Linking Applied Ethnobotany to Social Learning: A Participatory Tool for the Promotion of Indigenous Plants Use in Matutuíne, Southern Mozambique

In its search for pathways towards a more sustainable management of natural resources, development oriented research increasingly faces the challenge to develop new concepts and tools based on transdisciplinarity. Transdisciplinarity can, in terms of an idealized goal, be defined as a research approach that identifies and solves problems not only independently of disciplinary boundaries, but also including the knowledge and perceptions of non-scientific actors in a participatory process. In Mozambique, the Centre for Development and Environment (Berne, Switzerland), in partnership with Impacto and Helvetas (Maputo, Mozambique), has elaborated a new transdisciplinary tool to identify indigenous plants with a potential for commercialization. The tool combines methods from applied ethnobotany with participatory research in a social learning process. This approach was devised to support a development project aimed at creating alternative sources of income for rural communities of Matutuíne district, Southern Mozambique, while reducing the pressure on the natural environment. The methodology, which has been applied and tested, is innovative in that it combines important data collection through participatory research with a social learning process involving both local and external actors. This mutual learning process provides a space for complementary forms of knowledge to meet, eventually leading to the adoption of an integrated approach to natural resource management with an understanding of its ecological, socio-economic and cultural aspects; local stakeholders are included in the identification of potentials for sustainable development. Sustainable development itself, as a normative concept, can only be defined through social learning and consensus building between the local and external stakeholders.

Learning by Not Doing: Subsidy Disciplines in Services Trade

This paper explores the hitherto futile quest for developing disciplines on the trade- and investment-distorting effects of services subsidies. It sheds light on the multiplicity of factors that have weighed on the conduct of negotiations on subsidy disciplines in a services trade context at both the global and preferential levels, and advances a few thoughts on what the future may hold for the adoption of such disciplines. The analysis suggests that it is rather unlikely that WTO Members will any time soon reach a consensus on the matter of subsidy disciplines for services beyond those that currently (and timidly) obtain in the GATS and in many preferential trade agreements. The main reason behind such a conclusion stems from a marked rise in the value of preserving policy space in a trading environment characterized by considerably greater global market contestability than two decades ago.

Mining recurring concepts in a dynamic feature space

Most data stream classification techniques assume that the underlying feature space is static. However, in real-world applications the set of features and their relevance to the target concept may change over time. In addition, when the underlying concepts reappear, reusing previously learnt models can enhance the learning process in terms of accuracy and processing time at the expense of manageable memory consumption. In this paper, we propose mining recurring concepts in a dynamic feature space (MReC-DFS), a data stream classification system to address the challenges of learning recurring concepts in a dynamic feature space while simultaneously reducing the memory cost associated with storing past models. MReC-DFS is able to detect and adapt to concept changes using the performance of the learning process and contextual information. To handle recurring concepts, stored models are combined in a dynamically weighted ensemble. Incremental feature selection is performed to reduce the combined feature space. This contribution allows MReC-DFS to store only the features most relevant to the learnt concepts, which in turn increases the memory efficiency of the technique. In addition, an incremental feature selection method is proposed that dynamically determines the threshold between relevant and irrelevant features. Experimental results demonstrating the high accuracy of MReC-DFS compared with state-of-the-art techniques on a variety of real datasets are presented. The results also show the superior memory efficiency of MReC-DFS.

Development and implementation of a virtual laboratory for training process improvement in the mechanics of continuous media

