• Korean Journal of Clinical Laboratory Science
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• v.54 no.1
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• pp.61-67
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• 2022

Intraoperative neurophysiological monitoring (INM) ensures the stability and safety of specific surgeries in high-risk groups. As part of INM, intensive tests are conducted during the surgical process. When INM tests are applied during surgery, a delay in notifying the operating surgeon in cases of neurological defects can cause serious irreversible sequelae to the patient. Aortic replacement, which is necessitated due to aortic aneurysms and aortic dissection, is a complicated procedure that blocks the blood flow to the heart. When arteries that branch out from the aorta and supply blood to the spinal cord are replaced, blood flow to the spinal cord decreases, resulting in spinal ischemia. In aortic surgery, INM plays an important role in preventing spinal ischemia and serious complications by quickly detecting the early signs of spinal ischemia during cross-clamping and reporting it to the surgeon. Therefore, this paper was prepared to help examiners who conduct INM by detailing the process, method, time, and warning criteria for INM. This paper identifies the need for INM in aortic surgery and the process flow for a smooth test, accurate and rapid examination, and subsequent reporting.

• Journal of the Korean Geosynthetics Society
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• v.18 no.4
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• pp.129-138
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• 2019

In this study, the rebar rock bolt sensor and GFRP rock bolt sensor, which can be monitored, were embedded in a large model slope, and the behavior of slopes occurred in the early stage of slope collapse was analyzed after performing the field failure test, numerical analysis of the individual element method and finite element method. By comparing and analyzing the field test and numerical analysis results, field applicability of rock slope collapse monitoring on the rebar rock bolt sensor and GFRP rock bolt sensor was investigated. Through this study, smart slope collapse prediction and warning system was developed, which can be used to induce effective evacuation of residents living in the collapsible area by detecting landslide and ground decay precursor information in advance.

• Journal of Aquaculture
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• v.18 no.3
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• pp.173-179
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• 2005

Superoxide dismutase (SOD), an antioxidant enzyme catalyzing the first step for scavenging the reactive oxygen species is important as an early warning indicator to address various biological stresses. For this reason, the monitoring the expressed pattern of SOD gene in fish organs is one of important biomarkers to assess the aquatic pollution caused by many toxic chemicals. Based on the Northern blot hybridization, semi-quantitative and/or realtime RT-PCRs, the alteration of SOD gene transcripts in shark liver was examined during the experimental acute exposures to cadmium. The expression of SOD at mRNA level was up-regulated both by injection (0, 0.5, 1 or 2 mg $CdCl_2/kg$ body weight for 48 hours) and by immersion (0 or $5{\mu}M$ Cd for 0, 1, 4 and 7 days) treatments of cadmium. The transcriptional stimulation of shark SOD gene by cadmium exposure was dependent upon doses and durations: there was a trend toward more increase in higher dose and longer durations of exposure. The hepatic SOD mRNA levels showed also a general agreement with the tissue cadmium concentrations accumulated in immersion exposure. This result may provide useful strategy to develop a fine molecular biomarker at mRNA level for detecting aquatic pollution caused by toxic metals.

• Safety and Health at Work
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• v.10 no.4
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• pp.420-427
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• 2019

Introduction: To prevent and manage the societal and economic burden of occupational diseases (ODs), countries should develop strong prevention policies, health surveillance and registry systems. This study aims to contribute to the improvement of OD surveillance at national level as well as to identify priority actions in Turkey. Methods: The history and current status of occupational health studies were considered from the perspective of OD surveillance. Interpretative research was done through literature review on occupational health at national, regional and international level. Analyses were focused on countries' experiences in policy development and practice, roles and responsibilities of institutions, multidisciplinary and intersectoral collaboration. OD surveillance models of Turkey, Belgium and the Netherlands were examined through exchange visits. Face-to-face interviews were conducted to explore the peculiarities of legislative and institutional structures, the best and worst practices, and approach principles. Results: Some countries are more focused on exploring OD trends through effective and cost-efficient researches, with particular attention to new and emerging ODs. Other countries try to reach every single case of OD for compensation and rehabilitation. Each practice has advantages and shortcomings, but they are not mutually exclusive, and thus an effective combination is possible. Conclusion: Effective surveillance and registry approaches play a key role in the prevention of ODs. A well-designed system enables monitoring and assessment of OD prevalence and trends, and adoption of preventive measures while improving the effectiveness of redressing and compensation. A robust surveillance does not only provide protection of workers' health but also advances prevention of economic losses.

• Journal of Korean Society for Geospatial Information Science
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• v.20 no.4
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• pp.135-143
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• 2012

Remote sensing which observes repeatedly the whole Earth and GIS-based decision-making technology have been utilized widely in disaster management such as early warning monitoring, damage investigation, emergent rescue and response, rapid recovery etc. In addition, various countermeasures of national level to collect timely satellite imagery in emergency have been considered through the operation of a satellite with onboard multiple sensors as well as the practical joint use of satellite imagery by collaboration with space agencies of the world. In order to respond heavy snowfall disaster occurred on the east coast of the Korean Peninsula in February 2011, snow-covered regions were analyzed and detected in this study through NDSI(Normalized Difference Snow Index) considering reflectance of wavelength for MODIS sensor and change detection algorithm using satellite imagery collected from International Charter. We present the application case of National Disaster Management Institute(NDMI) which supported timely decision-making through GIS spatial analysis with various spatial data and snow cover map.

