2020 IEEE 14th International Conference on Application of Information and Communication Technologies (AICT)最新文献_第7页

Using Support Vector Regression in multi-target prediction of drug toxicity 支持向量回归在药物毒性多目标预测中的应用

2020 IEEE 14th International Conference on Application of Information and Communication Technologies (AICT) Pub Date : 2020-10-07 DOI: 10.1109/AICT50176.2020.9368837

F. Adilova, Alisher Ikramov

引用次数: 1

Sybil Attack Detection In Wireless Sensor Networks 无线传感器网络中的Sybil攻击检测

2020 IEEE 14th International Conference on Application of Information and Communication Technologies (AICT) Pub Date : 2020-10-07 DOI: 10.1109/AICT50176.2020.9368790

Zhukabayeva T. K, Mardenov E. M, Abdildaeva A.A

引用次数: 1

Blockchain-based open infrastructure for URL filtering in an Internet browser 基于区块链的开放基础设施，用于互联网浏览器中的URL过滤

2020 IEEE 14th International Conference on Application of Information and Communication Technologies (AICT) Pub Date : 2020-10-07 DOI: 10.1109/AICT50176.2020.9368678

Obadah Hammoud, I. Tarkhanov

引用次数: 0

Algorithm for the Abnormal Ventricular Electrical Excitation Detection 异常心室电兴奋检测算法

2020 IEEE 14th International Conference on Application of Information and Communication Technologies (AICT) Pub Date : 2020-10-07 DOI: 10.1109/AICT50176.2020.9368866

Z. Yuldashev, A. Nemirko, D. Ripka

引用次数: 0

Simulation of Business Projects in the Agent Model of the Russian Federation Spatial Development 俄罗斯联邦空间开发代理模型中的商业项目模拟

2020 IEEE 14th International Conference on Application of Information and Communication Technologies (AICT) Pub Date : 2020-10-07 DOI: 10.1109/AICT50176.2020.9368665

A. Mashkova, E. Novikova, O. Savina

{"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}

引用次数: 0

Multi-level lecture video classification using text content 基于文本内容的多级讲座视频分类

2020 IEEE 14th International Conference on Application of Information and Communication Technologies (AICT) Pub Date : 2020-10-07 DOI: 10.1109/AICT50176.2020.9368692

Veysel Sercan Ağzıyağlı, H. Oğul

{"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}

引用次数: 0

Flying Ad hoc Network Expedited by DTN Scenario: Reliable and Cost-effective MAC Protocols Perspective 由DTN场景加速的飞行自组织网络:可靠和经济的MAC协议的观点

2020 IEEE 14th International Conference on Application of Information and Communication Technologies (AICT) Pub Date : 2020-10-07 DOI: 10.1109/AICT50176.2020.9368575

Sobiya Arsheen, A. Wahid, Khaleel Ahmad, Khujamatov Khalim

引用次数: 20

Donabedian Approach for Simulation Modeling to Evaluate the Quality of Emergency Medical Services in a Large Metropolitan Area: A Case Study 基于Donabedian方法的大都市地区紧急医疗服务质量评估:一个案例研究

2020 IEEE 14th International Conference on Application of Information and Communication Technologies (AICT) Pub Date : 2020-10-07 DOI: 10.1109/AICT50176.2020.9368653

S. V. Begicheva

{"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}

引用次数: 0

Development of the N-gram Model for Azerbaijani Language 阿塞拜疆语N-gram模型的发展

2020 IEEE 14th International Conference on Application of Information and Communication Technologies (AICT) Pub Date : 2020-10-07 DOI: 10.1109/AICT50176.2020.9368645

Aliya Bannayeva, Mustafa Aslanov

引用次数: 1

Hadith Authenticity Prediction using Sentiment Analysis and Machine Learning 基于情感分析和机器学习的圣训真实性预测

2020 IEEE 14th International Conference on Application of Information and Communication Technologies (AICT) Pub Date : 2020-10-07 DOI: 10.1109/AICT50176.2020.9368569

F. Haque, Anika Hossain Orthy, Shahnewaz Siddique

{"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}

引用次数: 2