• Proceedings of the National Institute of Ecology of the Republic of Korea
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• v.3 no.2
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• pp.67-72
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• 2022

Ecological research relies on the interpretation of large amounts of visual data obtained from extensive wildlife surveys, but such large-scale image interpretation is costly and time-consuming. Using an artificial intelligence (AI) machine learning model, especially convolution neural networks (CNN), it is possible to streamline these manual tasks on image information and to protect wildlife and record and predict behavior. Ecological research using deep-learning-based object recognition technology includes various research purposes such as identifying, detecting, and identifying species of wild animals, and identification of the location of poachers in real-time. These advances in the application of AI technology can enable efficient management of endangered wildlife, animal detection in various environments, and real-time analysis of image information collected by unmanned aerial vehicles. Furthermore, the need for school education and social use on biodiversity and environmental issues using AI is raised. School education and citizen science related to ecological activities using AI technology can enhance environmental awareness, and strengthen more knowledge and problem-solving skills in science and research processes. Under these prospects, in this paper, we compare the results of our early 2013 study, which automatically identified African cichlid fish species using photographic data of them, with the results of reanalysis by CNN deep learning method. By using PyTorch and PyTorch Lightning frameworks, we achieve an accuracy of 82.54% and an F1-score of 0.77 with minimal programming and data preprocessing effort. This is a significant improvement over the previous our machine learning methods, which required heavy feature engineering costs and had 78% accuracy.

• Journal of Industrial Convergence
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• v.21 no.12
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• pp.37-43
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• 2023

In today's business landscape, collaboration and interoperability are crucial for organizational success and profitability. However, integrating operations across multiple organizations is challenging due to differing roles and policies in Identity and Access Management (IAM). User-centric identity (UCI) adopts a personalized approach to digital identity management, centering on the end-user for authentication and access control. It provides a decentralized system that ensures secure and customized access for each user. UCI aims to address complex security challenges by aligning access privileges with individual user requirements. This research delves into UCI's ability to streamline resource access amidst conflicting IAM roles and protocols across various organizations. The study presents a UCI-based multi-domain access control (MDAC) framework, which encompasses an ontology, a unified method for articulating access roles and policies across domains, and software services melding with UCI infrastructure. The goal is to enhance organizational resource management and decision-making by offering clear guidelines on access roles and policy management across diverse domains, ultimately boosting companies' return on investment.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.6B
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• pp.507-514
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• 2011

A numerical model has been developed by employing a finite element method to simulate the depth-averaged 2-D dispersion of the heat pollutant, which is an important pollutant material in natural streams. Among the finite element methods, the Streamline Upwind/Petrov Galerkin (SUPG) method was applied. Also both linear and quadratic elements can be applied so that irregular river boundaries can be easily represented. To show the movement of heat pollutants, the reaction term describing heat transfer was represented as an equation in which sink/source term is proportional to the difference between the equilibrium temperature and water surface temperature. The equation was expressed so that the water surface temperature changes according to the temperature transfer coefficient and the equilibrium temperature. For the calibration of the model developed, analytic and numerical results from a case of rectangular channel with full width continuous injection have been compared in a steady state. The comparisons showed that the numerical results were in good agreement with analytical solutions. The application site was selected from the downstream of Paldang dam to Jamsil submerged weir, and overall length of this site is about 22.5 km. The change of water temperature caused by the discharge from the Guri sewage treatment plant has been simulated, and results were similar to the observed data. Overall it is concluded that the developed model can represent the water temperature changes due to heat transport accurately. But the verification using observed data will further enhance the validity of the model.

