917 resultados para Probabilistic constraints


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Das Mahafaly Plateau im südwestlichen Madagaskar ist gekennzeichnet durch raue klimatische Bedingungen, vor allem regelmäßige Dürren und Trockenperioden, geringe Infrastruktur, steigende Unsicherheit, hohe Analphabetenrate und regelmäßige Zerstörung der Ernte durch Heuschreckenplagen. Da 97% der Bevölkerung von der Landwirtschaft abhängen, ist eine Steigerung der Produktivität von Anbausystemen die Grundlage für eine Verbesserung der Lebensbedingungen und Ernährungssicherheit in der Mahafaly Region. Da wenig über die Produktivität von traditionellen extensiven und neu eingeführten Anbaumethoden in diesem Gebiet bekannt ist, waren die Zielsetzungen der vorliegenden Arbeit, die limitierenden Faktoren und vielversprechende alternative Anbaumethoden zu identifizieren und diese unter Feldbedingungen zu testen. Wir untersuchten die Auswirkungen von lokalem Viehmist und Holzkohle auf die Erträge von Maniok, der Hauptanbaufrucht der Region, sowie die Beiträge von weiteren Faktoren, die im Untersuchungsgebiet ertragslimitierend sind. Darüber hinaus wurde in der Küstenregion das Potenzial für bewässerten Gemüseanbau mit Mist und Holzkohle untersucht, um zu einer Diversifizierung von Einkommen und Ernährung beizutragen. Ein weiterer Schwerpunkt dieser Arbeit war die Schätzung von Taubildung und deren Beitrag in der Jahreswasserbilanz durch Testen eines neu entworfenen Taumessgerätes. Maniok wurde über drei Jahre und in drei Versuchsfeldern in zwei Dörfern auf dem Plateau angebaut, mit applizierten Zeburindermistraten von 5 und 10 t ha-1, Holzkohleraten von 0,5 und 2 t ha-1 und Maniokpflanzdichten von 4500 Pflanzen ha-1. Maniokknollenerträge auf Kontrollflächen erreichten 1 bis 1,8 t Trockenmasse (TM) ha-1. Mist führte zu einer Knollenertragssteigerung um 30 - 40% nach drei Jahren in einem kontinuierlich bewirtschafteten Feld mit geringer Bodenfruchtbarkeit, hatte aber keinen Effekt auf den anderen Versuchsfeldern. Holzkohle hatte keinen Einfluss auf Erträge über den gesamten Testzeitraum, während die Infektion mit Cassava-Mosaikvirus zu Ertragseinbußen um bis zu 30% führte. Pflanzenbestände wurden felder-und jahresübergreifend um 4-54% des vollen Bestandes reduziert, was vermutlich auf das Auftreten von Trockenperioden und geringe Vitalität von Pflanzmaterial zurückzuführen ist. Karotten (Daucus carota L. var. Nantaise) und Zwiebeln (Allium cepa L. var. Red Créole) wurden über zwei Trockenzeiten mit lokal erhältlichem Saatgut angebaut. Wir testeten die Auswirkungen von lokalem Rindermist mit einer Rate von 40 t ha-1, Holzkohle mit einer Rate von 10 t ha-1, sowie Beschattung auf die Gemüseernteerträge. Lokale Bewässerungswasser hatte einen Salzgehalt von 7,65 mS cm-1. Karotten- und Zwiebelerträge über Behandlungen und Jahre erreichten 0,24 bis 2,56 t TM ha-1 beziehungsweise 0,30 bis 4,07 DM t ha-1. Mist und Holzkohle hatten keinen Einfluss auf die Erträge beider Kulturen. Beschattung verringerte Karottenerträge um 33% im ersten Jahr, während sich die Erträge im zweiten Jahr um 65% erhöhten. Zwiebelerträge wurden unter Beschattung um 148% und 208% im ersten und zweiten Jahr erhöht. Salines Bewässerungswasser sowie Qualität des lokal verfügbaren Saatgutes reduzierten die Keimungsraten deutlich. Taubildung im Küstendorf Efoetsy betrug 58,4 mm und repräsentierte damit 19% der Niederschlagsmenge innerhalb des gesamten Beobachtungszeitraum von 18 Monaten. Dies weist darauf hin, dass Tau in der Tat einen wichtigen Beitrag zur jährlichen Wasserbilanz darstellt. Tageshöchstwerte erreichten 0,48 mm. Die getestete Tauwaage-Vorrichtung war in der Lage, die nächtliche Taubildung auf der metallischen Kondensationsplatte zuverlässig zu bestimmen. Im abschließenden Kapitel werden die limitierenden Faktoren für eine nachhaltige Intensivierung der Landwirtschaft in der Untersuchungsregion diskutiert.

