• Korean Journal of Remote Sensing
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• v.36 no.4
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• pp.627-635
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• 2020

With the increasing severity of climate change, intense torrential rains are occurring more frequently globally. Flooding due to torrential rain not only causes substantial damage directly, but also via secondary events such as landslides. Therefore, accurate and prompt flood detection is required. Because it is difficult to directly access flooded areas, previous studies have largely used satellite images. Traditionally, water indices such asthe normalized difference water index (NDWI) and modified normalized difference water index (MNDWI) which are based on different optical bands acquired by satellites, are used to detect floods. In addition, as flooding likelihood is greatly influenced by the weather, synthetic aperture radar (SAR) images have also been used, because these are less influenced by weather conditions. In this study, we compared flood areas calculated from SAR images and water indices derived from Landsat-8 images, where the images were acquired at similar times. The flooded area was calculated from Landsat-8 and Sentinel-1 images taken between the end of May and August 2019 at Lijiazhou Island, China, which is located in the Changjiang (Yangtze) River basin and experiences annual floods. As a result, the flooded area calculated using the MNDWI was approximately 21% larger on average than that calculated using the NDWI. In a comparison of flood areas calculated using water indices and SAR intensity images, the flood areas calculated using SAR images tended to be smaller, regardless of the order in which the images were acquired. Because the images were acquired by the two satellites on different dates, we could not directly compare the accuracy of the water-index and SAR data. Nevertheless, this study demonstrates that floods can be detected using both optical and SAR satellite data.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.52 no.12
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• pp.705-712
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• 2003

In this paper, we propose new unified methodologies of reliability and its cost evaluation in power distribution systems. The unified method means that the proposed reliability approaches consider both conventional evaluation factor, i.e. sustained interruptions and additional ones, i.e. momentary interruptions and voltage sags. Because the three voltage quality phenomena generally originate from the outages on distribution systems, the basic and additional reliability indices are summarized considering the fault clearing mechanism. The proposed unified method is divided into the reliability evaluation for calculating the reliability indices and reliability cost evaluation for assessing the damage of customer. The analytic and probabilistic methodologies are presented for each unified reliability and its cost evaluation. The time sequential Monte Carlo technique is used for the probabilistic method. The proposed DVL(Demand Varying Load) model is added to the reliability cost evaluation substituting the average load model. The proposed methods are tested using the modified RBTS(Roy Billinton Test System) form and historical reliability data of KEPCO(Korea Electric Power Corporation) system. The daily load profile of the each customer type in domestic are gathered for the DVL model. Through the case studies, it is verified that the proposed methods can be effectively applied to the distribution systems for more detail reliability assessment than conventional approaches.

• Smart Structures and Systems
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• v.17 no.2
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• pp.167-194
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• 2016

This paper investigates the Synergetics based Damage Detection Method (SDDM) for frame structures by using surface-bonded PZT (Lead Zirconate Titanate) patches. After analyzing the mechanism of pattern recognition from Synergetics, the operating framework with cooperation-competition-update process of SDDM was proposed. First, the dynamic identification equation of structural conditions was established and the adjoint vector (AV) set of original vector (OV) set was obtained by Generalized Inverse Matrix (GIM).Then, the order parameter equation and its evolution process were deduced through the strict mathematics ratiocination. Moreover, in order to complete online structural condition update feature, the iterative update algorithm was presented. Subsequently, the pathway in which SDDM was realized through the modified Synergetic Neural Network (SNN) was introduced and its assessment indices were confirmed. Finally, the experimental platform with a two-story frame structure was set up. The performances of the proposed methodology were tested for damage identifications by loosening various screw nuts group scenarios. The experiments were conducted in different damage degrees, the disturbance environment and the noisy environment, respectively. The results show the feasibility of SDDM using piezoceramic sensors and actuators, and demonstrate a strong ability of anti-disturbance and anti-noise in frame structure applications. This proposed approach can be extended to the similar structures for damage identification.