• Journal of Energy Engineering
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• v.5 no.2
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• pp.160-169
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• 1996

Parametric studies are conducted for optimizing the integration design between gas turbine compressor and air separation unit (ASU) of integrated gasification combined cycle power plant. The present study adopts the ASU of double-distillation column process, from which integration conditions with compressor such as the heat exchanger condition between air and nitrogen, the amount and the pressure of extracted air are defined and mathematically formulated. The performance variations of the compressor integrated with ASU are analyzed by combining streamline curvature method and pressure loss models, and the predicted results are compared with the performance test results of actual compressors to verify the prediction accuracy. Using the present performance prediction method, the effects of pinch-point temperature difference (PTD) in the heat exchanger, the amount and the pressure of extracted air on compressor performances are quantitatively examined. As the extraction air amount or the PTD is increased, the pressure ratio and the power consumption of compressor are increased. The compressor efficiency deteriorates as the increase of the flow rate of air extracted at higher pressure level while improving at lower pressure air extraction. Furthermore, through the characteristic curve between generalized inlet condition and efficiency of compressor, optimal integration condition is presented to maximize the compressor efficiency.

• Journal of the Korean Association of Geographic Information Studies
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• v.5 no.4
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• pp.86-92
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• 2002

The feasibility of counting number of small vessels and position in Korean waters using the panchromatic imageries derived from the IRS-1C was tested. The parameters for interpretation of satellite's imageries of small vessels were location(position), size, shape, shadow, tone, texture and pattern, height and depth, situation and association with other vessels. The position of small vessels in the sea without GCP(ground control point) was considered to be inclusive in the satellite imagery with 35 km semi-diameter, denoting rough geographical position of the vessel. The size of vessel was measured by length from stem to stern of the vessel, distinguished by following wave on the surface water. Offshore fishing vessels were separated from merchant ships by their length smaller than 100 m. The shape of vessels on panchromatic imagery of IRS-1C appeared just streamline. In case of clouds which were similar to the shape of small vessels, we were able to distinguish between vessel and cloud by shadow of cloud in the water surface. The tone of sea surface was dark black while small vessel appeared bright white. Small vessel was distinguished from the rough texture of the sea surface and the regular pattern of the waves with white capes when weather was not so good. The situation of the fishing activity was estimated by information of fishing method related to the fishing boat such as the pair trawl in the Yellow Sea.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.7
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• pp.56-62
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• 2018

The bus bar is an electrical connection widely used for the power supply of skyscrapers and power distribution and industrial equipment electrical panels in industrial plants. There are various materials to be considered in the design of the bus bar, such as material based on the use environment, the sectional area according to the power capacity, the length of the surface circumference, and the tightening method. Even with a bus bar manufactured to a size of sufficient power capacity in the design, if the actual tightening is incorrect, it may lead to fire due to deterioration. For these reasons, a variety of research on the temperature rise of the electrical contact point has continued. However, the temperature rise of the contacts is a consequence of the result, not a direct cause. In this paper, the influence of contact resistance on the fastening force and the overlapping section of the bus bar are investigated by measuring the change in resistance from building the specimen. A total of eight bus bar specimens were manufactured and measured. Resistance was measured by varying the clamping force and the interval between overlapping sections when the specimens were crossed. We propose a safe power connection model by analyzing the contribution of these factors to the actual contact resistance change.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.6
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• pp.696-701
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• 2018

The nitrogen oxides generated during combustion reactions have a great influence on the generation of acid rain and fine dust. As an NOx reduction method, exhaust gas recirculation combustion using Coanda nozzles capable of recirculating a large amount of exhaust gas with a small amount of air has recently been utilized. In this study, for the burner outlet with dual end opening, the use of a recirculation burner was investigated for the distribution of the pressure, streamline, temperature, combustion reaction rate and nitrogen oxides using computational fluid analysis. The gas mixed with the combustion air and the recirculated exhaust gas flow in the tangential direction of the circular cylinder burner, so that there is a region with low pressure in the vicinity of the fuel nozzle exit. As a result, a reverse flow is formed in the central portion of the burner near the center of the circular cylinder burner and the exhaust gas is discharged to the outside region of the circular cylinder burner. The combustion reaction occurs on the right side of the burner and the temperature and NOx distribution are relatively higher than those on the left side of the burner. It was found that the average NOx production decreased from an air flow ratio of 1.0 to 1.5. When the air flow ratio is 1.8, the NOx production increases abruptly. It is considered that the NOx production reaction increases exponentially with temperature when the air ratio is more than 1.5 and the NOx production reaction rate increases rapidly on the right-hand side of the burner.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.4
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• pp.317-325
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• 2020

