• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 1998.04a
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• pp.44-56
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• 1998

Effects of the music and white noise on recovery of the autonomic and cortical responses evoked by aversive visual stimulation were analyzed in 20 subjects. It was suggested that the music is able to exert modulatory influence on the physiological activity resulted from exposure to unpleasant IAPS based stimuli. Spectral power of DDG, heart rate(HR)respiration rate (RSR) and electrodermal activity(EDA)were recorded and analyzed for each experimental condition. It was observed HR and RSR deceleration, increased EDA and electrocortical activation expressed in decreased alpha power and increase of delta activity ao occipital and frontal areas. Obtained results suggest that audutory stimulation both with pleasant and sad music lead to restoration of pre-stimulation activation levels of most physiological parameters during listenning to music and in post-stimulation period. White noise evoked short-term physiological responses typical for orienting reaction and quite distinct from changes produced by music. Available data to differentiate effeces among pleasant and sad music, due toqualitative similarities of physilolgical patterns, but suppert an assumption that music is capable to facilitate the process of recovery of physilolgical responses elicited by visual stimulation of negative valence, thus positively modulate post-stress state.

• Proceedings of the IEEK Conference
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• 2005.11a
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• pp.841-844
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• 2005

Multi-output VC-TCXO (Voltage Controlled-Temperature Compensated Crystal Oscillator) for WCDMA has integrated the additional CMOS inverter, so it can be normal clipped sinewave output and additional CMOS output and it can be satisfied the VC-TCXO Characteristics that WCDMA system required. In this paper, however 26MHz is used for reference frequency, similarly and practically, it is usable from 10MHz to 40MHz, Most important factor to integrate CMOS inverter internally is the isolation between normal output and additional output. For this, it is separated in package design, due to this, when it isn't used additional output, it shows the same electrical performance, when it is used additional output, it has minimum-rized the interference. and then the important characteristics in reference oscillator are met to WCDMA system's requirements, like phase noise and frequency short term stability.

• Journal of the Korea Society of Computer and Information
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• v.23 no.8
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• pp.17-23
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• 2018

In this paper, we implemented a flight posture simulator that intuitively understands aircraft flight posture and visualizes the principle of motion. The proposed system operates the 6 - axis motion platform according to the change of the navigation information and transmits the flight attitude to the simulator using the gyro sensor. A gyro sensor and an acceleration sensor are used together to analyze the attitude of the aircraft. The reason is that the gyro sensor has a cumulative error in the integration process. And the accelerometer sensor was compensated by using the complementary filter because noise was serious due to short term vibration. Using the compensated sensor information, the motion platform is operated by calculating the angle to be transmitted to the 6-axis motor. And visualization result is implemented using OpenGL. The results of this study can be used as teaching materials for students related to aviation in the future.

• Journal of Astronomy and Space Sciences
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• v.15 no.2
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• pp.437-447
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• 1998

Orbit error analysis was performed for the GPS navigation solutions and ground station tracking data of the KOMPSAT (Korea Multi-Purpose SATellite), which will be launched in 1999 for cartography of Korean peninsula as main mission. A least square method was used for the orbit determination and prediction error simulation including tracking data noises and dynamic modeling errors. It was found that a short-term periodic orbit determination error was caused by the tracking data noise and dominant orbit prediction error was caused by solar flux uncertainty.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.9
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• pp.893-897
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• 2008

To achieve the challenges of low-cost MEMS gyros for the precise self-localization of mobile robots, this paper examines an effective method of minimizing the drift on the heading angle that relies solely on integration of rate signals from a gyro. The main idea of the proposed approach is to use wavelet de-noising filter in order to reduce random noise which affects short-term performances. The proposed method was applied to Epson XV3500 gyro and the performances are verified by the comparisons with an existing commercial gyro module of vacuum cleaning robots.

