• Applied Chemistry for Engineering
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• v.34 no.3
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• pp.213-220
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• 2023

Mixed-matrix membranes (MMMs), which are composed of a polymer matrix filled with high-performance fillers as a dispersed phase, have been intensively studied for gas separations for the past 30 years. It has been demonstrated that MMMs exhibit superior gas separation performance compared to polymer membranes and are more scalable than polycrystalline membranes. Despite their potential, the commercialization of MMMs has yet to be reported due to several challenging issues. One of the major challenges of MMMs is the non-ideal interface between the continuous polymer phase and dispersed phase, which can result in defect formation (i.e., interfacial voids, etc.). With respect, many MMM studies have focused on addressing the issues through scientific approaches. The engineering approaches for facile and effective large-scale fabrication of MMMs, however, have been relatively underestimated. In this review paper, a novel strategy for fabricating MMMs in a facile and scalable manner using in situ metal-organic framework (MOF) formation is introduced. This new MMM fabrication methodology can effectively address the issues facing current MMMs, likely facilitating the commercialization of MMMs.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.43-45
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• 2021

The short-term quantitative precipitation prediction (QPF) system is important socially and economically to prevent damage from severe weather. Recently, many studies for short-term QPF model applying the Deep Neural Network (DNN) has been conducted. These studies require the sophisticated pre-processing because the mistreatment of various and vast meteorological data sets leads to lower performance of QPF. Especially, for more accurate prediction of the non-linear trends in precipitation, the dataset needs to be carefully handled based on the physical and dynamical understands the data. Thereby, this paper proposes the following approaches: i) refining and combining major factors (weather radar, terrain, air temperature, and so on) related to precipitation development in order to construct training data for pattern analysis of precipitation; ii) producing predicted precipitation fields based on Convolutional with ConvLSTM. The proposed algorithm was evaluated by rainfall events in 2020. It is outperformed in the magnitude and strength of precipitation, and clearly predicted non-linear pattern of precipitation. The algorithm can be useful as a forecasting tool for preventing severe weather.

• Composites Research
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• v.36 no.3
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• pp.162-166
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• 2023

Although composite materials are increasingly utilized in general high-strength structures, the demand of performance characteristics as the multifunctional materials has been increased especially in the area of complex electronic devices. While the heat dissipation properties of devices are typically required properties, control of thermal property of composite material especially in the vertical direction is one of the problems to be solved due to its lamination process. In this study, CFRP was manufactured using the Vacuum filtration method for three types of solvent and CFs. In the composite material manufacturing process, the effect of solvent was examined using three solvents where solvents are most frequently used for the dispersion of fibers. Morphology of fiber was observed through a microscope to confirm the arrangement of CFs in the vertical direction. The alignment of fiber was examined through the measurement of the thermal conductivity of the manufactured specimen. For the thermal conductivity measurement, the higher thermal conductivity was obtained with the lower aspect ratio of CF. For the thermal conductivity in the through-plane direction, 8.687 W/m·K, 10.322 W/m·K, and 13.005 W/m·K of thermal conductivity was measured in the DMF, NMP and Acetone, respectively.

• Journal of Korea Water Resources Association
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• v.55 no.4
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• pp.257-266
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• 2022

Inundation damage is increasing every year due to localized heavy rain and an increase of rainfall exceeding the design frequency. Accordingly, the importance of hydraulic structures for flood control and defense is also increasing. The hydraulic structures are designed according to its purpose and performance, and the amount of flood is an important calculation factor. However, in Korea, design rainfall is used as input data for hydrological analysis for the design of hydraulic structures due to the lack of sufficient data and the lack of reliability of observation data. Accurate probability rainfall and its temporal distribution are important factors to estimate the design rainfall. In practice, the regression equation of temporal distribution for the design rainfall is calculated using the cumulative rainfall percentage of Huff's quartile method. In addition, the 6^th order polynomial regression equation which shows high overall accuracy, is uniformly used. In this study, the optimized regression equation of temporal distribution is derived using the variable selection method according to the principle of parsimony in statistical modeling. The derived regression equation of temporal distribution is verified through the significance test. As a result of this study, it is most appropriate to derive the regression equation of temporal distribution using the stepwise selection method, which has the advantages of both forward selection and backward elimination.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.2A
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• pp.93-102
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• 2010

The numerical analysis and safety assessment by construction stages were considered the essential examination particular in order to solving the unstability of long-span bridges in the middle a construction. When estimating structural response characteristics by the construction stage analysis of long-span bridges, the influence of the near-field ground motion (NFGM) would be evaluated as a critical factor for the seismic design because it indicates clearly different aspects from the existing input earthquake motion data. Therefore, this study re-examined the response aspect of long-span bridges considering NFGM characteristics based on the response spectrum result, and advanced the presented numerical analysis program by the related research for conducting the construction stage analysis and reliability assessment of long-span bridges efficiently. The excellency of various construction schemes was assessed using the time history analysis result of critical member considering NFGM characteristics. For evaluating quantitative safety level, the reliability analysis was conducted considering the influence of external uncertainties included in random variables, and presented the safety index and failure probability of the critical construction stage by NFGM characteristics. In addition, the reliability result was examined the influence of internal uncertainties using monte carlo simulation (MCS), and assessed the distribution aspect of the essential analysis result. It is expected that this study will provide the basic information for the construction safety improvement when performing seismic design of long-span bridges considering NFGM characteristics.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.4A
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• pp.315-327
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• 2009

