Adaptive Crowd Algorithms for Open-Ended Problems

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

Euphorbia tirucalli L.–Comprehensive Characterization of a Drought Tolerant Plant with a Potential as Biofuel Source

Of late, decrease in mineral oil supplies has stimulated research on use of biomass as an alternative energy source. Climate change has brought problems such as increased drought and erratic rains. This, together with a rise in land degeneration problems with concomitant loss in soil fertility has inspired the scientific world to look for alternative bio-energy species. Euphorbia tirucalli L., a tree with C3/CAM metabolism in leaves/stem, can be cultivated on marginal, arid land and could be a good alternative source of biofuel. We analyzed a broad variety of E. tirucalli plants collected from different countries for their genetic diversity using AFLP. Physiological responses to induced drought stress were determined in a number of genotypes by monitoring growth parameters and influence on photosynthesis. For future breeding of economically interesting genotypes, rubber content and biogas production were quantified. Cluster analysis shows that the studied genotypes are divided into two groups, African and mostly non-African genotypes. Different genotypes respond significantly different to various levels of water. Malate measurement indicates that there is induction of CAM in leaves following drought stress. Rubber content varies strongly between genotypes. An investigation of the biogas production capacities of six E. tirucalli genotypes reveals biogas yields higher than from rapeseed but lower than maize silage.

Database evolution on an orthogonal persistent programming system: A semi-transparent approach

In this paper the problem of the evolution of an object-oriented database in the context of orthogonal persistent programming systems is addressed. We have observed two characteristics in that type of systems that offer particular conditions to implement the evolution in a semi-transparent fashion. That transparency can further be enhanced with the obliviousness provided by the Aspect-Oriented Programming techniques. Was conceived a meta-model and developed a prototype to test the feasibility of our approach. The system allows programs, written to a schema, access semi-transparently to data in other versions of the schema.

Classification multi-échelle d'images à très haute résolution spatiale basée sur une nouvelle approche texturale

Résumé : Face à l’accroissement de la résolution spatiale des capteurs optiques satellitaires, de nouvelles stratégies doivent être développées pour classifier les images de télédétection. En effet, l’abondance de détails dans ces images diminue fortement l’efficacité des classifications spectrales; de nombreuses méthodes de classification texturale, notamment les approches statistiques, ne sont plus adaptées. À l’inverse, les approches structurelles offrent une ouverture intéressante : ces approches orientées objet consistent à étudier la structure de l’image pour en interpréter le sens. Un algorithme de ce type est proposé dans la première partie de cette thèse. Reposant sur la détection et l’analyse de points-clés (KPC : KeyPoint-based Classification), il offre une solution efficace au problème de la classification d’images à très haute résolution spatiale. Les classifications effectuées sur les données montrent en particulier sa capacité à différencier des textures visuellement similaires. Par ailleurs, il a été montré dans la littérature que la fusion évidentielle, reposant sur la théorie de Dempster-Shafer, est tout à fait adaptée aux images de télédétection en raison de son aptitude à intégrer des concepts tels que l’ambiguïté et l’incertitude. Peu d’études ont en revanche été menées sur l’application de cette théorie à des données texturales complexes telles que celles issues de classifications structurelles. La seconde partie de cette thèse vise à combler ce manque, en s’intéressant à la fusion de classifications KPC multi-échelle par la théorie de Dempster-Shafer. Les tests menés montrent que cette approche multi-échelle permet d’améliorer la classification finale dans le cas où l’image initiale est de faible qualité. De plus, l’étude effectuée met en évidence le potentiel d’amélioration apporté par l’estimation de la fiabilité des classifications intermédiaires, et fournit des pistes pour mener ces estimations.

Orientation de l’effort des tests unitaires dans les systèmes orientés objet : une approche basée sur les métriques logicielles

