Performance analysis for hierarchical resource allocation in multiplexed mobile packet data networks

The general packet radio service (GPRS) can be thought of as an overlay network above a Global Systems for Mobile (GSM) network. In cooperation with the GSM system, GPRS supports both voice and packet data services. Obviously, combining voice and data traffic implies the nature of contending with finite radio resources. The paper focuses on voice/data integrated GPRS downlink traffic and proposes two hierarchical resource allocation strategies by considering time slots and radio blocks simultaneously with two different TDMA frame configurations. The radio block based resource allocation can characterize the multiplexing scheme of the practical GPRS operation. The performance of the proposed strategies were evaluated analytically by multidimensional Markov chain and verified through intensive computer simulations. Based on both the analytical and simulation results, it showed that the proposed allocation strategies can offer high utilization of transmission resource, as well as low blocking probability to GPRS users. The results of the study provide not only a practical thinking for implementation but also a guideline for analysis.     

Impacts of supply disruptions and customer differentiation on a partial-backordering inventory system

In this paper, we study a single-product inventory system which involves a supplier, a retailer, and differentiated customers. The supplier provides products to the retailer which in turn sells products to its customers. The supplier is unreliable and is subject to random disruptions. The retailer adopts a periodic-review inventory policy, under which the retailer reviews its inventory position every a fixed period of time and decides whether a replenishment is needed or not. Partial backordering is applied when a stockout occurs. That is, under the situations of stockouts, customers can choose either to backorder products or to abandon the purchase. Customers are segmented into two classes according to their backordering probabilities. The customer class with high backordering probability is provided with high priority to receive backorders. In this paper we allow more than one outstanding orders to exist, which is not the case in the previous literature. We develop a simulation model for such an inventory system and investigate the impacts of supply disruptions and customer differentiation on this inventory system.     

Concept-based evidential reasoning for multimodal fusion in human–computer interaction

Considerable research has been done on using information from multiple modalities, like hands, facial gestures or speech, for better interaction between humans and computers, and many promising human–computer interfaces (HCI) have been developed in recent years. However, most of the current HCI systems have a few drawbacks: firstly, they are highly dependent on the performance of individual sensors. S econdly, the information fusion process from these sensors tends to ignore the semantic nature of the modalities, which may reinforce or clarify each other over time. Finally, they are not robust enough at representing the imprecise nature of human gestures, since individual gestures are highly ambiguous in themselves. In this paper, we propose an approach for the semantic fusion of different input modalities, based on transferable belief models. We show that this approach allows for a better representation of the ambiguity involved in recognizing gestures. Ambiguity is resolved by combining the beliefs of the individual sensors on the input information, to form new extended concepts, based on a pre-defined domain specific knowledge base, represented by conceptual graphs. We apply this technique to a multimodal system consisting of a hand gesture recognition sensor and a brain computing interface. It is shown that the technique can successfully combine individual gestures obtained from the two sensors, to form meaningful concepts and resolve ambiguity. The advantage of this approach is that it is robust even if one of the sensors is inefficient or has no input. Another important feature is its scalability, wherein more input modalities, like speech or facial gestures, can be easily integrated into the system at minimal cost, to form a comprehensive HCI interface.     

利用创新技法指导控制策略创新初探

控制策略的创新在控制理论与工程的发展中起到举足轻重的作用,如何使控制策略的创新更加科学高效是一个需要研究的问题。提出利用创新技法指导控制策略创新的思想。讨论了创新技法对控制策略创新的指导作用及意义,归纳了可用于控制领域的7大类创新技法,对创新技法的应用层次、协同使用和依存性问题进行了初步讨论。最后以3个例子展示了创新技法对控制策略创新的指导作用和所带来的显著功效。     

Dynamic feedback robust stabilization of nonholonomic mobile robots based on visual servoing

This paper investigates the visual servoing robust stabilization of nonholonomic mobile robots. The calibration of visual parameters is not only complicated, but also needs great consumption of calculated time so that the accurate calibration is impossible in some situations for high requirement of real timing. Hence, it is interesting and important to consider the design of stabilizing controllers for nonholonomic kinematic systems with uncalibrated visual parameters. A novel uncertain model of these nonholonomic kinematic systems is proposed. Based on this model, a stabilizing controller is discussed by using dynamic feedback and two-step techniques. The proposed robust controller makes the mobile robot image pose and the orientation converge to the desired configuration despite the lack of depth information and the lack of precise visual parameters. The stability of the closed loop system is rigorously proved. The simulation is given to show the effectiveness of the presented controllers.     

