• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.4
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• pp.516-521
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• 2010

In this paper, we propose a video-based intelligent unmanned fire surveillance system using fuzzy color models. In general, to detect heat or smoke, a separate device is required for a fire surveillance system, this system, however, can be implemented by using widely used CCTV, which does not need separate devices and extra cost. The systems called video-based fire surveillance systems use mainly a method extracting smoke or flame from an input image only. The smoke is difficult to extract at night because of its gray-scale color, and the flame color depends on the temperature, the inflammable, the size of flame, etc, which makes it hard to extract the flame region from the input image. This paper deals with a intelligent fire surveillance system which is robust against the variation of the flame color, especially at night. The proposed system extracts the moving object from the input image, makes a decision whether the object is the flame or not by means of the color obtained by fuzzy color model and the shape obtained by histogram, and issues a fire alarm when the flame is spread. Finally, we verify the efficiency of the proposed system through the experiment of the controlled real fire.

• Smart Structures and Systems
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• v.25 no.3
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• pp.285-299
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• 2020

Long term structural health monitoring has gained wide attention among civil engineers in recent years due to the scale and severity of infrastructure deterioration. Establishing effective damage indicators and proposing enhanced monitoring methods are of great interests to the engineering practices. In the case of bridge health monitoring, long term structural vibration measurement has been acknowledged to be quite useful and utilized in the planning of maintenance works. Previous researches are majorly concentrated on linear time series models for the measurement, whereas nonlinear dependences among the measurement are not carefully considered. In this paper, a new bridge health monitoring method is proposed based on the use of long term vibration measurement. A combination of the fundamental ARMA model and copula theory is investigated for the first time in detecting bridge structural damages. The concept is applied to a real engineering practice in Japan. The efficiency and accuracy of the copula based damage indicator is analyzed and compared in different window sizes. The performance of the copula based indicator is discussed based on the damage detection rate between the intact structural condition and the damaged structural condition.

• Journal of The Korean Society of Agricultural Engineers
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• v.61 no.6
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• pp.81-92
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• 2019

The objective of this study is to evaluate hydrologic impacts of climate change according to downscaling methods using the Soil and Water Assessment Tool (SWAT) model at watershed scale. We used the APCC Integrated Modeling Solution (AIMS) for assessing various General Circulation Models (GCMs) and downscaling methods. AIMS provides three downscaling methods: 1) BCSA (Bias-Correction & Stochastic Analogue), 2) Simple Quantile Mapping (SQM), 3) SDQDM (Spatial Disaggregation and Quantile Delta Mapping). To assess future hydrologic responses of climate change, we adopted three GCMs: CESM1-BGC for flood, MIROC-ESM for drought, and HadGEM2-AO for Korea Meteorological Administration (KMA) national standard scenario. Combined nine climate change scenarios were assessed by Expert Team on Climate Change Detection and Indices (ETCCDI). SWAT model was established at the Mankyung watershed and the applicability assessment was completed by performing calibration and validation from 2008 to 2017. Historical reproducibility results from BCSA, SQM, SDQDM of three GCMs show different patterns on annual precipitation, maximum temperature, and four selected ETCCDI. BCSA and SQM showed high historical reproducibility compared with the observed data, however SDQDM was underestimated, possibly due to the uncertainty of future climate data. Future hydrologic responses presented greater variability in SQM and relatively less variability in BCSA and SDQDM. This study implies that reasonable selection of GCMs and downscaling methods considering research objective is important and necessary to minimize uncertainty of climate change scenarios.

