Pub Date : 2020-10-07DOI: 10.1109/AICT50176.2020.9368810
N. Voit, S. Bochkov, S. Kirillov
Authors have developed new temporal automaton grammatic analyzing complex diagrams, or diagrammatic business process models and gave it the name RVTI-grammar. In the scientific issue it differs from analogues in linear time of complex diagrams analysis and does not require storing sentential view form of such diagrams. On the practice, this RVTI-grammar reduces analysis time and does not require extra memory for the sentential view of the diagram. Authors have introduced RVTI-grammar development methodology for any graphic language.
{"title":"Temporal Automaton RVTI-Grammar for the Diagrammatic Design Workflow Models Analysis","authors":"N. Voit, S. Bochkov, S. Kirillov","doi":"10.1109/AICT50176.2020.9368810","DOIUrl":"https://doi.org/10.1109/AICT50176.2020.9368810","url":null,"abstract":"Authors have developed new temporal automaton grammatic analyzing complex diagrams, or diagrammatic business process models and gave it the name RVTI-grammar. In the scientific issue it differs from analogues in linear time of complex diagrams analysis and does not require storing sentential view form of such diagrams. On the practice, this RVTI-grammar reduces analysis time and does not require extra memory for the sentential view of the diagram. Authors have introduced RVTI-grammar development methodology for any graphic language.","PeriodicalId":136491,"journal":{"name":"2020 IEEE 14th International Conference on Application of Information and Communication Technologies (AICT)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128133971","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-10-07DOI: 10.1109/AICT50176.2020.9368625
Rasha Assaf, Rashid Jayousi
Patient readmission to the hospital within 30 days or 365 days is a challenging problem for hospitals as they get penalized and in many cases the Center of Medicaid and Medicare (CMS) will not reimburse the hospitals for the costs associated with these readmissions. Although readmission prediction is a common problem in healthcare and has been addressed by the researchers in the machine learning community, it remains a hard problem to solve. The goal of the project proposed in this paper is to build a predictive model for 30-day readmission based on the Medical Information Mart for Intensive Care (MIMIC III) dataset, which contains admissions for intensive care unit (ICU) patients. We used ICD9 embedding’s, chart events and demographics as features to train multiple classifiers including Random Forest (RF), Support Vector Machine (SVM), Logistic Regression (LR) and Multi-Layer Perceptron (MLP). Best model, Random Forest, achieved 0.65 accuracy and 0.66 Area Under the Curve (AUC).
患者在30天或365天内再入院对医院来说是一个具有挑战性的问题，因为他们会受到处罚，而且在许多情况下，医疗补助和医疗保险中心(CMS)不会报销医院与这些再入院相关的费用。虽然再入院预测是医疗保健中的一个常见问题，并且已经由机器学习社区的研究人员解决，但它仍然是一个难以解决的问题。本文提出的项目目标是基于重症监护医疗信息市场(MIMIC III)数据集构建30天再入院的预测模型，该数据集包含重症监护病房(ICU)患者的入院情况。我们使用ICD9嵌入，图表事件和人口统计作为特征来训练多个分类器，包括随机森林(RF)，支持向量机(SVM)，逻辑回归(LR)和多层感知器(MLP)。最佳模型Random Forest的准确率为0.65，曲线下面积(Area Under the Curve, AUC)为0.66。
{"title":"30-day Hospital Readmission Prediction using MIMIC Data","authors":"Rasha Assaf, Rashid Jayousi","doi":"10.1109/AICT50176.2020.9368625","DOIUrl":"https://doi.org/10.1109/AICT50176.2020.9368625","url":null,"abstract":"Patient readmission to the hospital within 30 days or 365 days is a challenging problem for hospitals as they get penalized and in many cases the Center of Medicaid and Medicare (CMS) will not reimburse the hospitals for the costs associated with these readmissions. Although readmission prediction is a common problem in healthcare and has been addressed by the researchers in the machine learning community, it remains a hard problem to solve. The goal of the project proposed in this paper is to build a predictive model for 30-day readmission based on the Medical Information Mart for Intensive Care (MIMIC III) dataset, which contains admissions for intensive care unit (ICU) patients. We used ICD9 embedding’s, chart events and demographics as features to train multiple classifiers including Random Forest (RF), Support Vector Machine (SVM), Logistic Regression (LR) and Multi-Layer Perceptron (MLP). Best model, Random Forest, achieved 0.65 accuracy and 0.66 Area Under the Curve (AUC).","PeriodicalId":136491,"journal":{"name":"2020 IEEE 14th International Conference on Application of Information and Communication Technologies (AICT)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127490001","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-10-07DOI: 10.1109/AICT50176.2020.9368739
I. Zimin, E. Zamyatina
The paper considers the issues of preventing the spread of harmful information in the social networks and suggests using simulation tools to develop various strategies that reduce the risk of this information diffusion. The authors put forward requirements for a simulation system to solve such problems, provide information on the developed software and then consider its functionality using the dynamic immunization strategy as an example.
