Parallelism in knowledge-based machines

1989 ◽  
Vol 4 (1) ◽  
pp. 53-71
Author(s):  
Apostolos N. Refenes
Keyword(s):  
Expert Systems ◽  
Programming Languages ◽  
Parallel Machine ◽  
Computer Architectures ◽  
Parallel Computer ◽  
Rule Based ◽  
Boltzmann Machines ◽  
Knowledge Based ◽  
Parallel Tasks ◽  
Language Classes

AbstractThe application area of knowledge-based expert systems is currently providing the main stimulus for developing powerful, parallel computer architectures. Languages for programming knowledge-based applications divide into four broad classes: Functional languages (e.g. LISP), Logic languages (e.g. PROLOG), Rule-Based languages (e.g. OPS5), and, what we refer to as self-organizing networks (e.g. BOLTZMANN machines).Despite their many differences, a common problem for all language classes and their supporting machine architectures is parallelism: how to de-compose a single computation into a number of parallel tasks that can be distributed across an ensemble of processors. The aim of this paper is to review the four types of language for programming knowledge-based expert systems, and their supporting parallel machine architectures. In doing so we analyze the concepts and relationships that exist between the programming languages and their parallel machine architectures in terms of their strengths and limitations for exploiting parallelization.

Investigation and Impact of Knowledge-Based Information on Programming Languages Based on Probabilistic Models

2010 ◽  
Vol 39 ◽  
pp. 436-440
Author(s):  
Zhi Ming Qu
Keyword(s):  
Expert Systems ◽  
Programming Languages ◽  
Probabilistic Models ◽  
Role Playing ◽  
Position Paper ◽  
The Other ◽  
Erasure Coding ◽  
Role Playing Games ◽  
Knowledge Based ◽  
Other Hand

In recent years, much research has been devoted to the refinement of IPv6; on the other hand, few have investigated the confusing unification of interrupts and Internet QoS. In this position paper, it demonstrates the emulation of interrupts. In order to overcome this quagmire, a novel system is presented for the intuitive unification of expert systems and massive multiplayer online role-playing games. It is concluded that erasure coding can be verified to make heterogeneous, interposable, and event-driven, which is proved to be applicable.

A survey of French developments in knowledge-based systems

1987 ◽  
Vol 2 (4) ◽  
pp. 287-295
Author(s):  
Jean-Claude Rault
Keyword(s):  
Artificial Intelligence ◽  
Expert Systems ◽  
Computer Applications ◽  
Computer Architectures ◽  
Software Components ◽  
Industrialized Countries ◽  
Public Announcement ◽  
Knowledge Based ◽  
Fifth Generation ◽  
Industrial Communications

AbstractLike other industrialized countries, France is currently enjoying a vogue for artificial intelligence and, generally, for hardware and software components and structures which will be needed for the design and implementation of the computer applications of the 1990s.Since public announcement of MITI's Fifth Generation Project in October 1981, the French scientific and industrial communications have exhibited increasing enthusiasm for AI languages, expert systems, man-computer interaction, novel computer architectures, and knowledge-based computer systems as a whole. The choice of the Prolog language for the Japanese project has stimulated many French industrialists to be aware of the existence of a basic AI tool designed mainly in France.In spite of the present fashion, often maintained by the journalistic milieu, it would be inaccurate to say that the French fifth generation project goes back to the Japanese announcement. The MITI project has certainly been a catalyst of ministerial and industrial awareness, but the bulk of ongoing projects stem from earlier work most often funded by government agencies.In spite of the current thrust in AI and the centralizing habit in France, a “flagship” AI project cannot be identified. French Research and Development initiatives in artificial intelligence in general, and expert systems in particular, correspond more to a set of distinct projects. These frequently complement each other in technical scope and in their scientific and industrial objectives.

scholarly journals Rule Based and Supervisory Training Approach To Develop Expert System Tool For Detecting Lung Cancer Disease