• Smart Structures and Systems
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• v.18 no.3
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• pp.405-423
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• 2016

In this study, the feasibility of using telecommunication single-mode optical fiber (SMF) as a distributed fiber optic strain and crack sensor was evaluated in concrete pavement monitoring. Tensile tests on various sensors indicated that the $SMF-28e^+$ fiber revealed linear elastic behavior to rupture at approximately 26 N load and 2.6% strain. Six full-scale concrete panels were prepared and tested under truck and three-point loads to quantify the performance of sensors with pulse pre-pump Brillouin optical time domain analysis (PPP-BOTDA). The sensors were protected by precast mortar from brutal action during concrete casting. Once air-cured for 2 hours after initial setting, half a mortar cylinder of 12 mm in diameter ensured that the protected sensors remained functional during and after concrete casting. The strains measured from PPP-BOTDA with a sensitivity coefficient of $5.43{\times}10^{-5}GHz/{\mu}{\varepsilon}$ were validated locally by commercial fiber Bragg grating (FBG) sensors. Unlike the point FBG sensors, the distributed PPP-BOTDA sensors can be utilized to effectively locate multiple cracks. Depending on their layout, the distributed sensors can provide one- or two-dimensional strain fields in pavement panels. The width of both micro and major cracks can be linearly related to the peak strain directly measured with the distributed fiber optic sensor.

• Journal of Environmental Health Sciences
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• v.47 no.5
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• pp.496-503
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• 2021

Background: Considering the expenses of and difficulties in arsenic speciation by high performance liquid chromatography-inductively coupled plasma-mass spectrometry (HPLC-ICP-MS), alternative measurement methods should be useful, especially for large-scale research and projects. Objectives: A measurement method was developed for arsenic speciation using HPLC-atomic fluorescence spectrometry (HPLC-AFS) as an alternative to HPLC-ICP-MS. Methods: Total arsenic and toxic arsenic species in some seafoods were determined by atomic absorption spectrometry coupled with hydride vapor generation (AAS-HVG) and HPLC-AFS, respectively. Recovery rate of arsenic species in seafood was evaluated by ultra sonication, microwave and enzyme (pepsin) for the optimal extraction method. Results: Limits of detection of HPLC-AFS for As³⁺, dimethylarsinate (DMA), monomethylarsonate (MMA) and As⁵⁺ were 0.39, 0.53, 0.60 and 0.64 ㎍/L, respectively. The average accuracy ranged from 97.5 to 108.7%, and the coefficient of variation was in the range of 1.2~16.7%. As³⁺, DMA, MMA and As⁵⁺ were detected in kelp, the sum of toxic arsenic in kelp was 40.4 mg/kg. As³⁺, DMA, MMA and As⁵⁺ were not detected in shrimp and squid, but total arsenic (iAS and oAS) content in shrimp and squid analyzed by AAS-HVG were 18.1 and 24.7 mg/kg, respectively. Conclusions: HPLC-AFS was recommendable for the quantitative analysis method of arsenic species. As toxic arsenic species are detected in seaweeds, further researches are needed for the contribution degree of seafood in arsenic exposure.

• Korean Journal of Clinical Pharmacy
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• v.29 no.3
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• pp.173-185
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• 2019

Objective: To gather inputs from clinical experts on selecting and prioritizing research topics, to address unmet vaccine safety needs. Methods: A questionnaire containing 15 vaccine safety assessment research proposals was sent to 28 vaccine experts chosen from various domestic medical association boards, and the rationale for each of the proposals was provided by presenting the following information: 1) a brief summary of the clinical safety studies on the vaccine, conducted by the Clinical Immunization Safety Assessment (CISA) project group, supervised by the United States Center for Disease Control (U.S. CDC), and 2) a summary of recently published studies that address vaccine safety issues. The experts were instructed to select and rank 5 topics in the order of preference, and the preference score for each proposed topic was calculated by assigning points on a scale of 1 to 5. Results: All 28 experts responded to the questionnaire, and the following topics were selected according to their calculated preference scores: 1) Human papillomavirus vaccine safety profile in the Korean female adolescents; 2) A signal detection of adverse events following Influenza vaccination: comparison between the US and South Korea; 3) Incidence of anaphylaxis following National Immunization Program vaccines between 2008 and 2017; 4) Safety of quadrivalent influenza vaccines compared to trivalent influenza vaccines; and 5) Pneumococcal vaccine safety profile in the general population. Conclusion: Five research topics addressing vaccine safety were selected, for which well-constructed research protocols need to be promptly developed to address current unmet vaccine safety needs in South Korea.

