• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.1D
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• pp.63-72
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• 2009

This study aims at establishing the decision-making support system for the highway assets, long-term performance presumption and evaluation of asset value, which are appropriate for Korea, and proposing the methods of the optimal engineering method and the timing decision for the preventive maintenance through the project evaluation, the optimization method and life-cycle analysis related to the highways. In order to supplement the current problem of the near-sighted budget management system, which chooses the maintenance place of the highway, depending on the level of the budget with fixed amount, the long-term required budget prediction system and the economy principle were introduced, so that the pavement agency can predict the level of the required budget, and it was aimed to develop the pavement asset evaluation system to maintain the performance of the highway with the minimum of the cost. In the use of the highway pavement asset evaluation system, to maintain the appropriate level of the pavement evaluation index, when the budget was efficiently established in the reference of the required maintenance budget for the chosen section of the highway in the year concerned, it was possible to analyze the most rational pavement maintenance budget. With this result, it is estimated to prevent the unnecessary waste of budget in advance, and through the development of the decision-making system for the long-term performance presumption and the asset value estimation of the pavement, it is expected to able to analyze the previous evaluation of the project related to the highway and the feasibility of introduction.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.399-401
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• 2022

A definitive diagnosis to classify the breast malignancy status may be achieved by microscopic analysis using surgical open biopsy. However, this procedure requires experts in the specializing of histopathological image analysis directing to time-consuming and high cost. To overcome these issues, deep learning is considered practically efficient to categorize breast cancer into benign and malignant from histopathological images in order to assist pathologists. This study presents a pre-trained convolutional neural network model architecture with a 100% fine-tuning scheme and Adagrad optimizer to classify the breast cancer histopathological images into benign and malignant using a 40× magnification BreaKHis dataset. The pre-trained architecture was constructed using the InceptionResNetV2 model to generate a modified InceptionResNetV2 by substituting the last layer with dense and dropout layers. The results by demonstrating training loss of 0.25%, training accuracy of 99.96%, validation loss of 3.10%, validation accuracy of 99.41%, test loss of 8.46%, and test accuracy of 98.75% indicated that the modified InceptionResNetV2 model is reliable to predict the breast malignancy type from histopathological images. Future works are necessary to focus on k-fold cross-validation, optimizer, model, hyperparameter optimization, and classification on 100×, 200×, and 400× magnification.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.171-173
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• 2022

The 4th industrial revolution technology is developing people's lives more efficiently. GIS provided on the Internet services such as traffic information and time information makes people getting more quickly to destination. National geographic information service(NGIS) and each local government are making basic data to investigate SOC accessibility for analyzing optimal point. To construct the shortest distance, the accessibility from the starting point to the arrival point is analyzed. Applying road network map, the starting point and the ending point, the shortest distance, the optimal accessibility is calculated by using Dijkstra algorithm. The analysis information from multiple starting points to multiple destinations was required more than 3 steps of manual analysis to decide the position for the optimal point, within about 0.1% error. It took more time to process the many-to-many (M×N) calculation, requiring at least 32G memory specification of the computer. If an optimal proximity analysis service is provided at a desired location more versatile, it is possible to efficiently analyze locations that are vulnerable to business start-up and living facilities access, and facility selection for the public.

• International Area Studies Review
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• v.15 no.1
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• pp.173-193
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• 2011

Most of the research regarding economic effects of policy loans has thus far been focused on whether policy loans can improve the financial status or the management performance of small and medium enterprises (SMEs). Unlike previous researches, this study implemented an empirical analysis focused on the contribution of policy loans to easing the liquidity restriction of investment. To analyze whether investment liquidity restriction can be alleviated or not, this study attempted an empirical analysis utilizing the nonlinear Euler equation induced through optimization of investment and GMM (generalized method of moments) as its analysis methodology. With the SMEs that received policy financing from the Small and medium Business Corporation (SBC) in 2004, this study analyzed three years of panel data before(2001~2003) and after(2004~2006) receipt of policy loans. According to the empirical results, it appears that policy loans had effects on resolving liquidity restriction of investment, implying that policy financing eases the liquidity restriction of SME investment and would contribute to the growth and development of SMEs. Further, I checked robustness of empirical results using Tobin's q model. The empirical results also support that policy loans help to resolve liquidity constraint. With these results, it is understood that the critical view to date, which has emphasized the ineffectiveness of policy financing due to it having no or insignificant economic effects, may be wrong.

