• Journal of the Korean Society of Marine Environment & Safety
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• v.26 no.7
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• pp.931-941
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• 2020

There is a growing interest this paper for ocean sensing where autonomous vehicles can play an essential role in assisting engineers, researchers, and scientists with environmental monitoring and collecting oceanographic data. This study was conducted to develop a rigid sail for the autonomous sailing drone. Our study aims to numerically analyze the aerodynamic characteristics of curvy twin sail and compare it with wing sail. Because racing regulations limit the sail shape, only the two-dimensional geometry (2D) was open for an optimization. Therefore, the first objective was to identify the aerodynamic performance of such curvy twin sails. The secondary objective was to estimate the effect of the sail's spacing and shapes. A viscous Navier-Stokes flow solver was used for the numerical aerodynamic analysis. The 2D aerodynamic investigation is a preliminary evaluation. The results indicated that the curvy twin sail designs have improved lift, drag, and driving force coefficient compared to the wing sails. The spacing between the port and starboard sails of curvy twin sail was an important parameter. The spacing is 0.035 L, 0.07 L, and 0.14 L shows the lift coefficient reduction because of dramatically stall effect, while flow separation is improved with spacing is 0.21 L, 0.28 L, and 0.35 L. Significantly, the spacing 0.28 L shows the maximum high pressure at the lower area and the small low pressure area at leading edges. Therefore, the highest lift was generated.

• The Journal of the Korea Contents Association
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• v.21 no.5
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• pp.561-580
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• 2021

This study analyses the historical and cultural streets at Pinggang Road in the city of Suzhou, by understanding the development and conservation of the area, and uses the following ways to investigate its development, re-organization, and current state. This paper comprehensively compares, collates and investigates 4 different historical and cultural areas in Insadong and Samcheong-dong in South Korea, and South Luogu Lane in China. From initial research and analysis, this paper gathers the cultural, economic, and societal perspectives as non-physical measures, and spatial structure, road structure, and building maintenance as physical factor framework. It is significant in that it can provide an evaluation model for the preservation and regeneration of historical and cultural streets by presenting the viewpoint of complex development of non-physical and physical elements in Pyeonggang-ro. In addition, it is necessary to conduct optimization and specific research on insufficient areas, such as maintenance and development of programs and signature systems for visitors, and continuous development of historical and cultural network platforms by combining on-site surveys. Basic data should be provided for reference on the street.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.1
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• pp.13-20
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• 2022

Aircraft weight is an important factor affecting performance and fuel efficiency. In the conceptual design stage of the aircraft, the process of balancing cost and weight is performed using empirical formulas such as fuel consumption cost per weight in estimating element weight. In addition, when an airline operates an aircraft, it promotes fuel efficiency improvement, fuel saving and carbon reduction through weight management activities. The relationship between changes in aircraft weight and changes in fuel consumption is called the cost of weight, and the cost of weight is used to evaluate the effect of adding or reducing weight to an aircraft on fuel consumption. In this study, the problems of the existing cost of weight calculation method are identified, and a new cost of weight calculation method is introduced to solve the problem. Using Breguet's Range Formula and actual flight data of the A350-900 aircraft, two weight costs are calculated based on take-off weight and landing weight. In conclusion, it was suggested that it is reasonable to use the cost of weight based on the take-off weight and the landing weight for other purposes. In particular, the cost of weight based on the landing weight can be used as an empirical formula for estimating element weight and optimizing cost and weight in the conceptual design stage of similar aircraft.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.3
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• pp.181-192
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• 2022

Active vibration control system(AVCS) for helicopter enables to control the vibration generated from the main rotor and has the superb vibration reduction performance with low weight compared passive vibration reduction device. In this paper, FxLMS algorithm-based vibration control software of the light civil helicopter tansmits the control command calculated using the signals of the tachometer and accelerometers to the circular force generator(CFG) is developed and verified. According to the RTCA DO-178C/DO-331, the vibration control software is developed through the model based design technique, and real-time operation performance is evaluated in PILS(processor in-the loop simulation) and HILS(hardware in-the loop simulation) environments. In particular, the reliability of the software is improved through the LDRA-based verification coverage in the PIL environments. In order to AVCS to light civil helicopter(LCH), the dynamic response characteristic model is obtained through the ground/flight tests. AVCS configuration which exhibits the optimal performance is determined using system optimization analysis and flight test and obtain STC certification.

• 한국노년학
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• v.40 no.2
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• pp.239-255
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• 2020

The purpose of this study is to examine whether family relationships of elderly single-person households affect community participation and whether these relationships differ by gender. Based on Baltes and Baltes (1990) 's selection, optimization, and compensation theory (SOC) and the argument that family members are a social capital by Prandini (2014), we test whether family relationships can affect community participation in old age. In order to verify this, single-person households were extracted from the 2017 National Survey of Living Conditions and Welfare Needs conducted by the Korea Institute for Health and Social Affairs (Male sample=370, Female sample=1770), multiple regression analysis were conducted with the dependent variables of friends·neighbors and the participation at Kyungrodang·welfare centers for the elderly. The results are as follows. In the case of men, family relations showed no significant effect on their participation in friends·neighbors, or Kyungrodang·welfare centers. However, in the case of women, the frequency of contact with family had a positive effect on the frequency of meeting friends·neighbors. Family contact frequency and child relationship satisfaction had a positive (+) effect on Kyungrodang·welfare center participation, while family meeting frequency had a negative effect on participation in Kyungrodang·welfare centers. For women, although Prandini's (2014) claim that family members are a social capital seems to be supported, it was found that the impact could vary depending on the type of community participation. In addition, practical discussions and suggestions were presented.

