Pub Date : 2020-10-07DOI: 10.1109/AICT50176.2020.9368837
F. Adilova, Alisher Ikramov
We consider the task of drug activity prediction, specifically we predict the toxicity of fullerene-based nanoparticles in interaction with 1117 proteins. We use a multi-target Support Vector Regression model with a greedy feature selection technique to achieve RMSE of 362.9 on a test set. We also demonstrate the impact of hyperparameter tuning on model performance.
{"title":"Using Support Vector Regression in multi-target prediction of drug toxicity","authors":"F. Adilova, Alisher Ikramov","doi":"10.1109/AICT50176.2020.9368837","DOIUrl":"https://doi.org/10.1109/AICT50176.2020.9368837","url":null,"abstract":"We consider the task of drug activity prediction, specifically we predict the toxicity of fullerene-based nanoparticles in interaction with 1117 proteins. We use a multi-target Support Vector Regression model with a greedy feature selection technique to achieve RMSE of 362.9 on a test set. We also demonstrate the impact of hyperparameter tuning on model performance.","PeriodicalId":136491,"journal":{"name":"2020 IEEE 14th International Conference on Application of Information and Communication Technologies (AICT)","volume":"335 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":"133956811","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/AICT50176.2020.9368790
Zhukabayeva T. K, Mardenov E. M, Abdildaeva A.A
There are many vulnerabilities to attack in wireless sensor networks. Among them, the sybil attack is especially malicious to generate many false nodes and enter false information on the network. They are detrimental to many functions of the FSU, such as data pooling, fair distribution of resources, etc. Therefore, it is crucial to protect and detect Sybil attacks. The Sybil attack has a significant impact on network performance, and once it was detected, network performance will be obviously improving.In this article, we consider a new method of detecting Sybil attacks using random keys. In the proposed method, signs are used that there is a weak connection between the group of normal nodes and the group of false nodes. Experiment results show that the proposed method detects a false node with a probability of more than 90% with a small energy consumption.
{"title":"Sybil Attack Detection In Wireless Sensor Networks","authors":"Zhukabayeva T. K, Mardenov E. M, Abdildaeva A.A","doi":"10.1109/AICT50176.2020.9368790","DOIUrl":"https://doi.org/10.1109/AICT50176.2020.9368790","url":null,"abstract":"There are many vulnerabilities to attack in wireless sensor networks. Among them, the sybil attack is especially malicious to generate many false nodes and enter false information on the network. They are detrimental to many functions of the FSU, such as data pooling, fair distribution of resources, etc. Therefore, it is crucial to protect and detect Sybil attacks. The Sybil attack has a significant impact on network performance, and once it was detected, network performance will be obviously improving.In this article, we consider a new method of detecting Sybil attacks using random keys. In the proposed method, signs are used that there is a weak connection between the group of normal nodes and the group of false nodes. Experiment results show that the proposed method detects a false node with a probability of more than 90% with a small energy consumption.","PeriodicalId":136491,"journal":{"name":"2020 IEEE 14th International Conference on Application of Information and Communication Technologies (AICT)","volume":"24 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":"132516621","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/AICT50176.2020.9368653
S. V. Begicheva
This study was carried out in order to develop a simulation model for a complex assessment of the quality of emergency medical services in a large metropolitan area. The study methods are based on the Donabedian model, a conceptual model that provides a framework for evaluating the quality of health care and emergency medical services. According to the Donabedian model, information about the quality of care can be drawn from three categories: the quality of structure, the quality of the process, and the quality of outcomes. The fourth category — environmental quality — is proposed to be added to the model in order to consider the specifics of emergency medical services in a large metropolitan area. The proposed conceptual model for the quality of emergency medical services defines the approach to emergency medical services modeling, i.e. creating a set of submodels that would allow assessing all the quality categories for emergency medical services. The paper includes a case study for such a model that combines methods from system dynamics and agent-based modeling. The study results can be used for health care institution modeling in order to lay down recommendations regarding how the health care institution management strategy can be improved.
