published_or_final_version / abstract / Computer Science / Doctoral / Doctor of Philosophy

<p> US asthma prevalence increased by five million in the last decade and health care spending for the disease increased from $53 billion to $56 billion. Children are more likely than adults to have an asthma attack and its estimated that 1-in-10 youth has asthma. Despite initiatives to promote adherence to practice guidelines, childhood asthma emergency room) visits, and hospitalizations remain steady while the number of asthma deaths have increased over a 17-year period. Preliminary studies find the majority of adolescents prefer smartphones as a means of education and guidance. A modified Technology Acceptance Model (TAM) survey was comprised of 15 statements that explored providers&rsquo; acceptance of smartphone applications (apps) as an adjunct strategy for management of asthma among adolescents in the outpatient setting. Current insight in adolescent asthma demonstrates multifaceted disparities in care stemming from biological and developmental transitions unique to adolescents. The quantitative, descriptive design of the project assessed two factors integral to the TAM related to provider acceptance and perception: 1) Perceived use (PU), and 2) Perceived ease of use (PEU). The survey sample consisted of 18 providers. Overwhelmingly, the majority of providers surveyed favored use of a smartphone app for adolescent asthma and believed apps had the potential to improve the quality of adolescent asthma management. Most participants agreed; smartphone apps might help accomplish benchmarks for adolescent asthma management. Numerous studies demonstrate adolescents&rsquo; preference for technological interventions for self-management of their asthma symptoms. The survey results reinforce the willingness of providers to accept asthma smartphone apps as a potential adjunct management strategy for adolescent asthma. Additional studies involving providers are required to further explore provider attitudes of acceptance and rejection relating to smartphone apps for chronic health conditions. </p>

