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1

Schumacher, T. "The Java-Medical Diagnostics Expert System Shell." Transfusion Medicine and Hemotherapy 28, no. 5 (2001): 292–96. http://dx.doi.org/10.1159/000053556.

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2

Thirumaran M. and Banupriya P. "Dynamic Interactive Voice Response System Using Ontology and Java Expert System Shell." Procedia Computer Science 70 (2015): 107–13. http://dx.doi.org/10.1016/j.procs.2015.10.049.

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3

Liu, Zhi Hai, Qing Liang Zeng, Cheng Long Wang, and Yu Shan Li. "Research of Equipment Selection and Matching Expert System in Fully Mechanized Caving Face Based on Ontology." Key Engineering Materials 419-420 (October 2009): 117–20. http://dx.doi.org/10.4028/www.scientific.net/kem.419-420.117.

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The technologies of expert system, ontology modeling and reasoning are studied and applied in this paper. A framework of ontology-based expert system for equipment selection and matching in fully mechanized caving face is built up. The OWL(Web Ontology Language) based equipment knowledge base is set up, and the redundant test is made in the protégé environment. The equipment selection and matching rules are built up by using SWRL(Semantic Web Rule Language). By using JAVA language, the output of equipment selection expert system is optimized based on the theory of Analytic Hierarchy Process. At last, the functions of the expert system are achieved under JESS(Java Expert System Shell) environment. Practical application shows that the equipments selected and matched by ontology-based expert system are more realistic.
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4

Vitkus, Donatas, Žilvinas Steckevičius, Nikolaj Goranin, Diana Kalibatienė, and Antanas Čenys. "Automated Expert System Knowledge Base Development Method for Information Security Risk Analysis." International Journal of Computers Communications & Control 14, no. 6 (November 27, 2019): 743–58. http://dx.doi.org/10.15837/ijccc.2019.6.3668.

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Information security risk analysis is a compulsory requirement both from the side of regulating documents and information security management decision making process. Some researchers propose using expert systems (ES) for process automation, but this approach requires the creation of a high-quality knowledge base. A knowledge base can be formed both from expert knowledge or information collected from other sources of information. The problem of such approach is that experts or good quality knowledge sources are expensive. In this paper we propose the problem solution by providing an automated ES knowledge base development method. The method proposed is novel since unlike other methods it does not integrate ontology directly but utilizes automated transformation of existing information security ontology elements into ES rules: The Web Ontology Rule Language (OWL RL) subset of ontology is segregated into Resource Description Framework (RDF) triplets, that are transformed into Rule Interchange Format (RIF); RIF rules are converted into Java Expert System Shell (JESS) knowledge base rules. The experiments performed have shown the principal method applicability. The created knowledge base was later verified by performing comparative risk analysis in a sample company.
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Panji, Pringga Satria, Tommy Ilyas, and Erly Bahsan. "Assessment of Bridge Substructure in Java Island." MATEC Web of Conferences 147 (2018): 07005. http://dx.doi.org/10.1051/matecconf/201814707005.

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Bridges play important roles in transportation system. Hazard to substructure of bridges become amplified. Based on previous year data, at least one-third of total bridges in Indonesia are damaged in certain level of defect. The performance of existing bridges shall be in-check everytime. Substructure of bridge itself is prone to hazards such as ground displacement, slope instability, seismic-related hazard and scour. Traffic data and soil investigation data will be used to analyse ground displacement and slope instability where the bridge located. Local geological and seismic data will be used to assess seismic-related hazard. Quantitative data is technical information and analyses from geotechnical aspects. Qualitative data is an expert system collected from bridge expert and local goverment. The expert system will have a rating system for each aspect. Fuzzy-based method is an effective tool for modeling some vague datas and this ease the decision-making process. Fuzzy Analytical Hierarchy Process (FAHP) will be used to analyses geotechnical aspect and expert system. Hazard identification, risk rating, risk analysis, and risk assessment are steps conducted in FAHP method. Classification and rating of risk can be done with proposed method. This assessment can be a tool or recommendation for local government where the bridge located.
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Vitkus, Donatas, Jonathan Salter, Nikolaj Goranin, and Dainius Čeponis. "Method for Attack Tree Data Transformation and Import Into IT Risk Analysis Expert Systems." Applied Sciences 10, no. 23 (November 26, 2020): 8423. http://dx.doi.org/10.3390/app10238423.

