While robots are extensively used in factories, our industry hasn't yet been able to prepare them for working in human environments - for instance in houses or in human-operated factories. The main obstacle to these applications lies in the amplitude of the uncertainty inherent to the environments humans are used to work in, and in the difficulty in programming robots to cope with it. For instance, in robot-oriented environments, robots can expect to find specific tools and objects in specific places. In a human environment, obstacles may force one to find a new way of holding a tool, and new objects appear continuously and need to be dealt with. As it proves difficult to build into robots the knowledge necessary for coping with uncertain environments, the robotics community is turning to the development of agents that acquire this knowledge progressively and that adapt to unexpected events. This thesis studies the problem of vision-based robotic grasping in uncertain environments. We aim to create an autonomous agent that develops grasping skills from experience, by interacting with objects and with other agents. To this end, we present a 3D object model for autonomous, visuomotor interaction. The model represents grasping strategies along with visual features that predict their applicability. It provides a robot with the ability to compute grasp parameters from visual observations. The agent acquires models interactively by manipulating objects, possibly imitating a teacher. With time, it becomes increasingly efficient at inferring grasps from visual evidence. This behavior relies on (1) a grasp model representing relative object-gripper configurations and their feasibility, and (2) a model of visual object structure, which aligns the grasp model to arbitrary object poses (3D positions and orientations). The visual model represents object edges or object faces in 3D by probabilistically encoding the spatial distribution of small segments of object edges or the distribution of small patches of object surface. A model is learned from a few segmented 3D scans or stereo images of an object. Monte Carlo simulation provides robust estimates of the object's 3D position and orientation in cluttered scenes. The grasp model represents the likelihood of success of relative object-gripper configurations. Initial models are acquired from visual cues or by observing a teacher. Models are then refined autonomously by ``playing' with objects and observing the effects of exploratory grasps. After the robot has learned a few object models, learning becomes a combination of cross-object generalization and interactive experience: grasping strategies are generalized across objects that share similar visual substructures; they are then adapted to new objects through autonomous exploration. The applicability of our model is supported by numerous examples of pose estimates in cluttered scenes, and by a robot platform that shows increasing grasping capabilities as it explores its environment.

Although Glass Fiber Reinforced Polymer (GFRP) has many potential advantages as reinforcement in concrete structures, the loss in tensile strength of the GFRP reinforcing bar can be significant when exposed to the high alkali environments. Much effort was made to estimate the durability performance of GFRP in concrete; however, it is widely believed the data from accelerated aging tests is not appropriate to predict the longer-term performance of GFRP reinforcing bars. The lack of validated long-term data is the major obstacle for broad application of GFRP reinforcement in civil engineering practices. The main purpose of this study is to evaluate the longer-term deterioration rate of GFRP bars embedded in concrete, and to develop an accurate model that can provide better information to predict the longer-term performance of GFRP bars. In previous studies performed by Trejo, three GFRP bar types (V1, V2, and P type) with two different diameters (16 and 19 mm [0.625, and 0.7 in. referred as #5 and #6, respectively]) provided by different manufacturers were embedded in concrete beams. After pre-cracking by bending tests, specimens were stored outdoors at the Riverside Campus of Texas A&M University in College Station, Texas. After 7 years of outdoor exposure, the GFRP bars were extracted from the concrete beams and tension tests were performed to estimate the residual tensile strength. Several physical tests were also performed to assess the potential changes in the material. It was found that the tensile capacity of the GFRP bars embedded in concrete decreased; however, no significant changes in modulus of elasticity (MOE) were observed. Using this data and limited data from the literature, a probabilistic capacity model was developed using Bayesian updating. The developed probabilistic capacity model appropriately accounts for statistical uncertainties, considering the influence of the missing variables and remaining error due to the inexact model form. In this study, the reduction in tensile strength of GFRP reinforcement embedded in concrete is a function of the diffusion rate of the resin matrix, bar diameter, and time. The probabilistic model predicts that smaller GFRP bars exhibit faster degradation in the tensile capacity than the larger GFRP bars. For the GFRP bars, the model indicates that the probability that the environmental reduction factor required by The American Concrete Institute (ACI) and the American Association of State Highway Transportation Officials (AASHTO) for the design of concrete structures containing GFRP reinforcement is below the required value is 0.4, 0.25, and 0.2 after 100 years for #3, #5, and #6, respectively. The ACI 440 and AASHTO design strength for smaller bars is likely not safe.

