bluuebunny/crossref_metadata_2025 huggingface dataset:
The Conception of the Intensity-Curvature Functional
Authors: Ciulla Carlo
Published: May 2011

The preceding chapter is to be viewed as a purely theoretical math intuition and the claim consists in that of the existence of a region within the voxel (the three dimensional pixel) where interpolation is most beneficial because it is meant to produce the least approximation of the true intensity value and this region has been named: “Sub-pixel Efficacy Region” (SRE). An energy function will be defined here as the ratio between the energy of the original image and the energy of the interpolated image. This ratio which is called the Intensity-Curvature Functional, is symbolized by the expression ?E = Eo / EIN, and it is prone to be studied to reveal its behavior within the voxel, and it is prone to determine the boundary of the Sub-pixel Efficacy Region within the voxel. In this chapter the Intensity-Curvature Functional will be treated for what concerns the trivariate liner interpolation function such to present its original conception. An application of the Intensity-Curvature Functional for the improvement of the trivariate liner interpolation function was however previously reported (Ciulla & Deek, 2005).
Catering for Personal Autonomy with E-Mentoring Supported by Recommendations
Authors: Santos Olga , Barrera Carmen , Mazzone Emanuela , Boticario Jesus
Published: May 2011

This chapter presents a technology solution based on a recommender system supporting people with intellectual disabilities in their work integration and independent life, in the scope of the CISVI and AMI4Inclusicion research projects. Information and Communication Technologies are essential for supporting personal autonomy and improving the quality of life of disabled people. The technology can contribute in a twofold way: (1) facilitating the work of the human mentor when training people with intellectual disabilities and (2) automatically offering them advice and recommendations in response to certain cues/actions detected in the environment.
A Projection of the Future Effects of Quantum Computation on Information Privacy
Authors: Skinner Geoff , Chang Elizabeth
Published: May 2011

Many of the current issues with Information Privacy have been the result of inadequate consideration for privacy during the planning, design and implementation of Information Systems and communication networks. The area of Quantum Computation is still in its infancy, and a truly functional quantum computer has not been implemented. However, it is anticipated that within the next decade it may be feasible. This presents a unique opportunity to give due consideration to Information Privacy in the realm of future quantum computational devices and environments while they are still in their infancy. This chapter provides an overview of the key Information Privacy issues that the authors feel may arise with the evolution and realization of quantum computation. Additionally they propose an integrated approach of technical, legal and social elements to address these issues.
Global Stability Analysis for Complex-Valued Recurrent Neural Networks and Its Application to Convex Optimization Problems
Authors: Yoshida Mitsuo , Mori Takehiro
Published: May 2011

Global stability analysis for complex-valued artificial recurrent neural networks seems to be one of yet-unchallenged topics in information science. This chapter presents global stability conditions for discrete-time and continuous- time complex-valued recurrent neural networks, which are regarded as nonlinear dynamical systems. Global asymptotic stability conditions for these networks are derived by way of suitable choices of activation functions. According to these stability conditions, there are classes of discrete-time and continuous-time complex-valued recurrent neural networks whose equilibrium point is globally asymptotically stable. Furthermore, the conditions are shown to be successfully applicable to solving convex programming problems, for which real field solution methods are generally tedious.
A Method of Estimation for Magnetic Resonance Spectroscopy Using Complex-Valued Neural Networks
Authors: Morita Naoyuki
Published: May 2011

The author proposes an automatic estimation method for nuclear magnetic resonance (NMR) spectra of the metabolites in the living body by magnetic resonance spectroscopy (MRS) without human intervention or complicated calculations. In the method, the problem of NMR spectrum estimation is transformed into the estimation of the parameters of a mathematical model of the NMR signal. To estimate these parameters, Morita designed a complex- valued Hopfield neural network, noting that NMR signals are essentially complex-valued. In addition, we devised a technique called sequential extension of section (SES) that takes into account the decay state of the NMR signal. Morita evaluated the performance of his method using simulations and shows that the estimation precision on the spectrum improves when SES is used in combination the neural network, and that SES has an ability to avoid the local minimum solution on Hopfield neural networks.
Qubit Neural Network
Authors: Matsui Nobuyuki , Nishimura Haruhiko , Isokawa Teijiro
Published: May 2011

