bluuebunny/crossref_metadata_2025 huggingface dataset:
COBRAS
Authors: Karoui Hager
Published: May 2011

In this chapter, the authors propose a case-based reasoning recommender system called COBRAS: a Peer-to-Peer (P2P) bibliographical reference recommender system. COBRAS’s task is to find relevant documents and interesting people related to the interests and preferences of a single person belonging to a like-minded group in an implicit and an intelligent way. Each user manages their own bibliographical database in isolation from others. Target users use a common vocabulary for document indexing but may interpret the indexing vocabulary differently from others. Software agents are used to ensure indirect cooperation between users. A P2P architecture is used to allow users to control their data sharing scheme with others and to ensure their autonomy and privacy. The system associates a software assistant agent with each user. Agents are attributed three main skills: a) detecting the associated user’s hot topics, b) selecting a subset of peer agents that are likely to provide relevant recommendations, and c) recommending both documents and other agents in response to a recommendation request sent by a peer agent. The last two skills are handled by implementing two inter-related data-driven case-based reasoning systems. The basic idea underlying the document recommendation process is to map hot topics sent by an agent to local topics. Documents indexed by mapped topics are then recommended to the requesting agent. This agent will provide later, a relevance feedback computed after the user evaluation of the received recommendations. Provided feedbacks are used to learn to associate a community of peer agents to each local hot topic. An experimental study involving one hundred software agents using real bibliographical data is described. The Obtained results demonstrate the validity of the proposed approach.
Music Recommendation by Modeling User's Preferred Perspectives of Content, Singer/Genre and Popularity
Authors: Cataltepe Zehra , Altinel Berna
Published: May 2011

As the amount, availability, and use of online music increase, music recommendation becomes an important field of research. Collaborative, content-based and case-based recommendation systems and their hybrids have been used for music recommendation. There are already a number of online music recommendation systems. Although specific user information, such as, demographic data, education, and origin have been shown to affect music preferences, they are usually not collected by the online music recommendation systems, because users would not like to disclose their personal data. Therefore, user models mostly contain information about which music pieces a user liked and which ones s/he did not and when.
An Artificial Immune Dynamical System for Optimization
Authors: Jiao Licheng , Gong Maoguo , Ma Wenping
Published: May 2011

Many immue-inspired algorithms are based on the abstractions of one or several immunology theories, such as clonal selection, negative selection, positive selection, rather than the whole process of immune response to solve computational problems. In order to build a general computational framework by simulating immune response process, this chapter introduces a population-based artificial immune dynamical system, termed as PAIS, and applies it to numerical optimization problems. PAIS models the dynamic process of human immune response as a quaternion (G, I, R, Al), where G denotes exterior stimulus or antigen, I denotes the set of valid antibodies, R denotes the set of reaction rules describing the interactions between antibodies, and Al denotes the dynamic algorithm describing how the reaction rules are applied to antibody population. Some general descriptions of reaction rules, including the set of clonal selection rules and the set of immune memory rules are introduced in PAIS. Based on these reaction rules, a dynamic algorithm, termed as PAISA, is designed for numerical optimization. In order to validate the performance of PAISA, 9 benchmark functions with 20 to 10,000 dimensions and a practical optimization problem, optimal approximation of linear systems are solved by PAISA, successively. The experimental results indicate that PAISA has high performance in optimizing some benchmark functions and practical optimization problems.
Immunocomputing for Spatio-Temporal Forecast
Authors: Tarakanov Alexander O.
Published: May 2011

Based on mathematical models of immunocomputing, this chapter describes an approach to spatio-temporal forecast (STF) by intelligent signal processing. The approach includes both low-level feature extraction and highlevel (“intelligent”) pattern recognition. The key model is the formal immune network (FIN) including apoptosis (programmed cell death) and immunization both controlled by cytokines (messenger proteins). Such FIN can be formed from raw signal using discrete tree transform (DTT), singular value decomposition (SVD), and the proposed index of inseparability in comparison with the Renyi entropy. Real-world application is demonstrated on data of space monitoring of the Caspian, Black, and Barents Sea. A surprising result is strong negative correlation between anomalies of sea surface temperature (SST) and sunspot number (SSN). This effect can be utilized for long-term STF.
Artificial Life Optimization Algorithm and Applications
Authors: Yang Bo-Suk
Published: May 2011