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Robots must act purposefully and successfully in an uncertain world. Sensory information is inaccurate or noisy, actions may have a range of effects, and the robot's environment is only partially and imprecisely modeled. This thesis introduces active randomization by a robot, both in selecting actions to execute and in focusing on sensory information to interpret, as a basic tool for overcoming uncertainty. An example of randomization is given by the strategy of shaking a bin containing a part in order to orient the part in a desired stable state with some high probability. Another example consists of first using reliable sensory information to bring two parts close together, then relying on short random motions to actually mate the two parts, once the part motions lie below the available sensing resolution. Further examples include tapping parts that are tightly wedged, twirling gears before trying to mesh them, and vibrating parts to facilitate a mating operation.

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A serial-link manipulator may form a mobile closed kinematic chain when interacting with the environment, if it is redundant with respect to the task degrees of freedom (DOFs) at the endpoint. If the mobile closed chain assumes a number of configurations, then loop consistency equations permit the manipulator and task kinematics to be calibrated simultaneously using only the joint angle readings; endpoint sensing is not required. Example tasks include a fixed endpoint (0 DOF task), the opening of a door (1 DOF task), and point contact (3 DOF task). Identifiability conditions are derived for these various tasks.

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This report presents a set of representations methodologies and tools for the purpose of visualizing, analyzing and designing functional shapes in terms of constraints on motion. The core of the research is an interactive computational environment that provides an explicit visual representation of motion constraints produced by shape interactions, and a series of tools that allow for the manipulation of motion constraints and their underlying shapes for the purpose of design.

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Graphical techniques for modeling the dependencies of randomvariables have been explored in a variety of different areas includingstatistics, statistical physics, artificial intelligence, speech recognition, image processing, and genetics.Formalisms for manipulating these models have been developedrelatively independently in these research communities. In this paper weexplore hidden Markov models (HMMs) and related structures within the general framework of probabilistic independencenetworks (PINs). The paper contains a self-contained review of the basic principles of PINs.It is shown that the well-known forward-backward (F-B) and Viterbialgorithms for HMMs are special cases of more general inference algorithms forarbitrary PINs. Furthermore, the existence of inference and estimationalgorithms for more general graphical models provides a set of analysistools for HMM practitioners who wish to explore a richer class of HMMstructures.Examples of relatively complex models to handle sensorfusion and coarticulationin speech recognitionare introduced and treated within the graphical model framework toillustrate the advantages of the general approach.

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Testing constraints for real-time systems are usually verified through the satisfiability of propositional formulae. In this paper, we propose an alternative where the verification of timing constraints can be done by counting the number of truth assignments instead of boolean satisfiability. This number can also tell us how “far away” is a given specification from satisfying its safety assertion. Furthermore, specifications and safety assertions are often modified in an incremental fashion, where problematic bugs are fixed one at a time. To support this development, we propose an incremental algorithm for counting satisfiability. Our proposed incremental algorithm is optimal as no unnecessary nodes are created during each counting. This works for the class of path RTL. To illustrate this application, we show how incremental satisfiability counting can be applied to a well-known rail-road crossing example, particularly when its specification is still being refined.

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In 2000 the European Statistical Office published the guidelines for developing the Harmonized European Time Use Surveys system. Under such a unified framework, the first Time Use Survey of national scope was conducted in Spain during 2002– 03. The aim of these surveys is to understand human behavior and the lifestyle of people. Time allocation data are of compositional nature in origin, that is, they are subject to non-negativity and constant-sum constraints. Thus, standard multivariate techniques cannot be directly applied to analyze them. The goal of this work is to identify homogeneous Spanish Autonomous Communities with regard to the typical activity pattern of their respective populations. To this end, fuzzy clustering approach is followed. Rather than the hard partitioning of classical clustering, where objects are allocated to only a single group, fuzzy method identify overlapping groups of objects by allowing them to belong to more than one group. Concretely, the probabilistic fuzzy c-means algorithm is conveniently adapted to deal with the Spanish Time Use Survey microdata. As a result, a map distinguishing Autonomous Communities with similar activity pattern is drawn. Key words: Time use data, Fuzzy clustering; FCM; simplex space; Aitchison distance

