• International Journal of Contents
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• v.9 no.4
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• pp.1-10
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• 2013

The electroencephalogram (EEG) time series is a measure of electrical activity received from multiple electrodes placed on the scalp of a human brain. It provides a direct measurement for characterizing the dynamic aspects of brain activities. These EEG signals are formed from a series of spatial and temporal data with multiple dimensions. Missing data could occur due to fault electrodes. These missing data can cause distortion, repudiation, and further, reduce the effectiveness of analyzing algorithms. Current methodologies for EEG analysis require a complete set of EEG data matrix as input. Therefore, an accurate and reliable imputation approach for missing values is necessary to avoid incomplete data sets for analyses and further improve the usage of performance techniques. This research proposes a new method to automatically recover random consecutive missing data from real world EEG data based on Linear Dynamical System. The proposed method aims to capture the optimal patterns based on two main characteristics in the coevolving EEG time series: namely, (i) dynamics via discovering temporal evolving behaviors, and (ii) correlations by identifying the relationships between multiple brain signals. From these exploits, the proposed method successfully identifies a few hidden variables and discovers their dynamics to impute missing values. The proposed method offers a robust and scalable approach with linear computation time over the size of sequences. A comparative study has been performed to assess the effectiveness of the proposed method against interpolation and missing values via Singular Value Decomposition (MSVD). The experimental simulations demonstrate that the proposed method provides better reconstruction performance up to 49% and 67% improvements over MSVD and interpolation approaches, respectively.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.43 no.5
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• pp.413-421
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• 2015

Since the first Cubesat was launched in 2003, there have been more than 230 Cubesats launched so far. Due to their small size and lightweight, Cubesats were launched by utilizing the empty space of regular launch vehicle. However, this launch method has a weakness that has been easily affecting by the schedule of major payloads. As a new solution to this problem, it has been proposed that a robot arm installed on ISS would be used to launch Cubesats. The orbits of Cubesat deployed from the ISS in various angles and directions are analyzed in this paper. We also analyze the possibility of collision between the Cubesat and ISS within the operational orbit of the CubeSat and eventually calculate the optimal angle of a robot arm, which maximizes the lifetime of Cubesat and minimizes the risk of collision between the Cubesat and ISS.

• The Journal of Korean Academy of Prosthodontics
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• v.45 no.4
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• pp.407-418
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• 2007

Purpose: The objective of this study was to evaluate the effects of hydrofluoric acid concentration & etching time on the shear bond strength between IPS Empress 2 ceramic and resin cement. Material and methods: Thirty three rectangular shape ceramic specimens($20{\times}12{\times}5mm$ size, IPS Empress 2 core materials) were used for this study. The ceramic specimens divided into ten experimental groups with three specimens in each group and were etched with hydrofluoric acid(4%, 9%) according to different etching times(30s, 60s, 90s, 120s, 180s). Etched surfaces of ceramic specimens were bonded with resin cement(Rely X Unicorn) using acrylic glass tube. All cemented specimens were tested under shear loading until fracture on universal testing machine at a crosshead speed of 0.5mm/min and the maximum load at fracture(kg) was recorded. Collected shear bond strength data were analyzed with one way ANOVA and Duncan tests. All etched ceramic surfaces were examined morphologically using SEM(scanning electron microscopy). Results: Shear bond strength of etching group$(35.89{\sim}68.01MPa)$ had four to seven times greater than no-etching group$(9.53{\pm}2.29MPa)$. The ceramic specimen etched with 4% hydrofluoric acid for 60s showed the maximum shear bond strength$(68.01{\pm}11.78MPa)$. Ceramic surface etched with 4% hydrofluoric acid for 60s showed most retentive surface texture. Conclusion: It is considered that 60s etching with 4% hydrofluoric acid is optimal etching methods for IPS Empress 2 ceramic bonding.