This chapter describes a hybrid artificial life optimization algorithm (ALRT) based on emergent colonization to compute the solutions of global function optimization problem. In the ALRT, the emergent colony is a fundamental mechanism to search the optimum solution and can be accomplished through the metabolism, movement and reproduction among artificial organisms which appear at the optimum locations in the artificial world. In this case, the optimum locations mean the optimum solutions in the optimization problem. Hence, the ALRT focuses on the searching for the optimum solution in the location of emergent colonies and can achieve more accurate global optimum. The optimization results using different types of test functions are presented to demonstrate the described approach successfully achieves optimum performance. The algorithm is also applied to the test function optimization and optimum design of short journal bearing as a practical application. The optimized results are compared with those of genetic algorithm and successive quadratic programming to identify the optimizing ability.
Ethology-Based Approximate Adaptive Learning
Authors: Peters James F. , Shahfar Shabnam
Published: May 2011

The problem considered in this chapter is how to use the observed behavior of organisms as a basis for machine learning. The proposed approach for machine learning combines near sets and ethology. It leads to novel forms of Q-learning algorithm that have practical applications in the controlling the behavior of machines, which learn to adapt to changing environments. Both traditional and new forms of adaptive learning theory and applications are considered in this chapter. A complete framework for an ethology-based approximate adaptive learning is established by using near sets.
Significance Estimation in fMRI from Random Matrices
Authors: Voultsidou Marotesa , Herrmann J. Michael
Published: May 2011

Indicative features of an fMRI data set can be evaluated by methods provided by theory of random matrices (RMT). RMT considers ensembles of matrices and yields statements on the properties of the typical eigensystems in these ensembles. The authors have studied the particular ensemble of random correlation matrices that can be used as a noise model for the empirical data and that allows us thus to select data features that significantly differ from the noisy background. In this sense RMT can be understood as offering a systematic approach to surrogate data. Interestingly, also the noise characteristics change between different experimental conditions. This is revealed by higher-order statistics available from RMT. The authors illustrate the RMT-based approach by an exemplary data set for the distinction between a visuomotor task and a resting condition. In addition it is shown for these data that the degree of sparseness and of localization can be evaluated in a strict way, provided that the data are sufficiently well described by the pairwise cross-correlations.
Image Registration Algorithms for Applications in Oncology
Authors: Passera Katia Marina , Tommaso Mainardi Luca
Published: May 2011

Image registration is the process of determining the correspondence of features between images collected at different times or using different imaging modalities. A wide range of registration algorithms was proposed in literature for solving this task. In this chapter the focus will be on oncology applications, where registration is the prior step of: i) subtraction imaging (to emphasize hyper (or hypo) enhanced structures), ii) fusion imaging (to integrate anatomical and functional information about lesions) and iii) serial imaging comparison (to monitor the progression/regression of a disease). These applications are of great relevance in tumors diagnosis, staging and treatment planning. The goal of this chapter is to provide an overview of registration algorithms considering these different applications in oncology. We discuss the advantages/disadvantages of each algorithm, the results gained and the possible future developments to comply with new requirements.
Diffusion Tensor Imaging and Fiber Tractography
Authors: Tripoliti Evanthia E. , Fotiadis Dimitrios I. , Veliou Konstantia
Published: May 2011

Diffusion Tensor Imaging (DTI) is a magnetic resonance imaging (MRI) modality which can significantly improve our understanding of the brain structures and neural connectivity. DTI measures are thought to be representative of brain tissue microstructure and are particularly useful for examining organized brain regions, such as white matter tract areas. DTI measures the water diffusion tensor using diffusion weighted pulse sequences which are sensitive to microscopic random water motion. The resulting diffusion weighted images (DWI) display and allow quantification of how water diffuses along axes or diffusion encoding directions. This can help to measure and quantify the tissue’s orientation and structure, making it an ideal tool for examining cerebral white matter and neural fiber tracts. In this chapter the authors discuss the theoretical aspects of DTI, the information that can be extracted from DTI data, and the use of the extracted information for the reconstruction of fiber tracts and the diagnosis of a disease. In addition, a review of known fiber tracking algorithms is presented.
Virtual Spaces for Teaching and Learning
Authors: Albion Peter R.
Published: May 2011

Interaction is fundamental to the learning process and game-like 3D online spaces present opportunities for enhancing learning through supporting a richer variety of interaction between learners and content, instructor and peers. Provision of a “low threshold application” for development of learning experiences in such spaces will extend the opportunities for more teachers to arrange learning experiences in virtual spaces. A heuristic that maps the possible variety of learning experiences in virtual spaces is one option for supporting teachers in the design of such experiences.
Modeling Classroom Behaviors in Software Agents
Authors: Gibson David
Published: May 2011

