• 한국태양에너지학회 논문집
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• 제34권4호
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• pp.111-122
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• 2014

The purpose of this study is to understand daily variation of short-wave radiation trends according to the state of surface and observation of atmosphere conditions in downtown and suburban observation area. The followings are main results from this study. 1) We found out daily air temperature variation of downtown is less than that of suburban area because of bigger heat capacity of artificial elements such as massive buildings and pavements. 2) It is more effective to estimate of air condition by water vapor pressure than relative humidity in the atmosphere. 3) The difference of solar radiation ratio between downtown and suburban area is dependant on different atmosphere conditions at two observation stations.

• 대한물리의학회지
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• 제11권2호
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• pp.83-91
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• 2016

PURPOSE: The purpose of this study was to determine the efficacy of dual-task action observation training (AOT) and single-task AOT related with daily living task on walking ability and ADL performance in chronic stroke patients. METHODS: Twenty-seven chronic stroke subjects were included in the study. They were randomly assigned to three task categorieds as follows: whole dual-task AOT or partial dual-task AOT or single-task AOT rehabilitation. Whole dual-task AOT observed the movement at once and partial dual-task AOT observed the movement divided into 4 parts related functional gait and activities of daily living task for 2 minutes 30 seconds. Single-task AOT observed the movement related functional gait for 2 minutes 30 seconds. Both groups had physical training session for 12 minutes 30 seconds. The study was conducted for four weeks, with three training sessions a week, for twelve weeks. All subjects were evaluated for their walking ability and activities of daily living through devices, 10m walking test (10MWT), dynamic gait index (DGI), and Korea-Modified Barthel Index (K-MBI). RESULTS: A significant improvement of walking ability and ADL performance happened among dual-task AOT subjects, compared with a single-task AOT subjects, during the 4-weeks course treatment. The results of the study showed statistically significant differences in 10MWT (p<0.05) and DGI (p<0.05), and K-MBI (p<0.05). CONCLUSION: Our results indicated that dual-task AOT has a positive additional impact on recovery of walking ability and ADL performance in chronic stroke patients.

• 대기
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• 제33권1호
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• pp.1-20
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• 2023

Holding the longest observation data from April 1904, Busan is one of the essential points to understand the climate variability of the Korean Peninsula without missing data since implementing the modern weather observation of the South Korea. Busan is featured by coastal areas and affected by various climate factors and fluctuations. This study aims to investigate climate variability and changes in climatic variables, extremes, and several weather indexes. The statistically significant change points in daily mean rainfall intensity and temperature were found in 1964 and 1965. Based on the change point detection, 117 years were divided into two periods for daily mean rainfall intensity and temperature, respectively. In the long-term temperature analysis of Busan, the increasing trend of the daily maximum temperature during the period of 1965~2021 was larger than the daily mean temperature and the daily minimum temperature. Applying Ensemble Empirical Mode Decomposition, daily maximum temperature is largely affected by the decadal variability compared to the daily mean and minimum temperature. In addition, the trend of daily precipitation intensity from 1964~2021 shows a value of about 0.50 mm day^-1, suggesting that the rainfall intensity has increased compared to the preceding period. The results in extremes analysis demonstrate that return values of both extreme temperatures and precipitation show higher values in the latter than in the former period, indicating that the intensity of the current extreme phenomenon increases. For Wet-Bulb Globe Temperature (effective humidity), increasing (decreasing) trend is significant in Busan with the second (third)-largest change among four stations.

• 대기
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• 제28권3호
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• pp.273-289
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• 2018

This paper evaluates daily precipitation products from Integrated Multisatellite Retrievals for Global Precipitation Measurement (IMERG), Tropical Rainfall Measuring Mission Multisatellite (TRMM) Precipitation Analysis (TMPA), and the Climate Prediction Center Morphing Method (CMORPH), validated against gauge observation over South Korea and gauge-based analysis data East Asia during one year from June 2014 to May 2015. It is found that the three products effectively capture the seasonal variation of mean precipitation with relatively good correlation from spring to fall. Among them, IMERG and TMPA show quite similar precipitation characteristics but overall underestimation is found from all precipitation products during winter compared with observation. IMERG shows reliably high performance in precipitation for all seasons, showing the most unbiased and accurate precipitation estimation. However, it is also noticed that IMERG reveals overestimated precipitation for heavier precipitation thresholds. This assessment work suggests the validity of the IMERG product for not only seasonal precipitation but also daily precipitation, which has the potential to be used as reference precipitation data.

