A prolog based expert system for the allocation of quality assurance program resources

The worldwide proliferation of fraudulent materials has brought about the need for a new approach to the control of purchased material quality. Nuclear power, defense, aerospace and many other industries are affected by the supply of poor quality clones that presume to be original replacement parts. Safety considerations abound as these highly defective materials are used in systems that are critical to the preservation of human lives. Commonly utilized quality assurance programs have not effectively stopped the influx of fraudulent materials. These programs fail to concentrate inspection efforts on materials and inspection attributes that would effectively prevent the acceptance of fraudulent materials. herein a solution is presented to this problem in the form of an expert system application. Information commonly available in industry is formulated into a knowledge based system wherein advisories are given to the user regarding key purchased material receipt inspection strategies.     

Bioprocess applications of model-based estimation techniques

The last decade has seen the development of a number of approaches for estimating those variables which are difficult to measure on-line in industrial process situations. Whilst a range of techniques is available, a common element is the use of process knowledge in the form of a system model. In the case of bioprocess systems, although a large range of models has been presented in the literature, their use in estimation schemes on an industrial scale has been limited. A number of reasons can be identified for their low level of utilisation. Of particular significance is the uncertainty which exists in quantifying system performance and the process-model mismatch which inevitably results. The level of ‘pre-defined model’ uncertainty, together with the knowledge gained during the course of the fermentation, serves to dictate estimator structure. The paper considers a range of estimation strategies and contrasts, through industrial applications, their performance characteristics and utility.     

Dental amalgam – the effect of the technology of alloy powder preparation on the corrosion behaviour and the release of mercury

Dental amalgams are based on a broad spectrum of materials differing in their chemical composition, metallurgical treatment, and in the way the initial alloys powders are prepared. In addition to their chemical composition, amalgams based on various powders differ in both their microstructure and the amount of mercury needed for preparation. All these facts may affect electrochemical processes occurring during their interaction with oral fluids, and also mercury release. While verifying the effect of the technology used for the preparation of the high‐copper ternary alloy powder on the properties of resulting amalgams, this study aimed at the mechanism of their interaction with a model saliva solution as well as mercury release was included. Measurements were done in a model saliva solution using standard electrochemical methods and exposition measurements. The interaction of individual types of amalgams with artificial saliva did not reveal any significant differences. The free corrosion potential of all these amalgams in an aerated solution settled in the range of values in which tin oxidation, resulting in a layer of insoluble corrosion producsts, turned out to be the dominant anodic process. The rate of mercury release was the lowest for amalgams based on a gas‐atomized alloy. The highest rate of mercury release, and also its dependence on time, was exhibited by lathe‐cut powder based amalgam. In addition to different volume fraction of the Ag‐Hg phase and the level of its tin alloying, this different behaviour may be explained by differences in the rate at which a layer of tin corrosion products acting as a barrier to mercury release is formed.     

A Proposal for Implementing Multi-User Data Base (MUD) Technology in and Academic Library

Multi-user Data base (MUD) technology, and its object-oriented descendant (MOO), is one of the most exciting tools to surface on the Internet, and offers libraries and librarians a unique opportunity to participate in creating user-friendly standardized interfaces to many of our most frequently used resources. These resources include those we access through the Internet already, using gopher, telnet, WWW, and FTP, and also those proprietary databases that we currently access through leased lines such as OCLC First Search, Prism, DIALOG, and many others. MOO technology is already being used successfully to create user-extensible collaborative professional environments for educators, astronomers, and computer network systems administrators. With the growing relevance of the Internet for libraries and other information professionals, it behooves the library community to engage those emerging technologies which will aloow us to interface most effectively with the Internet and its many resources, with the proprietary databases which we depend on, and with one another.     

Business intelligence approach to supporting strategy-making of ISP service management

The recent deregulation of telecommunication industry by the Taiwanese government has brought about the acute competition for Internet Service Providers (ISP). Taiwan’s ISP industry is characterized by the heavy pressure for raising revenue after hefty capital investments of last decade and the lack of knowledge to develop competitive strategies. To attract subscribers, all ISP dealers are making an all-out effort to improve their service management. This study proposes a Business Intelligence process for ISP dealers in Taiwan to assist management in developing effective service management strategies. We explore the customers’ usage characteristics and preference knowledge through applying the attribute-oriented induction (AOI) method on IP traffic data of users. Using the self-organizing map (SOM) method, we are able to divide customers into clusters with different usage behavior patterns. We then apply RFM modeling to calibrate customers’ value of each cluster, which will enable the management to develop direct and effective marketing strategies. For network resource management, this research mines the facility utilization over various administrative districts of the region, which could assist management in planning for effective network facilities investment. With actual data from one major ISP, we develop a BI decision support system with visual presentation, which is well received by its management staff.     

