Abstract: Rule-based systems (also known as production systems or expert systems) are the simplest form of artificial intelligence. A rule based system uses rules as the knowledge representation for knowledge coded into the system [1][3][4] [13][14][16][17][18][20]. The definitions of rule-based system depend almost entirely on expert systems, which are system that mimic the reasoning of human expert in solving a knowledge intensive problem. Instead of representing knowledge in a declarative, static way as a set of things which are true, rule-based system represent knowledge in terms of a set of rules that tells what to do or what to conclude in different situations.

Abstract: The success of intelligent signal processing systems lies in their capabilities of logical reasoning, decision making, adaptation, self-organization and communication in different modalities: speech, image, language, and so on This article describes how rule-based expert systems could be useful for signal processing tasks Heuristic problem solving is introduced, which is followed by some fundamental aspects of conventional rule-based systems and fuzzy expert systems The design of a fuzzy expert system for a forecast problem is also illustrated

Abstract: In a system for optimizing crop growth, vegetation is cultivated in a contained environment, such as a greenhouse, an underground cavern or other enclosed space. Imaging equipment is positioned within or about the contained environment, to acquire spatially distributed crop growth information, and environmental sensors are provided to acquire data regarding multiple environmental conditions that can affect crop development. Illumination within the contained environment, and the addition of essential nutrients and chemicals are in turn controlled in response to data acquired by the imaging apparatus and environmental sensors, by an “expert system” which is trained to analyze and evaluate crop conditions. The expert system controls the spatial and temporal lighting pattern within the contained area, and the timing and allocation of nutrients and chemicals to achieve optimized crop development. A user can access the “expert system” remotely, to assess activity within the growth chamber, and can override the “expert system”.

Abstract: The objective of this technical note is to illustrate the application of fuzzy expert systems to the modeling of a practical problem—that of predicting the labor productivity of two common industrial construction activities: rigging pipe and welding pipe. This note illustrates how to develop and test such a model, given the realistic constraints of subjective assessments, multiple contributing factors, and limitations on data sets. The factors that affect the productivity of each activity are identified, and fuzzy membership functions and expert rules are developed. The models are validated using data collected from an actual construction project. The resulting models are found to have high linguistic prediction accuracies. This note is of relevance to researchers by demonstrating how a fuzzy expert system can be developed and tested. It is of relevance to industry practitioners by illustrating how fuzzy logic and expert systems modeling can be exploited to help them solve real world problems.

Abstract: This paper proposes an expert system called VIBEX (VIBration EXpert) to aid plant operators in diagnosing the cause of abnormal vibration for rotating machinery. In order to automatize the diagnosis, a decision table based on the cause-symptom matrix is used as a probabilistic method for diagnosing abnormal vibration. Also a decision tree is used as the acquisition of structured knowledge in the form of concepts is introduced to build a knowledge base which is indispensable for vibration expert systems. The decision tree is a technique used for building knowledge-based systems by the inductive inference from examples and plays a role itself as a vibration diagnostic tool. The proposed system has been successfully implemented on Microsoft Windows environment and is written in Microsoft Visual Basic and Visual C++. To validate the system performance, the diagnostic system was tested with some examples using the two diagnostic methods.

Abstract: The effective debugging of ontologies is an important prerequisite for their successful application and impact on the semantic web. The heart of this debugging process is the diagnosis of faulty knowledge bases. In this paper we define general concepts for the diagnosis of ontologies. Based on these concepts, we provide correct and complete algorithms for the computation of minimal diagnoses of knowledge bases. These concepts and algorithms are broadly applicable since they are independent of a particular variant of an underlying logic (with monotonic semantics) and independent of a particular reasoning system. The practical feasibility of our method is shown by extensive test evaluations.

Abstract: Many industries have deployed expert systems (ESs) to provide support for solving complicated and specialized problems since 1980. Because ESs are originally designed for generating feasible alternatives in an automated manner, users, especially decision makers, expect ESs to make decisions proactively and intelligently by automatically detecting users' contextual data. In other words, decision makers require decision support systems (DSSs) to be reinforced with proactive and intelligent ESs that can utilize contextual data. Meanwhile, ubiquitous technology-based applications currently only provide limited personalization services that use the user's context and preferences; in other words, these systems do not fully make use of sophisticated decision making capabilities. Hence, this paper describes how decision making and context-aware computing are jointly used to establish ubiquitous computing technology-based applications. To do so, we propose an amended DSS paradigm, Context-Knowledge-Dialogue-Data-Model (CKDDM). This model describes what may be considered for future DSSs when we regard ubiquitous computing technology as an inevitable effect that changes how decision making decisions are described. Under the CKDDM paradigm, a framework of ubiquitous decision support systems (ubiDSS) is addressed with the description of the subsystems within. To show the feasibility of ubiDSS, a prototype system, Context-Aware Multi Agent System-My Optimization (CAMA-myOpt) has been implemented as an illustrative example system.