• 대기
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• 제26권4호
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• pp.697-709
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• 2016

This study estimates and evaluates the extreme value of 30 m-resolution daily maximum and minimum temperatures over South Korea, using inverse distance weighting (IDW), parameter-elevation regression on independent slopes model (PRISM) and generalized extreme value (GEV) method. The three experiments are designed and performed to find the optimal estimation strategy to obtain extreme value. First experiment (EXP1) applies GEV firstly to automated surface observing system (ASOS) to estimate extreme value and then applies IDW to produce high-resolution extreme values. Second experiment (EXP2) is same as EXP1, but using PRISM to make the high-resolution extreme value instead of IDW. Third experiment (EXP3) firstly applies PRISM to ASOS to produce the high-resolution temperature field, and then applies GEV method to make high resolution extreme value data. By comparing these 3 experiments with extreme values obtained from observation data, we find that EXP3 shows the best performance to estimate extreme values of maximum and minimum temperatures, followed by EXP1 and EXP2. It is revealed that EXP1 and EXP2 have a limitation to estimate the extreme value at each grid point correctly because the extreme values of these experiments with 30 m-resolution are calculated from only 60 extreme values obtained from ASOS. On the other hand, the extreme value of EXP3 is similar to observation compared to others, since EXP3 produces 30m-resolution daily temperature through PRISM, and then applies GEV to that result at each grid point. This result indicates that the quality of statistically produced high-resolution extreme values which are estimated from observation data is different depending on the combination and procedure order of statistical methods.

• 한국농공학회논문집
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• 제58권4호
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• pp.37-46
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• 2016

This study is to estimate COMS (Communication, Ocean and Meteorological Satellite) daily land surface temperature (LST) of Korea Peninsula from 15 minutes interval COMS LST (COMS LST-15) satellite data. Using daily observed LST data of Automated Agriculture Observing System (AAOS) 11 stations from January 2013 to May 2015, the COMS daily LST was compared and validated. For the representative time for daily mean LST value from COMS LST-15, the time of 23 : 45 and 0:00 showed minimum deviations with AAOS daily LST. The time zone from 23 : 45 to 1:15 and from 7 : 30 to 9 : 45 showed high determination coefficient (R2) of 0.88 and 0.90 respectively. The daily COMS LST by averaging COMS LST-15 of the day showed R2 of 0.83. From the 5 cases of results, the COMS daily LST could be extracted from the average LST by using 15 minutes data from 7 : 30 to 9 : 45.

• Journal of Biosystems Engineering
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• 제25권2호
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• pp.123-130
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• 2000

A forcasting scheme for daily solar irradiance on agricultural field sis proposed by application of chaos theory to a long term observation data. It was conducted by reconstruction of phase space, attractor analysis, and Lyapunov analysis. Using the methodology , it was determined whether evolution of the five climatic data such as daily air temperature , water temperature , relative humidity, solar radiation, and wind speed are chaotic or not. The climatic data were collected for three years by an automated weather station at Hwasung-gun, Kyonggi-province. The results showed that the evolution of solar radiation was chaotic , and could be predicted. The prediction of the evolution of the solar radiation data was executed by using ' local optimal linear reconstruction ' algorithm . The RMS value of the predicting for the solar radiation evolution was 4.32 MJ/$m^2$ day. Therefore, it was feasible to predict the daily solar radiation based on the chaos theory.

