An expert-system approach to the assembly planning of roller chains

In this paper, assembly planning of roller chains using an expert system is described. An Expert System Building Tool is used for the development of the expert system. Production rules are presented in OPS-5 language, in view of the information supporting the development of the expert system The frame-based representation of data, inference mechanism and conflict resolution strategy of the system are explained and discussed in detail.     

An integrated expert-system builder

The Expert System Builder, an AI tool kit implemented in Common Lisp on Symbolics workstations within ESPRIT Project 96 is described. The Expert System Builder system is intended to industrialize the process of building expert systems by providing developers with several powerful modeling and architectural facilities not found in most AI tool kits. To reach this goal, support for knowledge modularization and reusability were included in the system. The process of knowledge transfer is examined, as well as reasoning and control in the system. The Expert System Builder's concept system, model system, and building method are discussed. An example is given to illustrate its use     

An approach to literate and structured formal developments

We present an approach to the literate and structured presentation of formal developments. We discuss the presentation of formal developments in a logical framework and distinguish three aspects: language-related aspects, structural aspects of proofs, and presentational aspects. We illustrate the approach by two examples: a simple mathematical proof of the Knaster-Tarski fixpoint theorem, and a formalization of the VDM development of a revision management system.     

An image annotation approach using location references to enhance geographic knowledge discovery

With the continuously increasing needs of location information for users around the world, applications of geospatial information have gained a lot of attention in both research and commercial organizations. Extraction of semantics from the image content for geospatial information seeking and knowledge discovery has been thus becoming a critical process. Unfortunately, the available geographic images may be blurred, either too light or too dark. It is therefore often hard to extract geographic features directly from images. In this paper, we describe our developed methods in applying local scale-invariant features and bag-of-keypoints techniques to annotating images, in order to carry out image categorization and geographic knowledge discovery tasks. First, local scale-invariant features are extracted from geographic images as representative geographic features. Subsequently, the bag-of-keypoints methods are used to construct a visual vocabulary and generate feature vectors to support image categorization and annotation. The annotated images are classified by using geographic nouns. The experimental results show that the proposed approach is sensible and can effectively enhance the tasks of geographic knowledge discovery.     

An MDA approach to knowledge engineering

This paper proposes an MDA approach to knowledge engineering, centered on the CommonKADS knowledge model. The latter corresponds to the CIM level of MDA whereas PRR, which represents production rules and rulesets, corresponds to the PIM level. The paper explores the mapping between CommonKADS knowledge models and production rules and rulesets based on PRR. Mapping CommonKADS knowledge models into PRR is very useful, due to the fact that the CIM level remains relatively unexplored, despite its key role in MDA. This motivates our choice to focus on the CIM and PIM levels. Furthermore, the mapping between PIM and PSM (i.e. the implementation of production rules in specific rule-based systems) constitutes less of an issue. To map CommonKADS knowledge models into PRR production rules and rulesets, we propose and illustrate a set of transformations. To ease these transformations, we start by grouping elements of the CommonKADS knowledge models into so-called “inference groups”. We propose and illustrate an algorithm that defines these inference groups automatically. The definition of transformations between models (CIM to PIM levels) requires a specific metamodel for CommonKADS as well as a dedicated metamodel for PRR. Unlike PRR, there is no published CommonKADS metamodel. This paper proposes a comprehensive CommonKADS knowledge metamodel. We describe and discuss an example, applying the whole approach.     

Algebraic approach to controller design using structured singular value

The aim of this paper is to show an algebraic approach to controller design using the structured singular value (denoted μ) as a robust stability and performance indicator. The algebraic μ-synthesis is applied to three different problems–time-delay systems, the HIMAT vehicle model and the two-tank system. A way of treating general delayed systems with uncertain time delays via the linear fractional transformation is shown. A simple controller is derived, which handles uncertain time delay in both the numerator and denominator of an anisochronic system. The overall performance is verified by simulations for all systems and compared with the D–K iteration.     

KASER: knowledge amplification by structured expert randomization

In this paper and attached video, we present a third-generation expert system named Knowledge Amplification by Structured Expert Randomization (KASER) for which a patent has been filed by the U.S. Navy's SPAWAR Systems Center, San Diego, CA (SSC SD). KASER is a creative expert system. It is capable of deductive, inductive, and mixed derivations. Its qualitative creativity is realized by using a tree-search mechanism. The system achieves creative reasoning by using a declarative representation of knowledge consisting of object trees and inheritance. KASER computes with words and phrases. It possesses a capability for metaphor-based explanations. This capability is useful in explaining its creative suggestions and serves to augment the capabilities provided by the explanation subsystems of conventional expert systems. KASER also exhibits an accelerated capability to learn. However, this capability depends on the particulars of the selected application domain. For example, application domains such as the game of chess exhibit a high degree of geometric symmetry. Conversely, application domains such as the game of craps played with two dice exhibit no predictable pattern, unless the dice are loaded. More generally, we say that domains whose informative content can be compressed to a significant degree without loss (or with relatively little loss) are symmetric. Incompressible domains are said to be asymmetric or random. The measure of symmetry plus the measure of randomness must always sum to unity.     