Les logiciels actuels sont de grandes tailles, complexes et critiques. Le besoin de qualité exige beaucoup de tests, ce qui consomme de grandes quantités de ressources durant le développement et la maintenance de ces systèmes. Différentes techniques permettent de réduire les coûts liés aux activités de test. Notre travail s’inscrit dans ce cadre, est a pour objectif d’orienter l’effort de test vers les composants logiciels les plus à risque à l’aide de certains attributs du code source. À travers plusieurs démarches empiriques menées sur de grands logiciels open source, développés avec la technologie orientée objet, nous avons identifié et étudié les métriques qui caractérisent l’effort de test unitaire sous certains angles. Nous avons aussi étudié les liens entre cet effort de test et les métriques des classes logicielles en incluant les indicateurs de qualité. Les indicateurs de qualité sont une métrique synthétique, que nous avons introduite dans nos travaux antérieurs, qui capture le flux de contrôle ainsi que différentes caractéristiques du logiciel. Nous avons exploré plusieurs techniques permettant d’orienter l’effort de test vers des composants à risque à partir de ces attributs de code source, en utilisant des algorithmes d’apprentissage automatique. En regroupant les métriques logicielles en familles, nous avons proposé une approche basée sur l’analyse du risque des classes logicielles. Les résultats que nous avons obtenus montrent les liens entre l’effort de test unitaire et les attributs de code source incluant les indicateurs de qualité, et suggèrent la possibilité d’orienter l’effort de test à l’aide des métriques.

Sharing the vision: representing the matters of concern for design-led fledgling companies in Scotland

Design is being performed on an ever-increasing spectrum of complex practices arising in response to emerging markets and technologies, co-design, digital interaction, service design and cultures of innovation. This emerging notion of design has led to an expansive array of collaborative and facilitation skills to demonstrate and share how such methods can shape innovation. The meaning of these design things in practice can't be taken for granted as matters of fact, which raises a key challenge for design to represent its role through the contradictory nature of matters of concern. This paper explores an innovative, object-oriented approach within the field of design research, visually combining an actor-network theory framework with situational analysis, to report on the role of design for fledgling companies in Scotland, established and funded through the knowledge exchange hub Design in Action (DiA). Key findings and visual maps are presented from reflective discussions with actors from a selection of the businesses within DiA's portfolio. The suggestion is that any notions of strategic value, of engendering meaningful change, of sharing the vision of design, through design things, should be grounded in the reflexive interpretations of matters of concern that emerge.

THE HEALTH OF YOUNG ADULTS WITH DISABILITIES IN THE UNITED STATES: THE COLLECTIVE ROLES OF RISK FACTORS IN SOCIAL ECOLOGIC FRAMEWORK

Background: Over the last few decades, the prevalence of young adults with disabilities (YAD) has steadily risen as a result of advances in medicine, clinical treatment, and biomedical technologythat enhanced their survival into adulthood. Despite investments in services, family supports, and insurance, they experience poor health status and barriers to successful transition into adulthood. Objectives: We investigated the collective roles of multi-faceted factors at intrapersonal, interpersonal and community levels within the social ecological framework on health related outcome including self-rated health (SRH) of YAD. The three specific aims are: 1) to examine sociodemographic differences and health insurance coverage in adolescence; 2) to investigate the role of social skills in relationships with family and peers developed in adolescence; and 3) to collectively explore the association of sociodemographic characteristics, social skills, and community participation in adolescence on SRH. Methods: Using longitudinal data (N=5,020) from the National Longitudinal Transition Study (NLTS2), we conducted multivariate logistic regression analyses to understand the association between insurance status as well as social skills in adolescence and YAD’s health related outcomes. Structural equation modeling (SEM) assessed the confluence of multi-faceted factors from the social ecological model that link to health in early adulthood. Results: Compared with YAD who had private insurance, YAD who had public health insurance in adolescence are at higher odds of experiencing poorer health related outcomes in self-rated health [adjusted odds ratio (aOR=2.89, 95% confidence interval (CI): 1.16, 7.23), problems with health (aOR=2.60, 95%CI: 1.26, 5.35), and missing social activities due to health problems (aOR=2.86, 95%CI: 1.39, 5.85). At the interpersonal level, overall social skills developed through relationship with family and peers in adolescence do not appear to have association with health related outcomes in early adulthood. Finally, at the community level, community participation in adolescence does not have an association with SRH in early adulthood. Conclusions: Having public health insurance coverage does not equate to good health. YAD need additional supports to achieve positive health outcomes. The findings in social skills and community participation suggest other potential factors may be at play for health related outcomes for YAD and the need for further investigation.

