• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.5
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• pp.1-9
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• 2021

In Korea, various information related to COVID-19 has been provided to the public through an EAM (Emergency Alert Message) service using CBS (Cell Broadcast Service) technology to respond to COVID-19. In particular, local governments have been actively using the EAM service as a major means of responding to COVID-19. However, since excessive use of EAM service has caused the inconvenience of the people rather than the positive effects, the authority to be able to send EAMs has be limited. In this paper, with the purpose of providing primary data for establishing a plan to properly operate EAMs, we compare and analyze the number of EAMs issued and the incidence rate of COVID-19 cases during the period from 2020 to the present. In addition, the monthly EAM usage and incidence rate of COVID-19 cases are compared in detail and correlation analysis is performed for local governments that have issued many EAMs. We expect that the analysis results of this paper will be used as primary data in establishing strategies for EAM service to counteract the prolonged COVID-19.

• Tunnel and Underground Space
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• v.30 no.6
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• pp.540-550
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• 2020

Machine learning has been actively used in the field of automation due to the development and establishment of AI technology. The important thing in utilizing machine learning is that appropriate algorithms exist depending on data characteristics, and it is needed to analysis the datasets for applying machine learning techniques. In this study, advance rate is predicted using geotechnical and machine data of TBM tunnel section passing through the soil ground below the stream. Although there were no problems of application of statistical technology in the linear regression model, the coefficient of determination was 0.76. While, the ensemble model and support vector machine showed the predicted performance of 0.88 or higher. it is indicating that the model suitable for predicting advance rate of the EPB Shield TBM was the support vector machine in the analyzed dataset. As a result, it is judged that the suitability of the prediction model using data including mechanical data and ground information is high. In addition, research is needed to increase the diversity of ground conditions and the amount of data.

• The Korean Society of Law and Medicine
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• v.22 no.3
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• pp.31-55
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• 2021

The Personal Information Protection Act, one of the revised 3 Data Laws, established a special cases concerning pseudonymous data. As a result, a personal information controller may process pseudonymized information without the consent of data subjects for statistical purposes, scientific research purposes, and archiving purposes in the public interest, etc. In addition, as a follow-up to the revised Personal Information Protection Act, a 'Guidelines for Utilization of Healthcare Data' was prepared, which deals with the pseudonymization in the medical sector. The guidelines are meaningful in that they provide practical criteria for accomplices by defining specific interpretations and examples that take into account the characteristics of healthcare data. However, the guidelines need to clarify the purpose of using pseudonymous data and strengthen the fairness of the composition of the data deliberation committee. The guidelines also require establishing a healthcare data compensation framework and strengthening the protection of rights for vulnerable subjects. In addition, the guidelines need to be adjusted for inconsistency with the Bioethics and Safety Act and the Medical Service Act. It is expected that this study will contribute to the creation of a safe environment for the utilization of healthcare data as well as the improvement of related laws and systems.

• Journal of Appropriate Technology
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• v.7 no.2
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• pp.196-205
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• 2021

As industrial safety increases, various industrial accident prevention technologies using smart factory technology are being studied. However, small and medium enterprises (SMEs), which account for the majority of industrial accidents, are having difficulties in preventing industrial accidents by applying these smart factory technologies due to practical problems. In this study, customized monitoring and warning systems for each type of industrial accident were developed and applied to the actual field. Through this, we demonstrated industrial accident prevention technology through appropriate smart factory technology used by SMEs. A customized monitoring system using vision, current, temperature, and gas sensors was established for the four major disaster types: worker body access, short circuit and overcurrent, fire and burns due to high temperature, and emission of hazardous gas. In addition, a notification method suitable for each work environment was applied so that the monitored risk factors could be recognized quickly, and real-time data transmission and display enabled workers and managers to understand the disaster risk effectively. Through the application and demonstration of these appropriate smart factory technologies, the spread of these industrial safety technologies is to be discussed.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.4
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• pp.94-109
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• 2024

As autonomous vehicles are allowed to drive on public roads, there is an increasing amount of on-road data available for research. It has therefore become possible to analyze impacts of autonomous vehicles on traffic safety using real-world data. It is necessary to use indicators that are well-representative of the driving behavior of autonomous vehicles to understand the implications of them on traffic safety. This study aims to derive indicators that effectively reflect the driving stability of autonomous vehicles by analyzing the driving behavior using the Waymo Open Dataset. Principal component analysis was adopted to derive indicators with high explanatory capability for the dataset. Driving stability indicators were separated into longitudinal and lateral ones. The road segments on the dataset were divided into four based on the characteristics of each, which were signalized and unsignalized intersections, tangent road section, and curved road section. The longitudinal driving stability was 35.48% higher in the curved road sections compared to the unsignalized intersections. With regard to the lateral driving stability, the driving stability was 76.08% higher in the signalized intersections than in the unsignalized intersections. The comparison between curved and tangent road segments showed that tangent roads are 146.87% higher regarding lateral driving stability. The results of this study are valuable for the further research to analyze the impact of autonomous vehicles on traffic safety using real-world data.