We analyze a self-assembly model of flexible DNA tiles and develop a theoretical description of possible assembly products. The model is based on flexible branched DNA junction molecules, which are designed in laboratories and could serve for performing computation. They are also building blocks for make of even more complex molecules or structures. The branched junction molecules are flexible with sticky ends on their arms. They are modeled with "tiles", which are star like graphs, and "tile types", which are functions that give information about the number of sticky ends. A complex is a structure that is obtained by gluing several tiles via their sticky ends. A complex without free sticky ends is called "complete complex". Complete complexes are our main interest. In most experiments, besides the desired end product, a lot of unwanted material also appears in the test tube (or pot). The idea is to use the proper proportions of tiles of different types. The set of vectors that represent these proper proportions is called the "spectrum" of the pot. We classify the types of pots according to the complexes they acan admit, and we can identify the class of each pot from the spectrum and affine spaces. We show that the spectrum is a convex polytope and give an algorithm (and a MAPLE code), which calculates it, and classify the pots in PTIME. In the second part of the dissertation, we approach molecular self-assembly from a graph theoretical point of view. We assign a star-like graph to each tile in a pot, which induces a "pot-graph". A pot-graph is a labeled multigraph corresponding to a given pot type, whose vertices represent tile types. The complexes can be represented by "complex-graphs", and each such graph is mapped homomorphically into a pot-graph. Therefore, the pot-graph can be used to distinguish between pot types according to the structure of the complexes that can be assembled. We begin the third part of the dissertation with a pot containing uniformly distributed DNA junction molecules capable of forming a cyclic graph structure, in which all possible Watson-Crick connections have already been established, and compute the expectation and the variance of the number of self-assembled cycles of any size. We also tested our theoretical results in wet lab experiments performed at Prof. Nadrian C. Seeman's laboratory at New York University. Our main concern was the probability of obtaining cyclic structures. We present the obtained results, which also helped in defining an important parameter for the theoretical model.

The number of pods per plant and the number of seeds per pod are the most variable yield components in winter oilseed rape (WOSR). The production of a seed is the combination of several physiological processes, namely formation of ovules and pollen grains, fertilization of the ovules and development of young embryos, any problem in these processes may result in seed abortion or pod abortion. Both the number of ovules per pod and the potential for the ovule to develop into a mature seed may depend on pod position in the plant architecture and time of appearance. The complex developmental pattern of WOSR makes it difficult to analyse.In this study, we first investigate the variability of the following yield components (a) ovules/pod, (b) seeds/pod, and (c) pods/axis in relation to two explanatory variables. These two variables include (1) flower and inflorescence position and (2) time of pod appearance, linked to the effect of assimilate availability. Based on the biological phenomena of flower fertility, we developed a probabilistic model to simulate the number of ovules per ovary and seeds per pod. The model can predict the number of pollen grains per flower and distinguish the factors that influence the yield. Field experiments were conducted in 2008 and 2009. The number and position of flowers that bloomed within the inflorescence were recorded based on observations every two to three days throughout the flowering season. Different trophic states were created by clipping the main stem or ramifications to investigate the effect of assimilate competition.The results indicate that the amount of available assimilates was the primary determinant of pod and seed production. The distribution of resources was significantly affected by both the positions of pods within an inflorescence and the position of inflorescences within a plant in WOSR. In addition, model estimation for distribution parameter of pollen grain number indicated that pollination limitation could influence the seed production. Furthermore, the ovule viability could result in the decrease of the number of pods and the number of seeds per pod at the distal position of inflorescence. The model of flower fertility could be a tool to study the strategy of improving seed yield in flowering plants

It is well acknowledged in the AI community that finding a good reward function for reinforcement learning is extremely challenging. Apprenticeship learning (AL) is a class of “learning from demonstration” techniques where the reward function of a Markov Decision Process (MDP) is unknown to the learning agent and the agent uses inverse reinforcement learning (IRL) methods to recover expert policy from a set of expert demonstrations. However, as the agent learns exclusively from observations, given a constraint on the probability of the agent running into unwanted situations, there is no verification, nor guarantee, for the learnt policy on the satisfaction of the restriction. In this dissertation, we study the problem of how to guide AL to learn a policy that is inherently safe while still meeting its learning objective. By combining formal methods with imitation learning, a Counterexample-Guided Apprenticeship Learning algorithm is proposed. We consider a setting where the unknown reward function is assumed to be a linear combination of a set of state features, and the safety property is specified in Probabilistic Computation Tree Logic (PCTL). By embedding probabilistic model checking inside AL, we propose a novel counterexample-guided approach that can ensure both safety and performance of the learnt policy. This algorithm guarantees that given some formal safety specification defined by probabilistic temporal logic, the learnt policy shall satisfy this specification. We demonstrate the effectiveness of our approach on several challenging AL scenarios where safety is essential.