DIRECT NUMERICAL SIMULATION OF INCOMPRESSIBLE MULTIPHASE FLOW WITH PHASE CHANGE

Phase change problems arise in many practical applications such as air-conditioning and refrigeration, thermal energy storage systems and thermal management of electronic devices. The physical phenomenon in such applications are complex and are often difficult to be studied in detail with the help of only experimental techniques. The efforts to improve computational techniques for analyzing two-phase flow problems with phase change are therefore gaining momentum. The development of numerical methods for multiphase flow has been motivated generally by the need to account more accurately for (a) large topological changes such as phase breakup and merging, (b) sharp representation of the interface and its discontinuous properties and (c) accurate and mass conserving motion of the interface. In addition to these considerations, numerical simulation of multiphase flow with phase change introduces additional challenges related to discontinuities in the velocity and the temperature fields. Moreover, the velocity field is no longer divergence free. For phase change problems, the focus of developmental efforts has thus been on numerically attaining a proper conservation of energy across the interface in addition to the accurate treatment of fluxes of mass and momentum conservation as well as the associated interface advection. Among the initial efforts related to the simulation of bubble growth in film boiling applications the work in \cite{Welch1995} was based on the interface tracking method using a moving unstructured mesh. That study considered moderate interfacial deformations. A similar problem was subsequently studied using moving, boundary fitted grids \cite{Son1997}, again for regimes of relatively small topological changes. A hybrid interface tracking method with a moving interface grid overlapping a static Eulerian grid was developed \cite{Juric1998} for the computation of a range of phase change problems including, three-dimensional film boiling \cite{esmaeeli2004computations}, multimode two-dimensional pool boiling \cite{Esmaeeli2004} and film boiling on horizontal cylinders \cite{Esmaeeli2004a}. The handling of interface merging and pinch off however remains a challenge with methods that explicitly track the interface. As large topological changes are crucial for phase change problems, attention has turned in recent years to front capturing methods utilizing implicit interfaces that are more effective in treating complex interface deformations. The VOF (Volume of Fluid) method was adopted in \cite{Welch2000} to simulate the one-dimensional Stefan problem and the two-dimensional film boiling problem. The approach employed a specific model for mass transfer across the interface involving a mass source term within cells containing the interface. This VOF based approach was further coupled with the level set method in \cite{Son1998}, employing a smeared-out Heaviside function to avoid the numerical instability related to the source term. The coupled level set, volume of fluid method and the diffused interface approach was used for film boiling with water and R134a at the near critical pressure condition \cite{Tomar2005}. The effect of superheat and saturation pressure on the frequency of bubble formation were analyzed with this approach. The work in \cite{Gibou2007} used the ghost fluid and the level set methods for phase change simulations. A similar approach was adopted in \cite{Son2008} to study various boiling problems including three-dimensional film boiling on a horizontal cylinder, nucleate boiling in microcavity \cite{lee2010numerical} and flow boiling in a finned microchannel \cite{lee2012direct}. The work in \cite{tanguy2007level} also used the ghost fluid method and proposed an improved algorithm based on enforcing continuity and divergence-free condition for the extended velocity field. The work in \cite{sato2013sharp} employed a multiphase model based on volume fraction with interface sharpening scheme and derived a phase change model based on local interface area and mass flux. Among the front capturing methods, sharp interface methods have been found to be particularly effective both for implementing sharp jumps and for resolving the interfacial velocity field. However, sharp velocity jumps render the solution susceptible to erroneous oscillations in pressure and also lead to spurious interface velocities. To implement phase change, the work in \cite{Hardt2008} employed point mass source terms derived from a physical basis for the evaporating mass flux. To avoid numerical instability, the authors smeared the mass source by solving a pseudo time-step diffusion equation. This measure however led to mass conservation issues due to non-symmetric integration over the distributed mass source region. The problem of spurious pressure oscillations related to point mass sources was also investigated by \cite{Schlottke2008}. Although their method is based on the VOF, the large pressure peaks associated with sharp mass source was observed to be similar to that for the interface tracking method. Such spurious fluctuation in pressure are essentially undesirable because the effect is globally transmitted in incompressible flow. Hence, the pressure field formation due to phase change need to be implemented with greater accuracy than is reported in current literature. The accuracy of interface advection in the presence of interfacial mass flux (mass flux conservation) has been discussed in \cite{tanguy2007level,tanguy2014benchmarks}. The authors found that the method of extending one phase velocity to entire domain suggested by Nguyen et al. in \cite{nguyen2001boundary} suffers from a lack of mass flux conservation when the density difference is high. To improve the solution, the authors impose a divergence-free condition for the extended velocity field by solving a constant coefficient Poisson equation. The approach has shown good results with enclosed bubble or droplet but is not general for more complex flow and requires additional solution of the linear system of equations. In current thesis, an improved approach that addresses both the numerical oscillation of pressure and the spurious interface velocity field is presented by featuring (i) continuous velocity and density fields within a thin interfacial region and (ii) temporal velocity correction steps to avoid unphysical pressure source term. Also I propose a general (iii) mass flux projection correction for improved mass flux conservation. The pressure and the temperature gradient jump condition are treated sharply. A series of one-dimensional and two-dimensional problems are solved to verify the performance of the new algorithm. Two-dimensional and cylindrical film boiling problems are also demonstrated and show good qualitative agreement with the experimental observations and heat transfer correlations. Finally, a study on Taylor bubble flow with heat transfer and phase change in a small vertical tube in axisymmetric coordinates is carried out using the new multiphase, phase change method.

