An algorithm to compute maximal contractions for Horn clauses

In the theory of belief revision, the computation of all maximal subsets (maximal contractions) of a formula set with respect to a set of facts is one of the key problems. In this paper, we try to solve this problem by studying the algorithm to compute all maximal contractions for Horn clauses. First, we point out and prove the conversion relationship between minimal inconsistent subsets of union of the formula set and the set of facts and maximal contractions of the formula set with respect to th...     

Inference for Weibull distribution under generalized order statistics

Based on generalized order statistics from Weibull distribution the approach of Bayesian and non-Bayesian estimation are discussed. We present a simple and efficient simulational algorithm for generating a generalized order statistics sample from any continuous distribution. Specializations to Bayesian and non-Bayesian estimators, some lifetime parameters and confidence intervals of progressive II censoring and record values are obtained and compared with the existing results. Two examples are given to illustrate the proposed estimators and the simulation algorithm.     

基于压缩传感的背景差分方法研究

近年来国际上出现了一种新的信息获取理论——压缩传感理论（CS）,不同于传统的奈奎斯特采样定理,它指出只要信号具有稀疏性或可压缩性,就可以通过少量随机采样点来恢复原始信号。基于对CS理论基础的深入分析,提出一种运用背景差分进行运动目标检测的新方法,此方法可以显著减少信号采样点数和传输带宽,而且一定程度上了克服了由于如光照变化而造成的误检测,仿真结果证实了该文算法的可行性。     

基于单链表和散列表比较的词频统计研究

针对操作系统课程中的词频统计实验,介绍两种分别采用单链表和散列表进行词频统计的方法,并着重说明后一种方法在效率方面的优越性。     

Online phenotype discovery based on minimum classification error model

Identifying and validating novel phenotypes from images inputting online is a major challenge against high-content RNA interference (RNAi) screening. Newly discovered phenotypes should be visually distinct from existing ones and make biological sense. An online phenotype discovery method featuring adaptive phenotype modeling and iterative cluster merging using improved gap statistics is proposed. Clustering results based on compactness criteria and Gaussian mixture models (GMM) for existing phenotypes iteratively modify each other by multiple hypothesis test and model optimization based on minimum classification error (MCE). The method works well on discovering new phenotypes adaptively when applied to both of synthetic datasets and RNAi high content screen (HCS) images with ground truth labels.     

Ordinal Optimization and Quantification of Heuristic Designs

This paper focuses on the performance evaluation of complex man-made systems, such as assembly lines, electric power grid, traffic systems, and various paper processing bureaucracies, etc. For such problems, applying the traditional optimization tool of mathematical programming and gradient descent procedures of continuous variables optimization are often inappropriate or infeasible, as the design variables are usually discrete and the accurate evaluation of the system performance via a simulation model can take too much calculation. General search type and heuristic methods are the only two methods to tackle the problems. However, the “goodness” of heuristic methods is generally difficult to quantify while search methods often involve extensive evaluation of systems at many design choices in a large search space using a simulation model resulting in an infeasible computation burden. The purpose of this paper is to address these difficulties simultaneously by extending the recently developed methodology of Ordinal Optimization (OO). Uniform samples are taken out from the whole search space and evaluated with a crude but computationally easy model when applying OO. And, we argue, after ordering via the crude performance estimates, that the lined-up uniform samples can be seen as an approximate ruler. By comparing the heuristic design with such a ruler, we can quantify the heuristic design, just as we measure the length of an object with a ruler. In a previous paper we showed how to quantify a heuristic design for a special case but we did not have the OO ruler idea at that time. In this paper we propose the OO ruler idea and extend the quantifying method to the general case and the multiple independent results case. Experimental results of applying the ruler are also given to illustrate the utility of this approach.

On partial-information optimal singular control problem for mean-field stochastic differential equations driven by Teugels martingales measures

This paper is concerned with partial-information mixed optimal stochastic continuous–singular control problem for mean-field stochastic differential equation driven by Teugels martingales and an independent Brownian motion, where the Teugels martingales are a family of pairwise strongly orthonormal martingales associated with Lévy processes. The control variable has two components; the first being absolutely continuous, and the second singular. Partial-information necessary and sufficient conditions of optimal continuous–singular control for these mean-field models are investigated. As an illustration, this paper studies a partial-information linear quadratic control problem of mean-field type involving continuous–singular control.     

Optimal replacement policy for a two-dissimilar-component cold standby system with different repair actions

In this paper, a cold standby repairable system consisting of two dissimilar components and one repairman is studied. When failures occur, the repair of both component 1 and component 2 are not ‘as good as new’. The consecutive operating times of component 1 after repair constitute a decreasing geometric process, while the repair times of component 1 are independent and identically distributed. For component 2, its failure is rectified by minimal repair, and the repair time is negligible. Component 1 has priority in use when both components are good. The replacement policy N is based on the failure number of component 1. Under policy N, we derive the explicit expression of the long-run average cost rate C(N) as well as the average number of repairs of component 2 before the system replaced. The optimal replacement policy N*, which minimises the long-run average cost rate C(N), is obtained theoretically. If the failure rate r(t) of component 2 is increasing, the existence and uniqueness of the optimal policy N* is also proved. Finally, a numerical example is given to validate the developed theoretical model. Some sensitivity analyses are provided to show the influence of some parameters, such as the costs for replacement and repair, and the parameters of the lifetime and repair time distributions of both components, to the optimal replacement policy N* and corresponding average cost rate C(N*).     

Supervisory control based on minimal cuts and Petri net sub-controllers coordination

This paper addresses the synthesis of Petri net (PN) controller for the forbidden state transition problem with a new utilisation of the theory of regions. Moreover, as any method of control synthesis based on a reachability graph, the theory of regions suffers from the combinatorial explosion problem. The proposed work minimises the number of equations in the linear system of theory of regions and therefore one can reduce the computation time. In this paper, two different approaches are proposed to select minimal cuts in the reachability graph in order to synthesise a PN controller. Thanks to a switch from one cut to another, one can activate and deactivate the corresponding?PNcontroller. An application is implemented in a flexible manufacturing system to illustrate the present method. Finally, comparison with previous works with experimental results in obtaining a maximally permissive controller is presented.