In order for a digital simulation to provide an artificial teaching environment there needs to be a computational model of the act of teaching interacting with software agents. The COVE model integrates Cognitive science models, the OCEAN model of psychology and OCC model of emotions, Visual-Auditory- Kinesthetic perception and the Environment (social and physical expectations) for learning. A context for the COVE agent model is provided by the How People Learn (HPL) theory of learning and Behaviorist-Cognitivist-Constructivist (BCC) instructional framework. This chapter presents design considerations for computationally modeling COVE to enable agents to possess the psychological, physical, cognitive, and social aspects of learning that enable the representation of behaviors of students in learning environments and to allow simulation of HPL-BCC theories of instruction and learning.
A Simulation for Improving Teachers' Motivational Skills
Authors: Cheong Donguk , Kim Bokyeong
Published: May 2011

A computer simulation for improving teaching is expected to remove the potential negative effects on real students while creating an environment that combines academic theories in an abstracted world of the classroom. simClass II is a teaching simulation which was designed to allow pre-service and in-service teachers to develop and exercise their motivational skills as they work within a Web-based, simulated classroom environment. This chapter aims to provide background knowledge and the basic logic for developing a simulation to help teachers enhance their skills in motivating students, with simClass II serving as a concrete example. In addition, three phases—knowledge acquisition, exercise, and debriefing— are proposed for cyclical practice of these skills.
An Attack Graph Based Approach for Threat Identification of an Enterprise Network
Authors: Bhattacharya Somak , Malhotra Samresh , Ghosh S. K.
Published: May 2011

As networks continue to grow in size and complexity, automatic assessment of the security vulnerability becomes increasingly important. The typical means by which an attacker breaks into a network is through a series of exploits, where each exploit in the series satisfies the pre-condition for subsequent exploits and makes a causal relationship among them. Such a series of exploits constitutes an attack path where the set of all possible attack paths form an attack graph. Attack graphs reveal the threat by enumerating all possible sequences of exploits that can be followed to compromise a given critical resource. The contribution of this chapter is to identify the most probable attack path based on the attack surface measures of the individual hosts for a given network and also identify the minimum possible network securing options for a given attack graph in an automated fashion. The identified network securing options are exhaustive and the proposed approach aims at detecting cycles in forward reachable attack graphs. As a whole, the chapter deals with identification of probable attack path and risk mitigation which may facilitate in improving the overall security of an enterprise network.
A Repeatable Collaboration Process for Incident Response Planning
Authors: Davis Alanah , de Vreede Gert-Jan , Pietron Leah R.
Published: May 2011

This chapter presents a repeatable collaboration process as an approach for developing a comprehensive Incident Response Plan for an organization or team. Despite the process of incident response planning being an essential ingredient in security planning procedures in organizations, extensive literature reviews have not yielded any collaborative processes for such a crucial activity. As such, this chapter will discuss the background of incident response planning as well as Collaboration Engineering, which is an approach to design repeatable collaborative work practices. We then present a collaboration process for incident response planning that was designed using Collaboration Engineering principles, followed by a discussion of the application process in three cases. The presented process is applicable across organizations in various sectors and domains, and consist of codified “best facilitation practices” that can be easily transferred to and adopted by security managers. The chapter describes the process in detail and highlights research results obtained during initial applications of the process.
Introduction to the Study
Authors: Schoechle Timothy
Published: May 2011

This book is a study of the process of standardization—the process of establishing the technical standards that define nearly every artifact of the modern world. In the field of Information and Communication Technology (ICT)1 such standards are documents that specify everything from the prongs on plugs and cables to the software protocols that make the Internet work. Technical standards and standardization play a vital role in trade and commerce, and increasingly in economic and cultural globalization. The aim of this study was to setup a research project to explore the discourse around standardization and to analyze it to provide a better understanding of the underlying issues.
An Ontology-Based e-Learning Scenario
Authors: Guo WenYing
Published: May 2011

Selecting appropriate learning services for a learner from a large number of heterogeneous knowledge sources is a complex and challenging task. This chapter illustrates and discusses how Semantic Web technologies can be applied to e-learning system to help learner in selecting appropriate learning course or retrieving relevant information. It firstly presents the main features of e-learning scenario and the ontology on which it is based; then illustrates the scenario ontology with the training domain and the application domain. Finally, it presents Semantic Querying and Semantic Mapping approach.
Refining the Results of Automatic e-Textbook Construction by Clustering
Authors: Chen Jing , Li Qing , Feng Ling
Published: May 2011

The abundance of knowledge-rich information on the World Wide Web makes compiling an online etextbook both possible and necessary. In our previous work, we proposed an approach to automatically generate an e-textbook by mining the ranked lists of the search engine. However, the performance of the approach was degraded by Web pages that were relevant but not actually discussing the desired concept. In this article, we extend the previous work by applying a clustering approach before the mining process. The clustering approach serves as a post-processing stage to the original results retrieved by the search engine, and aims to reach an optimum state in which all Web pages assigned to a concept are discussing that exact concept.
eWorkbook
Authors: Costagliola Gennaro , Fuccella Vittorio
Published: May 2011

