In Jeju Island which has peculiarity for its geological features and hydrology system, hydrological factor analysis for the effective water management is necessary. Because in-situ hydro-meteorological data is affected by surrounding environment, the in-situ dataset could not be the spatially representative for the study area. For this reason, remote sensing data may be used to overcome the limit of the in-situ data. In this study, applicability assessment of MOD16 evapotranspiration data, Globas Land Data Assimilation System (GLDAS) based evapotranspiration/soil moisture data, and Advanced SCATterometer (ASCAT) soil moisture product which were evaluated their applicability on other study areas was conducted. In the case of evapotranspiration, comparison with total precipitation and flux-tower based evapotranspiration were conducted. And for soil moisture, 6 in-situ data and ASCAT soil moisture product were compared on each site. As a result, 57% of annual precipitation was calculated as evapotranspiration, and the correlation coefficient between MOD16 evapotranspiration and GLDAS evapotranspiration was 0.759, which was a robust value. The correlation coefficient was 0.434, indicating a relatively low fit. In the case of soil moisture, in the case of the GLDAS data, the RMSE value was less than 0.05 at all sites compared to the in-situ data, and a statistically significant result was obtained as a result of the significance test of the correlation coefficient. However, for satellite data, RMSE over than 0.05 were found at Wolgak and there was no correlation at Sehwa and Handong points. It is judged that the above results are due to insufficient quality control and spatial representation of the evapotranspiration and soil moisture sensors installed in Jeju Island. It is estimated as the error that appears when adjacent to the coast. Through this study, the necessity of improving the existing ground observation data of hydrometeorological factors is emphasized.
Kim, Yongwon;Byeon, Sangdon;Park, Jinseok;Woo, Soyoung;Kim, Seongjoon
Journal of Korea Water Resources Association
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v.54
no.10
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pp.819-833
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2021
This study is to evaluate applicability of linkage modeling using PHABSIM (Physical Habitat Simulation System) and SWAT (Soil and Water Assessment Tool) and to estimate ecological flow for target fishes of Andong downstream (4,565.7 km2). The SWAT was established considering 2 multi purpose dam (ADD, IHD) and 1 streamflow gauging station (GD). The SWAT was calibrated and validated with 9 years (2012 ~ 2020) data of 1 stream (GD) and 2 multi-purpose dam (ADD, IHD). For streamflow and dam inflows (GD, ADD and IHD), R2, NSE and RMSE were 0.52 ~ 0.74, 0.48 ~ 0.71, and 0.92 ~ 2.51 mm/day respectively. As a result of flow duration analysis for 9 years (2012 ~ 2020) using calibrated streamflow, the average Q185 and Q275 were 36.5 m3/sec (-1.4%) and 23.8 m3/sec (0%) respectively compared with the observed flow duration and were applied to flow boundary condition of PHABSIM. The target stream was selected as the 410 m section where GD is located, and stream cross-section and hydraulic factors were constructed based on Nakdong River Basic Plan Report and HEC-RAS. The dominant species of the target stream was Zacco platypus and the sub-dominant species was Puntungia herzi Herzenstein, and the HSI (Habitat Suitability Index) of target species was collected through references research. As the result of PHABSIM water level and velocity simulation, error of Q185 and Q275 were analyzed -0.12 m, +0.00 m and +0.06 m/s, +0.09 m/s respectively. The average WUA (Weighted Usable Area) and ecological flow of Zacco platypus and Puntungia herzi Herzenstein were evaluated 76,817.0 m2/1000m, 20.0 m3/sec and 46,628.6 m2/1000m, 9.0 m3/sec. This results indicated Zacco platypus is more adaptable to target stream than Puntungia herzi Herzenstein.
