• Journal of the Korea Safety Management & Science
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• v.15 no.3
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• pp.93-103
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• 2013

In recently, a growing concern for the health of urban residents increased interests in a variety of outdoor activities simply be done in terms of cost and time. They are specially interested in low-impact and safe exercises around residential or working area. Walking is the one of easily doing exercise in daytime or nighttime near residential area. The sidewalks of boulevard near the residential area is the best place for exercise because of easy access and the green space with roadside trees. However, if the nighttime is not guaranteed the proper lighting condition, the possibility of exposure to crime and the threat to pedestrian safety can be increased. Because roadside trees are one of the potential obstacle for lighting condition, supplementary lightings are important to mitigate interruption for safety. To meet such a need, the purpose of this study is to propose a simulation approach which improves lighting condition on sidewalks of boulevard with variety of roadside trees. To do so, the simulation approach is applied for analyzing the interrupted condition by classified five standard types of roadside trees considering the growth of them and finding optimal layout of supplementary luminaires by lighting types. The results of this approach shows that it is useful for assessing the safety of pedestrian in nighttime.

• Korean Journal of Construction Engineering and Management
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• v.19 no.6
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• pp.34-45
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• 2018

Nuclear power plant(NPP) is a large-sacle national infrastructure with total project cost of 77 billion dollars and period of 10 years or more. Moreover, since it is operated over 60 years, NPP is a facility closely related to national economy and public safety. Therefore, accurate information and consistent physical configuration should be maintained to enable accurate and economical decision making in NPP project process such as design, construction, operation, and decommission. Since NPP industry is more complicate and regulated than other industries, the importance of configuration management(CM) has been widely recognized in the early days. However, there were limitations in implementing systematic CM due to unclear purpose and subject. Therefore, this paper suggests a room-based database for CM in NPP reflects design requirements and facility configuration information.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.1243-1244
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• 2022

In recent years, the growing interest in off-site construction has led to factories scaling up their manufacturing and production processes in the construction sector. Consequently, continuous large-scale site monitoring in low-variability environments, such as prefabricated components production plants (precast concrete production), has gained increasing importance. Although many studies on computer vision-based site monitoring have been conducted, challenges for deploying this technology for large-scale field applications still remain. One of the issues is collecting and transmitting vast amounts of video data. Continuous site monitoring systems are based on real-time video data collection and analysis, which requires excessive computational resources and network traffic. In addition, it is difficult to integrate various object information with different sizes and scales into a single scene. Various sizes and types of objects (e.g., workers, heavy equipment, and materials) exist in a plant production environment, and these objects should be detected simultaneously for effective site monitoring. However, with the existing object detection algorithms, it is difficult to simultaneously detect objects with significant differences in size because collecting and training massive amounts of object image data with various scales is necessary. This study thus developed a large-scale site monitoring system using edge computing and a small-object detection system to solve these problems. Edge computing is a distributed information technology architecture wherein the image or video data is processed near the originating source, not on a centralized server or cloud. By inferring information from the AI computing module equipped with CCTVs and communicating only the processed information with the server, it is possible to reduce excessive network traffic. Small-object detection is an innovative method to detect different-sized objects by cropping the raw image and setting the appropriate number of rows and columns for image splitting based on the target object size. This enables the detection of small objects from cropped and magnified images. The detected small objects can then be expressed in the original image. In the inference process, this study used the YOLO-v5 algorithm, known for its fast processing speed and widely used for real-time object detection. This method could effectively detect large and even small objects that were difficult to detect with the existing object detection algorithms. When the large-scale site monitoring system was tested, it performed well in detecting small objects, such as workers in a large-scale view of construction sites, which were inaccurately detected by the existing algorithms. Our next goal is to incorporate various safety monitoring and risk analysis algorithms into this system, such as collision risk estimation, based on the time-to-collision concept, enabling the optimization of safety routes by accumulating workers' paths and inferring the risky areas based on workers' trajectory patterns. Through such developments, this continuous large-scale site monitoring system can guide a construction plant's safety management system more effectively.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.20 no.3
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• pp.339-347
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• 2022

Major accidents at nuclear power plants generate huge amounts of radioactive waste in a short period of time over a wide area outside the plant boundary. Therefore, extraordinary efforts are required for safe management of the waste. A well-established remediation plan including radioactive waste management that is prepared in advance will minimize the impact on the public and environment. In Korea, however, only limited plans exist to systematically manage this type of off-site radioactive waste generating event. In this study, we developed basic strategies for off-site radioactive waste management based on recommendations from the IAEA (International Atomic Energy Agency) and NCRP (National Council on Radiation Protection and Measurements), experiences from the Fukushima Daiichi accident in Japan, and a review of the national radioactive waste management system in Korea. These strategies included the assignment of roles and responsibilities, development of management methodologies, securement of storage capacities, preparation for the use of existing infrastructure, assurance of information transparency, and establishment of cooperative measures with international organizations.

• Food Science of Animal Resources
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• v.32 no.4
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• pp.389-395
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• 2012

Cloned animals are a result of asexual reproduction of animals using somatic cell nuclear transfer. Ever since the first report of a cloned sheep 'Dolly' produced by SCNT, increasing numbers of livestock, such as bovine and swine clones, have been generated worldwide. Foods derived from cloned animals have not been produced yet. However, the food safety of cloned animals has provoked controversy. The EU Food Safety Authority and U.S. Food and Drug Administration announced that milk and meat from cloned and non-cloned animals have no difference regarding food safety. However, food derived from cloned animals is considered unsuitable for eating vaguely. Moreover, there were scant information about cloned animals in Korea. Therefore, we surveyed the number of cloned animals worldwide including Korea and summarized the reports for cloned animals and discussed predictable problems.

