• Science of Emotion and Sensibility
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• v.23 no.4
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• pp.33-40
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• 2020

As the number of automobile registrations increases and luxury expectations grow, consumers are increasingly interested in indoor environment of vehicles. Therefore, manufacturers have an increasing interest in improving the indoor comfort as well as automobile performance. Research on indoor automobile comfort can help manufacturers increase driver satisfaction and reduce driver stress and discomfort, thereby reducing the risk of traffic accidents. Using electroencephalogram (EEG) measurements, we investigated the change in comfort and comfortable temperature according to the ventilating seat temperature change for both men and women. Results showed that the sensation of comfort was statistically significantly higher at 25℃ than at 28℃. Secondly, there was no statistically significant difference in temperature-based comfort feeling between male and female subjects. In the future, if the correlation between the driver's comfort feeling and the change in ventilating seat temperature is analyzed, it is possible to reduce traffic accidents caused by human error and reduce the electric energy consumption of the automobile.

• Journal of Climate Change Research
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• v.2 no.3
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• pp.175-189
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• 2011

In this research, we describe the methodology and the quantification about GHG reduction effects, expected by optimization of operation mode according to establishing additional heat storage system of Bundang Combined Cycle Power Plant. As an intermediate form of General Combined Cycle Power Plant and Heat supply only district heating plant, Bundang Combined Cycle Power Plant(and Ilsan, Anyang, Bucheon) is possible to satisfy demand for the electrical load and thermal load capacity at the same time through changes to the operation mode itself. Therefore, through the operating transition of high-efficiency mode that the condenser cooling water is recovered and supplied to district heat and cooling, establishing additional heat storage system have flexible supply ability at the power and heat market. In this research, We calculated using the operating performance for the last three years(2008~2010) and efficiency of each mode-specific values. As a result, GHG reduction effects were calculated as $97.95kg_{-}CO_2/Gcal$ per heat energy 1 Gcal supplied at the heat storage system and we expected emmision reduction effect about $13,500Ton_{-}CO_2/yr$.

• Journal of the Korean Applied Science and Technology
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• v.38 no.3
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• pp.903-913
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• 2021

Three-type PVC membranes denoted by AEM-1, AEM-2, and AEM-3 with a cross-linked anion-exchange group were prepared by substitution reaction of PVC with triethyldiamine (TEDA), 1,4-dimethylpiperazine (DMP), and 1,4-bis(imidazol-1-ylmethyl)benzene (BIB) in cyclohexanone, respectively. We confirmed the successful preparation of the AEM-1, AEM-2, and AEM-3 via ionic conductivity (S/cm), water uptake (%), contact angle, ion-exchange capacity (m_eq/g), thermal properties, SEM and XPS analysis, respectively. The electrochemical capacitor experiments using PVC membrane with cross-linked anion-exchange group in organic electrolytes were performed. The prepared AEM-1, AEM-2 AEM-3 have a good stability by charge and discharge performance in organic electrolyte. As a result, the AEM-2 and AEM-3 membrane based on PVC prepared by the solvent casting method after substituent reaction is suitable for the use as a separator in organic electrochemical capacitor (supercapacitor).

• KIPS Transactions on Software and Data Engineering
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• v.11 no.7
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• pp.299-306
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• 2022

In recent, sensors embedded in robots, equipment, and circuits have become common, and research for diagnosing device failures by learning measured sensor data is being actively conducted. This failure diagnosis study is divided into a classification model for predicting failure situations or types and a regression model for numerically predicting failure conditions. In the case of a classification model, it simply checks the presence or absence of a failure or defect (Class), whereas a regression model has a higher learning difficulty because it has to predict one value among countless numbers. So, the reason that regression modeling is more difficult is that there are many irregular situations in which it is difficult to determine one output from a similar input when predicting by matching input and output. Therefore, in this paper, we focus on input and output data with periodicity, analyze the input/output relationship, and secure regularity between input and output data by performing sliding window-based input data patterning. In order to apply the proposed method, in this study, current and temperature data with periodicity were collected from MMC(Modular Multilevel Converter) circuit system and learning was carried out using ANN. As a result of the experiment, it was confirmed that when a window of 2% or more of one cycle was applied, performance of 97% or more of fit could be secured.

