• Journal of the Korean Vacuum Society
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• v.18 no.4
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• pp.318-330
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• 2009

A high heat flux test facility using a graphite heating panel was constructed and is presently in operation at Korea Atomic Energy Research Institute, which is called KoHLT-1. Its major purpose is to carry out a thermal cycle test to verify the integrity of a HIP (hot isostatic pressing) bonded Be mockups which were fabricated for developing HIP joining technology to bond different metals, i.e., Be-to-CuCrZr and CuCrZr-to-SS316L, for the ITER (International Thermonuclear Experimental Reactor) first wall. The KoHLT-1 consists of a graphite heating panel, a box-type test chamber with water-cooling jackets, an electrical DC power supply, a water-cooling system, an evacuation system, an He gas system, and some diagnostics, which are equipped in an authorized laboratory with a special ventilation system for the Be treatment. The graphite heater is placed between two mockups, and the gap distance between the heater and the mockup is adjusted to $2{\sim}3\;mm$. We designed and fabricated several graphite heating panels to have various heating areas depending on the tested mockups, and to have the electrical resistances of $0.2{\sim}0.5$ ohms during high temperature operation. The heater is connected to an electrical DC power supply of 100 V/400 A. The heat flux is easily controlled by the pre-programmed control system which consists of a personal computer and a multi function module. The heat fluxes on the two mockups are deduced from the flow rate and the coolant inlet/out temperatures by a calorimetric method. We have carried out the thermal cycle tests of various Be mockups, and the reliability of the KoHLT-1 for long time operation at a high heat flux was verified, and its broad applicability is promising.

• Korean Journal of Remote Sensing
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• v.14 no.3
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• pp.296-306
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• 1998

Airborne MSS data is regarded as a potentially effective data source for the measurement of water quality and for the environmental change of water bodies. In this study, we measured the radiance reflectance by using multi-spectral image of low resolution camera(LRC) which will be reached in the multi-purpose satellite(KOMPSAT) to use the data in analyzing water pollution. We also investigated the possibility of extraction of water quality factors in water bodies by using high resolution remote sensing data such as Airborne MSS. Especially, we tried to extract environmental factors related with eutrophication such as chlorophyll-a, suspended sediments and turbidity, and also tried to develop the process technique and the radiance feature of reflectance related with eutrophication. Although it was difficult to explicitly correlate Airborne MSS data with water quality factors due to the insufficient number of ground truth data. The results were summarized as follows: First, the spectrum of sun's rays which reaches the surface of the earth was consistent with visible bands of 0.4${\mu}{\textrm}{m}$~0.7${\mu}{\textrm}{m}$ and about 50% of total quantity of radiation could be found. The spectrum was reached highest at around 0.5${\mu}{\textrm}{m}$ of green spectral band in visible bands. Second, as a result of the radiance reflectance Chlorophyll-a represented high mainly around 0.52${\mu}{\textrm}{m}$ of green spectral band, and suspended sediments and turbidity represented high at 0.8${\mu}{\textrm}{m}$ and at 0.57${\mu}{\textrm}{m}$, respectively. Finally, as a result of the water quality analysis by using Airborne MSS, Chlorophyll-a could have a distribution image after carrying out ratio of B3 and B5 to B7. Band 7 was useful for making the distribution image of suspended sediments. When we carried out PCA, suspended sediments and turbidity had distributions at PC 1 and PC 4 which are similar to the ground data. Above results can be changed according to the change of season and time. Therefore, in order to analyze the environmental factors of water quality by using LRC data more exactly, we need to investigate the ground data and the radiance feature of reflectance of water bodies constantly. For further studies, we will constantly analyze the radiance feature of the surface of water in wafter bodies by measuring the on-the-spot radiance reflectance and using low resolution satellite image(SeaWiFS). We will also gather the data of water quality analysis in water bodies and analyze the pattern of water pollution.

