• Journal of the Korean Institute of Intelligent Systems
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• v.27 no.1
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• pp.1-6
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• 2017

Recent researches on radio frequency energy harvesting networks(RF-EHNs) with limited energy resource like battery have been focusing on the development of a new scheme that can effectively extend the whole lifetime of a network to semipermanent. In order for considerable increase both in the amount of energy obtained from radio frequency energy harvesting and its charging effectiveness, it is very important to design a network that supports energy harvesting and data transfer simultaneously with the full consideration of various characteristics affecting the performance of a RF-EHN. In this paper, we proposes an interference-based charging aware routing protocol(ICARP) that utilizes interference information and charging time to maximize the amount of energy harvesting and to minimize the end-to-end delay from a source to the given destination node. To accomplish the research objectives, this paper gives a design of ICARP adopting new network metrics such as interference information and charging time to minimize end-to-end delay in energy harvesting wireless networks. The proposed method enables a RF-EHN to reduce the number of packet losses and retransmissions significantly for better energy consumption. Finally, simulation results show that the network performance in the aspects of packet transmission rate and end-to-end delay has enhanced with the comparison of existing routing protocols.

• Food Science and Preservation
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• v.19 no.4
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• pp.492-500
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• 2012

This study was conducted to develop a sauce prepared with sweet pumpkin and Korea Doenjang. The optimum conditions for manufacturing sweet pumpkin-doenjang sauce were investigated using the response surface methodology, based on the central composition design. The amount of stock added, the thickening agent, and doenjang were used as the independent variables, and the sensory characteristics (taste, flavor, color, and overall acceptability) were used as the dependent variables to evaluate the optimum conditions for the preparation of the sauce. The optimum conditions for the maximized-responses variables in the preparation of the sauce were 448.5 g of sweet pumpkin stock, 331.5 g of the thickening agent, and 20.0 g of doenjang. The quality characteristics of sweet pumpkin-doenjang sauce that was manufactured at optimum conditions were as follow: 89.55% moisture content, 0.70% crude protein, 0.10% crude lipids, and 0.71% crude ash. The pH of the sauce was 5.96; total acidity, 0.08%; and soluble solids, 6.80$^{\circ}Brix$. The total polyphenol content of the sauce was 5.70 mg/L. The electron-donating ability and reducing power of the sauce were, 14.24% and 1.64 OD, respectively.

• Korean Chemical Engineering Research
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• v.57 no.4
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• pp.525-530
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• 2019

The performance and stability of solid oxide fuel cells (SOFCs) depend on the microstructure of the electrode and electrolyte. In anode, porosity and pore distribution affect the active site and fuel gas transfer. In an electrolyte, density and thickness determine the ohmic resistance. To optimizing these conditions, using costly method cannot be a suitable research plan for aiming at commercialization. To solve these drawbacks, we made high performance unit cells with low cost and highly efficient ceramic processes. We selected the NiO-YSZ cermet that is a commercial anode material and used facile methods like die pressing and dip coating process. The porosity of anode was controlled by the amount of carbon black (CB) pore former from 10 wt% to 20 wt% and final sintering temperature from $1350^{\circ}C$ to $1450^{\circ}C$. To achieve a dense thin film electrolyte, the thickness and microstructure of electrolyte were controlled by changing the YSZ loading (vol%) of the slurry from 1 vol% to 5 vol. From results, we achieved the 40% porosity that is well known as an optimum value in Ni-YSZ anode, by adding 15wt% of CB and sintering at $1350^{\circ}C$. YSZ electrolyte thickness was controllable from $2{\mu}m$ to $28{\mu}m$ and dense microstructure is formed at 3vol% of YSZ loading via dip coating process. Finally, a unit cell composed of Ni-YSZ anode with 40% porosity, YSZ electrolyte with a $22{\mu}m$ thickness and LSM-YSZ cathode had a maximum power density of $1.426Wcm^{-2}$ at $800^{\circ}C$.