Constructing the Bayesian network structure from dependencies implied in multiple relational schemas

Relational models are the most common representation of structured data, and acyclic database theory is important in relational databases. In this paper, we propose the method for constructing the Bayesian network structure from dependencies implied in multiple relational schemas. Based on the acyclic database theory and its relationships with probabilistic networks, we are to construct the Bayesian network structure starting from implied independence information instead of mining database instances. We first give the method to find the maximum harmoniousness subset for the multi-valued dependencies on an acyclic schema, and thus the most information of conditional independencies can be retained. Further, aiming at multi-relational environments, we discuss the properties of join graphs of multiple 3NF database schemas, and thus the dependencies between separate relational schemas can be obtained. In addition, on the given cyclic join dependency, the transformation from cyclic to acyclic database schemas is proposed by virtue of finding a minimal acyclic augmentation. An applied example shows that our proposed methods are feasible.     

Partner selection in a virtual enterprise under uncertain information about candidates

Partner selection is a major issue in the formation of a virtual enterprise. In practice, in the partner selection process, the information about the candidates and their performances are incomplete and uncertain. Vague sets theory is one of the methods used to deal with uncertain information. In this paper, a new method based on vague sets is proposed to deal with the partner selection problem in the formation of a virtual enterprise while the factors of satisfaction degree, due date, cost and the precedence of tasks are taken into account. On the basis of the agreement index of satisfaction degree, the formulated partner selection problems are interpreted so as to maximize the minimum agreement index. To solve the problem, an improved particle swarm optimization (PSO) algorithm is proposed. Finally, the simulation of a numerical example demonstrates that the method is effective.     

A method based on preference degrees for handling hybrid multiple attribute decision making problems

In this paper, we investigate hybrid multiple attribute decision making problems with various forms of attribute values (real numbers, linguistic labels, interval numbers, intuitionistic fuzzy numbers and interval intuitionistic fuzzy numbers). We propose a method based on preference degrees which may take the forms of fuzzy numbers, intuitionistic fuzzy numbers and interval intuitionistic fuzzy numbers. The method first normalizes various forms of attribute values into preference degrees, and then uses a preference degree-based weighted averaging operator to aggregate the normalized preference degrees. Meanwhile, for convenience of calculation, a new linguistic representation model is presented, whose feasibility is verified by comparing it with the traditional 4-tuple linguistic representation model, and from our model, the mapping relationship between interval intuitionistic fuzzy numbers and linguistic labels can be constructed. Finally, we illustrate the rationality and practicality of the proposed method by an application example.     

复制式协同设计环境中基于地址空间转换的关联操作一致性维护策略研究

在复制式架构的二维协同设计系统中,地址空间转换算法可用来实现共享文档的一致性维护.然而,该算法无法直接处理关联操作,而是采用先分解后执行的方式进行,在操作分解执行过程中,远程并发操作的存在可能会导致关联操作所依赖的实体属性发生改变,从而使关联操作丢失被参照实体与参照实体之间的关联关系,导致其语义一致性无法维持.本文通过在地址空间转换策略的内部线性地址空间上添加原操作及本地操作历史序列,修正本地操作广播及远程操作接收过程以维持各分解操作的关联关系,并引入Retrace-Undo-VT-Redo-Retrace控制过程,实现对关联操作语义信息的分布式维持.本文最后通过实例分析展示了整个策略的工作过程.