Discussion: Knowledge-based advisory system for flexible pavement routine maintenance

This paper presents a low cost knowledge based system (KBS) framework for design of bending die. Considerations for development of KBS are discussed at some length. The proposed framework divides the task of development of expert system into different modules for major activities of bending die design. The procedure of development of KBS modules is also described at length. Production rules for each module are recommended to be coded in the AutoLISP language and designed to be loaded into the prompt area of AutoCAD or through user interface created using Visual Basic. Each module of the proposed framework is user interactive. Development of one module of the proposed framework is also described at length. This module is capable to assess manufacturability of bending sheet metal parts. An illustrative example is also included to demonstrate the usefulness of this module. The proposed system framework is flexible enough to accommodate new acquired knowledge. As the proposed system is implementable on a PC having AutoCAD software, therefore its low cost of implementation makes it affordable even by small scale sheet metal industries.

Financial industry is a core industry in Hong Kong. The business systems in financial institutes are widely applied throughout their front, mid, and back office. The system specialist who supports these systems must have finance and information-systems knowledge. This multi-disciplinary requirement leads to difficulties in finding capable candidates. It is reasonably assumed that a knowledge-based system (KBS) with the intelligence of a system specialist can assist a helpdesk to support the business systems. However, KBS development involves many known issues. In particular, the uncertainties of collected knowledge should be discussed and remodelled iteratively until the final knowledge set is close to the actual knowledge. Although the literature states that it is theoretically feasible to use Unified Modelling Language (UML) on knowledge acquisition, case studies on this area to date have been insufficient, hence this research experiment UML on developing a KBS for supporting business systems in a financial institute. The method of using UML diagrams is documented throughout the study. The results show that the UML was useful in different stages of KBS development. The case study articulates how the KBS helps to solve business system problems in the company. In summary, this paper can shed light on future research in using UML for KBS development.

Dutch research on knowledge-based instructional systems: Introduction to the special issue

The development of an online knowledge-based expert system for machinability data selection

This paper presents a framework called logical knowledge object (LKO), which is taken as a basis of the dependable development of knowledge based systems(KBSs). LKO combines logic programming and object-oriented programming paradigms, where objects are viewed as abstractions with states, constraints, behaviors and inheritance. The operational semantics defined in the style of natural semantics is simple and clear. A hybrid knowledge representation amalgamating rule, frame, semantic network and blackboard is available for both most structured and flat knowledge. The management of knowledge bases has been formally specified. Accordingly, LKO is well suited for the formal representation of knowledge and requirements of KBSs. Based on the framework, verification techniques are also explored to enhance the analysis of requirement specifications and the validation of KBSs. In addition, LKO provides a methodology for the development of KBSs, applying the concepts of rapid prototyping and top-down design to deal with changing and incomplete requirements, and to provide multiple abstract models of the domain, where formal methods might be used at each abstract level.

Research in verification and validation (V&V) of knowledge based systems (KBS) has emerged as a distinct field in the last decade and is intended to address issues associated with KBS quality aspects and to credit such applications to the same degree as conventional applications. Part of the knowledge and techniques developed are now ready to be transferred to industry for the implementation of software certification. Certification is probably the most advanced use of the V&V methods, techniques and knowledge that have been developed so far. The paper approaches the challenging issues of certifying the knowledge base (KB) component of a KBS. KB certification uses a number of different certification methods such as static analysis, testing, inspection, and modeling to assess the quality of the KB component. Although these methods are currently used in KBS development, it is not yet clear how they would be applied by an independent certification organization to arrive at a pass/fail decision. The article discusses the components of KB certification and identifies application areas directly connected with industrial needs.

Knowledge Based System (KBS) is a problem solving approach that makes use of human knowledge in decision strategies. Modeling and representing imperfect human knowledge associated with uncertainty is an important task in KBS development. There are various types of uncertainty, and randomness and fuzziness are among the most important. Handling hybrid uncertainty in one KBS is critical to support real world applications. Knowware System (KWS) is an intelligent tool designed to support application developers in constructing customized hybrid KBS without requiring developers being familiar with relevant intelligent techniques. It is essential for KWS to construct corresponding inference structure in resulting KBS and process the inference with hybrid uncertainty. To fulfill this requirement the extended Truth Value Flow Inference (TVFI) and Interval-Valued Confidence (IVC) have been defined and developed as ambedded mechanisms of KWS, and the hybrid logic has been adopted for the framework of handling hybrid uncertainty.This chapter discusses the IVC for the inference in hybrid KBS constructed by KWS with hierarchical knowledge representation. The knowledge content (precise or imprecise) represented in multiple units of knowledge hierarchy and the confidence obtained during inference process are treated as at two levels separately but simultaneously based on the extended TVFI. With the basic form of IVC, a fuzzy truth value is represented as a fuzzy number defined as a three-parametric triangular type-1 fuzzy set on the unit interval [0, 1]. The inference with both fuzzy truth and probability results an Extended Interval-Valued Confidence (EIVC) which is an interval type-2 fuzzy set on [0, 1] having the probability as an uncertainty measure on the fuzzy truth. The main focus of discussion will be put on interval-valued confidence. To provide the background of discussion, the KWS scheme, the extended TVFI and the concepts of hybrid logic will be briefly introduced.KeywordsUncertaintyRandomnessFuzzinessKnowwareSystemHybridLogicInterval-Valued Confidence

