• Journal of the Society of Disaster Information
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• v.17 no.2
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• pp.391-402
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• 2021

Purpose: By categorizing opinions by subject in the safety certification ecosystem, we want to identify weaknesses in system operation and suggest improvement plans so that the safety certification system can have quick resilience against future variability. Method: Through literature research and data analysis, similar domestic and foreign safety certifications and related cases, as well as the current status of international standards and national standards, etc. were confirmed, and a fact-finding survey was conducted for each stakeholder in the safety certification ecosystem, and problem types and improvement measures were established. Result: We conduct a fact-finding survey of the overall system, such as quality satisfaction with safety certification target products, obstacles in the development, manufacturing and use process, and safety certification-related improvements, targeting workplaces that manufacture, import or use safety certification target machines By discovering and categorizing problems and weaknesses in system operation, detailed implementation tasks were derived to establish improvement directions and improve operability. Conclusion: For the advancement and internationalization of the safety certification system, it is necessary to efficiently carry out the detailed promotion tasks derived from this study. In addition, in order to strengthen the resilience to the variability of the safety certification ecosystem, the operating system of a virtuous cycle structure by improving the mutual relationship between each subject construction is considered important.

• Membrane Journal
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• v.31 no.2
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• pp.87-100
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• 2021

With a striking increase in the level of contamination and subsequent degradations in the environment, detection and monitoring of contaminants in various sites has become a crucial mission in current society. In this review, we have summarized the current research areas in membrane-based colorimetric sensors for trace detection of various molecules. The researches covered in this summary utilize membranes composed of cellulose fibers as sensing platforms and metal nanoparticles or fluorophores as optical reagents. Displaying decent or excellent sensitivity, most of the developed sensors achieve a significant selectivity in the presence of interfering ions. The physical and chemical properties of cellulose membrane platforms can be customized by changing the synthesis method or type of optical reagent used, allowing a wide range of applications possible. Membrane-based sensors are also portable and have great mechanical properties, which enable on-site detection of contaminants. With such superior qualities, membrane-based sensors examined in the researches were used for versatile purposes including quantification of heavy metals in drinking water, trace detection of toxic antibiotics and heavy metals in environmental water samples. Some of the sensors exhibited additional features like antimicrobial ability and recyclability. Lastly, while most of the sensors aimed for a detection enabled by naked eyes through rapid colour change, many of them investigated further detection methods like fluorescence, UV-vis spectroscopy, and RGB colour intensity.

• Journal of the Korean Institute of Gas
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• v.25 no.3
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• pp.27-38
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• 2021

We devised the system to automatically shutdown the boiler and to fundamentally block the harmful gases, including carbon monoxide, into the indoor when the exhaust system swerves: (1) The discharge pressure of the exhaust gas decreases when the exhaust pipe is disconnected. The monitoring system of the exhaust pipe is implemented by measuring the output voltage of APS(Air Pressure Sensor) installed to control the amount of combustion air. (2) The operating software was modified so that when the system recognizes the fault condition of a flue pipe, the boiler control unit displays the fault status on the indoor regulator while shutting down the boiler. In accordance with the ventilation facility standards in the "Rules for Building Equipment Standards" by the Ministry of Land, Infrastructure and Transport, experiments were conducted to ventilate indoor air. When carbon monoxide leaked in worst-case scenario, it was possible to prevent poisoning accidents. However, since 2013, the number of indoor air exchange times has been mitigated from 0.7 to 0.5 times per hour. We observed the concentration exceeding TWA 30 ppm occasionally and thus recommend to reinforce this criterion. In conclusion, if the flue pipe fault detection and the indoor air ventilation system are introduced, carbon monoxide poisoning accidents are expected to decrease significantly. Also when the manufacturing and inspection steps, the correct installation and repair are supplemented with the user's attention in missing flue, it will be served to prevent human casualties from carbon monoxide poisoning.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.31 no.6
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• pp.367-372
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• 2018

