Mathematical Modeling in Adaptive Corporate Training

The method of forming the content of individual training courses in the corporate training system is proposed. The method is based on the use of a mathematical model to represent the content of the corporate knowledge base. The model is a cognitive map of the corporate knowledge base, representing information units of this base and logical connections between them. The vertices and arcs of the cognitive map have a number of quantitative characteristics used in the process of constructing models for the content of training courses. Based on this model, models of positions and models of employees of the organization are built. It is shown how by comparing the qualification requirements of a certain position with the set of competencies of a particular employee, to build a model of the content of an individualized training course adapted for this employee. The algorithm for solving this problem is developed. Also the optimization problem statement of planning the content of an individual training course is presented with a given restriction on the time of its study. The structural-functional model and the software module architecture for the automated construction of the content model of such a training course are presented

Modeling Financial Time Series with Artificial Neural Networks

Financial time series convey the decisions and actions of a population of human actors over time. Econometric and regressive models have been developed in the past decades for analyzing these time series. More recently, biologically inspired artificial neural network models have been shown to overcome some of the main challenges of traditional techniques by better exploiting the non-linear, non-stationary, and oscillatory nature of noisy, chaotic human interactions. This review paper explores the options, benefits, and weaknesses of the various forms of artificial neural networks as compared with regression techniques in the field of financial time series analysis.CELEST, a National Science Foundation Science of Learning Center (SBE-0354378); SyNAPSE program of the Defense Advanced Research Project Agency (HR001109-03-0001

Aerospace medicine and biology. A continuing bibliography with indexes, supplement 195

This bibliography lists 148 reports, articles, and other documents introduced into the NASA scientific and technical information system in June 1979

Aerospace medicine and biology: A continuing bibliography with indexes (supplement 323)

This bibliography lists 125 reports, articles and other documents introduced into the NASA Scientific and Technical Information System during April, 1989. Subject coverage includes; aerospace medicine and psychology, life support systems and controlled environments, safety equipment exobiology and extraterrestrial life, and flight crew behavior and performance