• Bulletin of the Korean Chemical Society
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• v.29 no.2
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• pp.413-416
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• 2008

A synthesis route to ordered mesoporous carbons with controllable nitrogen content has been developed for high-performance EDLC electrodes. Nitrogen-doped ordered mesoporous carbons (denoted as NMC) were prepared by carbonizing a mixture of two different carbon sources within the mesoporous silica designated by KIT-6. Furfuryl alcohol was used as a primary carbon precursor, and melamine as a nitrogen dopant. This synthesis procedure gave cubic Ia3d mesoporous carbons containing nitrogen as much as 13%. The carbon exhibited a narrow pore size distribution centered at 3-4 nm with large pore volume (0.6-1 cm3 g-1) and high specific BET surface area (700-1000 m2 g-1). Electrochemical behaviors of the NMC samples with various N-contents were investigated by a two-electrode measurement system at aqueous solutions. At low current density, the NMC exhibited markedly increasing capacitance due to the increase in the nitrogen content. This result could be attributed to the enhanced surface affinity between carbon electrode and electrolyte ions due to the hydrophilic nitrogen functional groups. At high current density conditions, the NMC samples exhibited decreasing specific capacitance against the increase in the nitrogen content. The loss of the capacitance with the N-content may be explained by high electric resistance which causes a significant IR drop at high current densities. The present results indicate that the optimal nitrogen content is required for achieving high power and high energy density simultaneously.

• Journal of Environmental Science International
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• v.2 no.1
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• pp.73-81
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• 1993

Adsorption process using granular activated carbon(GAC) has been considered as one of the most effective water treatment technologies to remove humic acid which is recon- niEed as trihalomethane(THM) precursor in chlorination. To design the most effective GAC process, it is necessary to conduct the test of adsor- ption performance by means of isothem, batch rate and column studies and to select the most effective activated carbon according to raw materials of GAC - lignite and coconut shell. The objective of this study is to investigate the adsorption performance of humid acid on two activated carbons - lignite activated carbon(LAC) and coconut shell activated car- bon(CAC) made in Korea. It is available to represent UV-abs and trihalomethane formation potential(THMFP) as concentration of humic acid due to good relationship. The adsorption capacity of humid acid is not concerned with surface area of activated carbon but with pore size related to about $100{\AA}$, and then LAC forming at the extent of mesopore is found to be eight times more effective in adsorption capacity than CAC forming at micropore. The adsorption capacity of LAC and CAC is better at pH 5.5 than at pH 7. Pore and surface diffusion coefficients calculated from the diffusion model are $7.61\times10^{-13}m^2/sec$, $3.52\times10^{-15}m^2/sec$ for CAC, and $3.38\times10^{-12}m^2$/sec and $Ds=1.48{\times}10^{-15}m^2/sec$ for GAC respectively. From the results of column test it shows that the performance of LAC is also better than CAC and the optimal EBCT(Empty Bed Contact Time) is 4.52min. and activated carbon removes selectively the components of humic acid to be easily formed to THM.

• Journal of the korean society of oceanography
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• v.32 no.4
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• pp.163-170
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• 1997

Some CMP gathers acquired from shallow marine seismic reflection survey in offshore Korea do not show the hyperbolic trend of moveout. It originated from so-called swell effect of source and streamer, which are towed under rough sea surface during the data acquisition. The observed time deviations of NMO-corrected traces can be entirely ascribed to the swell effect. To correct these time deviations, a residual statics is introduced using Genetic Algorithms (GA) into the swell correction. A new class of global optimization methods known as GA has recently been developed in the field of Artificial Intelligence and has a resemblance with the genetic evolution of biological systems. The basic idea in using GA as an optimization method is to represent a population of possible solutions or models in a chromosome-type encoding and manipulate these encoded models through simulated reproduction, crossover and mutation. GA parameters used in this paper are as follows: population size Q=40, probability of multiple-point crossover P$_c$=0.6, linear relationship of mutation probability P$_m$ from 0.002 to 0.004, and gray code representation are adopted. The number of the model participating in tournament selection (nt) is 3, and the number of expected copies desired for the best population member in the scaling of fitness is 1.5. With above parameters, an optimization run was iterated for 101 generations. The combination of above parameters are found to be optimal for the convergence of the algorithm. The resulting reflection events in every NMO-corrected CMP gather show good alignment and enhanced quality stack section.

