Results for ' Expert systems '

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  1. Expert System for Castor Diseases and Diagnosis.Fatima M. Salman & Samy S. Abu-Naser - 2019 - International Journal of Engineering and Information Systems (IJEAIS) 3 (3):1-10.
    Background: The castor bean is a large grassy or semi-wooden shrub or small tree. Any part of the castor plant parts can suffering from a disease that weakens the ability to grow and eliminates its production. Therefore, in this paper will identify the pests and diseases present in castor culture and detect the symptoms in each disease. Also images is showing the symptom form in this disease. Objectives: The main objective of this expert system is to obtain appropriate diagnosis (...)
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  2. Proposed Expert System for Calculating Inheritance in Islam.Alaa N. Akkila & Samy S. Abu Naser - 2016 - World Wide Journal of Multidisciplinary Research and Development 2 (9):38-48.
    The truth of every human being is the end his life with death, and this leads to leaving assets and funds for those after him and can lead to hate between the heirs, it has made a point of Islamic law on all aspects of life, including the subject of the inheritance of the deceased. The main problem is how to get the knowledge of the basics of inheritance. This paper reviews work done in the use of expert system (...)
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  3. Expert System for Chest Pain in Infants and Children.Randa A. Khella & Samy S. Abu-Naser - 2018 - International Journal of Engineering and Information Systems (IJEAIS) 1 (4):138-148.
    Chest pain is the pain felt in the chest by infants, children and adolescents. In most cases the pain is not associated with the heart. It is mainly recognized by the observance or report of pain by the infant, child or adolescent by reports of distress by parents or care givers. Chest pain is not unusual in children. Lots of children are seen in ambulatory clinics, emergency rooms and hospitals and cardiology clinics. Usually there is a benign cause for the (...)
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  4. An Expert System for Diagnosing Shortness of Breath in Infants and Children.Jihan Y. AbuEl-Reesh & Samy S. Abu-Naser - 2018 - International Journal of Engineering and Information Systems (IJEAIS) 1 (4):89-101.
    Background: With the coming of the Industrial Revolution, the levels of pollution grow significantly. This Technological development contributed to the worsening of shortness breath problems in great shape. especially in infants and children. There are many shortness breath diseases that infants and children face in their lives. Shortness of breath is one of a very serious symptom in children and infants and should never be ignored. Objectives: Along these lines, the main goal of this expert system is to help (...)
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  5. An Expert System for Depression Diagnosis.Izzeddin A. Alshawwa, Mohammed Elkahlout, Hosni Qasim El-Mashharawi & Samy S. Abu-Naser - 2019 - International Journal of Academic Health and Medical Research (IJAHMR) 3 (4):20-27.
    Background: Depression (major depressive disorder) is a common and serious medical illness that negatively affects how you feel, the way you think and how you act. Fortunately, it is also treatable. Depression causes feelings of sadness and/or a loss of interest in activities once enjoyed. It can lead to a variety of emotional and physical problems and can decrease a person’s ability to function at work and at home. Depression affects an estimated one in 15 adults (6.7%) in any given (...)
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  6. An Expert System for Arthritis Diseases Diagnosis Using SL5 Object.Hosni Qasim El-Mashharawi, Izzeddin A. Alshawwa, Mohammed Elkahlout & Samy S. Abu-Naser - 2019 - International Journal of Academic Health and Medical Research (IJAHMR) 3 (4):28-35.
    Background: Arthritis is very common but is not well understood. Actually, “arthritis” is not a single disease; it is an informal way of referring to joint pain or joint disease. There are more than 100 different types of arthritis and related conditions. People of all ages, sexes and races can and do have arthritis, and it is the leading cause of disability in America. More than 50 million adults and 300,000 children have some type of arthritis. It is most common (...)
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  7.  40
    Evaluating expert system prototypes.Pål Sørgaard - 1991 - AI and Society 5 (1):3-17.