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This paper proposes MSISpIC, a probabilistic sonar scan matching algorithm for the localization of an autonomous underwater vehicle (AUV). The technique uses range scans gathered with a Mechanical Scanning Imaging Sonar (MSIS), the robot displacement estimated through dead-reckoning using a Doppler velocity log (DVL) and a motion reference unit (MRU). The proposed method is an extension of the pIC algorithm. An extended Kalman filter (EKF) is used to estimate the robot-path during the scan in order to reference all the range and bearing measurements as well as their uncertainty to a scan fixed frame before registering. The major contribution consists of experimentally proving that probabilistic sonar scan matching techniques have the potential to improve the DVL-based navigation. The algorithm has been tested on an AUV guided along a 600 m path within an abandoned marina underwater environment with satisfactory results

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This paper proposes a pose-based algorithm to solve the full SLAM problem for an autonomous underwater vehicle (AUV), navigating in an unknown and possibly unstructured environment. The technique incorporate probabilistic scan matching with range scans gathered from a mechanical scanning imaging sonar (MSIS) and the robot dead-reckoning displacements estimated from a Doppler velocity log (DVL) and a motion reference unit (MRU). The proposed method utilizes two extended Kalman filters (EKF). The first, estimates the local path travelled by the robot while grabbing the scan as well as its uncertainty and provides position estimates for correcting the distortions that the vehicle motion produces in the acoustic images. The second is an augment state EKF that estimates and keeps the registered scans poses. The raw data from the sensors are processed and fused in-line. No priory structural information or initial pose are considered. The algorithm has been tested on an AUV guided along a 600 m path within a marina environment, showing the viability of the proposed approach

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The absolute necessity of obtaining 3D information of structured and unknown environments in autonomous navigation reduce considerably the set of sensors that can be used. The necessity to know, at each time, the position of the mobile robot with respect to the scene is indispensable. Furthermore, this information must be obtained in the least computing time. Stereo vision is an attractive and widely used method, but, it is rather limited to make fast 3D surface maps, due to the correspondence problem. The spatial and temporal correspondence among images can be alleviated using a method based on structured light. This relationship can be directly found codifying the projected light; then each imaged region of the projected pattern carries the needed information to solve the correspondence problem. We present the most significant techniques, used in recent years, concerning the coded structured light method

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Resumen tomado de la publicaci??n

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The paper discusses maintenance challenges of organisations with a huge number of devices and proposes the use of probabilistic models to assist monitoring and maintenance planning. The proposal assumes connectivity of instruments to report relevant features for monitoring. Also, the existence of enough historical registers with diagnosed breakdowns is required to make probabilistic models reliable and useful for predictive maintenance strategies based on them. Regular Markov models based on estimated failure and repair rates are proposed to calculate the availability of the instruments and Dynamic Bayesian Networks are proposed to model cause-effect relationships to trigger predictive maintenance services based on the influence between observed features and previously documented diagnostics

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This file contains the results of application of the model (4.6) and (4.8)

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El incumplimiento reiterado de la normatividad y políticas relacionadas con los tiempos de respuesta del proceso de contratación minera del país, desarrollado actualmente por la recién creada Agencia Nacional de Minería ANM, ha suscitado que la administración del recurso minero no se realice bajo los principios de eficiencia, eficacia, economía y celeridad. Estas debilidades manifiestas provocan represamientos en la resolución de trámites, congelación de áreas para contratar, sobrecostos, demoras en los tiempos de respuesta establecidos por la normatividad vigente y trae como consecuencia incertidumbre en los inversionistas mineros y pérdidas por concepto de recaudo de canon superficiario, entre otras. El objetivo del presente trabajo de investigación consiste en analizar el proceso de titulación minera de Colombia a partir de la filosofía de mejora continua desarrollado en la teoría de restricciones TOC (Theory Of Constraints), para poder identificar cuáles son los cuellos de botella que no permiten que el proceso fluya de manera adecuada y proponer alternativas de mejora, que con su implementación exploten y subordinen la limitaciones al sistema.

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This paper considers an overlapping generations model in which capital investment is financed in a credit market with adverse selection. Lenders’ inability to commit ex-ante not to bailout ex-post, together with a wealthy position of entrepreneurs gives rise to the soft budget constraint syndrome, i.e. the absence of liquidation of poor performing firms on a regular basis. This problem arises endogenously as a result of the interaction between the economic behavior of agents, without relying on political economy explanations. We found the problem more binding along the business cycle, providing an explanation to creditors leniency during booms in some LatinAmerican countries in the late seventies and early nineties.