abstract: This investigation is focused on the consideration of structural uncertainties in nearly-straight pipes conveying fluid and on the effects of these uncertainties on the dynamic response and stability of those pipes. Of interest more specifically are the structural uncertainties which affect directly the fluid flow and its feedback on the structural response, e.g., uncertainties on/variations of the inner cross-section and curvature of the pipe. Owing to the complexity of introducing such uncertainties directly in finite element models, it is desired to proceed directly at the level of modal models by randomizing simultaneously the appropriate mass, stiffness, and damping matrices. The maximum entropy framework is adopted to carry out the stochastic modeling of these matrices with appropriate symmetry constraints guaranteeing that the nature, e.g., divergence or flutter, of the bifurcation is preserved when introducing uncertainty. To support the formulation of this stochastic ROM, a series of finite element computations are first carried out for pipes with straight centerline but inner radius varying randomly along the pipe. The results of this numerical discovery effort demonstrate that the dominant effects originate from the variations of the exit flow speed, induced by the change in inner cross-section at the pipe end, with the uncertainty on the cross-section at other locations playing a secondary role. Relying on these observations, the stochastic reduced order model is constructed to model separately the uncertainty in inner cross-section at the pipe end and at other locations. Then, the fluid related mass, damping, and stiffness matrices of this stochastic reduced order model (ROM) are all determined from a single random matrix and a random variable. The predictions from this stochastic ROM are found to closely match the corresponding results obtained with the randomized finite element model. It is finally demonstrated that this stochastic ROM can easily be extended to account for the small effects due to uncertainty in pipe curvature. / Dissertation/Thesis / Masters Thesis Mechanical Engineering 2017

Le nombre de siliques par plante et le nombre de graines par silique sont les composantes du rendement du colza d'hiver qui présentent la plus grande variabilité. La production d'une graine résulte de la combinaison de plusieurs processus physiologiques, à savoir la formation des ovules et des grains de pollen, la fécondation des ovules et le développement de jeunes embryons. Un problème survenu à n’importe quelles des étapes peut entraîner l’avortement de graines ou de la silique. Le nombre potentiel d'ovules par silique et le nombre graines arrivant la maturité dépendraient de la position du dans l'architecture de plante et le temps de son apparition, mais le mode complexe de développement de colza rend difficile l’analyse des causes et effets.Dans cette étude, la variabilité des composantes du rendement suivantes est étudiée: (a) nombre d’ovules par silique, (b) nombre de graines par silique, et (c) nombre de siliques par axe en fonction d’une part, l’emplacement de la fleur dans l'inflorescence, et la position de cette dernière sur la tige, et l’autre part, le temps d'apparition de la silique, qui affectent la disponibilité d'assimilats. Basé sur les processus biologiques de la fertilité des fleurs, un modèle probabiliste est développé pour simuler le développement des graines. Le nombre de grains de pollen par fleur peut être déduit par le modèle et ainsi que les facteurs qui influent le rendement.Des expériences de terrain ont été menées en 2008 et 2009. Le nombre et la position des fleurs qui s'épanouissaient dans l'inflorescence ont été enregistrés sur la base des observations tous les deux à trois jours pendant la saison de floraison. Différents états trophiques ont été créés par tailler de la tige principale ou des ramifications à étudier l'effet de l'assimilation de la compétition.Les résultats montrent que la quantité d’assimilâtes disponibles a été le principal déterminant de la production de graines et de siliques. La répartition d’assimilâtes a été sensiblement affectée par l’emplacement de silique au sein d’une inflorescence et la location de l’inflorescence sur la tige colza. En outre, le paramètre de la distribution du nombre de pollen a indiqué que la production de graines pourrait être limitée par la pollinisation. La réduction de la viabilité des ovules pourrait entraîner la diminution du nombre de siliques et le nombre de graines par silique à l’extrémité de l'inflorescence. Le modèle proposé pourrait être un outil pour étudier la stratégie de l'amélioration du rendement des plantes à fleurs / The number of pods per plant and the number of seeds per pod are the most variable yield components in winter oilseed rape (WOSR). The production of a seed is the combination of several physiological processes, namely formation of ovules and pollen grains, fertilization of the ovules and development of young embryos, any problem in these processes may result in seed abortion or pod abortion. Both the number of ovules per pod and the potential for the ovule to develop into a mature seed may depend on pod position in the plant architecture and time of appearance. The complex developmental pattern of WOSR makes it difficult to analyse.In this study, we first investigate the variability of the following yield components (a) ovules/pod, (b) seeds/pod, and (c) pods/axis in relation to two explanatory variables. These two variables include (1) flower and inflorescence position and (2) time of pod appearance, linked to the effect of assimilate availability. Based on the biological phenomena of flower fertility, we developed a probabilistic model to simulate the number of ovules per ovary and seeds per pod. The model can predict the number of pollen grains per flower and distinguish the factors that influence the yield. Field experiments were conducted in 2008 and 2009. The number and position of flowers that bloomed within the inflorescence were recorded based on observations every two to three days throughout the flowering season. Different trophic states were created by clipping the main stem or ramifications to investigate the effect of assimilate competition.The results indicate that the amount of available assimilates was the primary determinant of pod and seed production. The distribution of resources was significantly affected by both the positions of pods within an inflorescence and the position of inflorescences within a plant in WOSR. In addition, model estimation for distribution parameter of pollen grain number indicated that pollination limitation could influence the seed production. Furthermore, the ovule viability could result in the decrease of the number of pods and the number of seeds per pod at the distal position of inflorescence. The model of flower fertility could be a tool to study the strategy of improving seed yield in flowering plants