• 한국전문물리치료학회지
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• 제18권2호
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• pp.27-34
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• 2011

The aim of this study was to determine the effect of action-observation training on arm function in people with stroke. Fourteen chronic stroke patients participated in action-observation training. Initially, they were asked to watch video that illustrated arm actions used in daily activities; this was followed by repetitive practice of the observed actions for 3 times a week for 3 weeks. Each training session lasted 30 min. All subject participated 12 training session on 9 consecutive training days. For the evaluation of the clinical status of standard functional scales, Wolf motor function test was carried out at before and after the training and at 2 weeks after the training. Friedman test and Wilcoxon signed rank test was used to analyze the results of the clinical test. There was a significant improvement in the upper arm functions after the 3-week action-observation training, as compared to that before training. The improvement was sustained even at two weeks after the training. This result suggest that action observation training has a positive additional impact on recovery of stroke-induced motor dysfunctions through the action observation-action execution matching system, which includes in the mirror neuron system.

• 대한원격탐사학회지
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• 제26권2호
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• pp.277-285
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• 2010

세계 최초로 개발된 정지궤도 해색탑재체(GOCI-I, Geostationary Ocean Color Imager-I)이 2010년 6월에 발사될 예정이다. GOCI-I의 수명은 약 7년 이므로 위성개발 소요기간 약 6년을 고려하면 제2호 정지궤도 해색탑재체의 개발을 위한 임무 및 이용자 요구사양을 준비해야할 시점이 되었다. 제2호의 임무는 우선 1호의 임무를 승계하는 것이므로 제1호와 유사한 관측 임무를 갖지만 가장 큰 차이점은 장기 기후 변화에 대응한 지구규모적 관측에 있다. 그리고 기존의 Local 관측은 그 공간해상도의 성능을 더 향상시킨 $250m{\times}250m$로 하였고, 1호에 비하여 부족한 band 수를 보강하여 12 개로 하였다. 어장정보를 위한 야간 관측을 위한 Panchromatic band를 추가하였다. 동시에 한반도 주변 고정된 영역 관측기능을 구름이 없는 해역 혹은 special event area로 신축적으로 변경 시킬 수 있는 기능을 갖게 함으로써 위성자료의 활용도를 크게 높이었다. 위성 운용은 1호와 같은 일 8회 관측, 그리고 Global mode인 full disk 관측에서는 일 1-2회 정도 관측할 수 있도록 하였다. 그리고 본 연구에서는 지금까지 위성개발 추진방법의 문제점을 해소한 개선된 개발 추진 방안에 대하여서도 제시하였다. 그 외 제2호의 하드웨어적인 구조 및 디자인에 대하여서는 국내외 개발사와의 상호협의가 필요하다.

• 한국농공학회논문집
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• 제61권2호
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• pp.63-74
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• 2019

The objective of this study was to evaluate the influence of rainfall observation network on daily dam inflow using artificial neural networks(ANNs). Chungju Dam and Soyangriver Dam were selected for the study watershed. Rainfall and dam inflow data were collected as input data for construction of ANNs models. Five ANNs models, represented by Model 1 (In watershed, point rainfall), Model 2 (All in the Thiessen network, point rainfall), Model 3 (Out of watershed in the Thiessen network, point rainfall), Model 1-T (In watershed, area mean rainfall), Model 2-T (All in the Thiessen network, area mean rainfall), were adopted to evaluate the influence of rainfall observation network. As a result of the study, the models that used all station in the Thiessen network performed better than the models that used station only in the watershed or out of the watershed. The models that used point rainfall data performed better than the models that used area mean rainfall. Model 2 achieved the highest level of performance. The model performance for the ANNs model 2 in Chungju dam resulted in the $R^2$ value of 0.94, NSE of 0.94 $NSE_{ln}$ of 0.88 and PBIAS of -0.04 respectively. The model-2 predictions of Soyangriver Dam with the $R^2$ and NSE values greater than 0.94 were reasonably well agreed with the observations. The results of this study are expected to be used as a reference for rainfall data utilization in forecasting dam inflow using artificial neural networks.