• Journal of the Korean Wood Science and Technology
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• v.42 no.3
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• pp.318-326
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• 2014

This study was conducted to investigate the potential of non-used forest biomass residues as raw materials for making wood pellets with additives such as wood tar and starch and to evaluate fuel characteristics of the pellets. Wood tar, a by-product provided from the carbonization process of wood, could be a suitable additive for wood pellet production due to its higher calorific value and lower hazardous heavy metals, such as cadmium and mercury, compared to woody biomass. When the wood tar (10 wt%) was added, the calorific value was increased from 4,630 kcal/kg (wood pellet without additive) to 4,800 kcal/kg (wood pellet with additive). With the increase of additive amount into wood pellet, the length and individual density of wood pellet increased. In addition, bulk density of the pellets was increased, whereas the fine content was decreased. Consequently the overall productivity of wood pellets was improved by adding 2 w% additives into wood pellets; the percentage of productivity increase was 5.9% and 4.9% for adding starch and wood tar, respectively.

• Journal of the Korean Wood Science and Technology
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• v.42 no.3
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• pp.258-265
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• 2014

By replacing the previous metal connector on the joints of timber structure, the GFRP reinforced laminated wooden pin was produced using a wooden material and Glass fiber reinforced plastic(GFRP) composite laminate. In addition, using the reinforced wooden pin, the tensile type shear strength test was conducted. Based on the result of the bending strength test of the reinforced laminated wooden pin according to the GFRP arrangement, a specimen(Type-A) with a single insertion of GFRP for each layer have shown the most favorable performance. Also, it was verified that densified specimen hot pressed for an hour at the temperature of $150^{\circ}C$ and with the oppression pressure $1.96N/mm^2$ have shown the improved performance of 1.57 times than the specimen without the densification. And in the bending strength test considering the load direction, edgewise have shown a higher performance of 3.51 times than the flatwise. A shear strength test was conducted using the Type-A reinforced laminated wooden pin which have shown a moderate performance on the test. Based on the test conducted by differentiating the type of the joint plate and the connector, compared to the specimen(Type-DS) applied with the drift pin and steel plate, the specimen( Type-WL) applied with the GFRP reinforced laminated wooden pin and GFRP reinforced wooden laminated plate have shown 1.12 times higher shear strength and also have shown an excellent toughness even after the maximum load.

• The Journal of the Acoustical Society of Korea
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• v.40 no.5
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• pp.408-416
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• 2021

In the ultrasonic dispersion, in order to avoid direct contact of the radiation surface of ultrasonic transducers with a liquid sample, the liquid sample is separated by a glass container and it receives ultrasonic energy through an acoustic medium. The transmission efficiency of the ultrasonic energy in the multi-layered ultrasonic system is an important factor. In this study, we suggested a method that can improve the ultrasonic energy transfer efficiency by using a propylene glycol solution as a liquid matching layer in the multi-layered acoustic system. In this method, a propylene glycol solution was filled between the Langevin-type ultrasonic transducer and the luminol solution and the sonoluminescence phenomena in the luminol solution, which is caused by nonlinear effect of high power ultrasound radiated from the transducer, was examined by using a Photo Multiplier Tube (PMT). The transmission efficiency depending on the concentration of propylene glycol solution was observed, and we can see that as the concentration of the propylene glycol solution increased, the matching effect increased while the acoustic attenuation increased. It was confirmed that there is an optimal concentration compromised these two conflicting conditions, and the optimum concentration of the propylene glycol solution was determined experimentally.