{"title":"Strategies of the Social Network Immunization: An Experience of an Investigation by Simulation Tools","authors":"I. Zimin, E. Zamyatina","doi":"10.1109/AICT50176.2020.9368739","DOIUrl":"https://doi.org/10.1109/AICT50176.2020.9368739","url":null,"abstract":"The paper considers the issues of preventing the spread of harmful information in the social networks and suggests using simulation tools to develop various strategies that reduce the risk of this information diffusion. The authors put forward requirements for a simulation system to solve such problems, provide information on the developed software and then consider its functionality using the dynamic immunization strategy as an example.","PeriodicalId":136491,"journal":{"name":"2020 IEEE 14th International Conference on Application of Information and Communication Technologies (AICT)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128646087","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-10-07DOI: 10.1109/AICT50176.2020.9368588
A. Trifonov, A. Kuzmin, S. Filist, S. Degtyarev, E. Petrunina
The aim of the study is to develop a biotechnical system of the rehabilitation type, designed to restore the motor activity of the patient’s muscles through biotechnical and biological feedback. The obtained classification models of surface signals of electromyograms can be used to create intelligent rehabilitation systems for patients with neurological diseases and will allow the development of diagnostic test stimulation programs that can be used to create artificial biological feedback. This will provide new predictors of the risk of socially significant diseases.
{"title":"Biotechnical System for Control to the Exoskeleton Limb Based on Surface Myosignals for Rehabilitation Complexes","authors":"A. Trifonov, A. Kuzmin, S. Filist, S. Degtyarev, E. Petrunina","doi":"10.1109/AICT50176.2020.9368588","DOIUrl":"https://doi.org/10.1109/AICT50176.2020.9368588","url":null,"abstract":"The aim of the study is to develop a biotechnical system of the rehabilitation type, designed to restore the motor activity of the patient’s muscles through biotechnical and biological feedback. The obtained classification models of surface signals of electromyograms can be used to create intelligent rehabilitation systems for patients with neurological diseases and will allow the development of diagnostic test stimulation programs that can be used to create artificial biological feedback. This will provide new predictors of the risk of socially significant diseases.","PeriodicalId":136491,"journal":{"name":"2020 IEEE 14th International Conference on Application of Information and Communication Technologies (AICT)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125457153","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-10-07DOI: 10.1109/aict50176.2020.9368736
{"title":"AICT 2020 About the Conference","authors":"","doi":"10.1109/aict50176.2020.9368736","DOIUrl":"https://doi.org/10.1109/aict50176.2020.9368736","url":null,"abstract":"","PeriodicalId":136491,"journal":{"name":"2020 IEEE 14th International Conference on Application of Information and Communication Technologies (AICT)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127847893","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-10-07DOI: 10.1109/AICT50176.2020.9368859
I. Bychkov, A. Feoktistov, S. Gorsky, A. Edelev, I. Sidorov, R. Kostromin, E. Fereferov, R. Fedorov
We propose a new approach to creating a subject-oriented distributed computing environment. Such an environment is used to support decision-making in solving relevant problems of ensuring energy systems resilience. The proposed approach is based on the idea of advancing and integrating the following important capabilities in supercomputer engineering: continuous integration, delivery, and deployment of the system and applied software, high-performance computing in heterogeneous environments, multi-agent intelligent computation planning and resource allocation, big data processing and geo-information servicing for subject information, including weakly structured data, and decision-making support. This combination of capabilities and their advancing are unique to the subject domain under consideration, which is related to combinatorial studying critical objects of energy systems. Evaluation of decision-making alternatives is carrying out through applying combinatorial modeling and multi-criteria selection rules. The Orlando Tools framework is used as the basis for an integrated software environment. It implements a flexible modular approach to the development of scientific applications (distributed applied software packages).
