Discussion

Artificial intelligence in pharmaceutical product formulation: knowledge-based and expert systems

This chapter aims to indicate some of the potential benefits and dangers inherent in the technology of Knowledge-Based Systems (KBSs) and to suggest courses of action that would both minimize risk and promote social benefit in future developments. KBSs offer cheap and ready access to knowledge, efficient management and organization of information, conversion of information into usable knowledge to guide human action, knowledge and advice relevant to the context in which it is needed. There are, however, potential dangers if a user is unfamiliar with the assumptions underlying KBS structures of reasoning and representing knowledge: the danger of a program becoming incomprehensible or unreliable in an emergency: the possibility of placing too much faith in the abilities of KBSs and thereby losing the capacity for critical evaluation of its judgments: the inevitable uncertainty or inexactitude programmed into KBSs: the economic implications at an uneven distribution of new technology: and the likelihood of misinterpretation or technical failure when autonomous. systems are automatically activating machinery (e. g. military/defence systems). The chapter argues for the regulation of KBS construction, particularly for those systems designed for public or “non-expert” use. Suggestions include programming into each system a clear qualification of answers and requests for data, setting up a workable Code of Conduct for AI practitioners, and constant supervision of the assumptions and activities of each computerized system. Since KBSs work by consulting an internal model of the world (supplied to them by a human programmer), their decisions must be challenged or ignored when necessary and always treated with an appropriate degree of scepticism

ABSTRACT:The diverse knowledge levels among first-year mechanical engineering students lead to significant disparities in individual learning. Intelligent tutoring systems (ITS) offer a solution by providing tailored digital one-to-one instruction, bridging knowledge gaps, and equalizing learning outcomes. This thesis develops an ITS for design theory based on a knowledge-based engineering system, presenting an innovative model that integrates key features of ITS and knowledge-based systems. Implemented in a specialized environment, the system’s application and validation demonstrate its ability to meet context-sensitive design teaching requirements and provide adaptive tutoring.

Building an influence diagram in a knowledge-based decision system

Intelligent information systems, such as those built using knowledge-based system (KBS) technology, stress the human-computer interface in new ways. Such systems use knowledge as well as lower-level information. The application of KBS technology depends on two aspects of the communication of knowledge (knowledge transfer). First, it depends on the ability of humans to explicate their knowledge in ways that can be incorporated into the computer system. Second, it depends on the ability of the computer to divulge its knowledge to humans in a palatable and understandable form.

To solve the problem of advanced digital manufacturing technology in the practical application, a knowledge engineering technology was introduced into the computer numerical control (CNC) programming. The knowledge acquisition, knowledge representation and reasoning used in CNC programming were researched. The CNC programming system functional architecture of impeller parts based on knowledge based engineering (KBE) was constructed. The structural model of the general knowledge-based system (KBS) was also constructed. The KBS of CNC programming system was established through synthesizing database technology and knowledge base theory. And in the context of corporate needs, based on the knowledge-driven manufacturing platform (i.e. UG CAD/CAM), VC++6.0 and UG/Open, the KBS and UG CAD/CAM were integrated seamlessly and the intelligent CNC programming KBE system for the impeller parts was developed by integrating KBE and UG CAD/CAM system. A method to establish standard process templates was proposed, so as to develop the intelligent CNC programming system in which CNC machining process and process parameters were standardized by using this KBE system. For the impeller parts processing, the method applied in the development of the prototype system is proven to be viable, feasible and practical.

The importance of operators' knowledge in the production of high-quality water and the need for consistent high-level expertise have fueled propositions for the application of computer technology, including knowledge-based expert systems (KBES), as a means of enhancing drinking water treatment operations. With this in mind, the authors have developed CHLOROS, a knowledge-based system which integrates both expert system and hypertext technologies in a WindowsTM environment. Designed as an off-line tool, the system does not directly control operations related to drinking water disinfection, but rather has been intended to assist treatment plant operations personnel. It is believed that CHLOROS will serve as a practical tool for water utilities because it creates a consistent decision-making environment, captures and preserves the expertise of human experts, and reduces the amount of manual effort and time that may be expended by searching through manuals and literature for information that is required to support the choice of control parameters.Key words: knowledge-based systems, expert system, hypertext system, disinfection, chlorination, chloramination.

Due to recent advances in knowledge-based systems technology it is suggested that students in a systems development course be given exposure to the concept of designing and implementing knowledge-based systems. The purpose of this paper is to describe the objective, scope, methods and procedures of knowledge-based projects. The first half of the paper introduces the knowledge-based approach and describes the structure and components of such a system. The second half of the paper deals with course design procedures. The scope, topics, project characteristics and experiences pertaining to such a project are covered here. A practical Knowledge-based Systems Development Life Cycle (KSDLC) is also proposed for use in such a course. It is a suitable methodology as it resembles the traditional Systems Development Life Cycle.

