• The Journal of the Korea Contents Association
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• v.22 no.3
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• pp.309-321
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• 2022

As the spread of COVID19 has compelled activities in various fields to transform to adapt to the non-face-to-face environment, various activities have either already been transitioned into non-face-to-face methods or been searching for alternative methods to carry out activities in a non-face-to-face manner. However, there are apparent limits in handling this transition with the pre-existing digital technology. Ironically, said limitations are more apparent in the UX design field that has thus far emphasized resolutions based on digital technology. The reason for this stems from the nature of UX design which strongly emphasizes the importance of collaboration. Especially, in the field of UX design, problems are expected to surface under areas of communication and collaboration in workshops, which are productive means of collecting the ideas of interested parties and coming up with other new ideas. Based on the aforementioned rise of necessity, this study aims to assess the characteristics of workshops in the field of UX design and suggest an effective method of transitioning UX workshops into a non-face-to-face environment. Along the line of this process, this study has created a standard process in regards to design workshops with active creation, suggestion, and acceptance of ideas, among the various types of workshops defined by the Nielsen Norman Group. This study also developed a framework consisting of non-face-to-face workshops by combining with the standard process the methodologies of workshop activation and non-face-to-face services meant for communication and designing activities, and confirmed the adaptability and the effectiveness of said transition against various types of workshops. Application of the results of this study is expected to effectively lead the transition into the non-face-to-face environment and improve the collaborative efforts of the interested parties via workshops.

• Korean Journal of Remote Sensing
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• v.38 no.5_2
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• pp.695-706
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• 2022

Medium and high-resolution optical satellites have proven their effectiveness in detecting wildfire areas. However, smoke plumes generated by wildfire scatter visible light incidents on the surface, thereby interrupting accurate monitoring of the area where wildfire occurs. Therefore, a technology to extract smoke in advance is required. Deep learning technology is expected to improve the accuracy of smoke extraction, but the lack of training datasets limits the application. However, for clouds, which have a similar property of scattering visible light, a large amount of training datasets has been accumulated. The purpose of this study is to develop a smoke extraction technique using deep learning, and the limits due to the lack of datasets were overcome by using a cloud dataset on transfer learning. To check the effectiveness of transfer learning, a small-scale smoke extraction training set was made, and the smoke extraction performance was compared before and after applying transfer learning using a public cloud dataset. As a result, not only the performance in the visible light wavelength band was enhanced but also in the near infrared (NIR) and short-wave infrared (SWIR). Through the results of this study, it is expected that the lack of datasets, which is a critical limit for using deep learning on smoke extraction, can be solved, and therefore, through the advancement of smoke extraction technology, it will be possible to present an advantage in monitoring wildfires.

• Journal of Conservation Science
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• v.37 no.3
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• pp.209-219
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• 2021

In this study, the wind environment in an urban area near Sungneymun gate was numerically investigated in the cases of inflow directions. The wind fields for the target area were simulated using Geographic Information System data and Computational Fluid Dynamics model. Results, including vector fields, three-dimensional wind velocity components, and wind speeds, were analyzed to examine flow characteristics. Wind direction variability affected by buildings was shown in the target area. The complex flows around Sungneymun did not depend on the inflow direction as a boundary condition. The wind speed around Sungneymun was generally 3 times stronger at 14 m above ground level (AGL) compared to the surface wind at 2 m AGL and relatively high in the case of easterly inflow. The effect of wind was also analyzed to be relatively significant at the southeast side of Sungneymun. Thus, it was suggested that the assessment of wind environment affected by high-rise and high-density buildings should be necessary for the architectural heritage in urban areas.

