• Molecular & Cellular Toxicology
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• v.2 no.2
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• pp.89-96
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• 2006

The detection of many synthetic chemicals used in industry that may pose a genetic hazard in our environment is of great concern at present. Since these substances are not limited to the original products, and enter the environment, they have become widespread environmental pollutants, thus leading to a variety of chemicals that possibly threaten the public health. In this respect, to regulate and to evaluate the chemical hazard will be important to environment and human health. The clastogenicity of 11 synthetic chemicals was evaluated in Chinese hamster lung fibroblast cells in vitro. 1-Chloro-3-bromopropane CAS No. 109-70-6) induced chromosomal aberrations with significance at the concentration of $185.0\;{\mu}g/mL\;and\;1,600\;{\mu}g/mL$ both in the presence and absence of metabolic activation system, respectively. Triphenyl phosphite (CAS No. 101-02-0), which is one of the most cytotoxic chemical among 11 chemicals tested revealed no clastogenicity in the range of $95.0-4.9\;{\mu}g/mL$ both in the presence and absence of metabolic activation system. From the results of chromosomal aberration assay with 11 synthetic chemicals in Chinese hamster lung cells in vitro, 1-chloro-3-bromopropane revealed a positive clastogenic result in this study.

• Journal of the Korean Society of Hazard Mitigation
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• v.5 no.2 s.17
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• pp.1-8
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• 2005

Microwave tomographic imaging technology using a bi-focusing operator has been developed in order to detect the internal voids/objects inside concrete structures. The imaging system consists of several cylindrical or planar array antennas for transmitting and receiving signals, and a numerical focusing operator is applied to the external signals both in transmitting and in receiving fields. In this study, the authors developed 3-dimensional (3D) electromagnetic (EM) imaging technology to detect such damage and to identify exact location of steel rebars or dowel. The authors have developed sub-surface two-dimensional (2D) imaging technique using tomographic antenna array in previous works. In this study, extending the earlier analytical and experimental works on 2D image reconstruction, a 3D microwave imaging system using tomographic antenna way was developed, and multi-frequency technique was applied to improve quality of the reconstructed image and to reduce background noises. Numerical simulation demonstrated that a sub-surface image can be successfully reconstructed by using the proposed tomographic imaging technology. For the experimental verification, a prototype antenna array was fabricated and tested on a concrete specimen.

• Journal of the Korean Society of Hazard Mitigation
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• v.11 no.1
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• pp.23-27
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• 2011

Due to the rapid development of construction technology with effective land utilization in this nation, many tunnels were and are being built across the country. However, the smoke and the heat generated from tunnel fire are the most important critical factors which may results in both massive personal injury and property damage, especially, due to the closed surrounding of the tunnel. Considering this particular nature of the tunnels, this study aims to install a fire detection system using an optic fiber cable to measure the temperature changes, compare, and analyze the resulted values with the times of temperature changes of the sensor by performing fire simulations under the same condition as a real fire test. From the results, it has been found that the temperature sensor detects a fire occurrence and generates an alarm within one minute after ignition for both a real fire test and a fire simulation alike, and also that the characteristics of temperature changes of the sensor has close relations with the speeds of the currents inside the tunnel. In addition, considering the tunnel fires can affect the evacuation efficiency and the fire extinguishing activities of the fire brigade inside the tunnel, the temperature sensor must be able to search and find the locations and directions of the fires correctly.

• Structural Monitoring and Maintenance
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• v.7 no.1
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• pp.59-67
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• 2020

This study aims to develop the fuzzy risk assessment model of the debris flow to verify the accuracy of risk assessment in order to help related organizations reduce losses caused by landslides. In this study, actual cases of landslides that occurred are utilized as the database. The established models help us assess the occurrence of debris flows using computed indicators, and to verify the model errors. In addition, comparisons are made between the models to determine the best one to use in practical applications. The results prove that the risk assessment model systems are quite suitable for debris flow risk assessment. The reproduction consequences of highlight point discovery are shown in highlight guide coordinating toward discover steady and coordinating component focuses and effectively identified utilizing these two systems, by examining the variety in the distinguished highlights and the element coordinating.

• International journal of steel structures
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• v.18 no.4
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• pp.1200-1209
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• 2018

In this study, a probabilistic framework of the damage assessment of pipelines subjected to extreme hazard scenario was developed to mitigate the risk and enhance design reliability. Nonlinear 3D finite element models of T-joint systems were developed based on experimental tests with respect to leakage detection of black iron piping systems, and a damage assessment analysis of the vulnerability of their components according to nominal pipe size, coupling type, and wall thickness under seismic wave propagations was performed. The analysis results showed the 2-inch schedule 40 threaded T-joint system to be more fragile than the others with respect to the nominal pipe sizes. As for the coupling types, the data indicated that the probability of failure of the threaded T-joint coupling was significantly higher than that of the grooved type. Finally, the seismic capacity of the schedule 40 wall thickness was weaker than that of schedule 10 in the 4-inch grooved coupling, due to the difference in the prohibition of energy dissipation. Therefore, this assessment can contribute to the damage detection and financial losses due to failure of the joint piping system in a liquid pipeline, prior to the decision-making.

