Asynchronous and Distributed Multi-Criteria Decision Making Using a Web-Based Group Support System

A detailed model for designing a Web-based Multi-Criteria Group Support System (MCGSS) is presented. The model is based on the Analytic Hierarchy Process (AHP) and uses the intensity of preferences of group members rather than simple voting procedures. This approach offers several advantages over simple voting mechanisms, including a much richer picture of both individual and group positions and more equitable decision-making. A prototype system, with a user-friendly graphical user interface (GUI), has been developed and used to analyze an experimental group decision process over the Internet. This permits a wider range of users, including those with limited typing skills, asynchronous communication across many time zones, and a larger number of participants than conventional systems. An agenda for further research is outlined.

Managing Process Compliance

The current best practice of providing reliable systems is to embody the development process in recent industry standards and guidelines, such as IEC61508 for safety and ISO9001 for quality assurance. These standards are generic, but every application is different because of the differences in project details. While current workflow systems have been used successfully in managing “administrative” process for some time, current products lack the ability to ensure that a process is planned and performed such that it complies with an industry standard that is necessary to support particular engineering processes. This chapter presents a Compliance Flow Workflow System for managing processes. Model-based reasoning is used to identify the compliance errors of a process by matching it against the model of standards used. Some examples drawing on a draft version of IEC61508 are used to illustrate the mechanism of modeling and compliance checks.

LEZI

In this chapter we present LEZI, an experimental software tool oriented to the production of indexed videos enriched with hypertextual and multimedia elements for distance learning applications. LEZI is based on the assumption that in particular types of educational hypermedia productions, the quality of educational content may easily compensate for a user interface limited to the essentials or a reduced set of multimedia features. Production of this kind of hypermedia application can be high quality, even with short production cycles at very low cost. The purpose of the chapter is to show how a traditional lesson or a conference can be effectively transformed into a powerful multimedia product based on a very simple and regular structure.

Integrating the End User into Infrastructure Systems

This chapter analyzes the role of users in enacting Intelligent Transportation Systems (ITS) functions and services. Preliminary evidence from recent demonstrations and market research studies is reviewed with a focus on the role of travelers in producing and using information about traffic conditions and traveler options. The potential for systems development is then considered with specific regard to alternative mode travel, flexible travel, emergency, and commercial services. Based on these findings, several directions and recommendations are made for creating the next generation of ITS systems that enhance user-based elements. Several areas for research and development are recommended, including integrating a wider range of market segments into ITS systems planning, developing a better understanding of how users drive complex systems, and creating new institutional partnerships for delivering innovative services.

Electronic Journalism in Peru

This chapter introduces electronic journalism as a new trend in the news services that have recently been boosted by Internet diffusion. It makes a presentation of electronic media pioneers in the world and the challenges they faced to deliver news to their traditional and Internet-based customers. Mainly, the chapter focuses on the description of the beginnings, evolution, strategies, and current state of Peruvian information media, focusing on Web-based journalism. Finally, the authors offer some conclusions about the approaches to develop Web news services adopted by traditional and virtual media, and suggest the need for future research in different countries in order to compare results and define the media trends in the Internet era.

Publishing Model for Web Applications

This chapter defines a publishing model for Web applications starting from the analysis of the most well-known modeling methodology, such as HDM, OOHDM, WebML, Conallen’s method and others. The analysis has been focused to verify the state of art about the modeling of Web application pages. In particular, the different types of elements that compose the Web page in the above models are taken into consideration. This chapter describes the evolution of the HDM methodology starting from the first approach based on the definition of a LP concept up to the more structured and complex Conceptual page, based on the influence of “operations” on the modeling of the dynamics of navigation between pages.

Culture and Anonymity in GSS Meetings

Anonymity is an important aspect of group support systems (GSS). However, as to the overall effectiveness of the use of anonymity, findings have been inconclusive. Some studies show positive effects in the number of ideas generated, quality of ideas, and uniqueness of ideas, whereas other studies show negative or neutral effects. An examination of social psychology literature indicates that the effect of public self-awareness on evaluation apprehension in different cultural groups may play a crucial role. Thus, social psychology and Hofstede’s model of cultural differentiation are used in this chapter to explain the different effects of anonymity on the behavior of Hong Kong and Canadian groups during GSS sessions. It is hoped that understanding the effects of anonymity in different cultural contexts will better inform the design and facilitation of GSS in increasingly diverse global settings.

Knowledge-Based Personalization

We present a novel method for software personalization. Personalization is understood broadly as a set of mechanisms by which an application is tailored to a particular end user and his or her task. The presented method outlined here is motivated by and remedies a few widely recognized problems in the way customization is carried out. The proposed method has been used in a collaborative system called Writer’s Aid. It relies on a declarative specification of preconditions and effects of system’s actions and applies artificial intelligence, automated reasoning, and planning framework and techniques to dynamically recognize the lack or availability of the personal information at the precise time when it affects a system action and initiates an interaction with the user aimed at eliciting this information in case it has not yet been specified.

An Integrated Network Management Framework Using CORBA, Mobile Agents and Web-Based Technologies

Today’s network management is still dominated by the platform-centered paradigm based on client/server technologies. This centralized approach has drawbacks in scalability, reliability, efficiency and flexibility, and is unsuitable for large and heterogenerous networks. Modern networks require an open management architecture, which can provide standard interfaces for information sharing among management systems, has extensibility for handling change quickly, and has means to manage large networks. Emerging technologies such as Web-, CORBA-, and Mobile Agent-based technologies represent an excellent opportunity to solve these problems. In this chapter a new Web-based network management framework is proposed, which combines the strengths of these novel ways of managing networks and the results of a prototype implementation are discussed. Our preliminary results indicate that the integration of Web-, CORBA-, and Mobile Agent-based technologies within an Integrated Network Management System framework can dramatically improve the performance of the networked environment.

The Effect of Training Set Distributions for Supervised Learning Artificial Neural Networks on Classification Accuracy

Neural networks have been repeatedly shown to outperform traditional statistical modeling techniques for both discriminant analysis and forecasting. While questions regarding the effects of architecture, input variable selection, learning algorithm, and size of training sets on the neural network model’s performance have been addressed, very little attention has been focused on distribution effects of training and out-of-sample populations on neural network performance. This article examines the effect of changing the population distribution within training sets for estimated distribution density functions, in particular for a credit risk assessment problem.