On-Line Testing is that sector of e-learning aimed at assessing learner’s knowledge through e-learning means. In on-line testing, due to the necessity of evaluating a big mass of learners in strict times, the means for knowledge evaluation had to evolve to satisfy the new necessities: objective tests, more rapidly assessable, started gaining more credence in the determination of learners’ results. In this chapter, the authors present an On-Line Testing system, named eWorkbook, which can be used for evaluating learner’s knowledge by creating (the tutor) and taking (the learner) on-line tests based on multiple choice question type. Its use is suitable within the academic environment in a blended learning approach, by providing tutors with an additional assessment tool, and learners with a distance self-assessment means. Among other features, eWorkbook can record and visualize, in a suitable graphical format, learner’s interactions with the system interface during the test session. This is valuable information for understanding the learner’s behaviour when taking a test. In particular, the graphical analysis of the test outcomes has helped us in the discovery of several strategies employed by the learners to perform the test. In the paper, the main characteristics of the system are presented together with a rationale behind them and an outline of the architectural design of the system.
On the Determinants of Enterprise Risk Management Implementation
Authors: Desender Kurt
Published: May 2011

Corporate governance failures and new legislation have emphasized the importance of enterprise risk management (ERM) in preventing fraudulent reporting. Despite the increased attention to ERM, little research has been done to explain why some organizations embrace ERM while others do not. The objective of this paper is to explore how the board composition is related to the degree of enterprise risk management implementation. Our main results reveal that the position of the CEO in the board has an important influence on the level of ERM. Furthermore, we find that board independence by itself is not sufficient to induce higher levels of ERM. Board independence is only significantly related to ERM when there is a separation of CEO and chairman. Firms with an independent board and a separation of CEO and chairman show the highest level of ERM. One possible explanation for our results is that CEOs do not favour ERM implementation and are able to withstand pressure from the board when they are occupying the seat of chairman.
The Business Value of IT
Authors: Silvius A.J. Gilbert
Published: May 2011

The relation between IT and value is a complex and often disputed one. Researchers and practitioners have created numerous models and valuation methods to capture this value, yet the advanced methods they have developed are hardly used. While these sophisticated instruments are based on scientific methods and empirical evidence, managers reject them, preferring to use methods they intuitively understand. What is missing that causes this mismatch? This chapter aims to add to the understanding of valuation methods by providing a comprehensive selection model for selecting the valuation method that fits the characteristics of the investment. The authors provide a categorized overview of valuation method and identify the qualities of and issues with each method or approach. They analyze how these methods can be combined in an investment selection process and identify the characteristics of an investment that determine the applicability of a given method. They conclude the paper by combining these characteristics in a decision tree shaped selection model to select the appropriate valuation method for any given set of characteristics.
The Relationship between Business Strategy, IT Strategy and Alignment Capability
Authors: Silvius A.J. Gilbert
Published: May 2011

A key factor for in company’s success in a dynamic environment is effective and efficient information technology (IT) supporting business strategies and processes. Research has shown that organizations that successfully align their business strategy and their IT strategy outperform their non-aligned peers. This chapter explores the relationship between business strategy, IT strategy, and alignment capability. The author found no conclusive relationship between business strategy and IT strategy. Each business strategy can be supported by all IT strategies, but certain combinations provide a better fit than others. He also found no conclusive relationship between business strategy and alignment capability either. However the author found a clear relationship between IT strategy and alignment capability. The chapter explores this relationship further in a dual case study of two organizations having distinctly different IT strategies. One organization sees IT as an enabler for the business processes with mainly an internal impact, whereas the other organization IT sees as a driver for business innovation that can create competitive advantage in the marketplace. Based upon an assessment of their alignment capabilities, the author found that the company with the innovative IT strategy scored a distinctly higher alignment capability than the company with the essential IT strategy. Although this conclusion may not be surprising, it provides further evidence for the statement that a more progressive IT strategy pairs with a better alignment of business and IT.
Ambivalent Interplay
Authors: Kim Heejoo
Published: May 2011