An effective structured approach to finding optimal partitions of networks

The problem considered is to partition an edge-valued, node-weighted, finite, connected, simple graph (called a network) into disjoint subgraphs, each of which has a total node weight that does not exceed a weight constraint, and so that the total value of edges interconnecting the subgraphs is minimized. This paper presents a new approach which is effective in solving the problem, and fast enough to be practical in finding optimal partitions of large networks. It uses the concept of “divide and conquer” to partition the problem into several subproblems, which can be efficiently solved one after the other by using depth-first search and branch-and-bound principle. The operations required under the algorithms are additions, comparisons, and logical operations on binary vectors.     

Heuristic knowledge representation of production scheduling: An integrated modeling approach

In spite of the efforts to automate production scheduling systems, most manufacturing plants rely on human schedulers for their practical production scheduling due mainly to the complexity and unpredictability of the manufacturing systems. One of the reasons for the difficulties in automating the production scheduling process is the lack of an explicit representation scheme of heuristic scheduling knowledge.

In this paper, an integrated modeling approach is presented to represent the complicated heuristic knowledge in production scheduling systems. The integrated modeling approach is based on object-oriented and event-driven modeling. It provides the explicit, declarative and executable representation of heuristic scheduling knowledge which aids the communication between human schedulers and system analysts. The declarative and executable representation of scheduling knowledge will enhance the flexibility of production scheduling systems and aid the development of production scheduling information systems.

A heuristic production scheduling model of a tire manufacturing system is used throughout the paper to illustrate the concepts and applicability of the approach.     

An approach to learning mathematics through knowledge engineering

This study deals with an AI approach to learning mathematics, which is realised through the development of expert system knowledge bases by using programming in logic and PROLOG. The paper presents this approach, and examines its theoretical values in the light of recent findings in computer science, mathematics education, didactics, psychology and philosophy. The examined values show evidence for the relevance of the approach to the computer-assisted learning of mathematics.     

An intrusion detection and alert correlation approach based on revising probabilistic classifiers using expert knowledge

Bayesian networks are important knowledge representation tools for handling uncertain pieces of information. The success of these models is strongly related to their capacity to represent and handle dependence relations. Some forms of Bayesian networks have been successfully applied in many classification tasks. In particular, naive Bayes classifiers have been used for intrusion detection and alerts correlation. This paper analyses the advantage of adding expert knowledge to probabilistic classifiers in the context of intrusion detection and alerts correlation. As examples of probabilistic classifiers, we will consider the well-known Naive Bayes, Tree Augmented Naïve Bayes (TAN), Hidden Naive Bayes (HNB) and decision tree classifiers. Our approach can be applied for any classifier where the outcome is a probability distribution over a set of classes (or decisions). In particular, we study how additional expert knowledge such as “it is expected that 80 % of traffic will be normal” can be integrated in classification tasks. Our aim is to revise probabilistic classifiers’ outputs in order to fit expert knowledge. Experimental results show that our approach improves existing results on different benchmarks from intrusion detection and alert correlation areas.     

SAFARI: a structured approach for automatic rule

This paper describes a new algorithm for obtaining rules automatically from training examples. The algorithm is applicable to examples involving both objects: with discrete and continuous-valued attributes. The paper explains a new quantization procedure fur continuous-valued attributes and shows how appropriate ranges of values of various attributes are obtained. The algorithm uses a decision-tree-based approach for obtaining rules, but unlike other tree-based algorithms such as ID3, it allows more than one attribute at a node which greatly improves its performance. The ability of the algorithm to obtain a measure of partial match further enhances its generalization characteristic. The algorithm produces the same rules irrespective of the order of presentation of training examples. The algorithm has been demonstrated on classification problems. The results have compared favorably with those obtained by existing inductive learning algorithms.     

Analysing industrial district performances: A structured approach

The goals of an organization of data and information collected from the European industrial systems and concerning networks of enterprises, mainly small-mid enterprises (SMEs), are many:

(a)

to offer an intelligent support system (ISS) to industrial analysers when they try to understand if a SME network, either cluster or industrial district, could be enforced by proper financing, or it cannot give sufficient assurance for a new development;

(b)

to offer to political people a support in understanding the dynamics of these SME networks, in order to be able to take decisions about public politics;

(c)

to give tools for analysing the performance of these industrial bodies to industrial people, mainly technicians and managers, such to be able to apply new strategies for their improvement;

(d)

to give information and data to researchers operating in university and RTD centers, such to be able to improve their knowledge about these so important industrial bodies.

