Relevant bibliographies by topics / Expert system shells

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Expert system shells'

Author: Grafiati
Published: 4 June 2021
Last updated: 12 February 2022

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Journal articles on the topic "Expert system shells"

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Martin, A., and RKH Law. "Expert system for selecting expert system shells." Information and Software Technology 30, no. 10 (1988): 579–86. http://dx.doi.org/10.1016/0950-5849(88)90114-0.

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Mitta, Deborah A. "Formulation of Expert System Knowledge." Proceedings of the Human Factors Society Annual Meeting 33, no. 5 (1989): 350. http://dx.doi.org/10.1177/154193128903300525.

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Expert system knowledge represents expertise obtained through formal education, training, and/or experience. Formal education provides deep knowledge of a particular domain; experience and training result in heuristic knowledge. A knowledge base defines the range of information and understanding with which the system is capable of dealing; therefore, its information must be structured and filed for ready access. The objective of this symposium is to address the challenges associated with establishment of valid expert system knowledge, specifically, knowledge to be used by expert system shells. As expert system knowledge is obtained, structured, and stored, it is formulated. In this symposium, knowledge formulation is addressed as a three-phase process: knowledge acquisition, the mechanics associated with structuring knowledge, and knowledge porting. Knowledge acquisition is the process of extracting expertise from a domain expert. Expertise may be collected through a series of interviews between the expert and a knowledge engineer or through sessions the expert holds with an automated knowledge acquisition tool. Thus, the ultimate outcome of knowledge acquisition is a collection of raw knowledge data. The following human factors issues become apparent: documenting mental models (where mental models are the expert's conceptualization of a problem), recording cognitive problem-solving strategies, and specifying an appropriate interface between the domain expert and the acquisition methodology. The knowledge structuring process involves the refinement of raw knowledge data, where knowledge is organized and assigned a semantic structure. One issue that must be considered is how to interpret knowledge data such that formal definitions, logical relationships, and facts can be established. Finally, formulation involves knowledge porting, that is, the movement of an expert system shell's knowledge base to various other shells. The outcome of this process is a portable knowledge base, where the challenges lie in maintaining consistent knowledge, understanding the constraints inherent to a shell (the shell's ability to incorporate all relevant knowledge), and designing an acceptable user-expert system interface. The fundamental component of any expert system is its knowledge base. The issues to be presented in this symposium are important because they address three processes that are critical to the development of a knowledge base. In addition to presenting computer science challenges, knowledge base formulation also presents human factors challenges, for example, understanding cognitive problem-solving processes, representing uncertain information, and defining human-expert system interface problems. This symposium will provide a forum for discussion of both types of challenges.
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Stylianou, Anthony C., Gregory R. Madey, and Robert D. Smith. "Selection criteria for expert system shells." Communications of the ACM 35, no. 10 (1992): 30–48. http://dx.doi.org/10.1145/135239.135240.

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Kowalski, Kazimierz. "Expert system shells in student advising." Computers & Education 19, no. 4 (1992): 359–68. http://dx.doi.org/10.1016/0360-1315(92)90083-h.

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VANHOOF, K., and J. SURMA. "COMPARING TWO HYBRID EXPERT SYSTEM SHELLS." International Journal of Software Engineering and Knowledge Engineering 04, no. 01 (1994): 159–64. http://dx.doi.org/10.1142/s0218194094000088.

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This paper describes in full detail an analysis of two expert system shells: Level 5 Object and Kappa PC. The major components of these tools (knowledge representation, inference and control, developer interface, user interface and explanation facility, interface to external data sources, support and documentation) were studied and tested by means of small prototypes. Results and experiences of this work are given together with some software engineering remarks.
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Quinn, Kenneth. "Expert System Shells: What To Look For." Reference Services Review 18, no. 1 (1990): 83–86. http://dx.doi.org/10.1108/eb049088.

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Vanthienen, J., and G. Wets. "From decision tables to expert system shells." Data & Knowledge Engineering 13, no. 3 (1994): 265–82. http://dx.doi.org/10.1016/0169-023x(94)00020-4.

