2021 IEEE 4th International Conference on Advanced Information and Communication Technologies (AICT)最新文献_第2页

Information System for Analysis of Forest Plantations and Monitoring of Ecological Condition 人工林分析与生态状况监测信息系统

2021 IEEE 4th International Conference on Advanced Information and Communication Technologies (AICT) Pub Date : 2021-09-21 DOI: 10.1109/aict52120.2021.9628990

B. Rusyn, Y. Obukh, R. Kosarevych, O. Lutsyk, V. Korniy

{"title":"Information System for Analysis of Forest Plantations and Monitoring of Ecological Condition","authors":"B. Rusyn, Y. Obukh, R. Kosarevych, O. Lutsyk, V. Korniy","doi":"10.1109/aict52120.2021.9628990","DOIUrl":"https://doi.org/10.1109/aict52120.2021.9628990","url":null,"abstract":"This paper proposes information technology for analyzing the condition of forest plantations and monitoring the ecological condition of forests. Information technology is based on the proposed approach to automatic localization and recognition of affected trees, and is of great practical importance for environmental monitoring and forestry. A deep learning model has been developed for localization and recognition. This model consists of a detector and separate classifier modules. In order to train and validate the proposed network based on remote sensing images, a training database containing 9000 images was created. Comparison of the proposed model with existing methods is based on characteristics such as accuracy and speed. The accuracy and speed of the proposed recognition system was assessed on a validation sample of images, the size of which is 2000 images. To ensure real-time operation, the software is optimized to work with the GPU. The results of the work and the developed software are used in remote monitoring and classification systems for environmental monitoring and in applied tasks of forestry.","PeriodicalId":375013,"journal":{"name":"2021 IEEE 4th International Conference on Advanced Information and Communication Technologies (AICT)","volume":"196 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115149874","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

Method of Semantic Coding of Speech Signals based on Empirical Wavelet Transform 基于经验小波变换的语音信号语义编码方法

2021 IEEE 4th International Conference on Advanced Information and Communication Technologies (AICT) Pub Date : 2021-09-21 DOI: 10.1109/aict52120.2021.9628985

O. Lavrynenko, R. Odarchenko, G. Konakhovych, A. Taranenko, D. Bakhtiiarov, T. Dyka

{"title":"Method of Semantic Coding of Speech Signals based on Empirical Wavelet Transform","authors":"O. Lavrynenko, R. Odarchenko, G. Konakhovych, A. Taranenko, D. Bakhtiiarov, T. Dyka","doi":"10.1109/aict52120.2021.9628985","DOIUrl":"https://doi.org/10.1109/aict52120.2021.9628985","url":null,"abstract":"The result of this work is to solve the current scientific and practical problem of developing and researching new effective methods of semantic coding of speech signals. A known method of semantic coding of speech signals based on mel-frequency cepstral coefficients, which does not comply with the condition of adaptability to the studied signal, which is a significant disadvantage of the existing method. A method of semantic coding of speech signals based on empirical wavelet transform is developed, which constructs sets of adaptive Meyer wavelet filters with subsequent application of Hilbert spectral analysis to find instantaneous amplitudes and frequencies of functions of internal empirical modes, which will determine semantic efficiency coding. It is proposed to use the method of adaptive empirical wavelet transform in problems of multiplescale analysis and semantic coding of speech signals, which will increase the efficiency of spectral analysis by decomposing high- frequency speech oscillations into its low-frequency components, namely internal empirical modes. An algorithm for semantic coding of speech signals based on empirical wavelet transform and its software implementation in the MATLAB R2020b programming language has been developed.","PeriodicalId":375013,"journal":{"name":"2021 IEEE 4th International Conference on Advanced Information and Communication Technologies (AICT)","volume":"358 4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114127643","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

Informational Technologies in Film Production - How ICT shaping Media Industry 电影制作中的信息技术-信息通信技术如何塑造媒体产业

2021 IEEE 4th International Conference on Advanced Information and Communication Technologies (AICT) Pub Date : 2021-09-21 DOI: 10.1109/aict52120.2021.9628901

Aidiye Aidarbekov, Gulmira Shakhmetova, Kamshat Asmaganbetova, Zamira Bekish, Abzal E. Kyzyrkanov, Abylay Salimzhanov

{"title":"Informational Technologies in Film Production - How ICT shaping Media Industry","authors":"Aidiye Aidarbekov, Gulmira Shakhmetova, Kamshat Asmaganbetova, Zamira Bekish, Abzal E. Kyzyrkanov, Abylay Salimzhanov","doi":"10.1109/aict52120.2021.9628901","DOIUrl":"https://doi.org/10.1109/aict52120.2021.9628901","url":null,"abstract":"This paper will provide a summary of the drivers which makes changes within the media industry and film production based on the progress of Information and Communications Technologies. As for now - the entertainment industry is constantly growing, based on reaching a more international audience and using new, creative ways of developing and delivering content. Despite the fact that entertainment is more close to Art - Information and Communications Technologies makes big and valuable changes to the industry, not only in terms of new devices, hardware, and software but also in the ways of creatively using those resources. Some of the examples in the article shows how technologies can change completely the ways how some instruments were used before, and how more sufficient and handier they can be only because new technologies opened new opportunities. Merging of the industries like game, movie and informational technologies is a matter of time and IT creations like “Unreal Engine” blurs the lines between gaming and filming, taking computer graphics and 3D modeling to a new level. Other big changes to the Art can bring Artificial Intelligence, Machine Learning, and Big Data instruments, although it’s still not so trusted by big production companies and film studios. But the more Information and Communications Technologies are evolving, the more Media Industry is changing.","PeriodicalId":375013,"journal":{"name":"2021 IEEE 4th International Conference on Advanced Information and Communication Technologies (AICT)","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114507911","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