UAV (Unmanned Aerial Vehicle) photogrammetry has recently emerged as a means of obtaining highly precise and rapid spatial information due to its cost-effectiveness and high efficiency. However, current procedures or regulations for quantitative quality verification methods and certification processes for UAV-images are insufficient. In addition, the current verification method for image quality is not evaluated by an MTF (Modulation Transfer Function) analysis or edge response analysis, which can analyze the degree of contrast including image resolution, and only relies on the GSD (Ground Sample Distance) analysis. Therefore, in this study, the edge response analysis using a Slanted edge target was performed along with GSD analysis to confirm the necessity of analyzing edge response analysis in UAV-images quality analysis. Furthermore, a Matlab GUI-based software tool was developed to help streamline the edge response analysis. As a result, we confirmed the need for edge response analysis since the outputs of the edge response analysis from the same GSD had significantly different outcomes. Additionally, we found that the quality of the edge response analysis of UAV-images is proportional to the performance of the camera mounted on the UAV.

• Journal of Bio-Environment Control
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• v.29 no.3
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• pp.285-292
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• 2020

Because the inner environment of greenhouse has a direct impact on crop production, many studies have been performed to develop technologies for controlling the environment in the greenhouse. However, it is difficult to apply the technology developed to all greenhouses because those studies were conducted through empirical experiments in specific greenhouses. It takes a lot of time and cost to develop the models that can be applicable to all greenhouse in real situation. Therefore studies are underway to solve this problem using computer-based simulation techniques. In this study, a model was developed to predict the inner environment of glass greenhouse using CFD simulation method. The developed model was validated using primary and secondary heating experiment and daytime greenhouse inner temperature data. As a result of comparing the measured and predicted value, the mean temperature and uniformity were 2.62℃ and 2.92%p higher in the predicted value, respectively. R² was 0.9628, confirming that the measured and the predicted values showed similar tendency. In the future, the model needs to improve by applying the shape of the greenhouse and the position of the inner heat exchanger for efficient thermal energy management of the greenhouse.

• Journal of Intelligence and Information Systems
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• v.29 no.4
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• pp.325-345
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• 2023

In the rapidly evolving domain of e-commerce, our study presents a cohesive approach to enhance customer satisfaction prediction from online reviews, aligning methodological innovation with practical insights. We integrate the RFE-SHAP feature selection with LDA topic modeling to streamline predictive analytics in e-commerce. This integration facilitates the identification of key features-specifically, narrowing down from an initial set of 28 to an optimal subset of 14 features for the Random Forest algorithm. Our approach strategically mitigates the common issue of overfitting in models with an excess of features, leading to an improved accuracy rate of 84% in our Random Forest model. Central to our analysis is the understanding that certain aspects in review content, such as quality, fit, and durability, play a pivotal role in influencing customer satisfaction, especially in the clothing sector. We delve into explaining how each of these selected features impacts customer satisfaction, providing a comprehensive view of the elements most appreciated by customers. Our research makes significant contributions in two key areas. First, it enhances predictive modeling within the realm of e-commerce analytics by introducing a streamlined, feature-centric approach. This refinement in methodology not only bolsters the accuracy of customer satisfaction predictions but also sets a new standard for handling feature selection in predictive models. Second, the study provides actionable insights for e-commerce platforms, especially those in the clothing sector. By highlighting which aspects of customer reviews-like quality, fit, and durability-most influence satisfaction, we offer a strategic direction for businesses to tailor their products and services.