The project arises from the need to develop improved teaching methodologies in field of the mechanics of continuous media. The objective is to offer the student a learning process to acquire the necessary theoretical knowledge, cognitive skills and the responsibility and autonomy to professional development in this area. Traditionally the teaching of the concepts of these subjects was performed through lectures and laboratory practice. During these lessons the students attitude was usually passive, and therefore their effectiveness was poor. The proposed methodology has already been successfully employed in universities like University Bochum, Germany, University the South Australia and aims to improve the effectiveness of knowledge acquisition through use by the student of a virtual laboratory. This laboratory allows to adapt the curricula and learning techniques to the European Higher Education and improve current learning processes in the University School of Public Works Engineers -EUITOP- of the Technical University of Madrid -UPM-, due there are not laboratories in this specialization. The virtual space is created using a software platform built on OpenSim, manages 3D virtual worlds, and, language LSL -Linden Scripting Language-, which imprints specific powers to objects. The student or user can access this virtual world through their avatar -your character in the virtual world- and can perform practices within the space created for the purpose, at any time, just with computer with internet access and viewfinder. The virtual laboratory has three partitions. The virtual meeting rooms, where the avatar can interact with peers, solve problems and exchange existing documentation in the virtual library. The interactive game room, where the avatar is has to resolve a number of issues in time. And the video room where students can watch instructional videos and receive group lessons. Each audiovisual interactive element is accompanied by explanations framing it within the area of knowledge and enables students to begin to acquire a vocabulary and practice of the profession for which they are being formed. Plane elasticity concepts are introduced from the tension and compression testing of test pieces of steel and concrete. The behavior of reticulated and articulated structures is reinforced by some interactive games and concepts of tension, compression, local and global buckling will by tests to break articulated structures. Pure bending concepts, simple and composite torsion will be studied by observing a flexible specimen. Earthquake resistant design of buildings will be checked by a laboratory test video.

Herramienta para la gestión de diarios de entretenimientos configurables

El Trabajo Fin de Grado ha consistido en el diseño e implementación de una herramienta para la gestión y administración de los entrenamientos de atletas de deportes individuales. Hasta ahora los deportistas debían gestionar sus entrenamientos a través de hojas de cálculo, teniendo que dedicar tiempo al aprendizaje de herramientas como Microsoft Excel u OpenOffice Excel para personalizar las plantillas y guardar los datos, utilizar otras herramientas como Google Calendar para obtener una visión de un calendario con los entrenamientos realizados o bien utilizar programas hechos a medida para un deporte e incluso para un deportista. El objetivo principal consistía en desarrollar una herramienta que unificara todas las tareas para ofrecer al deportista las funciones de configuración de plantillas, registro y generación de gráficas de los datos registrados y visionado del calendario de entrenamientos de una forma ágil, sencilla e intuitiva, adaptándose a las necesidades de cualquier deporte o deportista. Para alcanzar el objetivo principal realizamos encuestas a atletas de una gran diversidad de deportes individuales, detectando las particularidades de cada deporte y analizando los datos que nos ofrecían para alcanzar el objetivo de diseñar una herramienta versátil que permitiera su uso independientemente de los parámetros que se quisiera registrar de cada entrenamiento. La herramienta generada es una herramienta programada en Java, que ofrece portabilidad a cualquier sistema operativo que lo soporte, sin ser necesario realizar una instalación previa. Es una aplicación plug and play en la que solo se necesita del fichero ejecutable para su funcionamiento; de esta forma facilitamos que el deportista guarde toda la información en muy poco espacio, 6 megabytes aproximadamente, y pueda llevarla a cualquier lado en un pen drive o en sistemas de almacenamiento en la nube. Además, los ficheros en los que se registran los datos son ficheros CSV (valores separados por comas) con un formato estandarizado que permite la exportación a otras herramientas. Como conclusión el atleta ahorra tiempo y esfuerzo en tareas ajenas a la práctica del deporte y disfruta de una herramienta que le permite analizar de diferentes maneras cada uno de los parámetros registrados para ver su evolución y ayudarle a mejorar aquellos aspectos que sean deficientes. ---ABSTRACT---The Final Project consists in the design and implementation of a tool for the management and administration of training logs for individual athletes. Until now athletes had to manage their workouts through spreadsheets, having to spend time in learning tools such as Microsoft Excel or OpenOffice in order to save the data, others tools like Google Calendar to check their training plan or buy specifics programs designed for a specific sport or even for an athlete. The main purpose of this project is to develop an intuitive and straightforward tool that unifies all tasks offering setup functions, data recording, graph generation and training schedule to the athletes. Whit this in mind, we have interviewed athletes from a wide range of individual sports, identifying their specifications and analyzing the data provided to design a flexible tool that registers multitude of training parameters. This tool has been coded in Java, providing portability to any operating system that supports it, without installation being required. It is a plug and play application, that only requires the executable file to start working. Accordingly, athletes can keep all the information in a relative reduced space (aprox 6 megabytes) and save it in a pen drive or in the cloud. In addition, the files whit the stored data are CSV (comma separated value) files whit a standardized format that allows exporting to other tools. Consequently athletes will save time and effort on tasks unrelated to the practice of sports. The new tool will enable them to analyze in detail all the existing data and improve in those areas with development opportunities.

