This thesis aims to seek interesting patterns from massive amounts of Flickr data in Sweden with pro- posed new clustering strategies. The aim can be further divided into three objectives. The first one is to acquire large amount of timestamped geolocation data from Flickr servers. The second objective is to develop effective and efficient methods to process the data. More specifically, the methods to be developed are bifold, namely, the preprocessing method to solve the “Big Data” issue encountered in the study and the new clustering method to extract spatio-temporal patterns from data. The third one is to analyze the extracted patterns with scaling analysis techniques in order to interpret human social activities underlying the Flickr Data within the urban envrionment of Sweden. During the study, the three objectives were achieved sequentially. The data employed for this study was vector points downloaded through Flickr Application Programming Interface (API). After data ac- quisition, preprocessing was performed on the raw data. The whole dataset was firstly separated by year based on the temporal information. Then data of each year was accumulated with its former year(s) so that the evovling process can be explored. After that, large datasets were splitted into small pieces and each piece was clipped, georeferenced, and rectified respectively. Then the pieces were merged together for clustering. With respect to clustering, the strategy was developed based on the Delaunay Triangula- tion (DT) and head/tail break rule. After that, the generated clusters were analyzed with scaling analysis techniques and spatio-temporal patterns were interpreted from the analysis results. It has been found that the spatial pattern of the human social activities in the urban environment of Sweden generally follows the power-law distribution and the cities defined by human social activities are evolving as time goes by. To conclude, the contributions of this research are threefold and fulfill the objectives of this study, respectively. Firstly, large amount of Flickr data is acquired and collated as a contribution to other aca- demic researches related to Flickr. Secondly, the clustering strategy based on the DT and head/tail break rule is proposed for spatio-temporal pattern seeking. Thirdly, the evolving of the cities in terms of human activities in Sweden is detected from the perspective of scaling. Future work is expected in major two aspects, namely, data and data processing. For the data aspect, the downloaded Flickr data is expected to be employed by other studies, especially those closely related to human social activities within urban environment. For the processing aspect, new algorithms are expected to either accelerate the processing process or better fit machines with super computing capacities.

Antibiotic treatment failure might be due to bacterial resistance or suboptimal exposure at target site and there is a lack of knowledge on the interaction between antimicrobial pharmacodynamics (PD) and the immune response to bacterial infections. Therefore, it is crucial to develop tools to increase the understanding of drug disposition to better evaluate antibiotic candidates in drug development and to elucidate the role of the immune system in bacterial infections. Colistin is used as salvage therapy against multidrug resistant Gram-negative infections. In this work, a whole-body physiologically based pharmacokinetic model (WBPBPK) was developed to characterize the pharmacokinetics (PK) of colistin and its prodrug colistin methanesulfonate (CMS) in animal and human. The scalability of the model from animal to human was assessed with satisfactory predictive performance for CMS and demonstrating the need for a mechanistic understanding of colistin elimination. The WBPBPK model was applied to investigate the impact of pathophysiological changes commonly observed in critically ill patients on tissue distribution of colistin and to evaluate different dosing strategies. Model predicted concentrations in tissue were used in combination with a semi-mechanistic PKPD model to predict bacterial killing in tissue for two strains of Pseudomonas aeruginosa. Finally, a toxicokinetic (TK) model was constructed to describe the time course of E. coli endotoxin concentrations in plasma and the effect on pro-inflammatory cytokine release. The model adequately described the concentration-time profiles of endotoxin and its stimulation of IL-6 and TNF-α production using an indirect response model combined with a transit compartment chain with a tolerance component to endotoxemia. The WBPBPK model developed in this work increased the knowledge on colistin tissue exposure under various conditions and could be used in drug development process to assess antibiotic efficacy or to test new drug combinations. The model describing endotoxin TK and its effect on cytokines is a new tool to be further applied in longitudinal studies to explore the immune response cascade induced by bacterial infections. The methodology applied in this thesis contributes to the development of an integrated modeling framework including physiology, drug distribution, bacterial growth and killing as well as the immune response to infection.