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Haverda, Tony H., Peter B. Reitmeyer, and Newton C. Ellis. "Portability of an Expert System Knowledge Base." Proceedings of the Human Factors Society Annual Meeting 33, no. 5 (1989): 366–69. http://dx.doi.org/10.1177/154193128903300529.

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To ensure the widest possible use of an expert system knowledge base, the knowledge base, in its final form, must be portable to a broad spectrum of user operating environments. Demonstrating that possibility was the objective of the research reported in this paper. Three cognitive issues, knowledge representation, inference mechanisms and problem solving procedures, as they pertain to portability were examined. Structuring the portability question in terms of these cognitive issues, two commercially available expert system shells, EXSYS and TI PC+, were used to ferret out problems and suggest practical solutions. Results determined that it is possible to formulate a consistent model of domain information in a knowledge base which is portable between shells.
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Johnson, V. M., and J. V. Carlis. "Building a composite syntax for expert system shells." IEEE Expert 12, no. 6 (1997): 60–66. http://dx.doi.org/10.1109/64.642963.

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Welsh, Jack R., and Brent G. Wilson. "Expert system shells: Tools to aid human performance." Journal of Instructional Development 10, no. 2 (1987): 15–19. http://dx.doi.org/10.1007/bf02905787.

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Dissertations / Theses on the topic "Expert system shells"

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Swaan, Arons Henk de. "Delfi design, development and applicability of expert system shells /." Delft : Delft University Press, 1991. http://books.google.com/books?id=2NZQAAAAMAAJ.

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Thesis (doctoral)--Technische Universiteit Delft, 1991.<br>Summary and vita in Dutch and English; "stellingen" in Dutch. "Stellingen" inserted. Includes bibliographical references (p. 227-252) and index.
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Valley, Karen. "The use of expert system shells in education : an explanation-based approach." Thesis, University of Edinburgh, 1991. http://hdl.handle.net/1842/20258.

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Recent years hve seen the increasing use of expert systems and expert system shells in industry and commerce. However, there has been little use of the technology in schools and colleges, partly due to dissatisfaction with the available software. This thesis describes the design, implementation and evaluation of an expert system shell for use in education. An initial evaluation was carried out to establish some criteria for the design of the new shell. This comprised an evaluation of expert system shells by experienced teachers; an evaluation of several expert system shells by the author; and a case-study visit to a school Computer Studies department. The teachers were also asked for their views on the possible uses of shells in the classroom. An expert system shell was designed and implemented as a result of this evalation. This has an environment for building knowledge bases; an environment for consulting knowledge bases; a knowledge representation language allowing separation of domain and problem solving knowledge; and three supplementarty tools. The most important of these is an explanation tool, which allows exploration of the domain knowledge in a knowledge base. In response to posed questions, the tool can produce domain-based explanations using a domain-independent generation technique, and each explanation can be explored further through relevant follow-up questions. This tool provides a means whereby users can learn about the domain of the knowledge base being explored. An evaluation of this shell by teachers with previous experience of expert system shells suggests that it has the potential for use throughout the school curriculum as an educational medium.
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Stauffer, Scott T. "Expert system shells in chemistry : CHIRULE, a chiral chromatographic column selection system using similarity searching and personal construct theory /." Diss., This resource online, 1993. http://scholar.lib.vt.edu/theses/available/etd-10042006-143845/.

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Thesis (Ph. D.)--Virginia Polytechnic Institute and State University, 1993.<br>Vita. Abstract. Vol. 2 is appendices. Includes bibliographical references (leaves 327-337). Also available via the Internet.
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Smith, Lucy Michelle. "Development of a structured design and programming methodology for expert system shells utilizing a visual programming language : application of structured methodology to the MK92 Maintenance Advisor Expert System, Performance module prototype." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 1994. http://handle.dtic.mil/100.2/ADA289897.

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Thesis (M.S. in Information Technology Management) Naval Postgraduate School, September 1994.<br>Thesis advisor(s): Magdi Kamel, Martin J. McCaffrey. "September 1994." Bibliography: p. 144-145. Also available online.
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Sachdev, Sharad. "Temporal expert system shell." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp01/MQ33826.pdf.

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Bradshaw, John. "The P.R.O. expert system shell." Thesis, Rhodes University, 1987. http://hdl.handle.net/10962/d1006302.

