Развитие метода неразрушающего контроля латентных дефектов в конструкциях бортовой аппаратуры
The paper presents the results of research that can be put into the development and research of non-contact rapid method for assessing the quality of the assembly and installation of EM designs. To achieve the objectives, studied the behavior of the mechanical connection of the contact pairs, namely the definition of the contribution of R,L,C parameters contact joints in the modulation level and the spectral composition of the electromagnetic radiation mechanical contact pair
The relevance of the study is due to the increasing intensity of train traffic on the Russian railways. By virtue of this, a rapid restoration of railway automation (RAT) devices is required. For this purpose, diagnosis and monitoring systems (STDM) of RAT are being introduced on the Russian railways. However, STDM does not automatically locate each of the possible fault up to a removable element, and need to be supplemented with optimal fault location algorithms (AFL) performed by the engineering servicing personnel. The purpose of the article is to develop practical methods for development such algorithms. First of all, for RAT devices built on modern elemental base, which makes it possible to use logical models for solving problems of their diagnosis. We found the features of such devices, which made it possible to overcome the dimension problem when constructing AFL for complex RAT devices. RAT devices is not limited the scope of use the obtained results. The materials of the article will be useful to specialists dealing with technical diagnostics, postgraduate students and students specialty "Automatics and communication in railway transport" and students of similar areas of training in technical universities.
This article proposes a method of constructing dynamic neural network mathematical models that allow not only to diagnose the disease at the current time, but also to simulate the appearance and development of diseases in future periods of time, as well as to control their appearance and development by selecting the optimal lifestyle and optimal intake of drugs. It is assumed that the use of dynamic neural network medical systems, instead of static, allow doctors, before prescribing courses of treatment to patients, to test the effect of drugs not on patients, but on their virtual mathematical models. The action of the system is demonstrated by examples.
EWDTS-2019 explores the novel trends in testing, diagnosis, repair of microelectronic systems, and also cyber security, automotive, IoT, artificial intelligence.
This article describes development experience of the neural network system for medical diagnostic of gastrointestinal diseases. There was used patient’s practical medical information for its creation. As input parameters were taken into consideration different factor groups, include demographic, patient’s complaints, life history, medical history and additional methods of research. Neural network model allowed making a significance assessment of factors, which have disease’s development influence. As a result, was designed neural network system of differential diagnosis, allowing diagnoses “gastritis”, “peptic ulcer”. In the future, developed diagnostic system can be used as a “provisional diagnosis of gastrointestinal diseases”.
The article presents results of developing the Multidimensional Students’ Life Satisfaction Scale for primary school children based on MSLSS by E S Huebner The questionnaire involves five scales: Family, School, Teachers, Myself, Friends as well as an overall index of life satisfaction The reliability and validity of the questionnaire are demonstrated on the sample of primary school children (third and fourth grades, N=483) Five factor structure is confirmed by the results of confirmatory factor analysis All the scales have high reliability (0 82 < α < 0 89) and show expected correlations with other indicators of subjective well-being and different scales of self-esteem (as assessed by Dembo-Rubinstein technique) The article contains the text of the questionnaire and normative data for primary school children