• The Journal of the Convergence on Culture Technology
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• v.7 no.2
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• pp.405-410
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• 2021

In this study, a finite element analysis was performed applying a nonlinear material model and fatigue load conditions to evaluate the service life and spring stiffness of the resilient pad for rail fastening system. As a result of the fatigue analysis, the rate of change in spring stiffness compared to the initial condition was about 16%, indicating that fatigue hardening occurred. As for the stress generated in the longitudinal direction of the resilient pad, the difference between the stress generated at the center and the edge was about 10 times or more. In addition, it was analyzed that the equivalent stress of the outer boundary was more than twice as large as that of the central part. Therefore, it was analyzed that the damage and deformation of the resilient pad are the corners of the resilient pad under actual service conditions. The fatigue life diagram of the resilient pad (S-N curve) was derived using the equivalent stress of the resilient pad according to the fatigue cycles. Using the fatigue life diagram of the resilient pad derived in this study, it is considered that it can be used to predict the fatigue life under the relevant conditions by calculating the equivalent stress of the resilient pad under various load conditions.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.3
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• pp.99-106
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• 2019

Technology that cannot be excluded from 4th industry is self-driving sector. The self-driving sector can be seen as a key set of technologies in the fourth industry, especially in the DB sector is getting more and more popular as a business. The DB, which was previously produced and managed in two dimensions, is now evolving into three dimensions. Among the data obtained by Mobile Mapping System () to produce the HD MAP necessary for self-driving, Point Cloud, which is LiDAR data, is used as a DB because it contains accurate location information. However, at present, it is not widely used as a base data for 3D modeling in addition to HD MAP production. In this study, MMS Point Cloud was used to extract facilities around the road and to overlay the location to expand the usability of Point Cloud. Building utility poles and communication poles DB from Point Cloud and comparing road name address base and location, it is believed that the accuracy of the location of the facility DB extracted from Point Cloud is also higher than the basic road name address of the road, It is necessary to study the expansion of the facility field sufficiently.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.2
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• pp.1-6
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• 2019

The objective of this study was to investigate performance characteristics of thermal management system(TMS) in a fuel cell electric vehicle with 100kW Fuel Cell(FC) system. In order to build up analytic modelling for TMS, each component was installed and tested under various operating conditions, such as water pump, radiator, 3-Way valve, COD heater, and FC stack etc. and as the results of them, correlations reflecting component's characteristics with flow rate, air velocity were developed. Developed analytic modelling was carried out under various operating conditions on the road. To verify modelling's accuracy, after prediction for optimum coolant flow rate was fulfilled under certain operating conditions, such as FC system, water pump speed, opening of 3-way valve, and pipe resistance, analytic and experimental values were compared and good agreement was shown. In order to predict cold-start operating performance for analytic modelling, coolant temperature variation was analyzed with $-20^{\circ}C$ ambient temperature and duration was predicted to rise in optimum temperature for FC. Because there is appropriate temperature difference between inlet and outlet of FC stack to operate FC system properly, related analysis was performed with respect to power consumption for TMS and heat rejection rate and performance map was depicted along with FC operating conditions.

• Korean Chemical Engineering Research
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• v.59 no.4
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• pp.565-573
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• 2021

Isotherms, kinetics and thermodynamic properties for adsorption of Brilliant Green(BG), Quinoline Yellow(QY) dyes by activated carbon were carried out using variables such as dose of adsorbent, pH, initial concentration, contact time, temperature and competitive. BG showed the highest adsorption rate of 92.4% at pH 11, and QY was adsorbed at 90.9% at pH 3. BG was in good agreement with the Freundlich isothermal model, and QY was well matched with Langmuir model. The separation coefficients of isotherm model indicated that these dyes could be effectively treated by activated carbon. Estimated adsorption energy by Temkin isotherm model indicated that the adsorption of BG and QY by activated carbon is a physical adsorption. The kinetic experimental results showed that the pseudo second order model had a better fit than the pseudo first order model with a smaller in the equilibrium adsorption amount. It was confirmed that surface diffusion was a rate controlling step by the intraparticle diffusion model. The activation energy and enthalpy change of the adsorption process indicated that the adsorption process was a relatively easy endothermic reaction. The entropy change indicated that the disorder of the adsorption system increased as the adsorption of BG and QY dyes to activated carbon proceeded. Gibbs free energy was found that the adsorption reaction became more spontaneous with increasing temperature. As a result of competitive adsorption of the mixed solution, it was found that QY was disturbed by BG and the adsorption reduced.