• Journal of Appropriate Technology
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• v.7 no.1
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• pp.59-71
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• 2021

Hybrid hydrothermal carbonization (Hybrid HTC) technology is a proprietary thermochemical process for two or more organic wastes.The reaction time is less than two hours with temperature range 180~250℃ and pressure range 20~40bar. Thanks to accumulation of the carbon of the waste during Hybrid HTC process, the energy value of the solid fuel increases significantly with comparatively low energy consumption. It has also a great volume reduction with odor removal effect so that it is evaluated as the best solid fuel conversion technology for various organic wastes. In this study of the hybrid hydrothermal carbonization, the effect on the calorific value and yield of Cambodian mango waste were evaluated according to changes in temperature and reaction time. Through the study, parameter optimization has been sought with improving energy efficiency of the whole plant. It is decomposed in the Hydro-Carbonation Technology to Generate Gas. At this time, it is possible to develop manufacturing and production technologies such as hydrogen (H₂) and methane (CH₄). Based on the results of the study, a pilot plant (2t/day) has been proposed for future commercialization purpose along cost analysis, mass balance and energy balance calculations.

• Analytical Science and Technology
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• v.35 no.6
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• pp.256-266
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• 2022

It is important to determine the concentration of long-lived radionuclides (e.g., ¹²⁹I) in nuclear waste to ensure safety when handling it. To analyze nuclides in a solid sample (e.g., concrete and soil), it is essential to effectively separate and purify the nuclides of interest in the sample. This study reports the comprehensive efforts made to validate the analytical procedure for ¹²⁹I detection in solid samples, using a high-temperature combustion furnace. ¹²⁹I volatilized from the sample collected in 0.01 M HNO₃ solution with a reducing agent (e.g., NaHSO₃) and was rapidly measured by ICP-MS. Analytical conditions, such as pyrolysis temperature and types of mobile phase gas, catalyst, and trapping solution, were optimized to obtain a high recovery rate of spiked ¹²⁹I. Finally, the optimized method was applied for the simultaneous analysis of other volatile radionuclides, such as ³H and ¹⁴C. The performance test results for the optimized method confirmed that the LSC (for ³H and ¹⁴C) and ICP-MS (for ¹²⁹I) measurements, with the separation of volatile nuclides using a high-temperature combustion furnace, were reliable.

• Wind and Structures
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• v.34 no.1
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• pp.127-136
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• 2022

In this work a multi-fidelity non-intrusive polynomial chaos (MF-NIPC) has been applied to a structural wind engineering problem in architectural design for the first time. In architectural design it is important to design structures that are safe in a range of wind directions and speeds. For this reason, the computational models used to design buildings and bridges must account for the uncertainties associated with the interaction between the structure and wind. In order to use the numerical simulations for the design, the numerical models must be validated by experi-mental data, and uncertainties contained in the experiments should also be taken into account. Uncertainty Quantifi-cation has been increasingly used for CFD simulations to consider such uncertainties. Typically, CFD simulations are computationally expensive, motivating the increased interest in multi-fidelity methods due to their ability to lev-erage limited data sets of high-fidelity data with evaluations of more computationally inexpensive models. Previous-ly, the multi-fidelity framework has been applied to CFD simulations for the purposes of optimization, rather than for the statistical assessment of candidate design. In this paper MF-NIPC method is applied to flow around a rectan-gular 5:1 cylinder, which has been thoroughly investigated for architectural design. The purpose of UQ is validation of numerical simulation results with experimental data, therefore the radius of curvature of the rectangular cylinder corners and the angle of attack are considered to be random variables, which are known to contain uncertainties when wind tunnel tests are carried out. Computational Fluid Dynamics (CFD) simulations are solved by a solver that employs the Finite Element Method (FEM) for two turbulence modeling approaches of the incompressible Navier-Stokes equations: Unsteady Reynolds Averaged Navier Stokes (URANS) and the Large Eddy simulation (LES). The results of the uncertainty analysis with CFD are compared to experimental data in terms of time-averaged pressure coefficients and bulk parameters. In addition, the accuracy and efficiency of the multi-fidelity framework is demonstrated through a comparison with the results of the high-fidelity model.

• Smart Media Journal
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• v.11 no.10
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• pp.65-75
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• 2022

Deep learning is used as a creative tool that could overcome the limitations of existing analysis models and generate various types of results such as text, image, and music. In this paper, we propose a method necessary to preprocess audio data using the Niko's MIDI Pack sound source file as a data set and to generate music using Bi-LSTM. Based on the generated root note, the hidden layers are composed of multi-layers to create a new note suitable for the musical composition, and an attention mechanism is applied to the output gate of the decoder to apply the weight of the factors that affect the data input from the encoder. Setting variables such as loss function and optimization method are applied as parameters for improving the LSTM model. The proposed model is a multi-channel Bi-LSTM with attention that applies notes pitch generated from separating treble clef and bass clef, length of notes, rests, length of rests, and chords to improve the efficiency and prediction of MIDI deep learning process. The results of the learning generate a sound that matches the development of music scale distinct from noise, and we are aiming to contribute to generating a harmonistic stable music.

• 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.