Abstract: This monograph provides novel insights into cognitive mechanisms underlying the processing of sound and music in different environments. A solid understanding of these mechanisms is vital for numerous technological applications such as for example information retrieval from distributed musical databases or building expert systems. In order to investigate the cognitive mechanisms of music perception fundamentals of hearing psychophysiology and principles of music perception are presented. In addition, some computational intelligence methods are reviewed, such as rough sets, fuzzy logic, artificial neural networks, decision trees and genetic algorithms. The applications of hybrid decision systems to problem solving in music and acoustics are exemplified and discussed on the basis of obtained experimental results.

Abstract: The surface of stereolithography parts become rough due to the stair-stepping effect and burrs from the support structure. Therefore, most parts need some finishing work for further applications. Because post-processing operations are performed by skilled workers and require additional time and cost, the reduction of post-processing time and cost is a high priority. Basic approaches to minimizing post-processing are investigated. Surface roughness is analyzed through theoretical models and experiments developing an interpolation method to predict the behavior of the roughness under various equipment conditions and fabrication styles are conducted. Part orientation is optimized by a post-processing objective function. To accelerate the optimization, a model mapping method is developed and verified. An expert system is implemented by the suggested algorithms and examined by several models in real a workshop.

Abstract: A new method is proposed for selecting the most appropriate rapid prototyping process according to user's specific requirements by using the expert system and fuzzy synthetic evaluation. The selection process is divided into two stages. First, it is necessary to generate feasible alternatives, which are executed under the expert system environment. Second, given those feasible alternatives, the fuzzy synthetic evaluation approach is employed to produce a ranking order of the alternatives and to finalize the most suirapid prototyping system. One distinctive characteristic of this method is that quantitative as well as qualitative measures are employed, providing more accurate results. The decision system developed based on the proposed method is composed of four modules: a database to store the specifications of various rapid prototyping processes; a knowledge-based expert system for determining the feasible alternatives; a fuzzy synthetic evaluation model to select the most suitable rapid prototyping proc...

Abstract: The technology help desk function has grown in importance as information technology has proliferated throughout the organization. The primary objective of the help desk is to resolve problems related to IT in the organization. As such, the agents in the help desk must be very knowledgeable of the information systems, applications, and technologies supported. Most efforts at improving help desk performance have been to make the current system more efficient through application of information technologies. In this paper we propose a new approach, called a knowledge management-centric help desk. The proposed knowledge management system draws upon diverse knowledge sources in the organization including databases, files, experts, knowledge bases, and group chats. The knowledge management system is designed to be incorporated into the daily operation of the help desk in order to ensure high utilization and maintenance of the knowledge stores. The benefits of the knowledge management-centric help desk are evaluated using a simulation study with actual data from a help desk. The experimental results indicate the knowledge management-centric approach would significantly reduce the time to resolve problems and improve the throughput of the help desk.

Abstract: When a pig shows disease symptoms, it is important to make an accurate diagnosis to support control strategies. Diagnosing diseases in pigs requires considerable expertise. Only a few experts have the ability to do this, and each expert has his own specific domain. To make it more generally accessible and reduce the waiting time, an expert system named Pig-Vet has been developed by China Agricultural University. Based on investigations, this paper analyzes users' needs and describes the architecture, main components, and their functions. The system has over 300 rules and 202 images and graphics for different types of diseases and symptoms. It can diagnose 54 types of common diseases of pigs. At present the system is in pilot in north of China. The stage achievements in developing the intellectual expert system of pig disease diagnosis are summarized.

