bluuebunny/crossref_metadata_2025 huggingface dataset:
Non-Manual Control Devices
Authors: Scherer Reinhold , Rao Rajesh
Published: May 2011

Brain-computer interface (BCI) technology augments the human capability to interact with the environment by directly linking the brain to artificial devices. The first generation of BCIs provided simple 1D control in order to select targets on a screen or trigger pre-defined motion sequences of paralyzed limbs by means of functional electrical stimulation. BCIs today can provide users on-demand access to assistive robotic devices, Virtual Reality environments, and standard software applications such as Internet browsers. Here, we introduce readers to BCIs and review basic principles and methodologies underlying their operation. We illustrate the capabilities and limitations of modern BCI systems by discussing two practical examples: BCI-based control of a humanoid robot for physical manipulation and transport of objects in an indoor environment, and BCI-based interaction with the popular global navigation program Google Earth.
The Personal Research Portal
Authors: Peña-López Ismael
Published: May 2011

The author of this chapter proposes the concept of the Personal Research Portal (PRP) – a mesh of social software applications to manage knowledge acquisition and diffusion – as a means to create a digital identity for the researcher, an online public notebook and personal repository, and a virtual network of colleagues working in the same field. Complementary to formal publishing or taking part in events, and based on the concept of the e-portfolio, the PRP is a knowledge management system that enhances reading, storing and creating at both the private and public levels. Relying heavily on Web 2.0 applications easy to use, freely available – the PRP automatically implies a public exposure and a digital presence that enables conversations and network weaving without time and space boundaries.
Transliteracy as a Unifying Perspective
Authors: Thomas Sue , Joseph Chris , Laccetti Jess , Mason Bruce , Perril Simon , Pullinger Kate
Published: May 2011

Transliteracy might provide a unifying perspective on what it means to be literate in the 21st Century. It is not a new behaviour but has been identified as a working concept since the internet generated new ways of thinking about human communication. This chapter defines transliteracy as “the ability to read, write and interact across a range of platforms, tools and media from signing and orality through handwriting, print, TV, radio and film, to digital social networks” and opens the debate with examples from history, orality, philosophy, literature, ethnography and education. The authors invite responses, expansion, and development. See also http://www.transliteracy.com
Information Systems Security
Authors: Jahankhani Hamid , Fernando Shantha , Nkhoma Mathews Z.
Published: May 2011

In today’s business environment it is difficult to obtain senior management approval for the expenditure of valuable resources to “guarantee” that a potentially disastrous event will not occur that could affect the ultimate survivability of the organization. The total information network flexibility achieved depends to a great extent on how network security is implemented. However, this implementation depends on the network designers at the initial stage and the network administrators in the long term. Initial security level designed can be later changed, improved or compromised by the network administrators who look after day-to-day network and system functions. Their competencies and the motivation contribute in achieving the desired security objectives that are aligned with the business goals. Incompetent network administrator may pave the way to attacks that could take place either at once where an obvious vulnerability may exist or in several phases where it requires information gathering or scanning in order to enter into the target system. De-motivated network administrator may ignore the possible threats or find strategies to make his/ her presence vital for the existence of the network services. The latter may be an example of a competent network administrator who is not rewarded due to the lapses of the senior management, in which case backdoors or logic bombs may be deployed so that the administrator may take vengeance in case the career is terminated or someone else is given undue recognition. Two studies on real cases given in this paper highlights the influence of such network administrators. To preserve the confidentiality, the names of personnel or organizations are not revealed.
An Ontology of Information Security
Authors: Herzog Almut , Shahmehri Nahid , Duma Claudiu
Published: May 2011

The authors present a publicly available, OWL-based ontology of information security which models assets, threats, vulnerabilities and countermeasures and their relations. The ontology can be used as a general vocabulary, roadmap and extensible dictionary of the domain of information security. With its help, users can agree on a common language and definition of terms and relationships. In addition to browsing for information, the ontology is also useful for reasoning about relationships between its entities, that is, threats and countermeasures. The ontology helps answer questions like: Which countermeasures detect or prevent the violation of integrity of data? Which assets are protected by SSH? Which countermeasures thwart buffer overflow attacks? At the moment, the ontology comprises 88 threat classes, 79 asset classes, 133 countermeasure classes and 34 relations between those classes. The authors provide means for extending the ontology, and provide examples of the extendibility with the countermeasure classes “memory protection” and “source code analysis”. This chapter describes the content of the ontology as well as its usages, potential for extension, technical implementation and tools for working with it.
Complex-Valued Boltzmann Manifold
Authors: Kobayashi Masaki
Published: May 2011

