Repair Learning for a Working Knowledge-Based System

Author(s):  
P Olley ◽  
A K Kochhar

This paper addresses the issues of using a learning mechanism for closed-loop updating of the repair knowledge base of a working knowledge-based system (KBS). Issues addressed are stability under noisy data and errors arising from learning from cases in which several repairs are attempted. Simulated data are used to investigate the effects of the latter feature. It is shown that the learning method can cause a significant systematic error in learnt knowledge. A knowledge-based method, which aims to intelligently compensate for the systematic error using diagnostic domain knowledge, is investigated. It is shown that the method greatly reduces the systematic error in learnt repair knowledge.

Author(s):  
Shun-Chieh Lin ◽  
◽  
Chia-Wen Teng ◽  
Shian-Shyong Tseng ◽  

Knowledge acquisition is a critical bottleneck in building a knowledge-based system. Much research and many tools have been developed to acquire domain knowledge with embedded rules that may be ignored in constructing the initial prototype. Due to different backgrounds and dynamic knowledge changing over time, domain knowledge constructed at one time may be degraded at any time thereafter. Here, we propose knowledge acquisition, called enhanced embedded meaning capturing under uncertainty deciding (enhanced EMCUD), which constructs a domain ontology and traces information over time to efficiently update time-related domain knowledge based on the current environment. We enrich the knowledge base and ease the construction of domain knowledge that changes with times and the environment.


2021 ◽  
Author(s):  
Marciane Mueller ◽  
Rejane Frozza ◽  
Liane Mählmann Kipper ◽  
Ana Carolina Kessler

BACKGROUND This article presents the modeling and development of a Knowledge Based System, supported by the use of a virtual conversational agent called Dóris. Using natural language processing resources, Dóris collects the clinical data of patients in care in the context of urgency and hospital emergency. OBJECTIVE The main objective is to validate the use of virtual conversational agents to properly and accurately collect the data necessary to perform the evaluation flowcharts used to classify the degree of urgency of patients and determine the priority for medical care. METHODS The agent's knowledge base was modeled using the rules provided for in the evaluation flowcharts comprised by the Manchester Triage System. It also allows the establishment of a simple, objective and complete communication, through dialogues to assess signs and symptoms that obey the criteria established by a standardized, validated and internationally recognized system. RESULTS Thus, in addition to verifying the applicability of Artificial Intelligence techniques in a complex domain of health care, a tool is presented that helps not only in the perspective of improving organizational processes, but also in improving human relationships, bringing professionals and patients closer. The system's knowledge base was modeled on the IBM Watson platform. CONCLUSIONS The results obtained from simulations carried out by the human specialist allowed us to verify that a knowledge-based system supported by a virtual conversational agent is feasible for the domain of risk classification and priority determination of medical care for patients in the context of emergency care and hospital emergency.


1995 ◽  
Vol 48 (3) ◽  
pp. 243-270 ◽  
Author(s):  
Z. Hochman ◽  
H. Hearnshaw ◽  
R. Barlow ◽  
J.F. Ayres ◽  
C.J. Pearson

Plants ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 896
Author(s):  
Pierre J. Silvie ◽  
Pierre Martin ◽  
Marianne Huchard ◽  
Priscilla Keip ◽  
Alain Gutierrez ◽  
...  

Replacing synthetic pesticides and antimicrobials with plant-based extracts is a current alternative adopted by traditional and family farmers and many organic farming pioneers. A range of natural extracts are already being marketed for agricultural use, but many other plants are prepared and used empirically. A further range of plant species that could be effective in protecting different crops against pests and diseases in Africa could be culled from the large volume of knowledge available in the scientific literature. To meet this challenge, data on plant uses have been compiled in a knowledge base and a software prototype was developed to navigate this trove of information. The present paper introduces this so-called Knomana Knowledge-Based System, while providing outputs related to Spodoptera frugiperda and Tuta absoluta, two invasive insect species in Africa. In early October 2020, the knowledge base hosted data obtained from 342 documents. From these articles, 11,816 uses—experimental or applied by farmers—were identified in the plant health field. In total, 384 crop pest species are currently reported in the knowledge base, in addition to 1547 botanical species used for crop protection. Future prospects for applying this interdisciplinary output to applications under the One Health approach are presented.


Author(s):  
Leonardo Balduzzi ◽  
Ignacio Cuesta

The major aim of the chapter is to propose and study the use of ontology-based optimization for positioning websites in search engines. In this sense, using heterogeneous inductive learning techniques and ontology for knowledge representation, a knowledge-based system which is capable of supporting the activity of SEO (Search Engine Optimization) has been designed and implemented. From its knowledge base, the system suggests the most appropriate optimization tasks for positioning a pair (keyword, website) on the first page of search engines and infers the positioning results to be obtained. The system evolution and learning capacity allows optimizing the productivity and effectiveness of the SEO process.


Author(s):  
V.C. MOULIANITIS ◽  
A.J. DENTSORAS ◽  
N.A. ASPRAGATHOS

The paper presents a knowledge-based system (KBS) for the conceptual design of grippers for handling fabrics. Its main purpose is the integration of the domain knowledge in a single system for the systematic design of this type of grippers. The knowledge presented, in terms of gripper, material and handling process, are classified. The reasoning strategy is based upon a combination of a depth-first search method and a heuristic method. The heuristic search method finds a final solution from a given set of feasible solutions and can synthesize new solutions to accomplish the required specifications. Details of the main features of the system are given, including its ability to take critical design decisions according to four criteria, weighted by the designer. The knowledge-based system was implemented in the Kappa P. C. 2.3.2 environment. Two examples are given to illustrate some critical aspects concerning the KBS development, to explain the operation of the proposed searching heuristic method, and to show its effectiveness in producing design concepts for grippers.