    There is a disparity between the multitude of apparently successful expert system prototypes and the scarcity of expert systems in real everyday use. Modern tools make it deceptively easy to make reasonable prototypes, but these prototypes are seldom made subject to serious evaluation. Instead the development team confronts their product with a set of cases, and the primary evaluation criterion is the percentage of correct answers: we are faced with a “95% syndrome”. Other aspects related to the (...)
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  8.  44
    Expert systems and computer-controlled decision making in medicine.Barrie Lipscombe - 1989 - AI and Society 3 (3):184-197.
    The search for “usable” expert systems is leading somemedical researchers to question the appropriate role of these programs. Most current systems assume a limited role for the human user, delegating situated “decision-control” to the machine. As expert systems are only able to replace a narrow range of human intellectual functions, this leaves the programs unable to cope with the “constructivist” nature of human knowledge-use. In returning practical control to the human doctor, some researchers are abandoning (...)
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  9.  41
    Experts' systems instead of expert systems.Thomas Hermann & Katharina Just - 1995 - AI and Society 9 (4):321-355.
    By studying several cases of expert systems' use, a variety of difficulties were identified as directly depending on specific characteristics of experts and their tasks. This concerns more than the questions: “May experts be replaced by machines?” or “Is experts' knowledge explicable?”. The organisational structure of their work as well as the cyclic, non-plannable way of their task performing have further relevance. The paper introduces the concept of experts' systems to deal with diversities of their expertise and (...)
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  10.  40
    Expert systems: Lawyers beware!Ronald Stamper, James Backhouse & Karl Althaus - 1987 - Theoria 3 (1):317-340.
    Two fundamental paradigms are in conflict. Expert systems are the creation of the artificial intelligence paradigm which presumes that an objective reality can be understood and controlled by an individual expert intelligence that can be replaced by machinery. The alternative paradigm assumes that reality is the subjective product of human beings striving to collaborate through shared norms and experiences, a process that can be assisted by but never replaced by computers. The first paradigm is appropriate in the (...)
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  11.  3
    Reconstructive expert system explanation.Michael R. Wick & William B. Thompson - 1992 - Artificial Intelligence 54 (1-2):33-70.
  12.  34
    Expert systems and human knowledge: A view from the sociology of science. [REVIEW]Brian P. Bloomfield - 1988 - AI and Society 2 (1):17-29.
    After the setbacks suffered in the 1970s as a result of the ‘Lighthill Report’ (Lighthill, 1973), the science of Artificial Intelligence (AI) has undergone a dramatic revival of fortunes in the 1980s. But despite the obvious enormity and complexity of the problems tackled by AI, it still remains rather parochial in relation to the import of alternative though potentially fruitful ideas from other disciplines. With this in mind, the aim of the present paper is to utilise ideas from the sociology (...)
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  13.  25
    Expert Systems as General-Use Advisory Tools.Kimberly Cass - 1996 - Business and Professional Ethics Journal 15 (4):61-85.
  14. An expert system for cattle and buffalo health management.Yasser Abdelhamid, S. El-Azhari, Hesham Hassan & Ahmed Rafea - forthcoming - Seventh International Conference on Ai Applications, Cairo, Egypt: Egyptian Computer Society (Egs).
     
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  15.  31
    Do expert systems have a moral cost?Mark Alfino - manuscript
    When professionals are asked about the value of information technology to their work, they typically give two kinds of answers. Some see the advent or arrival of sophisticated information technology as a great boon to their professional lives. For them, the only question is how soon can the technology be deployed to open up new horizons for professional activity and end dull and tedious work. Others sense more acutely the serious..
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  16.  34
    Expert systems as extensions of the human mind: A user oriented, holistic approach to the design of multiple reasoning system environments and interfaces. [REVIEW]Barbara Gorayska & Kevin Cox - 1992 - AI and Society 6 (3):245-262.
    Expert systems have had little impact as computing artifacts. In this paper we argue that the reason for this stems from the underlying assumption of most builders of expert systems that an expert system needs to acquire information and to control the interaction between the human user and itself. We show that this assumption has serious linguistic and usability flaws which diminish the likelihood of producing socially acceptable expert systems. We propose a reversal (...)