Hacia un análisis cuantitativo de la Ciudad Informal: una aproximación desde la Habitabilidad Básica y la experiencia en Makeni (Sierra Leona)

La importantísima expansión urbana que sufren las principales ciudades de los países en vías de desarrollo, es el mayor reto que afronta la habitabilidad a nivel mundial. Dentro de la teoría general de la Habitabilidad Básica (HaB-ETSAM-UPM, 1995) la ordenación del territorio y el planeamiento urbanístico son las herramientas determinantes para orientar coherentemente los procesos de urbanización, como se reconoce también desde las principales esferas técnicas a nivel internacional. Pero tales herramientas deben enfocarse a una construcción eficiente del territorio, actuando desde una aproximación multidisciplinar, flexible y directa, que incida en las prioridades específicas de cada contexto. Para ello, resulta fundamental comprender a fondo las realidades específicas de estos ámbitos. La ciudad es un fenómeno complejo en esencia. El tejido construido, en constante proceso de cambio, es el caparazón visible que alberga una maravillosa mezcla entrelazada de espacios, funciones, flujos, personas.... Cada ciudad, diferente y única, se integra en su medio, se adapta a geografías, contextos y climas distintos, evoluciona según dinámicas propias, en incomprensibles (o casi) procesos evolutivos. El estudio de la ciudad, supone siempre una simplificación de la misma. La realidad urbana, por detallado que sea nuestro análisis, siempre contendrá indescifrables relaciones que se nos escapan. En cambio, necesitamos de métodos analíticos que nos ayuden a comprender algo esa complejidad. Acercarnos en ese análisis, es un paso previo fundamental para la formulación de respuestas. En este plano, de avance en la comprensión del hecho urbano, se sitúa este trabajo. Se pone el acento en el enfoque cuantitativo, profundizando en datos básicos concretos, siempre aceptando de partida que esta información es una componente mínima, pero esperamos que sustantiva, de un fenómeno inabordable. Y es esta búsqueda de comprensión material y cuantitativa de la ciudad, el objetivo esencial de la investigación. Se pretende proporcionar una base detallada de aquéllos aspectos fundamentales, que pueden ser medidos en los entornos urbanos y que nos proporcionan información útil para el diagnóstico y las propuestas. Para ello, se aportan rangos y referencias deseables, a través de una herramienta para la comprensión y la valoración de cada contexto, la Matriz de Indicadores. Esta herramienta se concibe desde la reflexión a la aplicación práctica, a la utilidad directa, al aporte concreto para quien pueda servir. Ésta es la voluntad decidida con la que se aborda este trabajo, centrado en los entornos urbanos donde el aporte técnico es prioritario: la Ciudad Informal. La Ciudad Informal, entendida aquí como aquélla que se desarrolla sin los medios suficientes (técnicos, económicos e institucionales) que proporciona la planificación, aquélla por donde la habitabilidad precaria se extiende. Es la ciudad que predomina en los países en vías de desarrollo, en los contextos de bajos recursos, allí donde, precisamente, se concentran los principales déficits y necesidades a nivel global. El enfoque nace de la teoría de la Habitabilidad Básica, de la definición de mínimos posibles para, desde allí, construir el espacio necesario para el desarrollo humano. Éste es el ámbito genérico objeto del trabajo que, a su vez, se nutre, de forma muy importante, de la experiencia directa en la ciudad de Makeni, en Sierra Leona. Esta ciudad nos sirve de prototipo experimental en un doble sentido. Por un lado, sirve como espacio empírico en el que chequear la metodología de valoración cuantitativa; y, por otro, el conocimiento de esta ciudad de tamaño medio africana, que se ha ido adquiriendo en los últimos cinco años, es una base directa para el desarrollo teórico de la propia metodología, que ayuda a atisbar lo esencial en contextos similares. El encaje de todo este recorrido se ha articulado desde una experiencia académica que, como docente, he coordinado directa e intensamente. Experiencia muy enriquecedora, que ha sumado muchas manos y mucho aprendizaje en este tiempo. Teoría y práctica en planeamiento urbano se alternan en el trabajo, nutriéndose la una de la otra y a la inversa. Trabajo que nace desde la pasión por la ciudad y el urbanismo. Desde la búsqueda por comprender y desde la vocación de actuar, de intentar mejorar y hacer más habitables los entornos urbanos. Especialmente allí donde las dificultades se agolpan y el camino se alarga, se llena de polvo. Acumular preguntas a cada paso. Cada vez más preguntas. Las respuestas, si existen, aparecen entrelazadas en dinámicas indescifrables de las que queremos formar parte. Fundirnos por momentos en la misma búsqueda, acompañarla. Sentirnos cerca de quiénes comienzan de cero casi cada día. Y otra vez, arrancar. Y