Author(s):  
Sisir K. Padhy ◽  
S. N. Dwivedi

Abstract In this paper, Printed Circuit Board Assembly Advisor (PCAAD), an object-oriented knowledge-based system is described. The system aims to aid the designer by suggesting design modifications that will lead to a better design for assembly of the Printed Circuit Boards. To account for the new trends in the printed circuit board production, hybrid technology, i.e. combination of both the through-hole mounted technology and surface mounted technology, is taken into consideration in developing the knowledge base. The assembly constraints as well as various limitations of different techniques and processes are considered to formulate the rules and guidelines. Moreover, a hierarchical rule structure has been employed in creating the knowledge base. Smalltalk-80, the object-oriented language and Surface Percept Description Language (SPDL) are used for the creation of knowledge base. The system provides a high-level user interface and reasoning capability to solve complex problems. It is capable of ranking different designs and suggesting design modifications to the designer during the design stage to eliminate assembly problems in the latter phase of board production.


2009 ◽  
Vol 28 (3) ◽  
pp. 187-204
Author(s):  
Nomusa Dlodlo ◽  
Lawrance Hunter ◽  
Anton Botha ◽  
Roger Metelerkamp

This article describes the concept and development of a knowledge-based advisory system for the optimum utilisation of South African wool for the benefit of present and potential investors and other interested parties. Wool is a natural animal fibre produced in varying quantities around the world. The wool fibre is far from homogenous; its type and quality, such as fineness and length, depending on the breed of sheep and the environmental conditions prevailing during its growth. Wool is used in a variety of end uses, ranging from fi ne worsted suiting, to hand knitting yarn, carpets, blankets and aircraft upholstery, its use depending largely on its fibre fineness and length. The wool industry is one of the oldest agricultural industries in South Africa, playing an important economic role as an earner of foreign exchange, and providing a living to many people. Wool is produced in many parts of South Africa under extensive, semi-extensive or intensive conditions, and is largely an export commodity. It is produced and traded in a sophisticated free market business environment into the international market place, where supply and demand forces determine price levels. More than 90% of locally produced wool is exported in an unprocessed or semi-processed form which detrimentally affects employment, foreign exchange and income-generating opportunities associated with value-addition prior to export. To reduce the amount of wool exported in unprocessed or semi-processed form, wool-processing enterprises need to be established to produce internationally marketable end products. Therefore, South Africa needs to attract investors into the wool sector, who will set up manufacturing mills in an economically sustainable manner. Potential and present investors in the South African (S.A.) wool industry need easily accessible and up-to-date information on the production statistics, processing properties and end-use pplications of the wool they need for the particular end-products they manufacture or could manufacture. To achieve this and ensure accessibility to such continuously updated information, it is essential to develop an integrated computer-based system. It is with the above in mind that a knowledge-based system for the optimum utilisation of South African wool has been developed, which is described here. This paper reviews relevant work in this fi eld and covers wool production statistics in South Africa, the end uses of the wool fibre versus the diameter of the fibre, the advantages of distributed architectures, and the flow of processes in a wool utilization system. It then sets out the concept and development of the proposed system, including the architecture of the proposed expert system, the associated analysis and finally the conclusions. The components of the expert system, namely the knowledge base, inference engine, knowledge acquisition component, and explanation system are described. The architecture of the system incorporates the concept of distributed systems and the related advantages incorporated in its general architecture and within its internal components. It marries both expert and general knowledge-based systems, consisting of a combination of an ordinary knowledge-based system (KBS) that can be queried for information and an expert system that provides advice to users. The distributed system developed involves collection of autonomous components that are interconnected, which enables these components to coordinate their activities and share resources of the system, so that users perceive the system as a single integrated facility. There are a number of advantages of such a distributed system and these are articulated in the paper. This approach allows not only incremental development of the system, but also facilitates sharing of data and information. The distributed nature of the architecture of the system developed, consists of three main elements: The expert system to advise on the characteristics of the wool that is required for a particular end use A knowledge-based system for querying on the distribution of wool of the various characteristics in South Africa An expert system for the selection of the best alternative area for investment for the particular product end use.The knowledge base consists of a number of databases, each representing the various wool characteristics. This represents a distributed architecture of the knowledge base. Therefore, this architecture inherits all the advantages of distributed processing systems as described in the paper. These knowledge bases can be queried by the user via a database management system (DBMS), a software that manages the creation, updating, maintenance and querying of the database. In terms of wool utilization, the system involves capturing the end-use and requirements of a product and from it, retrieving the characteristics of the wool that will meet the particular end-use. The availability of the wool is then checked by region and province for each style, type, clip type, yield, colour, vegetable matter fault and micron range, in line with the latest statistics available.The system developed enables questions such as the following to be asked at the user interface: What is the anticipated end use of the wool? What criteria must the wool satisfy for the selected end-use? What quantities of wool are required?The outputs at the user interface of the system are the quantities of wool per province and region in terms of micron, style, yield, colour, type, clip type as available on the web-site of Cape Wools SA. At the very end of the system, the best alternative site for siting the manufacturing base can also be indicated.


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