• Korean Journal of Ecology and Environment
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• v.56 no.4
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• pp.375-383
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• 2023

To determine the cause of the population decline in Gobiobotia naktongensis, substrate preference and burying behaviour were investigated in this study. In general, the species was shown to prefer a substrate size of 1 mm or less, depending on the flow. In addition, the burying depth varied according to the size of the fish and increased with a decrease in water temperature. Our findings showed that the main cause of the population reduction was the physical changes in the substrate structure due to the dams or barrages construction. Notably, the accumulation of silt and mud in the substrate upon the formation of an upstream lentic water region for structural construction and bed armouring caused by scouring and reduced downstream inflow of fine sediment were deterministic in the fish habitat changes, causing problems in burying. As sand substrate structure is critical for the survival and inhabitation of psammophilous species, efficient strategies should be developed with proper habitat management to reduce the anthropogenic damage

• Korean Journal of Ecology and Environment
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• v.56 no.4
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• pp.363-374
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• 2023

The limitation in deriving the species richness representing the entire country of South Korea lies in its relatively short history of species field observations and the scattered observation data, which has been collected by various organizations in different fields. In this study, a comprehensive compilation of the observation data for plants held by agencies under the Ministry of Environment was conducted, enabling the construction of a time series dataset spanning over 100 years. The data integration was carried out using minimal criteria such as species name, observed location, and time (year) followed by data verification and correction processes. Based on the integrated plant species data, the comprehensive collection of plant species in South Korea has occurred predominantly since 2000, and the number of plant species explored through these surveys appears to be converging recently. The collection of species survey data necessary for deriving national-level biodiversity information has recently begun to meet the necessary conditions. Applying the Chao 2 method, the species richness of indigenous plants estimated at 3,182.6 for the 70-year period since 1951. A minimum cumulative period of 7 years is required for this estimation. This plant species richness from this study can be a baseline to study future changes in species richness in South Korea. Moreover, the integrated data with the estimation method for species richness used in this study appears to be applicable to derive regional biodiversity indices such as for local government units as well.

• Journal of Internet of Things and Convergence
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• v.10 no.1
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• pp.39-45
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• 2024

Container volume is a very important factor in accurate evaluation of port performance, and accurate prediction of effective port development and operation strategies is essential. However, it is difficult to improve the accuracy of container volume prediction due to rapid changes in the marine industry. To solve this problem, it is necessary to analyze the impact on port performance using the Internet of Things (IoT) and apply it to improve the competitiveness and efficiency of Busan Port. Therefore, this study aims to develop a prediction model for predicting the future container volume of Busan Port, and through this, focuses on improving port productivity and making improved decision-making by port management agencies. In order to predict port container volume, this study introduced the Extreme Gradient Boosting (XGBoost) technique of a machine learning model. XGBoost stands out of its higher accuracy, faster learning and prediction than other algorithms, preventing overfitting, along with providing Feature Importance. Especially, XGBoost can be used directly for regression predictive modelling, which helps improve the accuracy of the volume prediction model presented in previous studies. Through this, this study can accurately and reliably predict container volume by the proposed method with a 4.3% MAPE (Mean absolute percentage error) value, highlighting its high forecasting accuracy. It is believed that the accuracy of Busan container volume can be increased through the methodology presented in this study.

• Journal of the Korea Society of Computer and Information
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• v.28 no.10
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• pp.85-92
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• 2023

In this paper, we propose a method for automatically generating story-based abbreviated summaries from long-form dramas and movies. From the shooting stage, the basic premise was to compose a frame with illusion of depth considering the golden division as well as focus on the object of interest to focus the viewer's attention in terms of content delivery. To consider how to extract the appropriate frames for this purpose, we utilized elemental techniques that have been utilized in previous work on scene and shot detection, as well as work on identifying focus-related blur. After converting the videos shared on YouTube to frame-by-frame, we divided them into a entire frame and three partial regions for feature extraction, and calculated the results of applying Laplacian operator and FFT to each region to choose the FFT with relative consistency and robustness. By comparing the calculated values for the entire frame with the calculated values for the three regions, the target frames were selected based on the condition that relatively sharp regions could be identified. Based on the selected results, the final frames were extracted by combining the results of an offline change point detection method to ensure the continuity of the frames within the shot, and an edit decision list was constructed to produce an abbreviated summary of 62.77% of the footage with F1-Score of 75.9%

• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.6
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• pp.75-87
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• 2023

This study presents an experimental design for demonstrating the role of nature-based solutions to climate change in the landscape and garden sector. The study suggests spatial strategies for a carbon-neutral society and its role as a cultural industry. This paper describes the use of a low-maintenance garden as part of a strategy for carbon reduction with the goal of protecting the environment and forming a carbon-neutral society. To this end, this study involved the design and construction of a realistic model garden to provide scientific data on the functions, spatial elements, and carbon neutrality of carbon-reducing gardens. The target site is located in the Sejong National Arboretum. The test area in which the carbon-reducing function is measured is located in the centre of the site, and other spaces include dry gardens, community gardens, and flower gardens intended for exhibition and relaxation. The experimental area is divided into several smaller areas within which the carbon-reducing effect is analysed according to the amount of biochar installed, the planting density, and the plant species present. The application of facilities and construction methods to promote carbon reduction were based on the method known as '10 types of carbon gardening for the earth'. In the model garden, we employed rainwater utilization facilities and used low-carbon certified wood and local materials. The carbon reduction effect of each facility and construction method is compared and presented here. The results are expected to serve as an important basis for realizing a carbon-neutral society and can be used as a reference in various fields that require sustainable development, such as the garden industry.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.5
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• pp.230-238
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• 2023

Small and medium-sized food manufacturing enterprises are largely reliant on manual labor, from inputting raw materials to palletizing the final product. Recently, there has been a trend toward smartness and digitization through the implementation of robotics and sensor data technology. In this study, we examined the effectiveness of improvement through 3D simulation on two repetitive work processes within a food manufacturing company. These processes involve workers whose speed cannot match the capacity of the applied equipment. Two manual processes were selected: the weighing and packing process performed by workers after skewer assembly, and the manual batch process of counting randomly delivered frozen foods, packing (both internal and external), and palletizing. The production volume, utilization rate, and number of workers were chosen as verification indicators. As a result of the simulation for improving the 3D process, production increased by 13.5% and 56.8% compared to the existing process, respectively. This was particularly evident in the process of applying palletizing robots. In both processes, as the utilization rate and number of input workers decreased, robots could replace tasks with high worker fatigue, thereby reducing work overload. This study demonstrates the potential to visually compare the process flow improvement using 3D simulations and confirms the possibility of pre-validation for improvement.

• Journal of the Korea Society of Computer and Information
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• v.28 no.11
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• pp.29-42
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• 2023

In this paper, we propose a method to enhance the prediction accuracy of solar irradiance for three major South Korean cities: Seoul, Busan, and Incheon. Our method entails the development of five generative models-vanilla GAN, CTGAN, Copula GAN, WGANGP, and TVAE-to generate independent variables that mimic the patterns of existing training data. To mitigate the bias in model training, we derive values for the dependent variables using random forests and deep neural networks, enriching the training datasets. These datasets are integrated with existing data to form comprehensive solar irradiance prediction models. The experimentation revealed that the augmented datasets led to significantly improved model performance compared to those trained solely on the original data. Specifically, CTGAN showed outstanding results due to its sophisticated mechanism for handling the intricacies of multivariate data relationships, ensuring that the generated data are diverse and closely aligned with the real-world variability of solar irradiance. The proposed method is expected to address the issue of data scarcity by augmenting the training data with high-quality synthetic data, thereby contributing to the operation of solar power systems for sustainable development.

• Geophysics and Geophysical Exploration
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• v.26 no.4
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• pp.229-237
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• 2023

The use of artificial sources such as explosives and mechanical vibrations for seismic exploration in urban areas poses challenges, as the vibrations and noise generated can lead to complaints. As an alternative to artificial sources, the surface waves generated by traffic noise can be used to investigate the subsurface properties of urban areas. However, traffic noise takes the form of plane waves moving continuously at a constant speed. To apply existing surface wave processing/inversion techniques to traffic noise, the recorded data need to be transformed into a virtual shot gather format using seismic interferometry. In this study, various seismic interferometry methods were applied to traffic noise data, and the optimal method was derived by comparing the results in the Radon and F-K domains. Additionally, the data acquired using various receiver arrays were processed using seismic interferometry, and the results were compared and analyzed to determine the most optimal receiver array direction for exploration.