{"title":"Donabedian Approach for Simulation Modeling to Evaluate the Quality of Emergency Medical Services in a Large Metropolitan Area: A Case Study","authors":"S. V. Begicheva","doi":"10.1109/AICT50176.2020.9368653","DOIUrl":"https://doi.org/10.1109/AICT50176.2020.9368653","url":null,"abstract":"This study was carried out in order to develop a simulation model for a complex assessment of the quality of emergency medical services in a large metropolitan area. The study methods are based on the Donabedian model, a conceptual model that provides a framework for evaluating the quality of health care and emergency medical services. According to the Donabedian model, information about the quality of care can be drawn from three categories: the quality of structure, the quality of the process, and the quality of outcomes. The fourth category — environmental quality — is proposed to be added to the model in order to consider the specifics of emergency medical services in a large metropolitan area. The proposed conceptual model for the quality of emergency medical services defines the approach to emergency medical services modeling, i.e. creating a set of submodels that would allow assessing all the quality categories for emergency medical services. The paper includes a case study for such a model that combines methods from system dynamics and agent-based modeling. The study results can be used for health care institution modeling in order to lay down recommendations regarding how the health care institution management strategy can be improved.","PeriodicalId":136491,"journal":{"name":"2020 IEEE 14th International Conference on Application of Information and Communication Technologies (AICT)","volume":"66 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":"123485490","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/AICT50176.2020.9368665
A. Mashkova, E. Novikova, O. Savina
In this paper we present the agent-based model of the Russian Federation spatial development as a tool for simulation of business projects in key industries and their impact on the regional economy. The model interface is used to define the region and industries for each project, as well as structure of its co-financing by organizations, federal and regional budget. Within the algorithm of the project realization the plan of investment supplies is determined, supplementary processes of the organization are simulated and reflected in the accounting. Within the computational experiment results of business projects realization in various regions were studied. The experimental program includes four regions from different federal districts. In each region, three key industries were selected according to perspective economic specializations defined in the Strategy of the Russian Federation spatial development. The results show significant increase in the output, property and equipment of the organizations, and also in employment and income of population in the selected regions.
{"title":"Simulation of Business Projects in the Agent Model of the Russian Federation Spatial Development","authors":"A. Mashkova, E. Novikova, O. Savina","doi":"10.1109/AICT50176.2020.9368665","DOIUrl":"https://doi.org/10.1109/AICT50176.2020.9368665","url":null,"abstract":"In this paper we present the agent-based model of the Russian Federation spatial development as a tool for simulation of business projects in key industries and their impact on the regional economy. The model interface is used to define the region and industries for each project, as well as structure of its co-financing by organizations, federal and regional budget. Within the algorithm of the project realization the plan of investment supplies is determined, supplementary processes of the organization are simulated and reflected in the accounting. Within the computational experiment results of business projects realization in various regions were studied. The experimental program includes four regions from different federal districts. In each region, three key industries were selected according to perspective economic specializations defined in the Strategy of the Russian Federation spatial development. The results show significant increase in the output, property and equipment of the organizations, and also in employment and income of population in the selected regions.","PeriodicalId":136491,"journal":{"name":"2020 IEEE 14th International Conference on Application of Information and Communication Technologies (AICT)","volume":"171 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":"121258363","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/AICT50176.2020.9368692
Veysel Sercan Ağzıyağlı, H. Oğul
Recent interest in e-learning and distance education services has significantly increased the amount of lecture video data in public and institutional repositories. In their current forms, users can browse in these collections using meta-data-based search queries such as course name, description, instructor and syllabus. However, lecture video entries have rich contents, including image, text and speech, which can not be easily represented by meta-data annotations. Therefore, there is an emerging need to develop tools that will automatically annotate lecture videos to facilitate more targeted search. A simple way to realize this is to classify lectures into known categories. With this objective, this paper presents a method for classifying videos based on extracted text content in several semantic levels. The method is based on Bidirectional Long-Short Term Memory (Bi-LSTM) applied on word embedding vectors of text content extracted by Optical Character Recognition (OCR). This approach can outperform conventional machine learning models and provide a useful solution for automatic lecture video annotation to support online education.
