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A Study on the Development and Standard Specification of Unmanned Traffic Enforcement Equipment for Two-Wheeled Vehicles (이륜차 무인교통단속장비 개발 및 표준규격 연구)

  • Byung chul In;Seong jun Yoo;Eum Han;Kyeongjin Lee;Sungho Park
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.22 no.1
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    • pp.126-142
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    • 2023
  • The purpose of this study is to develop unmanned traffic enforcement equipment and standard specifications for the prevention of traffic accidents and violations of the two-wheeled vehicle laws. To this end, we conducted a review of the problems and new technologies of the currently operating unmanned traffic enforcement equipment on two-wheeled vehicles. And through a survey, the feasibility of introducing unmanned traffic enforcement equipment for two-wheeled vehicles and the current status of technology were investigated. In addition, the two-wheeled vehicle enforcement function was implemented through field tests of the development equipment, and the addition of enforcement targets and the number recognition rate were improved through performance improvement. Based on the results of field experiments and performance evaluation, performance standards for unmanned two-wheeled vehicle traffic enforcement equipment were prepared, and in the communication protocol, two-wheeled vehicle-related matters were newly composed in the vehicle classification code and violation items to develop standards.

A Study on the Effect of Regulatory Focus and Self-construal on Digital Signage Advertisement (디지털 사이니지 광고유형별 효과에 조절초점과 자아해석이 미치는 영향)

  • Tae-Wook Ju;Hyun-Seok Kim
    • Journal of Industrial Convergence
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    • v.21 no.3
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    • pp.29-36
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    • 2023
  • In this study, the differential effects of exposure-type digital signage advertisement and interactive digital signage advertisement were examined through the moderating variables of regulatory focus and self-construal. As a result of the study, in the case of individuals with promotion focus and independent self-construal, interactive digital signage advertisements had a more positive effect than exposure-type digital signage advertisements. However, in the case of prevention focus and interdependent self-construal, there was no difference in effect between digital signage advertisement types. Therefore, we can help to establish a customized strategy according to individual characteristics using digital signage.

Influence of Violent Experience, Emotional Labor, and Positive Psychological Capital On the Burnout of Psychiatric and Emergency Department Nurse (정신병동간호사와 응급실간호사의 폭력경험, 감정노동과 긍정심리자본이 직무소진에 미치는 영향)

  • Oh, Eun-Joung
    • Journal of Digital Convergence
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    • v.20 no.1
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    • pp.445-458
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    • 2022
  • The purpose of this study was to examine the relationships among violence experience, emotional labor, positive psychological capital and job burnout in psychiatirc and emergency department nurse. During June and July 2021, date were collected from 183 psychiatric and emergency department nurse in J, K and I cities. Date were analyzed using hierarchical analysis with the SPSS WIN 21.0 programs. Emotional labor and verbal experience were positively correlated with burnout of psychiatric and emergency department nurse. Also positive psychological capital was negatively correlated with burnout. Violence experience, emotional labor and positive psychological capital were significant factors, explaining approximately 62.7% of the variance in burnout. These finding indicate that it will be more effective to strategies that can increase positive psychological capital that prevent burnout. Also based on these results, emphasizing the importance of understanding violence and emotional labor is needed to decrease burnout.

A Study on the Application Direction of Financial Industry Metaverse Platform to secure MZ Generation Contact Points (MZ 세대 접점 확보를 위한 금융권 메타버스 플랫폼 활용 방향 연구)

  • Ki-Jung Ryu;Ki-Bum Park;Sungwon Cho;Dongho Kim
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.23 no.3
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    • pp.127-137
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    • 2023
  • COVID-19 has not only affected all sectors of society, economy and politics, but also had a huge impact on industry. The non-face-to-face exchange method was essential to prevent infectious diseases, and the generation who experienced it recognizes the importance of a platform that can be quickly accessed anytime, anywhere, and attention is focused on the Metaverse that can accommodate it well. Each financial industry uses a differentiated metabus platform strategy, focuses on new customer service and revenue generation, and is also used as an internal and external communication channel. This paper analyzes the theoretical background of the financial sector metaverse and domestic and international cases, and studies and describes the direction of using the financial sector metaverse platform to secure MZ generation contact points.