• Journal of the Institute of Convergence Signal Processing
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• v.19 no.4
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• pp.153-161
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• 2018

This paper describes the performance improvement of Software (SW) digital filter using GPU (Graphical Processing Unit). The previous developed SW digital filter has a problem that it operates on a CPU (Central Processing Unit) basis and has a slow speed. The GPU was introduced to filter the data of the EAVN (East Asian VLBI Network) observation to improve the operation speed and to process data with other stations through filtering, respectively. In order to enhance the computational speed of the SW digital filter, NVIDIA Titan V GPU board with built-in Tensor Core is used. The processing speed of about 0.78 (1Gbps, 16MHz BW, 16-IF) and 1.1 (2Gbps, 32MHz BW, 16-IF) times for the observing time was achieved by filtering the 95 second observation data of 2 Gbps (512 MHz BW, 1-IF), respectively. In addition, 2Gbps data is digitally filtered for the 1 and 2Gbps simultaneously observed with KVN (Korean VLBI Network), and compared with the 1Gbps, we obtained similar values such as cross power spectrum, phase, and SNR (Signal to Noise Ratio). As a result, the effectiveness of developed SW digital filter using GPU in this research was confirmed for utilizing the data processing and analysis. In the future, it is expected that the observation data will be able to be filtered in real time when the distributed processing optimization of source code for using multiple GPU boards.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.9
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• pp.517-524
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• 2019

The overdrive hub clutch is attached to a 6-speed automatic transmission to reduce fuel consumption by using the additional power of the engine. This paper proposes a means to minimize the load and roll-over ratio on the punch during the piercing process for the overdrive hub clutch product. Die clearance, shear angle, and friction coefficient, which can affect the load and roll-over ratio of the punch during processing, were set as the design variables. Sensitivity analysis was also conducted to determine the influence of each design variable on the punch load and roll-over ratio. As a result, shear angle, friction coefficient and die clearance were found to be sensitive to load and roll-over ratio. The punch load and roll-over ratio were set as the objective function and the equation of each design variable and objective function was derives using the Response Surface Method. Finally, the optimal value of the design variables was derived using the Response Surface Method. Application of this model to finite element analysis resulted in 22.14% improvement in the roll-over ratio of the punch load and material.

• Journal of IKEEE
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• v.23 no.1
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• pp.193-199
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• 2019

In this study, we have proposed a floating metal guard ring structure based on TCAD simulation in order to enhance the breakdown voltage characteristics of gallium oxide ($Ga_2O_3$) vertical high voltage switching Schottky barrier diode. Unlike conventional guard ring structures, the floating metal guard rings do not require an ion implantation process. The locally enhanced high electric field at the anode corner was successfully suppressed by the metal guard rings, resulting in breakdown voltage enhancement. The number of guard rings and their width and spacing were varied for structural optimization during which the current-voltage characteristics and internal electric field and potential distributions were carefully investigated. For an n-type drift layer with a doping concentration of $5{\times}10^{16}cm^{-3}$ and a thickness of $5{\mu}m$, the optimum guard ring structure had 5 guard rings with an individual ring width of $1.5{\mu}m$ and a spacing of $0.2{\mu}m$ between rings. The breakdown voltage was increased from 940 V to 2000 V without degradation of on-resistance by employing the optimum guard ring structure. The proposed floating metal guard ring structure can improve the device performance without requiring an additional fabrication step.