Exact Solution of Bayes and Minimax Change-Detection Problems

The challenge of detecting a change in the distribution of data is a sequential decision problem that is relevant to many engineering solutions, including quality control and machine and process monitoring. This dissertation develops techniques for exact solution of change-detection problems with discrete time and discrete observations. Change-detection problems are classified as Bayes or minimax based on the availability of information on the change-time distribution. A Bayes optimal solution uses prior information about the distribution of the change time to minimize the expected cost, whereas a minimax optimal solution minimizes the cost under the worst-case change-time distribution. Both types of problems are addressed. The most important result of the dissertation is the development of a polynomial-time algorithm for the solution of important classes of Markov Bayes change-detection problems. Existing techniques for epsilon-exact solution of partially observable Markov decision processes have complexity exponential in the number of observation symbols. A new algorithm, called constellation induction, exploits the concavity and Lipschitz continuity of the value function, and has complexity polynomial in the number of observation symbols. It is shown that change-detection problems with a geometric change-time distribution and identically- and independently-distributed observations before and after the change are solvable in polynomial time. Also, change-detection problems on hidden Markov models with a fixed number of recurrent states are solvable in polynomial time. A detailed implementation and analysis of the constellation-induction algorithm are provided. Exact solution methods are also established for several types of minimax change-detection problems. Finite-horizon problems with arbitrary observation distributions are modeled as extensive-form games and solved using linear programs. Infinite-horizon problems with linear penalty for detection delay and identically- and independently-distributed observations can be solved in polynomial time via epsilon-optimal parameterization of a cumulative-sum procedure. Finally, the properties of policies for change-detection problems are described and analyzed. Simple classes of formal languages are shown to be sufficient for epsilon-exact solution of change-detection problems, and methods for finding minimally sized policy representations are described.

Contextual text mining

With the dramatic growth of text information, there is an increasing need for powerful text mining systems that can automatically discover useful knowledge from text. Text is generally associated with all kinds of contextual information. Those contexts can be explicit, such as the time and the location where a blog article is written, and the author(s) of a biomedical publication, or implicit, such as the positive or negative sentiment that an author had when she wrote a product review; there may also be complex context such as the social network of the authors. Many applications require analysis of topic patterns over different contexts. For instance, analysis of search logs in the context of the user can reveal how we can improve the quality of a search engine by optimizing the search results according to particular users; analysis of customer reviews in the context of positive and negative sentiments can help the user summarize public opinions about a product; analysis of blogs or scientific publications in the context of a social network can facilitate discovery of more meaningful topical communities. Since context information significantly affects the choices of topics and language made by authors, in general, it is very important to incorporate it into analyzing and mining text data. In general, modeling the context in text, discovering contextual patterns of language units and topics from text, a general task which we refer to as Contextual Text Mining, has widespread applications in text mining. In this thesis, we provide a novel and systematic study of contextual text mining, which is a new paradigm of text mining treating context information as the ``first-class citizen.'' We formally define the problem of contextual text mining and its basic tasks, and propose a general framework for contextual text mining based on generative modeling of text. This conceptual framework provides general guidance on text mining problems with context information and can be instantiated into many real tasks, including the general problem of contextual topic analysis. We formally present a functional framework for contextual topic analysis, with a general contextual topic model and its various versions, which can effectively solve the text mining problems in a lot of real world applications. We further introduce general components of contextual topic analysis, by adding priors to contextual topic models to incorporate prior knowledge, regularizing contextual topic models with dependency structure of context, and postprocessing contextual patterns to extract refined patterns. The refinements on the general contextual topic model naturally lead to a variety of probabilistic models which incorporate different types of context and various assumptions and constraints. These special versions of the contextual topic model are proved effective in a variety of real applications involving topics and explicit contexts, implicit contexts, and complex contexts. We then introduce a postprocessing procedure for contextual patterns, by generating meaningful labels for multinomial context models. This method provides a general way to interpret text mining results for real users. By applying contextual text mining in the ``context'' of other text information management tasks, including ad hoc text retrieval and web search, we further prove the effectiveness of contextual text mining techniques in a quantitative way with large scale datasets. The framework of contextual text mining not only unifies many explorations of text analysis with context information, but also opens up many new possibilities for future research directions in text mining.

