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The following topics are dealt with: computer education; computer aided instruction; network university; network curriculum; computer network education; distance learning; education information technology; educational technique standard; computation thought and computer method study; school teachers educational technique ability training; teaching resources' design, development and applications; college...
The paper is concerned in human grid computing for artificial intelligence systems. In general, grid computing enables to process a huge amounts of data in any fields, however, grid systems for Shogi, or Japanese chess, need to process astronomical combinations of positions. It is described that the proposed system is effective in reduction of computational complexity with collaboration from human...
Dempster-Shafer evidence theory (D-S theory) provides a useful computational scheme for integrating uncertainty information from multiple sources in artificial intelligence systems. D-S evidence theory is a useful method for dealing with uncertainty problems. Therefore, it has been successfully applied in data fusion and pattern recognition. However, it also has some shortcomings. The key problem...
The provision of embedding neural networks into software applications can enable variety of artificial intelligence systems for individual users as well as organizations. Previously, software implementation of neural networks remained limited to only simulations or application specific solutions. Tightly coupled solutions end up in monolithic systems and non reusable programming efforts. We adapt...
A definition and structure of intelligence is suggested based on research results in neurophysiology, psychology, and system theory. Intelligence is defined as the ability to solve problems using space and time resources. The problem solving behavior depends on experience, innovation, solution fusion, and learning mechanisms. Suggestions for implementing these proposed components are provided and...
The purpose of this paper is to present preliminary evidence that data mining and artificial intelligence systems may allow one to recognize the presence and severity of motor fluctuations in patients with Parkinson's disease (PD). We hypothesize that movement disorders in late-stage PD present with identifiable and predictable features that can be derived from accelerometer (ACC) and surface electromyographic...
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