Purpose: This study collects basic data on the awareness of evacuation methods and evacuation facilities in the event of a radiological disaster of residents living in the emergency planning zone. Method: The residents of emergency planning zone were sampled using a random sampling method. A 1:1 interview was conducted using a structured questionnaire, and statistical analysis was performed using the minitab program. Result: First, the survey subjects showed a relatively low and negative awareness of the local government's work on radioactive disasters. Second, in terms of resident safety education, they had little experience in education, but they felt it was necessary and wanted education on evacuation methods, action tips, and the location of relief centers. Third, the location of the relief centers related to radioactive disasters was not well known, and there were many responses that they did not receive any guidance, and that they would be with their families when using the relief centers. Satisfaction levels were generally low with regard to the relief facilities. Fourth, the necessary priorities in preparation for radioactive disasters were education and training for radioactive disasters, facility supplementation, and supply of protective chemicals. Conclusion: The residents of emergency planning zone perceived the policies and tasks of the government or local governments relatively negatively in preparation for the occurrence of radioactive disasters, and their satisfaction was low. Regarding the matters pointed out as a priority, the government and local governments should publicize and educate the residents of accurate information and policies on radioactive disasters.
There are cases where the mobility impaired have difficulty moving from the moment they leave the house. If guardians also do not have time to entrust their families, who are socially disadvantaged, to a shelter, the guardian has no choice but to check directly in order to know the location of the guardian. The AI home care solution was designed to relieve the anxiety and labor of caregivers and to provide convenience for protection facility officials and users. If more facilities distribute and use services free of charge to non-profit foundations and protective facilities, the concern of guardians will be reduced, and the burden of facility officials who have to manage facility users will be reduced. In this paper, we provide emergency notification services to guardians in the event of an emergency as well as location and status alarms for guardians, which are all data related to movement, in consideration of the mobility vulnerable. Furthermore, it is necessary to provide a service function that recommends the optimal route using a navigation function to ease the convenience and burden of facility officials. It is necessary to alleviate anxiety by providing necessary information to the guardian, such as the location of the shuttle used by the mobile weak and the time of getting on and off. In addition, while providing services for free, the goal is to improve the quality of service for facility managers and the quality of service for the mobility weak.
KSCE Journal of Civil and Environmental Engineering Research
/
v.43
no.5
/
pp.667-674
/
2023
In the event of a disaster occurring within a building, the prompt and efficient evacuation and rescue of occupants within the building becomes the foremost priority to minimize casualties. For the purpose of such rescue operations, it is essential to ascertain the distribution of individuals within the building. Nevertheless, there is a primary dependence on accounts provided by pertinent individuals like building proprietors or security staff, alongside fundamental data encompassing floor dimensions and maximum capacity. Consequently, accurate determination of the number of occupants within the building holds paramount significance in reducing uncertainties at the site and facilitating effective rescue activities during the golden hour. This research introduces a methodology employing computer vision algorithms to count the number of occupants within distinct building locations based on images captured by installed multiple CCTV cameras. The counting methodology consists of three stages: (1) establishing virtual Lines of Interest (LOI) for each camera to construct a multi-camera network environment, (2) detecting and tracking people within the monitoring area using deep learning, and (3) aggregating counts across the multi-camera network. The proposed methodology was validated through experiments conducted in a five-story building with the average accurary of 89.9% and the average MAE of 0.178 and RMSE of 0.339, and the advantages of using multiple cameras for occupant counting were explained. This paper showed the potential of the proposed methodology for more effective and timely disaster management through common surveillance systems by providing prompt occupancy information.
