Dynamic Models under Uncertainty for Large-Scale Enterprise Systems

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

Dynamic occupational therapy cognitive assessment for children: Perceived utility in Australian occupational therapy practice

Background and Aim: The Dynamic Occupational Therapy Cognitive Assessment for Children (DOTCA-Ch), recently developed in Israel, assesses the cognitive areas: orientation, spatial perception, praxis, visuomotor construction and thinking operations of 6- to 12-year-old children. The dynamic aspect, which incorporates mediation and prompting, has been presented as a valuable clinical feature of this new assessment. This study investigated the cultural suitability, dynamic nature and comprehensiveness of the DOTCA-Ch as a single cognitive assessment for occupational therapy practice in Australia. Methods: Twenty-three paediatric occupational therapists participated in three tutorial and video demonstrations, which were then followed by a group interview. Results and Conclusion: Thematic analysis of transcripts identified four main themes: appropriateness of assessment tasks, language, mediation and clinical utility. Within each theme, the participants raised both positive and negative features. This paper highlights occupational therapists' mixed views on the clinical utility of this assessment in Australia. Limitations of this study and areas for further research are suggested

An adaptive and dynamic dimensionality reduction method for high-dimensional indexing

The notorious "dimensionality curse" is a well-known phenomenon for any multi-dimensional indexes attempting to scale up to high dimensions. One well-known approach to overcome degradation in performance with respect to increasing dimensions is to reduce the dimensionality of the original dataset before constructing the index. However, identifying the correlation among the dimensions and effectively reducing them are challenging tasks. In this paper, we present an adaptive Multi-level Mahalanobis-based Dimensionality Reduction (MMDR) technique for high-dimensional indexing. Our MMDR technique has four notable features compared to existing methods. First, it discovers elliptical clusters for more effective dimensionality reduction by using only the low-dimensional subspaces. Second, data points in the different axis systems are indexed using a single B+-tree. Third, our technique is highly scalable in terms of data size and dimension. Finally, it is also dynamic and adaptive to insertions. An extensive performance study was conducted using both real and synthetic datasets, and the results show that our technique not only achieves higher precision, but also enables queries to be processed efficiently. Copyright Springer-Verlag 2005

Fast stereo matching by iterated dynamic programming and quadtree subregioning

The application of energy minimisation methods for stereo matching has been demonstrated to produce high quality disparity maps. However the majority of these methods are known to be computationally expensive, requiring minutes or even hours of computation. We propose a fast minimisation scheme that produces strongly competitive results for significantly reduced computation, requiring only a few seconds of computation. In this paper, we present our iterated dynamic programming algorithm along with a quadtree subregioning process for fast stereo matching.

Modeling and exploiting behavior patterns in dynamic environments

This paper presents a new approach to improving the effectiveness of autonomous systems that deal with dynamic environments. The basis of the approach is to find repeating patterns of behavior in the dynamic elements of the system, and then to use predictions of the repeating elements to better plan goal directed behavior. It is a layered approach involving classifying, modeling, predicting and exploiting. Classifying involves using observations to place the moving elements into previously defined classes. Modeling involves recording features of the behavior on a coarse grained grid. Exploitation is achieved by integrating predictions from the model into the behavior selection module to improve the utility of the robot's actions. This is in contrast to typical approaches that use the model to select between different strategies or plays. Three methods of adaptation to the dynamic features of the environment are explored. The effectiveness of each method is determined using statistical tests over a number of repeated experiments. The work is presented in the context of predicting opponent behavior in the highly dynamic and multi-agent robot soccer domain (RoboCup)

Methods for conflict resolution in policy-based management systems

While developments in distributed object computing environments, such as the Common Object Request Broker Architecture (CORBA) [17] and the Telecommunication Intelligent Network Architecture (TINA) [16], have enabled interoperability between domains in large open distributed systems, managing the resources within such systems has become an increasingly complex task. This challenge has been considered for several years within the distributed systems management research community and policy-based management has recently emerged as a promising solution. Large evolving enterprises present a significant challenge for policy-based management partly due to the requirement to support both mutual transparency and individual autonomy between domains [2], but also because the fluidity and complexity of interactions occurring within such environments requires an ability to cope with the coexistence of multiple, potentially inconsistent policies. This paper discusses the need of providing both dynamic (run-time) and static (compile-time) conflict detection and resolution for policies in such systems and builds on our earlier conflict detection work [7, 8] to introduce the methods for conflict resolution in large open distributed systems.

