901 resultados para sensor location problem
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INTRODUCTION Vasospastic brain infarction is a devastating complication of aneurysmal subarachnoid hemorrhage (SAH). Using a probe for invasive monitoring of brain tissue oxygenation or blood flow is highly focal and may miss the site of cerebral vasospasm (CVS). Probe placement is based on the assumption that the spasm will occur either at the dependent vessel territory of the parent artery of the ruptured aneurysm or at the artery exposed to the focal thick blood clot. We investigated the likelihood of a focal monitoring sensor being placed in vasospasm or infarction territory on a hypothetical basis. METHODS From our database we retrospectively selected consecutive SAH patients with angiographically proven (day 7-14) severe CVS (narrowing of vessel lumen >50%). Depending on the aneurysm location we applied a standard protocol of probe placement to detect the most probable site of severe CVS or infarction. We analyzed whether the placement was congruent with existing CVS/infarction. RESULTS We analyzed 100 patients after SAH caused by aneurysms located in the following locations: MCA (n = 14), ICA (n = 30), A1CA (n = 4), AcoA or A2CA (n = 33), and VBA (n = 19). Sensor location corresponded with CVS territory in 93% of MCA, 87% of ICA, 76% of AcoA or A2CA, but only 50% of A1CA and 42% of VBA aneurysms. The focal probe was located inside the infarction territory in 95% of ICA, 89% of MCA, 78% of ACoA or A2CA, 50% of A1CA and 23% of VBA aneurysms. CONCLUSION The probability that a single focal probe will be situated in the territory of severe CVS and infarction varies. It seems to be reasonably accurate for MCA and ICA aneurysms, but not for ACA or VBA aneurysms.
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AMS subject classification: 90B80.
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This paper demonstrates the capabilities of wavelet transform (WT) for analyzing important features related to bottleneck activations and traffic oscillations in congested traffic in a systematic manner. In particular, the analysis of loop detector data from a freeway shows that the use of wavelet-based energy can effectively identify the location of an active bottleneck, the arrival time of the resulting queue at each upstream sensor location, and the start and end of a transition during the onset of a queue. Vehicle trajectories were also analyzed using WT and our analysis shows that the wavelet-based energies of individual vehicles can effectively detect the origins of deceleration waves and shed light on possible triggers (e.g., lane-changing). The spatiotemporal propagations of oscillations identified by tracing wavelet-based energy peaks from vehicle to vehicle enable analysis of oscillation amplitude, duration and intensity.
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In most materials, short stress waves are generated during the process of plastic deformation, phase transformation, crack formation and crack growth. These phenomena are applied in acoustic emission (AE) for the detection of material defects in a wide spectrum of areas, ranging from nondestructive testing for the detection of materials defects to monitoring of microseismical activity. AE technique is also used for defect source identification and for failure detection. AE waves consist of P waves (primary longitudinal waves), S waves (shear/transverse waves) and Rayleigh (surface) waves as well as reflected and diffracted waves. The propagation of AE waves in various modes has made the determination of source location difficult. In order to use acoustic emission technique for accurate identification of source, an understanding of wave propagation of the AE signals at various locations in a plate structure is essential. Furthermore, an understanding of wave propagation can also assist in sensor location for optimum detection of AE signals along with the characteristics of the source. In real life, as the AE signals radiate from the source it will result in stress waves. Unless the type of stress wave is known, it is very difficult to locate the source when using the classical propagation velocity equations. This paper describes the simulation of AE waves to identify the source location and its characteristics in steel plate as well as the wave modes. The finite element analysis (FEA) is used for the numerical simulation of wave propagation in thin plate. By knowing the type of wave generated, it is possible to apply the appropriate wave equations to determine the location of the source. For a single plate structure, the results show that the simulation algorithm is effective to simulate different stress waves.
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In most materials, short stress waves are generated during the process of plastic deformation, phase transformation, crack formation and crack growth. These phenomena are applied in acoustic emission (AE) for the detection of material defects in wide spectrum areas, ranging from non-destructive testing for the detection of materials defects to monitoring of microeismical activity. AE technique is also used for defect source identification and for failure detection. AE waves consist of P waves (primary/longitudinal waves), S waves (shear/transverse waves) and Rayleight (surface) waves as well as reflected and diffracted waves. The propagation of AE waves in various modes has made the determination of source location difficult. In order to use the acoustic emission technique for accurate identification of source location, an understanding of wave propagation of the AE signals at various locations in a plate structure is essential. Furthermore, an understanding of wave propagation can also assist in sensor location for optimum detection of AE signals. In real life, as the AE signals radiate from the source it will result in stress waves. Unless the type of stress wave is known, it is very difficult to locate the source when using the classical propagation velocity equations. This paper describes the simulation of AE waves to identify the source location in steel plate as well as the wave modes. The finite element analysis (FEA) is used for the numerical simulation of wave propagation in thin plate. By knowing the type of wave generated, it is possible to apply the appropriate wave equations to determine the location of the source. For a single plate structure, the results show that the simulation algorithm is effective to simulate different stress waves.