The human vision, the most ubiquitous receptor of the human senses, has been the prevailing sensory organ for a noticeable manifestation of visual arts. Nevertheless, in the aspect of new technology art, the embodied experience through senses dismantled and amalgamated in hybrid aspects. Explicitly, new media artists perceive that interactive technology is evolving rapidly in such a short period of time. Rather than engaging in technology more interactively, however, it seems they are scrutinizing the subsequent progression of the phenomenon in interactive art. Artistic experiments have predominantly been transferred through the human sensorium in interlaced approaches: touch, sight, smell and hearing have synesthetic qualities in their interactive connections in between works and viewers. Recently digital art performs in multi sensory forms of knowing and communicating. There are investigating perceptual and emotional mechanisms of involuntary synesthetic experiences. This artistic phenomenon is not only historically intriguing, but may also contribute to present synesthesia research. The functions and interrelations of the synesthetic approaches in new media arts and neurological researches are discussed separately.
A Graphics Tablet as a Fine Art Tool
Authors: Quinn Nicola , Aboulafia Annette
Published: May 2011

People have used tools for artistic expression for millennia. Relatively recent is the use of digital technology to afford the creation of art. However, many draw into question digital technologies conduciveness to creativity during the artistic process. Recent developments of digital technology for artists have lead to the creation of a graphics tablet from Wacom Technologies. It is claimed that the graphics tablet is more favorable to creativity than other existing digital technologies. This chapter addresses this issue through a qualitative study of five artists using the Wacom graphics tablet, in particular the artist’s own experience using the graphics tablet is explored. The outcome of this study indicates that the graphics tablet is a useful tool. However, there are still several improvements required to advance the graphics tablet to a stage suitable for fine artists.
Memory Association Machine
Authors: Bogart Benjamin David Robert
Published: May 2011

“Memory Association Machine” (also known as “Self-Other Organizing Structure #1”) is the first prototype in a series of site-specific responsive installations inspired by cognitive processes. The artist provides a mechanism that allows the structure of the artwork to change in response to continuous stimulus from its context. Context is defined as those parameters of the environment that are perceivable by the system and make its place in space and time unique. “Memory Association Machine” relates itself to its context using three primary processes: perception, the integration of sensor data into a field of experience, and the free-association through that field. “Memory Association Machine” perceives through a video camera, integrates using a Kohonen Self-Organizing Map, and free-associates through an implementation of Liane M. Gabora’s model of memory and creativity.
The Challenge of Enculturation on Art
Authors: Grace Lindsay
Published: May 2011

Enculturation is the act of passing cultural ideologies from one person to the other. It is what breeds innovation instead of new creation. It is the disease of derivation, instead of the birth of creativity. This chapter assumes the practical perspective of critical anthropological distance to understand the culture of art. Such critical evaluation should illuminate the distinct characteristics that encourage patterns. In the tradition of anthropological and sociological study of existing culture, this chapter seeks to illuminate the distinguishing characteristics of contemporary art production and offer perspective on the critical creative process. It takes new media art as its case study because it serves as a cross-cultural intersection of scientific invention and artistic innovation.
A Telehealth Technology Model for Information Science in Rural Settings
Authors: Miller Thomas W. , Morgan Robert , Wood Jennifer
Published: May 2011

Examined is the application of telehealth technology in a rural community clinical and educational system. Telehealth is viewed as the removal of time and distance barriers in the provision of healthcare and patient education to underserved populations (Nickelson, 1996). Presented is a clinical consultation model of healthcare for underserved populations and where professional consultation with a team of professionals may benefit rural educational systems and their students. Offered are specific applications within a broad spectrum of services utilizing telehealth technology. Finally, shifts in administrative paradigms, clinical models, and educational information technology for healthcare services through telehealth technology are explored.
Psychological Guidelines in Cardiac Rehabilitation and Prevention
Authors: Sommaruga Marinella
Published: May 2011

A large number of evidence-based guidelines are drawn up all over the world to improve standards of healthcare and to reduce inequalities in access to effective treatment. Evidence-based practice in psychology is the integration of the best available research with clinical expertise in the context of patient characteristics, culture, and preferences. Despite widespread circulation and publicity of these guidelines, often they are not implemented effectively. Consequently, there is a substantial difference between evidence and practice, with best health outcomes not being achieved. The aim of this chapter is to describe and discuss the methodological process, development, and implementation of the Italian Guidelines for psychology activities in Cardiac Rehabilitation and Prevention, published in 2003 by the Working Group of Psychology of the Italian Society of Cardiac Rehabilitation and updated in the 2005 National Cardiac Rehabilitation guidelines issued by the Italian Programme for Guidelines.
Developing and Managing an Effective Virtual Campus
Authors: Botturi Luca , Cantoni Lorenzo , Lepori Benedetto , Tardini Stefano
Published: May 2011

