• 대한안전경영과학회:학술대회논문집
• /
• 대한안전경영과학회 2010년도 추계학술대회
• /
• pp.41-61
• /
• 2010

With increasing the quality of life in proportion to the national income, we have had cars as more convenient and safe means of transportation for a long time. The more we have the benefits from cars, the more seriously we should consider problems such as the destruction of the environment by air pollution, traffic accidents, parking problems, traffic congestion, etc. as social cost caused by the increase of cars. Among them, the traffic accidents are very serious, especially the accidents of the business cars occurs five times more than those of the private cars. Therefore if we analyze the cases of the various kinds of syst.em, test the results and apply them to business cars, we will reduce the traffic accidents of business cars.

• 한국정밀공학회지
• /
• 제33권9호
• /
• pp.761-768
• /
• 2016

Weight bearing is effective during rehabilitation of gait, in the elderly and disabled people. Various training devices using weight bearing function were developed along with treadmill walking; however, no device has been developed in conjunction to walking on the ground. Here, we designed a rail type frame of a gait rehabilitation system for body-weight support (BWS) function, and analyzed its mechanical safety in the static weight bearing condition of a vertical axis. Computational simulations were performed to analyze structure of the driving parts, which are connected with a rail and driving rollers and the lower plate of the BWS. Structural analyses showed the drivers and BWS were safe, when simulated at 135kg weight under static conditions. Thus, this rail type rehabilitation system can be used for gait training of the elderly and disabled.

• Safety and Health at Work
• /
• 제8권2호
• /
• pp.175-182
• /
• 2017

Background: With the recent rapid industrialization, occupational safety and health (OSH) has become an important issue in all industrial and human activities. However, incidents of injuries and fatality rates in the Ghanaian industry sector continue to increase. Despite this increase, there is no evidence regarding the element of OSH management in transport activities in Ghanaian industries. Thus, this study aims to examine the perceptions regarding the importance of safety and health in work-related transport activities in Ghanaian industries. Methods: A survey data collection technique was used to gather information on best safety practices over a 5-month period. We randomly selected 298 respondents from industries to answer structured questionnaires. The respondents included drivers, transport managers, and safety engineers. Standard multiple regression model and Pearson product-movement correlation were used to performed the analysis. Results: The result shows that for interventions to improve safety and health, concentration has been on drivers' safety practice with less attention to safe driving environments and vehicle usage. Additionally, the respondents are aware of the importance of OSH in transport activities, but the level of integration does not measure up to the standard to reduce operational accidents and injuries. Finally, strong commitment to changing unsafe practices at all levels of operations appears to be the effective way to improve safety situations. Conclusion: OSH culture is not fully complied in industries transport activities. This study, therefore, supports the use of safety seminars and training sessions for industry workers responsible for transport operations for better integration of safety standards.

• 한국ITS학회 논문지
• /
• 제19권2호
• /
• pp.89-103
• /
• 2020

고령화 사회에 접어들면서 거동이 어려운 장애인과 고령자의 개인 교통수단에 대한 수요가 증가하고 있다. 실제로 2017년 기준 전국 전동보장구 보급수는 9만여 대로 지속해서 증가하는 추세다. 하지만 장애인 및 고령자의 판단 능력과 조정 능력은 정상인보다 상대적으로 차이가 있는 관계로 주행 중 사고 발생의 가능성이 크다. 다양한 사고의 원인 중 하나는 도로 노면상태의 불균형으로 인해 개인 이동 수단 조향 제어의 간섭이다. 본 논문에서는 이 같은 사고를 예방하고자 도로 노면 상태를 고속으로 인지할 수 있는 암호화 형식 의미론적 분할 알고리즘을 소개한다. 이를 위하여 도로 노면 파손이 포함된 1,500여 장의 학습용 데이터와 150여 장의 테스트용 데이터를 새롭게 구성하였다. 그리고 이를 활용하여 기존의 Encoder와 Decoder 단계로 구성된 Auto-encoder 방식과 달리 Encoder 단계로 이루어진 심층 신경망을 제안하였다. 이 심층 신경망은 기존의 방식과 비교했을 때 평균 정확도(Mean Accuracy)는 4.45% 증가하였고 파라미터는 59.2% 감소하였으며 연산 속도는 11.9% 향상되었다. 이 같은 고속 알고리즘을 활용하여 안전한 개인 이동 수단이 확대 적용되길 기대한다.