On a weaker notion of controllability of a language K withrespect to a language L

A necessary and sufficient condition for a prefix-closed language K⊆Σ* to be controllable with respect to another prefix-closed language L⊆Σ* is that K⊆ L. A weaker notion of controllability where it is not required that K⊆L is considered here. If L is the prefix-closed language generated by a plant automaton G, then essentially there exists a supervisor Θ that is complete with respect to G such that L(Θ|G)=K ∩ L if and only if K is weakly controllable with respect to L. For an arbitrary modeling formalism it is shown that the inclusion problem is reducible to the problem of deciding the weaker notion of controllability. Therefore, removing the requirement that K ⊆ L from the original definition of controllability does not help the situation from a decidability viewpoint. This observation is then used to identify modeling formalisms that are not viable for supervisory control of the untimed behaviors of discrete-event dynamic systems     

CAREL: computer aided reliability evaluator for distributedcomputing networks

An efficient method to compute the terminal reliability (the probability of communication between a pair of nodes) of a distributed computing system (DCS) is presented. It is assumed that the graph model G(V,E) for DCS is given and that the path and/or cut information for the network G(V,E) is available. Boolean algebraic concepts are used to define four operators: compare, reduce, combine, and generate. The proposed method, called CAREL, uses the four operators to generate exclusive and mutually disjoint events. CAREL has been implemented using bit vector representation on an Encore MULTIMAX 320 system. It is shown that CAREL solves large DCS networks (having a pathset on the order of 780 and a cutset on the order of 7300 or more) with a reasonable memory requirement. A comparison with other algorithms reveals the computational efficiency of the method. The proof of correctness of CAREL is included     

基于改进多嵌入空间的实时语义数据流推理

将语义数据流处理引擎与知识图谱嵌入表示学习相结合,可以有效提高实时数据流推理查询性能,但是现有的知识表示学习模型更多关注静态知识图谱嵌入,忽略了知识图谱的动态特性,导致难以应用于实时动态语义数据流推理任务。为了使知识表示学习模型适应知识图谱的在线更新并能够应用于语义数据流引擎,建立一种基于改进多嵌入空间的动态知识图谱嵌入模型PUKALE。针对传递闭包等复杂推理场景,提出3种嵌入空间生成算法。为了在进行增量更新时更合理地选择嵌入空间,设计2种嵌入空间选择算法。基于上述算法实现PUKALE模型,并将其嵌入数据流推理引擎CSPARQL-engine中,以实现实时语义数据流推理查询。实验结果表明,与传统的CSPARQL和KALE推理相比,PUKALE模型的推理查询时间分别约降低85%和93%,其在支持动态图谱嵌入的同时能够提升实时语义数据流推理准确率。     

Explicit expressions for cascade factorization of generalnonminimum phase systems

Explicit expressions for two different cascade factorizations of any detectable left invertible nonminimum phase systems are given. The first one is a well known minimum phase/all-pass factorization by which all nonminimum phase zeros of a transfer function G(s) are collected into an all-pass factor V(s), and G (s) is written G_m(s)V$ where G_ms is considered as a minimum phase image of G(s). The second one is a new cascade factorization by which G(s) is rewritten as G_M( s)U(s) where U(s) collects all `awkward' zeros including all nonminimum phase zeros of G( s). Both G_m(s) and G_M(s) retain the given infinite zero structure of G(s). Further properties of G _m(s), G_M(s), and U (s) are discussed. These factorizations are useful in several applications including loop transfer recovery     

Out-of-roundness problem revisited

The properties and computation of the minimum radial separation (MRS) standard for out-of-roundness are discussed. Another standard out-of-roundness measurement called the minimum area difference (MAD) center is introduced. Although the two centers have different characteristics, the approach to finding both centers shares many commonalities. An O(n log n+k) time algorithm which is used to compute the MRS center is presented. It also computes the MAD center of a simple polygon G, where n is the number of vertices of G, and k is the number of intersection points of the medial axis and the farthest-neighbor Voronoi diagram of G. The relationship between MRS and MAD is discussed     

基于描述逻辑的主体服务匹配

多主体系统中的服务匹配是智能主体和多主体系统等领域中的重要研究课题．描述逻辑是知识表示和推理的形式化工具，它提供了可判定的和可靠的推理服务．该文利用描述逻辑有效的推理功能，特别是它对概念包含关系的有效判断，把它与多主体系统的服务推理结合起来．充分利用描述逻辑具有清晰模型一理论语义和有效的概念分层推理服务等功能，该文提出了基于描述逻辑的主体服务匹配算法，详细研究了如何利用描述逻辑的理论和推理机制来实现自动的服务分层及服务匹配．并提出了五种服务匹配算法．这些方法都是基于语义的服务匹配，利用服务分层机制实现了有效和高效的多主体系统中的服务匹配，克服了基于语义距离进行服务匹配的不足．     

Minimal realization of transfer function matrices via oneorthogonal transformation