• Journal of the Korean Recycled Construction Resources Institute
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• v.11 no.3
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• pp.226-233
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• 2023

In this study, two phases were conducted to investigate the direct injection of gaseous CO₂ into cement mortar. The aim was to advance carbon capture, utilization, and storage (CCUS) technology by harnessing industrial waste CO₂ from the domestic ready-mixed concrete industry. In the first phase, the factors influencing the physical properties of cement mortar when using gaseous CO₂ were identified. This included a review of materials to achieve physical properties comparable to a reference formulation. As a result of this phase, it was confirmed that traditional approaches, such as adjusting the water-to-cement ratio, had limitations in achieving the desired physical properties. Consequently, the second phase focused on the optimization of CO₂-injected mortar. This involved studying the CO₂ application and mixing method for cement mortar. Changes in properties were observed when gaseous CO₂ was injected into the mortar. The optimal injection quantity and time to enhance the compressive strength of mortar were determinded. As a result, this study indicated that an extra mixing time exceeding 120 seconds was necessary, compared to conventional mortar. The optimal CO₂ injection rate was identified as 0.1 to 0.2 % by weight of cement, taking both flowability and compressive strength performance into account. Increasing the CO₂ injection time did not further enhance strength. For this approach to be employed as a CCUS technology, additional studies are required, including a microstructural analysis evaluating the amount of immobilized CO₂.

• Phonetics and Speech Sciences
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• v.15 no.3
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• pp.75-82
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• 2023

Automatic speech recognition (ASR) has been revolutionized with deep learning-based approaches, among which self-supervised learning methods have proven to be particularly effective. In this study, we aim to enhance the performance of OpenAI's Whisper model, a multilingual ASR system on the Korean language. Whisper was pretrained on a large corpus (around 680,000 hours) of web speech data and has demonstrated strong recognition performance for major languages. However, it faces challenges in recognizing languages such as Korean, which is not major language while training. We address this issue by fine-tuning the Whisper model with an additional dataset comprising about 1,000 hours of Korean speech. We also compare its performance against a Transformer model that was trained from scratch using the same dataset. Our results indicate that fine-tuning the Whisper model significantly improved its Korean speech recognition capabilities in terms of character error rate (CER). Specifically, the performance improved with increasing model size. However, the Whisper model's performance on English deteriorated post fine-tuning, emphasizing the need for further research to develop robust multilingual models. Our study demonstrates the potential of utilizing a fine-tuned Whisper model for Korean ASR applications. Future work will focus on multilingual recognition and optimization for real-time inference.

• Membrane Journal
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• v.33 no.6
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• pp.362-368
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• 2023

This research article explores the application of Polymer of Intrinsic Microporosity (PIM-1) as a cutting-edge material for CO₂ gas separation membranes in response to the escalating global concern over climate change and the imperative to reduce greenhouse gas emissions. The study delves into the synthesis, molecular weight control, and fabrication of PIM-1 membranes, providing comprehensive insights through various characterization techniques. The intrinsic microporosity of PIM-1, arising from its unique crosslinked and rigid structure, is harnessed for selective gas permeation, particularly of carbon dioxide. The article emphasizes the tunable chemical properties of PIM-1, allowing for customization and optimization of gas separation membranes. By controlling the molecular weight, higher molecular weight (H-PIM-1) membranes are demonstrated to exhibit superior CO₂ permeability and selectivity compared to lower molecular weight counterparts (L-PIM-1). The study's findings highlight the critical role of molecular weight in tailoring PIM-1 membrane properties, contributing to the advancement of next-generation membrane technologies for efficient and selective CO₂ capture-an essential step in addressing the pressing global challenge of climate change.