Information geometry is one of the most effective tools to investigate stochastic learning models. In it, stochastic learning models are regarded as manifolds in the view of differential geometry. Amari applied it to Boltzmann Machines, which is one of the stochastic learning models. The purpose of this chapter is to apply information geometry to complex-valued Boltzmann Machines. First, we construct the complex-valued Boltzmann Machines. Next, the author describes information geometry. The author will know some important notions of information geometry, exponential families, mixture families, Kullback-Leibler divergence, connections, geodesics, Fisher metrics, potential functions and so on. Finally, they apply information geometry to complex-valued Boltzmann Machines. They will investigate the structure of complex-valued Boltzmann manifold and know the notions of the connections and Fisher metric. Moreover we will get an effective learning algorithm, what is called em algorithm, for complex-valued Boltzmann machines with hidden neurons.
Complex-Valued Neural Networks for Equalization of Communication Channels
Authors: Pandey Rajoo
Published: May 2011

The equalization of digital communication channel is an important task in high speed data transmission techniques. The multipath channels cause the transmitted symbols to spread and overlap over successive time intervals. The distortion caused by this problem is called inter-symbol interference (ISI) and is required to be removed for reliable communication of data over communication channels. In this task of ISI removal, the signals are complex-valued and processing has to be done in a complex multidimensional space. The growing interest in complex-valued neural networks has spurred the development of many new algorithms for equalization of communication channels in the recent past. This chapter illustrates the application of various types of complex-valued neural networks such as radial basis function networks (RBFN), multilayer feedforward networks and recurrent neural networks for training sequence-based as well as blind equalization of communication channels. The structures and algorithms for these equalizers are presented and performances based on simulation studies are analyzed highlighting their advantages and the important issues involved.
Face and Eye Detection
Authors: Kim Daijin , Sung Jaewon
Published: May 2011

Face detection is the most fundamental step for the research on image-based automated face analysis such as face tracking, face recognition, face authentication, facial expression recognition and facial gesture recognition. When a novel face image is given we must know where the face is located, and how large the scale is to limit our concern to the face patch in the image and normalize the scale and orientation of the face patch. Usually, the face detection results are not stable; the scale of the detected face rectangle can be larger or smaller than that of the real face in the image. Therefore, many researchers use eye detectors to obtain stable normalized face images. Because the eyes have salient patterns in the human face image, they can be located stably and used for face image normalization. The eye detection becomes more important when we want to apply model-based face image analysis approaches.
Face Tracking
Authors: Kim Daijin , Sung Jaewon
Published: May 2011

When we want to analyze the continuous change of the face in an image sequence, applying face tracking methods is a better choice than applying the face detection methods to each image frame. Usually, the face tracking methods are more efficient than the ordinary face detection methods because they can utilize the trajectory of the face in the previous image frames with an assumption that the shape, texture, or motion of the face change smoothly. There have been many approaches to face tracking. We divide the face tracking methods into several categories according to the cues that are extracted for tracking.
Cost-Sensitive Learning in Medicine
Authors: Freitas Alberto , Brazdil Pavel , Costa-Pereira Altamiro
Published: May 2011

This chapter introduces cost-sensitive learning and its importance in medicine. Health managers and clinicians often need models that try to minimize several types of costs associated with healthcare, including attribute costs (e.g. the cost of a specific diagnostic test) and misclassification costs (e.g. the cost of a false negative test). In fact, as in other professional areas, both diagnostic tests and its associated misclassification errors can have significant financial or human costs, including the use of unnecessary resource and patient safety issues. This chapter presents some concepts related to cost-sensitive learning and cost-sensitive classification and its application to medicine. Different types of costs are also present, with an emphasis on diagnostic tests and misclassification costs. In addition, an overview of research in the area of cost-sensitive learning is given, including current methodological approaches. Finally, current methods for the cost-sensitive evaluation of classifiers are discussed.
Preprocessing Perceptrons and Multivariate Decision Limits
Authors: Eklund Patrik , Kallin Westin Lena
Published: May 2011

Classification networks, consisting of preprocessing layers combined with well-known classification networks, are well suited for medical data analysis. Additionally, by adjusting network complexity to corresponding complexity of data, the parameters in the preprocessing network can, in comparison with networks of higher complexity, be more precisely understood and also effectively utilised as decision limits. Further, a multivariate approach to preprocessing is shown in many cases to increase correctness rates in classification tasks. Handling network complexity in this way thus leads to efficient parameter estimations as well as useful parameter interpretations.
Computational Mobile Grid
Authors: Vidyarthi Deo Prakash
Published: May 2011

