• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.663-664
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• 2016

Temperature difference power generation using sea water is a method repeatedly closed liquefaction and gasification by using the ammonia (refrigerant) of the deep sea water and surface water with a temperature difference between turning the turbine. The larger the temperature difference between the nature of the temperature characteristic energy generation development, the better. This is the story that the surface waters of the deep-water temperature difference is large. But the winter is not large temperature difference between surface water and deep water has lowered energy efficiency. And desalination technologies accounted for 97% of the earth, but we can not eat the technology to convert sea water into fresh water, fresh water produced by the desalination technology that is available for various industries such as irrigation, drinking water in the vessel.In this paper, LNG transport vessels, based on the LNG transport ship to the temperature difference power generation using cold energy of thermal energy and LNG marine diesel engines, which use the existing order to improve the temperature of the surface waters of the season that is the current problem we propose that a complex development of desalination and desalination of seawater freezing research into hybrid research and utilizing the cold energy of the engine.

• Journal of the Korean Crystal Growth and Crystal Technology
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• v.29 no.4
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• pp.143-148
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• 2019

We have successfully fabricated high aspect-ratio GaN-based nanowires on Si substrates using molecular beam epitaxy (MBE) system for high-efficiency hydrogen generation of photoelectrochemical water splitting. Scanning electron microscopy (SEM) and energy dispersive X-ray spectroscopy (EDX) demonstrated that p-GaN:Mg and p-InGaN nanowires were grown vertically on the substrate with high density. Furthermore, it was also confirmed that the emission wavelength of p-InGaN nanowire can be adjusted from 552 nm to 590 nm. Such high-aspect ratio p-InGaN nanowire structure will be a solid foundation for the realization of ultrahigh-efficiency photoelectrochemical water splitting through sunlight.

• Korean Journal of Materials Research
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• v.29 no.1
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• pp.1-6
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• 2019

Recent industrialization has led to a high demand for the use of fossil fuels. Therefore, the need for producing hydrogen and its utilization is essential for a sustainable society. For an eco-friendly future technology, photoelectrochemical water splitting using solar energy has proven promising amongst many other candidates. With this technique, semiconductors can be used as photocatalysts to generate electrons by light absorption, resulting in the reduction of hydrogen ions. The photocatalysts must be chemically stable, economically inexpensive and be able to utilize a wide range of light. From this perspective, cuprous oxide($Cu_2O$) is a promising p-type semiconductor because of its appropriate band gap. However, a major hindrance to the use of $Cu_2O$ is its instability at the potential in which hydrogen ion is reduced. In this study, gold is used as a bottom electrode during electrodeposition to obtain a preferential growth along the (111) plane of $Cu_2O$ while imperfections of the $Cu_2O$ thin films are removed. This study investigates the photoelectrochemical properties of $Cu_2O$. However, severe photo-induced corrosion impedes the use of $Cu_2O$ as a photoelectrode. Two candidates, $TiO_2$ and $SnO_2$, are selected for the passivation layer on $Cu_2O$ by by considering the Pourbaix-diagram. $TiO_2$ and $SnO_2$ passivation layers are deposited by atomic layer deposition(ALD) and a sputtering process, respectively. The investigation of the photoelectrochemical properties confirmed that $SnO_2$ is a good passivation layer for $Cu_2O$.

• Journal of Korean Medical classics
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• v.32 no.4
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• pp.67-90
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• 2019

Objectives : This study aims to summarize Tang Zong-hai's Qi transformation theory of the Six meridians through his book "Shanghanlun Qianzhubuzheng傷寒論淺注補正" where he integrated Western anatomy with the Qi transformation theory of East Asian Medicine to interpret Zhang Zhong Jing's "Shanghanlun(傷寒論)". The objective is to assist clinical application. Methods : Focusing on the contents of disease of the six meridians in the "傷寒論淺注補正", Tang's theories on the function of Zangfu(臟腑), Opening-Closing-Pivot(關闔樞), Inter-communication of Zangfu(臟腑相通), the Twelve Meridians(十二經脈) from his other publication "中西匯通醫經精義" were examined and related to in the process of explaining Qi transformation theory in detail. Results : 1. The Qi transformation function of the Taiyang meridian is related to "膀胱者, 氣化則能出" where the Small Intestine and Bladder inter-communicate. 2. The Qi transformation function of the Yangming meridian is related to the control of dryness and dampness through the Qi transformation of "陽明不從標本, 從乎中." 3. The Qi transformation function of the Shaoyang meridian is related to the Life-Fire function of the Triple Energizer-Gallbladder-Pericardium coalition through "少陽屬腎." 4. The Qi transformation function of the Taiyang meridian refers to the Heart Fire nurturing the Spleen Earth by creating 膏油 through veins. 5. The Qi transformation function of the Shaoyin meridian is related to the controlling of the Nutrient Qi(營氣) and Defense Qi(衛氣) through '心主血脈, 腎主元氣.' 6. The Qi transformation function of the Jueyin meridian is related to the ability of 和風 which results from '陰盡陽生' to harmonize and control the balance of Water Coldness(水冷) and Fire Heat(火熱). Conclusions : Tang's Qi Transformation Theory of the Six Meridians is his key theory explained from the perspective of Qi transformation of disease in the six meridians of "Shanghanlun", closely related to basic theories such as theory of Zang form(臟象學說), Opening-Closing-Pivot(關闔樞), Inter-communication of Zangfu(臟腑相通), the Twelve Meridians(十二經脈) of East Asian Medicine.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.2
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• pp.85-92
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• 2021

Ambient Air Vaporizer (AAV) is an essential facility in the process of generating natural gas that uses air in the atmosphere as a medium for heat exchange to vaporize liquid natural gas into gas-state gas. AAV is more economical and eco-friendly in that it uses less energy compared to the previously used Submerged vaporizer (SMV) and Open-rack vaporizer (ORV). However, AAV is not often applied to actual processes because it is heavily affected by external environments such as atmospheric temperature and humidity. With insufficient operational experience and facility operations that rely on the intuition of the operator, the actual operation of AAV is very inefficient. To address these challenges, this paper proposes an artificial intelligence-based model that can intelligent AAV operations based on operational big data. The proposed artificial intelligence model is used deep neural networks, and the superiority of the artificial intelligence model is verified through multiple regression analysis and comparison. In this paper, the proposed model simulates based on data collected from real-world processes and compared to existing data, showing a 48.8% decrease in power usage compared to previous data. The techniques proposed in this paper can be used to improve the energy efficiency of the current natural gas generation process, and can be applied to other processes in the future.