• Journal of the Korean Society of Marine Environment & Safety
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• v.20 no.3
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• pp.277-284
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• 2014

This paper describes the application method of bumper area defined in the ship domain theory and it is to identify risky sectors in VTS(Vessel Traffic Services) area. The final goal of this work is to develop early warning system providing the location information with high traffic risks in Mokpo VTS area and to prevent the human errors of VTS Officer(VTSO). The current goal of this paper is to find evaluation and detection method of risky sectors. The ratio between overlapped bumper area of each vessels and the summing area of a designated sector, Ratio to Evaluate Risk(RER) ${\gamma}$ is used as one of evaluation and detection parameter. The usability of overlapped bumper area is testified through three kinds of scenarios for various traffic situations. The marine traffic data used in the experiments is collected by AIS(Automatic Identification System) receiver and then compiled in the SQL(Structured Query Language) Server. Through the analysis of passing vessel's tracks within the boundary of Mokpo VTS area, the total of 11 sectors are identified as evaluation unit sector. As experiment results from risk evaluation for the 11 sectors, it is clearly known that the proposed method with RER ${\gamma}$ can provide the location information of high risky sectors which are need to keep traffic tracks of vessel movements and to maintain traffic monitoring by VTSO.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.30 no.3
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• pp.21-28
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• 2012

The main objective of this study is to reveal the basic information for structuring the subsequent information monitoring and early warning system and configuring the sustainable programme management of Donggung and wolji, Gyeongju which was much utilized as historic garden with the physical carrying capacity and the psychological carrying capacity according to on-spot observation and survey. The physical carrying capacity can be calculated with landscape node spatial capacity, road spatial capacity and other spatial capacity and the psychological carrying capacity can be calculated with vision, hearing, touch, action feeling and satisfaction. The number of actual tourists was lower than the carrying capacity in daytime, but it was about twice as great as that in the night. And because the tourists were mainly tour groups, the time of environment damaged was short and fixed. The management improvement program was brought forward centre around the results.

• Journal of Korean Society on Water Environment
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• v.27 no.4
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• pp.533-541
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• 2011

Algal blooms have caused problems for drinking water as well as eutrophication. However it is difficult to control algal blooms by current warning manual in rainy season because the algal blooms happen in a few days. The water quality data, which have high correlations with Chlorophyll-a on Daecheongho station, were analyzed and chosen as input data of Artificial Neural Networks (ANN) for training pattern changes. ANN was applied to early forecasting of algal blooms, and ANN was assessed by forecasting errors. Water temperature, pH and Dissolved oxygen were important factors in the cross correlation analysis. Some water quality items like Total phosphorus and Total nitrogen showed similar pattern to the Chlorophyll-a changes with time lag. ANN model (No. 3), which was calibrated by water temperature, pH and DO data, showed lowest error. The combination of 1 day, 3 days, 7 days forecasting makes outputs more stable. When automatic monitoring data were used for algal bloom forecasting in Daecheong reservoir, ANN model must be trained by just input data which have high correlation with Chlorophyll-a concentration. Modular type model, which is combined with the output of each model, can be effectively used for stable forecasting.

• Journal of the Korean Geosynthetics Society
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• v.22 no.1
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• pp.67-74
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• 2023

In order to monitor the stability of slopes, research on data-based slope failure prediction and early warning is increasing. However, most papers overlook the quality of data. Poor data quality can cause problems such as false alarms. Therefore, this paper proposes a two-step hybrid approach consisting of rules and machine learning models for quality control of data collected from slopes. The rule-based has the advantage of high accuracy and intuitive interpretation, and the machine learning model has the advantage of being able to derive patterns that cannot be explicitly expressed. The hybrid approach was able to take both of these advantages. Through a case study, the performance of using the two methods alone and the case of using the hybrid approach was compared, and the hybrid method was judged to have high performance. Therefore, it is judged that using a hybrid method is more appropriate than using the two methods alone for data quality control.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.13-13
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• 2020

'20년 3월 현재 전국 3,502개 읍면동 중 73개 읍면동이 지하수를 상수원으로 급수 중이며, 48개 산업단지에서 지하수를 주 수원으로 사용 중이다. 또한 급수 소외지역의 물 공급을 위해 주로 사용되는 소규모수도시설 14,811개 중 12,073개(81.5%)는 지하수를 이용하고 있으며, 그 위치는 전국에 산재해 있다. 이처럼 지하수는 댐, 저수지 및 하천과 더불어 생·공용수의 중요한 수원이라 할 수 있다. 본 연구에서는 급수 소외지역의 주요 수원인 지하수위 현황을 이용한 가뭄 모니터링 및 전망 기법을 개발하고자 하였다. 국가 지하수관측망 중 10년 이상 장기 관측 자료를 보유한 253개 관측소의 일단위 관측자료를 기반으로, 과거 관측수위 분포를 핵밀도함수로 추정하고 Quantile Function을 이용해 현재 수위의 높고 낮은 정도를 Percentile 값으로 산정하였다. 관측소별 지하수위 Percentile은 티센망을 이용해 167개 시군별로 공간평균하고 Percentile의 범위에 따른 가뭄등급을 설정하여 지하수 가뭄 정도를 모니터링 할 수 있는 기법을 제시하였다. 또한 지하수 가뭄을 전망하기 위해 강수와 지하수위의 거시적인 응답특성을 이용하였다. 관측소별로 추정된 핵밀도함수의 누적확률을 표준정규분포의 Quantile로 변환하여 표준지하수지수I(Standardized Groundwater level Index, SGI)를 산정하고, 시군별로 공간을 일치시킨 1~12개월 지속기간별 표준강수지수(Standardized Precipitation Index, SPI)와의 상관관계를 이용해 NARX(nonlinear autoregressive exogenous) 인공신경망 예측모형을 구축하였다. 이를 통해 기상청 정량전망 강수량을 이용해 전국의 1~3개월 후 지하수 가뭄을 빠르게 전망할 수 있는 체계를 구축하고, 생·공용수 분야 국가 가뭄 예·경보의 미급수지역 가뭄현황 및 전망에 활용중이다.