by Yung, Chan. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1995. / Includes bibliographical references (leaves 107-110). / Abstract --- p.i / Acknowledgement --- p.iii / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Cache --- p.1 / Chapter 1.1.1 --- Introduction --- p.1 / Chapter 1.1.2 --- Data Prefetching --- p.2 / Chapter 1.2 --- Register --- p.2 / Chapter 1.3 --- Problems and Challenges --- p.3 / Chapter 1.3.1 --- Overhead of registers --- p.3 / Chapter 1.3.2 --- EReg --- p.5 / Chapter 1.4 --- Organization of the Thesis --- p.6 / Chapter 2 --- Previous Studies --- p.8 / Chapter 2.1 --- Introduction --- p.8 / Chapter 2.2 --- Data aliasing --- p.9 / Chapter 2.3 --- Data prefetching --- p.12 / Chapter 2.3.1 --- Introduction --- p.12 / Chapter 2.3.2 --- Hardware Prefetching --- p.12 / Chapter 2.3.3 --- Prefetching with Software Support --- p.13 / Chapter 2.3.4 --- Reducing Cache Pollution --- p.14 / Chapter 3 --- BASIC and ADM Models --- p.15 / Chapter 3.1 --- Introduction of Basic Model --- p.15 / Chapter 3.2 --- Architectural and Operational Detail of Basic Model --- p.18 / Chapter 3.3 --- Discussion --- p.19 / Chapter 3.3.1 --- Implicit Storing --- p.19 / Chapter 3.3.2 --- Associative Logic --- p.22 / Chapter 3.4 --- Example for Basic Model --- p.22 / Chapter 3.5 --- Simulation Results --- p.23 / Chapter 3.6 --- Temporary Storage Problem in Basic Model --- p.29 / Chapter 3.6.1 --- Introduction --- p.29 / Chapter 3.6.2 --- Discussion on the Solutions --- p.31 / Chapter 3.7 --- Introduction of ADM Model --- p.35 / Chapter 3.8 --- Architectural and Operational Detail of ADM Model --- p.37 / Chapter 3.9 --- Discussion --- p.39 / Chapter 3.9.1 --- File Partition --- p.39 / Chapter 3.9.2 --- STORE Instruction --- p.39 / Chapter 3.10 --- Example for ADM Model --- p.40 / Chapter 3.11 --- Simulation Results --- p.40 / Chapter 3.12 --- Temporary storage Problem of ADM Model --- p.46 / Chapter 3.12.1 --- Introduction --- p.46 / Chapter 3.12.2 --- Discussion on the Solutions --- p.46 / Chapter 4 --- ADS Model and ADSM Model --- p.49 / Chapter 4.1 --- Introduction of ADS Model --- p.49 / Chapter 4.2 --- Architectural and Operational Detail of ADS Model --- p.50 / Chapter 4.3 --- Discussion --- p.52 / Chapter 4.3.1 --- Prefetching Priority --- p.52 / Chapter 4.3.2 --- Data Prefetching --- p.53 / Chapter 4.3.3 --- EReg File Splitting --- p.53 / Chapter 4.3.4 --- Compiling Procedure --- p.53 / Chapter 4.4 --- Example for ADS Model --- p.54 / Chapter 4.5 --- Simulation Results --- p.55 / Chapter 4.6 --- Discussion on the Architectural and Operational Variations for ADS Model --- p.62 / Chapter 4.6.1 --- Temporary storage Problem --- p.62 / Chapter 4.6.2 --- Operational variation for Data Prefetching --- p.63 / Chapter 4.7 --- Introduction of ADSM Model --- p.64 / Chapter 4.8 --- Architectural and Operational Detail of ADSM Model --- p.65 / Chapter 4.9 --- Discussion --- p.67 / Chapter 4.10 --- Example for ADSM Model --- p.67 / Chapter 4.11 --- Simulation Results --- p.68 / Chapter 4.12 --- Discussion on the Architectural and Operational Variations for ADSM Model --- p.71 / Chapter 4.12.1 --- Temporary storage Problem --- p.71 / Chapter 4.12.2 --- Operational variation for Data Prefetching --- p.73 / Chapter 5 --- IADSM Model and IADSMC&IDLC Model --- p.75 / Chapter 5.1 --- Introduction of IADSM Model --- p.75 / Chapter 5.2 --- Architectural and Operational Detail of IADSM Model --- p.76 / Chapter 5.3 --- Discussion --- p.79 / Chapter 5.3.1 --- Implicit Loading --- p.79 / Chapter 5.3.2 --- Compiling Procedure --- p.81 / Chapter 5.4 --- Example for IADSM Model --- p.81 / Chapter 5.5 --- Simulation Results --- p.84 / Chapter 5.6 --- Temporary Storage Problem of IADSM Model --- p.87 / Chapter 5.7 --- Introduction of IADSMC&IDLC Model..........: --- p.88 / Chapter 5.8 --- Architectural and Operational Detail of IADSMC & IDLC Model --- p.89 / Chapter 5.9 --- Discussion --- p.90 / Chapter 5.9.1 --- Additional Operations --- p.90 / Chapter 5.9.2 --- Compiling Procedure --- p.93 / Chapter 5.10 --- Example for IADSMC&IDLC Model --- p.93 / Chapter 5.11 --- Simulation Results --- p.94 / Chapter 5.12 --- Temporary Storage Problem of IADSMC&IDLC Model --- p.96 / Chapter 6 --- Compiler and Memory System Support for EReg --- p.99 / Chapter 6.1 --- Impact on Compiler --- p.99 / Chapter 6.1.1 --- Register Usage --- p.99 / Chapter 6.1.2 --- Effect of Unrolling --- p.100 / Chapter 6.1.3 --- Code Scheduling Algorithm --- p.101 / Chapter 6.2 --- Impact on Memory System --- p.102 / Chapter 6.2.1 --- Memory Bottleneck --- p.102 / Chapter 6.2.2 --- Size of EReg Files --- p.103 / Chapter 7 --- Conclusions --- p.104 / Chapter 7.1 --- Summary --- p.104 / Chapter 7.2 --- Future Research --- p.105 / Bibliography --- p.107 / Chapter A --- Source code of the Kernels --- p.111 / Chapter B --- Program Analysis --- p.126 / Chapter B.1 --- Program analysed by Basic Model --- p.126 / Chapter B.2 --- Program analysed by ADM Model --- p.133 / Chapter B.3 --- Program analysed by ADS Model --- p.140 / Chapter B.4 --- Program analysed by ADSM Model --- p.148 / Chapter B.5 --- Program analysed by IADSM Model --- p.156 / Chapter B.6 --- Program analysed by IADSMC&IDLC Model --- p.163 / Chapter C --- Cache Simulation on Prefetching of ADS model --- p.174

Thesis (Ph. D.)--University of Washington, 2000. / Vita. Includes bibliographical references (leaves 128-131).

Thesis (Ph. D.)--University of Texas at Austin, 2002. / Vita. Includes bibliographical references. Available also from UMI Company.

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