compartir, desde el conocimiento, si acaso es que se puede. Y la ciudad. Brutal, imponente, asfixiante, maravillosa, imposible. Creación colectiva insuperable, de energías sumadas que se cosen sin patrón aparente. O sin más razón que la del propio pulso de la vida. Así se siente Makeni. ABSTRACT The important urban growth suffering major cities of developing countries, is the biggest challenge facing the global habitability. Within the general theory of Basic Habitability (HAB-ETSAM-UPM, 1995) spatial planning and urban planning are the crucial tools to consistently guide the urbanization process, as also recognized from the main technical areas worldwide. But such tools should focus on an efficient construction of the territory, working from a multidisciplinary, flexible and direct approach, that affects the specific priorities of each context. To do this, it is essential to thoroughly understand the specific realities of these areas. The city is essentially a complex phenomenon. The urban fabric in constant flux, is the visible shell that houses a wonderful mixture interlocking spaces, functions, flows, people.... Every city, different and unique, is integrated into its environment, adapted to geographies, contexts and climates, it evolves according to its own dynamics, along (almost) incomprehensible evolutionary processes. The study of the city, is always a simplification of it. The urban reality, even studied from a detailed analysis, always contain undecipherable relationships that escape us. Instead, we need analytical methods that help us understand something that complexity. Moving forward in this analysis is an essential first step in formulating responses. At this level, progressing in understand the urban reality, is where this work is located. The emphasis on the quantitative approach is placed, delving into specific basic data, starting always accepting that this information is just a minimal component, but we hope that substantive, of an intractable phenomenon. And it is this search for materials and quantitative understanding of the city, the main objective of the research. It is intended to provide a detailed basis of those fundamental aspects that can be measured in urban environments that provide us useful information for the diagnosis and proposals. To do this, desirable ranges and references are provided, through a tool for understanding and appreciation of each context, the Indicator Matrix. This tool is conceived from reflection to practical application, to a direct utility, concrete contribution to who can serve. This is the firm resolve with which this work is addressed, centered in urban environments where the technical contribution is a priority: the Informal City. The Informal City, understood here as the urban areas developed without the sufficient resources (technical, economic and institutional) which planning provides, where it is extended the precarious habitability. It is the city that prevails in developing countries, in low-resource settings, where, precisely, the main gaps and needs in the global context are concentrated. The approach stems from the theory of Basic Habitability, the definition of possible minimum, to build the necessary space for human development. This is the generic scope of the work object, that is also based in the direct experience in the town of Makeni, Sierra Leone. This city serves as an experimental prototype in two ways. On the one hand, it serves as a space where empirically check the quantitative assessment methodology; and, secondly, the knowledge of this African city of medium size, which has been acquired in the last five years, is a direct basis for the theoretical development of the methodology itself, which helps to glimpse the essence in similar contexts. The engagement of this whole journey has been articulated from an academic experience, directly and intensely coordinated as teacher. Enriching experience that has added many hands and much learning at this time. Theory and practice in urban planning are mixed at work, enriching the one of the other and vice versa. Work is born from the passion for the city and urbanism. From the search for understanding and from the vocation of acting, trying to improve and make more livable urban environments. Especially where the difficulties are crowded and the road is so long, full of dust. To accumulate questions at every turn. More and more questions. The answers, if do exist, appears inside indecipherable dynamics in which we want to be involved. Merge at times in the same search. Feel close to those who start from scratch almost every day. And again, move forward. And share, from knowledge, if possible. And the city. Brutal, impressive, suffocating, wonderful, impossible. Unsurpassed collective creation, combined energy mix that are sewn with no apparent pattern. Or for no reason other than the pulse of life itself. As it feels the city of Makeni.

