Ice-atmosphere interactions and sea ice predictability at multiple resolutions in the Community Earth System Model

Thesis (Master's)--University of Washington, 2016-06

Teaching College Writing in a High School Setting: The Impact of Concurrent Enrollment on Teacher Learning and Practice

Thesis (Ph.D.)--University of Washington, 2016-06

Structural Insights into Viral Membrane Fusion Machinery via Cryo-Electron Tomography: Influenza Virus and Human Parainfluenza Virus

Thesis (Ph.D.)--University of Washington, 2016-06

Simulation of the cake formation and growth in cake filtration

A computer model was developed to simulate the cake formation and growth in cake filtration at an individual particle level. The model was shown to be able to generate structural information and quantify the cake thickness, average cake solidosity, filtrate volume, filtrate flowrate for constant pressure filtration or pressure drop across the filter unit for constant rate filtration as a function of filtration time. The effects of particle size distribution and key operational variables such as initial filtration flowrate, maximum pressure drop and initial solidosity were examined based on the simulated results. They are qualitatively comparable to those observed in physical experiments. The need for further development in simulation was also discussed. (c) 2006 Elsevier Ltd. All rights reserved.

Relations between social support, appraisal and coping and both positive and negative outcomes for children of a parent with multiple sclerosis and comparisons with children of healthy parents

Objective: To examine adjustment in children of a parent with multiple sclerosis within a stress and coping framework and compare them with those who have 'healthy' parents. Subjects: A total of 193 participants between 10 and 25 years completed questionnaires; 48 youngsters who had a parent with multiple sclerosis and 145 youngsters who reported that they did not have a parent with an illness or disability. Method: A questionnaire survey methodology was used. Variable sets included caregiving context (e.g. additional parental illness, family responsibilities, parental functional impairment, choice in helping), social support (network size, satisfaction), stress appraisal, coping (problem solving, seeking support, acceptance, wishful thinking, denial), and positive (life satisfaction, positive affect, benefits) and negative (distress, health) adjustment outcomes. Results: Caregiving context variables significantly correlated with poorer adjustment in children of a parent with multiple sclerosis included additional parental illness, higher family responsibilities, parental functional impairment and unpredictability of the parent's multiple sclerosis, and less choice in helping. As predicted, better adjustment in children of a parent with multiple sclerosis was related to higher levels of social support, lower stress appraisals, greater reliance on approach coping strategies (problem solving, seeking support and acceptance) and less reliance on avoidant coping (wishful thinking and denial). Compared with children of 'healthy' parents, children of a parent with multiple sclerosis reported greater family responsibilities, less reliance on problem solving and seeking social support coping, higher somatization and lower life satisfaction and positive affect. Conclusions: Findings delineate the key impacts of young caregiving and support a stress and coping model of adjustment in children of a parent with multiple sclerosis.

A bang-bang PLL employing dynamic gain control for low jitter and fast lock times

Bang-bang phase detector based PLLs are simple to design, suffer no systematic phase error, and can run at the highest speed a process can make a working flip-flop. For these reasons designers are employing them in the design of very high speed Clock Data Recovery (CDR) architectures. The major drawback of this class of PLL is the inherent jitter due to quantized phase and frequency corrections. Reducing loop gain can proportionally improve jitter performance, but also reduces locking time and pull-in range. This paper presents a novel PLL design that dynamically scales its gain in order to achieve fast lock times while improving fitter performance in lock. Under certain circumstances the design also demonstrates improved capture range. This paper also analyses the behaviour of a bang-bang type PLL when far from lock, and demonstrates that the pull-in range is proportional to the square root of the PLL loop gain.

Trait physiology and crop modelling to link phenotypic complexity to underlying genetic systems