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Reliable robotic perception and planning are critical to performing autonomous actions in uncertain, unstructured environments. In field robotic systems, automation is achieved by interpreting exteroceptive sensor information to infer something about the world. This is then mapped to provide a consistent spatial context, so that actions can be planned around the predicted future interaction of the robot and the world. The whole system is as reliable as the weakest link in this chain. In this paper, the term mapping is used broadly to describe the transformation of range-based exteroceptive sensor data (such as LIDAR or stereo vision) to a fixed navigation frame, so that it can be used to form an internal representation of the environment. The coordinate transformation from the sensor frame to the navigation frame is analyzed to produce a spatial error model that captures the dominant geometric and temporal sources of mapping error. This allows the mapping accuracy to be calculated at run time. A generic extrinsic calibration method for exteroceptive range-based sensors is then presented to determine the sensor location and orientation. This allows systematic errors in individual sensors to be minimized, and when multiple sensors are used, it minimizes the systematic contradiction between them to enable reliable multisensor data fusion. The mathematical derivations at the core of this model are not particularly novel or complicated, but the rigorous analysis and application to field robotics seems to be largely absent from the literature to date. The techniques in this paper are simple to implement, and they offer a significant improvement to the accuracy, precision, and integrity of mapped information. Consequently, they should be employed whenever maps are formed from range-based exteroceptive sensor data. © 2009 Wiley Periodicals, Inc.
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This article addresses the problem of how to select the optimal combination of sensors and how to determine their optimal placement in a surveillance region in order to meet the given performance requirements at a minimal cost for a multimedia surveillance system. We propose to solve this problem by obtaining a performance vector, with its elements representing the performances of subtasks, for a given input combination of sensors and their placement. Then we show that the optimal sensor selection problem can be converted into the form of Integer Linear Programming problem (ILP) by using a linear model for computing the optimal performance vector corresponding to a sensor combination. Optimal performance vector corresponding to a sensor combination refers to the performance vector corresponding to the optimal placement of a sensor combination. To demonstrate the utility of our technique, we design and build a surveillance system consisting of PTZ (Pan-Tilt-Zoom) cameras and active motion sensors for capturing faces. Finally, we show experimentally that optimal placement of sensors based on the design maximizes the system performance.
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Many problems in control and signal processing can be formulated as sequential decision problems for general state space models. However, except for some simple models one cannot obtain analytical solutions and has to resort to approximation. In this thesis, we have investigated problems where Sequential Monte Carlo (SMC) methods can be combined with a gradient based search to provide solutions to online optimisation problems. We summarise the main contributions of the thesis as follows. Chapter 4 focuses on solving the sensor scheduling problem when cast as a controlled Hidden Markov Model. We consider the case in which the state, observation and action spaces are continuous. This general case is important as it is the natural framework for many applications. In sensor scheduling, our aim is to minimise the variance of the estimation error of the hidden state with respect to the action sequence. We present a novel SMC method that uses a stochastic gradient algorithm to find optimal actions. This is in contrast to existing works in the literature that only solve approximations to the original problem. In Chapter 5 we presented how an SMC can be used to solve a risk sensitive control problem. We adopt the use of the Feynman-Kac representation of a controlled Markov chain flow and exploit the properties of the logarithmic Lyapunov exponent, which lead to a policy gradient solution for the parameterised problem. The resulting SMC algorithm follows a similar structure with the Recursive Maximum Likelihood(RML) algorithm for online parameter estimation. In Chapters 6, 7 and 8, dynamic Graphical models were combined with with state space models for the purpose of online decentralised inference. We have concentrated more on the distributed parameter estimation problem using two Maximum Likelihood techniques, namely Recursive Maximum Likelihood (RML) and Expectation Maximization (EM). The resulting algorithms can be interpreted as an extension of the Belief Propagation (BP) algorithm to compute likelihood gradients. In order to design an SMC algorithm, in Chapter 8 uses a nonparametric approximations for Belief Propagation. The algorithms were successfully applied to solve the sensor localisation problem for sensor networks of small and medium size.
