2021 IEEE Region 10 Symposium (TENSYMP)最新文献_第7页

COVID-19 Fake News Prediction On Social Media Data 基于社交媒体数据的COVID-19假新闻预测

2021 IEEE Region 10 Symposium (TENSYMP) Pub Date : 2021-08-23 DOI: 10.1109/TENSYMP52854.2021.9550957

Asma Ul Hussna, Iffat Immami Trisha, Md. Sanaul Karim, Md. Golam Rabiul Alam

{"title":"COVID-19 Fake News Prediction On Social Media Data","authors":"Asma Ul Hussna, Iffat Immami Trisha, Md. Sanaul Karim, Md. Golam Rabiul Alam","doi":"10.1109/TENSYMP52854.2021.9550957","DOIUrl":"https://doi.org/10.1109/TENSYMP52854.2021.9550957","url":null,"abstract":"It is, to tell the truth, that the COVID-19 pandemic has put the whole world in a tough time, and sensitive information concerning COVID-19 has grown tremendously online. Most importantly, the gradual spread of fake news and misleading information during these hard times can have dire consequences, causing widespread panic and exacerbating the apparent threat of a pandemic that we cannot ignore. Because of the time-consuming nature of evidence gathering and careful truth-checking, people get confused between fallacious and trustworthy statement. So, we need a way to keep track of misinformation on social media. Most people think that all social media information is real information though, at the same time, it is a shame that some people misuse this social media platform for their own benefit by spreading misinformation. Many individuals take advantage by playing with the weaknesses of others. As a result, people around the world not only are facing COVID-19, they are also facing infodemics. To get rid of this kind of fake news, we have proposed a research model that can predict fake news related to the COVID-19 issue on social media data using classical classification methods such as multinomial naïve bayes classifier, logistic regression classifier, and support vector machine classifier. Moreover, we have applied a deep learning based algorithm named distil BERT to accurately predict fake COVID-19 news. These approaches have been used in this paper to compare which technique is much more convenient for accurately predicting fake news about COVID-19 on social media posts. In addition, we have used a data-set that included 6424 social media posts.","PeriodicalId":137485,"journal":{"name":"2021 IEEE Region 10 Symposium (TENSYMP)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115274331","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: 3

The Effect of The COVID-19 Pandemic and Google Trends on the Forecasting of International Tourist Arrivals in Indonesia 2019冠状病毒病大流行和谷歌趋势对印尼国际游客入境人数预测的影响

2021 IEEE Region 10 Symposium (TENSYMP) Pub Date : 2021-08-23 DOI: 10.1109/TENSYMP52854.2021.9550838

Suci Karunia Prilistya, A. E. Permanasari, S. Fauziati

{"title":"The Effect of The COVID-19 Pandemic and Google Trends on the Forecasting of International Tourist Arrivals in Indonesia","authors":"Suci Karunia Prilistya, A. E. Permanasari, S. Fauziati","doi":"10.1109/TENSYMP52854.2021.9550838","DOIUrl":"https://doi.org/10.1109/TENSYMP52854.2021.9550838","url":null,"abstract":"The tourism sector is a strategic industrial pillar that contributes to a country’s economy. In future tourism development efforts, accurate tourism forecasting is needed. Despite its importance, tourism is also one of the most vulnerable industries. Since COVID-19 was declared a pandemic by WHO, social distancing has significantly impacted tourism development. It can be explored more deeply by including the COVID-19 pandemic in the forecast. In addition, it is necessary to include Google Trends, which is a product of the largest search engine in the world and is proven to improve forecasting accuracy. This study aimed to analyze the effect of the COVID-19 pandemic and search query data on the forecasting of foreign tourists to Indonesia. The methods used are ARIMAX and SARIMAX with the endogenous variables of foreign tourist visits to Indonesia. Meanwhile, the exogenous variables are Google Trends search query data and the COVID-19 pandemic. The performance of the two methods is then compared with the ARIMA and SARIMA methods, which do not use exogenous variables in forecasting. This study indicates that the exogenous variables increase the forecasting accuracy. Forecasting with the best accuracy is obtained by the SARIMAX method with the exogenous variable Google Trends. This method outperformed the other methods with MAPE = 5.4556, RMSE = 11041.0510 and MAE = 8479.6116. In addition, in this study, a framework was created to build a composite search index for Google Trends to improve forecasting accuracy.","PeriodicalId":137485,"journal":{"name":"2021 IEEE Region 10 Symposium (TENSYMP)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125257709","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: 3

Sustainable Energy Storage for Coastal Areas using Lighthouses 利用灯塔实现沿海地区可持续能源储存

2021 IEEE Region 10 Symposium (TENSYMP) Pub Date : 2021-08-23 DOI: 10.1109/TENSYMP52854.2021.9551010

Ananthu T Mani, Austin Origin, Elizabeth Poulose, Raeesa Thasneem, E. R. Samuel

引用次数: 0

Stem Cell like Incarnation Self Repairing System in the IoT Intelligent Network 物联网智能网络中类似干细胞化身的自我修复系统

2021 IEEE Region 10 Symposium (TENSYMP) Pub Date : 2021-08-23 DOI: 10.1109/TENSYMP52854.2021.9550824

Jeong-Yon Shim

引用次数: 1

Periodic Component Replacing Method with Recognition Rate Test on Vowel Voices 元音语音识别率测试的周期性分量替换方法