The minimal realization of a given arbitrary transfer function matrix G(s) is obtained by applying one orthogonal similarity transformation to the controllable realization of G( s). The similarity transformation is derived by computing the QR or the singular value decomposition of a matrix constructed from the coefficients of G(s). It is emphasized that the procedure has not been proved to be numerically stable. Moreover, the matrix to be decomposed is larger than the matrices factorized during the step-by-step procedures given     

Descent algorithms for optimal periodic output feedback control

Periodic output feedback is investigated in the context of linear-quadratic regulation for finite-dimensional time-invariant linear systems. Discrete output samples are multiplied by a periodic gain function to generate a continuous feedback control. The optimal solution is obtained in two steps by separating the continuous-time from the discrete-time structure. First, the optimal pole placement problem under periodic output feedback is solved explicitly under the assumption that the behavior at the sample times has been specified in terms of a gain matrix G. Then the minimum value, which depends on G, is substituted into the overall objective. This results in a finite-dimensional nonlinear programming problem over all admissible gain matrices G. The solution defines the optimal periodic output feedback control via the formulas of the optimal pole placement problem. A steepest descent and a direct iterative method for solving this problem are formulated and compared. Numerical examples show that the performance using periodic output feedback is almost equivalent to that using optimal continuous-state feedback     

New results in fuzzy clustering based on the concept ofindistinguishability relation

The issue of validity in clustering is considered and a definition of fuzzy r-cluster that extends E. Ruspini's definition (1982) is proposed. This definition is based on an indistinguishability relation based on the concept of t-norm. The fuzzy r-cluster's metrical properties are studied through the dual concept of t-conorm that leads to G-pseudometrics. From the concept of G-pseudometric, fuzzy r-clusters and fuzzy cluster coverages are defined. The authors propose a measure of cluster validity based on the concept of fuzzy coverage. The basic idea of the approach presented is that the smaller the difference between the degrees of membership and the degrees of indistinguishability, the better the clustering     

钢混构件诊断专家系统的研究与实现

基于不确定推理理论,该文对有关知识进行表达与组织,提出了一种新的采用层次结构的钢混构件诊断知识模型,并给出了专家系统的推理控制策略、冲突解决策略及其算法,最后介绍了专家系统的结构及其组成部分。     

Uniform approximation and the circle criterion

The input-output maps G of causal time-invariant systems are considered, and a complete characterization of those maps that can be uniformly approximated by the maps of certain simple structures is given. The criterion is that G must satisfy certain continuity and approximately-finite-memory conditions. It is proved that the conditions are satisfied by the input-output maps of control systems of a familiar type containing a sector nonlinearity for which the circle condition for stability is met. In particular, this shows that such feedback systems, with inputs drawn from a certain large set of bounded functions, possess arbitrarily good finite Volterra-series (or radial-basis-function) approximations     

Systolic computation of multivariable frequency response

An algorithm intended for software implementation on a programmable systolic/wavefront computer is presented for the computation of a complex-valued frequency-response matrix G. Typically, real-valued state-space model matrices are given and the calculation of G must be performed for a very large number of values of the scalar frequency parameter. The algorithm is an orthogonal version of an algorithm described previously by A.J. Laub (ibid., vol.26, no.4, p.407-8, 1981). The system matrix A is reduced initially to an upper Hessenberg form which is preserved as the frequency varies subsequently. A systolic QR factorization of a certain complex-valued matrix is then implemented for effecting the necessary linear system solution (inversion). The critical computational component is the back solve. This computational component's process dependency graph is embedded optimally in space and time through the use of a nonlinear spacetime transformation. The computational period of the algorithm is O(n) where n is the order of the matrix A     

Vibrational feedback control in the problem of acoustic stability

The problem of absolute stability in a vibrational feedback controller is introduced and discussed. It is shown that for any rational G(s)=n(s)/d(s ) with d(s) Hurwitz and deg d(s) -deg n(s)=1 there exists a linear dynamic periodic controller that ensures, in a certain sense, the infinite sector of absolute stability. This implies that an additional dynamical element, inserted in the feedback loop, may lead to improvements in the robustness of nonlinear systems     

Comments on `Conditions for stable zeros of sampled systems' by M.Ishitobi

The commenter argues that the result of the above-titled work (see ibid., vol.37, no.10, p.1558-1561, Oct. 1992) is incorrect. It is pointed out that when sampling a continuous-time system G(s ) using zero-order hold, the zeros of the resulting discrete-time system H(z) become complicated functions of the sampling interval T. The system G(s) has unstable continuous-time zeros, s=0.1±i. The zeros of the corresponding sampled system start for small T from a double zero at z=1 as exp(T(0.1±i )), i.e., on the unstable side. For T>1.067 . . . the zeros become stable. The criterion function of the above-titled work, F(T)=G*(jω_s/2)= H(-1)T/2, is, however, positive for all T, indicating only stable zeros. The zero-locus crosses the unit circle at complex values     