Recently, quantum neural networks have been explored as one of the candidates for improving the computational efficiency of neural networks. In this chapter, after giving a brief review of quantum computing, the authors introduce our qubit neural network, which is a multi-layered neural network composed of quantum bit neurons. In this description, it is indispensable to use the complex-valued representation, which is based on the concept of quantum bit (qubit). By means of the simulations in solving the parity check problems as a bench mark examination, we show that the computational power of the qubit neural network is superior to that of the conventional complex-valued and real-valued neural networks. Furthermore, the authors explore its applications such as image processing and pattern recognition. Thus they clarify that this model outperforms the conventional neural networks.
ECG Processing
Authors: Lhotská Lenka , Chudácek Václav , Huptych Michal
Published: May 2011

This chapter describes methods for preprocessing, analysis, feature extraction, visualization, and classification of electrocardiogram (ECG) signals. First we introduce preprocessing methods, mainly based on the discrete wavelet transform. Then classification methods such as fuzzy rule based decision trees and neural networks are presented. Two examples - visualization and feature extraction from Body Surface Potential Mapping (BSPM) signals and classification of Holter ECGs – illustrate how these methods are used. Visualization is presented in the form of BSPM maps created from multi-channel measurements on the patient’s thorax. Classification involves distinguishing between Holter recordings from premature ventricular complexes and normal ECG beats. Classification results are discussed. Finally the future research opportunities are proposed.
Gene Expression Mining Guided by Background Knowledge
Authors: Kléma Jirí , Železný Filip , Trajkovski Igor , Karel Filip , Crémilleux Bruno
Published: May 2011

This chapter points out the role of genomic background knowledge in gene expression data mining. The authors demonstrate its application in several tasks such as relational descriptive analysis, constraintbased knowledge discovery, feature selection and construction or quantitative association rule mining. The chapter also accentuates diversity of background knowledge. In genomics, it can be stored in formats such as free texts, ontologies, pathways, links among biological entities, and many others. The authors hope that understanding of automated integration of heterogeneous data sources helps researchers to reach compact and transparent as well as biologically valid and plausible results of their gene-expression data analysis.
Gaussian-Stacking Multiclassifiers for Human Embryo Selection
Authors: Morales Dinora A. , Bengoetxea Endika , Larrañaga Pedro
Published: May 2011

Infertility is currently considered an important social problem that has been subject to special interest by medical doctors and biologists. Due to ethical reasons, different legislative restrictions apply in every country on human assisted reproduction techniques such as in-vitro fertilization (IVF). An essential problem in human assisted reproduction is the selection of suitable embryos to transfer in a patient, for which the application of artificial intelligence as well as data mining techniques can be helpful as decision-support systems. In this chapter we introduce a new multi-classification system using Gaussian networks to combine the outputs (probability distributions) of standard machine learning classification algorithms. Our method proposes to consider these outputs as inputs for a superior-level and to apply a stacking scheme to provide a meta-level classification result. We provide a proof of the validity of the approach by employing this multi-classification technique to a complex real medical problem: The selection of the most promising embryo-batch for human in-vitro fertilization treatments.
Mobile and Pervasive Technology in Education and Training
Authors: Lee Mark J.W.
Published: May 2011

This chapter investigates the use of mobile digital technologies for learning, or mobile learning (mlearning), across a variety of education and training settings. In particular, it focuses on pervasive m-learning, defined as m-learning involving activities that are able to integrate into learners’ lives, coinciding with other actions and tasks in an unobtrusive fashion. It also considers new and emerging pervasive computing, wearable, and ambient intelligence (AmI) technologies that enable implicit, unseen interactions between humans, objects, and their environment. The chapter is primarily concerned with the question of whether, and if so, how mobile and pervasive computing technologies can be used in pedagogically sound ways. Drawing on a number of illustrative examples, the chapter examines the degree to which pervasive m-learning has been achieved, or can be achieved, with current technologies, as well as the resulting benefits. It then raises a number of potential challenges and risk factors, before synthesizing the above into a number of realistic visions and future applications of pervasive m-learning. The chapter concludes with a discussion of the implications for education and training practitioners and researchers.
Biometrical Identification as a Challenge for Legislation
Authors: Suomi Reima , Aho Tuomas , Björkroth Tom , Koponen Aki
Published: May 2011

Accurate identification of individuals is a cornerstone of any modern society. Without identification, we cannot recognize the parties of different transactions and bind individuals to their rights and liabilities. Without identification, the transactions, rights, and liabilities become useless, and society can no longer work. Biometrical identification offers a technologically effective solution to the identification problems. These technologies are spreading fast in the whole information and communication technology field and pervading into many aspects of using computers and similar devices. Just like any other technology, biometric identification cannot develop without a sufficient regulative environment. This chapter provides an overview of the challenges and approaches, in addition to introducing biometric technologies. Finland has had connection with biometric identification and this chapter covers some aspects of the same.
TRASS
Authors: Lotzmann Ulf
Published: May 2011