• Smart Structures and Systems
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• v.23 no.6
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• pp.695-702
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• 2019

The number of cable-stayed bridges has been increasing worldwide, causing issues in maintaining the structural safety and integrity of bridges. The stay cable, one of the most critical members in cable-stayed bridges, is vulnerable to wind-induced vibrations owing to its inherent low damping capacity. Thus, vibration mitigation of stay cables has been an important issue both in academia and practice. While a semi-active control scheme shows effective vibration reduction compared to a passive control scheme, real-world applications are quite limited because it requires complicated equipment, including for data acquisition, and power supply. This study aims to develop an Arduino-based integrated cable vibration control system implementing a semi-active control algorithm. The integrated control system is built on the low-cost, low-power Arduino platform, embedding a semi-active control algorithm. A MEMS accelerometer is installed in the platform to conduct a state feedback for the semi-active control. The Linear Quadratic Gaussian control is applied to estimate a cable state and obtain a control gain, and the clipped optimal algorithm is implemented to control the damping device. This study selects the magnetorheological damper as a semi-active damping device, controlled by the proposed control system. The developed integrated system is applied to a laboratory size cable with a series of experimental studies for identifying the effect of the system on cable vibration reduction. The semi-active control embedded in the integrated system is compared with free and passive mode cases and is shown to reduce the vibration of stay-cables effectively.

• The Journal of the Korea Contents Association
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• v.19 no.2
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• pp.99-111
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• 2019

With the low birth rate and the inner city decline, the number of small schools is expected to increase. In this trend, the Ministry of Education has consistently used the number of students as a standard for the merger and abolition of schools since 1982, but it seems that has generated a vicious circle of education in rural areas and also it did not reflect realistic requirements and changes in the times although it is efficiency of local education finances. With the number of students constantly decreasing, it has a high probability to make villages without schools in urban areas if decisions are made by the number of students. In this sense, it is suggested that regional contexts and socioeconomic environment should be taken into account rather than to conduct the merger and abolition of small schools with economic logic. It is necessary to change the direction of improving the quality of education through the operation of small schools for coexistence of schools and villages and a cultivating the manpower needed in the 21st century knowledge information society and the 4th industrial revolution era. Therefore, we tried to find tasks for expanding small schools of the local community and developing small schools suitable for future social change.

• Journal of the Korean Society of Radiology
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• v.10 no.3
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• pp.215-222
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• 2016

X-ray mammography is the most effective method for the diagnosis of calcified lesions of various breast diseases. To reduce patient dose and to obtain optimal image required for diagnosis, the performance of the mammography system should be maintained continuously. Because the target (anode) angle of the X-ray tube is measured from the central X-ray, the effective angle can be slightly different in view of the position on the detector, which can result in degrading spatial resolution of the imaging within the field of view. In this study, we measured the MTF to examine spatial resolution for positions on the detector in the digital mammography system. For a tungsten wire of $50{\mu}m$ diameter, the highest spatial frequency was obtained. It meant that a wire diameter for measuring MTF through LSF should be small compared to the pixel size of the detector used in the mammography system. The spatial resolution showed slightly different performance according to positions on the detector. The center position gave the best spatial resolution and positions away from the center showed the degraded performance although the difference of the spatial resolution was small. The effective focal spot size of the full width at half maximum also showed similar result. It concluded that the slightly increase of the effective focal spot size gave the degradation of the spatial resolution for positions on the detector.

• Journal of Internet Computing and Services
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• v.24 no.4
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• pp.127-135
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• 2023

This research paper explores the application of FinBERT, a variational BERT-based model pre-trained on financial domain, for sentiment analysis in the financial domain while focusing on the process of identifying suitable training data and hyperparameters. Our goal is to offer a comprehensive guide on effectively utilizing the FinBERT model for accurate sentiment analysis by employing various datasets and fine-tuning hyperparameters. We outline the architecture and workflow of the proposed approach for fine-tuning the FinBERT model in this study, emphasizing the performance of various datasets and hyperparameters for sentiment analysis tasks. Additionally, we verify the reliability of GPT-3 as a suitable annotator by using it for sentiment labeling tasks. Our results show that the fine-tuned FinBERT model excels across a range of datasets and that the optimal combination is a learning rate of 5e-5 and a batch size of 64, which perform consistently well across all datasets. Furthermore, based on the significant performance improvement of the FinBERT model with our Twitter data in general domain compared to our news data in general domain, we also express uncertainty about the model being further pre-trained only on financial news data. We simplify the complex process of determining the optimal approach to the FinBERT model and provide guidelines for selecting additional training datasets and hyperparameters within the fine-tuning process of financial sentiment analysis models.