The proliferation of the capable mobile devices has given the opportunity to utilize these devices for various purposes. The mobile devices being used as a Web portal is its short-term use as these devices have added many features and facility that does not only facilitate communication, but also adds to the huge computing power put together. The chapter proposes how a huge computational grid of these compute capable mobile devices can be formed, and the computing power from such a grid can be extracted. This kind of computational mobile grid put fourth many issues that require great attention before such a concept is fully functional.
Ubiquitous Computing for Microbial Forensics and Bioterrorism
Authors: Prasad Gaya
Published: May 2011

Microorganisms are ubiquitous in their presence. They are present in air, soil, water, and all kinds of living creatures. Varieties of microbes have been linked to diseases of humans, animals, and plants. Advances in molecular biology, electronics, nanotechnology, computer sciences, and information technology have made it possible to hybridize these to create ubiquitous devices and biosensors that would indicate presence of microbial agents in water, foods, air, hospitals, animal farms, and other environments. Analyses of microbial genomes and phylogenies have become increasingly important in the tracking and investigation of events leading to spread of microbial diseases and biocrimes. The capability of microorganisms to communicate with similar as well as different microorganisms, the ability to react to the environmental changes, and most of all, the intelligence to manage themselves without the need for supervision during deployment and operation; makes them attractive agents for use in Biosensors. Biosensors such as genetically engineered bacteria have been proven useful. It appears possible to develop biosensors that could detect the presence of biocrime/bioterror agents in diverse environments. Ubiquitous computing technology has the potential to develop integrated small devices which could detect bioterrorism agents. Similarly, pervasive computing could be a tool to monitor the microbial pollution in water, milk, and other edible commodities. Microbial forensics has become an important field for research and development due to increased threats of biocrimes. Microbial forensics requires utilization of diverse data that are acquired through standard processes in distributed locations. Technologies for data production are evolving rapidly, especially with respect to instrumentation and techniques that produce high-resolution data about the molecular constituents of living cells (DNA, mRNA, proteins, and metabolites) that are used as microbial signatures/fingerprints. Both bioinformatics and computational biology have grown over the last 20 years, and diverse database systems and analytical tools have been developed and deployed. Some public domain resources, such as GenBank, have become very important resources of research on a global scale. Effective responses to natural, accidental, or intentional outbreaks of infectious diseases in humans, livestock, and agricultural crops, will require that the information be easily accessed in realtime or near real-time. Flexible, decentralized, modular information system architectures, able to adapt to evolving requirements and available on the Internet, are needed.
Strategizing in the Digital World
Authors: Lee Yvonne , Kornberger Martin
Published: May 2011

In the rapidly changing digital marketplace, firms increasingly try to look for new ways to acquire, engage, and retain their consumers. In doing so, they hope to enhance their ability to monitor and predict consumer expression and affiliation while relying on consumers to spread the word about a product. The current state of the industry and enabling technologies that shape development is transitioning from an inexpensive medium for advertising, marketing, and customer support, to a common platform for transactions and business applications for information, communication, commerce, and entertainment as one large consolidated industry. More consumers are accessing the internet using multiple devices and over multiple communications networks, along with changing behavior and consumer patterns. With the evolution of digital media, Web technologies and consumer patterns changing rapidly, we see strategizing in the digital world of new media as essential. It needs to be addressed and understood holistically, including its impact on existing offline business models, branding practices, and the shape of future business models.
Business Models and Organizational Processes Changes
Authors: Halas Helena , Klobucar Tomaž
Published: May 2011

This chapter explores the influence of pervasive computing on companies and their businesses, with the main stress on business models. The role of business models for companies is presented. Introduction to pervasive computing and a survey of existing e-business models classifications are used as a base for our research. The main characteristics of today’s business models are discussed and a method for evaluating business models characteristics is proposed. We concentrate on characteristics of pervasive computing and their influence on companies’ business processes and business models. The present and future business characteristics and business models are briefly compared, and future research directions on pervasive computing and business models are presented.
Survey of Web Service Discovery Systems
Authors: Ngan Le Duy , Goh Angela
Published: May 2011

Web services form the core of e-business and hence, have experienced a rapid development in the past few years. This has led to a demand for a discovery mechanism for web services. Discovery is the most important task in the web service model because web services are useless if they cannot be discovered. A large number of web service discovery systems have been developed. Universal Description, Discovery and Integration (UDDI) is a typical mechanism that stores indexes to web services but it does not support semantics. Semantic web service discovery systems that have been developed include systems that support matching web services using the same ontology, systems that support matching web services using different ontologies, and systems that support limitations of UDDI. This paper presents a survey of web service discovery systems, focusing on systems that support semantics. The paper also elaborates on open issues relating to such discovery systems.
Learning Agents for Collaborative Driving
Authors: Desjardins Charles , Laumônier Julien , Chaib-draa Brahim
Published: May 2011