Tear film lipids:dynamic composition and clinical performance

Purpose: Meibomian-derived lipid secretions are well characterised but their subsequent fate in the ocular environment is less well understood. Phospholipids are thought to facilitate the interface between aqueous and lipid layers of the tear film and to be involved in ocular lubrication processes. We have extended our previous studies on phospholipid levels in the tear film to encompass the fate of polar and non-polar lipids in progressive accumulation and aging processes on both conventional and silicone-modified hydrogel lenses. This is an important aspect of the developing understanding of the role of lipids in the clinical performance of silicone hydrogels. Method: Several techniques were used to identify lipids in the tear film. Mass-spectrometric methods included Agilent 1100-based liquid chromatography coupled to mass spectrometry (LCMS) and Perkin Elmer gas chromatography mass spectrometry (GCMS). Thin layer chromatography (TLC) was used for separation of lipids on the basis of increasing solvent polarity. Routine assay of lipid extractions from patient-worn lenses was carried out using a Hewlett Packard 1090 liquid chromatograph coupled to both uv and Agilent 1100 fluorescence detection. A range of histological together with optical, and electron microscope techniques was used in deposit analysis. Results: Progressive lipid uptake was assessed in various ways, including: composition changes with wear time, differential lipid penetrate into the lens matrix and, particularly, the extent to which lipids become unextractable as a function of wear time. Solvent-based separation and HPLC gave consistent results indicating that the polarity of lipid classes decreased as follows: phospholipids/fatty acids > triglycerides > cholesterol/cholesteryl esters. Tear lipids were found to show autofluorescence—which underpinned the value of fluorescence microscopy and fluorescence detection coupled with HPLC separation. The most fluorescent lipids were found to be cholesteryl esters; histological techniques coupled with fluorescence microscopy indicated that white spots (’’jelly bumps’’) formed on silicone hydrogel lenses contain a high proportion of cholesteryl esters. Lipid profiles averaged for 30 symptomatic and 30 asymptomatic contact lens wearers were compiled. Peak classes were split into: cholesterol (C), cholesteryl esters (CE), glycerides (G), polar fatty acids/phospholipids (PL). The lipid ratio for ymptomatic/symptomatic was 0.6 ± 0.1 for all classes except one—the cholesterol ratio was 0.2 ± 0.05. Significantly the PL ratio was no different from that of any other class except cholesterol. Chromatography indicated that: lipid polarity decreased with depth of penetration and that lipid extractability decreased with wear time. Conclusions: Meibomian lipid composition differs from that in the tear film and on worn lenses. Although the same broad lipid classes were obtained by extraction from all lenses and all patients studied, quantities vary with wear and material. Lipid extractability diminishes with wear time regardless of the use of cleaning regimes. Dry eye symptoms in contact lens wear are frequently linked to lipid layer behaviour but seem to relate more to total lipid than to specific composition. Understanding the detail of lipid related processes is an important element of improving the clinical performance of materials and care solutions.

Mathematical methods in power system stability studies

In this thesis various mathematical methods of studying the transient and dynamic stabiIity of practical power systems are presented. Certain long established methods are reviewed and refinements of some proposed. New methods are presented which remove some of the difficulties encountered in applying the powerful stability theories based on the concepts of Liapunov. Chapter 1 is concerned with numerical solution of the transient stability problem. Following a review and comparison of synchronous machine models the superiority of a particular model from the point of view of combined computing time and accuracy is demonstrated. A digital computer program incorporating all the synchronous machine models discussed, and an induction machine model, is described and results of a practical multi-machine transient stability study are presented. Chapter 2 reviews certain concepts and theorems due to Liapunov. In Chapter 3 transient stability regions of single, two and multi~machine systems are investigated through the use of energy type Liapunov functions. The treatment removes several mathematical difficulties encountered in earlier applications of the method. In Chapter 4 a simple criterion for the steady state stability of a multi-machine system is developed and compared with established criteria and a state space approach. In Chapters 5, 6 and 7 dynamic stability and small signal dynamic response are studied through a state space representation of the system. In Chapter 5 the state space equations are derived for single machine systems. An example is provided in which the dynamic stability limit curves are plotted for various synchronous machine representations. In Chapter 6 the state space approach is extended to multi~machine systems. To draw conclusions concerning dynamic stability or dynamic response the system eigenvalues must be properly interpreted, and a discussion concerning correct interpretation is included. Chapter 7 presents a discussion of the optimisation of power system small sjgnal performance through the use of Liapunov functions.

Measuring the dynamic mechanical response of hydrated mouse bone by nanoindentation

This study demonstrates a novel approach to characterizing hydrated bone's viscoelastic behavior at lamellar length scales using dynamic indentation techniques. We studied the submicron-level viscoelastic response of bone tissue from two different inbred mouse strains, A/J and B6, with known differences in whole bone and tissue-level mechanical properties. Our results show that bone having a higher collagen content or a lower mineral-to-matrix ratio demonstrates a trend towards a larger viscoelastic response. When normalized for anatomical location relative to biological growth patterns in the antero-medial (AM) cortex, bone tissue from B6 femora, known to have a lower mineral-to-matrix ratio, is shown to exhibit a significantly higher viscoelastic response compared to A/J tissue. Newer bone regions with a higher collagen content (closer to the endosteal edge of the AM cortex) showed a trend towards a larger viscoelastic response. Our study demonstrates the feasibility of this technique for analyzing local composition-property relationships in bone. Further, this technique of viscoelastic nanoindentation mapping of the bone surface at these submicron length scales is shown to be highly advantageous in studying subsurface features, such as porosity, of wet hydrated biological specimens, which are difficult to identify using other methods. © 2010 Elsevier Ltd.