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Information technology (IT) security risk analysis preventatively helps organizations in identifying their vulnerable systems or internal controls. Some researchers propose expert systems (ES) as the solution for risk analysis automation since risk analysis by human experts is expensive and timely. By design, ES need a knowledge base, which must be up to date and of high quality. Manual creation of databases is also expensive and cannot ensure stable information renewal. These facts make the knowledge base automation process very important. This paper proposes a novel method of converting attack trees to a format usable by expert systems for utilizing the existing attack tree repositories in facilitating information and IT security risk analysis. The method performs attack tree translation into the Java Expert System Shell (JESS) format, by consistently applying ATTop, a software bridging tool that enables automated analysis of attack trees using a model-driven engineering approach, translating attack trees into the eXtensible Markup Language (XML) format, and using the newly developed ATES (attack trees to expert system) program, performing further XML conversion into JESS compatible format. The detailed method description, along with samples of attack tree conversion and results of conversion experiments on a significant number of attack trees, are presented and discussed. The results demonstrate the high method reliability rate and viability of attack trees as a source for the knowledge bases of expert systems used in the IT security risk analysis process.
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Hanif Md Saad, Mohamad, Rabiah Adawiyah Shahad, Kong Win, and Aini Hussain. "ExSIDE: Component Based Object Oriented Expert System’s Integrated Development Environment." JOIV : International Journal on Informatics Visualization 1, no. 3 (June 10, 2017): 88. http://dx.doi.org/10.30630/joiv.1.3.27.

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This paper describes the design and development of a component-based object oriented Expert System's Integrated Development Environment (ExSIDE). It is integrated with (i) a user-friendly manual and automated knowledge acquisition and management tool (ExSIDE_KAMT);(ii) an independent and customizable runtime module (ExSIDE_RTM); (iii) an object-oriented in-process Component Object Model (COM)-based inference engine (ExSIDE_IE); (iv) an object-oriented out-of-process COM-based inference engine (ExSIDE_IESvr); (v) and a PHP based inference engine (ExSIDE_PHP). ExSIDE_RTM can function independently as an Expert System Shell (ESS) and helps user to develop Expert Systems rapidly. ExSIDE_IE and ExSIDE_IES can be integrated with COM-supporting general purpose and scientific application development tools such as variants of C/C++/C#, BASIC (Visual BASIC®, REALbasic®), Java, MATLAB®, LabVIEW®, and Mathematica® to develop more advanced Expert Systems. Finally, ExSIDE_IE and ExSIDE_PHP can be used with Active Server Pages (ASP) and PHP technologies to generate web based Expert Systems. The unique framework of the ExSIDE enables rapid development of Expert Systems' on PC and web for technical and non-technical users. The overall system was developed successfully, and its usability was demonstrated via five unique Expert Systems case studies discussed in this paper.
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8

Munawar, Saima, Saba Khalil Toor, Muhammad Aslam, and Esma Aimeur. "PACA-ITS: A Multi-Agent System for Intelligent Virtual Laboratory Courses." Applied Sciences 9, no. 23 (November 25, 2019): 5084. http://dx.doi.org/10.3390/app9235084.