Currently, the domestic traditional market has not escaped the swamp of stagnation that began in the early 2000s despite various projects promoted by many related players such as the central government and local governments. In order to overcome the crisis faced by the traditional market, various R&Ds have recently been conducted on how to build a smart traditional market that combines information and communication technologies such as big data analysis, artificial intelligence, and the Internet of Things. This study analyzes various previous studies, users of traditional markets, and application cases of ICT technology in foreign traditional markets since 2012 and proposes a model to build a smart traditional market using ICT technology based on the analysis. The model proposed in this study includes building a traditional market metaverse that can interact with visitors, certifying visits to traditional markets through digital signage with NFC technology, improving accuracy of fire detection functions using IoT and AI technology, developing smartphone apps for market launch information and event notification, and an e-commerce system. If a smart traditional market platform is implemented and operated based on the smart traditional market platform model presented in this study, it will not only draw interest in the traditional market to MZ generation and foreigners, but also contribute to revitalizing the traditional market in the future.
Jongchan Yoon;Suwon Son;Junhyeok Park;Junseong Moon;Jinman Kim
Journal of the Korean GEO-environmental Society
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v.24
no.7
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pp.5-14
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2023
Recently, earthquakes have occurred frequently in worldwide. These earthquakes cause various forms of natural and physical damage. In particular, liquefaction in which the ground shows liquid-like behavior causes great damage to the structure. Accordingly, various liquefaction damage reduction methods are being studied and developed. Therefore, in this study, a method of reducing liquefaction damage in the event of an earthquake applicable to existing structures was studied using the sheet pile method. The 1-G Shaking table test was performed and the ground was constructed with Jumunjin standard sand. A two-story model structure was produced by applying the similitude law, and the input wave applied a sine wave with an acceleration level of 0.6 g and a frequency of 10 Hz. The effect of reducing structure damage according to various embedded depth ratio was analyzed. As a result of the study, the structure settlement when the ground is reinforced by applying the sheet pile method is decreased by about 71% compared to when the ground is not reinforced, and the EDR with minimum settlement is "1". In addition, as the embedded depth ratio is increased, the calculation of the pore water pressure in the ground tends to be delayed due to the sheet pile. Based on these results, the relationship with structural settlement according to the embedded depth ratio is proposed as a relational equation with the graph. The results of this study are expected to be used as basic data in developing sheet pile methods applicable to existing structures in the future.
Yang, Byoung Seon;Choi, Se Mook;Bae, Hyung Joon;Kim, Yoon Sik;Lim, Yong;Kang, Hee Jung;Bae, Do Hee;Choi, Byoung Ho;Lee, Jae Suk;Park, Ji Ae
Korean Journal of Clinical Laboratory Science
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v.54
no.1
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pp.49-60
/
2022
This study attempted to provide the basic data for developing a system to identify the role of medical technologists and ensure an efficient response for quick and accurate diagnostic tests in the COVID-19 era. The research method involved using focus group interviews for a survey and analysis of 15 medical institutions. Eleven sample collection institutions, 10.4 medical technologists, 2.1 minutes of collection time, 5.4 hours of test time, 9,670 tests, 6.2 member test workforce size, and 7 screening center operating institutions were surveyed. The results of the focus group interview analysis revealed that there were no standardized guidelines covering working hours, area, and environment to protect sample collectors and testers in relation to the COVID-19 tests. Also, legal protection measures were insufficient in the event of accidental infections and there were no personnel regulations related to COVID-19. In addition, the professional training of sample collectors and molecular diagnostic testers was required for reliable COVID-19 testing. In conclusion, it is necessary to provide professional education through special test short-term training institutions to cope with emergency infectious diseases such as COVID-19. Legal systems should be put in place to protect the workforce and ensure stability.
Kim, Soo Jun;Kwon, Young Soo;Lee, Keon Haeng;Kim, Hung Soo
KSCE Journal of Civil and Environmental Engineering Research
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v.30
no.2B
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pp.159-167
/
2010
The purpose of this study is to get the adjusted radar rainfalls by ANN(Artificial Neural Network) method. In the case of radar rainfall, it has an advantage of spatial distribution characteristics of rainfall while point rainfall has an advantage at the point. Therefore we adjusted the radar rainfall by ANN method considering the advantages of two rainfalls of radar and point. This study constructed two ANN models of Model I and Model II for radar rainfall adjustment. We collected the three rainfall events and adjusted the radar rainfall for Anseong-cheon basin. The two events were inputted into the Modeland Model to derive the optimum parameters and the rest event was used for validation. The adjusted radar rainfalls by ANN method and the raw radar rainfall were used as the input data of ModClark model which is a semi-distributed model to simulate the runoff. As the results of the simulation, the runoff by raw radar rainfall were overestimated but the peak time and peak runoff from the adjusted rainfall by ANN were well fitted to the observed hydrograph.