{"title":"Multi-level lecture video classification using text content","authors":"Veysel Sercan Ağzıyağlı, H. Oğul","doi":"10.1109/AICT50176.2020.9368692","DOIUrl":"https://doi.org/10.1109/AICT50176.2020.9368692","url":null,"abstract":"Recent interest in e-learning and distance education services has significantly increased the amount of lecture video data in public and institutional repositories. In their current forms, users can browse in these collections using meta-data-based search queries such as course name, description, instructor and syllabus. However, lecture video entries have rich contents, including image, text and speech, which can not be easily represented by meta-data annotations. Therefore, there is an emerging need to develop tools that will automatically annotate lecture videos to facilitate more targeted search. A simple way to realize this is to classify lectures into known categories. With this objective, this paper presents a method for classifying videos based on extracted text content in several semantic levels. The method is based on Bidirectional Long-Short Term Memory (Bi-LSTM) applied on word embedding vectors of text content extracted by Optical Character Recognition (OCR). This approach can outperform conventional machine learning models and provide a useful solution for automatic lecture video annotation to support online education.","PeriodicalId":136491,"journal":{"name":"2020 IEEE 14th International Conference on Application of Information and Communication Technologies (AICT)","volume":"9 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":"116802963","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/AICT50176.2020.9368678
Obadah Hammoud, I. Tarkhanov
this research is dedicated to the development of a prototype of open infrastructure for users’ internet traffic filtering on a browser level. We described the advantages of a distributed approach in comparison with current centralized solutions. Besides, we suggested a solution to define the optimum size for a URL storage block in Ethereum network. This solution may be used for the development of infrastructure of DApps applications on Ethereum network in future. The efficiency of the suggested approach is supported by several experiments.
{"title":"Blockchain-based open infrastructure for URL filtering in an Internet browser","authors":"Obadah Hammoud, I. Tarkhanov","doi":"10.1109/AICT50176.2020.9368678","DOIUrl":"https://doi.org/10.1109/AICT50176.2020.9368678","url":null,"abstract":"this research is dedicated to the development of a prototype of open infrastructure for users’ internet traffic filtering on a browser level. We described the advantages of a distributed approach in comparison with current centralized solutions. Besides, we suggested a solution to define the optimum size for a URL storage block in Ethereum network. This solution may be used for the development of infrastructure of DApps applications on Ethereum network in future. The efficiency of the suggested approach is supported by several experiments.","PeriodicalId":136491,"journal":{"name":"2020 IEEE 14th International Conference on Application of Information and Communication Technologies (AICT)","volume":"51 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":"114663966","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/AICT50176.2020.9368645
Aliya Bannayeva, Mustafa Aslanov
This research focuses on a text prediction model for the Azerbaijani language. Parsed and cleaned Azerbaijani Wikipedia is used as corpus for the language model. In total, there are more than a million distinct words and sentences, and over seven hundred million characters.For the language model itself, a statistical model with n-grams is implemented. N-grams are contiguous sequences of n strings or characters from a given sample of text or speech. The Markov Chain is used as the model to predict the next word.The Markov Chain focuses on the probabilities of the sequence of words in the n-grams, rather than the probabilities of the entire corpus. This simplifies the task at hand and yields in less computational overhead, while still maintaining sensible results. Logically, the higher the N in the n-grams, the more sensible the resulting prediction.Concretely, bigrams, trigrams, quadgrams and fivegrams are implemented. For the evaluation of the model, intrinsic type of evaluation is used, which computes the perplexity rate.