Abstract: The paper presents case based reasoning (CBR) methods of cases similarity calculation applied in the elaborated expert system for aided design ship's engine room automation These methods were implemented in the database application and expert system following the example of main propulsion automation Their results were compared and analyzed for similar ships search in the database For verification of the methods implemented in the database application fuzzy logic in expert system has been used

Abstract: System for identifying a threat associated person among a crowd in a protected area, the system including an expert system network, and a supervising system coupled with the expert system network, the expert system network including a plurality of local expert systems, each of the local expert systems being associated with a respective one of a plurality of surveillance fields within the protected area, each the local expert systems being coupled with a plurality of data acquisition systems of various types, each of the data acquisition systems acquiring threat related data and marking related data respective of selected persons among the crowd within the respective surveillance field, each the local expert systems determining a respective local threat level for every one of the selected persons within the respective surveillance field, according to the threat related data and the marking related data, the supervising system coordinating the operation of the local expert systems, the supervising system receiving from each of the local expert systems the respective local threat level, for every one of the selected persons within the respective surveillance field, the supervising system determining a global threat level according to the local threat levels, thereby identifying the threat associated person.

Abstract: Threat protection networks are described. Embodiments of threat protection network in accordance with the invention use expert systems to determine the nature of potential threats to a remote computer. In several embodiments, a secure peer-to-peer network is used to rapidly distribute information concerning the nature of the potential threat through the threat protection network. One embodiment of the invention includes at least one client computer connected to a network, a server that stores threat definition data and is connected to the network, an expert system in communication with the server. In addition, the client computer is configured to refer potential threats to the server, the server is configured to refer to the expert system any potential threat forwarded by a client computer that is not identified in the threat definition data and the expert system is configured to determine whether the potential threat is an actual threat by exposing at least one test computer to the potential threat and observing the behavior of the test computer.

Abstract: A method for controlling a non-linear process includes the steps of first providing a controller that is operable to receive inputs representing measured variables of the process and predicting on an output of the controller predicted control values for manipulatible variables that control the process. An expert system is provided that models the actions of an operator of the process over an operating region of the process that represents a set of rules for actions to be taken by an operator upon the occurrence of predetermined conditions in the operation of the process. The operation of the controller is modified with the expert system when one of the predetermined conditions exists.

Abstract: This work presents the development of a prototype expert system (ES) for the machine selection of manufacturing systems. This tool, called ESMRS (Expert System for Manufacturing Resource Selection) is used in a simulation based approach in order to structure the solution search mechanism and to overcome the try and error aspect. In fact, in such an approach a number of 'simulation-ES optimization' cycles are run until obtaining non-improvable performance measures. The ES main role is to suggest resource modifications based on due date related performance measures obtained through simulation. So, this paper introduces the 'ES-simulation approach' that constitutes the utilization scope of ESMRS and then describes the ES static and dynamic knowledge representation before presenting the basic ES features as well as its development using a commercial ES shell. Finally a simple case study illustrates the validity of the approach and its potential applicability for real cases.

Abstract: A Web-enabled hybrid approach to strategic marketing planning is established in this paper. The proposed approach combines the group Delphi technique with a Web-based expert system, called WebStra (developed by the author), to support some key stages of the strategic marketing planning process. The Web-enabled approach is based upon client-server architecture that enables the sharing and delivery of computerised planning models and knowledge via the Internet, intranets or extranets, which allows widespread access by authorised users around the clock, across the world or throughout the company. In order to assess the overall value of the proposed approach, case-based evaluation work has been undertaken. Evaluation findings indicate that the approach is effective and efficient in terms of overcoming time and geographical barriers, saving decision-making time, coupling analysis with human judgment, helping improve decision-making quality, etc.

Abstract: This paper describes GRAPE, an expert component for a scientific Conference Management System (CMS), to automatically assign reviewers to papers, one of the most difficult processes of conference management In the current practice, this is typically done by a manual and time-consuming procedure, with a risk of bad quality results due to the many aspects and parameters to be taken into account, and on their interrelationships and (often contrasting) requirements The proposed rule-based system was evaluated on real conference datasets obtaining good results when compared to the handmade ones, both in terms of quality of the assignments, and of reduction in execution time

Abstract: New trends in development of databases and expert systems seems to underline the role of graphical specification tools, visual information modeling and formal verification procedures. This paper incorporates these new ideas and, moreover, tries to present putting them in engineering practice. The main goal is to move the design procedure to a more abstract, logical level, where knowledge specification is based on use of abstract rule representation, called eXtended Tabular Trees. The main idea behind XTT is to build a hierarchy of ObjectAttribute-Value Tables (OAV table). The basic component for knowledge specification is an OAV table. It is analogous to a relational database table; however, it contains conditional part and decision columns. Moreover, the attribute values can be non-atomic ones. Each row provides specification of a single rule. The OAV tables can be connected with one another through appropriate links specifying the control flow in the system. The design specification is automatically translated into Prolog code, so the designer can focus on logical specification of safety and reliability. On the other hand, formal aspects such as completeness, determinism, etc. are automatically verified on-line during the design, so that it verifiable characteristics are preserved. From practical point of view, the design process is performed with a intelligent tool named Mirella.