• Journal of Korea Water Resources Association
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• v.54 no.5
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• pp.301-309
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• 2021

In this study, we tried to improve the performance of the existing U-net-based deep learning rainfall prediction model, which can weaken the meaning of time series order. For this, ConvLSTM2D U-Net structure model considering temporal consistency of data was applied, and we evaluated accuracy of the ConvLSTM2D U-Net model using a RainNet model and an extrapolation-based advection model. In addition, we tried to improve the uncertainty in the model training process by performing learning not only with a single model but also with 10 ensemble models. The trained neural network rainfall prediction model was optimized to generate 10-minute advance prediction data using four consecutive data of the past 30 minutes from the present. The results of deep learning rainfall prediction models are difficult to identify schematically distinct differences, but with ConvLSTM2D U-Net, the magnitude of the prediction error is the smallest and the location of rainfall is relatively accurate. In particular, the ensemble ConvLSTM2D U-Net showed high CSI, low MAE, and a narrow error range, and predicted rainfall more accurately and stable prediction performance than other models. However, the prediction performance for a specific point was very low compared to the prediction performance for the entire area, and the deep learning rainfall prediction model also had limitations. Through this study, it was confirmed that the ConvLSTM2D U-Net neural network structure to account for the change of time could increase the prediction accuracy, but there is still a limitation of the convolution deep neural network model due to spatial smoothing in the strong rainfall region or detailed rainfall prediction.

• Journal of Digital Convergence
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• v.18 no.12
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• pp.525-531
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• 2020

In today's IT environment where various pieces of information are distributed in large volumes, recommendation systems are in the spotlight capable of figuring out users' needs fast and helping them with their decisions. The current recommendation systems, however, have a couple of problems including that user preference may not be reflected on the systems right away according to their changing tastes or interests and that items with no relations to users' preference may be recommended, being induced by advertising. In an effort to solve these problems, this study set out to propose a Fuzzy-AHP-based movie recommendation system by applying the BRNN(Bidirectional Recurrent Neural Network) language model. Applied to this system was Fuzzy-AHP to reflect users' tastes or interests in clear and objective ways. In addition, the BRNN language model was adopted to analyze movie-related data collected in real time and predict movies preferred by users. The system was assessed for its performance with grid searches to examine the fitness of the learning model for the entire size of word sets. The results show that the learning model of the system recorded a mean cross-validation index of 97.9% according to the entire size of word sets, thus proving its fitness. The model recorded a RMSE of 0.66 and 0.805 against the movie ratings on Naver and LSTM model language model, respectively, demonstrating the system's superior performance in predicting movie ratings.

• Journal of Broadcast Engineering
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• v.26 no.3
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• pp.308-320
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• 2021

Conventional image quality studies have been focused on 'naturalness' and has relied on memory color. Memory colors are mainly formed for familiar objects with prior experience, and the more faithfully these memories are reflected, the more naturalness of the reproduced image quality increases. In particular, the brightness and saturation of memory colors play an important role in increasing the preference of image quality as well as naturalness. Therefore, in the case of existing image quality studies, image quality characteristics were studied focusing on natural objects and people with memory. We extracted representative images of each genre (sports, documentaries, news, entertainment and music, and movies), adjusted the brightness, contrast, and saturation of each image, and conducted an experiment to evaluate perceived quality. Based on situational context, the results of this classification indicated that genres of television content can be divided into two categories: proximate and indirect experiences. Proximate experience best characterizes outdoor sports, dramas, and nature documentaries, where their image qualities have shown to have a strong correlation with brightness and contrast. On the other hand, indirect experience best characterizes news, music shows and SF/action movies. The image quality perception for indirect experiences was shown to be closely related to and optimized by contrast and saturation.