2010 ◽  
Vol 9 (1) ◽  
pp. 1-11
Author(s):  
K. Balachandran ◽  
R. Anitha
Keyword(s):  
Lung Cancer ◽  
Expert System ◽  
Expert Systems ◽  
Medical Attention ◽  
Cancer Disease ◽  
Rule Based ◽  
Knowledge Based ◽  
Training Approach ◽  
Dreaded Disease ◽  
Rule Based Approach

Knowledge-based expert systems, or expert systems, use human knowledge to solve problems that normally would require human intelligence. These expert systems represent the expertise knowledge as data or rules within the computer. These rules and data can be called upon when needed to solve problems. Lung cancer is one of the dreaded disease in the modern era. It is responsible for the most cancer deaths in both men and women throughout the world. Early diagnosis and timely treatment are imperative for the cure. Longevity and cure depends on early detection. This paper gives on insight to identify the forget group of people who are suffering or susceptible to suffer lung cancer disease. Seeking proper medical attention con be initiated based on the findings. Expert system tool developed, to find this target group based on the non-clinical parameters. Symptoms and risk factors associated with Lung cancer ore token as the basis of this study. This expert system basically works on the rule based approach to collect the data. Then Supervisory learning approach is used to infer the basic data. Once sufficient knowledge base is generated the system can be made to adopt in unsupervised learning mode.

Expert Systems in Electrical Engineering Education

1988 ◽  
Vol 25 (2) ◽  
pp. 113-124 ◽  
Author(s):  
H. E. Hanrahan
Keyword(s):  
Expert System ◽  
Expert Systems ◽  
Electrical Engineering ◽  
Bachelor's Degree ◽  
Engineering Practice ◽  
Rule Based ◽  
Knowledge Based ◽  
The Status ◽  
Electrical Engineering Education ◽  
Future Potential

This paper reviews the status and future potential of knowledge-based expert systems in relation to electrical engineering practice and education. A generalised rule-based expert system is described. Uses of expert systems in the Bachelor's Degree are identified by means of examples. Software and tools are discussed.

scholarly journals Rule Based and Supervisory Training Approach to Develop Expert System Tool for Detecting Lung Cancer Disease

2010 ◽  
Vol 9 (2) ◽  
pp. 62-71
Author(s):  
K. Balachandran ◽  
R. Anitha
Keyword(s):  
Lung Cancer ◽  
Expert System ◽  
Expert Systems ◽  
Target Group ◽  
Medical Attention ◽  
Cancer Disease ◽  
Rule Based ◽  
Knowledge Based ◽  
Dreaded Disease ◽  
Rule Based Approach

Knowledge-based expert systems, or expert systems, use human knowledge to solve problems that normally would require human intelligence. These expert systems represent the expertise knowledge as data or rules within the computer. These rules and data can be called upon when needed to solve problems. Lung cancer is one of the dreaded disease in the modern era. It is responsible for the most cancer deaths in both men and women throughout the world. Early diagnosis and timely treatment are imperative for the cure. Longevity and cure depend on early detection. This paper gives on insight to identify the target group of people who are suffering or susceptible to suffer lung cancer disease. Seeking proper medical attention can be initiated based on the findings. Expert system tool developed, to find this target group based on the non-clinical parameters. Symptoms and risk factors associated with Lung cancer are taken as the basis of this study. This expert system basically works on the rule based approach to collect the data. Then Supervisory learning approach is used to infer the basic data. Once sufficient knowledge base is generated the system can be mode to adopt in unsupervised learning mode.