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This thesis reports the research which led to the development of the P.R .O. Expert System Shell. The P.R.O . System is primarily, though not exclusively , designed for use in ecological domains. In the light of two specific expert systems, The RCS (River Conservation Status) and the Aquaculture Systems, which were developed as part of this research, a number of areas of importance have been identified. The most significant of these is the need to handle uncertainty effectively. The style of knowledge representation to be implemented also plays an important role. After consulting the relevant literature and the available microcomputer expert system shells, a number of ideas have been included in the P.R.O. System. The P.R.O . System is a backward chaining, production system based expert system shell. It embodies a simple but effective method of handling uncertainty. An important feature of this method is that it takes cognizance of the different relative importances of the conditions which need to be satisfied before a conclusion can be reached. The knowledge base consists of more than rules and questions. It also contains meta-knowledge, which is used by the inference engine. The P.R.O. System has been designed to be of practical use. Its strongest recommendations are therefore, that the two non-trivial systems which have been implemented in it, have been accepted by the experts and their peers as systems which produce good, accurate answers .<br>KMBT_363<br>Adobe Acrobat 9.53 Paper Capture Plug-in
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St, Jacques Robert J. "XESS : the XML expert system shell /." Online version of thesis, 2008. http://hdl.handle.net/1850/7518.

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Salim, Juliani Susanti. "An expert system shell for processing logic grammars." Thesis, University of British Columbia, 1985. http://hdl.handle.net/2429/24912.

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Many expert systems have been developed over the past decades. ProGrammar is a modest expert system shell that has been developed recently. It is built on top of the CProlog/UNIX* system running on a VAX† 11/750. ProGrammar is designed for processing and developing grammars. It can also be used as a knowledge base constructor for other fields besides grammars, a learning tool, a Prolog interpreter, and as a consulting system. ProGrammar is an interactive system meaning not only can the user query ProGrammar but ProGrammar also can question the user. The user is allowed to request an explanation from the ProGrammar on how the solution to the query was derived.<br>Science, Faculty of<br>Computer Science, Department of<br>Graduate
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Lee, Newton Saiyuen. "GUESS/1: a general purpose expert systems shell." Thesis, Virginia Polytechnic Institute and State University, 1985. http://hdl.handle.net/10919/76038.

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Expert systems are very useful and probably the most fruitful products of applied artificial intelligence. Expert systems, however, are very· expensive to develop. Powerful construction tools are indispensable to construct, modify and maintain a practical expert system. GUESS/l is a domain-independent expert systems shell that captures and enhances the strengths of its predecessors while at the same time overcoming.their limitations. GUESS/l gives a strong emphasis on human engineering, language generality, diversity of data representation and control structures, programming and run-time environment, database construction facilities and security, and many other aspects that are related to the ease of development and maintenance of expert systems.<br>Master of Science
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Kollu, Kavya. "PROTOTYPE OF AN INTELLIGENT TUTORING SYSTEM USING THE JAVA EXPERT SYSTEM SHELL." Master's thesis, Temple University Libraries, 2011. http://cdm16002.contentdm.oclc.org/cdm/ref/collection/p245801coll10/id/118314.

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Electrical Engineering<br>M.S.E.<br>In a technology driven world, efforts are being made to make education/learning available to individuals at any time with no compromise in the quality of teaching/training. To make learning flexible, different techniques such as distributing learning material, uploading audio lectures on the web, and creating intelligent tutoring systems (ITS) are being used. The technique considered here is an adaptive ITS, a system that replicates the learning that occurs in a student teacher relationship. This thesis develops an adaptive intelligent tutoring system architecture prototype where the addition, modification and removal of educational material are relatively easy. The resulting software will take into account: the goals of the specific educational experience, the concepts to be covered, the preferred learning style of the student, measures to detect misuse of the system functionality, behavior based on the student's performance and the generation of hint sequences and feedback messages to improve learning gain. The system will accomplish these objectives by assessing the student's prior knowledge level, observing the actions performed by the student and by adapting to his/her learning abilities. The ITS will attempt to be more intelligent by performing some actions traditionally done by a human teacher - such as diagnosing misconceptions, identifying the most suitable learning style, stressing concepts that the student is finding difficult to understand, switching back to the learning material if the student shows no improvement after a set of trials. The system makes sure that the student is getting feedback where appropriate. Using this prototype system, the student will be tutored to acquire declarative knowledge. A problem based learning (PBL) approach will be used to strengthen the acquired knowledge by providing a high degree of personal attention to the student. To show how the prototype system works, an example of analysis of a control system problem using bode plot technique will be used to assist the student in using the technique to perform the stability analysis of an analog, linear, time-invariant control system problems and to recommend a controller to attain stability (if the system is not stable). Ideas of porting the system from standalone to web-based architecture and features required for collaborative learning will be discussed and an architecture for a web-based tutoring system for supporting multiple students enabling communication between students and sharing data among them will be proposed.<br>Temple University--Theses
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Books on the topic "Expert system shells"

