Thesis (Ph. D.)--University of Hong Kong, 2005. / Title proper from title frame. Also available in printed format.

Thesis (M.S. in computer engineering)--Washington State University, August 2006. / Includes bibliographical references (p. 83-84).

Thesis (Ph. D.)--University of Texas at Austin, 2007. / Vita. Includes bibliographical references.

Thesis (Ph. D.)--University of Texas at Austin, 2006. / Vita. Includes bibliographical references.

Thesis (Ph. D.)--University of Texas at Austin, 2006. / Vita. Includes bibliographical references.

Thesis (Ph. D.)--University of Texas at Austin, 2007. / Vita. Includes bibliographical references.

<p>Objectives: First, to identify the core Electronic Health Records (EHR) functionalities available to physicians who work in private and public health care facilities in Trinidad and Tobago and the extent to which physicians are using each function. Second, to understand the rate of adoption of Electronic Health Records in private and public hospitals/clinics, and finally, to identify the barriers to adoption of Electronic Health Records in private and public hospitals/clinics in Trinidad and Tobago. Background: The two largest public hospitals in Trinidad and Tobago, Port of Spain General Hospital and San Fernando General Hospital, utilized paper medical records. In Trinidad and Tobago, there is little known about the EHR functions available and being used, adoption rates, and barriers to adoption of EHR in the private and public sectors. Method: Electronic Health Records (n = 130) questionnaires were sent to number of health care practices in the private and public facilities in the five regions of Trinidad and Tobago, in order to understand availability and use of EHR, adoption rates, and barriers to the use of EHR. Results: The most commonly available function for the private and public physicians was Health Information and Data with respective scores of 58% and 29%. Sixty-three percent of the private physicians who adopted EHR reported using the Result Management and Order Management functions. The public physicians who had adopted EHR reported they were not utilizing the Decision Support, Result Management, and Order Management functions. There was no statistical difference between private and public physicians for the available and used functions. A total of 53 private and 19 public physicians responded to the survey (55% response rate). Thirteen (25%) private physicians reported adopting EHR and 2(11%) public physician reported adoption of EHR. Private and public physicians cited start-up cost and technical limitations of systems as the barriers to their practices' adoption of EHR. Conclusion: Findings showed the same availability and use of core functionalities, as well as adoption rate among the private and public facilities, and slightly fewer barriers in the private practices. A larger sample is merited to understand if there is any statistically significant difference between the two groups.

<p> Providing healthcare to the ever-rising elderly population has become a severe challenge and a top priority. Emerging innovations in healthcare, such as remote health monitoring technologies, promise to provide a better quality of care and reduce the cost of healthcare. However, many elderly people reject healthcare innovations. This lack of adoption constitutes a big practical problem because it keeps the elderly from benefiting from technology advances. The phenomenon is even more pronounced among elderly women, who represent the majority of the elderly population. </p><p> A plethora of studies in the field of technology adoption resulted in sound, but highly generalized theories that are too parsimonious to provide practical insight into the phenomenon of elderly healthcare technology adoption (EHTA). There is a call to arms for novel approaches that facilitate the creation of models that expand technology adoption theories to the specifics of EHTA. This dissertation is a response to this call to arms, and it contributes to modeling practice in the EHTA field. It uses fuzzy cognitive mapping to design a novel mixed-methods modeling approach. Since elderly women constitute the majority of the elderly population, this dissertation treats elderly women&rsquo;s health technology adoption (EWHTA) as the case-in-point.</p><p>