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This paper describes an intensive design leading to the implementation of an intelligent lab companion (ILC) agent for an intelligent virtual laboratory (IVL) platform. An IVL enables virtual labs (VL) to be used as online research laboratories, thereby facilitating and improving the analytical skills of students using agent technology. A multi-agent system enhances the capability of the learning system and solves students’ problems automatically. To ensure an exhaustive Agent Unified Modeling Language (AUML) design, identification of the agents’ types and responsibilities on well-organized AUML strategies is carried out. This work also traces the design challenge of IVL modeling and the ILC agent functionality of six basic agents: the practical coaching agent (PCA), practical dispatcher agent (PDA), practical interaction and coordination agent (PICA), practical expert agent (PEA), practical knowledge management agent (PKMA), and practical inspection agent (PIA). Furthermore, this modeling technique is compatible with ontology mapping based on an enabling technology using the Java Agent Development Framework (JADE), Cognitive Tutor Authoring Tools (CTAT), and Protégé platform integration. The potential Java Expert System Shell (Jess) programming implements the cognitive model algorithm criteria that are applied to measure progress through the CTAT for C++ programming concept task on IVL and successfully deployed on the TutorShop web server for evaluation. The results are estimated through the learning curve to assess the preceding knowledge, error rate, and performance profiler to engage cognitive Jess agent efficiency as well as practicable and active decisions to improve student learning.
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9

Rahimi, Shahram, Rishath A. S. Rias, and Elham S. Khorasani. "An Open-Bisimilarity Based Automated Verification Tool for -Calculus Family of Process Calculi." International Journal of Software Science and Computational Intelligence 4, no. 1 (January 2012): 55–83. http://dx.doi.org/10.4018/jssci.2012010103.

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The complexity of designing concurrent and highly-evolving interactive systems has grown to a point where system verification has become a hurdle. Fortunately, formal verification methods have arrived at the right time. They detect errors, inconsistencies and incompleteness at early development stages of a system formally modeled using a formal specification language. -calculus (Milner, 1999) is one such formal language which provides strong mathematical base that can be used for verifying system specifications. But manually verifying the specifications of concurrent systems is a very tedious and error-prone work, especially if the specifications are large. Consequently, an automated verification tool would be essential for efficient system design and development. In addition, formal verification tools are vital ingredient to fully harness the potential of component-based software composition. The authors developed such an automated verification tool which is highly portable and seamlessly integrates with the visualization, reduction and performance evaluation tools introduced (Ahmad & Rahimi, 2008; Rahimi, 2006; Rahimi et al., 2001, 2008) to provide a comprehensive tool for designing and analyzing multi process/agent systems. Open-Bisimulation (Sangiorgi, 1996) concept is utilized as the theoretical base for the design and implementation of the tool which incorporates an expert system implemented in Java Expert System Shell (JESS) (Friedman-Hill, 2003).
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10

Lan, Hong Bo, Yu Cheng Ding, Cheng Rui Zhang, and Zhuang De Jiang. "A Web-Based Cost Estimation System for Collaborative Development of Injection Mould." Materials Science Forum 532-533 (December 2006): 997–1000. http://dx.doi.org/10.4028/www.scientific.net/msf.532-533.997.

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To satisfy the increasing requirements in the collaborative development and price quotation for injection mould from the customers and companies, this paper presents a web-based cost estimation system of injection mould which can aid mould designers to evaluate the different design alternatives, implement the collaborative development of injection mould, and provide a reference for mould quotation. The overall architecture of the system based on a logical structure of four layers is established. Approach to cost estimation for injection mould is described in detail. Furthermore, a java-enabled solution together with the JESS 4.4 expert system shell and Microsoft Access 2000 is employed to develop such a networked cost estimation system. Finally, an actual example is given to demonstrate the use of the online cost estimation system of injection mould. The practical results from engineering application indicate the system can provide an effective and feasible tool to aid the evaluation of design alternatives and price quotation at the early development stages of injection mould.
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11

Ng, Y. C., K. S. Tey, K. R. Subramanian, S. B. Tor, L. P. Khoo, and S. G. Lee. "An Intelligent, Multi-Agent Environment for Concurrent and Collaborative Configuration of Personal Computers." Concurrent Engineering 10, no. 2 (June 2002): 143–51. http://dx.doi.org/10.1177/1063293x02010002639.

