Indexing the Earth Mover's Distance Using Normal Distributions

Querying uncertain data sets (represented as probability distributions) presents many challenges due to the large amount of data involved and the difficulties comparing uncertainty between distributions. The Earth Mover's Distance (EMD) has increasingly been employed to compare uncertain data due to its ability to effectively capture the differences between two distributions. Computing the EMD entails finding a solution to the transportation problem, which is computationally intensive. In this paper, we propose a new lower bound to the EMD and an index structure to significantly improve the performance of EMD based K-nearest neighbor (K-NN) queries on uncertain databases. We propose a new lower bound to the EMD that approximates the EMD on a projection vector. Each distribution is projected onto a vector and approximated by a normal distribution, as well as an accompanying error term. We then represent each normal as a point in a Hough transformed space. We then use the concept of stochastic dominance to implement an efficient index structure in the transformed space. We show that our method significantly decreases K-NN query time on uncertain databases. The index structure also scales well with database cardinality. It is well suited for heterogeneous data sets, helping to keep EMD based queries tractable as uncertain data sets become larger and more complex.Comment: VLDB201

Contribution to the development of mathematical programming tools to assist decision-making in sustainability problems

L'activitat humana està excedint la capacitat de resposta de la Terra, el que pot tenir implicacions perjudicials per al futur benestar humà i del medi ambient. Sens dubte, severs canvis estructurals seran necessaris, el que exigeix prendre solucions eficaces davant els problemes emergents de sostenibilitat. En aquest context, aquesta tesi es centra en dues transformacions clau per re-connectar el desenvolupament humà amb el progrés sostenible: la "seguretat alimentària sostenible", desacoblant la intensificació agrícola de l'ús insostenible dels recursos; i el "model energètic sostenible", donant suport al canvi cap a una economia respectuosa amb el medi ambient. El marc metodològic consisteix a abordar diferents problemes mitjançant el desenvolupament d'eines sistemàtiques de programació matemàtica amb l'objectiu de donar suport a la presa de decisions i la formulació de polítiques conduents a la consecució del desenvolupament sostenible. Aquesta tesi doctoral inclou quatre contribucions principals en forma d'eines de decisió i suport de polítiques prou flexibles com per abordar diferents casos d'estudi. En primer lloc, es proposa una eina multiobjectiu per assignar àrees de cultiu considerant simultàniament criteris productius i mediambientals. En segon lloc, es proposa un model multiperíode per determinar plans de cultiu òptims i subsidis efectius per tal de promoure pràctiques agrícoles sostenibles. En tercer lloc, es proposa una metodologia per a analitzar la sostenibilitat que permet avaluar sistemes muticriteri i proporciona potencials millores d'acord amb els principis de la sostenibilitat. En quart lloc, es proposa un nou enfocament basat en l'optimització d'accions cooperatives amb l'objectiu de promoure i enfortir la cooperació internacional en la lluita contra el canvi climàtic La informació derivada de la investigació, com la presentada en aquesta tesi, pot tenir un paper fonamental en la transició cap a una nova era en la qual l'economia, la societat i el medi ambient coexisteixin com a pilars clau del desenvolupament sostenible.La actividades humanas están excediendo la capacidad de carga de la Tierra, lo que puede potencialmente generar implicaciones perjudiciales para el futuro bienestar humano y del medio ambiente. Sin duda son necesarios profundos cambios estructurales, lo que exige tomar soluciones eficaces ante los problemas emergentes de sostenibilidad. En este contexto, esta