Adaptive control based on explicit model of robot manipulator

Adaptive and nonadaptive control algorithms, which make use of a fundamental mathematical property concerning positive definite matrices and Lyapunov stability theory, are proposed for the control of robot manipulators. Using the fact that the matrix dD(q)/dt-2C(q, dq/ dt) is skew symmetric, nonadaptive controllers which have a simplified structure with less computational burden are proposed. Using the dynamic equations for robot manipulators, parameter adaptation rules are developed for updating the controller's partially or totally unknown parameters, generalizing them to model reference adaptive controllers. To further take advantage of the simplified structure of the proposed adaptive controllers, a method for deriving the dynamic model of a robot manipulator which is linear in terms of its parameters is given. This dynamic model is also suitable for the pure identification of the parameters of links and payload of the manipulator     

Efficient Transitive Closure Reasoning in a Combined Class/Part/Containment Hierarchy

Class hierarchies form the backbone of many implemented knowledge representation and reasoning systems. They are used for inheritance, classification and transitive closure reasoning. Part hierarchies are also important in artificial intelligence. Other hierarchies, e.g. containment hierarchies, have received less attention in artificial intelligence. This paper presents an architecture and an implementation of a hierarchy reasoner that integrates a class hierarchy, a part hierarchy, and a containment hierarchy into one structure. In order to make an implemented reasoner useful, it needs to operate at least at speeds comparable to human reasoning. As real-world hierarchies are always large, special techniques need to be used to achieve this. We have developed a set of parallel algorithms and a data representation called maximally reduced tree cover for that purpose. The maximally reduced tree cover is an improvement of a materialized transitive closure representation which has appeared in the literature. Our experiments with a medical vocabulary show that transitive closure reasoning for combined class/part/containment hierarchies in near constant time is possible for a fixed hardware configuration. Received 10 January 2000 / Revised 25 November 2000 / Accepted in revised form 9 February 2001     

A logical foundation for the semantic Web

World Wide Web (WWW) has been one of important channels from which people acquire information and services, but most web pages are only used by humans at pre-sent, and these pages cannot be processed and understood automatically by computers. The semantic Web is an essential reformation of Web. The main objective of the seman-tic Web is to enrich Web with semantics and make Web be understood by computers, in order to communicate and cooperate between people and computer. The key of the se-…     

Solution to Morgan's problem

A necessary and sufficient condition is presented for the solution of the row-by-row decoupling problem (known as Morgan's problem) in the general case, that is, without any restrictive assumption added to the system to the feedback law u=Fx+Gy (G may be noninvertible). This is a structural condition in terms of invariant lists of integers which are easily computable from a given state realization of the system. These integers are the infinite zero orders (Morse's list I₄) and the essential orders of the system, which only depend on the input-output behavior, and Morse's list I₂ of the system, which depends on the choice of a particular state realization     

任务计算中基于语义Web的上下文感知服务选择

针对普适环境中任务计算的特点,分析了任务计算的层次结构和复杂任务的分解策略,设计了一种任务计算中服务发现的体系结构。此体系结构依赖于服务和内容的语义表示,而这种语义表示是基于本体的、共享的。它不仅可以增强精确度和调用率,而且能够实现知识共享、基于能力的搜索、自主推理以及语义匹配等功能。据此,提出了一种基于语义Web的上下文感知动态服务选择机制,这种机制可以根据待匹配的服务的动态上下文属性来对其进行过滤和排序,从而进一步优化了发现的过程、节约了用户的时间和精力。此外,该选择机制可用于发现有用的静态或动态上下文信息,从而为用户提供最合适、最相关的服务。     

视觉知识：跨媒体智能进化的新支点

回顾跨媒体智能的发展历程,分析跨媒体智能的新趋势与现实瓶颈,展望跨媒体智能的未来前景。跨媒体智能旨在融合多来源、多模态数据,并试图利用不同媒体数据间的关系进行高层次语义理解与逻辑推理。现有跨媒体算法主要遵循了单媒体表达到多媒体融合的范式,其中特征学习与逻辑推理两个过程相对割裂,无法综合多源多层次的语义信息以获得统一特征,阻碍了推理和学习过程的相互促进和修正。这类范式缺乏显式知识积累与多级结构理解的过程,同时限制了模型可信度与鲁棒性。在这样的背景下,本文转向一种新的智能表达方式——视觉知识。以视觉知识驱动的跨媒体智能具有多层次建模和知识推理的特点,并易于进行视觉操作与重建。本文介绍了视觉知识的3个基本要素,即视觉概念、视觉关系和视觉推理,并对每个要素展开详细讨论与分析。视觉知识有助于实现数据与知识驱动的统一框架,学习可归因可溯源的结构化表达,推动跨媒体知识关联与智能推理。视觉知识具有强大的知识抽象表达能力和多重知识互补能力,为跨媒体智能进化提供了新的有力支点。