{"title":"Supercomputer Engineering for Supporting Decision-making on Energy Systems Resilience","authors":"I. Bychkov, A. Feoktistov, S. Gorsky, A. Edelev, I. Sidorov, R. Kostromin, E. Fereferov, R. Fedorov","doi":"10.1109/AICT50176.2020.9368859","DOIUrl":"https://doi.org/10.1109/AICT50176.2020.9368859","url":null,"abstract":"We propose a new approach to creating a subject-oriented distributed computing environment. Such an environment is used to support decision-making in solving relevant problems of ensuring energy systems resilience. The proposed approach is based on the idea of advancing and integrating the following important capabilities in supercomputer engineering: continuous integration, delivery, and deployment of the system and applied software, high-performance computing in heterogeneous environments, multi-agent intelligent computation planning and resource allocation, big data processing and geo-information servicing for subject information, including weakly structured data, and decision-making support. This combination of capabilities and their advancing are unique to the subject domain under consideration, which is related to combinatorial studying critical objects of energy systems. Evaluation of decision-making alternatives is carrying out through applying combinatorial modeling and multi-criteria selection rules. The Orlando Tools framework is used as the basis for an integrated software environment. It implements a flexible modular approach to the development of scientific applications (distributed applied software packages).","PeriodicalId":136491,"journal":{"name":"2020 IEEE 14th International Conference on Application of Information and Communication Technologies (AICT)","volume":"129 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128196864","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-10-07DOI: 10.1109/AICT50176.2020.9368654
Darovskih Stanislav Nikiforovich, Shonazarov Parviz Mahmadnazarovich
The relevance of developing a new effective nature-like medical technology, which is intended for the prevention and treatment of diseases of viral and bacterial etiology, both now and in the future, is substantiated. This technology is aimed at the formation of antiviral protection in the body in the absence of appropriate vaccines for this. The mechanism of corrective action when using the simulated microwave radiation of the Sun on the human body is considered. It is based on the "radio vibration" effect due to the conversion of electromagnetic energy absorbed by the body into the energy of low-intensity elastic vibrations. This makes it possible to activate inhibited enzyme complexes for restoration in cellular structures under conditions of hypoxia of the free energy potential necessary for the synthesis of biostructures not only for antiviral, but also for antibacterial protection, regardless of the strain of the virus or the pathogenic microorganism. The evidence of the feasibility of using the developed hardware and software tools for modeling the microwave radiation of the Sun to provide antiviral protection is presented. The content of the article is addressed not only to virologists and immunologists, but also to government officials to coordinate efforts in developing areas of research to protect the population from a pandemic.
{"title":"On a Nature-like Technology for Treatment of Human Viral Diseases Based on the use of Simulated Microwave Radiation from the Sun","authors":"Darovskih Stanislav Nikiforovich, Shonazarov Parviz Mahmadnazarovich","doi":"10.1109/AICT50176.2020.9368654","DOIUrl":"https://doi.org/10.1109/AICT50176.2020.9368654","url":null,"abstract":"The relevance of developing a new effective nature-like medical technology, which is intended for the prevention and treatment of diseases of viral and bacterial etiology, both now and in the future, is substantiated. This technology is aimed at the formation of antiviral protection in the body in the absence of appropriate vaccines for this. The mechanism of corrective action when using the simulated microwave radiation of the Sun on the human body is considered. It is based on the \"radio vibration\" effect due to the conversion of electromagnetic energy absorbed by the body into the energy of low-intensity elastic vibrations. This makes it possible to activate inhibited enzyme complexes for restoration in cellular structures under conditions of hypoxia of the free energy potential necessary for the synthesis of biostructures not only for antiviral, but also for antibacterial protection, regardless of the strain of the virus or the pathogenic microorganism. The evidence of the feasibility of using the developed hardware and software tools for modeling the microwave radiation of the Sun to provide antiviral protection is presented. The content of the article is addressed not only to virologists and immunologists, but also to government officials to coordinate efforts in developing areas of research to protect the population from a pandemic.","PeriodicalId":136491,"journal":{"name":"2020 IEEE 14th International Conference on Application of Information and Communication Technologies (AICT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129185644","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In developed countries, many effective speech recognition systems have been developed using advanced technologies. But this speech recognition systems are not suitable for Uzbek language or the level of recognition of speech commands may be low. To solve this problem, the article discusses the stages of recognition of speech commands and intelligent processing algorithms. Based on the hidden Markov model, a recognition system for Uzbek speech commands was implemented in Python using CMU Sphinx technology that recognizes Uzbek speech commands on a computer and Raspberry Pi3 devices. The accuracy of the recognition system for Uzbek speech commands are showed 80-95%.