{"title":"Development of the N-gram Model for Azerbaijani Language","authors":"Aliya Bannayeva, Mustafa Aslanov","doi":"10.1109/AICT50176.2020.9368645","DOIUrl":"https://doi.org/10.1109/AICT50176.2020.9368645","url":null,"abstract":"This research focuses on a text prediction model for the Azerbaijani language. Parsed and cleaned Azerbaijani Wikipedia is used as corpus for the language model. In total, there are more than a million distinct words and sentences, and over seven hundred million characters.For the language model itself, a statistical model with n-grams is implemented. N-grams are contiguous sequences of n strings or characters from a given sample of text or speech. The Markov Chain is used as the model to predict the next word.The Markov Chain focuses on the probabilities of the sequence of words in the n-grams, rather than the probabilities of the entire corpus. This simplifies the task at hand and yields in less computational overhead, while still maintaining sensible results. Logically, the higher the N in the n-grams, the more sensible the resulting prediction.Concretely, bigrams, trigrams, quadgrams and fivegrams are implemented. For the evaluation of the model, intrinsic type of evaluation is used, which computes the perplexity rate.","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":"129956486","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/AICT50176.2020.9368835
K. Nisar, Ibrahim A. Lawal, Usman Ismail Abdulmalik, A. Mu'azu, B. Chowdhry, Sohrab Khan, Shuaib K. Memon
Mobile Ad Hoc Networks (MANETs) are types of wireless networks that communicate with mobile devices without centralized infrastructures. MANET networks are established through interconnected devices that communicate wirelessly within a relatively small, shared area. In MANET every single mobile node is presumed to travel in all directions at different speeds with challenges and open issues. Hence there is no guaranteed long-term path from one node to the next. This work proposes testing the three most common ad hoc routing protocols Ad-hoc On-demand Distance Vector (AODV), Dynamic Source Routing (DSR) and Optimized Link State Routing Protocol (OLSR) using Optimized Network Engineering Tool (OPNET) Modeler simulations using the performance metrics of Throughput, Delay, and Network loading to find an effective routing protocol for routing. The traffic network is used by the File Transfer Protocol (FTP), Digital Education, Battlefield, Surveillance and Security Agencies may benefit from the research work. MANETs reduced the costs of installation, maintenance and operation of such facilities as base stations and also reduced the risk to a minimum such as pollution. The outcome of the simulation shows that: according to the AODV and DSR, the lowest delay in 50 nodes was around 31.25 seconds respectively. And OLSR also had a high throughput performance of around 80 per cent compared with AODV and DSR. And it can be concluded that OLSR is the most suitable routing protocol for MANET, based on the routing protocols suggested.
{"title":"QoS Analysis of the MANET routing protocols with Respect to Delay, Throughput, & Network load: Challenges and Open Issues","authors":"K. Nisar, Ibrahim A. Lawal, Usman Ismail Abdulmalik, A. Mu'azu, B. Chowdhry, Sohrab Khan, Shuaib K. Memon","doi":"10.1109/AICT50176.2020.9368835","DOIUrl":"https://doi.org/10.1109/AICT50176.2020.9368835","url":null,"abstract":"Mobile Ad Hoc Networks (MANETs) are types of wireless networks that communicate with mobile devices without centralized infrastructures. MANET networks are established through interconnected devices that communicate wirelessly within a relatively small, shared area. In MANET every single mobile node is presumed to travel in all directions at different speeds with challenges and open issues. Hence there is no guaranteed long-term path from one node to the next. This work proposes testing the three most common ad hoc routing protocols Ad-hoc On-demand Distance Vector (AODV), Dynamic Source Routing (DSR) and Optimized Link State Routing Protocol (OLSR) using Optimized Network Engineering Tool (OPNET) Modeler simulations using the performance metrics of Throughput, Delay, and Network loading to find an effective routing protocol for routing. The traffic network is used by the File Transfer Protocol (FTP), Digital Education, Battlefield, Surveillance and Security Agencies may benefit from the research work. MANETs reduced the costs of installation, maintenance and operation of such facilities as base stations and also reduced the risk to a minimum such as pollution. The outcome of the simulation shows that: according to the AODV and DSR, the lowest delay in 50 nodes was around 31.25 seconds respectively. And OLSR also had a high throughput performance of around 80 per cent compared with AODV and DSR. And it can be concluded that OLSR is the most suitable routing protocol for MANET, based on the routing protocols suggested.","PeriodicalId":136491,"journal":{"name":"2020 IEEE 14th International Conference on Application of Information and Communication Technologies (AICT)","volume":"22 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":"128505672","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/AICT50176.2020.9368569