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Although Concurrent and Collaborative Engineering (CCE) has enjoyed widespread acceptance in industry, many implementation problems remain. With the advent of more powerful artificial intelligence techniques, CCE can be further improved. This paper demonstrates how intelligent software agents may be deployed to facilitate concurrent, collaborative engineering. A system architecture, Java Agent Alive!, is presented as a multi-agent environment. A case study of configuring a personal computer (PC) from its processor, memory and hard disk drive is discussed to highlight the power of software agents in negotiating for the PC configuration with the best price and performance. A software agent is created and assigned to each of the PC components. These agents attend two levels of agent conferences, viz. the bidding conference and the PC component vendor's conference. At both conferences, each agent strives to offer components with the best performance and the lowest price. The agents were ascribed artificial intelligence through the Java Expert System Shell (JESS). At the end of the negotiations, five PC configurations were finalised that met the expectations of the user, who is informed of the outcome via e-mail. The strengths and limitations of the system architecture and the domain application of PC assembly, as well as means to enhance security, are also discussed. Some recommendations to further improve the limitations of Java Agent Alive! and the PC Assembly application are made.
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12

Ostrowsky, Marianne F., and Ruth C. Swezey. "An expert system shell: Expert system environment/VM." ISA Transactions 28, no. 1 (January 1989): 9–14. http://dx.doi.org/10.1016/0019-0578(89)90049-9.

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13

Eugene Carter, E. "Creating a shell-based expert system." Computers & Operations Research 13, no. 2-3 (January 1986): 325–27. http://dx.doi.org/10.1016/0305-0548(86)90016-x.

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14

Koov, Merike, and Hannes Perkmann. "ExpertPriz — an integrated expert system shell." Knowledge-Based Systems 4, no. 1 (March 1991): 27–34. http://dx.doi.org/10.1016/0950-7051(91)90043-2.

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15

Yang, Jie, Chenzhou Ye, and Xiaoli Zhang. "An Expert System Shell for Fault Diagnosis." Robotica 19, no. 6 (September 2001): 669–74. http://dx.doi.org/10.1017/s0263574701003460.

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Traditional expert systems for fault diagnosis have a bottleneck in knowledge acquisition, and have limitations in knowledge representation and reasoning. A new expert system shell for fault diagnosis is presented in this paper to develop multiple knowledge models (object model, rules, neural network, case-base and diagnose models) hierarchically based on multiple knowledge. The structure of the expert system shell and the knowledge representation of multiple models are described. Diagnostic algorithms are presented for automatic modeling and hierarchical reasoning. It will be shown that the expert system shell is very effective in building diagnostic expert systems.
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16

Schneider, Victor. "A pedagogic expert system shell in Prolog." ACM SIGPLAN Notices 23, no. 6 (June 1988): 35–38. http://dx.doi.org/10.1145/44546.44548.

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17

Rodder, W., E. Reucher, and F. Kulmann. "Features of the Expert-System-Shell SPIRIT." Logic Journal of IGPL 14, no. 3 (September 6, 2006): 483–500. http://dx.doi.org/10.1093/jigpal/jzl020.

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18

Prasad, B. E., T. S. Perraju, G. Uma, and P. Umarani. "An expert system shell for aerospace applications." IEEE Expert 9, no. 4 (August 1994): 56–64. http://dx.doi.org/10.1109/64.336148.

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19

Verma, A. K., K. Seetharam, and S. Baijal. "Dex – An Expert System Shell For Diagnosis." International Journal of Modelling and Simulation 19, no. 4 (January 1999): 329–33. http://dx.doi.org/10.1080/02286203.1999.11760431.

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20

Hong-Min, Zhang. "Introduction to an expert system shell - STIM." Fuzzy Sets and Systems 36, no. 1 (May 1990): 167–80. http://dx.doi.org/10.1016/0165-0114(90)90090-s.