Submitted by (ana.araujo@ufrpe.br) on 2016-06-28T15:42:47Z No. of bitstreams: 1 Danila Maria Almeida de Abreu Silva.pdf: 4560746 bytes, checksum: e5e26a41955264a16144ee035716e1fb (MD5) / Made available in DSpace on 2016-06-28T15:42:47Z (GMT). No. of bitstreams: 1 Danila Maria Almeida de Abreu Silva.pdf: 4560746 bytes, checksum: e5e26a41955264a16144ee035716e1fb (MD5) Previous issue date: 2013-04-04 / The toxinfections caused by eating food contaminated with the bacillus of Salmonella represents a major concern for public health and for large producers of pork and derivatives. The presence of any Salmonella serovar in foods is enough to classify it as unfit for consumption, both domestically and internationally. The Salmonella is a bacterium that affects the animal’s intestinal tract, causing malaise, weight loss and death in consequence of infection. For a study of the dynamics of spreading disease in swine are developed mathematical models that provide the state of the population regarding the infection. The proposed model describes the dynamics of a population over time, divided into three classes of states regarding the presence or absence of the bacillus of Salmonella: Susceptible, Latent and Infected. This dynamics is governed by a system of ordinary differential equations, perturbed by the presence of random factors that pose a risk of infection to the farm. These factors are characterized as white noise whose impact on the dynamics is controlled by two constant functions, T1 and T2. The solution to the system of differential equations is obtained by the Runge-Kutta method of approximating 2a order, computationally implemented and simulated in different scenarios. The average rates of birth and contact were drawn from the literature and used as basis for parameters in the mathematical model. The results of computer simulations to calculate the probability of a farm infection levels reach any given time and observing the rules of management and creation. / As toxinfecções causadas por ingestão de alimentos contaminados pelo bacilo da Salmonella representam uma grande preocupação para a saúde púublica e para as grandes produtoras de carne suína e derivados. A presença de qualquer sorovar de Salmonella em alimentos é o suficiente para classificá-lo como impróprio para consumo, tanto no mercado nacional quanto internacional. A Salmonella é uma bactéria que afeta o trato intestinal do animal, causando indisposição, perda de peso e , na maioria dos casos, morte em consequência da infecção. Para um estudo da dinâmica de espalhamento da doença em suinos, são desenvolvidos modelos matemáticos que fornecem o estado da população em relação à infecção. O modelo proposto descreve a dinâmica de uma população ao longo do tempo, dividida em três classes de estados em relação a presença ou não do bacilo da Salmonella: Suscetível , Latente e Infectado . Esta dinâmica é regida por um sistema de equações diferenciais ordinárias, perturbadas pela presença de fatores aleatórios que representam risco de infecção para a granja. Esses fatores são caracterizados como ruído branco cujo impacto na dinâmica é controlado por duas funções constantes, T1 e T2. A solução para o sistema de equações diferenciais é obtido através do Método Runge-Kutta de aproximação de 2a ordem, implementado computacionalmente e simulado em diferentes cenários. A taxas médias de contato e natalidade foram retiradas da literatura e usadas como parâmetros base para o modelo matemático. O resultado das simulações permitiram calcular a probabilidade de uma granja atingir quaisquer níveis de infecção dado o tempo e observadas as normas de manejo e criação.

