Lyailya Tukenova - Academia.edu (original) (raw)
Papers by Lyailya Tukenova
Communications in Computer and Information Science, 2021
This interdisciplinary study is aimed at determining the informative signs of behavior of users o... more This interdisciplinary study is aimed at determining the informative signs of behavior of users of the social network Vkontakte of the Kazakh segment in connection with the level of severity of signs of depression in them. We applied six machine learning algorithms with different features to depression related post detection problem. Our experimental results show that the problem can be successfully solved and applied to detect depressive or suicidal behavior or texts in online user contents. Experiment results with depressive and suicide related texts detection show that we can achieve high accuracy in depression related text classification using the collected dataset.
Computers, Materials & Continua, 2022
Diseases of the cardiovascular system are one of the major causes of death worldwide. These disea... more Diseases of the cardiovascular system are one of the major causes of death worldwide. These diseases could be quickly detected by changes in the sound created by the action of the heart. This dynamic auscultations need extensive professional knowledge and emphasis on listening skills. There is also an unmet requirement for a compact cardiac condition early warning device. In this paper, we propose a prototype of a digital stethoscopic system for the diagnosis of cardiac abnormalities in real time using machine learning methods. This system consists of three subsystems that interact with each other (1) a portable digital subsystem of an electronic stethoscope, (2) a decision-making subsystem, and (3) a subsystem for displaying and visualizing the results in an understandable form. The electronic stethoscope captures the patient's phonocardiographic sounds, filters and digitizes them, and then sends the resulting phonocardiographic sounds to the decision-making system. The decision-making system classifies sounds into normal and abnormal using machine learning techniques, and as a result identifies abnormal heart sounds. The display and visualization subsystem demonstrates the results obtained in an understandable way not only for medical staff, but also for patients and recommends further actions to patients. As a result of the study, we obtained an electronic stethoscope that can diagnose cardiac abnormalities with an accuracy of more than 90%. More accurately, the proposed stethoscope can identify normal heart sounds with 93.5% accuracy, abnormal heart sounds with 93.25% accuracy. Moreover, speed is the key benefit of the proposed stethoscope as 15 s is adequate for examination.
Modern requirements to reduce the consumption of energy resources while maintaining comfortable c... more Modern requirements to reduce the consumption of energy resources while maintaining comfortable conditions for people in residential, public and administrative buildings pose the task of developing new approaches to assessing the comfort of the microclimate. Currently used methods for assessing the comfort of the microclimate do not take into account the specific hazards characteristic of non-industrial premises, and for this reason, the introduction of energy-saving measures may lead to a violation of the comfort conditions in the premises of buildings. In this regard, the development of methods and methods to take into account the impact of energy-saving measures on the microclimate is an urgent task. This research paper is devoted to solving the urgent problemenergy efficiency of buildings. We explore mathematical model of indoor microclimate thermal processes, parameters that affect to indoor microclimate, comfort microclimate serving, and represent simulation results of the developed mathematical model of thermal processes. Also, we explore how to control heating, ventilation and air conditioning equipments considering indoor and outdoor temperature and humidity level, and the problem , how to keep stable indoor comfort temperature and humidity
Communications in Computer and Information Science, 2021
This interdisciplinary study is aimed at determining the informative signs of behavior of users o... more This interdisciplinary study is aimed at determining the informative signs of behavior of users of the social network Vkontakte of the Kazakh segment in connection with the level of severity of signs of depression in them. We applied six machine learning algorithms with different features to depression related post detection problem. Our experimental results show that the problem can be successfully solved and applied to detect depressive or suicidal behavior or texts in online user contents. Experiment results with depressive and suicide related texts detection show that we can achieve high accuracy in depression related text classification using the collected dataset.
Computers, Materials & Continua, 2022
Diseases of the cardiovascular system are one of the major causes of death worldwide. These disea... more Diseases of the cardiovascular system are one of the major causes of death worldwide. These diseases could be quickly detected by changes in the sound created by the action of the heart. This dynamic auscultations need extensive professional knowledge and emphasis on listening skills. There is also an unmet requirement for a compact cardiac condition early warning device. In this paper, we propose a prototype of a digital stethoscopic system for the diagnosis of cardiac abnormalities in real time using machine learning methods. This system consists of three subsystems that interact with each other (1) a portable digital subsystem of an electronic stethoscope, (2) a decision-making subsystem, and (3) a subsystem for displaying and visualizing the results in an understandable form. The electronic stethoscope captures the patient's phonocardiographic sounds, filters and digitizes them, and then sends the resulting phonocardiographic sounds to the decision-making system. The decision-making system classifies sounds into normal and abnormal using machine learning techniques, and as a result identifies abnormal heart sounds. The display and visualization subsystem demonstrates the results obtained in an understandable way not only for medical staff, but also for patients and recommends further actions to patients. As a result of the study, we obtained an electronic stethoscope that can diagnose cardiac abnormalities with an accuracy of more than 90%. More accurately, the proposed stethoscope can identify normal heart sounds with 93.5% accuracy, abnormal heart sounds with 93.25% accuracy. Moreover, speed is the key benefit of the proposed stethoscope as 15 s is adequate for examination.
Modern requirements to reduce the consumption of energy resources while maintaining comfortable c... more Modern requirements to reduce the consumption of energy resources while maintaining comfortable conditions for people in residential, public and administrative buildings pose the task of developing new approaches to assessing the comfort of the microclimate. Currently used methods for assessing the comfort of the microclimate do not take into account the specific hazards characteristic of non-industrial premises, and for this reason, the introduction of energy-saving measures may lead to a violation of the comfort conditions in the premises of buildings. In this regard, the development of methods and methods to take into account the impact of energy-saving measures on the microclimate is an urgent task. This research paper is devoted to solving the urgent problemenergy efficiency of buildings. We explore mathematical model of indoor microclimate thermal processes, parameters that affect to indoor microclimate, comfort microclimate serving, and represent simulation results of the developed mathematical model of thermal processes. Also, we explore how to control heating, ventilation and air conditioning equipments considering indoor and outdoor temperature and humidity level, and the problem , how to keep stable indoor comfort temperature and humidity