2021 IEEE 15th International Conference on Application of Information and Communication Technologies (AICT)最新文献_第3页

Genetic Algorithm Based on Idempotent Algebra Methods for RCPSP 基于幂等代数方法的RCPSP遗传算法

2021 IEEE 15th International Conference on Application of Information and Communication Technologies (AICT) Pub Date : 2021-10-13 DOI: 10.1109/AICT52784.2021.9620510

Aleksandr M. Bulavchuk, D. Semenova

引用次数: 4

A Novel Approach towards using Internet-of-Things in Smart Agriculture Monitoring System 物联网在智能农业监测系统中的应用

2021 IEEE 15th International Conference on Application of Information and Communication Technologies (AICT) Pub Date : 2021-10-13 DOI: 10.1109/AICT52784.2021.9620508

Shreyans Shah, Anwita Chakraborty, Yelithoti Sravana Kumar, Tapaswini Samant, Swati Swayamsiddha

{"title":"A Novel Approach towards using Internet-of-Things in Smart Agriculture Monitoring System","authors":"Shreyans Shah, Anwita Chakraborty, Yelithoti Sravana Kumar, Tapaswini Samant, Swati Swayamsiddha","doi":"10.1109/AICT52784.2021.9620508","DOIUrl":"https://doi.org/10.1109/AICT52784.2021.9620508","url":null,"abstract":"With the introduction of the Internet-of-Things (IoT) in the field of agriculture, the concept of agribusiness has witnessed a surge in the production of high-quality crops, better yearly yield, and reduction in manual labor. This proposed technique is low-cost and easy to implement, which provides farmers with a smart field monitoring system with the aid of a mobile application and also provides a solution to tackle unsolicited climatic conditions without human intervention. Prediction of temperature, humidity, and rain for the next day is also a key feature of the system. In our proposed system, we have used a Node Micro Controller Unit, a Wi-Fi microchip for connectivity, various sensors for monitoring, various actuators for taking suitable actions, and an android application for displaying real-time data. The cloud used for storing real-time data is Firebase. The proposed technique will reduce human efforts to a great extent compared to the traditional way of farming. This concept can be implemented on large farmlands as well as polyhouses. This research proposes a prototype for a smart agriculture management system that would replace the time-consuming traditional farming approach with advanced technology that would not only assist in monitoring but also automate the essential operations without affecting crop quality and production.","PeriodicalId":150606,"journal":{"name":"2021 IEEE 15th International Conference on Application of Information and Communication Technologies (AICT)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116785677","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: 1

Distribution of Operations in Heterogeneous Computing Systems for Processing Speech Signals 语音信号处理异构计算系统中的操作分布

2021 IEEE 15th International Conference on Application of Information and Communication Technologies (AICT) Pub Date : 2021-10-13 DOI: 10.1109/AICT52784.2021.9620451

M. Rakhimov, Manon Ochilov

{"title":"Distribution of Operations in Heterogeneous Computing Systems for Processing Speech Signals","authors":"M. Rakhimov, Manon Ochilov","doi":"10.1109/AICT52784.2021.9620451","DOIUrl":"https://doi.org/10.1109/AICT52784.2021.9620451","url":null,"abstract":"The exponential growth of data is forcing the search for new approaches to computing power. The diversity of data is increasing, and with it is the need for advanced techniques such as artificial intelligence (AI), machine/deep learning to help transform that data into information. Speech signal processing in particular is one of them. As a solution, generic computing is being replaced by heterogeneous computing. This article describes the technologies of parallel processing and distributed operations of spectral transformation of speech signals using central processing unit (CPU) and graphics processing unit (GPU). The one problem of parallel processing of spectral transformation of speech signals is imbalance among the operations between CPU and GPU which leads to performance degradation. A serious problem with spectral transform is the selection of the appropriate frame size of the speech signal for parallel processing on the CPU or GPU. The article also proposes a fast algorithm for spectral transformation of speech signals using OpenMP and CUDA technologies, and results of the influence of the number of threads and the frame size of the speech signal on the acceleration is also shown.","PeriodicalId":150606,"journal":{"name":"2021 IEEE 15th International Conference on Application of Information and Communication Technologies (AICT)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122136496","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: 4