This chapter studies the use of agent technology in the domain of vehicle control. More specifically, it illustrates how agents can address the problem of collaborative driving. First, the authors briefly survey the related work in the field of intelligent vehicle control and inter-vehicle cooperation that is part of Intelligent Transportation Systems (ITS) research. Next, they detail how these technologies are especially adapted to the integration, for decision-making, of autonomous agents. In particular, they describe an agent-based cooperative architecture that aims at controlling and coordinating vehicles. In this context, the authors show how reinforcement learning can be used for the design of collaborative driving agents, and they explain why this learning approach is well-suited for the resolution of this problem.
The Merit of Agents in Freight Transport
Authors: Máhr Tamás , Srour F. Jordan , de Weerdt Mathijs , Zuidwijk Rob
Published: May 2011

While intermodal freight transport has the potential to introduce efficiency to the transport network,this transport method also suffers from uncertainty at the interface of modes. For example, trucks moving containers to and from a port terminal are often uncertain as to when exactly their container will be released from the ship, from the stack, or from customs. This leads to much difficulty and inefficiency in planning a profitable routing for multiple containers in one day. In this chapter, the authors examine agent-based solutions as a mechanism to handle job arrival uncertainty in the context of a drayage case at the Port of Rotterdam. They compare their agent-based solution approach to a wellknown on-line optimization approach and study the comparative performance of both systems across four scenarios of varying job arrival uncertainty. The chapter concludes that when less than 50% of all jobs are known at the start of the day then an agent-based approach performs competitively with an on-line optimization approach.
Integrated Business and Production Process Data Warehousing
Authors: Draheim Dirk , Mangisengi Oscar
Published: May 2011

Nowadays tracking data from activity checkpoints of unit transactions within an organization’s business processes becomes an important data resource for business analysts and decision-makers to provide essential strategic and tactical business information. In the context of business process-oriented solutions, business-activity monitoring (BAM) architecture has been predicted as a major issue in the near future of the business-intelligence area. On the other hand, there is a huge potential for optimization of processes in today’s industrial manufacturing. Important targets of improvement are production efficiency and product quality. Optimization is a complex task. A plethora of data that stems from numerical control and monitoring systems must be accessed, correlations in the information must be recognized, and rules that lead to improvement must be identified. In this chapter we envision the vertical integration of technical processes and control data with business processes and enterprise resource data. As concrete steps, we derive an activity warehouse model based on BAM requirements. We analyze different perspectives based on the requirements, such as business process management, key performance indication, process and state based-workflow management, and macro- and micro-level data. As a concrete outcome we define a meta-model for business processes with respect to monitoring. The implementation shows that data stored in an activity warehouse is able to efficiently monitor business processes in real-time and provides a better real-time visibility of business processes.
Selecting and Allocating Cubes in Multi-Node OLAP Systems
Authors: Loureiro Jorge , Belo Orlando
Published: May 2011

OLAP queries are characterized by short answering times. Materialized cube views, a pre-aggregation and storage of group-by values, are one of the possible answers to that condition. However, if all possible views were computed and stored, the amount of necessary materializing time and storage space would be huge. Selecting the most beneficial set, based on the profile of the queries and observing some constraints as materializing space and maintenance time, a problem denoted as cube views selection problem, is the condition for an effective OLAP system, with a variety of solutions for centralized approaches. When a distributed OLAP architecture is considered, the problem gets bigger, as we must deal with another dimension—space. Besides the problem of the selection of multidimensional structures, there’s now a node allocation one; both are a condition for performance. This chapter focuses on distributed OLAP systems, recently introduced, proposing evolutionary algorithms for the selection and allocation of the distributed OLAP Cube, using a distributed linear cost model. This model uses an extended aggregation lattice as framework to capture the distributed semantics, and introduces processing nodes’ power and real communication costs parameters, allowing the estimation of query and maintenance costs in time units. Moreover, as we have an OLAP environment, whit several nodes, we will have parallel processing and then, the evaluation of the fitness of evolutionary solutions is based on cost estimation algorithms that simulate the execution of parallel tasks, using time units as cost metric.
Swarm Quant' Intelligence for Optimizing Multi-Node OLAP Systems
Authors: Loureiro Jorge , Belo Orlando
Published: May 2011

