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시계열 교통데이터 기반 고속도로 교통흐름 예측 모델 연구
강동묵(DongMug Kang),이명오(MyungOh Lee),김용현(YongHyun Kim),윤상훈(SangHun Yoon),신대교(DaeKyo Shin),장수현(SooHyun Jang) 대한전자공학회 2021 대한전자공학회 학술대회 Vol.2021 No.6
There are short sections where congestion often occurs on the highway, such as the exit route of the highway. If traffic flow can be predicted in the future point for these sections, drivers can drive actively and efficiently in consideration of road conditions. In this paper, we propose study on traffic flow prediction based on time series data of highway and average speed is used as traffic flow. In the case of time series data, it is extracted through speed estimation and object detection algorithms from 10 CCTV video installed on Yeongdong highway(Maseong IC ~ Singal JC, 3.4km) in Korea. For traffic flow prediction, we use Conv2D-LSTM model that consider spatio-temporal features. Also, in order to intuitively and efficiently represent the traffic congestion degree of a highway, traffic congestion parameter is proposed. As a result, the prediction model shows performance with an error of 7.08 based on the MAE(Mean Absolute Error), and the speed at the future point can be predicted.
디지털 커뮤니케이션 환경에서 청소년들의 감정과 이모티콘의 관계
김윤지 ( Yoon-ji Kim ),강동묵 ( Dongmug Kang ),김주영 ( Ju-young Kim ),김종은 ( Jong-eun Kim ) 대한의료커뮤니케이션학회 2017 의료커뮤니케이션 Vol.12 No.1
Purpose: Adolescents use emoticons to express their emotions in an online environment. Hence, medical experts can understand the emotions of adolescents by emoticons. The goal of this study was to investigate the relationship between various emotions and emoticons among the Korean adolescents. Methods: The questionnaire survey was conducted between September 1 and 30, 2014, involving 3,272 students in elementary schools, middle schools, and high schools affiliated in the Department of Education of the metropolitan city of Busan. A total of 1,717 students responded to the survey. The participants consisted of 806 males (46.9%), and 911 females (53.1%). Among these, there were 557 elementary school students (32.4%), 617 middle school students (35.9%), and 543 high school students (31.6%). A social networking analysis was conducted using NodeXL. Results: The frequency of emoticon use among adolescents runs in the order of joy, sadness, fear, surprise, anger, disgust, and then depression. Elementary school females mainly use emoticons to express joy; middle school females use emoticons to express sadness, surprise, anger, disgust, and depression; and high school females use emoticons to express fear. Age- and gender-specific emoticon networks were visualized by using the Haren-Korel fast multiscale algorithm. Commonly used emoticons by age and gender were expressed in the networks. Results of age- and gender-specific emoticon networks visualization show similar results of centrality of seven emoticons. Conclusion: In the digital communication environment, emoticons could be used to catch the emotions of adolescents in Korea.
의학교육에서 기계학습방법 교육: 석면 언론 프레임 연구사례를 중심으로
김준혁,허소윤,강신익,김건일,강동묵,Kim, Junhewk,Heo, So-Yun,Kang, Shin-Ik,Kim, Geon-Il,Kang, Dongmug 연세대학교 의과대학 2017 의학교육논단 Vol.19 No.3
There is a more urgent call for educational methods of machine learning in medical education, and therefore, new approaches of teaching and researching machine learning in medicine are needed. This paper presents a case using machine learning through text analysis. Topic modeling of news articles with the keyword 'asbestos' were examined. Two hypotheses were tested using this method, and the process of machine learning of texts is illustrated through this example. Using an automated text analysis method, all the news articles published from January 1, 1990 to November 15, 2016 in South Korea which included 'asbestos' in the title and the body were collected by web scraping. Differences in topics were analyzed by structured topic modelling (STM) and compared by press companies and periods. More articles were found in liberal media outlets. Differences were found in the number and types of topics in the articles according to the partisanship and period. STM showed that the conservative press views asbestos as a personal problem, while the progressive press views asbestos as a social problem. A divergence in the perspective for emphasizing the issues of asbestos between the conservative press and progressive press was also found. Social perspective influences the main topics of news stories. Thus, the patients' uneasiness and pain are not presented by both sources of media. In addition, topics differ between news media sources based on partisanship, and therefore cause divergence in readers' framing. The method of text analysis and its strengths and weaknesses are explained, and an application for the teaching and researching of machine learning in medical education using the methodology of text analysis is considered. An educational method of machine learning in medical education is urgent for future generations.
직무스트레스와 근골격계질환 · 정신증상과의 관계에 대한 연구
정경희(Kyounghee Jung),김유창(Yu Chang Kim),강동묵(Dongmug Kang),김정원(Jungwon Kim) 대한인간공학회 2008 大韓人間工學會誌 Vol.27 No.1
Work related musculoskeletal disorders (WMSDs) have become a hot issue within the Korean workplace for the past several years. Recently, the effect of job related stress on WMSDs, cerebro-cardiovascular diseases, and psychiatric disorders has been steadily increasing. The study conducted questionnaire of Korea version job stress model, WMSDs from NIOSH, CES-D (Center for Epidemiologic Studies Depression Scale), and STAI (State-Trait Anxiety Inventory) against train drivers. The results of this study show that the job stress score of the train drivers is high in the areas of physical environment, job latitude, interpersonal conflict, job insecurity, and organization system. The relation between job stress and WMSDs represented statistical significance in the areas of job demand, interpersonal conflict, job insecurity and organizational system. The relation between job stress and depressive disorders showed statistical significance in the areas of job demand, job insecurity and low reward. Finally, the relation between job stress and anxiety disorders showed statistical significance in areas of job demand, interpersonal conflict, job insecurity, organizational system and low reward.