• Proceedings of the Acoustical Society of Korea Conference
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• 1995.06a
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• pp.146-149
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• 1995

This paper proposes a SM-CELP speech coder which applies different excitation signal according to the characteristic of speech segment at bit-rate below 4 kbps. Speech signal is divided with 2 modes such as stationary voice and etc. using the parameters of average energy of the short-time speech and the residual signal after long term prediction. Structured multi-pulse method is used for the excitation of mode-A and gaussian or pulse-like codebook for mode-B. 4.8kbps DoD-CELP are used to evaluate the performance of the proposed coder. As a result, the propose method shows 1~2 dB higher segmental signal to noise ratio and better subjectional quality without increasing the computational amount.

• Journal of Korean Society of Water and Wastewater
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• v.18 no.6
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• pp.758-769
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• 2004

The trends and seasonalities of most time series have a large variability. The result of the Singular Spectrum Analysis(SSA) processing is a decomposition of the time series into several components, which can often be identified as trends, seasonalities and other oscillatory series, or noise components. Generally, forecasting by the SSA method should be applied to time series governed (may be approximately) by linear recurrent formulae(LRF). This study examined forecasting ability of SSA-LRF model. These methods are applied to daily water demand data. These models indicate that most cases have good ability of forecasting to some extent by considering statistical and visual assessment, in particular forecasting validity shows good results during 15 days.

• ETRI Journal
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• v.39 no.6
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• pp.832-840
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• 2017

Recently, deep recurrent neural networks have achieved great success in various machine learning tasks, and have also been applied for sound event detection. The detection of temporally overlapping sound events in realistic environments is much more challenging than in monophonic detection problems. In this paper, we present an approach to improve the accuracy of polyphonic sound event detection in multichannel audio based on gated recurrent neural networks in combination with auditory spectral features. In the proposed method, human hearing perception-based spatial and spectral-domain noise-reduced harmonic features are extracted from multichannel audio and used as high-resolution spectral inputs to train gated recurrent neural networks. This provides a fast and stable convergence rate compared to long short-term memory recurrent neural networks. Our evaluation reveals that the proposed method outperforms the conventional approaches.

• Structural Engineering and Mechanics
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• v.70 no.6
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• pp.649-659
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• 2019

Vibration-based structural damage detection through optimization algorithms and minimization of objective function has recently become an interesting research topic. Application of various objective functions as well as optimization algorithms may affect damage diagnosis quality. This paper proposes a new damage identification method using Moth-Flame Optimization (MFO). MFO is a nature-inspired algorithm based on moth's ability to navigate in dark. Objective function consists of a term with modal assurance criterion flexibility and natural frequency. To show the performance of the said method, two numerical examples including truss and shear frame have been studied. Furthermore, Los Alamos National Laboratory test structure was used for validation purposes. Finite element model for both experimental and numerical examples was created by MATLAB software to extract modal properties of the structure. Mode shapes and natural frequencies were contaminated with noise in above mentioned numerical examples. In the meantime, one of the classical optimization algorithms called particle swarm optimization was compared with MFO. In short, results obtained from numerical and experimental examples showed that the presented method is efficient in damage identification.

• ETRI Journal
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• v.46 no.3
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• pp.379-391
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• 2024

To meet increasing traffic requirements in mobile networks, small base stations (SBSs) are densely deployed, overlapping existing network architecture and increasing system capacity. However, densely deployed SBSs increase energy consumption and interference. Although these problems already exist because of densely deployed SBSs, even more SBSs are needed to meet increasing traffic demands. Hence, base station (BS) switching operations have been used to minimize energy consumption while guaranteeing quality-of-service (QoS) for users. In this study, to optimize energy efficiency, we propose the use of deep reinforcement learning (DRL) to create a BS switching operation strategy with a traffic prediction model. First, a federated long short-term memory (LSTM) model is introduced to predict user traffic demands from user trajectory information. Next, the DRL-based BS switching operation scheme determines the switching operations for the SBSs using the predicted traffic demand. Experimental results confirm that the proposed scheme outperforms existing approaches in terms of energy efficiency, signal-to-interference noise ratio, handover metrics, and prediction performance.