KEYWORDS: Information technology, Data modeling, Software development, Chemical elements, Neurons, Analytical research, MS office, Absorption, Mathematical modeling, Neural networks
The article considers the information model of semantic structure of informational education material and the corresponding information technology for creation of semantic structure of educational materials. The formal representation of the semantic structure of such informational education materials includes the set of headings, the set of terms, the set of words and the set of relations. The set of relations includes elements of the semantic structure of the informational education materials, which determine the presence and character of relations between other elements of the semantic structure of the informational education materials. The set of relations include relations between headings, relations between headings and key terms, relations between key terms and words. This information model is the formal representation of semantic structure of informational education material of the course of discipline, and in the given form it allows to use it as the model for implementation of the corresponding information technology. The established effectiveness of the proposed technology allows use it to solution a number of urgent tasks, such as semantic assistance in creating tests, determination the conformity of educational materials to content requirements, determination the conformity of sets of test tasks to educational materials, etc.
KEYWORDS: Matrices, Detection and tracking algorithms, Algorithms, Algorithm development, Information technology, Computing systems, Classification systems
Method and algorithm of multidimensional information scaling of the characteristics features based on the results of the theory of perturbation of pseudo-inverse and projective matrices and solutions of systems of linear algebraic equations is proposed. The algorithm of a piecewise-hyperplane clusterization with the verification of a given criterion for the effectiveness of the proposed method of the clusterization is developed. An example of using the method of scaling characteristic features for recognizing the fingerspelling alphabet of the sign language is given.
KEYWORDS: Fuzzy logic, Vital signs, Sensors, Beam propagation method, Machine learning, Data processing, Data analysis, Oxygen, Body temperature, Signal processing
The methods of machine learning for real-time detection of abnormal values of the patient's vital signs are considered. The aim is to assess the risk of the disease with worsening of the patient's condition. The system is designed to monitor patients using expert assessments that are included in fuzzy logic rules to compare patient vitals signs with disease risk assessment. Deviation of values from the norm is identified as an "abnormal" class in order to determine the reasons for the worsening of the patient's condition. The integrated platform "m-Health" system for decision making with feedback control allows the patient to be mobile and their vital signs are mapping in the current mode.
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