Moon, Jong Pil;Bang, Ji Woong;Hwang, Jeongsu;Jang, Jae Kyung;Yun, Sung Wook
Journal of Bio-Environment Control
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v.30
no.4
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pp.419-428
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2021
In order to develope a mobile-based greenhouse energy calculation program, firstly, the overall thermal transmittance of 10 types of major covers and 16 types of insulation materials were measured. In addition, to estimate the overall thermal transmittance when the cover and insulation materials were installed in double or triple layers, 24 combinations of double installations and 59 combinations of triple installations were measured using the hotbox. Also, the overall thermal transmittance value for a single material and the thermal resistance value were used to calculate the overall thermal transmittance value at the time of multi-layer installation of covering and insulating materials, and the linear regression equation was derived to correct the error with the measured values. As a result of developing the model for estimating thermal transmittance when installing multiple layers of coverings and insulating materials based on the value of overall thermal transmittance of a single-material, the model evaluation index was 0.90 (good when it is 0.5 or more), indicating that the estimated value was very close to the actual value. In addition, as a result of the on-site test, it was evaluated that the estimated heat saving rate was smaller than the actual value with a relative error of 2%. Based on these results, a mobile-based greenhouse energy calculation program was developed that was implemented as an HTML5 standard web-based mobile web application and was designed to work with various mobile device and PC browsers with N-Screen support. It had functions to provides the overall thermal transmittance(heating load coefficient) for each combination of greenhouse coverings and thermal insulation materials and to evaluate the energy consumption during a specific period of the target greenhouse. It was estimated that an energy-saving greenhouse design would be possible with the optimal selection of coverings and insulation materials according to the region and shape of the greenhouse.
Kim, Gu;Kim, Gyeong Rip;Sung, Soon Ki;Kwak, Jong Hyeok
Journal of the Korean Society of Radiology
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v.13
no.4
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pp.503-508
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2019
In short a binary value according to a change in the tube voltage by using one of VOLUME AXIAL MODE of scanning techniques of chest CT image quality evaluation in order to obtain high image and to present the appropriate tube voltage. CT instruments were GE Revolution (GE Healthcare, Wisconsin USA) model and Phantom used Pediatric Whole Body Phantom PBU-70. The test method was examined in Volume Axial mode using the pediatric protocol used in the Y university hospital of mass-produced material. The tube voltage was set to 70kvp, 80kvp, 100kvp, and mAs was set to smart mA-ODM. The mean SNR difference of the heart was $-4.53{\pm}0.26$ at 70 kvp, $-3.34{\pm}0.18$ at 80 kvp, $-1.87{\pm}0.15$ at 100 kvp, and SNR at 70 kvp was about -2.66 higher than 100 kvp and statistically significant (p<0.05) In the Lung SNR mean difference analysis, $-78.20{\pm}4.16$ at 70 kvp, $-79.10{\pm}4.39$ at 80 kvp, $-77.43{\pm}4.72$ at 100 kvp, and SNR at 70 kvp at about -0.77 higher than 100 kvp were statistically significant. (p<0.05). Lung CNR mean difference was $73.67{\pm}3.95$ at 70 kvp, $75.76{\pm}4.25$ at 80 kvp, $75.57{\pm}4.62$ at 100 kvp and 20.9 CNR at 80 kvp higher than 70 kvp and statistically significant (p<0.05) At 100 kvp of tube voltage, the SNR was close to 1 while maintaining the quality of the heart image when 70 kvp and 80 kvp were compared. However, there is no difference in SNR between 70 kvp and 80 kvp, and 70 kvp can be used to reduce the radiation dose. On the other and, CNR showed an approximate value of 1 at 70 kvp. There is no difference between 80 kvp and 100 kvp. Therefore, 80 kvp can reduce the radiation dose by pediatric chest CT. In addition, it is possible to perform a scan with a short scan time of 0.3 seconds in the volume axial mode test, which is useful for pediatric patients who need to move or relax.