• Proceedings of the National Institute of Ecology of the Republic of Korea
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• v.1 no.1
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• pp.74-82
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• 2020

Predictions of suitable habitat areas can provide important information pertaining to the risk assessment and management of alien plants at early stage of their establishment. Here, we predict the invasion potential of Muhlenbergia capillaris (pink muhly) in South Korea using five bioclimatic variables. We adopt four models (generalized linear model, generalized additive model, random forest (RF), and artificial neural network) for projection based on 630 presence and 600 pseudo-absence data points. The RF model yielded the highest performance. The presence probability of M. capillaris was highest within an annual temperature range of 12 to 24℃ and with precipitation from 800 to 1,300 mm. The occurrence of M. capillaris was positively associated with the precipitation of the driest quarter. The projection map showed that suitable areas for M. capillaris are mainly concentrated in the southern coastal regions of South Korea, where temperatures and precipitation are higher than in other regions, especially in the winter season. We can conclude that M. capillaris is not considered to be invasive based on a habitat suitability map. However, there is a possibility that rising temperatures and increasing precipitation levels in winter can accelerate the expansion of this plant on the Korean Peninsula.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.6
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• pp.95-103
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• 2022

Quick and accurate understanding of the situation in a severe accident is essential for conducting the appropriate accident management and response using the accident diagnosis information. This study employed deep learning technology to diagnose severe accidents through the major safety parameters transferred from a nuclear power plant (NPP) to AtomCARE. After selecting the major accident scenarios to consider, a learning database was established for particular scenarios affiliated with major scenarios by performing a large number of severe accident analyses using MAAP5 code. The severe accident diagnosis technology, which classifies detailed accident scenarios using the major safety parameters from NPPs, was developed by training it with the established database . Verification and validation were conducted by blind test and principal component analysis. The technology developed in this study is expected to be extended and applied to all severe accident scenarios and be utilized as a base technology for quick and accurate severe accident diagnosis.

• Journal of the Society of Disaster Information
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• v.3 no.2
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• pp.119-128
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• 2007

A bioterrorism attack is the deliberate release of viruses, bacteria, or other agents used to cause illness or death in people, animals, or plant. These agents are found in nature, but it is possible that they could be changed to increase their ability to cause disease, make them resistant to current medicines, or to increase their ability to be spread into the environment. Terrorists may use biological agents because these agents can be extremely difficult to detect and do not cause illness for several days. Some bioterrorism agents, like smallpox virus, can spread from person to person, like anthrax, can not. From these agents, we discussed the characteristics of biological agents and national safety regulation on the weapons of mass destruction including bioterrorism.

• Journal of the Korean Society of Safety
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• v.28 no.1
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• pp.158-163
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• 2013

While job stress evaluations are reported in the recent surveys upon the nuclear power plants(NPPs), any significant advance in the types of questionnaires is not currently found. There are limitations to their usefulness as analytic tools for the management of safety resources in NPPs. Data mining(DM) has emerged as one of the key features for data computing and analysis to conduct a survey analysis. There are still limitations to its capability such as dimensionality associated with many survey questions and quality of information. Even though some survey methods may have significant advantages, often these methods do not provide enough evidence of causal relationships and the statistical inferences among a large number of input factors and responses. In order to address these limitations on the data computing and analysis capabilities, we propose an advanced procedure of survey analysis incorporating the DM method into a statistical analysis. The DM method can reduce dimensionality of risk factors, but DM method may not discuss the robustness of solutions, either by considering data preprocesses for outliers and missing values, or by considering uncontrollable noise factors. We propose three steps to address these limitations. The first step shows data mining with response surface method(RSM), to deal with specific situations by creating a new method called response surface data mining(RSDM). The second step follows the RSDM with detailed statistical relationships between the risk factors and the response of interest, and shows the demonstration the proposed RSDM can effectively find significant physical, psycho-social, and environmental risk factors by reducing the dimensionality with the process providing detailed statistical inferences. The final step suggest a robust stress management system which effectively manage job stress of the workers in NPPs as a part of a safety resource management using the surrogate variable concept.

• Nuclear Engineering and Technology
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• v.45 no.2
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• pp.125-140
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• 2013

This paper aims to give an overview of the methods to inherently prevent human errors and to effectively mitigate the consequences of such errors by securing defense-in-depth during plant management through the advanced man-machine interface system (MMIS). It is needless to stress the significance of human error reduction during an accident in nuclear power plants (NPPs). Unexpected shutdowns caused by human errors not only threaten nuclear safety but also make public acceptance of nuclear power extremely lower. We have to recognize there must be the possibility of human errors occurring since humans are not essentially perfect particularly under stressful conditions. However, we have the opportunity to improve such a situation through advanced information and communication technologies on the basis of lessons learned from our experiences. As important lessons, authors explained key issues associated with automation, man-machine interface, operator support systems, and procedures. Upon this investigation, we outlined the concept and technical factors to develop advanced automation, operation and maintenance support systems, and computer-based procedures using wired/wireless technology. It should be noted that the ultimate responsibility of nuclear safety obviously belongs to humans not to machines. Therefore, safety culture including education and training, which is a kind of organizational factor, should be emphasized as well. In regard to safety culture for human error reduction, several issues that we are facing these days were described. We expect the ideas of the advanced MMIS proposed in this paper to lead in the future direction of related researches and finally supplement the safety of NPPs.