In reinforcement learning, least-squares temporal difference methods (e.g., LSTD and LSPI) are effective, data-efficient techniques for policy evaluation and control with linear value function approximation. these alg...
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the proceedings contain 33 papers. the topics discussed include: tests, proofs and refinements;formal verification and biology;trust and automation in verification tools;CTL model-checking with graded quantifiers;gene...
ISBN:
(纸本)354088386X
the proceedings contain 33 papers. the topics discussed include: tests, proofs and refinements;formal verification and biology;trust and automation in verification tools;CTL model-checking with graded quantifiers;genetic programming and model checking: synthesizing new mutual exclusion algorithms;computation tree regular logic for genetic regulatory networks;compositional verification for component-based systems and application;a direct algorithm for multi-valued bounded model checking;model checking recursive programs with exact predicate abstraction;loop summarization using abstract transformers;automating algebraic specifications of non-freely generated data types;interpolants for linear arithmetic in SMT;controllable test cases for the distributed test architecture;and a dynamic assertion-based verification platform for validation of UML designs.
the paper presents a novel application of the shadowed clustering algorithm for uncertainty modeling and CT scan image segmentation. the core, shadowed and the exclusion regions, generated via shadowed c-means (SCM), ...
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ISBN:
(纸本)9783540884231
the paper presents a novel application of the shadowed clustering algorithm for uncertainty modeling and CT scan image segmentation. the core, shadowed and the exclusion regions, generated via shadowed c-means (SCM), quantize the ambiguity into three zones. this leads to faster convergence and reduced computational complexity. It is observed that SCM generates the best prototypes even in the presence of noise, thereby producing the best approximation of a structure in the unsupervised mode. A comparison with rough-fuzzy clustering algorithm reveals the automatic determination of the threshold and absence of externally tuned parameters in SCM. Experiments suggest that SCM is better suited for extraction of regions under vascular insult in the brain via pixel clustering. the relative efficacy of SCM in brain infarction diagnosis is validated by expert radiologists.
In this paper a further step towards a novel approach to adaptive nonlinear control developed at Budapest Tech in the past few years is reported. Its main advantage in comparison withthe complicated Lyapunov function...
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ISBN:
(纸本)9781424428755
In this paper a further step towards a novel approach to adaptive nonlinear control developed at Budapest Tech in the past few years is reported. Its main advantage in comparison withthe complicated Lyapunov function based techniques is that its fundament is some simple geometric consideration allowing to formulate the control task as a Fixed Point Problem for the solution of which various Contractive Mappings can be created that generate Iterative Cauchy Sequences for Single Input - Single Output (SISO) systems. these sequences can converge to the fixed points that are the solutions of the control tasks. Recently alternative potential solutions were proposed and sketched by the use of special functions built up of the "response function" of the excited system under control. these functions have almost constant values apart from a finite region in which they have a "wrinkle" in the vicinity of the desired solution that is the "proper" fixed point of these functions. It was shown that at one of their sides these fixed points were repulsive, while at the opposite side they were attractive. It was shown, too, that at the repulsive side another, so called "false" fixed points were present that were globally attractive, withthe exception of the basins of attraction of the "proper" ones. this structure seemed to be advantageous because no divergences could occur in the iterations, the convergence to the "false" values could easily be detected, and by using some ancillary tricks in the most of the cases the solutions could be kicked from the wrong fixed points into the basins of attraction of the "proper ones". It was expected that via adding simple rules to the application of these transformations good adaptive control can be developed. However, due to certain specialties of these functions practical problems arose. In the present paper novel transformations are presented that seem to evade these difficulties. their applicability is illustrated via simulations in the ad
In distributed environments, the shared resources access control by mutual exclusion paradigm is a recurrent key problem. To cope withthe new constraints implied by recently developed large scale distributed systems ...
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ISBN:
(纸本)9783540688549
In distributed environments, the shared resources access control by mutual exclusion paradigm is a recurrent key problem. To cope withthe new constraints implied by recently developed large scale distributed systems like grids, mutual exclusion algorithms become more and more complex and thus much harder to prove and/or verify. In this article, we propose the formal modeling and the verification of a new generic hierarchical approach. this approach is based on the composition of classical already proof checked distributed algorithms. It overcomes some limitations of these classical algorithms by taking into account the network topology latencies and have a high scalability where centralized ones don't. We also have formalized the properties of the mutual exclusion paradigm in order to verify them against our solution. We prove that our compositional approach preserves theses properties under the assumption that all used plain algorithms assert them. this verification by formal method checkers was eased by the efficient use of already proved mutual exclusion algorithms and the reduction of state spaces by exploiting the symmetries.
this book constitutes the refereed proceedings of the 6thinternational Workshop on Ant Colony Optimization and Swarm Intelligence, ANTS 2008, held in Brussels, Belgium, in September 2008. the 17 revised full papers, ...