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Shortt, Aidan M. An investigation into expert system shells. The Author), 1986.

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Mowforth, P. Some applications with inductive expert system shells. Turing Institute, 1986.

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Juss, Jagdev K. A comparative study of some expert system shells. The Polytechnic, Wolverhampton. School of Computing and Information Technology, 1987.

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Arons, Hindrik de Swaan. Delfi: Design, development and applicability of expert system shells. Delft University Press, 1991.

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Blanc, Louis A. Le. An evaluation and selection methodology for expert system shells. INSEAD, 1990.

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Morgan, R. F. Data warehousing and small systems: A practical application for expert system shells. Sheffield University Management School, 1996.

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Morgan, R. F. Data warehousing and small systems: A practical application for expert system shells. Sheffield University, School of Management, 1997.

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Steve, Parker. Shell scripting: Expert recipes for Linux, Bash, and more. John Wiley & Sons, 2011.

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Mockler, R. J. Developing knowledge-based systems using an expert system shell. Macmillan Pub. Co., 1992.

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Ron, Peters, ed. Expert Shell Scripting. Apress, 2008.

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Book chapters on the topic "Expert system shells"

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Nalepa, Grzegorz J. "Rule Interoperability with Expert System Shells." In Intelligent Systems Reference Library. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-66655-6_10.

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O’Keefe, Robert, Valerie Belton, and Theresa Ball. "Microcomputer Based Expert System Shells — The Spreadsheets of Artificial Intelligence." In Expert Systems and Artificial Intelligence in Decision Support Systems. Springer Netherlands, 1987. http://dx.doi.org/10.1007/978-94-009-3805-2_11.

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Valley, Karen. "Explanation in expert system shells: a tool for exploration and learning." In Intelligent Tutoring Systems. Springer Berlin Heidelberg, 1992. http://dx.doi.org/10.1007/3-540-55606-0_70.

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Faccilonco, F., D. Inglessis, E. Margaritis, A. Singh, and E. Frangoulis. "Traffic Data Synthesis and Topological Network Design with PC-based Expert System Shells." In Engineering Systems with Intelligence. Springer Netherlands, 1991. http://dx.doi.org/10.1007/978-94-011-2560-4_65.

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Weik, Martin H. "expert system shell." In Computer Science and Communications Dictionary. Springer US, 2000. http://dx.doi.org/10.1007/1-4020-0613-6_6581.

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Tano, Shun’ichi. "Fuzzy Expert System Shell." In Applied Research in Fuzzy Technology. Springer US, 1994. http://dx.doi.org/10.1007/978-1-4615-2770-1_9.

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Ecke-Schüth, Johannes. "KESS: A hybrid expert system shell." In Hector Heterogeneous Computers Together A Joint Project of IBM and the University of Karlsruhe. Springer Berlin Heidelberg, 1988. http://dx.doi.org/10.1007/978-3-642-73574-5_24.

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Vokroj, P. "Expert Like System for Cylindrical Shell Support." In Contact Loading and Local Effects in Thin-walled Plated and Shell Structures. Springer Berlin Heidelberg, 1992. http://dx.doi.org/10.1007/978-3-662-02822-3_9.

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Luo, Zhiyuan, and Alex Gammerman. "PRESS—A probabilistic reasoning expert system shell." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 1991. http://dx.doi.org/10.1007/3-540-54659-6_94.

