Vehicles with sensors produce large amounts of data. Transmission of data is connectedwith costs. By using data compression, less data has to be transmitted, reducing priceof operation. A number of algorithms are evaluated through tests with GPS and accelerometerdata. Performance is measured based on time usage, compression ratio,and euclidean errors (in the case of lossy compression). No algorithm or combinationof algorithms is shown to outperform the others on all data and all metrics. Threedierent recommendations are made. For lossless data compression focused on speed, acombination of Move-To-Front, Zero-Run-Length-Encoding, and Human coding is recommended.For lossless data compression focusing on compression ratio, a combinationof delta coding, Lempel-Ziv coding, and Human coding is recommended. Finally, fordata that can aord losses and that has a low amount of unique symbols, a model basedapproach is recommended.

Thesis (MPhil)--University of Stellenbosch, 2006. / On title page: Master of Philosophy (Information and Knowledge Management). Bibliography. Also available via the Internet.

Very little information is known about the impact electrification has on driving behavior, or how drivers charge their electrified vehicles. The recent influx of electrified vehicles presents a new market of vehicles which allow drivers the option between electrical or conventional gasoline energy sources. The current battery capacity in full battery electric vehicles requires planning of routes not required of conventional vehicles, due to the limited range, extended charging times, and limited charging infrastructure. There is currently little information on how drivers react to these limitations. A number of current models of fully electric and plug-in hybrid electric vehicles, transmit data wirelessly on key-on, key-off, and charging events. The data includes battery state of charge, distance of miles driven on gasoline and electric, energy consumed, and many other parameters associated to driving and charging behavior. In this thesis, this data was then processed and analyzed to benchmark the performance and characteristics of driving and charging patterns. Vehicles were analyzed and contrasted based on model type, geographic location, length of ownership and other variables. This data was able to show benchmarks and parameters in aggregate for 56 weeks of electrified vehicle tracking. These parameters were compared to the EV Project, a large scale electrified vehicle study performed by Idaho National Labs, to confirm patterns of expected behavior. New parameters which were not present in the EV Project were analyzed and provided insight to charging and driving behavior not examined in any previous study on a large scale. This study provides benchmarks and conclusions on this new driving behavior, such as large scale analysis of brake regeneration performance and degradation of range anxiety. Analysis of the differences on charging and driving behavior between geographic regions and experience were examined, providing insight to how these variables affect performance and driving and charging patterns. Comparison of parameters established by the EV Project and new parameters analyzed in this report will help build a benchmark for future studies of electrified vehicles.

published_or_final_version / Transport Policy and Planning / Master / Master of Arts in Transport Policy and Planning

This dissertation aims to examine factors associated with telehealth initiation among heart failure patients in home care settings using a mixed methods study design. Chapter One identifies the current gap in the literature on telehealth adoption and the significance of this study in filling this gap. Chapter Two provides an integrative review of the literature on factors affecting heart failure patients’ decision making to accept telehealth services in a home setting. Chapter Three presents a quantitative analysis of data from the Outcome and Assessment Information Set (OASIS) on 2,832 heart failure patients referred to telehealth services using a modified Unified Theory of Acceptance Use of Technology (UTAUT) framework, to identify patient-related factors or characteristics associated with telehealth initiation. Chapter Four describes the findings of a qualitative study using individual telephone interviews with heart failure patients at home to explore reasons for telehealth initiation. Finally, in Chapter Five, the findings of all three studies are summarized and overarching conclusions are reported with a discussion of their relationship to previous research. This chapter concludes with a consideration of the strengths and limitations of the study, and implications for practice, policy, and research.

Currently, reliable and appropriate medical information is difficult to find on the Internet. The potential for improvement in human health by the use of internet-based sources of information is potentially huge, as knowledge becomes more widely available, at much lower cost. Medical information has traditionally formed a large part of academic publishing. However, the increasing volume of available information, along with the demand for evidence based medicine makes Internet sources of information appear to be the only practical source of comprehensive and up-to date information. The aim of this work is to develop a system allowing groups of users to identify information that they find useful, and using those particular sources as examples develop an intelligent system that can classify new information sources in terms of their likely usefulness to such groups. Medical information sources are particularly interesting because they cover a very wide range of specialties, they require very strict quality control, and the consequence of error may be extremely serious, in addition, medical information sources are of increasing interest to the general public. This work covers the design, construction and testing of such a system and introduces two new concepts - document structure identification via information entropy and fuzzy ontology for knowledge representation. A mapping between query terms and members of ontology is usually a key part of any ontology enhanced searching tool. However many terms used in queries may be overloaded in terms of the ontology, which limits the potential use of automatic query expansion and refinement. In particular this problem affects information systems where different users are likely to expect different meanings for the same term. This thesis describes the derivation and use of a "Fuzzy Ontology" which uses fuzzy relations between components of the ontology in order to preserve a common structure. The concept is presented in the medical domain. Kolmogorov distance calculations are used to identify similarity between documents in terms of authorship, origin and topic. In addition structural measures such as paragraph tags were examined but found not to be effective in clustering documents. The thesis describes some theoretical and practical evaluation of these approaches in the context of a medical information retrieval system, designed to support ontology-based search refinement, relevance feedback and preference sharing between professional groups.

Thesis (M.A.)--Bowling Green State University, 2007. / Document formatted into pages; contains 96 p. Includes bibliographical references.

University of Macau / Faculty of Science and Technology / Department of Computer and Information Science

Thesis (Ph. D.)(Information Technology)--University of Pretoria, 2002. / Title from opening screen (viewed Apr. 19, 2004).

Thesis (M.A.)--University of Tennessee, Knoxville, 2003. / Title from title page screen (viewed Sept. 18, 2003). Thesis advisor: Janis Appier. Document formatted into pages (iii, 119 p.). Vita. Includes bibliographical references (p. 102-113).