ARPO-2: An expert system for legal advice on the breach of building contracts

Although Berman and Hafner [Berman 1989, pp. 928–938] presented the possibility to adapt the model of reasoning of development of an expert system for medical diagnosis to the reasoning of a judge when he/she sentences criminals does not resemble the reasoning found in the decisions of physicians, mathematicians or statisticians.When a lawyer reasons, he/she not only looks for the solution of a case; he/she simultaneously looks for the bases on which his/her reasoning can rest [Galindo 1992, pp. 363–367]. That is to say, he/she not only needs to find the solution but moreover he/she has to find the references (laws, jurisprudence and bibliography) that allow him/her to argue the solution.In many cases, computer solutions to these reasoning processes have been made in a separated way: the solution to the cases using expert systems, and the search of documentation using information retrieval systems.This paper presents the ARPO-2 prototype, a solution integrating the two aspects of legal reasoning: an expert system which is able to simultaneously find the solution to a problem and to give the necessary references so that the lawyer argues the solution. The subject on which the prototype solves problems is the breach of building contracts.In this paper, we describe the process of development of an expert system for solving, justification and documentation of breach of contracts, giving details on the way how the objects that intervene in the case were defined as well as on the reasoning followed.This paper was funded in part by DGICYT, Spanish Civil Law Computerization Project: PB870-632.     

Distributed artificial intelligence for FMS scheduling, control and design support

The aim of this paper is to point out some of the abilities of Distributed Artificial Intelligence in the domain of scheduling, control and design support of Flexible Manufacturing Systems. A distributed management system is proposed, based on Distributed Problem Solving, sub-field of Distributed Artificial Intelligence. The basic concepts are the concept of Resource Management Entity to ensure local optimization of the management of resources and the concept of cooperation to provide ability for global and local consistency. The management of resources is associated to activities such as scheduling, control or simulation. It is shown that this system computes not only practicable schedulings, but also presents, on the one hand, some abilities in supporting the design and the robust optimization of Flexible Manufacturing Systems, and, on the other hand, some abilities in supporting real-time control of such systems. This enables, in future works, to design a Distributed Decision Support System for integrated scheduling, control and design support of production systems.     

Towards the next generation of artificial neural networks for civil engineering

The purpose of this paper is to stimulate interest within the civil engineering research community for developing the next generation of applied artificial neural networks. In particular, it identifies what the next generation of these devices needs to achieve, and provides direction in terms of how their development may proceed. An analysis of the current situation indicates that progress in the development of artificial neural network applications has largely stagnated. Suggestions are made for advancing the field to the next level of sophistication and application, using genetic algorithms and related techniques. It is shown that this approach will require the design of some very sophisticated genetic coding mechanisms in order to develop the required higher-order network structures, and will utilize development mechanisms observed in nature such as growth, self-organization, and multi-stage objective functions. The capabilities of such an approach and the way in which they can be achieved are explored with reference to the problems of: (a) determining truck attributes from the strain envelopes they induce in structural members when crossing a bridge, and; (b) developing a decision support system for dynamic control of industrialized manufacturing of houses.     

A Review of the Application of Meta-Heuristic Algorithms to 2D Strip Packing Problems

This paper is a review of the approachesdeveloped to solve 2D packing problems withmeta-heuristic algorithms. As packing tasks arecombinatorial problems with very large searchspaces, the recent literature encourages theuse of meta-heuristic search methods, inparticular genetic algorithms. The objective ofthis paper is to present and categorise thesolution approaches in the literature for 2Dregular and irregular strip packing problems.The focus is hereby on the analysis of themethods involving genetic algorithms. Anoverview of the methods applying othermeta-heuristic algorithms including simulatedannealing, tabu search, and artificial neuralnetworks is also given.     

Predicting the Outcome of Construction Litigation Using Boosted Decision Trees

Construction litigation has become commonplace in numerous construction projects, particularly in large contracts. Miscommunication, inadequate plans and specifications, rigid contracts, changes in site conditions, nonpayment, catch up profits, limitations on manpower, tools, and equipment, improper supervision, notice requirements, constructive changes not recognized as such by owner, delays, and acceleration measures provoke claims and often result in disputes. A boosted decision tree system was used to predict the outcome of construction litigation. The study was conducted by using the same 114 Illinois court cases that were used in earlier prediction studies conducted with artificial neural networks in 1998 and case-based reasoning in 1999, augmented by an additional 18 cases that were filed in 1990–2000. All cases were extracted from the Westlaw on-line service. The best prediction result obtained with boosted decision trees was 90%. The boosted decision tree model appears to be a promising tool to help create a dispute-free construction industry.