• Journal of the Korean Operations Research and Management Science Society
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• v.36 no.1
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• pp.13-26
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• 2011

In order to explain the U-shaped pattern of autocorrelations of stock returns i.e., autocorrelations starting around 0 for short-term horizons and becoming negative and then moving toward 0 for long-term horizons, researchers suggested the use of a state-space model consisting of an I(1) permanent component and an AR(1) stationary component, where the two components are assumed to be independent. They concluded that auto-regression coefficients derived from the state-space model follow a U-shape pattern and thus there is mean-reversion in stock prices. In this paper, we show that only negative autocorrelations are feasible under the assumption that the permanent component and the stationary component are independent in the state-space model. When the two components are allowed to be correlated in the state-space model, we show that the sign of the auto-regression coefficients is not restricted as negative. Monthly return data for all NYSE stocks for the period from 1926 to 2007 support the state-space model with correlated noise processes. However, the auto-regression coefficients of the ARIMA process, equivalent to the state-space model with correlated noise processes, do not follow a U-shaped pattern, but are always positive.

• Ocean and Polar Research
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• v.23 no.4
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• pp.433-440
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• 2001

Marine organisms in Antarctica live in an environment which exhibits variability in physical processes over a wide range of temporal scales, from seconds to millennia. This time scale tends to be correlated with the spatial scale over which a given process operates, though this relationship is influenced by biology. The way organisms respond to variability in the physical environment depends on the time-scale of that variability in relation to life-span. Short-term variations are perceived largely as noise and probably have little direct impact on ecology. Of much greater importance to organisms in Antarctica are seasonal and decadal variations. Although seasonality has long been recognised as a key feature of polar environments, the realization that decadal scale variability is important is relatively recent. Long-term change has always been a feature of polar environments and may be a key factor in the evolution of the communities we see today.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.1203-1206
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• 2021

소음은 난청, 스트레스 등의 원인이 된다. 본 연구에서는 ANC(Active Noise Cancellation)을 바탕으로, 기술적인 방법을 통해 소음을 저감 시키는 스피커를 구현하였다. ANC 란 소음 주파수의 위상을 180° 변환하여 주파수와 레벨이 동일한 역 소음을 발생시켜 주변 소음을 저감, 차단하는 기술이다. 현재 시중 제품들에 적용되는 일반적인 ANC 의 경우, 피드백(Feedback) 방식이라는 점과 시간 지연(Time gap)이 발생한다는 한계가 있다. 이를 보완하기 위해 AI 학습으로 소음을 미리 예측하여 시간 지연을 줄이는 방법을 고안했다. 순환 신경망(RNN)의 장기의존성 문제를 해결하는 시계열 예측 딥러닝 알고리즘인 LSTM(Long Short-Term Memory Network) 모델을 사용하였다. 또한, AI 학습 효율을 향상시킬 수 있는 하드웨어 장비들을 활용하였다.

• Proceedings of the KSPS conference
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• 2003.10a
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• pp.97-100
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• 2003

This paper addresses a method of convolutive source separation that based on SEONS (Second Order Nonstationary Source Separation) [1] that was originally developed for blind separation of instantaneous mixtures using nonstationarity. In order to tackle this problem, we transform the convolutive BSS problem into multiple short-term instantaneous problems in the frequency domain and separated the instantaneous mixtures in every frequency bin. Moreover, we also employ a H infinity filtering technique in order to reduce the sensor noise effect. Numerical experiments are provided to demonstrate the effectiveness of the proposed approach and compare its performances with existing methods.

• Analytical Science and Technology
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• v.25 no.4
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• pp.223-229
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• 2012

Analytical signal from ICP was compensated by the light scattering of sample aerosols. Reference scattering signal was generated by a He-Ne or diode laser, monitored for the amount of aerosol producing and used for the compensation of analytical signals. The result showed that significant improvement in precision could be achieved for the short-term signal (within 1 minute) from 3.4% to 0.9% RSD in signal and 14.9% to 4.2% for the long-term (10 minutes) for Be, Pb and Co. This method is very useful not only for the pulse type but for continuous type signals especially when a nebulizer is unstable. To improve long-term precision, higher stability is required in the scattering cell and detector as well as the reduction of noise from the line between a nebulizer and plasma.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.14 no.12
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• pp.1279-1286
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• 2004

This paper continues companion paper, part I : measurement and analysis. As shown in companion Paper, information and energy in monaural signal is quite different from that of binaural signal. In this paper, difference between monaural and binaural signal of transportation noise are investigated in subjective response test. We executed hearing screening test before giving a subject response test and excluded subjects who had physical hearing loss. An annoyance response test was conducted using headphone to avoid cross-talk effect in binaural testing. Percentage of highly annoyed under binaural signal reproduction is higher than percentage of highly annoyed under monaural signal reproduction. Result implies binaural reproduction technique is proper for a study of human response to short-term noise exposure in a headphone simulated-environment.

