Abstract

Abstract
Recent studies of mobile Web trends show the continued explosion of mobile-friend content. However, the wide number and heterogeneity of mobile devices poses several challenges for Web programmers, who want automatic delivery of context and adaptation of the content to mobile devices. Hence, the device detection phase assumes an important role in this process. In this chapter, the authors compare the most used approaches for mobile device detection. Based on this study, they present an architecture for detecting and delivering uniform m-Learning content to students in a Higher School. The authors focus mainly on the XML device capabilities repository and on the REST API Web Service for dealing with device data. In the former, the authors detail the respective capabilities schema and present a new caching approach. In the latter, they present an extension of the current API for dealing with it. Finally, the authors validate their approach by presenting the overall data and statistics collected through the Google Analytics service, in order to better understand the adherence to the mobile Web interface, its evolution over time, and the main weaknesses. Copyright (C) 2013, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

Abstract
In addition to capital infrastructure and consumers, digital information created by individual and corporate consumers of information technology is quickly being recognized as a key economic resource and an extremely valuable asset to a company. Organizational, Legal, and Technological Dimensions of Information System Administration recognizes the importance of information technology by addressing the most crucial issues, challenges, opportunities, and solutions related to the role and responsibility of an information system. Highlighting various aspects of the organizational and legal implications of system administration, this reference work will be useful to managers, IT professionals, and graduate students who seek to gain an understanding in this discipline.

Abstract
The process of devising solutions for conflict resolution generally configures a challenging task. There exist different approaches to address the problem, namely the use of case-based models or even relying on the parties themselves to perform the task. From a computational point of view, these problems generally represent a NP-complete problem. In order to surpass this shortcoming, in this paper it is presented a biologically inspired method to deal with the problem in which genetic algorithms are used to create possible solutions for a given dispute. The approach presented is able to generate a broad number of diverse solutions that cover virtually the whole search space for a given problem. This approach provides better results than a case-based approach since: (1) it is independent of the legal domain and (2) it does not depend on the number and quality of cases present in a database. The results of this work are being applied in a negotiation tool that is part of the UMCourt conflict resolution platform.

Abstract

Abstract