• Smart Media Journal
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• v.11 no.9
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• pp.21-29
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• 2022

Ultra Violet(UV) is gradually being replaced with LED instead of general UV lamps. However, the light efficiency of UV LED is still lower than that of the general lamp, and the light efficiency is also low. Due to the current environment and technical problems of UV lamps, the LED replacements are gradually being made. In this study, a new package design and analysis were performed to increase the lifetime and performance of UV LEDs. A new packaging for UV LED were designed and implemented. The new packaging for UV LED was constructed to improve light efficiency. And the electrical and optical characteristics were analyzed respectively. To improve the optical efficiency in UV LED package, the Al has been used based on high reflectivity and applying the optimal lens focusing. Compared to the existing silver Ag, the light efficiency was improved by about 30% or more, and it was confirmed that the light output degradation characteristic was improved by about 10% in the newly applied optical device chip.

• Journal of the Korean Recycled Construction Resources Institute
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• v.11 no.4
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• pp.349-354
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• 2023

This study wa s conducted a s pa rt of ma ximizing the use of ca rbon dioxide by a pplying CCU(Ca rbon Ca pture, Utiliza tion) a mong technologies for reducing CO₂ in the cement industry. In a carbon dioxide curing environment, changes in carbonation depth and changes in basic physical properties by age due to the mixing of carbonation reaction accelerators were usually targeted at Portland cement paste. In addition, in order to check the fixed amount of CO₂ in the concrete field, a thermal analysis method was applied to evaluate CaCO₃ decarbonization at high temperatures. As a result of the evaluation, it was confirmed that the carbonation depth in the cured body significantly increased due to the incorporation of CRA in the carbonation depth diffusion performance. In addition, it was confirmed that the weight reduction rate increased by 23.8 % and 40.77 %, respectively, compared to Plain, in the order of curing conditions for constant temperature and humidity and curing conditions for carbonation chambers, so it was confirmed that the amount of excellent CaCO₃ produced by the addition of CRA increased as the concentration of CO₂ increased.

• Nuclear Engineering and Technology
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• v.56 no.3
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• pp.803-811
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• 2024

Nuclear accidents such as Fukushima Daiichi have highlighted the potential of passive safety systems to replace or complement active safety systems as part of the overall prevention and/or mitigation strategies. In addition, passive systems are key features of Small Modular Reactors (SMRs), for which they are becoming almost unavoidable and are part of the basic design of many reactors available in today's nuclear market. Nevertheless, their potential to significantly increase the safety of nuclear power plants still needs to be strengthened, in particular the ability of computer codes to determine their performance and reliability in industrial applications and support the safety demonstration. The PASTELS project (September 2020-February 2024), funded by the European Commission "Euratom H2020" programme, is devoted to the study of passive systems relying on natural circulation. The project focuses on two types, namely the SAfety COndenser (SACO) for the evacuation of the core residual power and the Containment Wall Condenser (CWC) for the reduction of heat and pressure in the containment vessel in case of accident. A specific design for each of these systems is being investigated in the project. Firstly, a straight vertical pool type of SACO has been implemented on the Framatome's PKL loop at Erlangen. It represents a tube bundle type heat exchanger that transfers heat from the secondary circuit to the water pool in which it is immersed by condensing the vapour generated in the steam generator. Secondly, the project relies on the CWC installed on the PASI test loop at LUT University in Finland. This facility reproduces the thermal-hydraulic behaviour of a Passive Containment Cooling System (PCCS) mainly composed of a CWC, a heat exchanger in the containment vessel connected to a water tank at atmospheric pressure outside the vessel which represents the ultimate heat sink. Several activities are carried out within the framework of the project. Different tests are conducted on these integral test facilities to produce new and relevant experimental data allowing to better characterize the physical behaviours and the performances of these systems for various thermo-hydraulic conditions. These test programmes are simulated by different codes acting at different scales, mainly system and CFD codes. New "system/CFD" coupling approaches are also considered to evaluate their potential to benefit both from the accuracy of CFD in regions where local 3D effects are dominant and system codes whose computational speed, robustness and general level of physical validation are particularly appreciated in industrial studies. In parallel, the project includes the study of single and two-phase natural circulation loops through a bibliographical study and the simulations of the PERSEO and HERO-2 experimental facilities. After a synthetic presentation of the project and its objectives, this article provides the reader with findings related to the physical analysis of the test results obtained on the PKL and PASI installations as well an overall evaluation of the capability of the different numerical tools to simulate passive systems.