• Earthquakes and Structures
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• v.13 no.3
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• pp.289-297
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• 2017

This paper presents seismic performance and reliability evaluation on steel-timber hybrid shear wall systems composed of steel moment resisting frames and infill light frame wood shear walls. Based on experimental observations, damage assessment was conducted to determine the appropriate damage-related performance objectives for the hybrid shear wall systems. Incremental time-history dynamic analyses were conducted to establish a database of seismic responses for the hybrid systems with various structural configurations. The associated reliability indices and failure probabilities were calculated by two reliability methods (i.e., fragility analysis and response surface method). Both methods yielded similar estimations of failure probabilities. This study indicated the greatly improved seismic performance of the steel-timber hybrid shear wall systems with stronger infill wood shear walls. From a probabilistic perspective, the presented results give some insights on quantifying the seismic performance of the hybrid system under different seismic hazard levels. The reliability-based approaches also serve as efficient tools to assess the performance-based seismic design methodology and calibration of relative code provisions for the proposed steel-timber hybrid shear wall systems.

• Fisheries and Aquatic Sciences
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• v.17 no.1
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• pp.105-113
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• 2014

Glufosinate-ammonium, a component of the herbicide Basta, is one of the most extensively used pesticides worldwide. In this study, we assessed subchronic and chronic toxicities of Basta and its histopathological effects on the marine medaka Oryzias dancena. Marine medaka were exposed to 0, 2, 4, or 8 mg/L of Basta for 28 or 42 days. The lethal concentration ($LC_{50}$) of Basta for 96 h is 8.76 mg/L. Histological changes in the gills and liver were evaluated with histopathological indices, allowing quantification of the damage to fish exposed to Basta. Blood congestion, lamellar fusion, and epithelial lifting were observed in the gills, and hydropic degeneration, fibrosis, lipid degeneration, leukocyte infiltration, and necrosis were found in the liver. These responses could be useful indicators of Basta toxicity in this species.

• International Journal of Computer Science & Network Security
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• v.21 no.5
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• pp.23-30
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• 2021

In recent years, hazardous flash flooding has caused deaths and damage to infrastructure in Saudi Arabia. In this paper, our aim is to assess patterns and trends in climate means and extremes affecting flash flood hazards and water resources in Saudi Arabia for the purpose to improve risk assessment for forecast capacity. We would like to examine temperature, precipitation climatology and trend magnitudes at surface stations in Saudi Arabia. Based on the assessment climate patterns maps and trends are accurately used to identify synoptic situations and tele-connections associated with flash flood risk. We also study local and regional changes in hydro-meteorological extremes over recent decades through new applications of statistical methods to weather station data and remote sensing based precipitation products; and develop remote sensing based high-resolution precipitation products that can aid to develop flash flood guidance system for the flood-prone areas. A dataset of extreme events has been developed using the multi-decadal station data, the statistical analysis has been performed to identify tele-connection indices, pressure and sea surface temperature patterns most predictive to heavy rainfall. It has been combined with time trends in extreme value occurrence to improve the potential for predicting and rapidly detecting storms. A methodology and algorithms has been developed for providing a well-calibrated precipitation product that can be used in the early warning systems for elevated risk of floods.

• Korean Journal of Remote Sensing
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• v.37 no.4
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• pp.815-831
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• 2021

Drought forecasting is crucial to minimize the damage to food security and water resources caused by drought. Satellite-based drought research has been conducted since 1980s, which includes drought monitoring, assessment, and prediction. Unlike numerous studies on drought monitoring and assessment for the past few decades, satellite-based drought forecasting has gained popularity in recent years. For successful drought forecasting, it is necessary to carefully identify the relationships between drought factors and drought conditions by drought type and lead time. This paper aims to provide an overview of recent research trends and challenges for satellite-based drought forecasts focusing on lead times. Based on the recent literature survey during the past decade, the satellite-based drought forecasting studies were divided into three groups by lead time (i.e., short-term, sub-seasonal, and seasonal) and reviewed with the characteristics of the predictors (i.e., drought factors) and predictands (i.e., drought indices). Then, three major challenges-difficulty in model generalization, model resolution and feature selection, and saturation of forecasting skill improvement-were discussed, which led to provide several future research directions of satellite-based drought forecasting.