This chapter presents a successful Swiss experience in developing and effectively managing virtual campus projects: eLab, the eLearning Laboratory of the University of Lugano and the University of Applied Sciences of Italian Switzerland. eLab activities are presented at two distinct moments in time. We first describe the context of e-learning in Swiss higher education institutions, focusing in particular on the Swiss Virtual Campus programme. During that programme, eLab emerged as one of the best performing e-learning support centres in Switzerland, thanks to three main elements: the establishment of a clear prototype-based design and development model, the definition of quality control procedures, and the implementation of a consistent and institution-wide online learning environment. After the end of the programme, eLab had to switch from a project-oriented laboratory towards a service unit. The general strategy that drove this change and the concrete tools and practices that made it possible are presented in this chapter.
QoS-based Job Scheduling and Resource Management Strategies for Grid Computing
Authors: Huang Kuo-Chan , Shih Po-Chi , Chung Yeh-Ching
Published: May 2011

This chapter elaborates the quality of service (QoS) aspect of load sharing activities in a computational grid environment. Load sharing is achieved through appropriate job scheduling and resource allocation mechanisms. A computational grid usually consists of several geographically distant sites each with different amount of computing resources. Different types of grids might have different QoS requirements. In most academic or experimental grids the computing sites volunteer to join the grids and can freely decide to quit the grids at any time when they feel joining the grids bring them no benefits. Therefore, maintaining an appropriate QoS level becomes an important incentive to attract computing sites to join a grid and stay in it. This chapter explores the QoS issues in such type of academic and experimental grids. This chapter first defines QoS based performance metrics for evaluating job scheduling and resource allocation strategies. According to the QoS performance metrics appropriate grid-level load sharing strategies are developed. The developed strategies address both user-level and site-level QoS concerns. A series of simulation experiments were performed to evaluate the proposed strategies based on real and synthetic workloads.
Achieving QoS in Highly Unreliable Grid Environments
Authors: Litke Antonios
Published: May 2011

Grids can form the basis for pervasive computing due to their ability of being open, scalable, and flexible to various changes (from topology changes to unpredicted failures of nodes). However, such environments are prone to failures due to their nature and need a certain level of reliability in order to provide viable and commercially exploitable solutions. This is causing nowadays a significant research activity which is focused on the topic of achieving certain levels of Quality of Service (QoS) in highly unreliable environments (such as mobile and ad hoc Grids). This study will focus on the state-of-the-art analysis of the QoS aspects in Grids and how this is achieved in terms of technological means. A small survey and related work will be also presented. A more detailed analysis on the features of unreliable environments such as mobile Grids will be described. An innovative and efficient mechanism will be described, which is especially designed for such environments, in order to enhance them with the QoS attributes of reliability (fault tolerance through replication of tasks) and service differentiation to the Grid users through a simple task prioritization scheme. The results that this recent research work is presenting are promising for the future advancement of Grid commercialization in such environments.
A Grid Aware Large Scale Agent-based Simulation System
Authors: Chen Dan
Published: May 2011

The emergence of Grid technologies provide exciting new opportunities for large scale simulation over Internet, enabling collaboration and the use of distributed computing resources, while also facilitating access to geographically distributed data sets. This chapter presents HLA_Grid_RePast, a middleware platform for executing large scale collaborating RePast agent-based models on the Grid. The chapter also provides performance results and analysis on Quality of Service from a deployment of the system between UK and Singapore.
The Key Requirements for deploying Knowledge Management Services in a Semantic Grid Environment
Authors: Mohamed Mirghani , Stankosky Michael , Ribière Vincent
Published: May 2011

The purpose of this article is to investigate the requirements of knowledge management (KM) services deployment in a Semantic Grid environment. A wide range of literature on Grid Computing, Semantic Web, and KM have been reviewed, related, and interpreted. The benefits of the Semantic Web and the Grid Computing convergence have been enumerated and related to KM principles in a complete service model. Although the Grid Computing contributed the shared resources, most of the KM tool obstacles within the grid are to be resolved at the semantic and cultural levels more than at the physical or logical grid levels. The early results from academia show a synergy and the potentiality of leveraging knowledge at a wider scale. However, the plethora of information produced in this environment will result in a serious information overload, unless proper standardization, automated relations, syndication, and validation techniques are developed.
Types of Resources and their Discover in HealthGrids
Authors: Naseer Aisha , Stergiolas Lampros
Published: May 2011

Adoption of cutting edge technologies in order to facilitate various healthcare operations and tasks is significant. There is a need for health information systems to be fully integrated with each other and provide interoperability across various organizational domains for ubiquitous access and sharing. The emerging technology of HealthGrids holds the promise to successfully integrate health information systems and various healthcare entities onto a common, globally shared and easily accessible platform. This chapter presents a systematic taxonomy of different types of HealthGrid resources, where the specialized resources can be categorised into three major types; namely, Data or Information or Files (DIF); Applications & Peripherals (AP); and Services. Resource discovery in HealthGrids is an emerging challenge comprising many technical issues encapsulating performance, consistency, compatibility, heterogeneity, integrity, aggregation and security of life-critical data. To address these challenges, a systematic search strategy could be devised and adopted, as the discovered resource should be valid, refined and relevant to the query. Standards could be implemented on domain-specific metadata. This chapter proposes potential solutions for the discovery of different types of HealthGrid resources and reflects on discovering and integrating data resources.
Data Provenance in Scientific Workflows
Authors: Belhajjame Khalid , Missier Paolo , Goble Carole
Published: May 2011