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  17. An Expert System for Land Resource Management.Xiaoyou Zhou - 1996 - Esda 1996: Expert Systems and Ai; Neural Networks 7:87.
     
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  18.  32
    Institutionalizing expert systems: Guidelines and legal concerns. [REVIEW]Janet S. Zeide & Jay Liebowitz - 1992 - AI and Society 6 (3):287-293.
    Often, knowledge engineers become so involved in the development process of the expert system that they fail to look further down the road toward the expert system's institutionalization within the organization. Institutionalization is an important component of the expert system planning process. More specifically, the legal issues associated with expert systems development and deployment are critical institutionalization factors. This paper looks at some expert system institutionalization guidelines, and then focuses on legal considerations.
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  19.  19
    The impacts of expert systems on working life — An assessment.Peter Schefe - 1990 - AI and Society 4 (3):183-195.
    Expert systems provide new languages and a new methodology for automating knowledge-intensive processes. Whilst the benefits expected are ubiquitously stated, probable negative impacts are seldom admitted by the dominant actors in the field. We deal with probable problematic impacts on employment as well as contents and structure of work both in production and the service and administration areas and make some suggestions concerning measures to be taken to account for these impacts assuming no radical change as to the (...)
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  20.  33
    Expert system technology transfer strategies: Selected cases from the United States and Mexico. [REVIEW]Jay Liebowitz & Francisco J. Cantu-Ortiz - 1992 - AI and Society 6 (4):324-336.
    Expert systems are being developed in a multitude of domains worldwide. The usage of expert systems within organizations is growing; however, many expert systems projects still fail due to poor ‘institutionalization’ practices. This paper addresses various strategies for providing the transfer of expert systems technology within organizations. Specifically, this paper will address expert system technology transfer strategies using examples from United States and Mexican organizations.
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  21. An Expert System for Automotive Diagnosis in Ray Kurzweil's book.Jeff Pepper - 1990 - In R. Kurzweil (ed.), The Age of Intelligent Machines. MIT Press.
  22.  44
    Expert system projects at the Banque de France an experience in modeling and representing knowledge.Duc Pham-Hi - 1989 - Theory and Decision 27 (1-2):163-173.
  23.  4
    Building expert systems.Johan de Kleer - 1985 - Artificial Intelligence 25 (1):105-107.
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  24.  2
    Expert Systems as a Colleague - Some New Problems for Psychology.Zdena Ruiselová & Jozef Kelemen - 1992 - Human Affairs 2 (1):48-57.
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  25.  15
    Neural Expert Systems in Medical Image Interpretation: Development, Use, and Ethical Issues.Athanasia Pouloudi & George D. Magoulas - 2000 - Journal of Intelligent Systems 10 (5-6):451-472.
  26. Expert system for the.Gerardo Martinez-Guridi & Guillermo Rodriguez - 1991 - Ai 1991 Frontiers in Innovative Computing for the Nuclear Industry Topical Meeting, Jackson Lake, Wy, Sept. 15-18, 1991 1.
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  27. Expert Systems Catching on at the Navy Finance Center.Toomas Tuba IkaIn & John W. Grlesser - forthcoming - Ai Systems in Government Conference: Proceedings.
     
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  28.  37
    Expert-System Software and Knowledge-Intensive Problem Solving.Brian D. Monahan & Sandra E. Belkin - 1986 - Thought: Fordham University Quarterly 61 (4):497-507.
  29.  2
    Expert-System Software and Knowledge-Intensive Problem Solving.Brian D. Monahan & Sandra E. Belkin - 1986 - Thought: Fordham University Quarterly 61 (4):497-507.
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  30.  45
    Law, liability and expert systems.Dr Joseph A. Cannataci - 1989 - AI and Society 3 (3):169-183.