In this chapter an agent-based traffic simulation approach is presented which sees agents as individual traffic participants moving in an artificial environment. There is no restriction on types of players, such as car drivers or pedestrians. A concept is introduced which is appropriate to model different kinds of traffic participants and to have them interact with each other in one single scenario. The scenario may not only include roads, but also stadiums, shopping malls and any other situations where pedestrians or vehicles of any kind move around. Core theme of the chapter is an agent model that is founded on a layered architecture. Experiences with implementation and usage of the agent model within the universal multi-agent simulation framework TRASS will be explained by means of several application examples which also support discussion about validation of concept and implementation.
Valuation-Aware Traffic Control
Authors: Schepperle Heiko , Böhm Klemens
Published: May 2011

Current intersection-control systems lack one important feature: They are unaware of the different valuations of reduced waiting time of the drivers. Drivers with high valuations may be willing to pay to be prioritized at intersections. In this chapter, the authors describe an agent-based valuation-aware intelligent traffic-control system for road intersections which increases the overall driver satisfaction. It combines valuation-aware intersection-control mechanisms with sophisticated driver-assistance features, subsequently referred to as adaptive cruise and crossing control (A3C). Driver-assistance agents and intersection agents negotiate so-called time slots to cross the intersection. The driver-assistance agent adapts the speed of the vehicle in line with the time slot obtained. Various obstacles are in the way of realizing such a system and making it operational. The authors discuss these challenges and present ideas for solutions. They examine the intersection-control and the driver-assistance perspective of the intelligent traffic-control system. After a brief evaluation, they finally describe application scenarios where agent-based valuation-aware intersection control may become operational in the near future.
Traffic Congestion Management as a Learning Agent Coordination Problem
Authors: Tumer Kagan , Welch Zachary T. , Agogino Adrian
Published: May 2011

Traffic management problems provide a unique environment to study how multi-agent systems promote desired system level behavior. In particular, they represent a special class of problems where the individual actions of the agents are neither intrinsically “good” nor “bad” for the system. Instead, it is the combinations of actions among agents that lead to desirable or undesirable outcomes. As a consequence, agents need to learn how to coordinate their actions with those of other agents, rather than learn a particular set of “good” actions. In this chapter, the authors focus on problems where there is no communication among the drivers, which puts the burden of coordination on the principled selection of the agent reward functions. They explore the impact of agent reward functions on two types of traffic problems. In the first problem, the authors study how agents learn the best departure times in a daily commuting environment and how following those departure times alleviates congestion. In the second problem, the authors study how agents learn to select desirable lanes to improve traffic flow and minimize delays for all drivers. In both cases, they focus on having an agent select the most suitable action for each driver using reinforcement learning, and explore the impact of different reward functions on system behavior. Their results show that agent rewards that are both aligned with and sensitive to, the system reward lead to significantly better results than purely local or global agent rewards. They conclude this chapter by discussing how changing the way in which the system performance is measured affects the relative performance of these rewards functions, and how agent rewards derived for one setting (timely arrivals) can be modified to meet a new system setting (maximize throughput).
Multiagent Learning on Traffic Lights Control
Authors: Oliveira Denise de , Bazzan Ana L.C.
Published: May 2011

In a complex multiagent system, agents may have different partial information about the system’s state and the information held by other agents in the system. In a distributed urban traffic control, where each junction has an independent controller, agents that learn can benefit from exchanging information, but this exchange of information may not always be useful. In this chapter the authors analyze how agents can benefit from sharing information in an urban traffic control scenario and the consequences of this cooperation in the performance of the traffic system.
A Multidimensional Pattern Based Approach for the Design of Data Marts
Authors: Ben-Abdallah Hanene , Feki Jamel , Abdallah Mounira Ben
Published: May 2011

Despite their strategic importance, the wide-spread usage of decision support systems remains limited by both the complexity of their design and the lack of commercial design tools. This chapter addresses the design complexity of these systems. It proposes an approach for data mart design that is practical and that endorses the decision maker involvement in the design process. This approach adapts a development technique well established in the design of various complex systems for the design of data marts (DM): Pattern-based design. In the case of DM, a multidimensional pattern (MP) is a generic specification of analytical requirements within one domain. It is constructed and documented with standard, real-world entities (RWE) that describe information artifacts used or produced by the operational information systems (IS) of several enterprises. This documentation assists a decision maker in understanding the generic analytical solution; in addition, it guides the DM developer during the implementation phase. After over viewing our notion of MP and their construction method, this chapter details a reuse method composed of two adaptation levels: one logical and one physical. The logical level, which is independent of any data source model, allows a decision maker to adapt a given MP to their analytical requirements and to the RWE of their particular enterprise; this produces a DM schema. The physical specific level projects the RWE of the DM over the data source model. That is, the projection identifies the data source elements necessary to define the ETL procedures. We illustrate our approaches of construction and reuse of MP with examples in the medical domain.
Methodology for Improving Data Warehouse Design using Data Sources Temporal Metadata
Authors: Araque Francisco , Salguero Alberto , Delgado Cecilia
Published: May 2011