• Proceedings of the Plant Resources Society of Korea Conference
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• 2020.08a
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• pp.81-81
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• 2020

본 연구는 새싹인삼(Panax ginseng sprout) 재배용으로 이용하기 위한 묘삼(종삼)의 장기 저온저장 시 사용되는 필름의 종류가 묘삼의 출아율이나 생육에 영향을 미치는 지 조사하기 위해 수행되었다. 포장에 사용된 필름은 다공성물질인 제올라이트와 페그마타이트가 5% 함유된 50㎛ low density polyethylene(기능성 LDPE) 필름과 nylon/polyethylene 80 ㎛(Ny/PE) 필름에 묘삼을 100g씩 포장한 후 골판지 상자에 담아 -2℃의 저장고에서 10개월 동안 저장하면서 8개월째부터 2개월마다 시료를 꺼내어 5℃에서 5일 동안 온도 순화를 시킨 후 1차 조사에서는 육안조사로 실험실에서 건전한 묘삼과 부패 묘삼을 조사하였고, 건전한 묘삼만 새싹인삼 수경재배 농가에 재식한 후 2차 조사로 묘삼의 출아율과 출아된 묘삼이 새싹인삼으로 건전하게 생육한 비율을 조사하였다. 조사결과 Ny/PE 필름에 8개월 저장된 묘삼의 경우 1차 육안검사 시 뇌두부위가 검게 변하여 묘삼이 대부분 고사된 것으로 조사되었다. 필름 개봉 전 필름 내부의 O₂ 및 CO₂ 가스농도를 측정한 결과 O₂ 농도는 1.91%, CO₂ 농도는 38.9%로 측정되었고, 필름 개봉 시 알코올 냄새의 이취가 나는 것으로 보아 Ny/PE 필름으로 포장 된 묘삼이 -2℃의 저온저장기간 동안에도 호흡을 하면서 필름 내 산소를 완전히 소모하고 혐기적인 환경으로 변화시켜 대사활동이 불가능하였기 때문에 뇌두의 싹이 고사된 것으로 조사되었다. 반면 기능성 필름으로 포장한 묘삼은 저장 8개월에 정식 후 74.3%의 출아율을 보였고, 건전한 새싹인삼의 비율은 67.2%로 조사되었다. 정식 전·후 묘삼의 개체수 대비 건전 출아율의 비율은 56.7%를 나타내어 Ny/PE 필름으로 포장한 묘삼의 결과와 큰 차이를 보였다. 기능성필름의 개봉 전 필름 내부의 O₂ 및 CO₂ 가스농도를 측정한 결과 O₂ 농도는 12.9%, CO₂ 농도는 4.6%로 측정되어 묘삼의 저온저장 시 필름을 적용할 경우 공기의 유동이 원활이 이루어져 내부 O₂ 농도를 일정 수준 이상 유지해주는 필름을 사용하는 것이 묘삼의 출아와 생육에 좋은 것으로 조사되었다.

• Journal of the Korean Society of Radiology
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• v.17 no.6
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• pp.835-841
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• 2023

The aim of this study is to evaluate the diagnostic ability of dual-energy computed tomography (DECT) for Composition determination of urinary stones in phantom model. Seventeen cases with urinary stones who underwent DECT were enrolled in the study. The composition of the urinary stones was extracted from the seventeen patients were analyzed with DECT in phantom model with fresh pork. The volume scan method using Dual-energy software was used and the scanned image sets were assessed. All 17 urinary stones of the phantom model were analyzed according to the stone composition using DE stone Analysis were divided into uric acid stones (n=6, 35.29%) and non-uric acid stones (n=11, 64.71%). These urinary stones were pathologically confirmed. The mean attenuation values of uric acid stones at 135 kV, 100 kV and 80 kV was 348.87 ± 166.37 HU, 345.33 ± 151.18 HU and 337.94 ± 172.77 HU, respectively. The mean attenuation values of non-uric acid stones at 135 kV, 100 kV and 80 kV was 551.93 ± 297.09 HU, 747.04 ± 351.31 HU and 958.19 ± 424.72 HU, respectively. At 80 kV, uric acid stones and non-uric acid stones showed significant difference in the attenuation values(P<0.05). The attenuation values of DECT could differentiate the compositions of urinary stones between uric acid and non-uric acid stones at 80 kV in phantom model.