• International journal of advanced smart convergence
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• v.9 no.1
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• pp.63-69
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• 2020

The rapid development in modern industrialization pollutant the water and atmospheric air across the globe that have a major impact on the human and livings health. In worldwide, every country government increasing the importance to improve the outdoor air pollution monitoring and control to provide quality of life and prevent the citizens and livings life from hazard disease. We proposed the environmental dust level detection method for outdoor facilities using sensor fusion technology to measure precise micro-dust level and monitor in realtime. In this proposed approach use the camera sensor and commercial dust level sensor data to predict the micro-dust level with data fusion method. The camera sensor based dust level detection uses the optical flow based machine learning method to detect the dust level and then fused with commercial dust level sensor data to predict the precise micro-dust level of the outdoor facilities and send the dust level informations to the outdoor air pollution monitoring system. The proposed method implemented on raspberry pi based open-source hardware with Internet-of-Things (IoT) framework and evaluated the performance of the system in realtime. The experimental results confirm that the proposed micro-dust level detection is precise and reliable in sensing the air dust and pollution, which helps to indicate the change in the air pollution more precisely than the commercial sensor based method in some extent.

• Journal of the Korean Institute of Intelligent Systems
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• v.9 no.4
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• pp.426-435
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• 1999

A high impedance fault(HIF) is one of the serious problems facing the electric utility industry today. Because of the high impedance of a downed conductor under some conditions these faults are not easily detected by over-current based protection devices and can cause fires and personal hazard. In this paper a new method for detection of HIF which uses adaptive neuro-fuzzy inference system (ANFIS) is proposed. Since arcing fault current shows different changes during high and low voltage portion of conductor voltage waveform we firstly divided one cycle of fault current into equal spanned four data windows according to the mangnitude of conductor voltage. Fast fourier transform(FFT) is applied to each data window and the frequency spectrum of current waveform are chosen asinputs of ANFIS after input selection method is preprocessed. Using staged fault and normal data ANFIS is trained to discriminate between normal and HIF status by hybrid learning algorithm. This algorithm adapted gradient descent and least square method and shows rapid convergence speed and improved convergence error. The proposed method represent good performance when applied to staged fault data and HIFLL(high impedance like load)such as arc-welder.

• Environmental Mutagens and Carcinogens
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• v.21 no.1
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• pp.14-22
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• 2001

The detection of many synthetic chemicals used in industry that may pose a genetic hazard in our environment is of great concern at present. In this respect, administrative authorities has great concern to regulate and to evaluate the chemical hazard to environment and human health. The clastogenicity of 28 synthetic chemicals was evaluated in Chinese hamster lung fibroblast cells in vitro. Glycidylacrylate which is one of the most cytotoxic chemical among 28 chemicals tested revealed clastogenicity in the range of 0.31-1.25 $\mu\textrm{g}$/$m\ell$ both in the presence and absence of metabolic activation system. Neopentyl glycol (340-1360 $\mu\textrm{g}$/$m\ell$) also revealed weak positive result both in the presence and absence of metabolic activation system. Cyanoguanidine (/$420.5-841 $\mu\textrm{g}$m\ell$) and N-butylchloride ($231.5-926 $\mu\textrm{g}$/m\ell$) revealed weak positive result only in the absence of S-9 metabolic activation system. Nevertheless total aberration percentages of N-butylchloride in the presence of metabolic activation system, and 3,4＇-dichlorobenztrifluoride in the absence of S-9 metabolic activation revealed above 5% aberration, there is no statistical significance. From the results of chromosomal aberration assay with 28 synthetic chemicals in Chinese hamster lung cells, glycidylacrylate (CAS No. 106-90-0), neopentyl glycol (CAS No. 126-30-7), N-butyl chloride (CAS No. 109-69-3) and cyanoguanidine (CAS No. 461-58-5) revealed positive clastogenic results in this study.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.321-323
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• 2015

Monitoring crane motion in real time is the first step to identifying and mitigating crane-related hazards on construction sites. However, no accurate and reliable crane motion capturing technique is available to serve this purpose. The objective of this research is to explore a method for real-time crane motion capturing and investigate an approach for assisting hazard detection. To achieve this goal, this research employed various techniques including: 1) a sensor-based method that accurately, reliably, and comprehensively captures crane motions in real-time; 2) computationally efficient algorithms for fusing and processing sensing data (e.g., distance, angle, acceleration) from different types of sensors; 3) an approach that integrates crane motion data with known as-is environment data to detect hazards associated with lifting tasks; and 4) a strategy that effectively presents crane operator with crane motion information and warn them with potential hazards. A prototype system was developed and tested on a real crane in a field environment. The results show that the system is able to continuously and accurately monitor crane motion in real-time.

• Journal of the Korea Society for Simulation
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• v.33 no.3
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• pp.13-26
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• 2024

The CBRN(Chemical, Biological, Radiological, and Nuclear) hazard prediction model is a system that supports commanders in making better decisions by creating contamination distribution and damage prediction areas based on the weapons used, terrain, and weather information in the events of biochemical and radiological accidents. NBC_RAMS(Nuclear, Biological and Chemical Reporting And Modeling S/W System) developed by ADD (Agency for Defense Development) is used not only supporting for decision making plan for various military operations and exercises but also for post analyzing CBRN related events. With the NBC_RAMS's core engine, we introduced a CBR hazard assessment scenario analysis system that can generate contaminant distribution prediction results reflecting various CBR scenarios, and described how to apply it in specific purposes in terms of input information, meteorological data, land data with land coverage and DEM, and building data with pologon form. As a practical use case, a technology development case is addressed that tracks the origin location of contaminant source with artificial intelligence and a technology that selects the optimal location of a CBR detection sensor with score data by analyzing large amounts of data generated using the CBRN scenario analysis system. Through this system, it is possible to generate AI-specialized CBRN related to training and analysis data and support planning of operation and exercise by predicting battle field.