To reach this goal, the aim of the EU-funded CODESNET (COllaborative DEmand & Supply NETwork) project is to give new ideas and concepts sufficient to drive the attention of the above-mentioned different types of people towards the SME networks and districts. To this aim, a crucial problem must be approached and solved: which model of a SME network should be stated and used as the basis for developing a clear and useful ISS, that is, able to collect information and data from existing SME networks and transfer such data into standard formats, easy to be read by both industrial people and scientific researchers. The present paper describes the theoretical methodology on which the data organization and interpretation adopted in the CODESNET project is based. The application of an original meta-model of SME network, developed in the mentioned project, is detailed according to the following steps. After the meta-model formulation (in Section 2), it is shown how the variables to be measured (such to have a clear understanding of the network status), have to be selected, and how the main issues concerning the design and management of the network has to be classified (Section 3). Then, it will be shown how the archive of both data/information from existing SME networks (for purpose of comparison-based analysis) and the catalogue of technical/scientific reports (for purpose of justifying the analysis considerations) has been organized in an integrated form. The scope is to give at disposal of industrial people the mentioned ISS which allow them to approach some main issues concerning the network design and management (Section 4). An example of ISS application in an Italian industrial district will be presented, such to illustrate the CODESNET results’ usefulness.     

Building insightful simulation models using Petri Nets — A structured approach

Petri Nets have essential strengths in capturing a system's static structure and dynamics, its mathematical underpinning, and providing a graphical representation. However, visual simulation models of realistic systems based on Petri Nets are often perceived as too large and too complex to be easily understood. This constrains stakeholders in participating in such modeling and solution finding, and limits acceptance. We address this issue by considering a structured approach for guiding the analyst in creating more insightful models. Key elements are a domain-related reference architecture that supports conceptual modeling coupled with uniform rules for mapping high-level concepts onto low-level Petri Net components. The proposed approach is implemented and illustrated in the manufacturing domain.     

The design of a fuzzy system shell using a database approach

This study presented a prototype of fuzzy system shell called FuzzyAccess. Using Microsoft Access database as a developing tools, the proposed system provided a friendly interface for user self-building a fuzzy system. A novice who has no programming-knowledge can also self-define a new fuzzy project. The main contributions of the proposed system were that using SQL method to search the candidate rules in rule evaluation stage and providing an integrated tuning interface for system adjustment. The SQL method can significantly reduce the search time in rule evaluation. The integrated tuning interface can assist user quickly inspecting the influence among different system parameters adjustment and reducing the system development time.     

An algebraic approach to revising propositional rule-based knowledge bases

One of the important topics in knowledge base revision is to introduce an efficient implementation algorithm. Algebraic approaches have good characteristics and implementation method; they may be a choice to solve the problem. An algebraic approach is presented to revise propositional rule-based knowledge bases in this paper. A way is firstly introduced to transform a propositional rule-based knowledge base into a Petri net. A knowledge base is represented by a Petri net, and facts are represented by the initial marking. Thus, the consistency check of a knowledge base is equivalent to the reachability problem of Petri nets. The reachability of Petri nets can be decided by whether the state equation has a solution; hence the consistency check can also be implemented by algebraic approach. Furthermore, algorithms are introduced to revise a propositional rule-based knowledge base, as well as extended logic programming. Compared with related works, the algorithms presented in the paper are efficient, and the time complexities of these algorithms are polynomial.     

An agent-based approach to knowledge management in distributed design

The collaboration process among individuals with heterogeneous skills in a distributed virtual environment represents a crucial element of the extended enterprise. In order to achieve global optima in design, there is an increasing need for design teams to establish and maintain cooperative work through effective communication, co-location, coordination and collaboration at the knowledge level. Because of the distributed nature of users and information resources involved in the design process, the need for appropriate knowledge management tools is imperative. This paper proposes an agent-based architecture to support multi-disciplinary design teams that cooperate in a distributed design environment (DDE). Using ontologies and multi-agent systems (MAS), the proposed framework aims to optimise design process operation and management by supporting the dialogue among distributed design actors. Received: February 2005/Accepted: January 2006     

An approach to support SMEs in manufacturing knowledge organization

Different kinds of technological data are available in manufacturing enterprises, concerning the resources available as well as the processes and the components needed for the production of specific products. These data usually are not stored in a centralized knowledge management system, thus one of the main problem of managers, especially in small enterprises, is to efficiently manage their data and reuse the knowledge deriving from previous products when a new product has to be produced. Starting form the analysis of the technological data available in manufacturing enterprises, we defined a formal model as set of matrices; their analysis allows the definition of a data model to structure the technological information. The model is at the basis of the proposed system, called manufacturing knowledge organization (MAKO) to support managers in structuring and reusing the technological knowledge available in their enterprise. A prototype of the MAKO system was implemented by using open-source software and its potentialities are shown in a case study.