Dimensionality Reduction Through Sub-Space Mapping for Nearest Neighbour Algorithms

Postprint

Discovery of genes involved with learning and memory: An experimental synthesis of Hirschian and Benzerian perspectives

The biological bases of learning and memory are being revealed today with a wide array of molecular approaches, most of which entail the analysis of dysfunction produced by gene disruptions. This perspective derives both from early “genetic dissections” of learning in mutant Drosophila by Seymour Benzer and colleagues and from earlier behavior-genetic analyses of learning and in Diptera by Jerry Hirsch and coworkers. Three quantitative-genetic insights derived from these latter studies serve as guiding principles for the former. First, interacting polygenes underlie complex traits. Consequently, learning/memory defects associated with single-gene mutants can be quantified accurately only in equilibrated, heterogeneous genetic backgrounds. Second, complex behavioral responses will be composed of genetically distinct functional components. Thus, genetic dissection of complex traits into specific biobehavioral properties is likely. Finally, disruptions of genes involved with learning/memory are likely to have pleiotropic effects. As a result, task-relevant sensorimotor responses required for normal learning must be assessed carefully to interpret performance in learning/memory experiments. In addition, more specific conclusions will be obtained from reverse-genetic experiments, in which gene disruptions are restricted in time and/or space.

Traces of learning in the auditory localization pathway

One of the fascinating properties of the central nervous system is its ability to learn: the ability to alter its functional properties adaptively as a consequence of the interactions of an animal with the environment. The auditory localization pathway provides an opportunity to observe such adaptive changes and to study the cellular mechanisms that underlie them. The midbrain localization pathway creates a multimodal map of space that represents the nervous system's associations of auditory cues with locations in visual space. Various manipulations of auditory or visual experience, especially during early life, that change the relationship between auditory cues and locations in space lead to adaptive changes in auditory localization behavior and to corresponding changes in the functional and anatomical properties of this pathway. Traces of this early learning persist into adulthood, enabling adults to reacquire patterns of connectivity that were learned initially during the juvenile period.

How online applications can help to achieve integral learning

The development of transversal competencies provides an integral education. However, its practical implementation among different subjects is not a trivial task. There are several issues that should be previously solved in an optimal way to take advantage of the synergy among subjects. Main issues are: i) the need for a common space for the documents management, ii) the availability of the document everywhere and anytime, and iii) the possibility to collaborate in the documents edition tasks. It was implemented a virtual portfolio for the students which allows the assessment of all the subjects in a global way. To this goal we used the Google apps due to its free access, availability and suitability for the collaborative editing tasks.

Selective SWIFT-R. A Flexible Software-Based Technique for Soft Error Mitigation in Low-Cost Embedded Systems

Commercial off-the-shelf microprocessors are the core of low-cost embedded systems due to their programmability and cost-effectiveness. Recent advances in electronic technologies have allowed remarkable improvements in their performance. However, they have also made microprocessors more susceptible to transient faults induced by radiation. These non-destructive events (soft errors), may cause a microprocessor to produce a wrong computation result or lose control of a system with catastrophic consequences. Therefore, soft error mitigation has become a compulsory requirement for an increasing number of applications, which operate from the space to the ground level. In this context, this paper uses the concept of selective hardening, which is aimed to design reduced-overhead and flexible mitigation techniques. Following this concept, a novel flexible version of the software-based fault recovery technique known as SWIFT-R is proposed. Our approach makes possible to select different registers subsets from the microprocessor register file to be protected on software. Thus, design space is enriched with a wide spectrum of new partially protected versions, which offer more flexibility to designers. This permits to find the best trade-offs between performance, code size, and fault coverage. Three case studies have been developed to show the applicability and flexibility of the proposal.