Probabilistic External Flood Hazard Assessment at Major National Facilities (국가주요시설물에 대한 확률론적 외부 침수 재해도 평가)

  • Kim, Beom Jin;Kim, Byunghyun;Han, Kun Yeun
    • Proceedings of the Korea Water Resources Association Conference
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    • 2020.06a
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    • pp.387-387
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    • 2020
  • 본 연구에서는 LIP에 의한 극한강우로부터 발생되는 극한홍수량을 산정한다. Huff 형 강우시간 분포를 기후변화 시나리오별로 적용하고, 원전주변지역에서의 상세한 토지이용조건의 변화를 고려하여 빈도별 홍수량을 산정한다. 외부침수해석의 정교화를 위한 상세 지형자료를 구축하고, 원자력발전소 부지의 상세 DEM 자료를 생성한다. 이를 위해서 원자력발전소 부지에서 건물, 연석, 도로 등의 영향을 분석하고 토지이용상황에 따른 조도계수를 산정한다. 또한 원전지역에서의 외부침수재해도 분석을 위해서 국립해양조사원에서 검토한 기후변화를 고려한 조위분석 자료를 외부경계조건으로 설정한 후 부지에 대한 2차원 수리분석을 실시한다. 침수심, 침수유속, 침수시간, 침수동압력 분석 등 2차원 침수해석결과를 바탕으로 발생빈도별 침수심, 침수강도 등의 정량적인 분석을 통해서 빈도별 재해도 곡선을 개발한다. 그리고 원전지역에서의 외부 침수에 대한 대표적인 재해도 곡선을 산정하기 위하여 재현기간별 지속시간에 따른 침수심을 분석하고 정리한다. 재현기간별 침수심에 대해 확률 분포형을 적용하기 위해서 AIC검증을 통한 분포형의 적합성을 분석을 실시한다. 또한 재현기간별 지속시간에 따른 침수심들 간의 상관관계를 분석하여 분포형에 적용한다. 적용된 분포형을 몬테칼로 시뮬레이션을 통한 대표적인 확률론적 외부 침수 재해도 곡선을 산정한다. 본 연구를 바탕으로 원전 부지 및 그 부속 시설물(SSC)의 홍수방지 기능과 홍수 대비 시설물에 대한 적용 절차의 신뢰성, 홍수 저감 및 대응 전략에 대한 정량화가 가능하여 원전 홍수 위험에 대한 정량적인 평가 지원이 가능하겠다. 고려할 외부 홍수와 관련된 원전 내부시설 및 장비에 대한 상세한 모델링 절차, 특정 시나리오에 대한 홍수 방지 및 예방과 관련한 SSC의 정량화, 홍수저감 활동과 관련된 통제실 외부 시설물에 대한 수동 조작에 대한 평가가 이루어질 수 있겠다.

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Data Preprocessing for Predicting Sarcopenia Based on Machine Learning (기계학습 기반 근감소증 예측을 위한 데이터 전처리 기법)

  • Yoon Choi;Yourim Yoon
    • The Journal of the Convergence on Culture Technology
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    • v.9 no.3
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    • pp.737-744
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    • 2023
  • Sarcopenia is an increasingly common disease among the elder that has recently received attention. Although the causes of sarcopenia are diverse, aging, dietary habits, lack of exercise are the one of the major factors. As the causes of sarcopenia are diverse, it is important to develop strategies for prevention and treatment. However, predicting sarcopnia accuartely is difficult due to the variety of factors involved. Here, machine learning can significantly improve the accuracy and convenience of predicting sarcopenia. However, since lifestyle habits and biological data are vast, using data without preprocessing may be inappropriate in terms of time complexity and accuracy. This paper reviews recent literature on sarcopnia and its causes, focusing on preprocessing the data to be used in sarcopnia prediction machine learning accrodingly.

