associated with data within specific usage contexts. Our utility-driven framework addresses the limitations of structural measurements and offers alternative measurements for evaluating completeness, validity, accuracy, and currency, as well as a single measure that aggregates these data quality dimensions.
Querying and Integrating P2P Deductive Databases
Authors: Caroprese Luciano , Greco Sergio , Zumpano Ester
Published: May 2011

Recently, there have been several proposals that consider the integration of information and the computation of queries in an open-ended network of distributed peers (Bernstein, Giunchiglia, Kementsietsidis, Mylopulos, Serafini, & Zaihrayen, 2002; Calvanese, De Giacomo, Lenzerini, & Rosati, 2004; Franconi, Kuper, Lopatenko, & Zaihrayeu, 2003) as well as the problem of schema mediation and query optimization in P2P (peerto- peer) environments (Gribble, Halevy, Ives, Rodrig, & Suciu, 2001; Halevy, Ives, Suciu, & Tatarinov, 2003; Madhavan & Halevy, 2003; Tatarinov & Halevy, 2004). Generally, peers can both provide or consume data and the only information a peer participating in a P2P system has is about neighbors, that is, information about the peers that are reachable and can provide data of interest. More specifically, each peer joining a P2P system exhibits a set of mapping rules, in other words, a set of semantic correspondences to a set of peers that are already part of the system (neighbors). Thus, in a P2P system, the entry of a new source, or peer, is extremely simple as it just requires the definition of the mapping rules. By using mapping rules as soon as it enters the system, a peer can participate and access all data available in its neighborhood, and through its neighborhood it becomes accessible to all the other peers in the system.
Ontologies Application to Knowledge Discovery Process in Databases
Authors: Nigro Héctor Oscar , González Císaro Sandra Elizabeth
Published: May 2011

Nowadays one of the most important and challenging problems in Knowledge Discovery Process in Databases (KDD) or Data Mining is the definition of the prior knowledge; this can be originated either from the process or the domain. This contextual information may help select the appropriate information, features or techniques, decrease the space of hypothesis, represent the output in a more comprehensible way and improve the whole process.
Data Clustering
Authors: Zhao Yanchang , Cao Longbing , Zhang Huaifeng , Zhang Chengqi
Published: May 2011

Clustering is one of the most important techniques in data mining. This chapter presents a survey of popular approaches for data clustering, including well-known clustering techniques, such as partitioning clustering, hierarchical clustering, density-based clustering and grid-based clustering, and recent advances in clustering, such as subspace clustering, text clustering and data stream clustering. The major challenges and future trends of data clustering will also be introduced in this chapter. The remainder of this chapter is organized as follows. The background of data clustering will be introduced in Section 2, including the definition of clustering, categories of clustering techniques, features of good clustering algorithms, and the validation of clustering. Section 3 will present main approaches for clustering, which range from the classic partitioning and hierarchical clustering to recent approaches of bi-clustering and semisupervised clustering. Challenges and future trends will be discussed in Section 4, followed by the conclusions in the last section.