• 분석과학
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• 제33권1호
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• pp.42-48
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• 2020

Bromate is a disinfection by-product generated mainly from the oxidation of bromide during the ozonation and disinfection process in order to remove pathogenic microorganism of drinking water, and classified as a possible human carcinogen by International Agency for Research of Cancer (IARC) and World Health Organization (WHO). For the purpose of determining the trace level concentration of bromate, several sensitive techniques are applied mostly based on suppressed conductivity detection and UV/Visible detection after postcolumn reaction (PCR). In this study, the suppressed conductivity detection method and the PCR-UV/Visible detection method through the triiodide reaction were compared to analyze the trace bromate in water samples and estimated for the availability of these analytical methods. In addtion, the state-of-the-art techniques was applied for the determination of trace level bromate in various water matrices, i.e., soft drinking water, hard drinking water, mineral water, swimming pool water, and raw water. In comparison of two analytical methods, it was found that the conductivity detection had the suitable advantage to simultaneously analyze bromate and inorganic anions, however, the bromate might not be precisely quantified due to the matrix effect especially by chloride ion. On the other hand, the trace bromate was analyzed effectively by the method of PCR-UV/Visible detection through triiodide reaction to satisfactorily minimize the matrix interference of chloride ion in various water samples, showing the good linearity and reproducibility. Furthermore, the method detection limit (MDL) and recovery were 0.161 ㎍/L and 101.0-108.1 %, respectively, with a better availability compared to conductivity detection.

• Journal of Preventive Medicine and Public Health
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• 제41권4호
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• pp.214-218
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• 2008

Bioterrorism events have worldwide impacts, not only in terms of security and public health policy, but also in other related sectors. Many countries, including Korea, have set up new administrative and operational structures and adapted their preparedness and response plans in order to deal with new kinds of threats. Korea has dual surveillance systems for the early detection of bioterrorism. The first is syndromic surveillance that typically monitors non-specific clinical information that may indicate possible bioterrorism-associated diseases before specific diagnoses are made. The other is infectious disease specialist network that diagnoses and responds to specific illnesses caused by intentional release of biologic agents. Infectious disease physicians, clinical microbiologists, and infection control professionals play critical and complementary roles in these networks. Infectious disease specialists should develop practical and realistic response plans for their institutions in partnership with local and state health departments, in preparation for a real or suspected bioterrorism attack.

• Smart Structures and Systems
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• 제31권4호
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• pp.351-363
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• 2023

Visual structural inspections are an inseparable part of post-earthquake damage assessments. With unmanned aerial vehicles (UAVs) establishing a new frontier in visual inspections, there are major computational challenges in processing the collected massive amounts of high-resolution visual data. We propose twin deep learning models that can provide accurate high-resolution structural components and damage segmentation masks efficiently. The traditional approach to cope with high memory computational demands is to either uniformly downsample the raw images at the price of losing fine local details or cropping smaller parts of the images leading to a loss of global contextual information. Therefore, our twin models comprising Trainable Resizing for high-resolution Segmentation Network (TRS-Net) and DmgFormer approaches the global and local semantics from different perspectives. TRS-Net is a compound, high-resolution segmentation architecture equipped with learnable downsampler and upsampler modules to minimize information loss for optimal performance and efficiency. DmgFormer utilizes a transformer backbone and a convolutional decoder head with skip connections on a grid of crops aiming for high precision learning without downsizing. An augmented inference technique is used to boost performance further and reduce the possible loss of context due to grid cropping. Comprehensive experiments have been performed on the 3D physics-based graphics models (PBGMs) synthetic environments in the QuakeCity dataset. The proposed framework is evaluated using several metrics on three segmentation tasks: component type, component damage state, and global damage (crack, rebar, spalling). The models were developed as part of the 2^nd International Competition for Structural Health Monitoring.

• Smart Structures and Systems
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• 제29권1호
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• pp.181-193
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• 2022

Data-driven structural health monitoring (SHM) of civil infrastructure can be used to continuously assess the state of a structure, allowing preemptive safety measures to be carried out. Long-term monitoring of large-scale civil infrastructure often involves data-collection using a network of numerous sensors of various types. Malfunctioning sensors in the network are common, which can disrupt the condition assessment and even lead to false-negative indications of damage. The overwhelming size of the data collected renders manual approaches to ensure data quality intractable. The task of detecting and classifying an anomaly in the raw data is non-trivial. We propose an approach to automate this task, improving upon the previously developed technique of image-based pre-processing on one-dimensional (1D) data by enriching the features of the neural network input data with multiple channels. In particular, feature engineering is employed to convert the measured time histories into a 3-channel image comprised of (i) the time history, (ii) the spectrogram, and (iii) the probability density function representation of the signal. To demonstrate this approach, a CNN model is designed and trained on a dataset consisting of acceleration records of sensors installed on a long-span bridge, with the goal of fault detection and classification. The effect of imbalance in anomaly patterns observed is studied to better account for unseen test cases. The proposed framework achieves high overall accuracy and recall even when tested on an unseen dataset that is much larger than the samples used for training, offering a viable solution for implementation on full-scale structures where limited labeled-training data is available.

