An axiom system for sequence-based specification

This paper establishes an axiomatic foundation and a representation theorem for the rigorous, constructive process, called sequence-based specification, of deriving precise specifications from ordinary (informal) statements of functional requirements. The representation theorem targets a special class of Mealy state machines, and algorithms are presented for converting from the set of sequences that define the specification to the equivalent Mealy machine, and vice versa. Since its inception, sequence-based specification has been effectively used in a variety of real applications, with gains reported in quality and productivity. This paper establishes the mathematical foundation independently of the process itself.     

Analytical modelling of networks in multicomputer systems under bursty and batch arrival traffic

The hypercube and torus are two important message-passing network architectures of high-performance multicomputers. Analytical models of multicomputer networks under the non-bursty Poisson traffic have been widely reported. Motivated by the convincing evidence of bursty and batch arrival nature of traffic generated by many real-world parallel applications in high-performance computing environments, we develop a new and concise analytical model in this paper for hypercube and torus networks in the presence of batch message arrivals modelled by the compound Poisson process with geometrically distributed batch sizes. The average degree of virtual channel multiplexing is derived by employing a Markov chain which can capture the batch arrival nature. An attractive advantage of the model is its constant computation complexity independent of the network size. The accuracy of the analytical performance results is validated against those obtained from simulation experiments of an actual system.     

基于复杂网络的 Internet 流量分析

基于复杂网络理论对 Internet 网络结构进行分析,模拟 Internet 网络中选择服务器的过程,建立一个基于距离和流量的 Internet 自组织网络结构模型(FDM).通过仿真Internet 网络数据传输过程,分析比较 FDM 与 BBV 模型的丢包率,研究 Interact 网络中心连接节点的缓存器容量、...     

一种基于可信度矩阵的多传感器目标识别方法

为了解决多传感器目标识别中不同等级信息源数据的融合问题,在研究DSmT证据理论的基础上,引入证据可信度矩阵.依据可信度矩阵对证据进行转化,使之可以用传统的方法进行证据融合.将这种方法应用到等级不同的多传感器目标识别中,可以解决传统证据理论只能进行相同等级传感器目标识别的难题.仿真实验表明,该方法提高了目标识别的准确性和有效性.     

安全事件模糊等量约束的因果关联算法研究

通过对异构网络的安全事件特点的深入分析,指出在大量不完整、模糊的安全事件中准确地定位潜在的安全威胁,对态势和威胁及其重要程度进行全面及时的评估,是当前安全管理的一个技术难题.提出一种基于时间关联窗口的安全事件模糊关联算法,在一定程度上解决安全事件的漏报与领域知识的不完备性问题,对当前的安全态势、安全威胁及其重要程度进行全面及时评估提供有力的支持.     

Fuzzy two-stage material procurement planning problem

Material procurement planning (MPP) deals with the problem that purchasing the right quantity of material from the right supplier at the right time, a purchaser can reduce the material procurement costs via a reasonable MPP model. In order to handle the MPP problem in a fuzzy environment, this paper presents a new class of two-stage fuzzy MPP models, in which the material demand, the spot market material unit price and the spot market material supply quantity are assumed to be fuzzy variables with known possibility distributions. In addition, the procurement decisions are divided into two groups. Some procurement decisions, called first-stage decisions, must be taken before knowing the the particular values taken by the fuzzy variables; while some other decisions, called second-stage decisions, can be taken after the realizations of the fuzzy variables are known. The objective of the proposed fuzzy MPP model is to minimize the expected material procurement costs over the two stages. On other hand, since the fuzzy material demand, the fuzzy spot market material unit price and the fuzzy spot market material supply quantity are usually continuous fuzzy variables with infinite supports, the proposed MPP model belongs to an infinite-dimensional optimization problem whose objective function cannot be computed exactly. To avoid this difficulty, we suggest an approximation approach (AA) to evaluating the objective function, and turn the original MPP model into an approximating finite-dimensional one. To show the credibility of the AA, the convergence about the objective function of the approximating MPP model to that of the original MPP one is discussed. Since the exact analytical expression for the objective function in the approximating fuzzy MPP model is unavailable, and the approximating MPP model is a mixed-integer program that is neither linear nor convex, the traditional optimization algorithms cannot be used to solve it. Therefore, we design an AA-based particle swarm optimization to solve the approximating two-stage fuzzy MPP model. Finally, we apply the two-stage MPP model to an actual fuel procurement problem, and demonstrate the effectiveness of the designed algorithm via numerical experiments.     

Economic lot sizing in a production system with random demand

An extended economic production quantity model that copes with random demand is developed in this paper. A unique feature of the proposed study is the consideration of transient shortage during the production stage, which has not been explicitly analysed in existing literature. The considered costs include set-up cost for the batch production, inventory carrying cost during the production and depletion stages in one replenishment cycle, and shortage cost when demand cannot be satisfied from the shop floor immediately. Based on renewal reward process, a per-unit-time expected cost model is developed and analysed. Under some mild condition, it can be shown that the approximate cost function is convex. Computational experiments have demonstrated that the average reduction in total cost is significant when the proposed lot sizing policy is compared with those with deterministic demand.     

Pose-and-illumination-invariant face representation via a triplet-loss trained deep reconstruction model

Face recognition under variable pose and illumination is a challenging problem in computer vision tasks. In this paper, we solve this problem by proposing a new residual based deep face reconstruction neural network to extract discriminative pose-and-illumination-invariant (PII) features. Our deep model can change arbitrary pose and illumination face images to the frontal view with standard illumination. We propose a new triplet-loss training method instead of Euclidean loss to optimize our model, which has two advantages: a) The training triplets can be easily augmented by freely choosing combinations of labeled face images, in this way, overfitting can be avoided; b) The triplet-loss training makes the PII features more discriminative even when training samples have similar appearance. By using our PII features, we achieve 83.8% average recognition accuracy on MultiPIE face dataset which is competitive to the state-of-the-art face recognition methods.     

南水北调中线穿黄工程盾构机刀具维护技术

南水北调中线穿黄隧洞工程地质条件复杂,隧洞穿越地层有全砂层、全土层及上砂下土的复合地层。盾构机刀盘设计采用软土型刀具、重载型刀盘传力架,并采取了多种防磨损措施,以保护刀盘具。但在盾构施工过程中,掘进参数出现异常,且在出渣物中发现金属件,表明盾构机刀盘具受到严重磨损。通过带压进仓检查,及时查清了情况,更换了部分刀具,对需要修复的刀具,在对地基进行加固后,采用常压进舱方案,进行了彻底修复。本次刀盘具检查维护的经验,对于保证穿黄工程的顺利掘进具有重要的指导意义,对于其他类似工程也有重要的参考价值。     

A comment on: “Fast and numerically stable methods for the computation of Zernike moments” by Singh et al. [Pattern Recognition, 43(2010), Pages 2497-2506]

The aim of the present comment is to point out that the q-Recursive relation introduced by Singh et al. is wrong. These errors have been corrected in the comment. The numerical experiments show that the correct recurrence relation is consistent with the original q-Recursive method.