<p>Between October 2001 and May 2012 approximately 70% of U.S. military personnel killed in action and 75% wounded in action were the direct result of exposure to an explosion. As of 2008, it was estimated that close to 20% of all Operation Iraqi Freedom and Operation Enduring Freedom (OIF/OEF) veterans had sustained some form of traumatic brain injury (TBI). Further, blast exposure is also a civilian problem due to the increased usage of explosives in terrorist attacks. Blast injury research has historically focused on the pulmonary system and the other air-containing organs which have been shown through extensive experimentation to be susceptible to blast overpressure injury. A shift in injury pattern during recent conflicts is characterized by decreased incidence of pulmonary injuries with an increase in TBI thought to be associated with blast exposure. This increase in observation of blast TBI has resulted in a large research effort to understand mechanisms and thresholds. However, due to the relatively sudden shift, much of this research is being conducted without a proper understanding and consideration of blast mechanics and interspecies scaling effects.</p><p>This dissertation used experimental and computational finite element (FE) analysis to investigate some large questions surrounding blast TBI research. An experimental investigation was conducted to determine the effects of modern thoracic body armor usage on blast pressure exposure seen by the body. To improve FE modeling capabilities, brain tissue mechanics in common blast TBI animal model species were investigated experimentally and computationally to determine viscoelastic constitutive behavior and measure interspecies variation. Meta-analysis of blast pulmonary literature was conducted to update interspecies scaling and injury risk models. To derive interspecies scaling and injury risk models for blast neurotrauma endpoints a meta-analysis of existing experimental data was used.</p><p>This dissertation makes major contributions to the field of injury biomechanics and blast injury research. Research presented in this dissertation showed that modern thoracic body armor has the ability to lower the risk of pulmonary injury from blast exposure by attenuating and altering blast overpressure. The study shows that the use of soft body armor results in the pulmonary injury threshold being similar to that for neurotrauma. The use of hard body armor results in the threshold for pulmonary injury occurring at higher levels than that of neurotrauma. This finding is important, as it helps to explain the recent shift in injury types observed and highlights the importance of continued widespread usage of body armor not only for ballistic protection but for protection from blast as well.</p><p>This dissertation also shows the importance of interspecies scaling for investigation of blast neurotrauma. This work looks at existing in vivo animal model data to derive appropriate scaling across a wide range of brain size. Appropriate scaling for apnea occurrence and fatality for blast isolated to the head was found to be approximately equal to a characteristic length scaling of brain size, assuming similar brain geometry. By combining the interspecies scaling developed and existing tests data, injury risk models were derived for short duration blast exposures.</p><p>The contributions and conclusions of this dissertation serve to inform the injury biomechanics field and to improve future research efforts. The consideration by researchers of the recommendations presented in this dissertation for in vivo animal model testing will serve to maximize the value gained from experimentation and improve our understanding of blast injury mechanisms and thresholds. The injury risk models presented in this work help to improve our ability to prevent, diagnose, and treat blast neurotrauma.</p> / Dissertation

In this thesis a design for a smart high efficiency voltage regulating module capable of supplying the core of modern microprocessors incorporating dynamic voltage and frequency scaling (DVS) capability is accomplished using a RISC based microcontroller to facilitate all the functions required to control, protect, and supply the core with the required variable operating voltage as set by the DVS management system. Normally voltage regulating modules provide maximum power efficiency at designed peak load, and the efficiency falls off as the load moves towards lesser values. A mathematical model has been derived for the main converter and small signal analysis has been performed in order to determine system operation stability and select a control scheme that would improve converter operation response to transients and not requiring intense computational power to realize. A Simulation model was built using Matlab/Simulink and after experimenting with tuned PID controller and fuzzy logic controllers, a simple fuzzy logic control scheme was selected to control the pulse width modulated converter and several methods were devised to reduce the requirements for computational power making the whole system operation realizable using a low power RISC based microcontroller. The same microcontroller provides circuit adaptations operation in addition to providing protection to load in terms of over voltage and over current protection. A novel circuit technique and operation control scheme enables the designed module to selectively change some of the circuit elements in the main pulse width modulated buck converter so as to improve efficiency over a wider range of loads. In case of very light loads as the case when the device goes into standby, sleep or hibernation mode, a secondary converter starts operating and the main converter stops. The secondary converter adapts a different operation scheme using switched capacitor technique which provides high efficiency at low load currents. A fuzzy logic control scheme was chosen for the main converter for its lighter computational power requirement promoting implementation using ultra low power embedded controllers. Passive and active components were carefully selected to augment operational efficiency. These aspects enabled the designed voltage regulating module to operate with efficiency improvement in off peak load region in the range of 3% to 5%. At low loads as the case when the computer system goes to standby or sleep mode, the efficiency improvent is better than 13% which will have noticeable contribution in extending battery run time thus contributing to lowering the carbon footprint of human consumption.