• Journal of Animal Science and Technology
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• v.65 no.4
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• pp.779-791
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• 2023

This study aimed to assess the effects of embryonic developmental stage, quality grade, and fresh or frozen/thawed conditions on the pregnancy rate and sex ratio of live offspring in Hanwoo (Bos taurus coreanae) cows. The quality and developmental stage of in vivo-derived (IVD) transferred embryos were evaluated using the standard criteria of the International Embryo Technology Society. The recipient cows were synchronized using conventional (estradiol benzoate and progesterone) protocols before embryo transfer. Embryos were transferred to 297 cows, and pregnancy was monitored for 60-70 days after embryo transfer. The pregnancy rates of fresh and frozen/thawed embryos were 56.90% and 52.49%, respectively. Pregnancy rates varied according to embryo quality (56.18% for grade 1 vs. 36.67% for grade 2). Pregnancy rates also varied by developmental stage and cryopreservation (67.86% vs. 63.49% for stage 4-1, 64.00% vs. 54.72% for 5-1, and 50.00% vs. 47.83% for 6-1, in fresh embryos vs. frozen/thawed embryos, respectively). For stage 7-1, the pregnancy rates were 72.73% for fresh embryos and 20.00% for frozen/thawed embryos. In 66 fresh embryos, the sex ratio of live offspring was 5:5, whereas it was 4(female):6(male) for frozen/thawed embryos among the 95 frozen/thawed embryos. The miscarriage rate was approximately 3% higher for frozen/thawed embryos than for fresh embryos (18.1% for fresh vs. 21.1% for frozen). Seasonal fertility rates were 33.3% in spring, 55.67% in summer, 52.8% in autumn, 60.0% in winter. The following male-to-female ratios were observed in different seasons: 6.7:3.3 in spring, 4.0:6.0 in summer, 5.5:4.5 in autumn, and 3.3:6.7 in winter. The current data revealed no significant differences in pregnancy rates between fresh and frozen/thawed IVD embryos. However, there was a lower pregnancy rate with advanced-stage frozen/thawed embryos (stage 7-1). The current study provides comprehensive results for the better optimization of embryo transfer in Hanwoo cattle to obtain the desired fertility rate, pregnancy rate, and sex ratio of calves. These results provide important insights into the factors that influence the viability and success of IVD embryo transfer in Hanwoo cows and may have practical applications for improving breeding programs and reducing production costs.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.36 no.6
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• pp.638-646
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• 2023

Recently, active research has been conducted to enhance the power characteristics and thermal stability of lithium-ion batteries (LiBs) by modifying separators using a ceramic coating method. However, since the thermal properties and surface features of the separator vary depending on the characteristics of the ceramic powders applied to the separator, it is crucial to manufacture ceramic powders optimized for the separator's performance. In this study, we evaluated the characteristics of three types of α-alumina (A-1, A-2, and A-3) produced with varying dispersant contents and milling times, in addition to commercial α-alumina (AES-11). Subsequently, the optimized powders (A-3) were coated onto the separator using an aqueous binder for comparison with the characteristics of an AES-11 coated separator and an uncoated PE separator. The A-3 coated separator improved electrolyte wettability with a low contact angle (44.69°) and increased puncture strength (538 gf). Furthermore, it exhibited excellent thermal stability, with a shrinkage value of 5.64% when exposed to 140℃ for 1 hour, compared to the AES11 coated separator (6.09%) and the bare PE separator (69.64%).

• Economic and Environmental Geology
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• v.56 no.5
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• pp.515-532
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• 2023

Bentonite, predominantly consists of expandable clay minerals, is considered to be the suitable buffering material in high-level radioactive waste disposal repository due to its large swelling property and low permeability. Additionally, the bentonite has large cation exchange capacity and specific surface area, and thus, it effectively retards the transport of leaked radionuclides to surrounding environments. This study aims to review the thermodynamic sorption models for four radionuclides (U, Am, Se, and Eu) and eight bentonites. Then, the thermodynamic sorption models and optimized sorption parameters were precisely analyzed by considering the experimental conditions in previous study. Here, the optimized sorption parameters showed that thermodynamic sorption models were related to experimental conditions such as types and concentrations of radionuclides, ionic strength, major competing cation, temperature, solid-to-liquid ratio, carbonate species, and mineralogical properties of bentonite. These results implied that the thermodynamic sorption models suggested by the optimization at specific experimental conditions had large uncertainty for application to various environmental conditions.