Points-of-Interest Recommendation Algorithms for a COVID-19 Restrictions Scenario in the Catering Industry 餐饮业COVID-19限制场景的兴趣点推荐算法

2021 IEEE 15th International Conference on Application of Information and Communication Technologies (AICT) Pub Date : 2021-10-13 DOI: 10.1109/AICT52784.2021.9620251

Gleb Glukhov, Ivan Derevitskii

{"title":"Points-of-Interest Recommendation Algorithms for a COVID-19 Restrictions Scenario in the Catering Industry","authors":"Gleb Glukhov, Ivan Derevitskii","doi":"10.1109/AICT52784.2021.9620251","DOIUrl":"https://doi.org/10.1109/AICT52784.2021.9620251","url":null,"abstract":"The COVID-19 pandemic has affected many areas of day-to-day life, including tourism and restaurants. Many countries imposed restrictions on restaurants during the COVID19 period. Many restaurants closed, and others switched to delivery and take-out services. These restrictions affect both the catering system as a whole and smart catering systems, such as recommender systems and user experience aggregators. The main purpose of the article is to assess the impact of COVID-19 on these digital components in different countries, depending on the COVID-19 strategy. In particular, the author’s contribution is as follows: (1) assessing the stability of recommendation algorithms depending on the country’s COVID-19 elimination strategy, (2) identifying factors associated with changes in user behavior during the COVID-19 pandemic, (3) using these factors to improve the recommendation system, (4) answering the counter-question of whether the actual quarantine compliance can be determined using these data. As a result of the experiments, we have identified a change in the accuracy of recommendation algorithms both during and after the lockdown. We also obtained factors for changing user behavior and made assumptions about quarantine compliance in various countries using user experience data. The proposed contextual method has shown increased efficiency during the COVID-19 period.","PeriodicalId":150606,"journal":{"name":"2021 IEEE 15th International Conference on Application of Information and Communication Technologies (AICT)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126019516","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: 1

Context-Aware Recommender System based on Content Filtering 基于内容过滤的上下文感知推荐系统

2021 IEEE 15th International Conference on Application of Information and Communication Technologies (AICT) Pub Date : 2021-10-13 DOI: 10.1109/AICT52784.2021.9620478

Mai Abusair, Mohammad Sharaf, Mosab Bozeya, Abdulrhman Beiruti

引用次数: 0

Application of BG / NBD and Gamma-Gamma Models to Predict Customer Lifetime Value for Financial Institution BG / NBD和Gamma-Gamma模型在金融机构客户终身价值预测中的应用

2021 IEEE 15th International Conference on Application of Information and Communication Technologies (AICT) Pub Date : 2021-10-13 DOI: 10.1109/AICT52784.2021.9620535

Asiman Mammadzada, Emin Alasgarov, Agasalim Mammadov

引用次数: 3

Development of a System for Designing Wireless Networks with Incomplete Coverage and Specified Subscriber Routes 不完全覆盖和指定用户路由无线网络设计系统的开发

2021 IEEE 15th International Conference on Application of Information and Communication Technologies (AICT) Pub Date : 2021-10-13 DOI: 10.1109/AICT52784.2021.9620348

O. Blinova

引用次数: 0

Techniques of Malware Detection: Research Review 恶意软件检测技术:研究综述

2021 IEEE 15th International Conference on Application of Information and Communication Technologies (AICT) Pub Date : 2021-10-13 DOI: 10.1109/AICT52784.2021.9620415

Elshan Baghirov

{"title":"Techniques of Malware Detection: Research Review","authors":"Elshan Baghirov","doi":"10.1109/AICT52784.2021.9620415","DOIUrl":"https://doi.org/10.1109/AICT52784.2021.9620415","url":null,"abstract":"Analysis, and detection of malicious software play a crucial role in computer security. Signature-based malware detection methods were a classical solution in this area. However, malware creators are able to bypass these detection methods using some obfuscation methods like metamorphism, polymorphism. To address this issue, methods based on machine learning have been applied. However, some challenges are still present. This work presents a planned and detailed review of the malware detection mechanisms used by researchers. For this purpose, scientific works on malware detection topics were classified according to applied methods of malware detection, the accuracy of detection, etc. Several scientific works have been reviewed for analysis, and the current situation in the fight against malware has been analyzed. The main contributions of this paper are to provide detailed information to researchers about challenges on malware detection, to present to researchers a general overview of the malware detection field, to provide valuable information about tools and malware datasets that are commonly used by researchers.","PeriodicalId":150606,"journal":{"name":"2021 IEEE 15th International Conference on Application of Information and Communication Technologies (AICT)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126590622","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