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Reservoir heterogeneities exhibit a wide range of length scales, and their interaction with various transport mechanisms control the overall performance of subsurface flow and transport processes. Modeling these processes at large-scales requires proper scale-up of both heterogeneity and the underlying transport mechanisms. This research demonstrates a new reservoir modeling procedure to systematically quantify the scaling characteristics of transport processes by accounting for sub-scale heterogeneities and their interaction with various transport mechanisms based on the volume averaging approach. Although treatments of transport problems with the volume averaging technique have been published in the past, application to real geological systems exhibiting complex heterogeneity is lacking. A novel procedure, where results from a fine-scale numerical flow simulation reflecting the full physics of the transport process albeit over a small sub-volume of the reservoir, can be integrated with the volume averaging technique to provide effective description of transport at the coarse scale. In a volume averaging procedure, scaled up equations describing solute transport in single-phase flow are developed. Scaling characteristics of effective transport coefficient corresponding to different reservoir heterogeneity correlation lengths as well as different transport mechanisms including convection, dispersion, and diffusion are studied. The method is subsequently extended to describe transport in multiphase systems to study scaling characteristics of processes involving adsorption and inter-phase transport. Key conclusions drawn from this dissertation show that 1) variance of reservoir properties and flow responses generally decrease with scale; 2) scaling of recovery processes can be described by the scaling of effective mass transfer coefficient (Keff); in particular, mean and variance of Keff decrease with length scale, similar in the fashion of recovery statistics (e.g., variances in tracer breakthrough time and recovery); 3) the scaling of Keff depends on the underlying heterogeneity and is influenced by the dominant transport mechanisms. To show the versatility of the approach for studying scale-up of other transport mechanisms, it is also applied to derive scaled up formulations of non-Newtonian polymer flow to investigate the scaling characteristics of the apparent viscosity and effective shear rate in porous media. / text

Energy consumption is increasingly affecting battery life and cooling for real- time systems. Dynamic Voltage and frequency Scaling (DVS) has been shown to substantially reduce the energy consumption of uniprocessor real-time systems. It is worthwhile to extend the efficient DVS scheduling algorithms to distributed system with dependent tasks. The dissertation describes how to extend several effective uniprocessor DVS schedul- ing algorithms to distributed system with dependent task set. Task assignment and deadline assignment heuristics are proposed and compared with existing heuristics concerning energy-conserving performance. An admission test and a deadline com- putation algorithm are presented in the dissertation for dynamic task set to accept the arriving task in a DVS scheduled real-time system. Simulations show that an effective distributed DVS scheduling is capable of saving as much as 89% of energy that would be consumed without using DVS scheduling. It is also shown that task assignment and deadline assignment affect the energy- conserving performance of DVS scheduling algorithms. For some aggressive DVS scheduling algorithms, however, the effect of task assignment is negligible. The ad- mission test accept over 80% of tasks that can be accepted by a non-DVS scheduler to a DVS scheduled real-time system.

This dissertation proves the feasibility of accurate runtime prediction of processor performance under frequency scaling. The performance predictors developed in this dissertation allow processors capable of dynamic voltage and frequency scaling (DVFS) to improve their performance or energy efficiency by dynamically adapting chip or core voltages and frequencies to workload characteristics. The dissertation considers three processor configurations: the uniprocessor capable of chip-level DVFS, the private cache chip multiprocessor capable of per-core DVFS, and the shared cache chip multiprocessor capable of per-core DVFS. Depending on processor configuration, the presented performance predictors help the processor realize 72–85% of average oracle performance or energy efficiency gains. / text

Whether the stated goal of a program is to improve health, reduce crime, or to increase standard of living, the ultimate goal of social programs is to improve overall quality of life. An adequate measure of this outcome would help determine whether achievement of these more specific goals (e.g., health, education) really leads to improvements in overall life quality, and would allow trade-offs to be made in terms of funding across programs. However, an understanding of the determinants of life quality (i.e., the mechanism by which a program did or did not have its intended effect) is also essential to program evaluation and the design of future programs.This study constitutes the analysis of an existing dataset of individual traits, life circumstances, satisfaction with a list of 30 life domains, and overall quality of life for 193 healthy elders to test a hypothesized model of the determinants of life quality. As expected, domain satisfaction appears to be a function of life circumstances. Individuals' traits (e.g., age, sex, personality) modify this relationship, but neither they, nor respondents' reports of domain importance, appear to have any direct effect on quality of life. Instead, domain satisfactions alone are the most proximal determinants of overall quality of life. It also appears that individuals respond differently in terms of overall quality of life to reductions in satisfaction with certain domains than to increases. These findings should be evaluated further as they could affect the design of future successful programs. Because individuals' traits and individuals' ratings of domain importance seem to have no effect on the relationship between domain satisfaction and overall quality of life, it may not be essential to measure these in future studies. Finally, although the data on life domains available to this study were sufficient to generate these results, the first step in the development of adequate measures of overall quality of life and of domain satisfactions will be the construction of a comprehensive, fully-representative list of the life domains that comprise life as a whole.

No description available.