Globalization and market deregulation has increased business competition, which imposed OLAP data and technologies as one of the great enterprise’s assets. Its growing use and size stressed underlying servers and forced new solutions. The distribution of multidimensional data through a number of servers allows the increasing of storage and processing power without an exponential increase of financial costs. However, this solution adds another dimension to the problem: space. Even in centralized OLAP, cube selection efficiency is complex, but now, we must also know where to materialize subcubes. We have to select and also allocate the most beneficial subcubes, attending an expected (changing) user profile and constraints. We now have to deal with materializing space, processing power distribution, and communication costs. This chapter proposes new distributed cube selection algorithms based on discrete particle swarm optimizers; algorithms that solve the distributed OLAP selection problem considering a query profile under space constraints, using discrete particle swarm optimization in its normal(Di-PSO), cooperative (Di-CPSO), multi-phase (Di-MPSO), and applying hybrid genetic operators.
Multidimensional Anlaysis of XML Document Contents with OLAP Dimensions
Authors: Ravat Franck , Teste Olivier , Tournier Ronan
Published: May 2011

With the emergence of Semi-structured data format (such as XML), the storage of documents in centralised facilities appeared as a natural adaptation of data warehousing technology. Nowadays, OLAP (On-Line Analytical Processing) systems face growing non-numeric data. This chapter presents a framework for the multidimensional analysis of textual data in an OLAP sense. Document structure, metadata, and contents are converted into subjects of analysis (facts) and analysis axes (dimensions) within an adapted conceptual multidimensional schema. This schema represents the concepts that a decision maker will be able to manipulate in order to express his analyses. This allows greater multidimensional analysis possibilities as a user may gain insight within a collection of documents.
Using Active Rules to Maintain Data Consistency in Data Warehouse Systems
Authors: Huang Shi-Ming , Tait John , Su Chun-Hao , Tsai Chih-Fong
Published: May 2011

Data warehousing is a popular technology, which aims at improving decision-making ability. As the result of an increasingly competitive environment, many companies are adopting a “bottom-up” approach to construct a data warehouse, since it is more likely to be on time and within budget. However, multiple independent data marts/cubes can easily cause problematic data inconsistency for anomalous update transactions, which leads to biased decision-making. This research focuses on solving the data inconsistency problem and proposing a temporal-based data consistency mechanism (TDCM) to maintain data consistency. From a relative time perspective, we use an active rule (standard ECA rule) to monitor the user query event and use a metadata approach to record related information. This both builds relationships between the different data cubes, and allows a user to define a VIT (valid interval temporal) threshold to identify the validity of interval that is a threshold to maintain data consistency. Moreover, we propose a consistency update method to update inconsistent data cubes, which can ensure all pieces of information are temporally consistent.
Training Coordination Proxy Agents Using Reinforcement Learning
Authors: Abramson Myriam
Published: May 2011

In heterogeneous multi-agent systems, where human and non-human agents coexist, intelligent proxy agents can help smooth out fundamental differences. In this context, delegating the coordination role to proxy agents can improve the overall outcome of a task at the expense of human cognitive overload due to switching subtasks. Stability and commitment are characteristics of human teamwork, but must not prevent the detection of better opportunities. In addition, coordination proxy agents must be trained from examples as a single agent, but must interact with multiple agents. We apply machine learning techniques to the task of learning team preferences from mixed-initiative interactions and compare the outcome results of different simulated user patterns. This chapter introduces a novel approach for the adjustable autonomy of coordination proxies based on the reinforcement learning of abstract actions. In conclusion, some consequences of the symbiotic relationship that such an approach suggests are discussed.
Reputation
Authors: Paolucci Mario , Conte Rosaria
Published: May 2011

This chapter is focused on social reputation as a fundamental mechanism in the diffusion and possibly evolution of socially desirable behaviour (e.g., cooperation, altruism, and norm-abiding behaviour). Reputation is seen as both a property of agents and a process of transmission of beliefs about this property. The main current views and hypotheses about reputation are found to underestimate the importance of the process of transmission. Next, a cognitive analysis of reputation and of its transmission is presented. Hypotheses concerning the transmissibility of reputation are discussed, and checked by means of simulation. Finally, speculations concerning the role of reputation in the evolution of reciprocal altruism are discussed, and ideas for future studies are sketched out.
Relationships Between the Processes of Emergence and Abstraction in Societies
Authors: Baumer Eric , Tomlinson Bill
Published: May 2011