Abstract: Artificial intelligence (AI) is a computer based science which aims to simulate human brain faculties using a computational system. A brief history of this new science goes from the creation of the first artificial neuron in 1943 to the first artificial neural network application to genetic algorithms. The potential for a similar technology in medicine has immediately been identified by scientists and researchers. The possibility to store and process all medical knowledge has made this technology very attractive to assist or even surpass clinicians in reaching a diagnosis. Applications of AI in medicine include devices applied to clinical diagnosis in neurology and cardiopulmonary diseases, as well as the use of expert or knowledge-based systems in routine clinical use for diagnosis, therapeutic management and for prognostic evaluation. Biological applications include genome sequencing or DNA gene expression microarrays, modeling gene networks, analysis and clustering of gene expression data, pattern recognition in DNA and proteins, protein structure prediction. In the field of hematology the first devices based on AI have been applied to the routine laboratory data management. New tools concern the differential diagnosis in specific diseases such as anemias, thalassemias and leukemias, based on neural networks trained with data from peripheral blood analysis. A revolution in cancer diagnosis, including the diagnosis of hematological malignancies, has been the introduction of the first microarray based and bioinformatic approach for molecular diagnosis: a systematic approach based on the monitoring of simultaneous expression of thousands of genes using DNA microarray, independently of previous biological knowledge, analysed using AI devices. Using gene profiling, the traditional diagnostic pathways move from clinical to molecular based diagnostic systems.

Abstract: In this chapter, I have shown that problem solving depend on how the problem is represented to the learners. That representation affects, to some degree, they ways that problem solvers represent problem mentally. A more efficacious way of affecting those internal mental representation is to provide students with a variety of knowledge representation tools, such as concept maps, expert systems, and systems dynamics tools, to represent the problem space, that is, their mental representation of the problem and the domain knowledge required to solve it.

Abstract: System diagnosis is an integral part of any Integrated System Health Management application. Diagnostic applications make use of system information from the design phase, such as safety and mission assurance analysis, failure modes and effects analysis, hazards analysis, functional models, fault propagation models, and testability analysis. In modern process control and equipment monitoring systems, topological and analytic , models of the nominal system, derived from design documents, are also employed for fault isolation and identification. Depending on the complexity of the monitored signals from the physical system, diagnostic applications may involve straightforward trending and feature extraction techniques to retrieve the parameters of importance from the sensor streams. They also may involve very complex analysis routines, such as signal processing, learning or classification methods to derive the parameters of importance to diagnosis. The process that is used to diagnose anomalous conditions from monitored system signals varies widely across the different approaches to system diagnosis. Rule-based expert systems, case-based reasoning systems, model-based reasoning systems, learning systems, and probabilistic reasoning systems are examples of the many diverse approaches ta diagnostic reasoning. Many engineering disciplines have specific approaches to modeling, monitoring and diagnosing anomalous conditions. Therefore, there is no "one-size-fits-all" approach to building diagnostic and health monitoring capabilities for a system. For instance, the conventional approaches to diagnosing failures in rotorcraft applications are very different from those used in communications systems. Further, online and offline automated diagnostic applications are integrated into an operations framework with flight crews, flight controllers and maintenance teams. While the emphasis of this paper is automation of health management functions, striking the correct balance between automated and human-performed tasks is a vital concern.

Abstract: The paper presents a new control strategy and its real-time implementation for a power transmission line inspection robot based on expert system design methods. In this paper, an algorithm is proposed to coordinate the operations between distributed expert systems, in which the principle of the goodness to fit to the rules and facts is employed for decision making and reasoning. To implement the control strategy, a combination of computer languages including C, VC++ and CLIPS are adopted that provide a convenient and effective software platform. On-line experiment results show that the control strategy can guide the inspection robot to patrol along the transmission lines and cross various typical obstacles efficiently. At the locations of corners and bends of the transmission line, more complicated obstacles occur, so two sub-expert systems work together and guide the robot passing through the locations smoothly. At those locations, the speed of the robot obviously slows down for safety consideration