Made available in DSpace on 2014-06-12T15:59:55Z (GMT). No. of bitstreams: 2 arquivo5803_1.pdf: 2496332 bytes, checksum: b4666e127bf620dbcb7437f9d83c2344 (MD5) license.txt: 1748 bytes, checksum: 8a4605be74aa9ea9d79846c1fba20a33 (MD5) Previous issue date: 2010 / Faculdade de Amparo à Ciência e Tecnologia do Estado de Pernambuco / A análise da segurança (Safety Assessment) é um processo bem conhecido que serve para garantir que as restrições de segurança de um sistema crítico sejam cumpridas. Dentro dele, a análise de segurança quantitativa lida com essas restrições em um contexto numérico (probabilístico). Os métodos de análise de segurança, como a tradicional Fault Tree Analysis (FTA), são utilizados no processo de avaliação da segurança quantitativo, seguindo as diretrizes de certificação (por exemplo, a ARP4761 Guia de Práticas Recomendadas da Aviação). No entanto, este método é geralmente custoso e requer muito tempo e esforço para validar um sistema como um todo, uma vez que para uma aeronave chegam a ser construídas, em média, 10.000 árvores de falha e também porque dependem fortemente das habilidades humanas para lidar com suas limitações temporais que restringem o âmbito e o nível de detalhe que a análise e os resultados podem alcançar. Por outro lado, as autoridades certificadoras também permitem a utilização da análise de Markov, que, embora seus modelos sejam mais poderosos que as árvores de falha, a indústria raramente adota esta análise porque seus modelos são mais complexos e difíceis de lidar. Diante disto, FTA tem sido amplamente utilizada neste processo, principalmente porque é conceitualmente mais simples e fácil de entender. À medida que a complexidade e o time-to-market dos sistemas aumentam, o interesse em abordar as questões de segurança durante as fases iniciais do projeto, ao invés de nas fases intermediárias/finais, tornou comum a adoção de projetos, ferramentas e técnicas baseados em modelos. Simulink é o exemplo padrão atualmente utilizado na indústria aeronáutica. Entretanto, mesmo neste cenário, as soluções atuais seguem o que os engenheiros já utilizavam anteriormente. Por outro lado, métodos formais que são linguagens, ferramentas e métodos baseados em lógica e matemática discreta e não seguem as abordagens da engenharia tradicional, podem proporcionar soluções inovadoras de baixo custo para engenheiros. Esta dissertação define uma estratégia para a avaliação quantitativa de segurança baseada na análise de Markov. Porém, em vez de lidar com modelos de Markov diretamente, usamos a linguagem formal Prism (uma especificação em Prism é semanticamente interpretada como um modelo de Markov). Além disto, esta especificação em Prism é extraída de forma sistemática a partir de um modelo de alto nível (diagramas Simulink anotados com lógicas de falha do sistema), através da aplicação de regras de tradução. A verificação sob o aspecto quantitativo dos requisitos de segurança do sistema é realizada utilizando o verificador de modelos de Prism, no qual os requisitos de segurança tornam-se fórmulas probabilísticas em lógica temporal. O objetivo imediato do nosso trabalho é evitar o esforço de se criar várias árvores de falhas até ser constatado que um requisito de segurança foi violado. Prism não constrói árvores de falha para chegar neste resultado. Ele simplesmente verifica de uma só vez se um requisito de segurança é satisfeito ou não no modelo inteiro. Finalmente, nossa estratégia é ilustrada com um sistema simples (um projeto-piloto), mas representativo, projetado pela Embraer

Předkládaná práce se zabývá problémem automatizované syntézy pravděpodobnostních systémů: máme-li rodinu Markovských řetězců, jak lze efektivně identifikovat ten který odpovídá zadané specifikaci? Takové rodiny často vznikají v nejrůznějších oblastech inženýrství při modelování systémů s neurčitostí a rozhodování i těch nejjednodušších syntézních otázek představuje NP-těžký problém. V dané práci my zkoumáme existující techniky založené na protipříklady řízené induktivní syntéze (counterexample-guided inductive synthesis, CEGIS) a na zjemňování abstrakce (counterexample-guided abstraction refinement, CEGAR) a navrhujeme novou integrovanou metodu pro pravděpodobnostní syntézu. Experimenty nad relevantními modely demonstrují, že navržená technika je nejenom srovnatelná s moderními metodami, ale ve většině případů dokáže výrazně překonat, někdy i o několik řádů, existující přístupy.