• Journal of Radiation Protection and Research
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• 제20권3호
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• pp.155-162
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• 1995

비전리방사선에 대한 방호의 관점에서 현재의 검출 및 측정기술을 검토하였다. 특히 전파와 자외선을 중심으로 노출계측량, 측정기기 및 측정 시 고려사항을 설명하였다. 전파장에 대해서는 실제 파원별로 출력밀도의 수준을 요약하여 실무에 참고가 되게 하였다. 대체로 비 전리방사선의 측정에는 아직 큰 오차가 있으므로 늘어나는 비 전리방사선원과 이로 인한 유해한 건강영향에 대한 대중의 관심을 고려하면 비 전리방사선 측정기술의 개발수요는 크다.

• 세라미스트
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• 제21권2호
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• pp.38-48
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• 2018

This paper reports a comprehensive review of the state-of-the-art in research on the enhancement of sensing properties for the detection of gases in exhaled breath. Daily health monitoring and early diagnosis of specific diseases via the analysis of exhaled breath is possible. Because biomarkers in exhaled breath are emitted in a very small amount, it is necessary to develop highly sensitive gas sensors. In recent years, a number of researches have been carried out using various strategies for the enhancement of sensing properties such as doping, catalyst, hollow sphere, heterojunction, size effect. We introduced each strategy and summarized recent progress on sensing properties for detection of biomarkers in exhaled breath.

• International Journal of Railway
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• 제7권4호
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• pp.94-99
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• 2014

Urban railway systems are located under populated areas and are mostly constructed for underground structures which demand high standards of structural safety. However, the damage progression of underground structures is hard to evaluate and damaged underground structures may not effectively stand against successive earthquakes. This study attempts to examine initial damage-stage and to access structural damage condition of the ground structures using Earthquake Damage Monitoring (EDM) system. For actual underground structure, vulnerable damaged member of Ulchiro-3ga station is chosen by finite element analysis using applied artificial earthquake load, and then damage pattern and history of damaged members is obtained from measured acceleration data introduced unsupervised learning recognition. The result showed damage index obtained by damage scenario establishment using acceleration response of selected vulnerable members is useful. Initial damage state is detected for selected vulnerable member according to established damage scenario. Stiffness degrading ratio is increasing whereas the value of reliability interval is decreasing.

• 지구물리
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• 제8권1호
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• pp.7-14
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• 2005

Early detection in real-time response of slope movements ensures tremendous saving of lives and repair costs from catastrophic disaster. Therefore, it is essential to constantly monitor the performance and integrity of slope-stabilizing structures such as Rock bolt, Nail and Pile during or after installation. We developed a novel monitoring system using Fiber Bragg Grating (FBG) sensor. It's advantages are highly sensitivity, small dimension and electro-magnetic immunity. capability of multiplexing, system integrity, remote sensing - these serve real-time health monitoring of the structures. Real-time strain measurement by the signal processing program is shown graphically and it gives a warning sound when the monitored strain state exceeds a given threshold level so that any sign of abnormal disturbance on the spot can be easily perceived.

• 한국지반공학회:학술대회논문집
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• 한국지반공학회 2000년도 사면안정 학술발표회
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• pp.60-76
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• 2000

Early detection in real-time response of slope movements ensures tremendous saving of lives and repair costs from catastrophic disaster Therefore, it is essential to constantly monitor the performance and integrity of slope-stabilizing structures such as Rock bolt, Nail and Pile during or after installation. We developed a novel monitoring system using Fiber Bragg Grating (FBG)sensor. It's advantages are highly sensitivity, small dimension and electro-magnetic immunity. capability of multiplexing, system integrity, remote sensing - these serve real-time health monitoring of the structures. Real-time strain measurement by the signal processing program is shown graphically and it gives a warning sound when the monitored strain state exceeds a given threshold level so that any sign of abnormal disturbance on the spot can be easily perceived.

• 한국산업융합학회 논문집
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• 제25권2_1호
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• pp.169-176
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• 2022

Prognostics and health management (PHM) is recently converging throughout the industry, one of the trending issue is to detect abnormal conditions at decanter centrifuge during water treatment facilities. Wastewater treatment operation produces corrosive gas which results failures on attached sensors. This scenario causes frequent sensor replacement and requires highly qualified manager's visual inspection while replacing important parts such as bearings and screws. In this paper, we propose anomaly detection by measuring the vibration of the decanter centrifuge based on the video camera images. Measuring the vibration of the screw decanter by applying the optical flow technique, the amount of movement change of the corresponding pixel is measured and fed into the LST M model. As a result, it is possible to detect the normal/warning/dangerous state based on LSTM classification. In the future work, we aim to gather more abnormal data in order to increase the further accuracy so that it can be utilized in the field of industry.