• Clean Technology
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• v.27 no.1
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• pp.85-92
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• 2021

A solar water battery is a system that generates power using solar energy. It is a combination of photoelectrochemical cells and an energy storage system. It can simultaneously convert and store solar energy without additional external voltage. Solar water batteries consist of photoelectrodes, storage electrodes and counter electrodes, and their properties and combination are important for the performance and the efficiency of the system. In this study, we tried to find the effect that changing the components of solar water batteries has on its system. The effects of the counter electrode during discharge, the kinds of photoelectrode and storage electrode materials, and electrolytes on the solar energy conversion and storage capacitance were studied. The optimized composition (TiO2 : NaFe-PB : Pt foil) exhibited 72.393 mAh g-1 of discharge capacity after 15 h of photocharging. It indicates that the efficiency of solar energy conversion and storage is largely affected by the configuration of the system. Also, the addition of organic pollutants to the chamber of the photoelectrode improved the battery's photo-current and discharge capacity by efficient photoelectron-hole pair separation with simultaneous degradation of organic pollutants. Solar water batteries are a new eco-friendly solar energy conversion and storage system that does not require additional external voltages. It is also expected to be used for water treatment that utilizes solar energy.

• Journal of the Korea Convergence Society
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• v.12 no.8
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• pp.31-37
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• 2021

As the size of buildings increases due to urbanization due to the development of industry, the need to purify the air and maintain a comfortable indoor environment is also increasing. With the development of monitoring technology for refrigeration systems, it has become possible to manage the amount of electricity consumed in buildings. In particular, refrigeration systems account for about 40% of power consumption in commercial buildings. Therefore, in order to develop the refrigeration system failure diagnosis algorithm in this study, the purpose of this study was to understand the structure of the refrigeration system, collect and analyze data generated during the operation of the refrigeration system, and quickly detect and classify failure situations with various types and severity . In particular, in order to improve the classification accuracy of failure types that are difficult to classify, a three-step diagnosis and classification algorithm was developed and proposed. A model based on SVM and LGBM was presented as a classification model suitable for each stage after a number of experiments and hyper-parameter optimization process. In this study, the characteristics affecting failure were preserved as much as possible, and all failure types, including refrigerant-related failures, which had been difficult in previous studies, were derived with excellent results.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.2
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• pp.59-76
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• 2023

Since the COVID-19 era, the rise in apartment prices has been unconventional. In this uncertain real estate market, price prediction research is very important. In this paper, a model is created to predict the actual transaction price of future apartments after building a vast data set of 870,000 from 2015 to 2020 through data collection and crawling on various real estate sites and collecting as many variables as possible. This study first solved the multicollinearity problem by removing and combining variables. After that, a total of five variable selection algorithms were used to extract meaningful independent variables, such as Forward Selection, Backward Elimination, Stepwise Selection, L1 Regulation, and Principal Component Analysis(PCA). In addition, a total of four machine learning and deep learning algorithms were used for deep neural network(DNN), XGBoost, CatBoost, and Linear Regression to learn the model after hyperparameter optimization and compare predictive power between models. In the additional experiment, the experiment was conducted while changing the number of nodes and layers of the DNN to find the most appropriate number of nodes and layers. In conclusion, as a model with the best performance, the actual transaction price of apartments in 2021 was predicted and compared with the actual data in 2021. Through this, I am confident that machine learning and deep learning will help investors make the right decisions when purchasing homes in various economic situations.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.2
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• pp.265-278
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• 2022

The global energy paradigm is rapidly changing by centering on carbon neutrality, and wind energy is positioning itself as a leader in renewable energy-based power sources. The success of onshore and offshore wind energy projects focuses on securing the economic feasibility of the project, which depends on securing high-quality wind resources and optimal arrangement of wind turbines. In the process of constructing the wind farm, the optimal arrangement method of wind turbines considering the main wind direction is important, and this is related to minimizing the wake effect caused by the fluid passing through the structure located on the windward side. The accuracy of the predictability of the wake effect is determined by the wake model and modeling technique that can properly simulate it. Therefore, in this paper, using WindSim, a commercial CFD model, the wake diffusion pattern is analyzed through the sensitivity study of each wake model of the proposed onshore wind farm located in the mountainous complex terrain in South Korea, and it is intended to be used as basic research data for wind energy projects in complex terrain in the future.