Data provenance is key to understanding and interpreting the results of scientific experiments. This chapter introduces and characterises data provenance in scientific workflows using illustrative examples taken from real-world workflows. The characterisation takes the form of a taxonomy that is used for comparing and analysing provenance capabilities supplied by existing scientific workflow systems.
Grid Analysis of Radiological Data
Authors: Germain-Renaud Cecile , Breton Vincent , Clarysse Patrick , Delhay Bertrand , Gaudeau Yann , Glatard Tristan , Jeannot Emmanuel , Legre Yannick
Published: May 2011

Grid technologies and infrastructures can contribute to harnessing the full power of computer-aided image analysis into clinical research and practice. Given the volume of data, the sensitivity of medical information, and the joint complexity of medical datasets and computations expected in clinical practice, the challenge is to fill the gap between the grid middleware and the requirements of clinical applications. This chapter reports on the goals, achievements and lessons learned from the AGIR (Grid Analysis of Radiological Data) project. AGIR addresses this challenge through a combined approach. On one hand, leveraging the grid middleware through core grid medical services (data management, responsiveness, compression, and workflows) targets the requirements of medical data processing applications. On the other hand, grid-enabling a panel of applications ranging from algorithmic research to clinical use cases both exploits and drives the development of the services.
Porting Applications to Grids and Clouds
Authors: Gentzsch Wolfgang
Published: May 2011

A Grid enables remote, secure access to a set of distributed, networked computing and data resources. Clouds are a natural next step of Grids towards the provisioning of computing as a service. To “Gridenable” applications, users have to cope with: complexity of grid architectures; different compute and data nodes; wide spectrum of grid middleware tools and services; the e-science application architectures, algorithms and programs. Therefore, the aim of this chapter is to guide users through the important stages of implementing applications on Grid and Cloud infrastructures, together with a discussion of important challenges and their potential solutions. As a case study, we present the DEISA Distributed European Infrastructure for Supercomputing Applications and describe the DEISA Extreme Computing Initiative DECI for porting and running scientific grand challenge applications on the DEISA Grid. This chapter concludes with an outlook on Compute Clouds, and the top ten rules of building a sustainable Grid.
Large-Scale Co-Phylogenetic Analysis on the Grid
Authors: Stockinger Heinz , Auch Alexander , Goeker Markus , Meier-Kolthoff Jan , Stamatakis Alexandros
Published: May 2011

Phylogenetic data analysis represents an extremely compute-intensive area of Bioinformatics and thus requires high-performance technologies. Another compute- and memory-intensive problem is that of host-parasite co-phylogenetic analysis: given two phylogenetic trees, one for the hosts (e.g., mammals) and one for their respective parasites (e.g., lice) the question arises whether host and parasite trees are more similar to each other than expected by chance alone. CopyCat is an easy-to-use tool that allows biologists to conduct such co-phylogenetic studies within an elaborate statistical framework based on the highly optimized sequential and parallel AxParafit program. We have developed enhanced versions of these tools that efficiently exploit a Grid environment and therefore facilitate large-scale data analyses. Furthermore, we developed a freely accessible client tool that provides co-phylogenetic analysis capabilities. Since the computational bulk of the problem is embarrassingly parallel, it fits well to a computational Grid and reduces the response time of large scale analyses.
Machine Learning Enhancing Adaptivity of Multimodal Mobile Systems
Authors: Esposito Floriana , Basile Teresa M.A. , Di Mauro Nicola , Ferilli Stefano
Published: May 2011

One of the most important features of a mobile device concerns its flexibility and capability to adapt the functionality it provides to the users. However, the main problems of the systems present in literature are their incapability to identify user needs and, more importantly, the insufficient mappings of those needs to available resources/services. In this paper, we present a two-phase construction of the user model: firstly, an initial static user model is built for the user connecting to the system the first time. Then, the model is revised/adjusted by considering the information collected in the logs of the user interaction with the device/context in order to make the model more adequate to the evolving user’s interests/ preferences/behaviour. The initial model is built by exploiting the stereotype concept, its adjustment is performed exploiting machine learning techniques and particularly, sequence mining and pattern discovery strategies.
Broadband Development Challenges and Measures
Authors: Trkman Peter , Turk Tomaž
Published: May 2011