    This paper examines some of the possible legal implications of the production, marketing and use of expert systems. The relevance of a legally useful definition of expert systems, comprising systems designed for use both by laymen and professionals, is related to the distinctions inherent in the legal doctrine underlying provision of goods and provision of services. The liability of the sellers and users of, and contributors to, expert systems are examined in terms of (...)
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  31.  2
    Expert Systems as a Necessity.Jozef Kelemen - 1993 - Human Affairs 3 (1):1-10.
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    Expert systems and the abductive circle.G. Luger & C. Stern - 1993 - In René J. Jorna, Barend van Heusden & Roland Posner (eds.), Signs, Search and Communication: Semiotic Aspects of Artificial Intelligence. De Gruyter. pp. 151-171.
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  33.  14
    From expert systems to knowledge-based companies: How the AI industry negotiated a market for knowledge.Janet Vaux - 2001 - Social Epistemology 15 (3):231 – 245.
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  34. Kse: Expert system monitoring electric power supplies in a pwr power plant.J. Ancelin, F. Cheriaux, J. P. Gaussot, P. Legaud, D. Pichot, G. Sancerni & G. Voisin - 1991 - Ai 1991 Frontiers in Innovative Computing for the Nuclear Industry Topical Meeting, Jackson Lake, Wy, Sept. 15-18, 1991 1.
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  35.  2
    Building expert systems.Clive L. Dym - 1985 - Artificial Intelligence 25 (1):101-104.
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  36. Expert systems and artificial intelligence applications in engineering design and inspection.Ron Sharpe, Jacek Gibert & Stephen Oakes - forthcoming - 8th Int Conf. On Industrial and Engrg Applications of Ai and Expert Sys., International Society of Applied Intelligence (Isai).
  37.  41
    Ethical issues concerning expert systems' applications in education.Marvin J. Croy - 1989 - AI and Society 3 (3):209-219.
    This article traces the connection between expert systems used as consultants in medicine and their design for instructional purposes in education. It is suggested that there are important differences between these applications. Recognizing these differences leads to the view that the development of intelligent computer-assisted instructions (ICAI) should be guided by empirical research into social/psychological consequences and by ethical inquiries into the acceptability of those consequences. Three proposals are put forward: (1) that the pedagogical role of intelligent CAI (...)
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  38.  19
    An Expert System for Construction Tendering Process.Waldemar W. Koczkodaj & Wojciech Trochymiak - 1996 - Esda 1996: Expert Systems and Ai; Neural Networks 7:79.
  39.  28
    Testability of expert systems in system development and application.Elke Steven, Michael Hoenen & Matthias Kloth - 1992 - AI and Society 6 (4):337-344.
    In this paper the difficulties arising out of a necessary examination of expert systems as to the ‘correctness’ of functioning are outlined. The argumentation is based on the problematic use of the knowledge term in expert system development and the design perspectives connected with the cognitivistic knowledge concept. It becomes obvious that fundamental problems in system development will involve negative consequences for utilization. The perspective developed from this analysis is assuming that these problems have to be taken (...)
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  40.  42
    Working with expert systems: Three case studies.Peter Senker, Joe Townsend & Joanna Buckingham - 1989 - AI and Society 3 (2):103-116.
    Three case studies were conducted on the implications of the use of expert systems for the work of clerks and operators in Britain. An expert system had been introduced in a process control application. The operators' work was deskilled. The second case was a fault diagnosis application. An operator was very happy with his new work. In the third case, insurance clerks received training to operate an expert system which extended the scope of their work. In (...)
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  41. A methodology for expert systems testing and debugging.Naser Abu & S. S. - unknown
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  42.  54
    W(h)ither expert systems? — A view from outside.Ian White - 1988 - AI and Society 2 (2):161-171.
    The paper questions the expert system paradigm, both in terms of its range of application, and as a significant contribution to the understanding of artificial intelligence. The viewpoint is that of the systems designer who must judge the applicability of these methods in imminent and future systems. The expert system paradigm, (ESP for short), is criticised not because it is ubiquitously wrong, but because its range of application appears to be very limited, and much promise is (...)