F. Haque, Anika Hossain Orthy, Shahnewaz Siddique
Starting around 815AD/200AH scholars have put immense effort towards gathering and sifting authentic hadiths, which are prophetic traditions of the Muslim community. The authenticity of a hadith solely depends on the reliability of its reporters and narrators. Till now scholars have had to do this task manually by precisely anatomizing each hadith’s chain of narrators or the list of people related to the transmission of a particular hadith. The evolution of modern computer science techniques has enabled new methods and introduced a potential paradigm shift in the science of hadith authentication. Focusing on the chain of narrators (also known as "Isnad") of a hadith, we have used a technique called ‘Sentiment Analysis’ from Natural Language Processing (NLP) to build a text classifier which tries to predict the authenticity of a hadith. It learns from our custom-made dataset of Isnads and predicts an unknown hadith to be either authentic or fabricated based upon its Isnad. Our classifier was 86% accurate when tested on the test hadith dataset.
{"title":"Hadith Authenticity Prediction using Sentiment Analysis and Machine Learning","authors":"F. Haque, Anika Hossain Orthy, Shahnewaz Siddique","doi":"10.1109/AICT50176.2020.9368569","DOIUrl":"https://doi.org/10.1109/AICT50176.2020.9368569","url":null,"abstract":"Starting around 815AD/200AH scholars have put immense effort towards gathering and sifting authentic hadiths, which are prophetic traditions of the Muslim community. The authenticity of a hadith solely depends on the reliability of its reporters and narrators. Till now scholars have had to do this task manually by precisely anatomizing each hadith’s chain of narrators or the list of people related to the transmission of a particular hadith. The evolution of modern computer science techniques has enabled new methods and introduced a potential paradigm shift in the science of hadith authentication. Focusing on the chain of narrators (also known as \"Isnad\") of a hadith, we have used a technique called ‘Sentiment Analysis’ from Natural Language Processing (NLP) to build a text classifier which tries to predict the authenticity of a hadith. It learns from our custom-made dataset of Isnads and predicts an unknown hadith to be either authentic or fabricated based upon its Isnad. Our classifier was 86% accurate when tested on the test hadith dataset.","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":"130137693","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/AICT50176.2020.9368798
S. Rakhimov, A. Seytov, N. Rakhimova, Bahrom Xonimqulov
Mathematical models of optimum water distribution in channels of irrigation systems under the conditions of discrete water supply to consumers have been developed. These include the models of direct wave, kinematical wave, convectional and diffusive model, as well as complete model of unsteady water flow in channel sections, and take into account all main hydraulic characteristics of the channel section.
{"title":"Mathematical models of optimal distribution of water in main channels","authors":"S. Rakhimov, A. Seytov, N. Rakhimova, Bahrom Xonimqulov","doi":"10.1109/AICT50176.2020.9368798","DOIUrl":"https://doi.org/10.1109/AICT50176.2020.9368798","url":null,"abstract":"Mathematical models of optimum water distribution in channels of irrigation systems under the conditions of discrete water supply to consumers have been developed. These include the models of direct wave, kinematical wave, convectional and diffusive model, as well as complete model of unsteady water flow in channel sections, and take into account all main hydraulic characteristics of the channel section.","PeriodicalId":136491,"journal":{"name":"2020 IEEE 14th International Conference on Application of Information and Communication Technologies (AICT)","volume":"14 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":"125303465","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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