tesis se centra en dos transformaciones clave para reconectar el desarrollo humano con el progreso sostenible: la "seguridad alimentaria sostenible", desacoplando la intensificación agrícola del uso insostenible de los recursos; y el " modelo energético sostenible", apoyando el cambio hacia una economía respetuosa con el medio ambiente. El marco metodológico consiste en abordar distintos problemas mediante el desarrollo de herramientas sistemáticas de programación matemática cuyo objetivo es apoyar la toma de decisiones y la formulación de políticas tendentes hacia la consecución del desarrollo sostenible. La tesis incluye cuatro contribuciones principales en forma de herramientas de decisión y apoyo de políticas suficientemente flexibles para abordar diferentes casos de estudio. En primer lugar, se propone una herramienta multiobjetivo para asignar áreas de cultivo considerando simultáneamente criterios productivos y medioambientales. En segundo, se propone un modelo multiperiodo para determinar planes de cultivo óptimos y subsidios efectivos con el fin de promover prácticas agrícolas sostenibles. En tercero, se propone una metodología para realizar análisis de sostenibilidad que permite evaluar sistemas muticriterio y proporciona potenciales mejoras de acuerdo con principios de sostenibilidad. En cuarto lugar, se propone un nuevo enfoque basado en la optimización de acciones cooperativas con el objetivo de promover y fortalecer la cooperación internacional en la lucha contra el cambio climático La información derivada de la investigación, como la presentada en esta tesis, puede desempeñar un papel fundamental en la transición hacia una nueva era en la que la economía, la sociedad y el medio ambiente coexistan como pilares clave del desarrollo sostenible.Impacts from human activities are exceeding the Earth’s carrying capacity, which may lead to irreversible changes posing a serious threat to future human well-being and the environment. There is no doubt that an urgent shift is needed for sustainability, which calls for effective solutions when facing ongoing and emerging sustainability challenges. Against this background, this thesis focuses on two key structural transformations needed to reconnect the human development to sustained progress: the “food security transformation”, through decoupling the intensification of agricultural production from unsustainable use of resources; and the “clean energy transformation”, supporting the transition towards a more environmentally friendly economy. Methodologically, different sustainability issues are tackled by developing systematic mathematical programming tools aiming at supporting sustainable decision and policy-making which ultimately will lead to the development of more efficient mechanisms to foster a sustainable development. This thesis includes four major contributions in the form of decision and policy- support tools which are flexible and practical enough to address different case studies towards a more sustainable agriculture and energy future. First, a multi-objective tool is proposed which allows allocating cropping areas simultaneously maximizing the production and minimizing the environmental impact on ecosystems and resources. Second, a multi-period model is proposed which allows determining optimal cropping plans and effective subsidies to promote agricultural practices beneficial to the climate and the environment. Third, a novel methodology tailored to perform sustainability assessments is proposed which allows evaluating multi-criterion systems and providing improvements targets for such systems according to sustainability principles. Fourth, an optimised cooperative approach is proposed to promote and strengthen international cooperation in the fight against climate change. Research-based work as the one proposed herein may play a major role in the transition towards a new era where the economy, society and the environment coexist as key pillars of sustainable development