One of the most complex issues of the integration and transformation interface is the case where there are multiple sources for a single data element in the enterprise Data Warehouse (DW). There are many facets due to the number of variables that are needed in the integration phase. This chapter presents our DW architecture for temporal integration on the basis of the temporal properties of the data and temporal characteristics of the data sources. If we use the data arrival properties of such underlying information sources, the Data Warehouse Administrator (DWA) can derive more appropriate rules and check the consistency of user requirements more accurately. The problem now facing the user is not the fact that the information being sought is unavailable, but rather that it is difficult to extract exactly what is needed from what is available. It would therefore be extremely useful to have an approach which determines whether it would be possible to integrate data from two data sources (with their respective data extraction methods associated). In order to make this decision, we use the temporal properties of the data, the temporal characteristics of the data sources, and their extraction methods. In this chapter, a solution to this problem is proposed.
Students' Attitudes toward Process and Product Oriented Online Collaborative Learning
Authors: Wang Xinchun
Published: May 2011

Although the pedagogical advantages of online interactive learning are well known, much needs to be done in instructional design of applicable collaborative learning tasks that motivate sustained student participation and interaction. In a previous study based on a Web-based course offered in 2004, Wang (2007) investigated the factors that promote sustained online collaboration for knowledge building. By providing new data from the same Web-based course offered in 2006 and 2007, this study investigates students’ attitudes toward process- and product-oriented online collaborative learning. The analysis of 93 post course survey questionnaire data show that the overwhelming majority of students have positive experience with online collaborative learning. Data also suggest that students are more enthusiastic about process-oriented tasks and their attitudes toward product-oriented collaborative learning tasks are mixed.
An Agent Based Framework for Personalized E-Learning Services
Authors: Esmahi Larbi
Published: May 2011

This paper provides an overview of personalized e-learning services and related technology and presents a multi-agent system for delivering adaptive e-learning. We discussed the main issues related to personalization in e-learning: technology advancement and the shift in perception of the learning process, one size fits all versus personalized services, and the adaptation process. The paper provides also an overview of most known implemented systems for adaptive e-learning, as well as detailed description of the architecture and components of the proposed multi-agent framework. Finally, the paper concludes with some comments about the dimensions to consider for implementing personalization..
Supporting Argumentative Collaboration in Communities of Practice
Authors: Karacapilidis Nikos , Tzagarakis Manolis
Published: May 2011

Providing the necessary means to support and foster argumentative collaboration is essential for Communities of Practice to achieve their goals. However, current tools are unable to cope with the evolving stages of the collaboration. This is primarily due to the inflexible level of formality they provide. Arguing that a varying level of formality needs to be offered in systems supporting argumentative collaboration, this chapter proposes an incremental formalization approach that has been adopted in the development of CoPe_it!, a Web-based tool that complies with collaborative principles and practices, and provides members of communities engaged in argumentative discussions and decision making processes with the appropriate means to collaborate towards the solution of diverse issues. According to the proposed approach, incremental formalization can be achieved through the consideration of alternative projections of a collaborative workspace.
Schema Evolution Models and Languages for Multidimensional Data Warehouses
Authors: Benítez-Guerrero Edgard , Rechy-Ramírez Ericka-Janet
Published: May 2011

A Data Warehouse (DW) is a collection of historical data, built by gathering and integrating data from several sources, which supports decisionmaking processes (Inmon, 1992). On-Line Analytical Processing (OLAP) applications provide users with a multidimensional view of the DW and the tools to manipulate it (Codd, 1993). In this view, a DW is seen as a set of dimensions and cubes (Torlone, 2003). A dimension represents a business perspective under which data analysis is performed and organized in a hierarchy of levels that correspond to different ways to group its elements (e.g., the Time dimension is organized as a hierarchy involving days at the lower level and months and years at higher levels). A cube represents factual data on which the analysis is focused and associates measures (e.g., in a store chain, a measure is the quantity of products sold) with coordinates defined over a set of dimension levels (e.g., product, store, and day of sale). Interrogation is then aimed at aggregating measures at various levels. DWs are often implemented using multidimensional or relational DBMSs. Multidimensional systems directly support the multidimensional data model, while a relational implementation typically employs star schemas(or variations thereof), where a fact table containing the measures references a set of dimension tables.
Artifacts for Collaborative Software Development
Authors: Tiako Pierre F.
Published: May 2011