by Chi-sum, Ho. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1995. / Includes bibliographical references (leaves 110-113). / Abstract --- p.i / Acknowledgement --- p.iii / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Overview --- p.1 / Chapter 1.2 --- Cache Memories --- p.1 / Chapter 1.3 --- Improving Cache Performance --- p.3 / Chapter 1.4 --- Improving System Performance --- p.4 / Chapter 1.5 --- Organization of the dissertation --- p.6 / Chapter 2 --- Related Work --- p.8 / Chapter 2.1 --- Cache Performance --- p.8 / Chapter 2.2 --- Non-Blocking Cache --- p.9 / Chapter 2.3 --- Cache Prefetching --- p.10 / Chapter 2.3.1 --- Hardware Prefetching --- p.10 / Chapter 2.3.2 --- Software-assisted Prefetching --- p.13 / Chapter 2.3.3 --- Improving Cache Effectiveness --- p.22 / Chapter 2.4 --- Other Techniques to Reduce and Hide Memory Latencies --- p.25 / Chapter 2.4.1 --- Register Preloading --- p.25 / Chapter 2.4.2 --- Write Policies --- p.26 / Chapter 2.4.3 --- Small Specialized Cache --- p.26 / Chapter 2.4.4 --- Program Transformation --- p.27 / Chapter 3 --- Stride CAM Prefetching --- p.30 / Chapter 3.1 --- Introduction --- p.30 / Chapter 3.2 --- Architectural Model --- p.32 / Chapter 3.2.1 --- Compiler Support --- p.33 / Chapter 3.2.2 --- Hardware Support --- p.35 / Chapter 3.2.3 --- Model Details --- p.39 / Chapter 3.3 --- Optimization Issues --- p.39 / Chapter 3.3.1 --- Eliminating Reductant Prefetching --- p.40 / Chapter 3.3.2 --- Code Motion --- p.40 / Chapter 3.3.3 --- Burst Mode --- p.44 / Chapter 3.3.4 --- Stride CAM Overflow --- p.45 / Chapter 3.3.5 --- Effects of Loop Optimizations --- p.46 / Chapter 3.4 --- Practicability --- p.50 / Chapter 3.4.1 --- Evaluation Methodology --- p.51 / Chapter 3.4.2 --- Prefetch Accuracy --- p.54 / Chapter 3.4.3 --- Stride CAM Size --- p.56 / Chapter 3.4.4 --- Software Overhead --- p.60 / Chapter 4 --- Stride Register Prefetching --- p.67 / Chapter 4.1 --- Motivation --- p.67 / Chapter 4.2 --- Architectural Model --- p.67 / Chapter 4.2.1 --- Stride Register --- p.69 / Chapter 4.2.2 --- Compiler Support --- p.70 / Chapter 4.2.3 --- Prefetch Bits --- p.72 / Chapter 4.2.4 --- Operation Details --- p.77 / Chapter 4.3 --- Practicability and Optimizations --- p.78 / Chapter 4.3.1 --- Practicability on NASA7 Benchmark Programs --- p.78 / Chapter 4.3.2 --- Optimization Issues --- p.81 / Chapter 4.4 --- Comparison Between Stride CAM and Stride Register Models --- p.84 / Chapter 5 --- Small Software-Driven Array Cache --- p.87 / Chapter 5.1 --- Introduction --- p.87 / Chapter 5.2 --- Cache Pollution in MXM --- p.88 / Chapter 5.3 --- Architectural Model --- p.89 / Chapter 5.3.1 --- Operation Details --- p.91 / Chapter 5.4 --- Effectiveness of Array Cache --- p.92 / Chapter 6 --- Conclusion --- p.96 / Chapter 6.1 --- Conclusion --- p.96 / Chapter 6.2 --- Future Research: An Extension of the Stride CAM Model --- p.97 / Chapter 6.2.1 --- Background --- p.97 / Chapter 6.2.2 --- Reference Address Series --- p.98 / Chapter 6.2.3 --- Extending the Stride CAM Model --- p.100 / Chapter 6.2.4 --- Prefetch Overhead --- p.109 / Bibliography --- p.110 / Appendix --- p.114 / Chapter A --- Simulation Results - Stride CAM Model --- p.114 / Chapter A.l --- Execution Time --- p.114 / Chapter A.1.1 --- BTRIX --- p.114 / Chapter A.1.2 --- CFFT2D --- p.115 / Chapter A.1.3 --- CHOLSKY --- p.116 / Chapter A.1.4 --- EMIT --- p.117 / Chapter A.1.5 --- GMTRY --- p.118 / Chapter A.1.6 --- MXM --- p.119 / Chapter A.1.7 --- VPENTA --- p.120 / Chapter A.2 --- Memory Delay --- p.122 / Chapter A.2.1 --- BTRIX --- p.122 / Chapter A.2.2 --- CFFT2D --- p.123 / Chapter A.2.3 --- CHOLSKY --- p.124 / Chapter A.2.4 --- EMIT --- p.125 / Chapter A.2.5 --- GMTRY --- p.126 / Chapter A.2.6 --- MXM --- p.127 / Chapter A.2.7 --- VPENTA --- p.128 / Chapter A.3 --- Overhead --- p.129 / Chapter A.3.1 --- BTRIX --- p.129 / Chapter A.3.2 --- CFFT2D --- p.130 / Chapter A.3.3 --- CHOLSKY --- p.131 / Chapter A.3.4 --- EMIT --- p.132 / Chapter A.3.5 --- GMTRY --- p.133 / Chapter A.3.6 --- MXM --- p.134 / Chapter A.3.7 --- VPENTA --- p.135 / Chapter A.4 --- Hit Ratio --- p.136 / Chapter A.4.1 --- BTRIX --- p.136 / Chapter A.4.2 --- CFFT2D --- p.137 / Chapter A.4.3 --- CHOLSKY --- p.137 / Chapter A.4.4 --- EMIT --- p.138 / Chapter A.4.5 --- GMTRY --- p.139 / Chapter A.4.6 --- MXM --- p.139 / Chapter A.4.7 --- VPENTA --- p.140 / Chapter B --- Simulation Results - Array Cache --- p.141 / Chapter C --- NASA7 Benchmark --- p.145 / Chapter C.1 --- BTRIX --- p.145 / Chapter C.2 --- CFFT2D --- p.161 / Chapter C.2.1 --- cfft2dl --- p.161 / Chapter C.2.2 --- cfft2d2 --- p.169 / Chapter C.3 --- CHOLSKY --- p.179 / Chapter C.4 --- EMIT --- p.192 / Chapter C.5 --- GMTRY --- p.205 / Chapter C.6 --- MXM --- p.217 / Chapter C.7 --- VPENTA --- p.220