• Korean Journal of Remote Sensing
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• v.39 no.1
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• pp.77-86
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• 2023

Ship detection is widely used in areas such as maritime security, maritime traffic, fisheries management, illegal fishing, and border control, and ship detection is important for rapid response and damage minimization as ship accident rates increase due to recent increases in international maritime traffic. Currently, according to a number of global and national regulations, ships must be equipped with automatic identification system (AIS), which provide information such as the location and speed of the ship periodically at regular intervals. However, most small vessels (less than 300 tons) are not obligated to install the transponder and may not be transmitted intentionally or accidentally. There is even a case of misuse of the ship'slocation information. Therefore, in this study, ship detection was performed using high-resolution optical satellite images that can periodically remotely detect a wide range and detectsmallships. However, optical images can cause false-alarm due to noise on the surface of the sea, such as waves, or factors indicating ship-like brightness, such as clouds and wakes. So, it is important to remove these factors to improve the accuracy of ship detection. In this study, false alarm wasreduced, and the accuracy ofship detection wasimproved by removing wake.As a ship detection method, ship detection was performed using machine learning-based random forest (RF), and convolutional neural network (CNN) techniquesthat have been widely used in object detection fieldsrecently, and ship detection results by the model were compared and analyzed. In addition, in this study, the results of RF and CNN were combined to improve the phenomenon of ship disconnection and the phenomenon of small detection. The ship detection results of thisstudy are significant in that they improved the limitations of each model while maintaining accuracy. In addition, if satellite images with improved spatial resolution are utilized in the future, it is expected that ship and wake simultaneous detection with higher accuracy will be performed.

• Clean Technology
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• v.28 no.3
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• pp.249-257
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• 2022

The adsorption equilibria of nitrogen on a region of nanoporous carbonaceous adsorbent with local molecular orientation (LMO) were calculated by grand canonical Monte Carlo simulation at 77.16 K. Regions of LMO of identical size were arranged on a regular lattice with uniform spacing. Microporosity was predominately introduced to the model by removing successive out-of-plane domains from the regions of LMO and tilting pores were generated by tilting the basic structure units. This pore structure is a more realistic model than slit-shaped pores for studying adsorption in nanoporous carbon adsorbents. Their porosities, surface areas, and pore size distributions according to constrained nonlinear optimization were also reported. The adsorption in slit shaped pores was also reported for reference. In the slit shaped pores, a clear hysteresis loop was observed in pores of greater than 5 times the nitrogen molecule size, and in capillary condensation and reverse condensation, evaporation occurred immediately at one pressure. In the LMO pore model, three series of local condensations at the basal slip plane, armchair slip plane and interconnected channel were observed during adsorption at pore sizes greater than about 6 times the nitrogen molecular size. In the hysteresis loop, on the other hand, evaporation occurred at one or two pressures during desorption.

• Journal of Korea Water Resources Association
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• v.55 no.11
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• pp.855-863
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• 2022

In this study, the Artificial Neural Network (ANN) was used to mapping air temperature in Seoul. MODerate resolution Imaging Spectroradiomter (MODIS) data was used as auxiliary data for mapping. For the ANN network topology optimizing, scatterplots and statistical analysis were conducted, and input-data was classified and combined that highly correlated data which surface temperature, Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), time (satellite observation time, Day of year), location (latitude, hardness), and data quality (cloudness). When machine learning was conducted only with data with a high correlation with air temperature, the average values of correlation coefficient (r) and Root Mean Squared Error (RMSE) were 0.967 and 2.708℃. In addition, the performance improved as other data were added, and when all data were utilized the average values of r and RMSE were 0.9840 and 1.883℃, which showed the best performance. In the Seoul air temperature map by the ANN model, the air temperature was appropriately calculated for each pixels topographic characteristics, and it will be possible to analyze the air temperature distribution in city-level and national-level by expanding research areas and diversifying satellite data.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.34 no.3
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• pp.82-92
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• 2022