The development of software applications generally requires the following: hardware resources (computers, networks, peripherals, etc.), software resources (data, tools, etc.), human resources (individuals with various qualifications), and working methods. These resources are distributed in different autonomous software development environments. A single environment does not always have all the necessary resources to realize some large and/or complex projects. Therefore, collaboration between the environment in charge of the project (coordinator) and others (contractors) will be required to do the job. While several research projects have contributed to various aspects of collaboration among software development environments during the past decade, little has been done on explicitly defining and modeling processes and environment artifacts involved in such partnerships. That is what this chapter is about. In the context of this study, environments work together by assigning tasks and sharing working methods. Tasks and working methods can be defined explicitly using process models. Process models, already the main focus in monolithic software development, will still be an important factor in our approach of collaborative software development. Because they are process-based, all software development environments considered here will be qualified in the continuation of Process-sensitive Software Engineering Environments (PSEEs).
Similarity Search in Time Series
Authors: Kontaki Maria , Papadopoulos Apostolos N. , Manolopoulos Yannis
Published: May 2011

In many application domains, data are represented as a series of values in different time instances (time series). Examples include stocks, seismic signals, audio, and so forth. Similarity search in time series databases is an important research direction. Several methods have been proposed to provide efficient query processing in the case of static time series of fixed length. Research in this field has focused on the development of effective transformation techniques, the application of dimensionality reduction methods, and the design of efficient indexing schemes. These tools enable the process of similarity queries in time series databases. In the case where time series are continuously updated with new values (streaming time series), the similarity problem becomes even more difficult to solve, since we must take into consideration the new values of the series. The dynamic nature of streaming time series precludes the use of methods proposed for the static case. To attack the problem, significant research has been performed towards the development of effective and efficient methods for streaming time series processing. In this article, we introduce the most important issues concerning similarity search in static and streaming time series databases, presenting fundamental concepts and techniques that have been proposed by the research community.
Spatial Data Integration Over the Web
Authors: Díaz Laura , Granell Carlos , Gould Michael
Published: May 2011

Spatial data are increasingly becoming available on the Internet in applications such as routing portals that involve map-based and satellite imagery backgrounds, allowing a large audience to access and share the rich databases that are currently used by the specialized geographic community. These spatial data are heterogeneous, being available in various formats, and stored in disparate formats (flat files, relational or object-oriented databases, etc.). Some data are structured according to well-established data modeling techniques such as the relational or object-oriented data models; other data, such as data maintained in various information systems, spreadsheets, or Internet repositories, are in proprietary formats, semistructured, or unstructured. In practice, this situation of multiple models and schemas combined with the difficulty for establishment agreements for data representation in the application domains becomes spatial data in special regarding other types of scientific data, making the interoperability problem a nontrivial task (Lemmens, Wytzisk, de By, Granell, Gould & van Oosterom, 2006). In addition to the scale of data integration, the complex and heterogeneous query processing and domain-specific computational capabilities supported by these sources make spatial data integration a real challenge (Boulcema, Essid & Lacroix, 2002; Devogele, Parent & Spaccapietra, 1998; Goodchild, Egenhofer, Fegeas & Kottman, 1999).
Synopsis Data Structures for Representing, Querying, and Mining Data Streams
Authors: Cuzzocrea Alfredo
Published: May 2011

Data-stream query processing and mining is an emerging challenge for the database research community. This issue has recently gained the attention from the academic as well as the industrial world. Data streams are continuously flooding data produced by untraditional information sources. They are generated by a growing number of data entities, among all we recall performance measurements in network monitoring and traffic management systems, call details records in telecommunication systems, transactions in retail chains, ATM operations, log records generated by Web servers, sensor network data, RFID- (radio frequency identification) based readings, and so forth.
Adaptive XML-to-Relational Storage Strategies
Authors: Mlynkova Irena
Published: May 2011

Without any doubt, the eXtensible Markup Language (XML) (Bray et al., 2006) is currently one of the most popular formats for data representation. Its wide popularity naturally invoked an enormous endeavour to propose faster and more efficient methods and tools for managing and processing of XML data. Soon it was possible to distinguish several different directions. The four most popular ones are methods which store XML data in a classical file system, methods which store and process XML data using a relational database management system, methods which exploit a pure object-oriented approach and native methods that use special indices, numbering schemas and/or data structures proposed or suitable particularly for tree structure of XML data.
User Culture, User-System Relation and Trust – The Case of Finnish Wikipedia
Authors: Kokkonen Juhana
Published: May 2011