Defects in aging infrastructures such as pre-stressed concrete bridges and cable bridges can cause a collapse of the entire structure. Defects, however, are often located inside of the structures that they are not visible from the outside. For example, in PSC bridges, because reinforcement steels are encased by exterior covers, corrosion and void on the reinforcement steel cannot be detected with a visual inspection. Therefore, in this paper, a new non-destructive evaluation(NDE) method that can detect defects inside of structures is presented. The new method utilizes sending of electrical signals, a method often utilized in electrical engineering to detect any discontinuities on power cables. In order to confirm the applicability and accuracy of the method, some experiments were conducted in the laboratory. And to overcome the hardship of conducting experiments on real structures due to their enormous size, simualtions were conudcted using a commercial program, COMSOL. The results of the experiments were analyzed and compared to confirm the accuracy of the simualtions.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.4
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• pp.44-57
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• 2019

Various studies have been conducted to solve traffic congestions in many metropolitan cities through accurate traffic flow prediction. Most studies are based on the assumption that past traffic patterns repeat in the future. Models based on such an assumption fall short in case irregular traffic patterns abruptly occur. Instead, the approaches such as predicting traffic pattern through big data analytics and artificial intelligence have emerged. Specifically, deep learning algorithms such as RNN have been prevalent for tackling the problems of predicting temporal traffic flow as a time series. However, these algorithms do not perform well in terms of long-term prediction. In this paper, we take into account various external factors that may affect the traffic flows. We model the correlation between the multi-dimensional context information with temporal traffic speed pattern using deep neural networks. Our model trained with the traffic data from TOPIS system by Seoul, Korea can predict traffic speed on a specific date with the accuracy reaching nearly 90%. We expect that the accuracy can be improved further by taking into account additional factors such as accidents and constructions for the prediction.

• Journal of the Korean Society of Marine Environment & Safety
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• v.24 no.7
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• pp.870-874
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• 2018

In the worst maritime accidents, people should abandon ship, but ship structures are narrow and complex and operation takes place on rough seas, so escape is not easy. In particular, passengers on cruise ships are untrained and varied, making evacuation prospects worse. In such a case, the evacuation management of the crew plays a very important role. If a rescuer enters a ship at distress and conducts rescue activities, which zones represent the most effective entry should be examined. Generally, crew and rescuers take the shortest route, but if an accident occurs along the shortest route, it is necessary to select the second-best alternative. To solve this situation, this study aims to calculate evacuation routes using Q-Learning of Reinforcement Learning, which is a machine learning technique. Reinforcement learning is one of the most important functions of artificial intelligence and is currently used in many fields. Most evacuation analysis programs developed so far use the shortest path search method. For this reason, this study explored optimal paths using reinforcement learning. In the future, machine learning techniques will be applicable to various marine-related industries for such purposes as the selection of optimal routes for autonomous vessels and risk avoidance.

• Korean Journal of Remote Sensing
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• v.35 no.2
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• pp.299-316
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• 2019

The purpose of this study was to analyze landslide susceptibility in the Pyeongchang area using Weight of Evidence (WOE) and Evidential Belief Function (EBF) as probability models and Artificial Neural Networks (ANN) as a machine learning model in a geographic information system (GIS). This study examined the widespread shallow landslides triggered by heavy rainfall during Typhoon Ewiniar in 2006, which caused serious property damage and significant loss of life. For the landslide susceptibility mapping, 3,955 landslide occurrences were detected using aerial photographs, and environmental spatial data such as terrain, geology, soil, forest, and land use were collected and constructed in a spatial database. Seventeen factors that could affect landsliding were extracted from the spatial database. All landslides were randomly separated into two datasets, a training set (50%) and validation set (50%), to establish and validate the EBF, WOE, and ANN models. According to the validation results of the area under the curve (AUC) method, the accuracy was 74.73%, 75.03%, and 70.87% for WOE, EBF, and ANN, respectively. The EBF model had the highest accuracy. However, all models had predictive accuracy exceeding 70%, the level that is effective for landslide susceptibility mapping. These models can be applied to predict landslide susceptibility in an area where landslides have not occurred previously based on the relationships between landslide and environmental factors. This susceptibility map can help reduce landslide risk, provide guidance for policy and land use development, and save time and expense for landslide hazard prevention. In the future, more generalized models should be developed by applying landslide susceptibility mapping in various areas.