Suggestions for establishing a smart system to revitalize the local traditional market (지역 전통시장 활성화를 위한 지능형 시스템 구축 제언)

  • Lee, Junghun;Cho, Jungwon
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2022.10a
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    • pp.191-193
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    • 2022
  • The advent of the 4th Industrial Revolution due to the trigger of digital technologies such as artificial intelligence and big data has caused many changes in society, culture, and industry. However, traditional markets in each region are not responding quickly to new distribution environments and consumer changes. In particular, in the case of traditional markets in Jeju, regional characteristics such as marketing strategies for tourists visiting Jeju have not been utilized. Therefore, this study proposes the establishment of a smart traditional market based on big data and artificial intelligence that utilizes the regional characteristics of Jeju. The research contents include customer profiling through visitor big data analysis, providing tourist movement results through traffic analysis, providing real-time popular product charts, and developing video-based fire and crime prevention functions.

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The Efficient Extraction Strategy for ship displays in AIS Monitoring System (AIS 모니터링 시스템의 효율적 선박표시를 위한 데이터 추출 전략)

  • Kim, Byoung-Kug;Hong, Sung-Hwa;Lee, Jaeho
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2022.10a
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    • pp.588-590
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    • 2022
  • Sharing both locations and positions of ships makes it possible to utilize critical item for their safe and efficient navigation in such diversifying meantime environments. AIS is the representative technology for the sharing solutions. The AIS is even used in airspace and ground stations, so that AIS could facilitate the ships' safety navigation and their prevention/rescue from endangers. Due to AIS's many advantages, IMO(International Maritime Organization) made adapting the AIS mandatory for international passenger ships and the ships that are over than 300 tons. AIS uses VHF band areas for transmitting information and the information can be propagated to several hundreds km in range. Due to the large range, AIS monitoring system can acquire huge number of ships, which makes system performance lower and busier. In this paper, we propose the strategy of AIS information extraction for efficient monitoring system. Thus, the monitoring system has higher processing performance and lower network usage. As well as, the proposal affects the monitoring system has more capacity to include other systems' targets, in result.

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AI Crime Prediction Modeling Based on Judgment and the 8 Principles (판결문과 8하원칙에 기반한 인공지능 범죄 예측 모델링)

  • Hye-sung Jung;Eun-bi Cho;Jeong-hyeon Chang
    • Journal of Internet Computing and Services
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    • v.24 no.6
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    • pp.99-105
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    • 2023
  • In the 4th industrial revolution, the field of criminal justice is paying attention to Legaltech using artificial intelligence to provide efficient legal services. This paper attempted to create a crime prediction model that can apply Recurrent Neural Network(RNN) to increase the potential for using legal technology in the domestic criminal justice field. To this end, the crime process was divided into pre, during, and post stages based on the criminal facts described in the judgment, utilizing crime script analysis techniques. In addition, at each time point, the method and evidence of crime were classified into objects, actions, and environments based on the sentence composition elements and the 8 principles of investigation. The case summary analysis framework derived from this study can contribute to establishing situational crime prevention strategies because it is easy to identify typical patterns of specific crime methods. Furthermore, the results of this study can be used as a useful reference for research on generating crime situation prediction data based on RNN models in future follow-up studies.

A Study on Improvement of Soldier Mental Health Care Using Wearable Devices (웨어러블 기기를 이용한 군 장병 정신건강 관리 향상 방안)

  • In-Chan Kim;Sang-Keun Cho;Jun-Hak Sim;Jong-Hoon Kim;Sang-Hyuk Park
    • The Journal of the Convergence on Culture Technology
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    • v.9 no.6
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    • pp.801-805
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    • 2023
  • In Korea, the population is continuously decreasing due to the decrease in fertility rates. Military troops are continuously decreasing, but soldiers' suicide, mental health care and medicine prescriptions, and inadequate decisions are increasing. In other words, the mental health of the intestines is getting worse. The mental health of the soldiers is a personal problem, but it can also have a big impact on the troops. This is because accidents such as suicide, divorce, and military leave lead to the restriction of the combat power and the deterioration of fraud. Currently, domestic and foreign academics are studying mental health care plans using wearable devices. The Korean military can also use this to objectively measure the mental health of soldiers and use the accumulated big data to predict and measure various situations. In this study, this study suggests mental health care measures for military soldiers using wearable devices, and further research will be conducted smoothly to improve the mental health of our soldiers.