In this chapter the open-source based collaboration model of Finnish Wikipedia is examined from the perspective of user culture, which is the fundamental basis of Wikipedia’s project management. The concept of user culture in a mediated collaboration project is introduced and the user culture of Finnish Wikipedia is analyzed in terms of this concept. Also the concept of user-system-relation is presented and the relation between users and the socio-technical system of Wikipedia is examined. This analysis considers the crucial factors in the process of building a trusting relation between the user and the Wikipedia system. From the perspective of user-system-relation, the relationship of trust between the user and the system is much more important than the trust relations between individual users. This article explains the role of user culture and user culture design in a collaborative Web community and considers the nature of a trusting user-system-relation. Examination of one functional example of open information management gives understanding of management tools for open peer-collaboration in general.
Ambient Networks
Authors: Galis Alex , Mathieu Bertrand
Published: May 2011

This chapter introduces the Ambient Network (AN) which is a network integration solution that aims at fostering dynamic co-operation between the next generation, heterogeneous wireless and wired networks, in order to gather resources within and across networks to provide new services to end users. First, it depicts the main characteristics of AN before describing the Ambient Control Space, which is the space where functional entities managing the networks and the services are active, and the interfaces. Then it focuses on the SATO (Service-aware Adaptive Transport Overlays), which is a service overlay networks deployed on top of the underlying heterogeneous physical networks and tailored according to the services‘ requirements and users‘ context. This chapter aims at giving the readers a good overview of what Ambient networks are since they will be present in the next years everywhere.
Towards an Integral Approach of Organizations in Multi-Agent Systems
Authors: Ferber Jacques , Stratulat Tiberiu , Tranier John
Published: May 2011

In this chapter, we stress the importance of thinking a MAS in all its aspects (agents, environment, interactions, organizations, and institutions), using a more integral vision. We show that a genuine organizational approach has to take into account both the environment and the institutional part of MAS societies. Then, we propose the MASQ (Multi-Agent System based on Quadrants) meta-model, which constitutes an abstraction of the various aspects of an OCMAS (Organization Centered Multi-Agent Systems), extending AGR (Agent/Group/Role). MASQ is based on a four-quadrant framework, where the analysis and design of a system is performed along two axes: an interior/exterior dimension and an individual/collective dimension. We give a conceptual definition of this approach and we will show that it is possible to apply it to practical models.
OMACS
Authors: DeLoach Scott A.
Published: May 2011

This chapter introduces a suite of technologies for building complex, adaptive systems. It is based in the multi-agent systems paradigm and uses the Organization Model for Adaptive Computational Systems (OMACS). OMACS defines the knowledge needed about a system’s structure and capabilities to allow it to reorganize at runtime in the face of a changing environment and its agent’s capabilities. However, the OMACS model is only useful if it is supported by a set of methodologies, techniques, and architectures that allow it to be implemented effectively on a wide variety of systems. To this end, this chapter presents a suite of technologies including (1) the Organization-based Multiagent Systems Engineering (O-MaSE) methodology, (2) a set of policy specification techniques that allow an OMACS system to remain flexible while still providing guidance, and (3) a set of architectures and algorithms used to implement OMACSbased systems. The chapter also includes the presentation of a small OMACS-based system.
Hermes
Authors: Cheong Christopher , Winikoff Michael
Published: May 2011

Although intelligent agents individually exhibit a number of characteristics, including social ability, flexibility, and robustness, which make them suitable to operate in complex, dynamic, and error-prone environments, these characteristics are not exhibited in multi-agent interactions. For instance, agent interactions are often not flexible or robust. This is due to the traditional message-centric design processes, notations, and methodologies currently used. To address this issue, we have developed Hermes, a goaloriented design methodology for agent interactions which is aimed at being pragmatic for practicing software engineers. Hermes focuses on interaction goals, i.e., goals of the interaction which the agents are attempting to achieve, and results in interactions that are more flexible and robust than messagecentric approaches. In this chapter, we present the design and implementation aspects of Hermes. This includes an explanation of the Hermes design processes, notations, and design artifacts, along with a detailed description of the implementation process which provides a mapping of design artifacts to goal-plan agent platforms, such as Jadex.
Structural Aspects of Organizations
Authors: Grossi Davide , Dignum Frank
Published: May 2011