The chapter analyses the use of broadband in EU countries in an attempt to find the main reasons, which explain the differences among countries. With the use of factor analysis the underlying factors were identified as: 1. enablers and means; 2. the use of services; and 3. the ICT sector’s development. Cluster analysis was used to identify similar countries. Based on these findings, a two-dimensional framework that enables the classification of policy actions depending on the influencing factor and type of influence was developed. Finally, a novel conceptualization of the field of broadband and e-commerce/e-government is proposed.
Competence in Transforming the Norwegian Welfare Sector
Authors: Rolland Knut H. , Dingsøyr Torgeir
Published: May 2011

E-government initiatives need to take the competence involved in producing high-quality services for citizens into account. We draw on insights from a pilot project in a Norwegian municipal aiming at radically restructuring the Norwegian welfare sector and show how the competence to provide highquality services rely on the collective achievement of individuals’ knowing-in-practice when dealing with particular cases and situations. Furthermore, we show how competence in terms of ‘processes of knowing’ is intrinsically related to organization structure and existing information systems. Transforming the Norwegian Welfare Sector then, involves transforming a sociotechnical network of heterogeneous elements, where existing processes of knowing plays an important role. Based on this, we discuss implications for implementing e-government in local municipals, and in particular e-government initiatives that aim at introducing all-embracing integrated IT solutions across organizational and geographical borders. The chapter concludes by sketching implications for future research on e-government.
Nous
Authors: Bablekou Zoe
Published: May 2011

The path to the study of cognition has to take into account working memory, as it is a key process of thinking operations in the human cognitive system. Naturally, this also holds for cognitive operations in the Web. The chapter introduces readers to current trends regarding models of working memory. The major models proposed in the literature are discussed here: Baddeley and Hitch’s multi-component model, Daneman and Carpenter’s account, Cowan’s embedded-process model, Kane and Engle’s executive attention model and long-term working memory model by Ericsson and Kintsch. The chapter focuses on the Baddeley and Hitch model, and the author argues that this specific model offers a more theoretically sound account of working memory operations. Unresolved issues and inefficiencies are also discussed and research directions are proposed.
The Effect of Communication Styles on Computer-Supported Collaborative Learning
Authors: Cho Hichang , Gay Geri
Published: May 2011

This chapter investigates the relationships between communication styles, social networks, and learning in a Computer-Supported Collaborative Learning (CSCL) community. Using Social Network Analysis (SNA) and longitudinal survey data, the authors analyzed how 31 distributed learners developed collaborative learning social networks, when they had work together on the design of aerospace systems using online collaboration tools. The results showed that both learner’s personality characteristics (communication styles) and structural factors (a pre-existing friendship network) significantly affected the way the learners developed collaborative learning social networks. More specifically, learners who possessed high Willingness to Communicate (WTC) or occupied initially peripheral network positions were more likely to explore new network linkages in a distributed learning environment. The authors propose that the addition of personality theory (operationalized here as communication styles) to structural analysis (SNA) contributes to an enhanced picture of how distributed learners build their social and intellectual capital in the context of CSCL.
Incorporating Graph Features for Predicting Protein-Protein Interactions
Authors: Paradesi Martin S.R. , Caragea Doina , Hsu William H.
Published: May 2011

This chapter presents applications of machine learning to predicting protein-protein interactions (PPI) in Saccharomyces cerevisiae. Several supervised inductive learning methods have been developed that treat this task as a classification problem over candidate links in a PPI network – a graph whose nodes represent proteins and whose arcs represent interactions. Most such methods use feature extraction from protein sequences (e.g., amino acid composition) or associated with protein sequences directly (e.g., GO annotation). Others use relational and structural features extracted from the PPI network, along with the features related to the protein sequence. Topological features of nodes and node pairs can be extracted directly from the underlying graph. This chapter presents two approaches from the literature (Qi et al., 2006; Licamele & Getoor, 2006) that construct features on the basis of background knowledge, an approach that extracts purely topological graph features (Paradesi et al., 2007), and one that combines knowledge-based and topological features (Paradesi, 2008). Specific graph features that help in predicting protein interactions are reviewed. This study uses two previously published datasets (Chen & Liu, 2005; Qi et al., 2006) and a third dataset (Paradesi, 2008) that was created by combining and augmenting three existing PPI databases. The chapter includes a comparative study of the impact of each type of feature (topological, protein sequence-based, etc.) on the sensitivity and specificity of classifiers trained using specific types of features. The results indicate gains in the area under the sensitivity-specificity curve for certain algorithms when topological graph features are combined with other biological features such as protein sequence-based features.