359 research outputs found

    Skeletonization and segmentation of binary voxel shapes

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    Preface. This dissertation is the result of research that I conducted between January 2005 and December 2008 in the Visualization research group of the Technische Universiteit Eindhoven. I am pleased to have the opportunity to thank a number of people that made this work possible. I owe my sincere gratitude to Alexandru Telea, my supervisor and first promotor. I did not consider pursuing a PhD until my Master’s project, which he also supervised. Due to our pleasant collaboration from which I learned quite a lot, I became convinced that becoming a doctoral student would be the right thing to do for me. Indeed, I can say it has greatly increased my knowledge and professional skills. Alex, thank you for our interesting discussions and the freedom you gave me in conducting my research. You made these four years a pleasant experience. I am further grateful to Jack vanWijk, my second promotor. Our monthly discussions were insightful, and he continuously encouraged me to take a more formal and scientific stance. I would also like to thank Prof. Jan de Graaf from the department of mathematics for our discussions on some of my conjectures. His mathematical rigor was inspiring. I am greatly indebted to the Netherlands Organisation for Scientific Research (NWO) for funding my PhD project (grant number 612.065.414). I thank Prof. Kaleem Siddiqi, Prof. Mark de Berg, and Dr. Remco Veltkamp for taking part in the core doctoral committee and Prof. Deborah Silver and Prof. Jos Roerdink for participating in the extended committee. Our Visualization group provides a great atmosphere to do research in. In particular, I would like to thank my fellow doctoral students Frank van Ham, Hannes Pretorius, Lucian Voinea, Danny Holten, Koray Duhbaci, Yedendra Shrinivasan, Jing Li, NielsWillems, and Romain Bourqui. They enabled me to take my mind of research from time to time, by discussing political and economical affairs, and more trivial topics. Furthermore, I would like to thank the senior researchers of our group, Huub van de Wetering, Kees Huizing, and Michel Westenberg. In particular, I thank Andrei Jalba for our fruitful collaboration in the last part of my work. On a personal level, I would like to thank my parents and sister for their love and support over the years, my friends for providing distractions outside of the office, and Michelle for her unconditional love and ability to light up my mood when needed

    Tree rules in probabilistic transition system specifications with negative and quantitative premises

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    Probabilistic transition system specifications (PTSSs) in the ntmufnu/ntmuxnu format provide structural operational semantics for Segala-type systems that exhibit both probabilistic and nondeterministic behavior and guarantee that isimilarity is a congruence.Similar to the nondeterministic case of rule format tyft/tyxt, we show that the well-foundedness requirement is unnecessary in the probabilistic setting. To achieve this, we first define an extended version of the ntmufnu/ntmuxnu format in which quantitative premises and conclusions include nested convex combinations of distributions. This format also guarantees that bisimilarity is a congruence. Then, for a given (possibly non-well-founded) PTSS in the new format, we construct an equivalent well-founded transition system consisting of only rules of the simpler (well-founded) probabilistic ntree format. Furthermore, we develop a proof-theoretic notion for these PTSSs that coincides with the existing stratification-based meaning in case the PTSS is stratifiable. This continues the line of research lifting structural operational semantic results from the nondeterministic setting to systems with both probabilistic and nondeterministic behavior.Comment: In Proceedings EXPRESS/SOS 2012, arXiv:1208.244

    Robust Classification and Analysis of Anatomical Surfaces Using 3D Skeletons

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    Robust Classification and Analysis of Anatomical Surfaces Using 3D Skeletons

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    Efficiently enforcing mutual state exclusion requirements in symbolic supervisor synthesis

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    Given a model of an uncontrolled system and a requirement specification, a supervisory controller can be synthesized so that the system under control adheres to the requirements. There are several ways in which informal behavioral safety requirements can be formalized, one of which is using mutual state exclusion requirements. In current implementations of the supervisor synthesis algorithm, synthesis may be inefficient when mutual state exclusion requirements are used. We propose a method to efficiently enforce these requirements in supervisor synthesis. We consider symbolic supervisor synthesis, where Binary Decision Diagrams are used to represent the system. The efficiency of the proposed method is evaluated by means of an industrial and academic case study

    Robustness of Equations Under Operational Extensions

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    Sound behavioral equations on open terms may become unsound after conservative extensions of the underlying operational semantics. Providing criteria under which such equations are preserved is extremely useful; in particular, it can avoid the need to repeat proofs when extending the specified language. This paper investigates preservation of sound equations for several notions of bisimilarity on open terms: closed-instance (ci-)bisimilarity and formal-hypothesis (fh-)bisimilarity, both due to Robert de Simone, and hypothesis-preserving (hp-)bisimilarity, due to Arend Rensink. For both fh-bisimilarity and hp-bisimilarity, we prove that arbitrary sound equations on open terms are preserved by all disjoint extensions which do not add labels. We also define slight variations of fh- and hp-bisimilarity such that all sound equations are preserved by arbitrary disjoint extensions. Finally, we give two sets of syntactic criteria (on equations, resp. operational extensions) and prove each of them to be sufficient for preserving ci-bisimilarity.Comment: In Proceedings EXPRESS'10, arXiv:1011.601

    Uncertainty-based decision-making in fire safety: Analyzing the alternatives

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    Large accidents throughout the 20th century marked the development of safety fields in engineering, devoted to better identify hazards, understand risks and properly manage them. As these fields evolved rather quickly and moved from a compliance to a risk-based approach, a significant delay in this transition was experienced in fire safety engineering (FSE). Devastating fires well into the 21st century and the restrictive nature of prescriptive codes signaled the need to transition towards a performance-based one. A performance-based approach provides flexibility and capitalizes on learning from accidental events and engineering disciplines such as process safety and FSE. This work provides an overview of the main alternatives to account for uncertainty in safety studies within the context of FSE, including traditional probabilistic analyses and emerging approaches such as strength of knowledge. A simple example is used to illustrate the impact of the uncertainty analysis on the results of a simple fire safety assessment. A structured evaluation is performed on each alternative to assess its ease of implementation and communication. The outcome is a compendium of advantages and disadvantages of the alternatives that constitute a toolbox for fire safety engineers to configure and use within their fire risk assessments. Process safety engineers are expected to gain an understanding of the similar and important challenges of FSE, being it directly relevant for process risk management and fire risk management in administrative buildings

    Detection and Isolation of Small Faults in Lithium-Ion Batteries via the Asymptotic Local Approach

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    This contribution presents a diagnosis scheme for batteries to detect and isolate internal faults in the form of small parameter changes. This scheme is based on an electrochemical reduced-order model of the battery, which allows the inclusion of physically meaningful faults that might affect the battery performance. The sensitivity properties of the model are analyzed. The model is then used to compute residuals based on an unscented Kalman filter. Primary residuals and a limiting covariance matrix are obtained thanks to the local approach, allowing for fault detection and isolation by chi-squared statistical tests. Results show that faults resulting in limited 0.15% capacity and 0.004% power fade can be effectively detected by the local approach. The algorithm is also able to correctly isolate faults related with sensitive parameters, whereas parameters with low sensitivity or linearly correlated are more difficult to precise.Comment: 8 pages, 2 figures, 3 tables, conferenc
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