Towards structured, block-based PDF

The Portable Document Format (PDF), defined by Adobe Systems Inc. as the basis of its Acrobat product range, is discussed in some detail. Particular emphasis is given to its flexible object-oriented structure, which has yet to be fully exploited. It is currently used to represent not logical structure but simply a series of pages and associated resources. A definition of an Encapsulated PDF (EPDF) is presented, in which EPDF blocks carry with them their own resource requirements, together with geometrical and logical information. A block formatter called Juggler is described which can lay out EPDF blocks from various sources onto new pages. Future revisions of PDF supporting uniquely-named EPDF blocks tagged with semantic information would assist in composite-pagemakeup and could even lead to fully revisable PDF.

Similarity Measures for Exam Timetabling Problems

A large number of heuristic algorithms have been developed over the years which have been aimed at solving examination timetabling problems. However, many of these algorithms have been developed specifically to solve one particular problem instance or a small subset of instances related to a given real-life problem. Our aim is to develop a more general system which, when given any exam timetabling problem, will produce results which are comparative to those of a specially designed heuristic for that problem. We are investigating a Case based reasoning (CBR) technique to select from a set of algorithms which have been applied successfully to similar problem instances in the past. The assumption in CBR is that similar problems have similar solutions. For our system, the assumption is that an algorithm used to find a good solution to one problem will also produce a good result for a similar problem. The key to the success of the system will be our definition of similarity between two exam timetabling problems. The study will be carried out by running a series of tests using a simple Simulated Annealing Algorithm on a range of problems with differing levels of similarity and examining the data sets in detail. In this paper an initial investigation of the key factors which will be involved in this measure is presented with a discussion of how the definition of good impacts on this.

Similarity Measures for Exam Timetabling Problems

A large number of heuristic algorithms have been developed over the years which have been aimed at solving examination timetabling problems. However, many of these algorithms have been developed specifically to solve one particular problem instance or a small subset of instances related to a given real-life problem. Our aim is to develop a more general system which, when given any exam timetabling problem, will produce results which are comparative to those of a specially designed heuristic for that problem. We are investigating a Case based reasoning (CBR) technique to select from a set of algorithms which have been applied successfully to similar problem instances in the past. The assumption in CBR is that similar problems have similar solutions. For our system, the assumption is that an algorithm used to find a good solution to one problem will also produce a good result for a similar problem. The key to the success of the system will be our definition of similarity between two exam timetabling problems. The study will be carried out by running a series of tests using a simple Simulated Annealing Algorithm on a range of problems with differing levels of similarity and examining the data sets in detail. In this paper an initial investigation of the key factors which will be involved in this measure is presented with a discussion of how the definition of good impacts on this.

Linear non-local diffusion problems in metric measure spaces

The aim of this paper is to provide a comprehensive study of some linear non-local diffusion problems in metric measure spaces. These include, for example, open subsets in ℝN, graphs, manifolds, multi-structures and some fractal sets. For this, we study regularity, compactness, positivity and the spectrum of the stationary non-local operator. We then study the solutions of linear evolution non-local diffusion problems, with emphasis on similarities and differences with the standard heat equation in smooth domains. In particular, we prove weak and strong maximum principles and describe the asymptotic behaviour using spectral methods.

Systematic review and meta-analysis of interventions relevant for young offenders with mood disorders, anxiety disorders, or self-harm

Background: Mood and anxiety disorders, and problems with self harm are significant and serious issues that are common in young people in the Criminal Justice System. Aims: To examine whether interventions relevant to young offenders with mood or anxiety disorders, or problems with self harm are effective. Method: Systematic review and meta-analysis of data from randomised controlled trials relevant to young offenders experiencing these problems. Results: An exhaustive search of the worldwide literature (published and unpublished)yielded 10 studies suitable for inclusion in this review. Meta-analysis of data from three studies (with a total population of 171 individuals) revealed that group-based Cognitive Behaviour Therapy (CBT) may help to reduce symptoms of depression in young offenders. Conclusions: These preliminary findings suggest that group-based CBT may be useful for young offenders with such mental health problems, but larger high quality RCTs are now needed to bolster the evidence-base.