• Korean Journal of Remote Sensing
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• v.35 no.3
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• pp.359-373
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• 2019

Bursaphelenchus xylophilus(Pine wilt disease) is a serious threat to the pine forest in Korea. However, dead wood observation by Pine wilt disease is based on field survey. Therefore, it is difficult to observe large-scale forests due to physical and economic problems. In this paper, high resolution images were obtained using the unmanned aerial vehicle (UAV) in the area where the pine wilt disease recurred. The damaged tree due to pine wilt disease was detected using Artificial Neural Network (ANN), Support Vector Machine (SVM) supervision classification technique. Also, the accuracy of supervised classification results was calculated. After conducting supervised classification on accessible forests, the reliability of the accuracy was verified by comparing the results of field surveys.

• The Journal of the Acoustical Society of Korea
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• v.38 no.2
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• pp.145-153
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• 2019

Adaptive beamforming methods are known to suppress sidelobes and improve detection performance of weak signal by constructing weight vectors depending on the received signal itself. A standard adaptive beamforming like the MVDR (Minimum Variance Distortionless Response) is very sensitive to mismatches between weight vectors and actual signal steering vectors. Also, a large computational complexity for estimating a stable covariance matrix is required when wideband beamforming for a large-scale array is used. In this paper, we exploit the WBRCB (Wideband Robust Capon Beamforming) method for stable and robust wideband adaptive beamforming of a passive large uniform line array sonar. To improve robustness of adaptive beamforming performance in the presence of mismatches, we extract a optimum mismatch parameter. WBRCB with extracted mismatch parameter shows performance improvement in beamforming using synthetic and experimental passive sonar signals.

• Korean Journal of Pharmacognosy
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• v.52 no.3
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• pp.186-191
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• 2021

We developed a method to identify and quantify 6-hydroxyluteolin 7-O-glucoside in the powder of Salvia plebeia (PS) using high-performance liquid chromatography coupled with diode array detector (HPLC/DAD) and equipped with reverse-phase INNO C18 column. The analytical method was optimized and validated using novel parameters. The obtained values for the limits of detection and quantification were 3.60 and 10.90 ㎍/mL, respectively. Calibration curve showed good linearity in the concentration range tested (0.00625-0.1 mg/mL, r² = 1.0000), high accuracy (96.2-101.4%), and precision values (RSD ≤ 0.27%). Our analysis support the use of our method for accurately identifying and quantifying 6-hydroxyluteolin 7-O-glucoside from PS in routine analyses and large-scale extraction processes for content determination.

• Journal of radiological science and technology
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• v.44 no.4
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• pp.307-313
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• 2021

The purpose of this study was to analyze the risk factors for uterine myoma diagnosed by ultrasonography in Korea women and to evaluate the risk. Among the patients who visited the outpatient department of obstetrics and gynecology at I hospital in Busin between January 2019 and March 2021 for the purpose of examination, 98 patients in the experimental group diagnosed with uterine myoma and 163 patients in the normal control group without other diseases were retrospectively conducted. Among the general characteristics of the subjects, age, body mass index, parity, and menopause showed significant differences between the myoma group and the normal control group. ROC(receiver operating characteristic) curve analysis and logistic regression analysis were performed to obtain the cut off value and odds ratio that can predict the occurrence of uterine myoma. The cut off value for the prediction of uterine myoma was determined to be 30 years old and a body mass index of 23 kg/m². After that adjusting for menopause, non menopausal cases with a body mass index of 23 kg/m² and over 39 years of age had the highest odds ratio of 6.04. Therefore, premenopausal women over 40 years of age require regular checkups and thorough weight management. This study was conducted with a small number of subjects. Therefore, there is a limit to generalizing to all Korean women. However, based on this study if a large scale prospective study considering various variables is made, it can play a role as a predictive marker in early detection of uterine myoma.