Use of Content-Filtering Method for Hardware Vulnerabilities Identification System 内容过滤方法在硬件漏洞识别系统中的应用

2021 IEEE 4th International Conference on Advanced Information and Communication Technologies (AICT) Pub Date : 2021-09-21 DOI: 10.1109/aict52120.2021.9628948

M. Iavich, G. Iashvili, A. Gagnidze, R. Odarchenko

{"title":"Use of Content-Filtering Method for Hardware Vulnerabilities Identification System","authors":"M. Iavich, G. Iashvili, A. Gagnidze, R. Odarchenko","doi":"10.1109/aict52120.2021.9628948","DOIUrl":"https://doi.org/10.1109/aict52120.2021.9628948","url":null,"abstract":"Content filtering tools are fairly well established today. They allow us to find content that is relevant to our needs and interests. Many web platforms such as travel databases, online shops, educational systems and others use recommender tools to filter the content. For these systems, the issue of user security is quite acute on the agenda as hardware based systems are very often attacked by hackers. Many efficient results can be achieved by incorporating machine learning mechanisms into the recommendation systems. This will notably increase hardware-based systems security level. Information retrieval systems that rely on content-based mechanisms provide users with the relevant information and at the same time analyze their behavior. This is done to Figure out how effective the search was for the user. A model of a content-based recommendation system can be incorporated into existing security mechanisms. The network system developed in our study uses the integrated filtering mechanism to identify the frequency of the term received from the user input and it delivers the relevant content to the end user. This system has the advantage of the interacting with specific user cases. It should be noted that the content-based systems may not be fully functional by taking more complex interactions and user actions. This fact is the important field of the research in the world.","PeriodicalId":375013,"journal":{"name":"2021 IEEE 4th International Conference on Advanced Information and Communication Technologies (AICT)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126062005","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

Experimental Researches of Biometric Authentication Using Convolutional Neural Networks and Histograms of Oriented Graphs 基于卷积神经网络和有向图直方图的生物特征认证实验研究

2021 IEEE 4th International Conference on Advanced Information and Communication Technologies (AICT) Pub Date : 2021-09-21 DOI: 10.1109/aict52120.2021.9628932

A. Kuznetsov, Serhii Datsenko, Yuriy Gorbenko, Tetiana Chupilko, M. Korneyev, Victoria Klym

引用次数: 1

Method of Masking Information in the Contours of Video Images 视频图像轮廓信息掩蔽方法

2021 IEEE 4th International Conference on Advanced Information and Communication Technologies (AICT) Pub Date : 2021-09-21 DOI: 10.1109/aict52120.2021.9628973

V. Barannik, D. Barannik, Yevhenii Sidchenko, O. Ignatyev, O. Slobodyanyuk, Lazuta Roman

引用次数: 0

A Low-Cost Intelligent Metal Recycling Machine 一种低成本智能金属回收机

2021 IEEE 4th International Conference on Advanced Information and Communication Technologies (AICT) Pub Date : 2021-09-21 DOI: 10.1109/aict52120.2021.9628923

Saruhan Furkan Senturk, Muhammet Fatih Donmez, Huseyin Kaan Gulmez, Mehmet Gul, Pınar Kırcı

引用次数: 0

Information Model of Outdoor Air Pollution Prediction for Medical Diagnosis System 面向医疗诊断系统的室外空气污染预测信息模型

2021 IEEE 4th International Conference on Advanced Information and Communication Technologies (AICT) Pub Date : 2021-09-21 DOI: 10.1109/aict52120.2021.9628981

Valerii Lovkin, A. Oliinyk, Tetiana Fedoronchak, Yurii Lukashenko

引用次数: 0

A Model for the Organization of Adaptive Dialogue Interaction “Man-Computer” Taking into Account the Requirements of Reliability and Efficiency 考虑可靠性和效率要求的“人机”自适应对话交互组织模型

2021 IEEE 4th International Conference on Advanced Information and Communication Technologies (AICT) Pub Date : 2021-09-21 DOI: 10.1109/aict52120.2021.9628939

E. Lavrov, O. Siryk, Y. Chybiriak, L. Danilova, V. Nahornyi, Svetlana Vakal

引用次数: 0

Mechanisms of Fine Tuning of Neuroevolutionary Synthesis of Artificial Neural Networks 人工神经网络神经进化合成的微调机制

2021 IEEE 4th International Conference on Advanced Information and Communication Technologies (AICT) Pub Date : 2021-09-21 DOI: 10.1109/aict52120.2021.9628974

Serhii Leoshcheko, A. Oliinyk, S. Subbotin, Mykyta Zaiko

引用次数: 0