New tools derived from advances in molecular biology have not been widely adopted in plant breeding because of the inability to connect information at gene level to the phenotype in a manner that is useful for selection. We explore whether a crop growth and development modelling framework can link phenotype complexity to underlying genetic systems in a way that strengthens molecular breeding strategies. We use gene-to-phenotype simulation studies on sorghum to consider the value to marker-assisted selection of intrinsically stable QTLs that might be generated by physiological dissection of complex traits. The consequences on grain yield of genetic variation in four key adaptive traits – phenology, osmotic adjustment, transpiration efficiency, and staygreen – were simulated for a diverse set of environments by placing the known extent of genetic variation in the context of the physiological determinants framework of a crop growth and development model. It was assumed that the three to five genes associated with each trait, had two alleles per locus acting in an additive manner. The effects on average simulated yield, generated by differing combinations of positive alleles for the traits incorporated, varied with environment type. The full matrix of simulated phenotypes, which consisted of 547 location-season combinations and 4235 genotypic expression states, was analysed for genetic and environmental effects. The analysis was conducted in stages with gradually increased understanding of gene-to-phenotype relationships, which would arise from physiological dissection and modelling. It was found that environmental characterisation and physiological knowledge helped to explain and unravel gene and environment context dependencies. We simulated a marker-assisted selection (MAS) breeding strategy based on the analyses of gene effects. When marker scores were allocated based on the contribution of gene effects to yield in a single environment, there was a wide divergence in rate of yield gain over all environments with breeding cycle depending on the environment chosen for the QTL analysis. It was suggested that knowledge resulting from trait physiology and modelling would overcome this dependency by identifying stable QTLs. The improved predictive power would increase the utility of the QTLs in MAS. Developing and implementing this gene-to-phenotype capability in crop improvement requires enhanced attention to phenotyping, ecophysiological modelling, and validation studies to test the stability of candidate QTLs.

The role of migration in urban transition : studies of the relationship between migration and modernisation for Brisbane and Stockholm

Wilbur Zelinsky formulated a Hypothesis of Mobility Transition in 1971,in which he tried to relate all aspects of mobility to the Demographic Transition and modernisation. This dissertation applies the theoretical framework, proposed by Zelinsky and extended to encompass a family of transitions, to understand migration patterns of city regions. The two city regions, Brisbane and Stockholm, are selected as case studies, representing important city regions of similar size, but drawn from contrasting historical settings. A comparison of the case studies with the theoretical framework aims to determine how the relative contributions of net migration, the source areas of migrants, and the migration intensity change with modernisation. In addition, the research also aims to identify aspects of modernisation affecting migration. These aspects of migration are analysed with a "historical approach" and a "multivariate approach". An extensive investigation into the city regions' historical background provides the source, from which evidence for a relationship between migration and modernisation is extracted. With this historical approach, similarities and differences in migration patterns are identified. The other research approach analyse multivariate data, from the last two decades, on migration flows and modernisation. Correlations between migration and key aspects of modernisation are tested with multivariate regression, based on an alternative version of a spatial interaction model. The project demonstrates that the changing functions of cities and the structural modernisation are influential on migration. Similar patterns are found, regarding the relative contributions of net migration and natural increase to population growth. The research finds links between these changes in the relative contribution of net migration and demographic modernisation. The findings on variations in urban and rural source areas of migrants to city regions do not contradict the expected pattern, but data limitations prevent definite conclusion to be drawn. The assessment of variations in migration intensity resulted in the expected pattern not being supported. Based on Swedish data, the hypothesised increase in migration intensity is rejected. Interactional migration data also show patterns different from those derived from the theoretical framework. The findings, from both research approaches, suggested that structural modernisation affected migration flows more than demographic modernisation. The findings lead to a formulation of hypothesised patterns for migration to city regions. The study provides an important research contribution by applying the two research approaches to city regions. It also combines the study of internal and international migration to address the research objectives within a framework of transitional change.

Simulation based knowledge elicitation:effect of visual representation and model parameters

Since much knowledge is tacit, eliciting knowledge is a common bottleneck during the development of knowledge-based systems. Visual interactive simulation (VIS) has been proposed as a means for eliciting experts’ decision-making by getting them to interact with a visual simulation of the real system in which they work. In order to explore the effectiveness and efficiency of VIS based knowledge elicitation, an experiment has been carried out with decision-makers in a Ford Motor Company engine assembly plant. The model properties under investigation were the level of visual representation (2-dimensional, 2½-dimensional and 3-dimensional) and the model parameter settings (unadjusted and adjusted to represent more uncommon and extreme situations). The conclusion from the experiment is that using a 2-dimensional representation with adjusted parameter settings provides the better simulation-based means for eliciting knowledge, at least for the case modelled.

Development of a risk-oriented strategic sourcing (ROSS) framework for the construction and electronics manufacturing industries