This chapter presents an argument that the process of emergence is the converse of the process of abstraction. Emergence involves complex behavior resulting from simple rules, while abstraction forming simple rules that describe complex behavior. This converse relationship suggests the possibility that similar mechanisms underlie both processes, and a greater understanding of one can lead to a greater understanding of the other. Especially in the case of human and artificial social systems, the processes of abstraction and emergence are inextricably interconnected; the abstractions that individuals make will determine what behaviors emerge, and the behaviors that emerge in the society determine what abstractions will be made. This relationship between the two processes, which we call the abstraction-emergence loop, can be used to gain a better understanding of both. It is argued that the abstraction-emergence loop functions over various degrees of complexity and levels of detail, and that the loop has the greatest efficacy in certain ranges of detail. This way of understanding the two processes has particular bearing on social interactions; in order to understand macro-level emergent social phenomena, we must also simultaneously understand the micro-level phenomena from which they arise. In considering when emergence occurs, the role of the observer in the emergence abstraction loop is also discussed. In addition to describing various properties of the abstraction-emergence loop, this chapter presents descriptions of several ongoing and future research projects in the creation of autonomous agent societies, and offers pointers to future research directions aimed at exploring and understanding the nature of the abstraction-emergence loop. Such an understanding of the relationship between abstraction and emergence can be helpful in designing communities of autonomous agents that interact socially with each other and with humans, and may also be a helpful step toward understanding the phenomena of emergence and abstraction in general.
Supporting Evolution of Knowledge Artifacts in Web Based Learning Environments
Authors: Kotzinos Dimitris , Flouris Giorgos , Tzitzikas Yannis
Published: May 2011

The development of collaborative e-learning environments that support the evolution of semantically described knowledge artifacts is a challenging task. In this chapter we elaborate on usage scenarios and requirements for environments grounded on learning theories that stress on collaborative knowledge creation activities. Subsequently, we present a comprehensive suite of services, comprising an emerging framework, called Semantic Web Knowledge Middleware (SWKM), that enables the collaborative evolution of both domain abstractions and conceptualizations, and data classified using them. The suite includes advanced services for ontology change, comparison and versioning over a common knowledge repository offering persistent storage and validation.
Computer-Aided Personalised System of Instruction for Teaching Mathematics in an Online Learning Environment
Authors: Brinkman Willem-Paul , Rae Andrew , Dwivedi Yogesh Kumar
Published: May 2011

This paper presents a case study of a university’s discrete mathematics course with over 170 students who had access to an online learning environment (OLE) that included a variety of online tools, such as videos, self-tests, discussion boards, and lecture notes. The course is based on the ideas of the Personalised System of Instruction (PSI) modified to take advantage of an OLE. Students’ learning is initially examined over a period of 2 years, and compared with that in a more traditionally taught part of the course. To examine students’ behaviour, learning strategies, attitudes, and performance, both qualitative and quantitative techniques, were used as a mixed methodology approach, including in-depth interviews (N=9), controlled laboratory observations (N=8), surveys (N=243), diary studies (N=10), classroom observations, recording online usage behaviour, and learning assessments. In addition, students’ attitude and performance in 2 consecutive years where PSI was applied to the entire course provides further understanding that is again in favour of PSI in the context of OLE. This chapter aims to increase understanding of whether PSI, supported by an OLE, could enhance student appreciation and achievement as findings suggest.
Social Software for Sustaining Interaction, Collaboration, and Learning in Communities of Practice
Authors: el Helou Sandy , Gillet Denis , Salzmann Christophe , Rekik Yassin
Published: May 2011

The École Polytechnique Fédérale de Lausanne is developing a Web 2.0 social software called eLogbook and designed for sustaining interaction, collaboration, and learning in online communities. This chapter describes the 3A model on which eLogbook is based as well as the main services that the latter provides. The proposed social software has several innovative features that distinguish it from other classical online collaboration solutions. It offers a high-level of flexibility and adaptability so that it can fulfill the requirements of various Communities of Practice. It also provides community members with ubiquitous access and awareness through its different interfaces. Finally, eLogbook strengthens usability and acceptability thanks to its personalization and contextualization mechanisms.
Document Versioning and XML in Digital Libraries
Authors: Martínez-González M. Mercedes
Published: May 2011

Digital libraries are systems that contain organized collections of objects, serving in their most basic functions as a mirror of the traditional library that contains paper documents. Most of the information contained in the collections of a digital library consists of documents, which can evolve with time. That is, a document can be modified to obtain a new document, and digital library users may want access to any of those versions. This introduces in digital libraries the problem of versioning, a problem that is also of interest for the hypertext community and the Semantic Web community. Some domains in which document evolution is a very important issue are the legislative domain (Arnold-Moore, 1997; Martínez González, de la Fuente, Derniame & Pedrero, 2003a; Vitali, 1999), the management of errata made to scientific articles (Poworotznek, 2003), software construction (Conradi & Westfechtel, 1998), and collaborative e-learning (Brooks, Cooke & Vassileva, 2003).
Internet Map Services and Weather Data
Authors: Kelly Maurie Caitlin , Haupt Bernd J. , Baxter Ryan E.
Published: May 2011