Detection, Averaging, and 3D Reconstruction of Biological Specimens on Hypercubes (Transputer-based) Computers

1990 ◽  
Vol 48 (1) ◽  
pp. 454-455
Author(s):  
Jose-Maria Carazo ◽  
I. Benavides ◽  
S. Marco ◽  
J.L. Carrascosa ◽  
E.L. Zapata
Keyword(s):  
3D Reconstruction ◽  
3D Structure ◽  
Three Dimensional ◽  
Software Tools ◽  
Mapping Method ◽  
Computer Architectures ◽  
Parallel Computer ◽  
Reconstruction Process ◽  
Computing Power ◽  
Order Of Magnitude

Obtaining the three-dimensional (3D) structure of negatively stained biological specimens at a resolution of, typically, 2 - 4 nm is becoming a relatively common practice in an increasing number of laboratories. A combination of new conceptual approaches, new software tools, and faster computers have made this situation possible. However, all these 3D reconstruction processes are quite computer intensive, and the middle term future is full of suggestions entailing an even greater need of computing power. Up to now all published 3D reconstructions in this field have been performed on conventional (sequential) computers, but it is a fact that new parallel computer architectures represent the potential of order-of-magnitude increases in computing power and should, therefore, be considered for their possible application in the most computing intensive tasks.We have studied both shared-memory-based computer architectures, like the BBN Butterfly, and local-memory-based architectures, mainly hypercubes implemented on transputers, where we have used the algorithmic mapping method proposed by Zapata el at. In this work we have developed the basic software tools needed to obtain a 3D reconstruction from non-crystalline specimens (“single particles”) using the so-called Random Conical Tilt Series Method. We start from a pair of images presenting the same field, first tilted (by ≃55°) and then untilted. It is then assumed that we can supply the system with the image of the particle we are looking for (ideally, a 2D average from a previous study) and with a matrix describing the geometrical relationships between the tilted and untilted fields (this step is now accomplished by interactively marking a few pairs of corresponding features in the two fields). From here on the 3D reconstruction process may be run automatically.

Knowledge-Based Decision Support for Diagnosis and Therapy: On the Multiple Usability of Patient Data

1989 ◽  
Vol 28 (02) ◽  
pp. 69-77 ◽  
Author(s):  
R. Haux
Keyword(s):  
Expert Systems ◽  
Statistical Data ◽  
Patient Data ◽  
Attribute Selection ◽  
Patient Specific ◽  
Statistical Data Analysis ◽  
Inference Mechanism ◽  
Diagnosis And Therapy ◽  
Knowledge Based ◽  
Clinical Registries

Abstract:Expert systems in medicine are frequently restricted to assisting the physician to derive a patient-specific diagnosis and therapy proposal. In many cases, however, there is a clinical need to use these patient data for other purposes as well. The intention of this paper is to show how and to what extent patient data in expert systems can additionally be used to create clinical registries and for statistical data analysis. At first, the pitfalls of goal-oriented mechanisms for the multiple usability of data are shown by means of an example. Then a data acquisition and inference mechanism is proposed, which includes a procedure for controlling selection bias, the so-called knowledge-based attribute selection. The functional view and the architectural view of expert systems suitable for the multiple usability of patient data is outlined in general and then by means of an application example. Finally, the ideas presented are discussed and compared with related approaches.

Application of Expert Systems Technology in Water Quality Modeling

1989 ◽  
Vol 21 (8-9) ◽  
pp. 1045-1056 ◽  
Author(s):  
Thomas O. Barnwell ◽  
Linfield C. Brown ◽  
Wiktor Marek
Keyword(s):  
Water Quality ◽  
Expert Systems ◽  
Knowledge Engineering ◽  
Stream Water ◽  
Environmental Modeling ◽  
Water Quality Modeling ◽  
Stream Water Quality ◽  
Quality Model ◽  
Knowledge Based ◽  
Available Technology

Computerized modeling is becoming an integral part of decision making in water pollution control. Expert systems is an innovative methodology that can assist in building, using, and interpreting the output of these models. This paper reviews the use and evaluates the potential of expert systems technology in environmental modeling and describes elements of an expert advisor for the stream water quality model QUAL2E. Some general conclusions are presented about the tools available to develop this system, the level of available technology in knowledge-based engineering, and the value of approaching problems from a knowledge engineering perspective.

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