Extraction of Building Roof Contours From LiDAR Data Using a Markov-Random-Field-Based Approach

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Extração automática de contornos de telhados usando dados de varredura a laser e campos randômicos de Markov

This paper proposes a methodology for automatic extraction of building roof contours from a Digital Elevation Model (DEM), which is generated through the regularization of an available laser point cloud. The methodology is based on two steps. First, in order to detect high objects (buildings, trees etc.), the DEM is segmented through a recursive splitting technique and a Bayesian merging technique. The recursive splitting technique uses the quadtree structure for subdividing the DEM into homogeneous regions. In order to minimize the fragmentation, which is commonly observed in the results of the recursive splitting segmentation, a region merging technique based on the Bayesian framework is applied to the previously segmented data. The high object polygons are extracted by using vectorization and polygonization techniques. Second, the building roof contours are identified among all high objects extracted previously. Taking into account some roof properties and some feature measurements (e. g., area, rectangularity, and angles between principal axes of the roofs), an energy function was developed based on the Markov Random Field (MRF) model. The solution of this function is a polygon set corresponding to building roof contours and is found by using a minimization technique, like the Simulated Annealing (SA) algorithm. Experiments carried out with laser scanning DEM's showed that the methodology works properly, as it delivered roof contours with approximately 90% shape accuracy and no false positive was verified.

Variable parameter and double sampling (X)over-bar charts in the presence of correlation: The Markov chain approach

The general assumption under which the (X) over bar chart is designed is that the process mean has a constant in-control value. However, there are situations in which the process mean wanders. When it wanders according to a first-order autoregressive (AR (1)) model, a complex approach involving Markov chains and integral equation methods is used to evaluate the properties of the (X) over bar chart. In this paper, we propose the use of a pure Markov chain approach to study the performance of the (X) over bar chart. The performance of the chat (X) over bar with variable parameters and the (X) over bar with double sampling are compared. (C) 2011 Elsevier B.V. All rights reserved.

Novel zero-current-switching PWM converters

This paper presents a new family of pulsewidth-modulated (PWM) converters, featuring soft commutation of the semiconductors at zero current (ZC) in the transistors and zero voltage (ZV) in the rectifiers, Besides operating at constant frequency and with reduced commutation losses, these new converters have output characteristics similar to the hard-switching-PWM counterpart, which means that there is no circulating reactive energy that would cause large conduction losses, the new family of zero-current-switching (ZCS)-PWM converters is suitable for high-power applications using insulated gate bipolar transistors (IGBT's). The advantages of the new ZCS-PWM boast converter employing IGBT's, rated at 1.6 kW and operating at 20 kHz, are presented, This new ZCS operation can reduce the average total power dissipation in the semiconductors practically by half, when compared with the hard-switching method, This new ZCS-PWM boost converter is suitable for high-power applications using Ie;BT's in power-factor correction, the principle of operation, theoretical analysis, and experimental results of the new ZCS-PWM boost converter are provided in this paper to verify the performance of this new family of converters.

Power Factor Correction Boost Converter Based on the Three-State Switching Cell

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Métodos estatisticos em cadeias de Markov

Este trabalho tem como objetivo o estudo do comportamento assintótico da estatística de Pearson (1900), que é o aparato teórico do conhecido teste qui-quadrado ou teste x2 como também é usualmente denotado. Inicialmente estudamos o comportamento da distribuição da estatística qui-quadrado de Pearson (1900) numa amostra {X1, X2,...,Xn} quando n → ∞ e pi = pi0 , 8n. Em seguida detalhamos os argumentos usados em Billingley (1960), os quais demonstram a convergência em distribuição de uma estatística, semelhante a de Pearson, baseada em uma amostra de uma cadeia de Markov, estacionária, ergódica e com espaço de estados finitos S

Estimação paramétrica e não-paramétrica em modelos de markov ocultos

In this work we study the Hidden Markov Models with finite as well as general state space. In the finite case, the forward and backward algorithms are considered and the probability of a given observed sequence is computed. Next, we use the EM algorithm to estimate the model parameters. In the general case, the kernel estimators are used and to built a sequence of estimators that converge in L1-norm to the density function of the observable process

