Assessing the Migration and Transformation of Pesticides in the Subsurface : The Role of Expert Systems

1990 ◽  
Vol 25 (3) ◽  
pp. 293-324 ◽  
Author(s):  
A.S. Crowe ◽  
J.P. Mutch
Keyword(s):  
Expert System ◽  
Numerical Models ◽  
Simulation Models ◽  
Management Tool ◽  
Transport And Transformation ◽  
Knowledge Based System ◽  
Knowledge Based ◽  
Regulatory Evaluation ◽  
Agricultural Regions

Abstract The expert system described here is designed to aid regulatory personnel in their assessment of the potential for pesticides to contaminate groundwater. The expert system, known as EXPRES (EXpert system for Pesticide Regulatory Evaluation Simulations), consists of existing simulation models coupled with a knowledge-based system. The numerical models are used to simulate the transport and transformation of pesticides in the unsaturated zone. The knowledge-based system guides the user through the choice of all the necessary information for characterizing the physical, climatic, hydrogeological, pedological and agricultural settings of typical agricultural regions across Canada required by the pesticide model, as well as aiding the user with the model predictions. EXPRES is designed to be used as a management tool to aid in policy decisions and is not intended for use as a research tool. Thus, its purpose is not to provide insight into the processes that control the fate of pesticides in porous media, but to provide an assessment of the potential hazards and to identify if further study is warranted.

An Advisory Conceptual Design Tool for Mechanical Transmission Systems

1994 ◽  
Author(s):  
C. P. Huang ◽  
F. W. Liou ◽  
J. J. Malyamakkil ◽  
W. F. Lu
Keyword(s):  
Decision Making ◽  
Expert System ◽  
Conceptual Design ◽  
Design Process ◽  
Design Tool ◽  
Mechanical Transmission ◽  
Transmission Systems ◽  
Knowledge Based System ◽  
Knowledge Based ◽  
Packaging Machine

Abstract This paper presents an advisory conceptual design tool for mechanical transmission systems. Space consideration was taken into account during the design process. A prototype function tree was built in the form of knowledge-based system to transfer a designer’s idea into a set of mechanical components. An advisory expert system was also developed to help a designer in decision making. As an example, a packaging machine is designed using the developed system.

scholarly journals Fasting Ontology in Pillars of Islam

2018 ◽  
Vol 12 (2) ◽  
pp. 562
Author(s):  
Sara Afiqah Mohd Zailani ◽  
Nurul Aswa Omar ◽  
Aida Mustapha ◽  
Mohd Hisyam Abdul Rahim
Keyword(s):  
Life Cycle ◽  
Expert System ◽  
Search Engine ◽  
Ontology Development ◽  
Knowledge Based System ◽  
Knowledge Based ◽  
Instance Search ◽  
The Individual

The development of Fasting Ontology in the Pillars of Islam is presented in this paper and has been built based on reliable sources of Islamic Knowledge. The METHONTOLOGY methodology is used for the ontology development, which include identifying motivation scenarios, creating the competency questions, implementation and evaluation. From the beginning of the development of life cycle, the ontology was appraised from the competency questions and the outcome were clear. Therefore, this ontology can link each concept specifically to the individual verse together with the Tafsir that is related to the topics. The ontology proposed will be part of a larger ontology on Five Pillars of Islam. This development of the ontology is intended to refer to the field of learning for other purpose. For instance, search engine, chatbot, expert system or knowledge-based system.

BRAINDEX: An Interactive, Knowledge-Based System Supporting Brain Death Diagnosis

1990 ◽  
Vol 29 (03) ◽  
pp. 193-199 ◽  
Author(s):  
G. Schwarz ◽  
R. Grims ◽  
E. Rumpl ◽  
G. Rom ◽  
G. Pfurtscheller ◽  
...  
Keyword(s):  
Decision Making ◽  
Expert System ◽  
Natural Language ◽  
Brain Death ◽  
Knowledge Based System ◽  
Forward Chaining ◽  
Brain Death Diagnosis ◽  
Knowledge Based ◽  
Expert System Shell

AbstractBRAINDEX (Brain-Death Expert System) is an interactive, knowledge-based expert system offering support to physicians in decision making concerning brain death. The physician is given the possibility of communicating in almost natural language and, therefore, in terms with which he is familiar. This updated version of the system is implemented on an IBM-PC/AT with the expert system shell PC-PLUS and consists of about 430 rules. The determination of brain death is realized with backward chaining and for the optional coma-scaling a forward-chaining mechanism is used.

Human–computer co-operative risk management systems

1990 ◽  
Vol 4 (3) ◽  
pp. 139-150
Author(s):  
Kiyoshi Niwa
Keyword(s):  
Risk Management ◽  
Expert System ◽  
Computer System ◽  
Operative Risk ◽  
Management Systems ◽  
Next Generation ◽  
Project Risk ◽  
Knowledge Based System ◽  
Knowledge Based ◽  
Project Risks

This paper presents a new concept, a ‘human-computer co-operative system’, as the next-generation knowledge-based system for application to project risk management. It first discusses the characteristics of project risks followed by the development of a common expert system for managing such risks. Then, system limitations are identified in terms of knowledge association, and a ‘human–computer co-operative system’ is proposed to overcome these limitations by explicitly incorporating human intuitive ability into the computer system. Finally, evaluations of the human–computer co-operative system are also described.

Fault Diagnosis with Fuzzy Expert System

2011 ◽  
Vol 48-49 ◽  
pp. 519-522 ◽  
Author(s):  
Yang Lan Ou
Keyword(s):  
Expert System ◽  
Numerical Models ◽  
Energy Systems ◽  
Sensor Data ◽  
Fuzzy Expert System ◽  
Sensor Fault ◽  
Knowledge Based ◽  
Fuzzy Expert Systems ◽  
Mass Flow Rates ◽  
Fault Mode

Locating the causes of malfunctions in complex energy systems is an extremely difficult task, more than one fault mode may produce similar and possibly undistinguishable patterns of effects. This paper shows how fuzzy expert systems can exploit the available measurements from the data acquisition system to identify different component and sensor fault modes. Real sensor data (mass flow rates, pressures, temperatures, and key operating parameters) are compared with the expected values of the same quantities that are calculated using numerical models of local subsystems. The final objective is to verify the existence of some patterns of these attributes that univocally identify the considered fault modes. These patterns are then implemented as the set of rules forming the knowledge based on fuzzy expert system.

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