The Modern Symbolic Artificial Intelligence and Its Use in Medical Tourism 现代符号人工智能及其在医疗旅游中的应用

2021 IEEE 15th International Conference on Application of Information and Communication Technologies (AICT) Pub Date : 2021-10-13 DOI: 10.1109/AICT52784.2021.9620321

N. Sakipov, O. Vikhnin

{"title":"The Modern Symbolic Artificial Intelligence and Its Use in Medical Tourism","authors":"N. Sakipov, O. Vikhnin","doi":"10.1109/AICT52784.2021.9620321","DOIUrl":"https://doi.org/10.1109/AICT52784.2021.9620321","url":null,"abstract":"The “top-down” ideology of creating digital products imitating some properties of human intelligence, such as texts understanding, their translation into other languages, expert opinions, etc. is described.It has been shown that the use by authors concepts from different spheres of life leads to quite reasonable and practical solutions like Symbolic Artificial Intelligence (SAI).SAI is associated with language (communicative and semantic) human activity and is designed to work with symbolic information, e.g. in the form of texts and voice audio messages. According to [1], the text can be represented as a set of minimal, further indivisible structural units of the text, that carry elementary meanings. Thus, by breaking the text into such units, which are also “units of meaning” and defining their meanings, the SAI “understands” the content of the input text, that means the program is able to analyze the content of the message, determine the participants and their roles in the analyzed situation, and respond to questions such as who is the main character, his actions, time and place of action, etc. Thus, the program - a digital simulator of human intelligence “understands” the meaning and is able, for example, to annotate the text “in its own words” without using the vocabulary of the text.The SAI developed by the authors belongs to the category of “small data” and implements the aforementioned capabilities of human intelligence.The corresponding SAI algorithms for high quality machine translation for using in medical tourism are described.","PeriodicalId":150606,"journal":{"name":"2021 IEEE 15th International Conference on Application of Information and Communication Technologies (AICT)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126166323","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

Sentiment Analysis Model for Fake News Identification in Arabic Tweets 阿拉伯语推文虚假新闻识别的情感分析模型

2021 IEEE 15th International Conference on Application of Information and Communication Technologies (AICT) Pub Date : 2021-10-13 DOI: 10.1109/AICT52784.2021.9620509

Aktham Sawan, Thaer Thaher, Noor Abu-El-Rub

{"title":"Sentiment Analysis Model for Fake News Identification in Arabic Tweets","authors":"Aktham Sawan, Thaer Thaher, Noor Abu-El-Rub","doi":"10.1109/AICT52784.2021.9620509","DOIUrl":"https://doi.org/10.1109/AICT52784.2021.9620509","url":null,"abstract":"Over the last few years, the exponential rise of social media, particularly Twitter, is becoming a major source of news sharing and consumption among users. These platforms allow users to publish, author and distribute content. These environments may be used to report and spread gossip and false news, whether accidentally or maliciously. Fake news and inaccurate machine-generated text are serious issues affecting societies worldwide, particularly the Arab world. This motivates efforts to identify fake and distorted news. This paper aims to introduce a robust prediction model to identify fake news in Arabic Tweets. Several Natural Language Processing (NLP), feature selection, and advanced ML algorithms were exploited to achieve this purpose. NLP techniques were used to process and transform the given tweets into structured form. The recursive feature elimination (RFE) technique was employed to eliminate uninformative features. ML methods were used to build the prediction model. Experimental results revealed the superiority of the Logistic Regression (LR) classifier among other algorithms. Moreover, RFE proved its ability to enhance the overall performance of the LR classifier. Overall, the proposed model provided an acceptable prediction accuracy of 82%.","PeriodicalId":150606,"journal":{"name":"2021 IEEE 15th International Conference on Application of Information and Communication Technologies (AICT)","volume":"239 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133852719","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