• Korean Journal of Remote Sensing
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• v.37 no.2
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• pp.321-335
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• 2021

Particulate matter (PM10 and PM2.5 with a diameter less than 10 and 2.5 ㎛, respectively) can be absorbed by the human body and adversely affect human health. Although most of the PM monitoring are based on ground-based observations, they are limited to point-based measurement sites, which leads to uncertainty in PM estimation for regions without observation sites. It is possible to overcome their spatial limitation by using satellite data. In this study, we developed machine learning-based retrieval algorithm for ground-level PM10 and PM2.5 concentrations using aerosol parameters from Geostationary Ocean Color Imager (GOCI) satellite and various meteorological parameters from a numerical weather prediction model during January to December of 2019. Gradient Boosted Regression Trees (GBRT) and Light Gradient Boosting Machine (LightGBM) were used to estimate PM concentrations. The model performances were examined for two types of feature sets-all input parameters (Feature set 1) and a subset of input parameters without meteorological and land-cover parameters (Feature set 2). Both models showed higher accuracy (about 10 % higher in R2) by using the Feature set 1 than the Feature set 2. The GBRT model using Feature set 1 was chosen as the final model for further analysis(PM10: R2 = 0.82, nRMSE = 34.9 %, PM2.5: R2 = 0.75, nRMSE = 35.6 %). The spatial distribution of the seasonal and annual-averaged PM concentrations was similar with in-situ observations, except for the northeastern part of China with bright surface reflectance. Their spatial distribution and seasonal changes were well matched with in-situ measurements.

• Korean Journal of Remote Sensing
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• v.37 no.2
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• pp.275-290
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• 2021

Sulfur dioxide (SO2) in the atmosphere is mainly generated from anthropogenic emission sources. It forms ultra-fine particulate matter through chemical reaction and has harmful effect on both the environment and human health. In particular, ground-level SO2 concentrations are closely related to human activities. Satellite observations such as TROPOMI (TROPOspheric Monitoring Instrument)-derived column density data can provide spatially continuous monitoring of ground-level SO2 concentrations. This study aims to propose a 2-step residual corrected model to estimate ground-level SO2 concentrations through the synergistic use of satellite data and numerical model output. Random forest machine learning was adopted in the 2-step residual corrected model. The proposed model was evaluated through three cross-validations (i.e., random, spatial and temporal). The results showed that the model produced slopes of 1.14-1.25, R values of 0.55-0.65, and relative root-mean-square-error of 58-63%, which were improved by 10% for slopes and 3% for R and rRMSE when compared to the model without residual correction. The model performance by country was slightly reduced in Japan, often resulting in overestimation, where the sample size was small, and the concentration level was relatively low. The spatial and temporal distributions of SO2 produced by the model agreed with those of the in-situ measurements, especially over Yangtze River Delta in China and Seoul Metropolitan Area in South Korea, which are highly dependent on the characteristics of anthropogenic emission sources. The model proposed in this study can be used for long-term monitoring of ground-level SO2 concentrations on both the spatial and temporal domains.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.1
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• pp.1-18
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• 2019

This research measured and visualized the spatial dependency and the spatial heterogeneity of the small business in Cheonan-si, Asan-si with $100m{\times}100m$ grids based on global and local spatial autocorrelation. First, we confirmed positive spatial autocorrelation of small business in the research area using Moran's I Index, which is ESDA(Exploratory Spatial Data Analysis). And then, through Getis-Ord $GI{\ast}$, one kind of LISA(Local Indicators of Spatial Association), local patterns of spatial autocorrelation were visualized. These verified that Spatial Regression Model is valid for the location factor analysis on small business commercial buildings. Next, GWR(Geographically Weighted Regression) was used to analyze the spatial relations between the distribution of small business, hourly mobile traffic-based floating population, land use attributes index, residence, commercial building, road networks, and the node of traffic networks. Final six variables were applied and the accessibility to bus stops, afternoon time floating population, and evening time floating population were excluded due to multicollinearity. By this, we demonstrated that GWR is statistically improved compared to OLS. We visualized the spatial influence of the individual variables using the regression coefficients and local coefficients of determinant of the six variables. This research applied the measured population information in a practical way. Reflecting the dynamic information of the urban people using the commercial area. It is different from other studies that performed commercial analysis. Finally, this research has a differentiated advantage over the existing commercial area analysis in that it employed hourly changing commercial service population data and it applied spatial statistical models to micro spatial units. This research proposed new framework for the commercial analysis area analysis.