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Um dos problemas mais relevantes em organizações de grande porte é a escolha de locais para instalação de plantas industriais, centros de distribuição ou mesmo pontos comerciais. Esse problema logístico é uma decisão estratégica que pode causar um impacto significativo no custo total do produto comercializado. Existem na literatura diversos trabalhos que abordam esse problema. Assim, o objetivo desse trabalho é analisar o problema da localização de instalações proposto por diferentes autores e definir um modelo que seja o mais adequado possível ao mercado de distribuição de combustíveis no Brasil. Para isso, foi realizada uma análise do fluxo de refino e distribuição praticado neste segmento e da formação do respectivo custo de transporte. Foram consideradas restrições como capacidade de estoque, gama de produtos ofertados e níveis da hierarquia de distribuição. A partir dessa análise, foi definido um modelo matemático aplicado à redução dos custos de frete considerando-se a carga tributária. O modelo matemático foi implementado, em linguagem C, e permite simular o problema. Foram aplicadas técnicas de computação paralela visando reduzir o tempo de execução do algoritmo. Os resultados obtidos com o modelo Single Uncapacited Facility Location Problem (SUFLP) simulado nas duas versões do programa, sequencial e paralela, demonstram ganhos de até 5% em economia de custos e redução do tempo de execução em mais de 50%.
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介绍了一种新型的移动机器人激光全局定位系统。重点讨论了结构化环境中移动机器人的全局定位方法 ,提出了一种新的基于最小二乘法的迭代搜索定位算法。全方位移动机器人平台上进行的定位实验 ,证实了该算法的有效性。
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La calidad de energía eléctrica incluye la calidad del suministro y la calidad de la atención al cliente. La calidad del suministro a su vez se considera que la conforman dos partes, la forma de onda y la continuidad. En esta tesis se aborda la continuidad del suministro a través de la localización de faltas. Este problema se encuentra relativamente resuelto en los sistemas de transmisión, donde por las características homogéneas de la línea, la medición en ambos terminales y la disponibilidad de diversos equipos, se puede localizar el sitio de falta con una precisión relativamente alta. En sistemas de distribución, sin embargo, la localización de faltas es un problema complejo y aún no resuelto. La complejidad es debida principalmente a la presencia de conductores no homogéneos, cargas intermedias, derivaciones laterales y desbalances en el sistema y la carga. Además, normalmente, en estos sistemas sólo se cuenta con medidas en la subestación, y un modelo simplificado del circuito. Los principales esfuerzos en la localización han estado orientados al desarrollo de métodos que utilicen el fundamental de la tensión y de la corriente en la subestación, para estimar la reactancia hasta la falta. Como la obtención de la reactancia permite cuantificar la distancia al sitio de falta a partir del uso del modelo, el Método se considera Basado en el Modelo (MBM). Sin embargo, algunas de sus desventajas están asociadas a la necesidad de un buen modelo del sistema y a la posibilidad de localizar varios sitios donde puede haber ocurrido la falta, esto es, se puede presentar múltiple estimación del sitio de falta. Como aporte, en esta tesis se presenta un análisis y prueba comparativa entre varios de los MBM frecuentemente referenciados. Adicionalmente se complementa la solución con métodos que utilizan otro tipo de información, como la obtenida de las bases históricas de faltas con registros de tensión y corriente medidos en la subestación (no se limita solamente al fundamental). Como herramienta de extracción de información de estos registros, se utilizan y prueban dos técnicas de clasificación (LAMDA y SVM). Éstas relacionan las características obtenidas de la señal, con la zona bajo falta y se denominan en este documento como Métodos de Clasificación Basados en el Conocimiento (MCBC). La información que usan los MCBC se obtiene de los registros de tensión y de corriente medidos en la subestación de distribución, antes, durante y después de la falta. Los registros se procesan para obtener los siguientes descriptores: a) la magnitud de la variación de tensión ( dV ), b) la variación de la magnitud de corriente ( dI ), c) la variación de la potencia ( dS ), d) la reactancia de falta ( Xf ), e) la frecuencia del transitorio ( f ), y f) el valor propio máximo de la matriz de correlación de corrientes (Sv), cada uno de los cuales ha sido seleccionado por facilitar la localización de la falta. A partir de estos descriptores, se proponen diferentes conjuntos de entrenamiento y validación de los MCBC, y mediante una metodología que muestra la posibilidad de hallar relaciones entre estos conjuntos y las zonas en las cuales se presenta la falta, se seleccionan los de mejor comportamiento. Los resultados de aplicación, demuestran que con la combinación de los MCBC con los MBM, se puede reducir el problema de la múltiple estimación del sitio de falta. El MCBC determina la zona de falta, mientras que el MBM encuentra la distancia desde el punto de medida hasta la falta, la integración en un esquema híbrido toma las mejores características de cada método. En este documento, lo que se conoce como híbrido es la combinación de los MBM y los MCBC, de una forma complementaria. Finalmente y para comprobar los aportes de esta tesis, se propone y prueba un esquema de integración híbrida para localización de faltas en dos sistemas de distribución diferentes. Tanto los métodos que usan los parámetros del sistema y se fundamentan en la estimación de la impedancia (MBM), como aquellos que usan como información los descriptores y se fundamentan en técnicas de clasificación (MCBC), muestran su validez para resolver el problema de localización de faltas. Ambas metodologías propuestas tienen ventajas y desventajas, pero según la teoría de integración de métodos presentada, se alcanza una alta complementariedad, que permite la formulación de híbridos que mejoran los resultados, reduciendo o evitando el problema de la múltiple estimación de la falta.