Journal of the Korean Association of Geographic Information Studies
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v.22
no.3
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pp.82-98
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2019
The importance of spatial information is rapidly rising. In particular, 3D spatial information construction and modeling for Real World Objects, such as smart cities and digital twins, has become an important core technology. The constructed 3D spatial information is used in various fields such as land management, landscape analysis, environment and welfare service. Three-dimensional modeling with image has the hig visibility and reality of objects by generating texturing. However, some texturing might have occlusion area inevitably generated due to physical deposits such as roadside trees, adjacent objects, vehicles, banners, etc. at the time of acquiring image Such occlusion area is a major cause of the deterioration of reality and accuracy of the constructed 3D modeling. Various studies have been conducted to solve the occlusion area. Recently the researches of deep learning algorithm have been conducted for detecting and resolving the occlusion area. For deep learning algorithm, sufficient training data is required, and the collected training data quality directly affects the performance and the result of the deep learning. Therefore, this study analyzed the ability of detecting the occlusion area of the image using various image quality to verify the performance and the result of deep learning according to the quality of the learning data. An image containing an object that causes occlusion is generated for each artificial and quantified image quality and applied to the implemented deep learning algorithm. The study found that the image quality for adjusting brightness was lower at 0.56 detection ratio for brighter images and that the image quality for pixel size and artificial noise control decreased rapidly from images adjusted from the main image to the middle level. In the F-measure performance evaluation method, the change in noise-controlled image resolution was the highest at 0.53 points. The ability to detect occlusion zones by image quality will be used as a valuable criterion for actual application of deep learning in the future. In the acquiring image, it is expected to contribute a lot to the practical application of deep learning by providing a certain level of image acquisition.
The purpose of this study was to develop a smartphone based voice therapy program for patients with voice disorders. Contents of voice therapy were collected through analysis of mobile contents related to voice therapy in Korea, experts and users' demand survey, and the program was developed using Android Studio. Content needed for voice therapy was collected through analysis of mobile contents related to voice therapy. The user satisfaction evaluation for application was conducted for five patient with functional voice disorders. The results showed that the mobile contents related to voice therapy in Korea were mostly related to breathing, followed by voice and singing, but only 13 applications were practically practiced for voice therapy. Expert and user demand surveys showed that the patients and therapists both had a high need for content that could provide voice training in places other than the treatment room. Based on this analysis, 'Home Voice Trainer', an smartphone based voice therapy program, was developed. Home Voice Trainer is an application for voice therapy and management based on Android smartphones. It is designed to train voice therapy activities at home that have been trained offline. In addition, the records of voice training of patients were managed online so that patients can maintain voice improvement through continuous voice consulting even after the end of voice therapy. User evaluations show that patients are satisfied with the difficulty and content of voice therapy programs provided by home voice trainers, but lack of a portion of user interface, such as the portion of home button and interface between screens. Further study suggests the clinical application of home voice trainer to the patients with voice disorders. It is expected that the development study and the clinical application of smart contents related to voice therapy will be actively conducted.
The Journal of Sustainable Design and Educational Environment Research
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v.21
no.3
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pp.1-13
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2022
This study is a case study to identify the spatial composition and structural problems of existing schools for spatial innovation as a future school that can operate a credit system for old high schools and establish a mid-to-long-term arrangement plan as a credit system operating school capable of various teaching and learning in the future. The study results are as follows: First, most of the problems of the old high schools entailed that there was very poor connectivity between buildings as most of them were arranged in a single, standard design-type unit building and distributed in multiple buildings. In addition, the floor plan of each building is suggested to be a structure in which student exchange and rest functions cannot be achieved during the break period due to the spatial composition of the classroom and hallway concepts. Second, in the direction of the high school space configuration for future school space innovation, the arrangement plan should be established by reflecting the collective arrangement in consideration of the shortening of the movement route and the expansion of subject areas due to the movement of students on the premise of the subject classroom system. Moreover, it is desirable to provide a square-type space for rest and exchange in the central area where communication and exchange are possible according to the moving class. Third, as the evaluation criteria for relocating old high schools, a space program is prepared based on the number of classes in the future, and legal analysis of school land use and land use efficiency analysis considering regional characteristics are conducted. Based on such analysis data, mid-to-long-term land use plans and space arrangement plans for the entire school space such as the school facility complex are established.