{"title":"Uzbek speech commands recognition and implementation based on HMM","authors":"Shukurov Kamoliddin Elbobo ugli, Kholdorov Shokhrukhmirzo Imomali ugli, Khasanov Umidjon Komiljon ugli","doi":"10.1109/AICT50176.2020.9368591","DOIUrl":"https://doi.org/10.1109/AICT50176.2020.9368591","url":null,"abstract":"In developed countries, many effective speech recognition systems have been developed using advanced technologies. But this speech recognition systems are not suitable for Uzbek language or the level of recognition of speech commands may be low. To solve this problem, the article discusses the stages of recognition of speech commands and intelligent processing algorithms. Based on the hidden Markov model, a recognition system for Uzbek speech commands was implemented in Python using CMU Sphinx technology that recognizes Uzbek speech commands on a computer and Raspberry Pi3 devices. The accuracy of the recognition system for Uzbek speech commands are showed 80-95%.","PeriodicalId":136491,"journal":{"name":"2020 IEEE 14th International Conference on Application of Information and Communication Technologies (AICT)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127336380","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-10-07DOI: 10.1109/AICT50176.2020.9368840
M. Rakhimov, Doniyor Mamadjanov, Abulkosim Mukhiddinov
Digital image processing is an actual task in the digital communication systems, IP-telephony and video conferencing, in digital television, and video surveillance. Digital processing of large video images takes a lot of time, especially if it happens in a real-time system. And, processing speed plays an important role in recognition of objects in video images received from IP-cameras in real time. This requires the use of modern technologies, and fast algorithms that increase the acceleration of digital image processing. Acceleration problems have not been fully resolved till present. Today's realities are such that the development of accelerated image processing programs requires a good knowledge of parallel and distributed computing. Both of these areas are united by the fact that both parallel and distributed software consists of several processes that together solve one common problem. This article proposes an accelerated method for the tasks of recognizing objects in video images received from IP-cameras using parallel and distributed computing technologies
{"title":"A High-Performance Parallel Approach to Image Processing in Distributed Computing","authors":"M. Rakhimov, Doniyor Mamadjanov, Abulkosim Mukhiddinov","doi":"10.1109/AICT50176.2020.9368840","DOIUrl":"https://doi.org/10.1109/AICT50176.2020.9368840","url":null,"abstract":"Digital image processing is an actual task in the digital communication systems, IP-telephony and video conferencing, in digital television, and video surveillance. Digital processing of large video images takes a lot of time, especially if it happens in a real-time system. And, processing speed plays an important role in recognition of objects in video images received from IP-cameras in real time. This requires the use of modern technologies, and fast algorithms that increase the acceleration of digital image processing. Acceleration problems have not been fully resolved till present. Today's realities are such that the development of accelerated image processing programs requires a good knowledge of parallel and distributed computing. Both of these areas are united by the fact that both parallel and distributed software consists of several processes that together solve one common problem. This article proposes an accelerated method for the tasks of recognizing objects in video images received from IP-cameras using parallel and distributed computing technologies","PeriodicalId":136491,"journal":{"name":"2020 IEEE 14th International Conference on Application of Information and Communication Technologies (AICT)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115211975","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-11-29DOI: 10.1109/AICT50176.2020.9368834
Marco Forgione, D. Piga
This paper focuses on the identification of dynamical systems with tailor-made model structures, where neural networks are used to approximate uncertain components and domain knowledge is retained, if available. These model structures are fitted to measured data using different criteria including a computationally efficient approach minimizing a regularized multi-step ahead simulation error. The neural net-work parameters are estimated along with the initial conditions used to simulate the output signal in small-size subsequences. A regularization term is included in the fitting cost in order to enforce these initial conditions to be consistent with the estimated system dynamics.
{"title":"Model Structures and Fitting Criteria for System Identification with Neural Networks","authors":"Marco Forgione, D. Piga","doi":"10.1109/AICT50176.2020.9368834","DOIUrl":"https://doi.org/10.1109/AICT50176.2020.9368834","url":null,"abstract":"This paper focuses on the identification of dynamical systems with tailor-made model structures, where neural networks are used to approximate uncertain components and domain knowledge is retained, if available. These model structures are fitted to measured data using different criteria including a computationally efficient approach minimizing a regularized multi-step ahead simulation error. The neural net-work parameters are estimated along with the initial conditions used to simulate the output signal in small-size subsequences. A regularization term is included in the fitting cost in order to enforce these initial conditions to be consistent with the estimated system dynamics.","PeriodicalId":136491,"journal":{"name":"2020 IEEE 14th International Conference on Application of Information and Communication Technologies (AICT)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133272705","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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