• Korean Chemical Engineering Research
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• v.56 no.6
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• pp.901-908
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• 2018

Graphite is used as a sample anode active material. However, since the maximum theoretical capacity is limited to $372mA\;h\;g^{-1}$, a new anode active material is required for the development of a high capacity lithium ion battery. The maximum theoretical capacity of Si is $4200mA\;h\;g^{-1}$, which is higher than that of graphite. However, it is not suitable for direct application to the anode active material because it has a volume expansion of 400%. In order to minimize the decrease of the discharge capacity due to the volume expansion, the Si was pulverized by the dry method to reduce the mechanical stress and the volume change of the reaction phase, and the change of the volume was suppressed by coating the carbon layers to the particle size controlled Si particles. And carbon fiber is grown like a thread on the particle surface to control secondary volume expansion and improve electrical conductivity. The physical and chemical properties of the materials were measured by XRD, SEM and TEM, and their electrochemical properties were evaluated. In this study, we have investigated the synthesis method that can be used as anode active material by improving cycle characteristics of Si.

• Particle and aerosol research
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• v.14 no.4
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• pp.97-105
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• 2018

Recently, people's interest in particulate matter (PM) has been increasing, due to its hazardous health effects. The purpose of this study was to investigate the concentrations and as well as the inhaled weight of PM, correlated with person's heart rate in subway, bus, vehicle and bicycle in the major public transportation (Sadang - Jamsil and Nowon - Dongdaemun) in Seoul. The concentration of $PM_{10}$ and $PM_{2.5}$ were measured from each of transportation means and calculated the average concentrations which were 87.2 and $57.8{\mu}g/m^3$ for subway, 62.8 and $42.5{\mu}g/m^3$ for vehicle, 61.5 and $36.8{\mu}g/m^3$ for bus and 53.0 and $29.4{\mu}g/m^3$ for bicycle in $PM_{10}$ and $PM_{2.5}$ respectively. Inhalation dose for $PM_{10}$ and $PM_{2.5}$ were estimated at 248.1 and $139.4{\mu}g$ for bicycle, 56.7 and $39.3{\mu}g$ for vehicle, 49.4 and $29.9{\mu}g$ for bus and 44.3 and $29.1{\mu}g$ for subway, respectively. Even though subway had the highest concentration, the highest inhalation dose was the bicycle. It was due to the long travel time-exposure and breathing rate which leads to maximum of $PM_{10}$ 5.6 and $PM_{2.5}$ with 4.8 times inhalation dose comparing with other modes of transportation. With regards to future studies, the amount of inhalation in each transportation means should be considered in risk assessments of PM.

• Tunnel and Underground Space
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• v.28 no.6
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• pp.609-619
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• 2018

This study was carried out at a local limestone mine to analyze the ventilation efficiency of the shaft equipped with a main fan. The results show that its ventilation efficiency is clearly verified for the natural as well as the mechanical ventilation. The airflow rate of $11.7m^3/s$ was induced by the natural ventilation force and the maximum quantity is almost same as the airflow rate estimated by monitoring the average temperatures in the upcast and downcast air columns. Meanwhile, the airflow rate exhausted by the main fan through the shaft was $20.3{\sim}24.8m^3/s$; variation of the quantity was caused by the upward shift of the mine ventilation characteristic curve due to the frequent movement of the equipment. This indicates efforts are required to reduce the ventilation resistance and raise the quantity supplied by the main fan. The turbulent diffusion coefficients along the 1912 m long airway from the portal to the shaft bottom was estimated to be $15m^2/s$ and $18m^2/s$. Since these higher coefficients imply that contaminants will be dispersed at a faster velocity than the airflow, prompt exhaust method should be planned for the effective air quality control. The ventilation shaft and main fan are definitely what local limestone mines inevitably need for better working environment and sustainable development.