Robust nonlinear control of vectored thrust aircraft

An interdisciplinary program in robust control for nonlinear systems with applications to a variety of engineering problems is outlined. Major emphasis will be placed on flight control, with both experimental and analytical studies. This program builds on recent new results in control theory for stability, stabilization, robust stability, robust performance, synthesis, and model reduction in a unified framework using Linear Fractional Transformations (LFT's), Linear Matrix Inequalities (LMI's), and the structured singular value micron. Most of these new advances have been accomplished by the Caltech controls group independently or in collaboration with researchers in other institutions. These recent results offer a new and remarkably unified framework for all aspects of robust control, but what is particularly important for this program is that they also have important implications for system identification and control of nonlinear systems. This combines well with Caltech's expertise in nonlinear control theory, both in geometric methods and methods for systems with constraints and saturations

Real options for adaptive decisions in primary industries

Abstract The long term sustainability of Australian crop and livestock farms is threatened with climate change and climate variability. In response, farmers may decide to (1) adjust practices and technologies, (2) change production systems, or (3) transform their industries, for example, by relocating to new geographical areas. Adjustments to existing practices are easy to make relative to changes to production systems or transformations of an industry. Switching between production regimes requires new investments and infrastructure and can leave assets stranded. These changes can be partially or wholly irreversible but hysteresis effects can make switching difficult and mistakes costly to reverse. ‘Real options’ is a framework to structure thinking and analysis of these difficult choices. Previous work has demonstrated how real options can be applied to adaptation, and extends traditional economic analyses of agricultural investment decisions based on net present values to better represent the uncertainty and risks of climate change. This project uses transects across space as analogues for future climate scenarios. We simulate yields from climate data and draw on data from actual farms to estimate a real options model referred to as ‘Real Options for Adaptive Decisions’ (ROADs). We present results for the transformation of wheat dominant cropping systems in South Australia, New South Wales, and Western Australia. We find that farmers’ decisions, as much as a changing climate, determine how agriculture will be transformed. Please cite this report as: Hertzler, G, Sanderson, T, Capon, T, Hayman, P, Kingwell, R, McClintock, A, Crean, J, Randall, A 2013 Will primary producers continue to adjust practices and technologies, change production systems or transform their industry – an application of real options,  National Climate Change Adaptation Research Facility, Gold Coast, pp. 93. The long term sustainability of Australian crop and livestock farms is threatened with climate change and climate variability. In response, farmers may decide to (1) adjust practices and technologies, (2) change production systems, or (3) transform their industries, for example, by relocating to new geographical areas. Adjustments to existing practices are easy to make relative to changes to production systems or transformations of an industry. Switching between production regimes requires new investments and infrastructure and can leave assets stranded. These changes can be partially or wholly irreversible but hysteresis effects can make switching difficult and mistakes costly to reverse. ‘Real options’ is a framework to structure thinking and analysis of these difficult choices. Previous work has demonstrated how real options can be applied to adaptation, and extends traditional economic analyses of agricultural investment decisions based on net present values to better represent the uncertainty and risks of climate change. This project uses transects across space as analogues for future climate scenarios. We simulate yields from climate data and draw on data from actual farms to estimate a real options model referred to as ‘Real Options for Adaptive Decisions’ (ROADs). We present results for the transformation of wheat dominant cropping systems in South Australia, New South Wales, and Western Australia. We find that farmers’ decisions, as much as a changing climate, determine how agriculture will be transformed

FTT:Power : A global model of the power sector with induced technological change and natural resource depletion

This work introduces a model of Future Technology Transformations for the power sector (FTT:Power), a representation of global power systems based on market competition, induced technological change (ITC) and natural resource use and depletion. It is the first component of a family of sectoral bottom-up models of future technology transformations, designed to be integrated into the global macroeconometric model E3MG. ITC occurs as a result of technological learning as given by cumulative investment and leads to highly nonlinear, irreversible and path dependent technological transitions. The model makes use of a dynamic coupled set of logistic differential equations. As opposed to traditional bottom-up energy models based on systems optimisation, logistic equations offer an appropriate treatment of the times and rates of change involved in sectoral technology transformations. Resource use and depletion are represented by local cost-supply curves, which give rise to different regional energy landscapes. The model is explored using two simple scenarios, a baseline and a mitigation case where the price of carbon is gradually increased. While a constant price of carbon leads to a stagnant system, mitigation produces successive technology transitions leading towards the gradual decarbonisation of the global power sector.This work was supported by the Three Guineas TrustSubmitted for publication to Energy Polic

Endogenous monetary policy with unobserved potential output

This paper characterizes endogenous monetary policy when policymakers are uncertain about the extent to which movements in output and inflation are due to changes in potential output or to cyclical demand and cost shocks. We refer to this informational limitation as the “information problem” (IP). Main results of the paper are: 1. Policy is likely to be excessively loose (restrictive) for some time when there is a large decrease (increase) in potential output in comparison with a full information benchmark. 2. Errors in forecasting potential output and the output gap are generally serially correlated. These ndings provide a partial explanation for the inflation of the seventies and the price stability of the nineties. 3. A quantitative assessment, based on an empirical model of the US economy developed by Rudebusch and Svensson (1999), indicates that during and following periods of large changes in potential output the IP significantly affects the dynamics of inflation and output. 4. The increase in the Fed’s conservativeness between the seventies and the nineties, and a more realistic appreciation of the uncertainties surrounding potential output in the second period, imply that the IP problem had a stronger impact in the seventies than in the nineties.monetary policy, potential output, filtering, inflation, output gap