Internet map services (IMSs) are redefining the ways in which people interact with geospatial information system (GIS) data. The driving forces behind this trend are the pervasiveness of GIS software and the emerging popularity of mobile devices and navigation systems utilizing GPS (Global Positioning System), as well as the ever-increasing availability of geospatial data on the Internet. These forces are also influencing the increasing need for temporal or real-time data. One trend that has become particularly promising in addressing this need is the development of IMS. IMS is changing the face of data access and creating an environment in which users can view, download, and query geospatial and real-time data into their own desktop software programs via the Internet. In this section, the authors will provide a brief description of the evolution and system architecture of an IMS, identify some common challenges related to implementing an IMS, and provide an example of how IMSs have been developed using real-time weather data from the National Digital Forecast Database (NDFD). Finally, the authors will briefly touch on some emerging trends in IMS, as well as discuss the future direction of IMS and their role in providing access to real-time data.
Improving Constraints Checking in Distributed Databases with Complete, Sufficient, and Support Tests
Authors: Alwan Ali Amer , Ibrahim Hamidah , Udzir Nur Izura
Published: May 2011

A database state is said to be consistent if and only if it satisfies the set of integrity constraints. A database state may change into a new state when it is updated either by a single update operation (insert, delete, or modify) or by a sequence of updates (transaction). If a constraint is false in the new state, the new state is inconsistent, therefore the enforcement mechanism can either perform compensatory actions to produce a new consistent state, or restore the initial state by undoing the update operation. The steps generate integrity tests that are queries composed from the integrity constraints and the update operations, and run these queries against the database, which check whether all the integrity constraints of the database are satisfied; are referred to as integrity checking (Alwan, Ibrahim, & Udzir, 2007; Ibrahim, 2006; Ibrahim, Gray & Fiddian, 2001), is the main focus of this chapter.
Data Integration
Authors: Navas-Delgado Ismael , Aldana-Montes Jose F.
Published: May 2011

The growth of the Internet has simplified data access, which has involved an increment in the creation of new data sources. Despite this increment, in most cases, these large data repositories are accessed manually. This problem is aggravated by the heterogeneous nature and extreme volatility of the information on the Web. This heterogeneity includes three types: intentional (differences in the contents), semantic (differences in the interpretation), and schematic (data types, labeling, structures, etc.). Thus, the increase of the available information and the complexity of dealing with this amount of information have involved a considerable amount of research into the subject of heterogeneous data integration. The database community, one of the most important groups dealing with data heterogeneity and dispersion, has provided a wide range of solutions to this problem. However, this issue has also been addressed and solutions have been offered by the information retrieval and knowledge representation communities, making this area a connection point between the three communities.
Natural Human-System Interaction Using Intelligent Conversational Agents
Authors: Benahmed Yacine , Selouani Sid-Ahmed , Hamam Habib
Published: May 2011

In the context of the prodigious growth of network-based information services, messaging and edutainment, we introduce new tools that enable information management through the use of efficient multimodal interaction using natural language and speech processing. These tools allow the system to respond to close-to natural language queries by means of pattern matching. A new approach which gives the system the ability to learn new utterances of natural language queries from the user is presented. This automatic learning process is initiated when the system encounters an unknown command. This alleviates the burden of users learning a fixed grammar. Furthermore, this enables the system to better respond to spontaneous queries. This work investigates how an information system can benefit from the use of conversational agents to drastically decrease the cognition load of the user. For this purpose, Automated Service Agents and Artificial Intelligence Markup Language (AIML) are used to provide naturalness to the dialogs between users and machines.
DYONIPOS
Authors: Makolm Josef , Weiss Silke , Ipsmiller Doris
Published: May 2011