by Chin-Ming, Cheung. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1996. / Includes bibliographical references (leaves 95-97). / Abstract --- p.i / Acknowledgement --- p.iii / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Overview --- p.1 / Chapter 1.2 --- Objective --- p.3 / Chapter 1.3 --- Organization of the dissertation --- p.4 / Chapter 2 --- Related Works --- p.6 / Chapter 2.1 --- Previous Cache Works --- p.6 / Chapter 2.2 --- Data Prefetching Techniques --- p.7 / Chapter 2.2.1 --- Hardware Vs Software Assisted --- p.7 / Chapter 2.2.2 --- Non-selective Vs Highly Selective --- p.8 / Chapter 2.2.3 --- Summary on Previous Data Prefetching Schemes --- p.12 / Chapter 3 --- Program Data Mapping --- p.13 / Chapter 3.1 --- Regular and Irregular Data Access --- p.13 / Chapter 3.2 --- Propagation of Data Access Regularity --- p.16 / Chapter 3.2.1 --- Data Access Regularity in High Level Program --- p.17 / Chapter 3.2.2 --- Data Access Regularity in Machine Code --- p.18 / Chapter 3.2.3 --- Data Access Regularity in Memory Address Sequence --- p.20 / Chapter 3.2.4 --- Implication --- p.21 / Chapter 4 --- Register Value Prediction Table (RVPT) --- p.22 / Chapter 4.1 --- Predictability of Register Values --- p.23 / Chapter 4.2 --- Register Value Prediction Table --- p.26 / Chapter 4.3 --- Control Scheme of RVPT --- p.29 / Chapter 4.3.1 --- Details of RVPT Mechanism --- p.29 / Chapter 4.3.2 --- Explanation of the Register Prediction Mechanism --- p.32 / Chapter 4.4 --- Examples of RVPT --- p.35 / Chapter 4.4.1 --- Linear Array Example --- p.35 / Chapter 4.4.2 --- Linked List Example --- p.36 / Chapter 5 --- Program Register Dependency --- p.39 / Chapter 5.1 --- Register Dependency --- p.40 / Chapter 5.2 --- Generalized Concept of Register --- p.44 / Chapter 5.2.1 --- Cyclic Dependent Register(CDR) --- p.44 / Chapter 5.2.2 --- Acyclic Dependent Register(ADR) --- p.46 / Chapter 5.3 --- Program Register Overview --- p.47 / Chapter 6 --- Generalized RVPT Model --- p.49 / Chapter 6.1 --- Level N RVPT Model --- p.49 / Chapter 6.1.1 --- Identification of Level N CDR --- p.51 / Chapter 6.1.2 --- Recording CDR instructions of Level N CDR --- p.53 / Chapter 6.1.3 --- Prediction of Level N CDR --- p.55 / Chapter 6.2 --- Level 2 Register Value Prediction Table --- p.55 / Chapter 6.2.1 --- Level 2 RVPT Structure --- p.56 / Chapter 6.2.2 --- Identification of Level 2 CDR --- p.58 / Chapter 6.2.3 --- Control Scheme of Level 2 RVPT --- p.59 / Chapter 6.2.4 --- Example of Index Array --- p.63 / Chapter 7 --- Performance Evaluation --- p.66 / Chapter 7.1 --- Evaluation Methodology --- p.66 / Chapter 7.1.1 --- Trace-Drive Simulation --- p.66 / Chapter 7.1.2 --- Architectural Method --- p.68 / Chapter 7.1.3 --- Benchmarks and Metrics --- p.70 / Chapter 7.2 --- General Result --- p.75 / Chapter 7.2.1 --- Constant Stride or Regular Data Access Applications --- p.77 / Chapter 7.2.2 --- Non-constant Stride or Irregular Data Access Applications --- p.79 / Chapter 7.3 --- Effect of Design Variations --- p.80 / Chapter 7.3.1 --- Effect of Cache Size --- p.81 / Chapter 7.3.2 --- Effect of Block Size --- p.83 / Chapter 7.3.3 --- Effect of Set Associativity --- p.86 / Chapter 7.4 --- Summary --- p.87 / Chapter 8 --- Conclusion and Future Research --- p.88 / Chapter 8.1 --- Conclusion --- p.88 / Chapter 8.2 --- Future Research --- p.90 / Bibliography --- p.95 / Appendix --- p.98 / Chapter A --- MCPI vs. cache size --- p.98 / Chapter B --- MCPI Reduction Percentage Vs cache size --- p.102 / Chapter C --- MCPI vs. block size --- p.106 / Chapter D --- MCPI Reduction Percentage Vs block size --- p.110 / Chapter E --- MCPI vs. set-associativity --- p.114 / Chapter F --- MCPI Reduction Percentage Vs set-associativity --- p.118