In recent years, coastal and port structures have attempted to prevent wave-overtopping or provide waterfront areas by installing superstructures on the structural crowns. In general, in the design stage, the Goda formula acting on the front the structure is applied to calculate the wave pressure acting on the superstructure in consideration of the wave-runup of the design wave. However, the wave pressure exceeding the Goda wave pressure could generate depending on the installation location of the superstructure where the wave-overtopping occurs. This study analyzed the applicability of the Goda formula to the wave pressure calculation for the superstructure of the vertical structures through hydraulic model experiments and numerical simulations. Furthermore, this study investigated the magnitude of the wave pressure acting on the superstructure based on detailed numerical results. As a result, the wave pressure acting on the superstructure was up to 120% higher than the maximum wave pressure on the still water surface. In addition, the wave pressure increases exponentially with the Froude number computed by the overtopping water depth at the crown of the structure, and we proposed an empirical formula for predicting the wave pressure based on the Froude number.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.5
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• pp.753-763
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• 2022

In coastal and inland bays, where most of Korea's aquaculture is located, massive aquaculture damage occurs every year due to frequent anomalous high water temperatures. The interannual fluctuations of water temperature in July over the past four years (2018-2021) were the second largest since 1990 (after the period of 1994-1997) due to anomalous high temperatures, rainy seasons, and typhoons. Through analysis of heat flux and heat balance in areas of concern for high water temperatures (i.e., Cheonsu Bay, Gamak Bay, Guryongpo), the occurrence of high water temperatures in Cheonsu Bay and Gamak Bay in the summer seasons was confirmed to derive mainly from heat inflow through the sea surface from the air. Based on estimations of the average ocean heat transport rate in July for the four-year period of 2018-2021, Cheonsu Bay and Gamak Bay accounted for 13.5% and 62.3% outflow of the net heat flux, respectively. However, the ocean heat transport rate in Guryongpo Hajeong differed significantly from -174.5% to 132.5% of the net heat flux by year depending on the occurrence of cold water mass.

• Journal of Korean Society on Water Environment
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• v.39 no.2
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• pp.142-152
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• 2023

Infiltration is a process by which precipitation infuses into subsurface soils. The process determines the surface flow and baseflow volume, and it is one of most important hydrological processes regarding nonpoint source pollution management. Therefore, the Ministry of Environment has developed a guideline to determine the impervious area ratio to understand the hydrological process in administrative districts and watersheds. The impervious area ratio can be determined using land use or land cover maps. Three approaches were explored to determine the impervious area ratio in 25 districts in Seoul. The impervious area ratio was determined by employing the Land registration map and Land property data in the first approach, Land property map in the second approach, and Land cover map in the third approach. The ratio ranged from 38.96% to 83.01% in the first approach, 38.98% to 83.02% in the second approach, and 37.62% to 76.63% in the third approach. Although the ranges did not provide any significant differences in the approaches, some districts displayed differences up to 9.48% by the approach. These differences resulted from the fact that the data were land use or land cover, especially in the area of airport, residential complex area, and school sites. In other words, division of the pervious and impervious areas in an individual plot was not allowed in the Land registration map, while it was allowed in the Land cover map. Therefore, it was concluded that there is a need to revise the guideline so that a reasonable impervious area ratio can be determined in the districts.

• Journal of Korea Water Resources Association
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• v.55 no.4
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• pp.291-300
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• 2022

Artificial disturbance in mountainous areas increases the sensitivity to erosion by exposure of the subsoil with a low loam ratio to the surface. In this study, rainfall simulations were conducted to evaluate the erodibility of sand and loamy sand in the interrill erosion by the rainfall-induced sheet flow. The mean diameters of sand and loamy sand used in the experiment were 0.936 mm and 0.611 mm, respectively, and the organic matter content was 2.0% and 4.2%, respectively. In the experimental plot, the runoff coefficient of overland flow increased 1.16 times in loamy sand rather than sand. Mean sediment yields of loamy sand and sand by sheet erosion were 3.71kg/m²/hr and 1.13kg/m²/hr respectively. The erodibility, the rate of soil erosion for rainfall erosivity factor, was 3.65 times greater in loamy sand than in sand. As the gradient of the steep slope increased from 24° to 28°, the sediment concentration and the erodibility for two soils increased by about 20%. The erodibility factor K of sandy soils for small plots was overestimated compared to the measured erodibility. This means that RUSLE can overestimate the sediment yields by sheet erosion on sandy soils.