Estimador do Tipo Núcleo para Densidades Limites de Cadeias de Markov com Espaço de Estados Geral

In this work we studied the consistency for a class of kernel estimates of f f (.) in the Markov chains with general state space E C Rd case. This study is divided into two parts: In the first one f (.) is a stationary density of the chain, and in the second one f (x) v (dx) is the limit distribution of a geometrically ergodic chain

Modelagem dos algorítmos simples e Simulated Annealing por cadeias de Markov

Os Algoritmos Genético (AG) e o Simulated Annealing (SA) são algoritmos construídos para encontrar máximo ou mínimo de uma função que representa alguma característica do processo que está sendo modelado. Esses algoritmos possuem mecanismos que os fazem escapar de ótimos locais, entretanto, a evolução desses algoritmos no tempo se dá de forma completamente diferente. O SA no seu processo de busca trabalha com apenas um ponto, gerando a partir deste sempre um nova solução que é testada e que pode ser aceita ou não, já o AG trabalha com um conjunto de pontos, chamado população, da qual gera outra população que sempre é aceita. Em comum com esses dois algoritmos temos que a forma como o próximo ponto ou a próxima população é gerada obedece propriedades estocásticas. Nesse trabalho mostramos que a teoria matemática que descreve a evolução destes algoritmos é a teoria das cadeias de Markov. O AG é descrito por uma cadeia de Markov homogênea enquanto que o SA é descrito por uma cadeia de Markov não-homogênea, por fim serão feitos alguns exemplos computacionais comparando o desempenho desses dois algoritmos

Teoria da Ruína em um Modelo de Markov com dois Estados

In this work, we present a risk theory application in the following scenario: In each period of time we have a change in the capital of the ensurance company and the outcome of a two-state Markov chain stabilishs if the company pays a benece it heat to one of its policyholders or it receives a Hightimes c > 0 paid by someone buying a new policy. At the end we will determine once again by the recursive equation for expectation the time ruin for this company

Estimadores do tipo núcleo para a densidade de transição de uma cadeia de markov com espaço de estados geral

In this work, we studied the strong consistency for a class of estimates for a transition density of a Markov chain with general state space E ⊂ Rd. The strong ergodicity of the estimates for the density transition is obtained from the strong consistency of the kernel estimates for both the marginal density p(:) of the chain and the joint density q(., .). In this work the Markov chain is supposed to be homogeneous, uniformly ergodic and possessing a stationary density p(.,.)

Ergodicidade em cadeias de Markov não-homogêneas e cadeias de Markov com transições raras

The central objective of a study Non-Homogeneous Markov Chains is the concept of weak and strong ergodicity. A chain is weak ergodic if the dependence on the initial distribution vanishes with time, and it is strong ergodic if it is weak ergodic and converges in distribution. Most theoretical results on strong ergodicity assume some knowledge of the limit behavior of the stationary distributions. In this work, we collect some general results on weak and strong ergodicity for chains with space enumerable states, and also study the asymptotic behavior of the stationary distributions of a particular type of Markov Chains with finite state space, called Markov Chains with Rare Transitions

Stress Analysis in Platform-Switching Implants: A 3-Dimensional Finite Element Study

