Integrating integer programming and probabilistic deduction graphs for probabilistic reasoning

Optimal solutions of several variants of the probabilistic reasoning problem were found by a new technique that integrates integer programming and probabilistic deduction graphs (PDG). PDGs are extended from deduction graphs of the and-type via normal deduction graphs. The foregoing variants to be solved can involve multiple hypotheses and multiple evidences where the former is given and the latter is unknown and being found or vice versa. The relationship among these hypotheses and evidences with possible intermediaries is represented by a causal graph. The proposed method can handle a large causal graph of any type and find an optimal solution by invoking a linear integer programming package. In addition, formulating the reasoning problem to fit integer programming takes a polynomial time. H.-L. Li was visiting the Department of Computer Sciences, University of North Texas in 1988–1989. He is with the Institute of Information Management, National Chiao Tung University, Hsinchu, Taiwan, R.O.C.     

Detection of multiple cracks using frequency measurements

A method for detection of multiple open cracks in a slender Euler-Bernoulli beams is presented based on frequency measurements. The method is based on the approach given by Hu and Liang [J. Franklin Inst. 330 (5) (1993) 841], transverse vibration modelling through transfer matrix method and representation of a crack by rotational spring. The beam is virtually divided into a number of segments, which can be decided by the analyst, and each of them is considered to be associated with a damage parameter. The procedure gives a linear relationship explicitly between the changes in natural frequencies of the beam and the damage parameters. These parameters are determined from the knowledge of changes in the natural frequencies. After obtaining them, each is treated in turn to exactly pinpoint the crack location in the segment and determine its size. The forward, or natural frequency determination, problems are examined in the passing. The method is approximate, but it can handle segmented beams, any boundary conditions, intermediate spring or rigid supports, etc. It eliminates the need for any symbolic computation which is envisaged by Hu and Liang [J. Franklin Inst. 330 (5) (1993) 841] to obtain mode shapes of the corresponding uncracked beams. The proposed method gives a clear insight into the whole analysis. Case studies (numerical) are presented to demonstrate the method effectiveness for two simultaneous cracks of size 10% and more of section depth. The differences between the actual and predicted crack locations and sizes are less than 10% and 15% respectively. The numbers of segments into which the beam is virtually divided limits the maximum number of cracks that can be handled. The difference in the forward problem is less than 5%.     

An application of expert systems techniques to the on-line control and fault diagnosis of a mixing process

An application of expert hierarchical control is described in this paper. The control is implemented in a two-level configuration, where the lower layer performs direct regulation control and the upper layer performs supervisory functions. In the regulation layer, a rule-based controller performs the regulation task, where the controller is constructed upon causal relations between subsystems. The control action is inferred from the measurement of both controlled and noncontrolled variables. In the supervisory layer, the main function is a fault diagnosis system which diagnoses faults on-line. The diagnosis is based upon reasoning from the structure of the system and the functions of its components, and efficient diagnosis is achieved by dividing the system into several subsystems. The overall technique has been successfully implemented on a pilot scale mixing process under on-line computer control.     

水泥基压电复合材料的制备及极化工艺研究

采用压制成型法，首次以快硬早强的硫铝酸盐水泥为基体制备了水泥基压电复合材料。详细阐述了水泥基压电复合材料的制备过程；通过实验确定了适宜的极化条件，分析讨论了极化过程中出现漏电流的原因，并提出了一些初步的解决途径。结果表明，对硫铝酸盐水泥基压电复合材料来说，适宜的极化工艺参数：极化电场强度为4kV／mm，极化时间为45min，极化温度应低于130℃。     

Granular Reasoning Using Zooming In & Out: Part 2. Aristotle's Categorical Syllogism

The concept of granular computing is applied to Aristotle's categorical syllogism. Such kind of reasoning is called granular reasoning in this paper. For the purpose, two operations called zooming in & out are introduced to reconstruct granules of possible worlds.     

Enhancing cognitive radio systems with robust reasoning

Cognitive radio systems dynamically reconfigure the algorithms and parameters they use, in order to adapt to the changing environment conditions. However, reaching proper reconfiguration decisions presupposes a way of knowing, with high enough assurance, the capabilities of the alternate configurations, especially in terms of achievable transmission capacity and coverage. The present paper addresses this problem, firstly, by specifying a complete process for extracting estimations of the capabilities of candidate configurations, in terms of transmission capacity and coverage, and, secondly, by enhancing these estimations with the employment of a machine learning technique. The technique is based on the use of Bayesian Networks, in conjunction with an effective learning and adaptation strategy, and aims at extracting and exploiting knowledge and experience, in order to reach robust (i.e. stable and reliable) estimations of the configurations' capabilities. Comprehensive results of the proposed method are presented, in order to validate its functionality. Copyright © 2007 John Wiley & Sons, Ltd.     

On a responsive replenishment system: a fuzzy logic approach

In today's competitive business environment, it is important that customers are able to obtain their preferred items in the shops they visit, particularly for convenience store chains such as 7–Eleven where popular items are expected to be readily available on the shelves of the stores for buyers. To minimize the cost of running such store chains, it is essential that stocks be kept to a minimum and at the same time large varieties of popular items are available for customers. In this respect, the replenishment system needs to be able to cope with the taxing demands of minimal inventory but at the same time keeping large varieties of needed items. This paper proposes a replenishment system which is able to respond to the fluctuating demands of customers and provide a timely supply of needed items in a cost–effective way. The proposed system embraces the principle of fuzzy logic which is able to deal with uncertainties by virtue of its fuzzy rules reasoning mechanism, thereby leveraging the responsiveness of the entire replenishment system for the chain stores. To validate the feasibility of the approach, a case study has been conducted in an emulated environment with promising results.     

Plasticity of feature-based selection in triple-conjunction search.

Two experiments examined the disruption of feature-based selection in triple-conjunction search at multiple target transfers. In Experiment 1, after 10 training sessions, a new target possessing previous distractor features was introduced. This produced disruption in RT and fixation number, but no disruption in feature-based selection. Specifically, there was a tendency to fixate objects sharing the target's contrast polarity and shape and this did not change even upon transfer to the new target. In Experiment 2, 30 training sessions were provided with three target transfers. At the first transfer, the results replicated Experiment 1. Subsequent transfers did not produce disruption on any measure. These findings are discussed in terms of strength theory, Guided Search, rule-based approaches to perceptual learning, and the area activation model. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Evaluating an intelligent diagnosis system of historical text comprehension

This work aims to present and evaluate a Fuzzy-Case Based Reasoning Diagnosis system of Historical Text Comprehension. The synergism of fuzzy logic and case based reasoning techniques handles the uncertainty in the acquisition of human expert's knowledge regarding learner's observable behaviour and integrates the right balance between expert's knowledge described in the form of fuzzy sets and previous experiences documented in the form of cases. The formative evaluation focused on the comparison of the system's performance to the performance of human experts concerning the diagnosis accuracy. The system was also evaluated for its behaviour when using two different historical texts. Empirical evaluation conducted with human experts and real students indicated the need for revision of the diagnosis model. The evaluation results are encouraging for the system's educational impact on learners and for future work concerning an intelligent educational system for individualized learning.