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Journal articles on the topic 'Java Expert System Shell'

Author: Grafiati

Published: 4 June 2021

Last updated: 8 February 2022

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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. A

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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 (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

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5

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 use

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6

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 (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 atta

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7

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 (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 independent

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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 (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 AU

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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 (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

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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

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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 (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 agen

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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 (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 (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 (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 (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 e

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16

Schneider, Victor. "A pedagogic expert system shell in Prolog." ACM SIGPLAN Notices 23, no. 6 (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 (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 (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 (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 (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 (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 (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 (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 (1988): 22–26. http://dx.doi.org/10.1007/bf02771224.

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25

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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26

Leung, K. S., W. S. Felix Wong, and W. Lam. "Applications of a novel fuzzy expert system shell." Expert Systems 6, no. 1 (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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28

Bonačic, Davor, Bruno Stiglic, and Tomaž Kolmanič. "An object language versus an expert system shell." ACM SIGPLAN OOPS Messenger 3, no. 3 (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 (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 (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 (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 (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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34

Leung, K. S., and M. H. Wong. "Fuzzy concepts in an object oriented expert system shell." International Journal of Intelligent Systems 7, no. 2 (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 (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 (1990): VI. http://dx.doi.org/10.1016/0957-4174(90)90017-o.

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37

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 (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 (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 (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 examp

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40

Cradwick, Peter D. G. "Designing a practical user interface for an expert system shell." Expert Systems 8, no. 4 (1991): 273–76. http://dx.doi.org/10.1111/j.1468-0394.1991.tb00375.x.

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41

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 (1993): 53–63. http://dx.doi.org/10.1016/0169-7439(93)80082-s.

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42

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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43

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

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44

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 (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 (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 (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 po

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47

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 (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 likeliho

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48

SHIN, HEUNG-YEOUL, and JAE-WON LEE. "An expert system for pneumatic design." Artificial Intelligence for Engineering Design, Analysis and Manufacturing 12, no. 1 (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

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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 (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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50

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 (2019): 87–104. http://dx.doi.org/10.1142/s0219622018500499.

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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 ext

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