• Journal of the Korean Society of Marine Environment & Safety
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• v.24 no.7
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• pp.848-857
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• 2018

Recently, around the world, active development of new renewable energy sources including solar power, waves, and fuel cells, etc. has taken place. Particularly, floating offshore wind farms have been developed for saving costs through large scale production, using high-quality wind power and minimizing noise damage in the ocean area. The development of floating wind farms requires an evaluation of the Maritime Safety Audit Scheme under the Maritime Safety Act in Korea. Floating wind farms shall be assessed by applying the line and area concept for systematic development, management and utilization of specified sea water. The development of appropriate evaluation methods and standards is also required. In this study, proper standards for marine traffic surveys and assessments were established and a systemic treatment was studied for assessing marine spatial area. First, a marine traffic data collector using AIS or radar was designed to conduct marine traffic surveys. In addition, assessment methods were proposed such as historical tracks, traffic density and marine traffic pattern analysis applying the line and area concept. Marine traffic density can be evaluated by spatial and temporal means, with an adjusted grid-cell scale. Marine traffic pattern analysis was proposed for assessing ship movement patterns for transit or work in sea areas. Finally, conceptual design of a Marine Traffic and Safety Assessment Solution (MaTSAS) was competed that can be analyzed automatically to collect and assess the marine traffic data. It could be possible to minimize inaccurate estimation due to human errors such as data omission or misprints through automated and systematic collection, analysis and retrieval of marine traffic data. This study could provides reliable assessment results, reflecting the line and area concept, according to sea area usage.

• Sleep Medicine and Psychophysiology
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• v.25 no.2
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• pp.51-57
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• 2018

Objectives: Previous studies have shown that periodic limb movements in sleep (PLMS) could be one of risk factors for cardiovascular morbidity. The purpose of this study was to investigate the association between PLMS and blood pressure changes during sleep. Methods: We analyzed data from 358 adults (176 men and 182 women) aged 18 years and older who were free from sleep apnea syndrome (Respiratory Disturbance Index < 5) and sleep disorders such as REM sleep behavior disorder or narcolepsy. Demographic characteristics, polysomnography records, and clinical variable data including blood pressure, body mass index, alcohol, smoking, and current medications were collected. In addition, self-report questionnaires including the Beck Depression Index, Epworth Sleepiness Scale and Pittsburgh Sleep Quality Index were completed. Blood pressure change from bedtime to awakening was compared between the two periodic limb movement index (PLMI) groups [low PLMI ($PLMI{\leq}15$) and high PLMI (PLMI > 15)]. Blood pressure change patterns were compared using repeated measures analysis of variance. Results: Systolic blood pressure in the high PLMI group was lower than that in the low PLMI group (p = 0.036). These results were also significant when adjusted for gender and age, but were not statistically significant when adjusted for BMI, alcohol, smoking, anti-hypertension medication use and sleep efficiency (p = 0.098). Systolic blood pressure dropped by 9.7 mm Hg in the low PLMI group, and systolic blood pressure in the high PLMI group dropped by 2.9 mm Hg. There was a significant difference in delta systolic blood pressure after sleep between the two groups in women when adjusted for age, BMI, alcohol, smoking, antihypertensive medication use and sleep efficiency (p = 0.023). Conclusion: PLMS was significantly associated with a decreasing pattern in nocturnal BP during sleep, and this association remained significant in women when adjusted for age, BMI, alcohol, smoking, antihypertension medication use and sleep efficiency related to blood pressure. We suggest that PLMS may be associated with cardiovascular morbidity.

• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.1
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• pp.1-28
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• 2019