Learning representations for Information Retrieval

La recherche d'informations s'intéresse, entre autres, à répondre à des questions comme: est-ce qu'un document est pertinent à une requête ? Est-ce que deux requêtes ou deux documents sont similaires ? Comment la similarité entre deux requêtes ou documents peut être utilisée pour améliorer l'estimation de la pertinence ? Pour donner réponse à ces questions, il est nécessaire d'associer chaque document et requête à des représentations interprétables par ordinateur. Une fois ces représentations estimées, la similarité peut correspondre, par exemple, à une distance ou une divergence qui opère dans l'espace de représentation. On admet généralement que la qualité d'une représentation a un impact direct sur l'erreur d'estimation par rapport à la vraie pertinence, jugée par un humain. Estimer de bonnes représentations des documents et des requêtes a longtemps été un problème central de la recherche d'informations. Le but de cette thèse est de proposer des nouvelles méthodes pour estimer les représentations des documents et des requêtes, la relation de pertinence entre eux et ainsi modestement avancer l'état de l'art du domaine. Nous présentons quatre articles publiés dans des conférences internationales et un article publié dans un forum d'évaluation. Les deux premiers articles concernent des méthodes qui créent l'espace de représentation selon une connaissance à priori sur les caractéristiques qui sont importantes pour la tâche à accomplir. Ceux-ci nous amènent à présenter un nouveau modèle de recherche d'informations qui diffère des modèles existants sur le plan théorique et de l'efficacité expérimentale. Les deux derniers articles marquent un changement fondamental dans l'approche de construction des représentations. Ils bénéficient notamment de l'intérêt de recherche dont les techniques d'apprentissage profond par réseaux de neurones, ou deep learning, ont fait récemment l'objet. Ces modèles d'apprentissage élicitent automatiquement les caractéristiques importantes pour la tâche demandée à partir d'une quantité importante de données. Nous nous intéressons à la modélisation des relations sémantiques entre documents et requêtes ainsi qu'entre deux ou plusieurs requêtes. Ces derniers articles marquent les premières applications de l'apprentissage de représentations par réseaux de neurones à la recherche d'informations. Les modèles proposés ont aussi produit une performance améliorée sur des collections de test standard. Nos travaux nous mènent à la conclusion générale suivante: la performance en recherche d'informations pourrait drastiquement être améliorée en se basant sur les approches d'apprentissage de représentations.

Learning representations for Information Retrieval

La recherche d'informations s'intéresse, entre autres, à répondre à des questions comme: est-ce qu'un document est pertinent à une requête ? Est-ce que deux requêtes ou deux documents sont similaires ? Comment la similarité entre deux requêtes ou documents peut être utilisée pour améliorer l'estimation de la pertinence ? Pour donner réponse à ces questions, il est nécessaire d'associer chaque document et requête à des représentations interprétables par ordinateur. Une fois ces représentations estimées, la similarité peut correspondre, par exemple, à une distance ou une divergence qui opère dans l'espace de représentation. On admet généralement que la qualité d'une représentation a un impact direct sur l'erreur d'estimation par rapport à la vraie pertinence, jugée par un humain. Estimer de bonnes représentations des documents et des requêtes a longtemps été un problème central de la recherche d'informations. Le but de cette thèse est de proposer des nouvelles méthodes pour estimer les représentations des documents et des requêtes, la relation de pertinence entre eux et ainsi modestement avancer l'état de l'art du domaine. Nous présentons quatre articles publiés dans des conférences internationales et un article publié dans un forum d'évaluation. Les deux premiers articles concernent des méthodes qui créent l'espace de représentation selon une connaissance à priori sur les caractéristiques qui sont importantes pour la tâche à accomplir. Ceux-ci nous amènent à présenter un nouveau modèle de recherche d'informations qui diffère des modèles existants sur le plan théorique et de l'efficacité expérimentale. Les deux derniers articles marquent un changement fondamental dans l'approche de construction des représentations. Ils bénéficient notamment de l'intérêt de recherche dont les techniques d'apprentissage profond par réseaux de neurones, ou deep learning, ont fait récemment l'objet. Ces modèles d'apprentissage élicitent automatiquement les caractéristiques importantes pour la tâche demandée à partir d'une quantité importante de données. Nous nous intéressons à la modélisation des relations sémantiques entre documents et requêtes ainsi qu'entre deux ou plusieurs requêtes. Ces derniers articles marquent les premières applications de l'apprentissage de représentations par réseaux de neurones à la recherche d'informations. Les modèles proposés ont aussi produit une performance améliorée sur des collections de test standard. Nos travaux nous mènent à la conclusion générale suivante: la performance en recherche d'informations pourrait drastiquement être améliorée en se basant sur les approches d'apprentissage de représentations.

Flexible structure control laboratory development and technology demonstration /

"Final report for the period July 1985 to July 1987."

Making Space: Feasibility of Urban Manufacturing through Shared Resources

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