• Journal of Industrial Convergence
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• v.22 no.10
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• pp.21-28
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• 2024

Personal Mobility devices pose a significant safety risk to users depending on road conditions. With the recent surge in usage, the number of accidents has also increased, highlighting the need for a preventative system. This study aims to design and develop a warning system to enhance the safety of drivers by detecting road obstacles. To achieve this, a dataset is constructed using images of road obstacles, and the YOLOv5 model is trained. The system is based on the Raspberry Pi 4B, which processes video frames captured by a camera in real-time and triggers an LED warning when an obstacle is detected. The Flask framework is used to monitor the obstacle detection status in real time. Additionally, a GPS sensor is utilized to collect the user's location and speed data, and an auditory warning is triggered via a buzzer if the set speed is exceeded. In the future, this system could be expanded to transmit detected road obstacles and GPS information to a server, providing users with real-time road safety information. The results of this study can serve as essential technology for developing such a system.

• Proceedings of the KIEE Conference
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• 2006.10d
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• pp.253-255
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• 2006

본 논문은 고속선에서 전차선 귀선전류를 측정하여 UM71-C 궤도회로의 유지보수를 향상하고자한다. KTX 36호에 구축된 차상 검측시스템 중 귀선전류 검측시스템에서 레일 좌/우에 흐르는 전차선 귀선전류 및 레일 간의 귀선전류 차를 검측하여 불평형 상태를 비교 및 분석하였다. 이러한 결과는 궤도회로 설비들에 대한 구성요소의 기능저하를 사전 예측하여 열차의 안전운행을 확보하기 위한 자료로 활용하고, 또한 검측시스템에서 얻어진 데이터들과 비를 통해 향후 유지보수에 활용 가능한 지침 및 분석기준을 마련하고자 한다.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2014.06a
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• pp.297-299
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• 2014

그동안 관제사의 업무량과 관제권 설정 연구는 해상교통량과 혼잡도를 기반으로 한 위험성 평가에 치중되어 왔으나 실제 관제사의 업무는 해상교통을 유효하게 모니터링하는 것 뿐만 아니라 음성교신을 통해 관제업무를 수행하고 이를 기록하는 범위에 이른다. 관제통신을 측정하고 분석, 평가하는 방식이 보다 효과적인 데이터로 활용된다면 관제 한계치를 가름할 수 있는 수단으로 활용될 뿐만 아니라 관제권역의 구성, 해상교통안전성 평가, 해양안전정책 수립 등, 활용될 수 있는 새로운 가치가 창출될 것이다.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2016.05a
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• pp.252-254
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• 2016

VTS에서 정보제공실적은 대내 외적으로 많이 활용되며, VTS 성과평가 자료로 중요하게 활용되고 있다. 지금까지 VTS에서 산정되는 정보제공 실적은 대부분 관제사가 관제업무 중 정보제공 발생시 관제일지에 수기로 기록하고 있으나, 선박관제 및 선박모니터링, PORT-MIS 등 여러 업무를 수행하고 있는 관제사가 정보제공 실적을 일일이 기록하는데 한계가 있다. 본 연구에서는 객관적인 정보제공 실적 산출을 위해 VHF 음성 자료 및 선박간 조우데이터를 분석하여 선박교통데이터 기반의 선박 안전정보 제공 회귀모형식을 도출하고자 한다.

• Proceedings of the Korea Multimedia Society Conference
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• 2003.11a
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• pp.191-194
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• 2003

공간정보의 처리는 방대한 양의 자료처리가 필수적이므로 이를 지원할 수 있는 하드웨어와 소프트웨어의 발전과 함께 최근에 비약적인 발전을 가져온 분야이다. 공간자료구조를 활용한 지리정의시스템(GIS)에 의한 공간정의의 분석과 처리는 근래에 많은 응용을 갖는 분야로서 자리를 잡고 있으며 파생되는 응용분야가 날로 증가하고 있는 추세에 있다. 그러나 지하정보에 대한 연구는 지하정보의 비가시적인 특성상 아직은 초기단계라고 할 수 있다. 특히 지하 지층 분포를 체계적으로 분석하기 위한 연구는 지하 광물자원에 대한 정보 또는 지상의 구조물에 대한 안전성 평가에 대단히 중요한 역할을 한다. 본 논문은 탄성파를 이용하여 얻어진 지하 지층구조를 공간자료구조를 활용하여 분석하는 시스템 개발 방법을 제안하고 이와 관련된 사항을 기술하였다. 공간자료구조를 활용하여 지하지층을 인식하는 시스템의 개발은 지질 전문가의 해석을 위한 전처리 시스템으로서 중요한 역할을 할 것이다.