Efficient and effective knowledge management plays an increasingly important role in knowledge intensive organizations. The research project DYONIPOS focuses on detecting the knowledge needs of knowledge workers and automatically providing this required knowledge just in time. The prototype DYONIPOS generates new knowledge out of artifacts, while avoiding additional work and violations of the knowledge worker’s privacy. The knowledge is made accessible through semantic linkage of the relevant information from existing repositories. In addition DYONIPOS creates an individual and an organizational knowledge data base to achieve the knowledge. This chapter is structured as follows: the introduction section describes the current knowledge management approach and the new approach with use of the DYONIPOS prototype. The background section addresses the relation between the applied approach and the challenge in E-Government, summarizes the aims of the research project DYONIPOS and delivers also insight into the topic knowledge management by describing and criticizing the “SECImodel” according to Ikujiro Nonaka and Hirotaka Takeuchi. After this the research project DYONIPOS, the semantic and knowledge discovery technologies used are presented as well as the use case project DYONIPOS showing the results of the first and the second test and screenshots of the updated DYONIPOS application. The chapter concludes with presentation of the benefits and the technical advantages of the prototype DYONIPOS.
A Formal Framework for Organization Modeling and Analysis
Authors: Popova Viara , Sharpanskykh Alexei
Published: May 2011

This chapter introduces a formal framework for modeling and analysis of organizations. It allows representing and reasoning about all important aspects of artificial and human organizations structured in a number of views, including performance-oriented, process-oriented, and power- and interactionrelated aspects. The framework provides means to model formal (pre)defined organizational structures and dynamics, informal relations, and behavior of organizational actors. The meaning attached to the modeling concepts is specified based on the literature from Social Science. Unlike many existing organization modeling approaches, the proposed framework has formal foundations based on the order-sorted predicate logic which enables different types of analysis of organizational specifications of particular views and across views. The framework allows scalability of modeling and analysis of complex organizations, by considering them at different aggregation levels. Furthermore, the framework provides support for real- time management of organizational processes. The framework was applied in several case studies, one of which is discussed here.
A Logic for Agent Organizations
Authors: Dignum Virgina , Dignum Frank
Published: May 2011

Organization concepts and models are increasingly being adopted for the design and specification of multi-agent systems. Agent organizations can be seen as mechanisms of social order, created to achieve common goals for more or less autonomous agents. In order to develop a theory on the relationship between organizational structures, organizational actions, and actions of agents performing roles in the organization, we need a theoretical framework to describe and reason about organizations. The formal model presented in this chapter is sufficiently generic to enable the comparison of different existing organizational approaches to Multi-Agent Systems (MAS), while having enough descriptive power to describe realistic organizations.
Dynamic Specifications for Norm-Governed Systems
Authors: Artikis Alexander , Kaponis Dimosthenis , Pitt Jeremy
Published: May 2011

We have been developing a framework for executable specification of norm-governed multi-agent systems. In this framework, specification is a design-time activity; moreover, there is no support for run-time modification of the specification. Due to environmental, social, or other conditions, however, it is often desirable, or even necessary, to alter the system specification during the system execution. In this chapter we extend our framework by allowing for “dynamic specifications”, that is, specifications that may be modified at run-time by the members of a system. The framework extension is motivated by Brewka’s “dynamic argument systems”—argument systems in which the rules of order may become the topic of the debate. We illustrate our framework for dynamic specifications by presenting: (i) a dynamic specification of an argumentation protocol, and (ii) an execution of this protocol in which the participating agents modify the protocol specification.
Personal Assistants for Human Organizations
Authors: Okamoto Steven , Sycara Katia , Scerri Paul
Published: May 2011

Intelligent software personal assistants are an active research area with the potential to revolutionize the way that human organizations operate, but there has been little research quantifying how they will impact organizational performance or how organizations will or should adapt in response. In this chapter we develop a computational model of the organization to evaluate the impact different proposed assistant abilities have on the behavior and performance of the organization. By varying the organizational structures under consideration, we can identify which abilities are most beneficial, as well as explore how organizations may adapt to best leverage the new technology. The results indicate that the most beneficial abilities for hierarchical organizations are those that improve load balancing through task allocation and failure recovery, while for horizontal organizations the most beneficial abilities are those that improve communication. The results also suggest that software personal assistant technology will facilitate more horizontal organizations.
Organizational Self-Design in Worth-Oriented Domains
Authors: Kamboj Sachin , Decker Keith S.
Published: May 2011

This chapter presents an approach to organizational-self design (OSD), a method of designing organizations at run-time in which the agents are responsible for generating their own organizational structures. OSD is especially suitable for environments that are dynamic, albeit slowly changing. Such environments preclude the use of static, design-time generated, organizational structures, and yet contain certain characteristics and conditions that change slowly, if at all, and these characteristics can be harnessed for the purposes of creating stable organizational structures. This chapter extends the existing approaches to OSD by applying them to worth-oriented domains – that is, domains in which problems are represented using TÆMS based task structures. This chapter presents our OSD primitives and framework and discusses some interesting future lines of research.