Most of the existing work about fairness verification was carried out by checking the fairness based on state, action, or process respectively. It is hard to resolve the fairness issue for complex software systems, es...
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Most of the existing work about fairness verification was carried out by checking the fairness based on state, action, or process respectively. It is hard to resolve the fairness issue for complex software systems, especially in life-critical systems and safety-critical systems. In this paper, we verify the fairness based on both state and action, which is realized mainly by introducing an extended Kripke structure and four kinds of fairness (weak global/local fairness and strong global/local fairness). The experimental results show the superiority of our method by the savings in memory (2.08%) and time consumption (26.45%).
This paper is devoted to the modeling problem of hypersonic vehicle with significant couplings. An integrated approach is developed to analytically model the dynamics of hypersonic vehicle, in which the effects of var...
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ISBN:
(纸本)9781467325813
This paper is devoted to the modeling problem of hypersonic vehicle with significant couplings. An integrated approach is developed to analytically model the dynamics of hypersonic vehicle, in which the effects of variable mass, spherical rotating earth, and couplings among the sub-models are considered. Furthermore, a preliminary analysis is conducted using the general data of a hypersonic vehicle. The simulation results show that the maximum of the Coriolis force can reach values up to 7.02% of the vehicle weight, and that the thermal load determined by the nonuniform aerodynamic heating and the properties of the structure has a significant influence on the elastic deformation.
Ultrasound (US) images have been widely used in the diagnosis of breast cancer in particular. While experienced doctors may locate the tumor regions in a US image manually, it is highly desirable to develop algorithms...
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ISBN:
(纸本)9781457718571
Ultrasound (US) images have been widely used in the diagnosis of breast cancer in particular. While experienced doctors may locate the tumor regions in a US image manually, it is highly desirable to develop algorithms that automatically detect the tumor regions in order to assist medical diagnosis. In this paper, we propose a novel algorithm for automatic detection of breast tumors in US images. We formulate the tumor detection as a two step learning problem: tumor localization by bounding box and exact boundary delineation. Specifically, the proposed method uses an AdaBoost classifier on Harr-like features to detect a preliminary set of tumor regions. The preliminarily detected tumor regions are further screened with a support vector machine using quantized intensity features. Finally, the random walk segmentation algorithm is performed on the US image to retrieve the boundary of each detected tumor region. The proposed method has been evaluated on a data set containing 112 breast US images, including histologically confirmed 80 diseased ones and 32 normal ones. The data set contains one image from each patient and the patients are from 31 to 75 years old. Experiments demonstrate that the proposed algorithm can automatically detect breast tumors, with their locations and boundary shapes retrieved with high accuracy.
Context Awareness and Mobility are two fundamental characteristics of ubiquitous and pervasive computing, where users may wander among smart spaces equipped with kinds of devices providing types of services with respe...
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The paper presents a new approach to computing the abstract state and a maximum weight heuristic method for finding the shortest counter-example in verification of imperative programs. The strategy is incorporated in ...
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The paper presents a new approach to computing the abstract state and a maximum weight heuristic method for finding the shortest counter-example in verification of imperative programs. The strategy is incorporated in a verification system based on the counterexample-guided abstraction refinement method. The proposed method slashes both the size of the abstract state space and the number of invokes of a decision procedure. A number of benchmarks are employed to evaluate the effectiveness of the approach.
JIT spraying is a new code-reuse technique to attack virtual machines based on JIT (Just-in-time) compilation. It has proven to be capable of circumventing the defenses such as data execution prevention (DEP) and addr...
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The authors use unified modelling language (UML) 2.0 interaction overview diagrams (IODs) and sequence diagrams to construct simple and expressive scenario-based specifications, and present an approach to runtime veri...
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In this paper, the H_2 optimal state-feedback control problem is investigated for discrete-time Markov jump systems subject to periodic coefficients and multiplicative noise. First of all, an exhaustive analysis is pu...
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ISBN:
(纸本)9781457710957
In this paper, the H_2 optimal state-feedback control problem is investigated for discrete-time Markov jump systems subject to periodic coefficients and multiplicative noise. First of all, an exhaustive analysis is pursued to set up an H_2 performance criterion (H_2 norm), which can be characterized by the periodic solutions of two generalized Lyapunov equations. Based on the obtained H_2 norm, the H_2 optimal state-feedback controller is designed in terms of the stabilizing solution of a discrete-time generalized Riccati equation with periodic coefficients. Moreover, this stabilizing solution can be computed efficiently by the available iterative algorithm.
E-commerce web sites usually have to maintain a large number of product information. To organize this product information, a feasible way is to add semantic tags to the information. However, the Web product informatio...
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Programmable shader is a powerful tool to describe objects' appearances in the realm of computer graphics. However, executing shaders takes up much time during rendering and can easily go beyond the computer hardw...
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