Snow is an essential climate factor that affects the climate system and surface energy balance, and it also has a crucial role in water balance by providing solid water stored during the winter for spring runoff and groundwater recharge. In this study, statistical analysis of Local Data Assimilation and Prediction System (LDAPS), Modern.-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), and ERA5-Land snow depth data were used to evaluate the applicability in South Korea. The statistical analysis between the Automated Synoptic Observing System (ASOS) ground observation data provided by the Korea Meteorological Administration (KMA) and the reanalysis data showed that LDAPS and ERA5-Land were highly correlated with a correlation coefficient of more than 0.69, but LDAPS showed a large error with an RMSE of 0.79 m. In the case of MERRA-2, the correlation coefficient was lower at 0.17 because the constant value was estimated continuously for some periods, which did not adequately simulate the increase and decrease trend between data. The statistical analysis of LDAPS and ASOS showed high and low performance in the nearby Gangwon Province, where the average snowfall is relatively high, and in the southern region, where the average snowfall is low, respectively. Finally, the error variance between the four independent snow depth data used in this study was calculated through triple collocation (TC), and a merged snow depth data was produced through weighting factors. The reanalyzed data showed the highest error variance in the order of LDAPS, MERRA-2, and ERA5-Land, and LDAPS was given a lower weighting factor due to its higher error variance. In addition, the spatial distribution of ERA5-Land snow depth data showed less variability, so the TC-merged snow depth data showed a similar spatial distribution to MERRA-2, which has a low spatial resolution. Considering the correlation, error, and uncertainty of the data, the ERA5-Land data is suitable for snow-related analysis in South Korea. In addition, it is expected that LDAPS data, which is highly correlated with other data but tends to be overestimated, can be actively utilized for high-resolution representation of regional and climatic diversity if appropriate corrections are performed.
Journal of Korea Entertainment Industry Association
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v.13
no.3
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pp.193-202
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2019
This study focuses on what changes are required as to a curriculum of dance department in the university in the age of the 4th industrial revolution. By comparing and analyzing the curricula of dance department in the five universities in Seoul, five academic subjects as to curricula of dance department, which covers what to learn for dance education in the age of the 4th industrial revolution, are presented. First, dance integrative education, the integration of creativity and science education, can be referred to as a subject that stimulates ideas and creativity and raises artistic sensitivity based on STEAM. Second, the curriculum characterized by prediction of the future prospect through Big Data can be utilized well in dealing with dance performance, career path of dance-majoring people, and job creation by analyzing public opinion, evaluation, and feelings. Third, video education. Seeing the images as modern major media tends to occupy most of the expressive area of art, dance by dint of video enables existing dance work to be created as new form of art, expanding dance boundaries in academic and performing art viewpoint. Fourth, VR and AR are essential techniques in the era of smart media. Whether upcoming dance studies are in the form of performance or education or industry, for VR and AR to be digitally applied into every relevant field, keeping with the time, learning about VR and AR is indispensable. Last, the 4th industrial revolution and the curriculum of dance art are needed to foresee the changes in the 4th industrial revolution and to educate changes, development and seeking in dance curriculum.
Humans have adapted and evolved to natural light. However, as humans stay in indoor longer in modern times, the problem of biorhythm disturbance has been induced. To solve this problem, research is being conducted on lighting that reproduces the correlated color temperature(CCT) of natural light that varies from sunrise to sunset. In order to reproduce the CCT of natural light, multiple LED light sources with different CCTs are used to produce lighting, and then a control index DB is constructed by measuring and collecting the light characteristics of the combination of input currents for each light source in hundreds to thousands of steps, and then using it to control the lighting through the light characteristic matching method. The problem with this control method is that the more detailed the steps of the combination of input currents, the more time and economic costs are incurred. In this paper, an LED lighting control method that applies interpolation and combination calculation based on the minimum spectral power distribution information for each light source is proposed to reproduce the CCT of natural light. First, five minimum SPD information for each channel was measured and collected for the LED lighting, which consisted of light source channels with different CCTs and implemented input current control function of a 256-steps for each channel. Interpolation calculation was performed to generate SPD of 256 steps for each channel for the minimum SPD information, and SPD for all control combinations of LED lighting was generated through combination calculation of SPD for each channel. Illuminance and CCT were calculated through the generated SPD, a control index DB was constructed, and the CCT of natural light was reproduced through a matching technique. In the performance evaluation, the CCT for natural light was provided within the range of an average error rate of 0.18% while meeting the recommended indoor illumination standard.
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