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Vraneš, Sanja. "Expert System Shell Flexibility: Best Case Study." In Engineering Systems with Intelligence. Springer Netherlands, 1991. http://dx.doi.org/10.1007/978-94-011-2560-4_3.

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Conference papers on the topic "Expert system shells"

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Islam, S. N. "ShellAg: Expert System Shell for Agricultural Crops." In 2013 International Conference on Cloud & Ubiquitous Computing & Emerging Technologies (CUBE). IEEE, 2013. http://dx.doi.org/10.1109/cube.2013.24.

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Cheng, Stephen C., John Comella, and Phaih-Lan Law. "Expert's Toolkit: An Expert System Shell For Building Diagnostic Systems." In SPIE 1989 Technical Symposium on Aerospace Sensing, edited by Mohan M. Trivedi. SPIE, 1989. http://dx.doi.org/10.1117/12.969268.

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Hart, P. K., and J. Rodriguez. "A Dual-Purpose KBES for Preliminary Structural Design." In ASME 1989 Design Technical Conferences. American Society of Mechanical Engineers, 1989. http://dx.doi.org/10.1115/detc1989-0092.

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Abstract A prototype expert system for automatic preliminary shape synthesis is being developed. The purpose of this system is to generate preliminary designs which can be used either for basic engineering or as an initial solution in an optimization scheme. The developed prototype intends to emulate the conceptual-design/preliminary-redesign phases in the design process. Both phases have been modularized and developed under adequate computational shells. Modules requiring heuristic support are implemented in a LISP/KEE™ environment, the ones being computer-intensive are in C subroutines. Heuristics are applied in the initial design phase to produce an adequate definition of the geometric domain. For the redesign phase, a set of options were programmed into the inference mechanism. These rules focus on molding the geometric domain. Rules for the inference mechanism, and common databases were elaborated. The two-dimensional problems of a fillet in a tension bar, and a connecting link are used to illustrate the system. This is part of an ongoing project at the Center for Computer Aids for Industrial Productivity (CAIP) in New Jersey.
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Turksen, I. B., Tanju Yurtsever, and K. Demirli. "Fuzzy expert system shell for scheduling." In Optical Tools for Manufacturing and Advanced Automation, edited by Bruno Bosacchi and James C. Bezdek. SPIE, 1993. http://dx.doi.org/10.1117/12.165037.

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Ishii, K., and R. Nekkanti. "Compatibility Representation of Knowledge About Design for Net Shape Manufacturing." In ASME 1989 Design Technical Conferences. American Society of Mechanical Engineers, 1989. http://dx.doi.org/10.1115/detc1989-0008.

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Abstract This paper proposes a model for representing knowledge about design for net shape manufacturing (NSM) and a means of applying the model to conduct simultaneous engineering. The three major issues that the designers have to balance are: 1) user requirements, 2) process constraints, and 3) candidate designs. We view the goal of design for NSM to be achieving the best possible compatibility among these three issues. Expert designers develop skilled know-how of achieving good compatibility. This paper conceptualizes this knowledge as compatibility-data (c-data) and constructs a knowledge-base CKB. Further, we present two methods that use the CKB to help designers. The first method is the compatibility-based classification system (CCS) which, given the user requirements and the process constraints, searches the CKB for candidate designs. The second is the design assessment system which utilizes the concept of design compatibility analysis (DCA). Given a partial or full description of all the three issues, DCA evaluates the overall compatibility and gives suggestions for improvement, i.e., to modify the design, to respecify the process, or to negotiate the user requirements. Both methods accommodate hardness of constraints, the degree to which the constraints must be satisfied. Using these systems, designers can rapidly generate sound part designs that satisfy requirements and are producible. We illustrate our model by an example: injection molded composite shells for electrical connectors.
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Chu, Wei-Han. "Generic expert system shell for diagnostic reasoning." In the first international conference. ACM Press, 1988. http://dx.doi.org/10.1145/51909.51910.

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Hao, Bo, Dewei Dong, and Huijing Zhao. "Expert System Shell Based on Forward Deduction Algorithm." In 2009 International Workshop on Intelligent Systems and Applications. IEEE, 2009. http://dx.doi.org/10.1109/iwisa.2009.5072859.

