Peer-to-Peer(P2P) systems have emerged as a promising paradigm to structure large scale distributed systems. They provide a robust, scalable and decentralized way to share and publish data.The unstructured P2P systems have gained much popularity in recent years for their wide applicability and simplicity. However efficient resource discovery remains a fundamental challenge for unstructured P2P networks due to the lack of a network structure. To effectively harness the power of unstructured P2P systems, the challenges in distributed knowledge management and information search need to be overcome. Current attempts to solve the problems pertaining to knowledge management and search have focused on simple term based routing indices and keyword search queries. Many P2P resource discovery applications will require more complex query functionality, as users will publish semantically rich data and need efficiently content location algorithms that find target content at moderate cost. Therefore, effective knowledge and data management techniques and search tools for information retrieval are imperative and lasting. In my dissertation, I present a suite of protocols that assist in efficient content location and knowledge management in unstructured Peer-to-Peer overlays. The basis of these schemes is their ability to learn from past peer interactions and increasing their performance with time.My work aims to provide effective and bandwidth-efficient searching and data sharing in unstructured P2P environments. A suite of algorithms which provide peers in unstructured P2P overlays with the state necessary in order to efficiently locate, disseminate and replicate objects is presented. Also, Existing approaches to federated search are adapted and new methods are developed for semantic knowledge representation, resource selection, and knowledge evolution for efficient search in dynamic and distributed P2P network environments. Furthermore,autonomous and decentralized algorithms that reorganizes an unstructured network topology into a one with desired search-enhancing properties are proposed in a network evolution model to facilitate effective and efficient semantic search in dynamic environments.

Over a decade ago, there was no standardised method for information sharing during emergency situations. Governments, first responders, and emergency practitioners often had to rely on what little technology that was available to them. This situation slowed down communications, putting entire recovery operations, and lives at stake. The Emergency Data Exchange Language (EDXL) is the umbrella standard for several emergency communication standards that are being developed to address this issue. The Semantic Web is slowly, but steadily becoming a natural extension of the present-day Web. Thanks to efforts from researchers, and corporations such as Google, Facebook, etc., we are seeing more, and more semantics aware applications on the Web. These applications have been successful in bringing Semantic Web technologies to the common user to a large extent. Semantic Web technologies have found applications in a wide range of domains, from medical research to media management. However, a study to see if EDXL messaging standards can benefit from Semantic Web technologies has not yet been made. In this thesis, we investigate the possibility of enabling Semantic Web technologies for EDXL standards, specifically the EDXL Resource Messaging (EDXL-RM) standard, and explore the benefits that can come out of it. The possibility of converting XML based EDXL-RM messages to semantic formats is explored at first. This step is achieved through the evaluation of existing tools and technologies. Based on the outcome of this study, an EDXL to OWL converter that works in two stages is developed. The motivation for enabling semantic support for EDXL standards is illustrated through several use cases.

The current study provides evidence for the dissociation between two types of asymmetries in relations within semantic memory: those due to unidirectional associative strength (e.g., Kahan, Neely & Forsythe, 1999), and the inherent asymmetry of causal relations (e.g., Fenker, Waldmann & Holyoak, 2005). By manipulating the stimulus onset asynchrony (SOA) in a relation recognition task, I demonstrate that expectancy differentially impacts the effects of these asymmetries. An asymmetrical directional response time advantage was seen with causal relations at both long (1000 ms) and short (150 ms) SOAs, but only at long SOAs for unidirectional associates. These data are taken to support the hypothesis that latencies due to unidirectional association are a result of the manner in which these relations are accessed, and latencies due to the asymmetry of causal relations are reflective of the manner in which cause-effect asymmetries are represented.

The current study was designed to investigate the effect of an expected or unexpected sound on performance of a visual perception task. On each trial, listeners were required to indicate whether an arrow presented on a computer screen directly in front of them was pointing to the left or right. The arrow stimulus was immediately preceded by a to-be ignored auditory event that was either a pure tone, the word ‘left’ or the word ‘right’. The probability that the arrow was preceded by a tone, a congruent word, or an incongruent word was manipulated across experiments. Congruent words facilitated classification of the arrow stimulus regardless of whether or not they were expected. Incongruent words slowed classification regardless of whether or not they were expected. These results revealed that both expected and unexpected auditory events receive involuntary semantic processing in a cross-modal oddball task.

No description available.

The current study was designed to investigate the effect of an expected or unexpected sound on performance of a visual perception task. On each trial, listeners were required to indicate whether an arrow presented on a computer screen directly in front of them was pointing to the left or right. The arrow stimulus was immediately preceded by a to-be ignored auditory event that was either a pure tone, the word ‘left’ or the word ‘right’. The probability that the arrow was preceded by a tone, a congruent word, or an incongruent word was manipulated across experiments. Congruent words facilitated classification of the arrow stimulus regardless of whether or not they were expected. Incongruent words slowed classification regardless of whether or not they were expected. These results revealed that both expected and unexpected auditory events receive involuntary semantic processing in a cross-modal oddball task.

No description available.

Zugl.: Wien, Wirtschaftsuniv., Diplomarb.

Thesis (M.S.) -- Central Connecticut State University, 2008. / Thesis advisor: Roger Bilisoly. "... in partial fulfillment of the requirements for the degree of Master of Science in Data Mining." Includes bibliographical references (leaves 122-127). Also available via the World Wide Web.

Thesis (Ph. D.)--George Mason University, 2008. / Vita: p. 177. Thesis director: Larry Kerschberg. Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Information Technology. Title from PDF t.p. (viewed July 3, 2008). Includes bibliographical references (p. 169-176). Also issued in print.