In this chapter we investigate how organizations can be represented as graphs endowed with formal semantics. We distinguish different dimensions of organizations. Each of these dimensions leads to a different structure in the organizational graph. By giving the graphs a formal semantics in Description Logic we show that it is possible to formalize the effect of the organization on the activities of the agents playing the roles of the organization. Such perspective, which combines quantitative (graph-theory) and qualitative (logic) methods is shown to provide a formal ground for the study and analysis of properties of organizations which are commonly addressed only informally.
Autonomous Agents Adopting Organizational Rules
Authors: van der Vecht Bob , Dignum Frank , Meyer John-Jules Ch.
Published: May 2011

This chapter discusses how autonomous agents can adopt organizational rules into their reasoning process. Agents in an organization need to coordinate their actions in order to reach the organizational goals. Organizational models specify the desired behaviour in terms of roles, relations, norms, and interactions. We have developed a method to translate norms into event-processing rules of the agents. We propose a modular reasoning model that includes the organizational rules explicitly. Since the agents are autonomous, they will have their own reasoning rules next to the organizational rules. The modular approach allows for meta-reasoning about these rules. We show that this stimulates bottom-up dynamics in the organization.
Verifying Organizations Regulated by Institutions
Authors: Viganò Francesco , Colombetti Marco
Published: May 2011

Institutions have been proposed to explicitly represent norms in open multi-agent systems, where agents may not follow them and which therefore require mechanisms to detect violations. In doing so, they increase the efficiency of electronic transactions carried out by agents, but raise the problem of ensuring that such institutions are not characterized by contradictory norms, and provide agents with all the needed powers to fulfill their objectives. In this chapter we present a framework to verify organizations regulated by institutions, which is characterized by a precise formalization of institutional concepts, a language to describe institutions, and a tool to model check them. Finally, to evaluate and exemplify our approach, we model and verify the Chaired Meeting Institution, showing that the verification of institutional rules constitutes a necessary step to define sound institutions.
Capturing Data from Customers
Authors: Al-Shammari Minwir
Published: May 2011

The customer is a strategic element in a company’s downstream supply chain. In the new economy, customers, whether they are individual consumers or businesses, are becoming demanding, powerful, and more knowledgeable than before. The pressure of customers for more improvements (e.g. in quality, cost, and delivery), has been intensified by globalization of marketplaces and the emergence of new business philosophies and models (e.g. click and mortar direct-sale business model). Customer data is the key to successful relationships with customers. Data acquisition is the process to capture, integrate, cleanse, and load customer data, from various customer touchpoints, into the operational data store (ODS) and DW in order to create customer information and knowledge. This chapter intends to examine the concepts, issues, and trends related to capturing customer data and routing it to, or sharing it with, people in other units within the organization.
Measuring Return on Relationships with Customers
Authors: Al-Shammari Minwir
Published: May 2011

Effective development of customer products and/or services requires valid and up-to-date CK in order to target the right customer with the right offering at the right time and through the right channel. Increasing value-adding content of customer offerings is hoped to be reflected on major gains in cost, time, and quality of products and/or services. Doing good things for customers is doing good things good for business. This chapter addresses customer value reciprocity for business represented by durable and profitable customer relationship.
Developing Interoperability in Mass Customization Information Systems
Authors: Jardim-Goncalves Ricardo , Grilo António , Steiger-Garcao Adolfo
Published: May 2011

This chapter proposes a standard-based framework to assist industrial organizations to develop interoperability in mass customization Information Systems. After identifying the major challenges for business and information systems in mass customization, the authors propose an innovative standardbased conceptual architecture for a combined model-driven and services-oriented platform. The chapter concludes by describing a global methodology for integration of models and applications, to enhance an enterprise’s interoperability in the support of mass customization practices, keeping the same organization’s technical and operational environment, but improving its methods of work and the usability of the installed technology through harmonization and integration of the enterprise models in use by customers, manufacturers, and suppliers. Its platform aims to stimulate the adoption of mass customization concepts and improve those practices through proper integration and harmonization of information system models, knowledge, and data.
Mass Customization with Configurable Products and Configurators
Authors: Heiskala Mikko , Tihonen Juha , Paloheimo Kaija-Stiina , Soininen Timo
Published: May 2011

Configurable products are an important way to achieve mass customization. A configurable product is designed once, and this design is used repetitively in the sales-delivery process to produce specifications of product individuals meeting customer requirements. Configurators are information systems that support the specification of product individuals and the creation and management of configuration knowledge, therefore being prime examples of information systems supporting mass customization. However, to the best of our knowledge, there is no systematic review of literature on how mass customization with configurable products and use of configurators affect companies. In this chapter, we provide such a review. We focus on benefits that can be gained and challenges which companies may face. A supplier can move to mass customization and configuration from mass production or from full customization; we keep the concerns separate. We also review benefits and challenges from the customer perspective. Finally, we identify future research directions and open challenges and problems.
Wireless Video Transmission
Authors: Aramvith Supavadee , Cajote Rhandley D.
Published: May 2011