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Wang, Shijie, and Marco Valtorta. "A prototype belief network-based expert systems shell." In the third international conference. ACM Press, 1990. http://dx.doi.org/10.1145/98784.98877.

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Tai, K. K., Yuyi Lin, and L. X. Wang. "Knowledge-Based Mechanical Spring Design System." In ASME 1995 15th International Computers in Engineering Conference and the ASME 1995 9th Annual Engineering Database Symposium collocated with the ASME 1995 Design Engineering Technical Conferences. American Society of Mechanical Engineers, 1995. http://dx.doi.org/10.1115/cie1995-0813.

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Abstract Expert systems are best known for qualitative or heuristic reasoning capability. However, the design of high performance and critical mechanical components, such as automotive valve springs, requires that precise and quantitative issues be resolved. This paper discusses the extended use of an expert system shell for mechanical spring design automation. An expert system shell is utilized as a user friendly front end and a binding agent among system components. Building blocks of the complete system include a product information data base which is provided by commercial manufacturers, a dynamic modeling and simulation module which includes typical-applications models, an optimization module which uses simulated annealing algorithms, and a design specification generation module which produces production drawings and a design report. The basic methodology discussed in this paper can be applied to the design automation of other mechanical components.
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Khorasani, Elham S., Shahram Rahimi, Purvag Patel, and Daniel Houle. "CWJess: An expert system shell for computing with words." In 2011 IEEE International Conference on Information Reuse & Integration (IRI 2011). IEEE, 2011. http://dx.doi.org/10.1109/iri.2011.6009580.

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Reports on the topic "Expert system shells"

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Shaw, Frederick J., and Robert A. Fifer. An Evaluation of Five PC-Based Expert System Shells. Defense Technical Information Center, 1988. http://dx.doi.org/10.21236/ada197915.

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Friedman-Hill, E. J. Jess, the Java expert system shell. Office of Scientific and Technical Information (OSTI), 1997. http://dx.doi.org/10.2172/565603.

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Osella, Stephen A. Expert Control System Shell, version 1.0:. National Institute of Standards and Technology, 1995. http://dx.doi.org/10.6028/nist.ir.5601.

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Pan, Juiyao, Guilherme N. DeSouza, and Avinash C. Kak. FuzzyShell: A Large-Scale Expert System Shell Using Fuzzy Logic for Uncertainty Reasoning. Defense Technical Information Center, 1998. http://dx.doi.org/10.21236/ada335107.

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Kaetzel, L. J., J. R. Clifton, and D. P. Bentz. Integrating knowledge for the identification of cracks in concrete using an expert system shell and extensions. National Institute of Standards and Technology, 1989. http://dx.doi.org/10.6028/nist.ir.89-4206.

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Bruder, Brittany L., Katherine L. Brodie, Tyler J. Hesser, Nicholas J. Spore, Matthew W. Farthing, and Alexander D. Renaud. guiBath y : A Graphical User Interface to Estimate Nearshore Bathymetry from Hovering Unmanned Aerial System Imagery. Engineer Research and Development Center (U.S.), 2021. http://dx.doi.org/10.21079/11681/39700.

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This US Army Engineer Research and Development Center, Coastal and Hydraulics Laboratory, technical report details guiBathy, a graphical user interface to estimate nearshore bathymetry from imagery collected via a hovering Unmanned Aerial System (UAS). guiBathy provides an end-to-end solution for non-subject-matter-experts to utilize commercia-off-the-shelf UAS to collect quantitative imagery of the nearshore by packaging robust photogrammetric and signal-processing algorithms into an easy-to-use software interface. This report begins by providing brief background on coastal imaging and the photogrammetry and bathymetric inversion algorithms guiBathy utilizes, as well as UAS data collection requirements. The report then describes guiBathy software specifications, features, and workflow. Example guiBathy applications conclude the report with UAS bathymetry measurements taken during the 2020 Atlantic Hurricane Season, which compare favorably (root mean square error = 0.44 to 0.72 m; bias = -0.35 to -0.11 m) with in situ survey measurements. guiBathy is a standalone executable software for Windows 10 platforms and will be freely available at www.github.com/erdc.
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