Knowledge-based Systems and Expert Systems, in particular, are expensive to build and difficult to validate and debug because of their complexity and dynamism. Therefore, it is not easy for knowledge engineer and domain expert to identify the gaps and mistakes in knowledge base. Unit testing is unable to cover validation process at all stages, in many cases manual thorough review of decision process is needed. In this paper we spot main approaches to validation and verification issue and describe a component that helps to debug a knowledge base by visualising execution of rules that derive a particular result. This component is developed for Knowledge-based Systems built on Drools Platform1 and we demonstrate application of this component in a knowledge-based engineering system for structural optical design.

Progress in software engineering has led to system development following models of the system life cycle. These models incorporate the use of prototyping and formal methods of program verification. They are becoming supported by integrated project support environments and permit the planning and monitoring of software development projects.In contrast, knowledge based systems (KBS) are developed using informal views of the system life cycle. Tools have been developed to support some stages of the life cycle in an undisciplined manner. The commercial use of KBS needs development projects to be planned and monitored. This requires methods and tools based on systematic life cycle models to be established for KBS.This paper reviews the current state of life cycle approaches to software engineering and KBS development projects in order to provide a direction for the development of methodical KBS life cycle models.

This paper explores the integration of a Knowledge-Based Engineering System (KBES) for design heuristics to enhance sustainable engineering education. The primary goal is to equip students with the skills needed to develop sustainable products while comprehending the complexities and multifaceted nature of sustainability. As sustainability is highly context-dependent, the importance of utilizing context-specific knowledge in product development is emphasized. A key question addressed in this study is how digital tools can effectively provide and facilitate the sharing of knowledge critical for sustainability-oriented design. The paper also examines how to build competency in sustainability using design heuristics, which are easy to understand and apply, offering students a practical approach to sustainable problem-solving. By integrating KBE systems with these heuristics, this paper proposes a framework for engineering education that fosters a deeper understanding and actionable skills for developing sustainable products. This approach aims to empower future engineers to create solutions that are not only innovative but also responsible and adaptive to the complex demands of sustainability.

Today’s textile-apparel industrial complex is characterized by a multitude of conflicting demands: smaller lot sizes, increased product flexibility, higher product quality and decreasing delivery times. The textile/apparel industry must deploy state-of-the-art manufacturing and information management techniques to operate successfully in such a demanding and highly competitive global market. In this context, the role and scope of mechatronics in textile-apparel production systems are discussed with specific examples. The need for techniques and tools such as information engineering, electronic data interchange and knowledge-based systems technology is established and their relevance to the textile-apparel complex is discussed. An overview of major research endeavors including the development of an enterprise architecture, knowledge-based systems and product data standards is presented. Finally, some topics for further research in areas ranging from distributed design and manufacturing to the development of product data exchange standards are proposed.

A classification of audit tasks by level of complexity is advocated in the literature for automation of structured tasks and for developing decision support systems (DSS) and knowledge-based expert systems (KES) to aid the auditor in semistructured and unstructured tasks (Abdolmohammadi, 1987; Messier & Hansen, 1984). This literature is based on the works of organizational scientists and decision aid theorists who suggested a correlation between task structure and decision aids. For example, Simon (1960) suggested a model of decision process whereby the process is viewed as three distinctive phases—intelligence, design, and choice— which have implications for the level of programmability of the specific decision context. Based on the work by Simon (1960), Keen and Scott-Morton (1978) suggested a model of task structure and decision aids with a positive correlation between task structure and decision aid types.KeywordsDecision Support SystemHuman ProcessingTask StructureAudit TaskAccounting FirmThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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. >

The development of a knowledge-based software package for the analysis and control of electric distribution networks is discussed. A relational knowledge base, implemented in Prolog, is used to insure fast access to the data and an efficient post-reconfiguration update algorithm. An expert system shell DECIDE, is used to interpret human knowledge coded as knowledge clusters, and to provide a menu-driven user interface. The knowledge-based system described here has the following advantages: its expert system shell provides 'backup' and 'explanation' facilities; it can generate all the possible network reconfigurations and recommend the best choice; and the Prolog implementation of the algorithms is easy to maintain. The knowledge base is easy to expand and can be modified during execution. The prototype system demonstrates that artificial intelligence techniques can be used in power system analysis and reconfiguration, and provides a platform on which a base future research on the utility of expert system technology in distribution automation. >