• The Korean Journal of Physiology and Pharmacology
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• v.17 no.2
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• pp.169-173
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• 2013

Renal ischemia-reperfusion (IR) causes remote liver damage. Oxytocin has anti-inflammatory and antioxidant effects. The main purpose of this study was to evaluate the protective function of oxytocin (OT) in remote liver damage triggered by renal IR in rats. Twenty four rats were randomly divided into four different groups, each containing 8 rats. The groups were as follows: (1) Sham operated group; (2) Sham operated+OT group (3) Renal IR group; (4) Renal IR+OT group. OT ($500{\mu}g/kg$) was administered subcutaneously 12 and 24 hours before and immediately after ischemia. At the end of experimental procedure, the rats were sacrificed, and liver specimens were taken for histological assessment or determination of malondialdehyde (MDA), total oxidant status (TOS), total antioxidant status (TAS), paraoxonase (PON-1) activity and nitric oxide (NO). The results showed that renal IR injury constituted a notable elevation in MDA, TOS, Oxidative stress index (OSI) and significantly decreased TAS, PON-1 actvity and NO in liver tissue (p<0.05). Additionally renal IR provoked significant augmentation in hepatic microscopic damage scores. However, alterations in these biochemical and histopathological indices due to IR injury were attenuated by OT treatment (p<0.05). These findings show that OT ameliorates remote liver damage triggered by renal ischemia-reperfusion and this preservation involves suppression of inflammation and regulation of oxidant-antioxidant status.

• Journal of Korean Society of Steel Construction
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• v.20 no.6
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• pp.723-730
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• 2008

Due to the higher ratio of live load to total loads of railway bridges, the accumulated damage by cyclic fatigue is significant. Moreover, it is highly possible that the initiated crack grows faster than that of highway bridges. Therefore, it is strongly needed to assess the safety for the accumulated damage analytically. The initiation and growth of fatigue-crack are related with the stress range, number of cycles, and the stiffness of the structural system. The stiffness of the structural system includes uncertainties of the planning, design, construction and maintenance, which varies as time goes. In this study, the authors developed the design and risk assessment techniques based on the reliability theories considering the uncertainties in load and resistance. For the probabilistic risk assessment of crack growth and the remaining life of the structures by the cyclic load of railway and subway bridges, response surface method (RSM) combined with first order second moment method were used. For composing limit state function, the stress range, stress intensity factor and the remaining life were selected as input important random variables to the RSM program. The probabilities of failure and the reliability indices of fatigue life for the considered specimen under cyclic loads were evaluated and discussed.

• Korean Journal of Soil Science and Fertilizer
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• v.45 no.5
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• pp.711-716
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• 2012

Due to the climate change in South Korea the annual total precipitation will increase by 17 percent by 2100. Rainfall is concentrated during the summer in South Korea and the landslide of farmland by heavy rain is expected to increase. Because regional torrential rains accompanied by a storm continue to cause the damage in farmland urgent establishment of adaptation plant for minimizing the damage is in need. In this study we assessed vulnerability of landslide of farmland by heavy rain for local governments. Temporal resolution is 2000 year and the future 2020 year, 2050 year, 2100 year via A1B scenario. Vulnerability of local government were evaluated by three indices such as climate exposure, sensitivity, adaptive capacity and each index is calculated by selected alternative variable. Collected data was normalized and then multiplied by weight value that was elicited in delphi investigation. Current vulnerability is concentrated in Jeju island and Gyeongsangnam-do, however, it is postulated that Kangwon-do will be vulnerable in the future. Through this study, local governments can use the data to establish adaptation plans for farmland landslide by climate change.