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21

Tomić, Bojan, Jelena Jovanović, and Vladan Devedžić. "JavaDON: an open-source expert system shell." Expert Systems with Applications 31, no. 3 (October 2006): 595–606. http://dx.doi.org/10.1016/j.eswa.2005.09.085.

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22

Depradine, Colin. "Expert system for extracting syntactic information from Java code." Expert Systems with Applications 25, no. 2 (August 2003): 187–98. http://dx.doi.org/10.1016/s0957-4174(03)00046-0.

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23

Oyen, R. A., M. A. Keyes, and M. P. Lukas. "An Expert System Shell Embedded in the Control System." IFAC Proceedings Volumes 21, no. 13 (September 1988): 61–66. http://dx.doi.org/10.1016/s1474-6670(17)53700-3.

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24

Lippert, Renate C. "An expert system shell to teach problem solving." TechTrends 33, no. 2 (March 1988): 22–26. http://dx.doi.org/10.1007/bf02771224.

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Matwin, S., S. Szpakowicz, Z. Koperczak, G. E. Kersten, and W. Michalowski. "Negoplan: an expert system shell for negotiation support." IEEE Expert 4, no. 4 (1989): 50–62. http://dx.doi.org/10.1109/64.43285.

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Leung, K. S., W. S. Felix Wong, and W. Lam. "Applications of a novel fuzzy expert system shell." Expert Systems 6, no. 1 (February 1989): 2–10. http://dx.doi.org/10.1111/j.1468-0394.1989.tb00070.x.

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27

Bradshaw, J. A., K. J. Carden, and D. Riordan. "Ecological applications using a novel expert system shell." Bioinformatics 7, no. 1 (1991): 79–83. http://dx.doi.org/10.1093/bioinformatics/7.1.79.

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Bonačic, Davor, Bruno Stiglic, and Tomaž Kolmanič. "An object language versus an expert system shell." ACM SIGPLAN OOPS Messenger 3, no. 3 (July 1992): 41–50. http://dx.doi.org/10.1145/140959.140968.

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29

Storr, A., and H. Wiedmann. "DESIS—an expert system shell for technical diagnosis." Computers in Industry 15, no. 1-2 (January 1990): 69–81. http://dx.doi.org/10.1016/0166-3615(90)90085-4.

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30

Dan, Qiu, and J. Dudeck. "MKS: An expert system shell for HIS environment." Artificial Intelligence in Medicine 2, no. 1 (March 1990): 5–19. http://dx.doi.org/10.1016/0933-3657(90)90013-h.

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31

Jarvis, J. R. "Developing an expert system using a PC-based shell." Information Services & Use 9, no. 1-2 (January 1, 1989): 67–77. http://dx.doi.org/10.3233/isu-1989-91-207.

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32

Qiu, D., and J. Dudeck. "Temporal propositions in a HIS-oriented expert system shell." Medical Informatics 16, no. 1 (January 1991): 65–76. http://dx.doi.org/10.3109/14639239109025296.

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33

Mathkour, Hassan, Israa Al-Turaiki, and Ameur Touir. "The Development of a Bilingual Fuzzy Expert System Shell." Journal of King Saud University - Computer and Information Sciences 21 (2009): 27–44. http://dx.doi.org/10.1016/s1319-1578(09)80003-7.

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Leung, K. S., and M. H. Wong. "Fuzzy concepts in an object oriented expert system shell." International Journal of Intelligent Systems 7, no. 2 (February 1992): 171–92. http://dx.doi.org/10.1002/int.4550070206.

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35

Huffman, John E., Abu Masud, and Don Hommertzheim. "Essex — An intelligent advisor for expert system shell selection." Computers & Industrial Engineering 17, no. 1-4 (January 1989): 12–17. http://dx.doi.org/10.1016/0360-8352(89)90028-4.

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36

Choi, King F. "4885705 Expert system shell for building photofinishing diagnostic systems." Expert Systems with Applications 1, no. 3 (January 1990): VI. http://dx.doi.org/10.1016/0957-4174(90)90017-o.