2021 IEEE Region 10 Symposium (TENSYMP) Pub Date : 2021-08-23 DOI: 10.1109/TENSYMP52854.2021.9550762

Jing Zhi Lim, Hisashi Suzuki

引用次数: 0

Implementation of Dolph-Chebyshev Window on Proximity-Fed Circularly Polarized Array Slotted Square Patch Antenna 邻近馈源圆极化阵开槽方形贴片天线的dolphor - chebyshev窗口实现

2021 IEEE Region 10 Symposium (TENSYMP) Pub Date : 2021-08-23 DOI: 10.1109/TENSYMP52854.2021.9550814

A. Munir, C. Pratiwi, Hartuti Mistialustina, Budi Irawan

引用次数: 3

Comparison of Rigorous Coupled-Wave Analysis and Finite Difference Time Domain Method on Dielectric Gratings 介质光栅严格耦合波分析与时域有限差分法的比较

2021 IEEE Region 10 Symposium (TENSYMP) Pub Date : 2021-08-23 DOI: 10.1109/TENSYMP52854.2021.9550974

H. Jang, J. Yi

引用次数: 1

Analysis of Electronic Medical Records to Forecast Probable Disease Outbreaks in Bangladesh 分析电子医疗记录以预测孟加拉国可能爆发的疾病

2021 IEEE Region 10 Symposium (TENSYMP) Pub Date : 2021-08-23 DOI: 10.1109/TENSYMP52854.2021.9550984

Khadija Akter, Mehedi Islam, K. H. Kabir

{"title":"Analysis of Electronic Medical Records to Forecast Probable Disease Outbreaks in Bangladesh","authors":"Khadija Akter, Mehedi Islam, K. H. Kabir","doi":"10.1109/TENSYMP52854.2021.9550984","DOIUrl":"https://doi.org/10.1109/TENSYMP52854.2021.9550984","url":null,"abstract":"Electronic medical data repository system provides the research platform for interconnecting healthcare and fore-casting probable disease outbreak. It offers the opportunity to collect, organize and manage medical data for further usages. However, in an overpopulated country like Bangladesh, due to the lack of a centralized medical data repository and complex disease analysis, the prediction of the outbreak of deadly diseases (e.g., dengue fever) becomes difficult and time consuming. This paper attempts to describe a web-based development of a medical data repository system, named ‘Lifeline of Medical Data’ (LMD), aiming to improve the medical data storage system focusing on Bangladesh. It offers analysis on the data, particularly on usages of medicine data in a particular period or particular areas, and responds to epidemic outbreaks quickly. LMD extends multiple wings to collect, visualize and analyze diverse medicine usages through web and app-based profile creation and prescription generation of multiple stakeholders (e.g., patients, doctors, etc.). Moreover, it shows the possible impact in recurring disease outbreak prediction using the time series forecasting model, i.e., Autoregressive Integrated Moving Average (ARIMA). This paper also describes socio economic impact of this multi-functional web platform based on individual and national practice.","PeriodicalId":137485,"journal":{"name":"2021 IEEE Region 10 Symposium (TENSYMP)","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133977945","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 Speech Dialogue Systems for Social AI in Cooperative Game Environments 协作游戏环境下社交AI语音对话系统的开发

2021 IEEE Region 10 Symposium (TENSYMP) Pub Date : 2021-08-23 DOI: 10.1109/TENSYMP52854.2021.9550859

Jae-Gon Suh, Casey C. Bennett, Benjamin Weiss, Eunseo Yoon, Jihong Jeong, Yejin Chae

{"title":"Development of Speech Dialogue Systems for Social AI in Cooperative Game Environments","authors":"Jae-Gon Suh, Casey C. Bennett, Benjamin Weiss, Eunseo Yoon, Jihong Jeong, Yejin Chae","doi":"10.1109/TENSYMP52854.2021.9550859","DOIUrl":"https://doi.org/10.1109/TENSYMP52854.2021.9550859","url":null,"abstract":"There is increasing interest in developing more human-like artificial intelligence (AI) capable of natural social interaction. Previous research has suggested ideas about what it means to be \"life-like\" AI, and some studies have attempted to test these hypotheses using game environments. In this paper, we introduce the development of the Speech Dialogue System for a \"Social AI\", which communicates and interacts autonomously with a human player in cooperative game environments (in this case a social survival game called \"Don’t Starve Together\"). Based on our hypothesis that the AI should contain specific components to be perceived as more human-like, we conducted a series of pilot tests to develop the Social AI using a data-driven approach. After finishing the pilot tests, we identified six components to add or revise, based on participant interactions and feedback. These components mainly include features of the Speech Dialogue System that pertain to the interplay of AI behavior with contextual factors of the social environment (\"the game state\"). In future work, we intend to improve the Social AI based on these findings. The research here highlights the use of cooperative game environments for data-driven development of speech dialogue systems for artificial agents.","PeriodicalId":137485,"journal":{"name":"2021 IEEE Region 10 Symposium (TENSYMP)","volume":"90 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133655792","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: 3

Decision Theory-based Content Selection and Ranking for Social Media Newsfeed using Fuzzy Analytic Hierarchy Process 基于决策理论的模糊层次分析法在社交媒体信息流内容选择与排序中的应用

2021 IEEE Region 10 Symposium (TENSYMP) Pub Date : 2021-08-23 DOI: 10.1109/TENSYMP52854.2021.9550917

Sadia Nasrin Tisha, Mahjabeen Tamanna Abed, Md. Golam Rabiul Alam

引用次数: 1