• Journal of Broadcast Engineering
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• v.27 no.3
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• pp.332-340
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• 2022

Recently, with the development of deep learning and artificial neural network technologies, research on the application of neural network has been actively conducted in the field of video coding. In particular, deep learning-based intra prediction is being studied as a way to overcome the performance limitations of the existing intra prediction techniques. This paper presents a method of context-adaptive neural network-based intra prediction model training and its coding performance analysis. In other words, in this paper, we implement and train a known intra prediction model based on convolutional neural network (CNN) that predicts a current block using contextual information from reference blocks. Then, we integrate the trained model into HM16.19 as an additional intra prediction mode and evaluate the coding performance of the trained model. Experimental results show that the trained model gives 0.28% BD-rate bit saving over HEVC in All Intra (AI) coding mode. In addition, the coding performance change of training considering block partition is also presented.

• Journal of Broadcast Engineering
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• v.26 no.6
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• pp.758-765
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• 2021

Recently, various research on the application of deep learning to video encoding for enhancing coding efficiency are being actively studied. This paper proposes a deep learning based intra prediction which uses multiple models by extending Matrix-based Intra Prediction(MIP) that is a neural network-based technology adopted in VVC. It also presents an efficient learning method for the multi-model intra prediction. To evaluate the performance of the proposed method, we integrated the VVC MIP and the proposed fully connected layer based multi-model intra prediction into HEVC reference software, HM16.19 as an additional intra prediction mode. As a result of the experiments, the proposed method can obtain bit-saving coding gain up to 0.47% and 0.19% BD-rate, respectively, compared to HM16.19 and VVC MIP.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.32 no.4
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• pp.425-434
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• 2022

Objectives: This study analyzes TVOC concentrations in root industry workplaces in order to prevent probable occupational disease among workers. Root industry includes all the infrastructure of manufacturing, such as casting and molding. Methods: Real-time TVOC sensors were deployed in three root industry workplaces. We measured TVOC concentrations with these sensors and analyzed the results using a data-analysis tool developed with Python 3.9. Results: During the study period, the mean of the TVOC concentrations remained in an acceptable range, 0.30, 2.15, and 1.63 ppm across three workplaces. However, TVOC concentrations increased significantly at specific times, with respective maximum values of 4.98, 28.35, and 26.65 ppm for the three workplaces. Moreover, the analysis of hourly TVOC concentrations showed that during working hours or night shifts TVOC concentrations increased significantly to higher than twice the daily mean values. These results were scrutinized through classical decomposition results and autocorrelation indices, where seasonal graphs of the corresponding classical decomposition results showed that TVOC concentrations increased at a specific time. Trend graphs showed that TVOC concentrations vary by day. Conclusions: Deploying a real-time TVOC sensor should be considered to reflect irregularly high TVOC concentrations in workplaces in the root industry. It is expected that the real-time TVOC sensor with the presented data analysis methodology can eradicate probable occupational diseases caused by detrimental gases.

• Journal of Korean Society of Disaster and Security
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• v.16 no.1
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• pp.91-103
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• 2023

This study aims to investigate the dynamic fracture characteristics of rocks and rock-like materials subjected to the Nonex Rock Cracker (NRC), a vapor pressure crushing agent that produces vapor pressure by instantaneously vaporizing a liquid mixture crystallized through the thermite reaction. Furthermore, the study seeks to develop an analytical technique for predicting the fracture pattern. A dynamic fracture test was performed on a PMMA block, an artificial brittle material, using the NRC. High-speed cameras and dynamic pressure gauges were employed to capture the moment of vapor pressure generation and measure the vapor pressure-time history, respectively. The 2-dimensional Dynamic Fracture Process Analysis (2D DFPA) was used to simulate the fracture process caused by the vapor pressure, with the applied pressure determined based on the vapor pressure-time history. The proposed analytical method was used to examine various fracture patterns with respect to granite material and high-performance explosives.

• Journal of Surface Science and Engineering
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• v.56 no.2
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• pp.137-146
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• 2023

Nanosized TiO₂ has been widely investigated in photoelectrochemical or photocatalytic applications due to their intrinsic properties such as suitable band position, high photocorrosion resistance, and surface area. In this study, to achieve the high efficiency in photoelectrochemical and photocatalytic performance, TiO₂ nanotubular structures were formed by anodization at various temperatures and times. The morphological and crystal structure of the anodized TiO₂ nanotubes (NTs) were characterized by scanning electron microscope (SEM) and X-ray diffraction (XRD). The photoelectrochemical (PEC) properties and incident photon-to-current conversion efficiency (IPCE) of the TiO₂ NTs were studied with different lengths and morphologies. From the detailed investigations, the optimum thickness of TiO₂ nanotubes was 3 ㎛. Moreover, we found that the optimum photocatalytic pollutant removal efficiency of TiO₂ nanotubes for photodegradation of Rhodamine B (RhB) under simulated solar light was 5.34 ㎛ of tube length.