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Spoor, E. R. K., and J. W. B. Vermeulen. "FRESH: expert-system shell with foundation in data modelling." Information and Software Technology 31, no. 6 (July 1989): 313–23. http://dx.doi.org/10.1016/0950-5849(89)90133-x.

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38

Leung, K. S., Y. T. So, Ares Leung, and W. S. Felix Wong. "A fuzzy expert system shell: From minicomputer to PC." Artificial Intelligence in Medicine 4, no. 1 (February 1992): 75–85. http://dx.doi.org/10.1016/0933-3657(92)90038-q.

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39

SOO, HSU LOKE. "A PROLOG-BASED CHINESE EXPERT SYSTEM." International Journal of Pattern Recognition and Artificial Intelligence 02, no. 01 (March 1988): 17–24. http://dx.doi.org/10.1142/s0218001488000030.

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This paper presents the design and implementation of a Chinese Expert System Shell which is based on a Chinese Prolog interpreter. The system is divided into three parts: the knowledge acquisition module, the knowledge application module and the inference engine. The knowledge engineer defines the syntax of the language to be used by himself and by the users when they interact with the system. The natural language interface is table driven and can be modified easily. The system also caters for the case when the domain expert finds it difficult to articulate the rules, but is able to give examples. An inductive engine is included to extract rules from examples.
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Cradwick, Peter D. G. "Designing a practical user interface for an expert system shell." Expert Systems 8, no. 4 (November 1991): 273–76. http://dx.doi.org/10.1111/j.1468-0394.1991.tb00375.x.

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Ramsbottom, D. J., M. J. Adams, J. Sumiga, and J. Carroll. "Uncertainty within a commercial expert system shell for polymer analysis." Chemometrics and Intelligent Laboratory Systems 19, no. 1 (May 1993): 53–63. http://dx.doi.org/10.1016/0169-7439(93)80082-s.

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Tong, Wei-Guang, and Lin-Liang Zhao. "An expert system shell for analysis of real time signals." Annual Review in Automatic Programming 15 (January 1989): 65–67. http://dx.doi.org/10.1016/0066-4138(89)90012-8.

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Wei-Guang, Tong, and Zhao Lin-Liang. "An Expert System Shell for Analysis of Real Time Signals." IFAC Proceedings Volumes 22, no. 13 (September 1989): 65–67. http://dx.doi.org/10.1016/b978-0-08-040185-0.50016-6.

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Rödder, Wilhelm, Ivan Ricardo Gartner, and Sandra Rudolph. "An entropy-driven expert system shell applied to portfolio selection." Expert Systems with Applications 37, no. 12 (December 2010): 7509–20. http://dx.doi.org/10.1016/j.eswa.2010.04.095.

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45

Dunne, Morgan G., and Sean B. Dunne. "A simple expert system shell for microcomputer-aided radiographic diagnosis." Journal of Digital Imaging 3, no. 1 (February 1990): 10–14. http://dx.doi.org/10.1007/bf03168104.

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46

Kaur, Gurpreet, Derminder Singh, and Rajan Aggarwal. "Geographical Information Based Expert System to Estimate Submersible Pump System Specifications." Oriental journal of computer science and technology 10, no. 2 (June 7, 2017): 497–501. http://dx.doi.org/10.13005/ojcst/10.02.34.

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During past two decades, groundwater utilization has increased tremendously in the state of Punjab (India) particularly for agriculture purposes. Higher energy demand for lifting water is a result of decline in water table. Punjab is presently facing water crises which exasperate monetary conditions of small farmers, abrogate the natural value and unfavorably influence farming generation and economy of the state.In this research, an expert system was developed using Java Standard Edition 7 which provide appropriate selection of submersible pump set and required associated components such as power cable rating and size, generator capacity, ammeter rating, voltmeter rating, capacitor rating and Polyvinyl Chloride pipe diameter based on the spatial information of last 18 years (1998-2015) of ground water table for the state of Punjab. The developed system will be beneficial for the farmer’s in estimation of the required submersible pumping system and allied electrical components.
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Mulya, Dimmas, Dian Pratiwi, and Is Mardianto. "Decision Support System for Diagnose Hepatitis Type using Expert System Method." Journal of Information Technology and Computer Science 6, no. 1 (April 30, 2021): 66–79. http://dx.doi.org/10.25126/jitecs.202161231.