Neural network enhanced self tuning adaptive control application for non-linear control of dynamic systems

The main theme of research of this project concerns the study of neutral networks to control uncertain and non-linear control systems. This involves the control of continuous time, discrete time, hybrid and stochastic systems with input, state or output constraints by ensuring good performances. A great part of this project is devoted to the opening of frontiers between several mathematical and engineering approaches in order to tackle complex but very common non-linear control problems. The objectives are: 1. Design and develop procedures for neutral network enhanced self-tuning adaptive non-linear control systems; 2. To design, as a general procedure, neural network generalised minimum variance self-tuning controller for non-linear dynamic plants (Integration of neural network mapping with generalised minimum variance self-tuning controller strategies); 3. To develop a software package to evaluate control system performances using Matlab, Simulink and Neural Network toolbox. An adaptive control algorithm utilising a recurrent network as a model of a partial unknown non-linear plant with unmeasurable state is proposed. Appropriately, it appears that structured recurrent neural networks can provide conveniently parameterised dynamic models for many non-linear systems for use in adaptive control. Properties of static neural networks, which enabled successful design of stable adaptive control in the state feedback case, are also identified. A survey of the existing results is presented which puts them in a systematic framework showing their relation to classical self-tuning adaptive control application of neural control to a SISO/MIMO control. Simulation results demonstrate that the self-tuning design methods may be practically applicable to a reasonably large class of unknown linear and non-linear dynamic control systems.

Temporal finite elements in the dynamic analysis of structures

This thesis demonstrates that the use of finite elements need not be confined to space alone, but that they may also be used in the time domain, It is shown that finite element methods may be used successfully to obtain the response of systems to applied forces, including, for example, the accelerations in a tall structure subjected to an earthquake shock. It is further demonstrated that at least one of these methods may be considered to be a practical alternative to more usual methods of solution. A detailed investigation of the accuracy and stability of finite element solutions is included, and methods of applications to both single- and multi-degree of freedom systems are described. Solutions using two different temporal finite elements are compared with those obtained by conventional methods, and a comparison of computation times for the different methods is given. The application of finite element methods to distributed systems is described, using both separate discretizations in space and time, and a combined space-time discretization. The inclusion of both viscous and hysteretic damping is shown to add little to the difficulty of the solution. Temporal finite elements are also seen to be of considerable interest when applied to non-linear systems, both when the system parameters are time-dependent and also when they are functions of displacement. Solutions are given for many different examples, and the computer programs used for the finite element methods are included in an Appendix.

A dynamic model for the activated sludge treatment of coke oven effluents

This is an Inter-Disciplinary Higher Degree (IHD) thesis about Water Pollution Control in the Iron and Steel Industry. After examining the compositions, and various treatment methods, for the major effluent streams from a typical Integrated Iron and Steel works, it was decided to concentrate investigative work on the activated-sludge treatment of coke-oven effluents. A mathematical model of this process was developed in an attempt to provide a tool for plant management that would enable improved performance, and enhanced control of Works Units. The model differs from conventional models in that allowance is made for the presence of two genera of microorganisms, each of which utilises a particular type of substrate as its energy source. Allowance is also made for the inhibitive effect of phenol on thiocyanate biodegradation, and for the self-toxicity of the bacteria when present in a high substrate concentration environment. The enumeration of the kinetic characteristics of the two groups of micro-organisms was shown to be of major importance. Laboratory experiments were instigated in an attempt to determine accurate values of these coefficients. The use of the Suspended Solids concentration was found to be too insensitive a measure of viable active mass. Other measures were investigated, and Adenosine Triphosphate concentration was chosen as the most effective measure of bacterial populations. Using this measure, a model was developed for phenol biodegradation from experimental results which implicated the possibility of storage of substate prior to metabolism. A model for thiocyanate biodegradation was also developed, although the experimental results indicate that much work is still required in this area.

Approximate, Average, Dynamic Models of Uncontrolled Rectifiers for Aircraft Applications

To carry out stability and voltage regulation studies on more electric aircraft systems in which there is a preponderance of multi-pulse, rectifier-fed motor-drive equipment, average dynamic models of the rectifier converters are required. Existing methods are difficult to apply to anything other than single converters with a low pulse number. Therefore an efficient, compact method for deriving the approximate, linear, average model of 6- and 12-pulse rectifiers, based on the assumption of a small duration of the overlap angle is presented. The models are validated against detailed simulations and laboratory prototypes.