Energy exchange in a dense urban environment Part II: impact of spatial heterogeneity of the surface
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The centre of cities, characterised by spatial and temporal complexity, are challenging environments for micrometeorological research. This paper considers the impact of sensor location and heterogeneity of the urban surface on flux observations in the dense city centre of London, UK. Data gathered at two sites in close vicinity, but with different measurement heights, were analysed to investigate the influence of source area characteristics on long-term radiation and turbulent heat fluxes. Combining consideration of diffuse radiation and effects of specular reflections, the non-Lambertian urban surface is found to impact the measurements of surface albedo. Comparisons of observations from the two sites reveal that turbulent heat fluxes are similar under some flow conditions. However, they mostly observe processes at different scales due to their differing measurement heights, highlighting the critical impact of siting sensors in urban areas. A detailed source area analysis is presented to investigate the surface controls influencing the energy exchanges at the different scales
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We consider the two-level network design problem with intermediate facilities. This problem consists of designing a minimum cost network respecting some requirements, usually described in terms of the network topology or in terms of a desired flow of commodities between source and destination vertices. Each selected link must receive one of two types of edge facilities and the connection of different edge facilities requires a costly and capacitated vertex facility. We propose a hybrid decomposition approach which heuristically obtains tentative solutions for the vertex facilities number and location and use these solutions to limit the computational burden of a branch-and-cut algorithm. We test our method on instances of the power system secondary distribution network design problem. The results show that the method is efficient both in terms of solution quality and computational times. (C) 2010 Elsevier Ltd. All rights reserved.
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Optimal location on the transport infrastructure is the preferable requirement for many decision making processes. Most studies have focused on evaluating performances of optimally locate p facilities by minimizing their distances to a geographically distributed demand (n) when p and n vary. The optimal locations are also sensitive to geographical context such as road network, especially when they are asymmetrically distributed in the plane. The influence of alternating road network density is however not a very well-studied problem especially when it is applied in a real world context. This paper aims to investigate how the density level of the road network affects finding optimal location by solving the specific case of p-median location problem. A denser network is found needed when a higher number of facilities are to locate. The best solution will not always be obtained in the most detailed network but in a middle density level. The solutions do not further improve or improve insignificantly as the density exceeds 12,000 nodes, some solutions even deteriorate. The hierarchy of the different densities of network can be used according to location and transportation purposes and increase the efficiency of heuristic methods. The method in this study can be applied to other location-allocation problem in transportation analysis where the road network density can be differentiated.
Brazilian international and inter-state trade flows: an exploratory analysis using the gravity model
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Recent efforts toward a world with freer trade, like WTO/GATT or regional Preferential Trade Agreements(PTAs), were put in doubt after McCallum's(1995) finding of a large border effect between US and Canadian provinces. Since then, there has been a great amount of research on this topic employing the gravity equation. This dissertation has two goals. The first goal is to review comprehensively the recent literature about the gravity equation, including its usages, econometric specifications, and the efforts to provide it with microeconomic foundations. The second goal is the estimation of the Brazilian border effect (or 'home-bias trade puzzle') using inter-state and international trade flow data. It is used a pooled cross-section Tobit model. The lowest border effect estimated was 15, which implies that Brazilian states trade among themselves 15 times more than they trade with foreign countries. Further research using industry disaggregated data is needed to qualify the estimated border effect with respect to which part of that effect can be attributed to actual trade costs and which part is the outcome of the endogenous location problem of the firm.