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ISBN:
(数字)9783540875277
ISBN:
(纸本)9783540875260
this book constitutes the refereed proceedings of the 6thinternational Workshop on Ant Colony Optimization and Swarm Intelligence, ANTS 2008, held in Brussels, Belgium, in September 2008. the 17 revised full papers, 24 revised short papers, and 10 extended abstracts presented were carefully reviewed and selected from 91 submissions. the papers cover theoretical and foundational aspects of computational intelligence and related disciplines with special focus on swarm intelligence and are devoted to behavioral models of social insects and new algorithmic approaches, empirical and theoretical research in swarm intelligence, applications such as ant colony optimization or particle swarm optimization, and theoretical and experimental research in swarm robotics systems.
this paper deals with an image compression algorithm based on the three- dimensional Karhunen- Loeve transform (3D KLT), whose task is to reduce time redundancy for an image data. there are many cases for which the re...
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ISBN:
(纸本)9780819473790
this paper deals with an image compression algorithm based on the three- dimensional Karhunen- Loeve transform (3D KLT), whose task is to reduce time redundancy for an image data. there are many cases for which the reduction of time redundancy is very efficient and brings perceptible bitstream reduction. this is very desirable for transfering image data through telephone links, GSM networks etc. the time redundancy is very perceptible e. g. in camera security systems where relative unchanging frames are very conventional. the time evolution of grabbed scene is reviews according an energy content in eigenimages. these eigenimages are obtained in KLT for a suitable number of incoming frames. Required number of transfered eigenimages and eigenvectors is determined on the basis of the energy content in eigenimages.
A major concern about distance-vector routing protocols for wireless mesh networks is its slow convergence in the presence of link changes, which can potentially degrade network stability. this paper studies the impac...
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this paper presents Depth Image-Based Haptic Rendering (DIBHR), a haptic rendering algorithm that enables users to haptically explore 3D video media based on depth image-based representation (DIBR). the algorithm comp...
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ISBN:
(纸本)9783540690566
this paper presents Depth Image-Based Haptic Rendering (DIBHR), a haptic rendering algorithm that enables users to haptically explore 3D video media based on depth image-based representation (DIBR). the algorithm computes the shortest proxy (god-object) path along which the proxy goes into the local distance minimum to the goal (haptic interaction point) constrained on surface in order to obtain correct friction force when the friction cone algorithm is applied. this algorithm is based on the god-object [3] concept and adopted the neighborhood search algorithm [5][6]. the experiments compare DIBHR with two previous algorithms [5][6] as per computation time and smoothness of resultant force rendering. the results show slower computation time yet within 1 millisecond and smoother force with friction.
作者：
Simon, ElfriedeSiemens AG
Corporate Research and Technology Power and Sensor Systems Otto-Hahn-Ring 6 D-81739 Munich Germany
Within the coming decades there will be a need for improved personal healthcare. Sensor systems can provide cost-effective solutions and applications, and can lead to a shift of healthcare from specialized and provide...
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ISBN:
(纸本)9780889867215
Within the coming decades there will be a need for improved personal healthcare. Sensor systems can provide cost-effective solutions and applications, and can lead to a shift of healthcare from specialized and provider centric actually existing approaches towards proactive, integrated, and patient centric solutions. the integration of complex functionalities into small sensor systems is the leverage to robust functionality and limitation in price. Since medieval times it is well known that the smell of the body odour of humans or of the exhaled air gives an indication for the presence of a disease. the detection of certain marker gases in breath as a simple and non invasive method, and the correlation to malfunction of the respiratory tract, metabolic diseases or other dysfunctions is one aim in view of personal health care. One medical target application is e.g. Asthma Bronchiale which is a widespread disease with prevalence in of 5-15% and shows a well defined and well described marker gas, nitrogen oxide (NO) in the exhaled air which can be used for therapy control or asthma diagnostics. Sensor systems for diagnosis and therapy of diseases can also be useful for the detection of target compounds (biomarkers) in body fluidics like blood or urine. the combination of different transducer principles with biological receptor layers results to sensor systems which can be applied to different important medical relevant tasks. Biosensor arrays integrated in CMOS chips which allow a fully electronic signal read of the biological information can reduce the device costs and simplify the sensor system. these advantages open the way to new applications in the field of clinical diagnosis, especially in view of point of care systems e.g. simple allergy tests.
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