Strategic sourcing has increased in importance in recent years, and now plays an important role in companies’ planning. The current volatility in supply markets means companies face multiple challenges involving lock-in situations, supplier bankruptcies or supply security issues. In addition, their exposure can increase due to natural disasters, as witnessed recently in the form of bird flu, volcanic ash and tsunamis. Therefore, the primary focus of this study is risk management in the context of strategic sourcing. The study presents a literature review on sourcing based on the 15 years from 1998–2012, and considers 131 academic articles. The literature describes strategic sourcing as a strategic, holistic process in managing supplier relationships, with a long-term focus on adding value to the company and realising competitive advantage. Few studies discovered the real risk impact and status of risk management in strategic sourcing, and evaluation across countries and industries was limited, with the construction sector particularly under-researched. This methodology is founded on a qualitative study of twenty cases across Ger-many and the United Kingdom from the construction sector and electronics manufacturing industries. While considering risk management in the context of strategic sourcing, the thesis takes into account six dimensions that cover trends in strategic sourcing, theoretical and practical sourcing models, risk management, supply and demand management, critical success factors and the strategic supplier evaluation. The study contributes in several ways. First, recent trends are traced and future needs identified across the research dimensions of countries, industries and companies. Second, it evaluates critical success factors in contemporary strategic sourcing. Third, it explores the application of theoretical and practical sourcing models in terms of effectiveness and sustainability. Fourth, based on the case study findings, a risk-oriented strategic sourcing framework and a model for strategic sourcing are developed. These are based on the validation of contemporary requirements and a critical evaluation of the existing situation. It contemplates the empirical findings and leads to a structured process to manage risk in strategic sourcing. The risk-oriented framework considers areas such as trends, corporate and sourcing strategy, critical success factors, strategic supplier selection criteria, risk assessment, reporting, strategy alignment and reporting. The proposed model highlights the essential dimensions in strategic sourcing and guides us to a new definition of strategic sourcing supported by this empirical study.

Breakage model development and application with CFD for predicting breakage of whey protein precipitate particles

Particle breakage due to fluid flow through various geometries can have a major influence on the performance of particle/fluid processes and on the product quality characteristics of particle/fluid products. In this study, whey protein precipitate dispersions were used as a case study to investigate the effect of flow intensity and exposure time on the breakage of these precipitate particles. Computational fluid dynamic (CFD) simulations were performed to evaluate the turbulent eddy dissipation rate (TED) and associated exposure time along various flow geometries. The focus of this work is on the predictive modelling of particle breakage in particle/fluid systems. A number of breakage models were developed to relate TED and exposure time to particle breakage. The suitability of these breakage models was evaluated for their ability to predict the experimentally determined breakage of the whey protein precipitate particles. A "power-law threshold" breakage model was found to provide a satisfactory capability for predicting the breakage of the whey protein precipitate particles. The whey protein precipitate dispersions were propelled through a number of different geometries such as bends, tees and elbows, and the model accurately predicted the mean particle size attained after flow through these geometries. © 2005 Elsevier Ltd. All rights reserved.

Knowledge assisted data management and retrieval in multimedia database systems

With the proliferation of multimedia data and ever-growing requests for multimedia applications, there is an increasing need for efficient and effective indexing, storage and retrieval of multimedia data, such as graphics, images, animation, video, audio and text. Due to the special characteristics of the multimedia data, the Multimedia Database management Systems (MMDBMSs) have emerged and attracted great research attention in recent years. Though much research effort has been devoted to this area, it is still far from maturity and there exist many open issues. In this dissertation, with the focus of addressing three of the essential challenges in developing the MMDBMS, namely, semantic gap, perception subjectivity and data organization, a systematic and integrated framework is proposed with video database and image database serving as the testbed. In particular, the framework addresses these challenges separately yet coherently from three main aspects of a MMDBMS: multimedia data representation, indexing and retrieval. In terms of multimedia data representation, the key to address the semantic gap issue is to intelligently and automatically model the mid-level representation and/or semi-semantic descriptors besides the extraction of the low-level media features. The data organization challenge is mainly addressed by the aspect of media indexing where various levels of indexing are required to support the diverse query requirements. In particular, the focus of this study is to facilitate the high-level video indexing by proposing a multimodal event mining framework associated with temporal knowledge discovery approaches. With respect to the perception subjectivity issue, advanced techniques are proposed to support users' interaction and to effectively model users' perception from the feedback at both the image-level and object-level.

Actionable pattern analysis in computing and business intelligence systems

With advances in science and technology, computing and business intelligence (BI) systems are steadily becoming more complex with an increasing variety of heterogeneous software and hardware components. They are thus becoming progressively more difficult to monitor, manage and maintain. Traditional approaches to system management have largely relied on domain experts through a knowledge acquisition process that translates domain knowledge into operating rules and policies. It is widely acknowledged as a cumbersome, labor intensive, and error prone process, besides being difficult to keep up with the rapidly changing environments. In addition, many traditional business systems deliver primarily pre-defined historic metrics for a long-term strategic or mid-term tactical analysis, and lack the necessary flexibility to support evolving metrics or data collection for real-time operational analysis. There is thus a pressing need for automatic and efficient approaches to monitor and manage complex computing and BI systems. To realize the goal of autonomic management and enable self-management capabilities, we propose to mine system historical log data generated by computing and BI systems, and automatically extract actionable patterns from this data. This dissertation focuses on the development of different data mining techniques to extract actionable patterns from various types of log data in computing and BI systems. Four key problems—Log data categorization and event summarization, Leading indicator identification , Pattern prioritization by exploring the link structures , and Tensor model for three-way log data are studied. Case studies and comprehensive experiments on real application scenarios and datasets are conducted to show the effectiveness of our proposed approaches.