The aim of this study was to evaluate the influence of the platform-switching technique on stress distribution in implant, abutment, and pen-implant tissues, through a 3-dimensional finite element study. Three 3-dimensional mandibular models were fabricated using the Solid Works 2006 and InVesalius software. Each model was composed of a bone block with one implant 10 mm long and of different diameters (3.75 and 5.00 mm). The UCLA abutments also ranged in diameter from 5.00 mm to 4.1 mm. After obtaining the geometries, the models were transferred to the software FEMAP 10.0 for pre- and postprocessing of finite elements to generate the mesh, loading, and boundary conditions. A total load of 200 N was applied in axial (0 degrees), oblique (45 degrees), and lateral (90) directions. The models were solved by the software NeiNastran 9.0 and transferred to the software FEMAP 10.0 to obtain the results that were visualized through von Mises and maximum principal stress maps. Model A (implants with 3.75 mm/abutment with 4.1 mm) exhibited the highest area of stress concentration with all loadings (axial, oblique, and lateral) for the implant and the abutment. All models presented the stress areas at the abutment level and at the implant/abutment interface. Models B (implant with 5.0 mm/abutment with 5.0 mm) and C (implant with 5.0 mm/abutment with 4.1 mm) presented minor areas of stress concentration and similar distribution pattern. For the cortical bone, low stress concentration was observed in the pen-implant region for models B and C in comparison to model A. The trabecular bone exhibited low stress that was well distributed in models B and C. Model A presented the highest stress concentration. Model B exhibited better stress distribution. There was no significant difference between the large-diameter implants (models B and C).

Photoelastic Analysis of the Influence of Platform Switching on Stress Distribution in Implants

The aim of this study was to evaluate the stress distribution of platform switching implants using a photoelastic method. Three models were constructed of the photoelastic resin PL-2, with a single implant and a screw-retained implant-supported prosthesis. These models were Model A, platform 5.0 mm/abutment 4.1 mm; Model B, platform 4.1 mm/abutment 4.1 mm; and Model C, platform 5.00 mm/abutment 5.00 mm. Axial and oblique (45 degrees) loads of 100 N were applied using a Universal Testing Machine (EMIC DL 3000). Images were photographed with a digital camera and visualized with software (AdobePhotoshop) to facilitate the qualitative analysis. The highest stress concentrations were observed at the apical third of the 3 models. With the oblique load, the highest stress concentrations were located at the implant apex, opposite the load application. Stress concentrations decreased in the cervical region of Model A (platform switching), and Models A (platform switching) and C (conventional/wide-diameter) displayed similar stress magnitudes. Finally, Model B (conventional/regular diameter) displayed the highest stress concentrations of the models tested.

Platform Switching: Biomechanical Evaluation Using Three-Dimensional Finite Element Analysis

Purpose: The objective of this study was to evaluate, using three-dimensional finite element analysis (3D FEA), the stress distribution in peri-implant bone tissue, implants, and prosthetic components of implant-supported single crowns with the use of the platform-switching concept. Materials and Methods: Three 3D finite element models were created to replicate an external-hexagonal implant system with peri-implant bone tissue in which three different implant-abutment configurations were represented. In the regular platform (RP) group, a regular 4.1-mm-diameter abutment (UCLA) was connected to regular 4.1-mm-diameter implant. The platform-switching (PS) group was simulated by the connection of a wide implant (5.0 mm diameter) to a regular 4.1-mm-diameter UCLA abutment. In the wide-platform (WP) group, a 5.0-mm-diameter UCLA abutment was connected to a 5.0-mm-diameter implant. An occlusal load of 100 N was applied either axially or obliquely on the models using ANSYS software. Results: Both the increase in implant diameter and the use of platform switching played roles in stress reduction. The PS group presented lower stress values than the RP and WP groups for bone and implant. In the peri-implant area, cortical bone exhibited a higher stress concentration than the trabecular bone in all models and both loading situations. Under oblique loading, higher intensity and greater distribution of stress were observed than under axial loading. Platform switching reduced von Mises (17.5% and 9.3% for axial and oblique loads, respectively), minimum (compressive) (19.4% for axial load and 21.9% for oblique load), and maximum (tensile) principal stress values (46.6% for axial load and 26.7% for oblique load) in the peri-implant bone tissue. Conclusion: Platform switching led to improved biomechanical stress distribution in peri-implant bone tissue. Oblique loads resulted in higher stress concentrations than axial loads for all models. Wide-diameter implants had a large influence in reducing stress values in the implant system. INT J ORAL MAXILLOFAC IMPLANTS 2011;26:482-491