This study analyzed the density and mortality rate of Korean fir at 9 sites where individuals of Korean firs were marked into the live and dead trees with coordinates on orthorectified aerial images by digital photogrammetric system. As a result of the analysis, Korean fir in each site showed considerable heterogeneity in density and mortality rate depending on the location within site. This make it possible to assume that death of Korean fir can occur by specific factors that vary depending on the location. Based on the analyzed densities and mortality rates of Korea fir, we investigated the correlation between topographic factors such as altitude, terrain slope, drainage network, solar radiation, aspect and the death of Korean fir. The density of Korean fir increases with altitude, and the mortality rate also increases. A negative correlation is found between the terrain slope and the mortality rate, and the mortality rate is higher in the gentle slope where the drainage network is less developed. In addition, it is recognized that depending on the aspect, the mortality rate varies greatly, and the mean solar radiation is higher in live Korean fir-dominant area than in dead Korean fir-dominant area. Overall, the mortality rate of Korean fir in Mt. Halla area is relatively higher in areas with relatively low terrain slope and low solar radiation. Considering the results of previous studies that the terrain slope has a strong negative correlation with soil moisture and the relationship between solar radiation and evaporation, these results lead us to infer that excess soil moisture is the cause of Korean fir mortality. These inferences are supported by a series of climate change phenomena such as precipitation increase, evaporation decrease, and reduced sunshine duration in the Korean peninsula including Jeju Island, increase in mortality rate along with increased precipitation according to the elevation of Mt. Halla and the vegetation change in the mountain. It is expected that the spatial patterns in the density and mortality rate of Korean fir, which are controlled by topography such as altitude, slope, aspect, solar radiation, drainage network, can be used as spatial variables in future numerical modeling studies on the death or decline of Korean fir. In addition, the method of forest distribution survey using the orthorectified aerial images can be widely used as a numerical monitoring technique in long - term vegetation change research.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.4
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• pp.428-434
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• 2019

Many countries have interested animal welfare. Similarly, domestic people have concern for the welfare from companion animals to livestock. Environmental enrichments (EE) are tool to enforce the welfare, however, research with sows is limited. Therefore, this study was investigate to effects of environmental enrichments on performance and behavior properties of gestating sows. A total of 30 pregnant sows (Landrace) were assigned into three treatments that control, T1 (plastic device) and T2 (Rice straw). Period of trial was from Mar. 03. 18. to Mary 19. 18. The EE were allotted to center of experimental pen ($11.6{\times}6.0m$). Body weight (BW), backfat thickness (BF) and cortisol were identified at experimental initial or end date. Behavior was recorded during 24 hours on days 91 of gestation, and then analyzed the patterns. BF was reduced (15.73 vs. 16.56 mm; p>0.05) in T1 than control, but Ending BW, total litter size and alive piglets did not differ. Born dead piglets showed lower tendency (1.00 and 0.63 vs. 1.50 heads; p>0.05) in T1 and T2 than control. Similarly, the enrichments declined farrowing mortality (C, 8.68%; T1, 6.86%; T2, 3.40%; p>0.05). Cortisol was not differed among treatments. In the behavior characteristics, eating showed lower (1.81 vs. 9.68 and 6.99%; p<0.05) in T2 than control and T1. Furthermore, playing or digging were only observed (0.33 and 2.10%; p<0.05) in T1 and T2, respectively, whereas rubbing (0.91%, p<0.05) only showed in the control. These results suggest that the provision of EE would be not negatively affected the performance of the gestating sows and could be led to improvement of the livestock welfare.

• The Journal of Engineering Geology
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• v.30 no.4
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• pp.457-468
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• 2020

Problems arising during pile design works for plant construction, civil and architecture work are mostly come from uncertainty of geotechnical characteristics. In particular, obtaining the N-value measured through the Standard Penetration Test (SPT) is the most important data. However, it is difficult to obtain N-value by drilling investigation throughout the all target area. There are many constraints such as licensing, time, cost, equipment access and residential complaints etc. it is impossible to obtain geotechnical characteristics through drilling investigation within a short bidding period in overseas. The geotechnical characteristics at non-drilling investigation points are usually determined by the engineer's empirical judgment, which can leads to errors in pile design and quantity calculation causing construction delay and cost increase. It would be possible to overcome this problem if N-value could be predicted at the non-drilling investigation points using limited minimum drilling investigation data. This study was conducted to predicted the N-value using an Artificial Neural Network (ANN) which one of the Artificial intelligence (AI) method. An Artificial Neural Network treats a limited amount of geotechnical characteristics as a biological logic process, providing more reliable results for input variables. The purpose of this study is to predict N-value at the non-drilling investigation points through patterns which is studied by multi-layer perceptron and error back-propagation algorithms using the minimum geotechnical data. It has been reviewed the reliability of the values that predicted by AI method compared to the measured values, and we were able to confirm the high reliability as a result. To solving geotechnical uncertainty, we will perform sensitivity analysis of input variables to increase learning effect in next steps and it may need some technical update of program. We hope that our study will be helpful to design works in the future.