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  43.  31
    Channeling knowledge: Expert Systems as communications media. [REVIEW]Randall Whitaker & Olov Östberg - 1988 - AI and Society 2 (3):197-208.
    Expert Systems (ES) are as yet imperfectly defined. Their two consistently cited characteristics are domain knowledge and expert-level performance. We propose that current structural definitions are inadequate and suggest a view of ES as communication channels. We proceed to explore the factors influencing applicability of ES technology to an enterprise and the impacts that could be expected. A consequence of this view is the idea of incremental information loss on the path from the expert to the (...)
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  44.  4
    Bayesian diagnosis in expert systems.Gernot D. Kleiter - 1992 - Artificial Intelligence 54 (1-2):1-32.
  45. From socrates to expert systems: The limits and dangers of calculative rationality.Hubert L. Dreyfus - 1985 - In Carl Mitcham & Alois Huning (eds.), Philosophy and Technology II: Information Technology and Computers in Theory and Practice. Reidel.
    Actual AI research began auspiciously around 1955 with Allen Newell and Herbert Simon's work at the RAND Corporation. Newell and Simon proved that computers could do more than calculate. They demonstrated that computers were physical symbol systems whose symbols could be made to stand for anything, including features of the real world, and whose programs could be used as rules for relating these features. In this way computers could be used to simulate certain important aspects intelligence. Thus the information-processing (...)
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  46. Detecting Health Problems Related to Addiction of Video Game Playing Using an Expert System.Samy S. Abu Naser & Mohran H. Al-Bayed - 2016 - World Wide Journal of Multidisciplinary Research and Development 2 (9):7-12.
    Today’s everyone normal life can include a normal rate of playing computer games or video games; but what about an excessive or compulsive use of video games that impact on our life? Our kids, who usually spend a lot of time in playing video games will likely have a trouble in paying attention to their school lessons. In this paper, we introduce an expert system to help users in getting the correct diagnosis of the health problem of video game (...)
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  47. On techniques of expert systems on the example of the Akinator program.Zhangozha A. R. - 2020 - Artificial Intelligence Scientific Journal 25 (2):7-13.
    On the example of the online game Akinator, the basic principles on which programs of this type are built are considered. Effective technics have been proposed by which artificial intelligence systems can build logical inferences that allow to identify an unknown subject from its description. To confirm the considered hypotheses, the terminological analysis of definition of the program "Akinator" offered by the author is carried out. Starting from the assumptions given by the author's definition, the article complements their definitions (...)
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  48.  12
    An Educational Web-Based Expert System for Novice Highway Technology in Flexible Pavement Maintenance.Abdalrhman Milad, Nur Izzi Md Yusoff, Sayf A. Majeed, Zainab Hasan Ali, Mohmed Solla, Nadhir Al-Ansari, Riza Atiq Rahmat & Zaher Mundher Yaseen - 2021 - Complexity 2021:1-17.
    Nowadays, higher education worldwide is affected by the COVID-19 pandemic. It has affected students’ attendance in the universities and causes universities to close down in more than 190 countries. On the other hand, novice engineers studied only a few lectures related to highway engineering. Their lectures have included very little knowledge about asphalt pavement construction as highway engineering consists of many areas that are not studied in detail during their studying years subject to their traditional education. Due to all mentioned, (...)
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  49.  18
    Probabilistic Reasoning in Expert Systems Reconstructed in Probability Semantics.Roger M. Cooke - 1986 - PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association 1986:409 - 421.
    Los's probability semantics are used to identify the appropriate probability conditional for use in probabilistic explanations. This conditional is shown to have applications to probabilistic reasoning in expert systems. The reasoning scheme of the system MYCIN is shown to be probabilistically invalid; however, it is shown to be "close" to a probabilistically valid inference scheme.
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  50.  4
    Measures of uncertainty in expert systems.Peter Walley - 1996 - Artificial Intelligence 83 (1):1-58.
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