KSCE Journal of Civil and Environmental Engineering Research
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v.28
no.5B
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pp.485-493
/
2008
The Artificial Neural Network (ANN) model was suggested for predicting probability of precipitation (PoP) using RDAPS NWP model, observation at AWS and upper-air sounding station. The prediction work was implemented for flood season and the data period is the July, August of 2001 and June of 2002. Neural network input variables (predictors) were composed of geopotential height 500/750/1000 hPa, atmospheric thickness 500-1000 hPa, X & Y-component of wind at 500 hPa, X & Y-component of wind at 750 hPa, wind speed at surface, temperature at 500/750 hPa/surface, mean sea level pressure, 3-hr accumulated precipitation, occurrence of observed precipitation, precipitation accumulated in 6 & 12 hrs previous to RDAPS run, precipitation occurrence in 6 & 12 hrs previous to RDAPS run, relative humidity measured 0 & 12 hrs before RDAPS run, precipitable water measured 0 & 12 hrs before RDAPS run, precipitable water difference in 12 hrs previous to RDAPS run. The suggested ANN has a 3-layer perceptron (multi layer perceptron; MLP) and back-propagation learning algorithm. The result shows that there were 6.8% increase in Hit rate (H), especially 99.2% and 148.1% increase in Threat Score (TS) and Probability of Detection (POD). It illustrates that the suggested ANN model can be a useful tool for predicting rainfall event prediction. The Kuipers Skill Score (KSS) was increased 92.8%, which the ANN model improves the rainfall occurrence prediction over RDAPS.
KSCE Journal of Civil and Environmental Engineering Research
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v.28
no.4B
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pp.383-392
/
2008
It is not always easy to estimate the parameters in hydrologic models due to insufficient hydrologic data when hydraulic structures are designed or water resources plan are established. Therefore, uncertainty analysis are inevitably needed to examine reliability for the estimated results. With regard to this point, this study applies a Bayesian Markov Chain Monte Carlo scheme to the NWS-PC rainfall-runoff model that has been widely used, and a case study is performed in Soyang Dam watershed in Korea. The NWS-PC model is calibrated against observed daily runoff, and thirteen parameters in the model are optimized as well as posterior distributions associated with each parameter are derived. The Bayesian Markov Chain Monte Carlo shows a improved result in terms of statistical performance measures and graphical examination. The patterns of runoff can be influenced by various factors and the Bayesian approaches are capable of translating the uncertainties into parameter uncertainties. One could provide against an unexpected runoff event by utilizing information driven by Bayesian methods. Therefore, the rainfall-runoff analysis coupled with the uncertainty analysis can give us an insight in evaluating flood risk and dam size in a reasonable way.
In this study, an investigation was conducted on the features, events, and processes (FEP) that could impact the long-term safety of the natural barriers constituting high-level radioactive waste geological repositories. The FEP list was developed utilizing the IFEP list 3.0 provided by the Nuclear Energy Agency (NEA) as foundational data, supplemented by geological investigations and research findings from leading countries in this field. A total of 49 FEPs related to the performance of the natural barrier were identified. For each FEP, detailed definitions, classifications, impacts on long-term safety, significance in domestic conditions, and feasibility of quantification were provided. Moreover, based on the compiled FEP list, three scenarios that could affect the long-term safety of the disposal facility were developed. Geological factors affecting the performance of the natural barrier in each scenario were selected and their relationships were visualized. The constructed FEP list and the visualization of interrelated factors in various scenarios are anticipated to provide essential information for selecting and organizing factors that must be considered in the development of mathematical models for quantitatively evaluating the long-term safety of deep geological repositories. In addition, these findings could be effectively utilized in establishing criteria related to the key performance of natural barriers for the confirmation of repository sites.
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