The use of knowledge-based systems (KBS) in the development of energy management system (EMS) applications is addressed. Since the user interaction principles in today's EMSs are not considered good enough, a tentative specification for the next generation of EMS applications is proposed. The justification for the use of KBS technology in power system operation is discussed, and a prototype KBS development environment is presented. The goal of this project was to get security analysis tools into daily operation through a user-friendly and powerful man-machine interface. Dedicated hardware (LISP-machine) and sophisticated software tools (expert system shell) were used in the KBS development environment. >

Different industries were transitioning to the utilization of Industry 4.0 tools such as Artificial Intelligence (AI) techniques particularly Neural Network Modelling. The neural network application in pavement management is a serviceable tool to forecast the occurrence of pavement distress which leads to efficient allocation of budget for pavement maintenance. The aim of this research is to create a model for predicting the percentage occurrence of pothole in a flexible pavement and investigating the relative importance of the traffic and climate – associated factors. A database of 55 datasets was obtained including input parameters such as temperature, precipitation, pavement age, total Average Annual Daily Traffic (AADT) and AADT of heavy vehicles and target output which is the pothole % occurrence. Using the database, a backpropagation – neural network model (BP–NN) was established to forecast the percentage occurrence of potholes in a flexible pavement. The weights and biases generated from the simulation of the best model was employed to achieve a comprehensive sensitivity analysis to explore the effect of the input parameters to the pothole % occurrence. Results show that the BP-NN can effectively predict the pothole % occurrence in a flexible pavement and the best model generated has a topology of 5-12-1 (input-hidden-output). Additionally, the AADT of heavy vehicles is the most influential parameter affecting pothole % occurrence in flexible pavements based on the sensitivity analysis performed using Garson's algorithm.

The Log Quality Monitoring System (LQMS) is a medium-sized knowledge-based system that was developed to address the problem of providing real-time assistance to the wireline field engineer. The authors discuss the motivation for the project, review the major decisions that were made, detail how they affected the direction of the project, and identify the basic lessons that were learned. The research version of LQMS was developed at Schlumberger-Doll Research over a period of about three and a half years. The project successfully dealt with several thorny issues in the development of knowledge-based systems: multiple domain experts, real time constraints, embedded environment, coordination and communication of multiple knowledge sources, and technology transfer. The project evolved from an exploratory, rapid prototyping style of development to a more traditional specify/design/implement/test methodology. Much of this evolution was driven by the field testing and technology transfer requirements of the later stages of the project. >

This article alms to provide biology educators with some simple Ideas of how techniques used In the development of Knowledge-Based Systems (KBS) can assist in the analysis of classification problems in school biology. The major focus of this paper is not to review KBS technology, but to show how some of the tools of thought which can be used to design and develop these systems can help biology teachers. In so doing, some valuable didactic ideas that may be transferred are described. The paper looks at rule-based systems and applies ideas to some examples of biological classification namely, classifying vertebrates and bird wings. Following on from this, some more general Issues are discussed about concepts and classification

Expert System to Control Construction Problems in Flexible Pavements

<p>Bridges are particularly vulnerable elements of transport infrastructures. In many cases, bridge structures may be subject to higher volumes of traffic and higher loads as well as more severe environmental conditions than it was designed. Sound procedures to ensure monitoring, quality control, and preventive maintenance systems are therefore vital. The paper presents main challenges and arriving possibilities in management of bridge structures, including: relationships between environment and bridge infrastructure, improvement of diagnostic technologies, advanced modelling of bridges in computer-based management systems, development of knowledge-based expert systems with application of artificial intelligence, applications of technology of Bridge Information Modelling (BrIM) with augmented and virtual reality techniques. Presented activities are focused on monitoring the safety of bridges for lowering the risk of an unexpected collapse significantly as well as on efficient maintenance of bridges as components of transport infrastructure − by means of integrated management systems.</p>

The development, validation and implementation of knowledge-based systems

An integrated methodology for knowledge-based system development