In this study, the static test of CFT truss girders for different f/L ratios was conducted to determine how the ultimate strength of the CFT truss girder was affected by different f/L ratios. A total of two CFT truss girders were constructed and tested under bending condition. The length of all specimens is 20,000 mm. The CFT truss girder is a tubular truss composed of chord members made of concrete-filled circular tubes. The main parameter analyzed in the experimental study was the f/L ratio. This factor was experimentally investigated to assess their influence on ultimate strength and stiffness. The test results show that CFT truss girder has good elastic-plastic property and ductility. The presence of the f/L ratios in CFT truss girders alters its ultimate strength because of the global stiffness of the CFT truss girders. The ultimate strength of CFT truss girders increases as the f/L ratio increases. If the f/L ratio of the CFT truss girders increases twofold, the ultimate strengths increase by 80%. The CFT truss girders showed that they retained large deformation capacity, even after reaching the ultimate strength. Results of this investigation demonstrated the potential for efficiently using a CFT truss as a bridge girder.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.212-215
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• 2022

In the era of so-called digital transformation today, the need for the construction and utilization of big data in various fields has increased. Today, a lot of data is produced and stored in a digital device and media-friendly manner, but the production and storage of data for a long time in the past has been dominated by print books. Therefore, the need for Optical Character Recognition (OCR) technology to utilize the vast amount of print books accumulated for a long time as big data was also required in line with the need for big data. In this study, a system for digitizing the structure and content of a document object inside a scanned book image is proposed. The proposal system largely consists of the following three steps. 1) Recognition of area information by document objects (table, equation, picture, text body) in scanned book image. 2) OCR processing for each area of the text body-table-formula module according to recognized document object areas. 3) The processed document informations gather up and returned to the JSON format. The model proposed in this study uses an open-source project that additional learning and improvement. Intelligent OCR proposed as a system in this study showed commercial OCR software-level performance in processing four types of document objects(table, equation, image, text body).

• Membrane Journal
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• v.33 no.6
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• pp.427-438
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• 2023

In this study, in order to improve the performance of the reverse osmosis membrane with high water flux and high salt rejection, a study was conducted on the evaluation of characteristics according to the curing temperature and time during various additives and interfacial polymerization. The morphology of the membrane with no additives and the membrane with additives both showed a "rigid-and-valley" structure, confirming that the polyamide layer was successfully polymerized on the surface of the porous support layer. In addition, the additive of 2-Ethyl-1,3-hexanediol (EHD) had improved hydrophilicity and water flux, which was confirmed by measuring the contact angle. Finally, a highly permeable TFC membrane with NaCl and MgSO₄ salt rejection of 97.78% and 98.7% and a high water flux of 3.31 L/(m²⋅h⋅bar) was prepared.

• The Journal of the Convergence on Culture Technology
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• v.9 no.6
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• pp.967-971
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• 2023

Recently, a variety of AI-based platform services are available, and one of them is ChatGPT that processes a large quantity of data in the natural language and generates an answer after self-learning. ChatGPT can perform various tasks including software programming in the IT sector. Particularly, it may help generate a simple program and correct errors using C Language, which is a major programming language. Accordingly, it is expected that ChatGPT is capable of effectively using Verilog HDL, which is a hardware language created in C Language. Verilog HDL synthesis, however, is to generate imperative sentences in a logical circuit form and thus it needs to be verified whether the products are executed properly. In this paper, we aim to select small-scale logical circuits for ease of experimentation and to verify the results of circuits generated by ChatGPT and human-designed circuits. As to experimental environments, Xilinx ISE 14.7 was used for module modeling, and the xc3s1000 FPGA chip was used for module embodiment. Comparative analysis was performed on the use area and processing time of FPGA to compare the performance of ChatGPT products and Verilog HDL products.

• Phonetics and Speech Sciences
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• v.15 no.4
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• pp.109-118
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• 2023

Cardiac arrest is a critical medical emergency where immediate response is essential for patient survival. This is especially true for Out-of-Hospital Cardiac Arrest (OHCA), for which the actions of emergency medical services in the early stages significantly impact outcomes. However, in Korea, a challenge arises due to a shortage of dispatcher who handle a large volume of emergency calls. In such situations, the implementation of a machine learning-based OHCA detection program can assist responders and improve patient survival rates. In this study, we address this challenge by developing a machine learning-based OHCA detection program. This program analyzes transcripts of conversations between responders and callers to identify instances of cardiac arrest. The proposed model includes an automatic transcription module for these conversations, a text-based cardiac arrest detection model, and the necessary server and client components for program deployment. Importantly, The experimental results demonstrate the model's effectiveness, achieving a performance score of 79.49% based on the F1 metric and reducing the time needed for cardiac arrest detection by 15 seconds compared to dispatcher. Despite working with a limited dataset, this research highlights the potential of a cardiac arrest detection program as a valuable tool for responders, ultimately enhancing cardiac arrest survival rates.