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In the medical world, there are five types of Hepatitis, namely Hepatitis A, B, C, D, and E. However, the five types of hepatitis have similar symptoms, including yellowing of the skin color, yellowing of the eyeball, loss of appetite, etc. Thus, many of the Medical Personnel often misdiagnose the patient for the type of hepatitis or not suffer from hepatitis.Therefore, previous diagnostic data ware collected from Medical Specialists which will be processed and developed into the Java-based Decision Support System Application with Expert System method with the percentage output of the likelihood of patients from each type of hepatitis along with the possibility of patients not suffering from hepatitis.With the output of this application, the percentage of the possibility of each type of hepatitis or the possibility of not suffering from hepatitis can help Medical Personnel to make diagnostic decisions based on alternatives provided by the application.
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SHIN, HEUNG-YEOUL, and JAE-WON LEE. "An expert system for pneumatic design." Artificial Intelligence for Engineering Design, Analysis and Manufacturing 12, no. 1 (January 1998): 3–11. http://dx.doi.org/10.1017/s0890060498121121.

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One of the biggest problems in pneumatic system design is over design. Thus, the results are excessive in costs of the initial investment and it requires too much energy. This article describes the development of expert system based pneumatic design system, PNEUDES (PNEUmatic Design Expert System), prototype that enables the user the optimal design of pneumatic system. Once the design requirements such as cylinder type and work load, etc. are input to the system, optimal cylinder specifications with standardized order-based size, valves types, and necessary accessories are all determined. Also the configuration information such as the connectivity among components and cylinder image data are supplied to the user. It can also help the novice of pneumatic design. The rule-based reasoning approach is used as a reasoning strategy with Intelligent Rule Element shell.
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49

Premkumar, P., and S. Kramer. "A Generalized Expert System Shell for Implementing Mechanical Design Applications: Review, Introduction, and Fundamental Concepts." Journal of Mechanisms, Transmissions, and Automation in Design 111, no. 3 (September 1, 1989): 439–42. http://dx.doi.org/10.1115/1.3259017.

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The foundations for an expert system shell for implementing mechanical design applications are presented in this paper. The shell supports facilities for knowledge acquisition, quasi-reactive planning, design evaluation, and subjective explanation. The underlying philosophy of each of these facilities and some preliminary implementation issues are discussed. A brief summary of a recent research effort and its implications on the development of a generalized expert system shell for implementing mechanical design applications are also presented.
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Carreño, Ricardo, Verónica Aguilar, Daniel Pacheco, Marco Antonio Acevedo, Wen Yu, and María Elena Acevedo. "An IoT Expert System Shell in Block-Chain Technology with ELM as Inference Engine." International Journal of Information Technology & Decision Making 18, no. 01 (January 2019): 87–104. http://dx.doi.org/10.1142/s0219622018500499.

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Abstract:
Knowledge society blockchain is one of the most powerful and recent tools to make the internet environment safer and reliable. Manufacturing has traditionally been dominated by standard designs that are mass-produced, due to the fact, that custom production causes additional costs that make it less affordable than mass production. This paper proposes to develop a designer expert system for IoT installation layout designs, using blockchain distributed system based on a machine learning, with users entering data to the expert system by a smart bot software. This expert system will work using extreme learning machine as inference engine; therefore, this is a shell to develop any expert system with fast learning. The whole system is represented by a smart contract with a value linked to the value of the expert system, the more this expert system be quoted on the web, the more the shares of the smart contract will cost.
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