Presently, both wireless communications and multimedia communications have experienced unequaled rapid growth and commercial success. Building on advances of network infrastructure, low-power integrated circuits, and powerful signal processing/compression algorithms, wireless multimedia services to support digital video applications such as videophone, video conferencing, video streaming, video on demand (VoD), and video surveillance, likely finds widespread acceptance. Many wireless multimedia applications require video coding schemes and underlying transport that can provide acceptable quality of service to the end users. Due to the burst errors nature of wireless channels and the error propagation property of compressed video, suitable source and channel coding schemes are required to handle such conditions. This chapter provides overview of video compression techniques, and the latest video coding standard, H.264/AVC, its implication for the wireless video transmission, and our research contribution on joint source-channel coding for wireless video transmission.
Trust in the Value-Creation Chain of Multimedia Goods
Authors: Schmidt Andreas U. , Kuntze Nicolai
Published: May 2011

Security in the value creation chain hinges on many single components and their interrelations. Trusted Platforms open ways to fulfil the pertinent requirements. This chapter gives a systematic approach to the utilisation of trusted computing platforms over the whole lifecycle of multimedia products. This spans production, aggregation, (re)distribution, consumption, and charging. Trusted Computing technology as specified by the Trusted Computing Group provides modular building blocks which can be utilized at many points in the multimedia lifecycle. We propose an according research roadmap beyond the conventional Digital Rights Management use case. Selected technical concepts illustrate the principles of Trusted Computing applications in the multimedia context.
Adaptive Image Steganography Based on Structural Similarity Metric
Authors: Liu Guangjie , Lian Shiguo , Dai Yuewei , Wang Zhiquan
Published: May 2011

Image steganography is a common form of information hiding which embeds as many message bits into images and keep the introduced distortion imperceptible. How to balance the trade-off between the capacity and imperceptibility has become a very important issue in the researches of steganography. In this chapter, we discuss one kind of the solution for disposing the trade-off, named adaptive image steganography. After a brief review, we present two methods based on structural similarity metric. The first one is based on the generalized LSB, in which the substitution depth vector is obtained via the dynamic programming under the constraint of an allowable distortion. The second method is proposed to use adaptive quantization-embedder to carry message bits. Different from the first method, the distortion index is constructed by contrast-correlation distortion. The other difference is that the parameters of the adaptive quantization embedder are embedded into the image containing message bits by the reversible da a hiding method. Beside that, we also bring forward some attractive directions worthy of being studied in the future. Furthermore, we find that the existing methods do not have a good way to control the amount of information and the distortion as an extract manner, and most schemes are designed just according to the experiences and experiments.
Multiple Description Coding with Application in Multimedia Watermarking
Authors: Liu Minglei , Zhu Ce
Published: May 2011

Digital watermarking is a useful and powerful tool for multimedia security such as copyright protection, tamper proofing and assessment, broadcast monitoring, and fingerprinting. Many multimedia services are provided through wire/wireless communications, where transmission errors are present. Robustness of watermarking is a major concern during the transmission of watermarked multimedia messages. Multiple description coding (MDC) is a promising method for robust transmission of information over non-prioritized and unpredictable networks. As a source coding scheme, multiple description coding has been extensively studied and applied in audio, image, and video sources. It is also interesting to find that multiple description coding can be applied in multimedia watermarking. Recently several multiple description watermarking schemes have been developed which have exhibited some advantages. In this chapter, the concept, design algorithms, and some applications of multiple description coding are reviewed. Particularly, the application of MDC in watermarking, known as multiple description watermarking, is elaborated based on recent research results.
Socio-Technical Theory and Work Systems in the Information Age
Authors: Eason Ken , Abdelnour-Nocera José
Published: May 2011

This chapter sets the traditional focus of socio-technical systems theory on primary work systems in a modern context where information and communication technology (ICT) has a major influence in the way work is undertaken. The chapter begins with a summary of the original work of the Tavistock Institute of Human Relations and critically reviews the major concepts to emerge from these studies. This is followed by a review of recent studies of the impact of ICT on work systems and how socio-technical systems concepts are used to interpret these findings. Finally, concepts and methods of designing socio-technical systems are reviewed in the context of current ways of designing and implementing customizable and generic ICT systems in organizations. The authors call for a recognition and evaluation of socio-technical systems as never completed but evolving over time; placing an emphasis on the emergent behavior resulting from the use of new technical systems.