• Journal of the Korean Wood Science and Technology
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• v.45 no.5
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• pp.559-571
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• 2017

This study was conducted to determine the adhesive performances of plywoods affected by layering direction and the amounts of thermoplastic films. The face and back layers of veneer were hardwood species (Mixed light hardwood) and core layer veneer was radiata pine (Pinus radiata D. Don). Thermoplastic film used as adhesive were polypropylene (PP) film and polyethylene (PE) film. Thermal analysis and tensile strength were investigated on each films. As a result, the melting temperature of PP and PE films were $163.4^{\circ}C$ and $109.7^{\circ}C$, respectively, and the crystallization temperature were $98.9^{\circ}C$ and $93.6^{\circ}C$, respectively. Tensile strength and elongation of each films appeared higher on the width direction than length direction. Considering the characteristics of the thermoplastic films, the test for the amount of film used was carried out by layering film to the target thickness on veneer. The effecting of layering direction of film on plywood manufacturing was conducted by laminating in the length and width directions of the film according to the grain direction of veneer. Tensile-shear strength of plywood in wet condition was satisfied with the quality standard (0.7 MPa) of KS F 3101 when the film was used over 0.05 mm of PP film and over 0.10 mm of PE film. Tensile-shear strength of plywood after cyclic boiling exceeded the KS standard when PP film was used 0.20 mm thickness. Furthermore, higher bonding strength was observed on a plywood made with width direction of film according to grain direction of veneer than that of length direction of film. Based on microscopic analysis of the surface and bonding line of plywood, interlocking between veneers by penetration of a thermoplastic film into inner and cracks were observed.

• Korean Chemical Engineering Research
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• v.50 no.2
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• pp.365-370
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• 2012

In this study, Economic analysis of supercritical coal-fired power plant with $CO_2$ capture process was performed. For this purpose, chemical absorption method using amine solvent, which is commercially available and most suitable for existing thermal power plant, was studied. For the evaluation of the economic analysis of coal-fired power plant with post-combustion $CO_2$ capture process in Korea, energy penalty after $CO_2$ capture was calculated using the power equivalent factor suggested by Bolland et al. And the overnight cost of power plant (or cost of plant construction) and the operation cost reported by the IEA (International Energy Agency) were used. Based on chemical absorption method using a amine solvent and 3.31 GJ/$tonCO_2$ as a regeneration energy in the stripper, the net power efficiency was reduced from 41.0% (without $CO_2$ capture) to 31.6% (with $CO_2$ capture) and the levelized cost of electricity was increased from 45.5 USD/MWh (Reference case, without $CO_2$ capture) to 73.9 USD/MWh (With $CO_2$ capture) and the cost of $CO_2$ avoided was estimated as 41.3 USD/$tonCO_2$.

• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.979-995
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• 2023

As wildfires are difficult to predict, real-time monitoring is crucial for a timely response. Geostationary satellite images are very useful for active fire detection because they can monitor a vast area with high temporal resolution (e.g., 2 min). Existing satellite-based active fire detection algorithms detect thermal outliers using threshold values based on the statistical analysis of brightness temperature. However, the difficulty in establishing suitable thresholds for such threshold-based methods hinders their ability to detect fires with low intensity and achieve generalized performance. In light of these challenges, machine learning has emerged as a potential-solution. Until now, relatively simple techniques such as random forest, Vanilla convolutional neural network (CNN), and U-net have been applied for active fire detection. Therefore, this study proposed an active fire detection algorithm using state-of-the-art (SOTA) deep learning techniques using data from the Advanced Himawari Imager and evaluated it over East Asia and Australia. The SOTA model was developed by applying EfficientNet and lion optimizer, and the results were compared with the model using the Vanilla CNN structure. EfficientNet outperformed CNN with F1-scores of 0.88 and 0.83 in East Asia and Australia, respectively. The performance was better after using weighted loss, equal sampling, and image augmentation techniques to fix data imbalance issues compared to before the techniques were used, resulting in F1-scores of 0.92 in East Asia and 0.84 in Australia. It is anticipated that timely responses facilitated by the SOTA deep learning-based approach for active fire detection will effectively mitigate the damage caused by wildfires.