A generic model of execution for synthesizing domain-specific models

Software engineering researchers are challenged to provide increasingly more powerful levels of abstractions to address the rising complexity inherent in software solutions. One new development paradigm that places models as abstraction at the forefront of the development process is Model-Driven Software Development (MDSD). MDSD considers models as first class artifacts, extending the capability for engineers to use concepts from the problem domain of discourse to specify apropos solutions. A key component in MDSD is domain-specific modeling languages (DSMLs) which are languages with focused expressiveness, targeting a specific taxonomy of problems. The de facto approach used is to first transform DSML models to an intermediate artifact in a HLL e.g., Java or C++, then execute that resulting code.^ Our research group has developed a class of DSMLs, referred to as interpreted DSMLs (i-DSMLs), where models are directly interpreted by a specialized execution engine with semantics based on model changes at runtime. This execution engine uses a layered architecture and is referred to as a domain-specific virtual machine (DSVM). As the domain-specific model being executed descends the layers of the DSVM the semantic gap between the user-defined model and the services being provided by the underlying infrastructure is closed. The focus of this research is the synthesis engine, the layer in the DSVM which transforms i-DSML models into executable scripts for the next lower layer to process.^ The appeal of an i-DSML is constrained as it possesses unique semantics contained within the DSVM. Existing DSVMs for i-DSMLs exhibit tight coupling between the implicit model of execution and the semantics of the domain, making it difficult to develop DSVMs for new i-DSMLs without a significant investment in resources.^ At the onset of this research only one i-DSML had been created for the user- centric communication domain using the aforementioned approach. This i-DSML is the Communication Modeling Language (CML) and its DSVM is the Communication Virtual machine (CVM). A major problem with the CVM's synthesis engine is that the domain-specific knowledge (DSK) and the model of execution (MoE) are tightly interwoven consequently subsequent DSVMs would need to be developed from inception with no reuse of expertise.^ This dissertation investigates how to decouple the DSK from the MoE and subsequently producing a generic model of execution (GMoE) from the remaining application logic. This GMoE can be reused to instantiate synthesis engines for DSVMs in other domains. The generalized approach to developing the model synthesis component of i-DSML interpreters utilizes a reusable framework loosely coupled to DSK as swappable framework extensions.^ This approach involves first creating an i-DSML and its DSVM for a second do- main, demand-side smartgrid, or microgrid energy management, and designing the synthesis engine so that the DSK and MoE are easily decoupled. To validate the utility of the approach, the SEs are instantiated using the GMoE and DSKs of the two aforementioned domains and an empirical study to support our claim of reduced developmental effort is performed.^

Hide, survive and hitch a ride, the dispersal of Antarctic krill into the nursery habitats

Antarctic krill (Euphausia superba), a key species of Southern Ocean food webs plays a central role in ecosystem processes, community dynamics of apex predators and as a commercial fishery target. A decline in krill abundance during the late 20th century in the SW Atlantic sector has been linked to a concomitant decrease in sea ice, based on the hypothesis that sea ice acts as a feeding ground for overwintering larvae. However, evidence supporting this hypothesis has been scarce due to logistical challenges of collecting data in austral winter. Here we report on a winter study that involved diver observations of larval krill in their under-ice environment, ship-based studies of krill, sea ice physical characteristics, and biophysical model analyses of krill-ocean-ice interactions. We present evidence that complex under-ice topography is vital for larval krill in terms of dispersal and advection into high productive nursery habitats, rather than the provision by the ice environment of food. Further, ongoing changes in sea ice will lead to increases in sea-ice regimes favourable for overwintering larval krill but shifting southwards. This will result in ice-free conditions in the SW Atlantic, which will be conducive for enhancing food supplies due to sufficient light and iron availability, thus enhancing larvae development and growth. However, the associated impact on dispersal and advection may lead to a net shift in krill from the SW Atlantic to regions further east by the eastward flowing ACC and the northern branch of the Weddell Gyre, with profound consequences for the Southern Ocean pelagic ecosystem.