• Korean Journal of Remote Sensing
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• v.37 no.4
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• pp.719-731
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• 2021

This study proposes a two-stage hybrid classification model for crop classification using multi-temporal remote sensing images; the model combines feature embedding by using an autoencoder (AE) with a convolutional neural network (CNN) classifier to fully utilize features including informative temporal and spatial signatures. Long short-term memory (LSTM)-based AE (LAE) is fine-tuned using class label information to extract latent features that contain less noise and useful temporal signatures. The CNN classifier is then applied to effectively account for the spatial characteristics of the extracted latent features. A crop classification experiment with multi-temporal unmanned aerial vehicle images is conducted to illustrate the potential application of the proposed hybrid model. The classification performance of the proposed model is compared with various combinations of conventional deep learning models (CNN, LSTM, and convolutional LSTM) and different inputs (original multi-temporal images and features from stacked AE). From the crop classification experiment, the best classification accuracy was achieved by the proposed model that utilized the latent features by fine-tuned LAE as input for the CNN classifier. The latent features that contain useful temporal signatures and are less noisy could increase the class separability between crops with similar spectral signatures, thereby leading to superior classification accuracy. The experimental results demonstrate the importance of effective feature extraction and the potential of the proposed classification model for crop classification using multi-temporal remote sensing images.

• Smart Structures and Systems
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• v.29 no.4
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• pp.599-616
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• 2022

Bridge displacement contains vital information for bridge condition and performance. Due to the limits of direct displacement measurement methods, the indirect displacement reconstruction methods based on the strain or acceleration data are also developed in engineering applications. There are still some deficiencies of the displacement reconstruction methods based on strain or acceleration in practice. This paper proposed a novel method based on long short-term memory (LSTM) networks to reconstruct the bridge dynamic displacements with the strain and acceleration data source. The LSTM networks with three hidden layers are utilized to map the relationships between the measured responses and the bridge displacement. To achieve the data fusion, the input strain and acceleration data need to be preprocessed by normalization and then the corresponding dynamic displacement responses can be reconstructed by the LSTM networks. In the numerical simulation, the errors of the displacement reconstruction are below 9% for different load cases, and the proposed method is robust when the input strain and acceleration data contains additive noise. The hyper-parameter effect is analyzed and the displacement reconstruction accuracies of different machine learning methods are compared. For experimental verification, the errors are below 6% for the simply supported beam and continuous beam cases. Both the numerical and experimental results indicate that the proposed data fusion method can accurately reconstruct the displacement.

• Journal of Sensor Science and Technology
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• v.14 no.6
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• pp.395-401
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• 2005

A highly stable quartz crystal microbalance (QCM) that showed a stability of frequencies and exhibited a very low noise level has been developed. The long-term drift was <0.05 Hz/h over a period of 10 h, and the short-term rms (root mean square) noise was <0.015 Hz. Our QCM sensor was used as a humidity sensor employing a poly(methyl methacrylate) (PMMA) polymer film as a hygroscopic layer, which showed good characteristics in the relative humidity (RH) range of $2{\sim}90%$ RH. Comparing the characteristics of the QCM sensor with those of other types of humidity sensors employing PMMA film as a hygroscopic layer, and with other QCM sensors employing other hygroscopic layers is represented.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.43 no.8 s.350
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• pp.6-12
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• 2006

Recently, according to the rapid development of mobile system, the development of relative mobile components has been required, and especially, with the miniaturization of mobile component, the complex with nearby components has been progressed. In this paper, multi-output VC-TCXO (Voltage Controlled-Temperature Compensated Crystal Oscillator) for WCDMA integrates the additional CMOS inverter, so it can be the normal clipped sinewave output and additional CMOS output, and also it can be satisfied the VC-TCXO's requirements for WCDMA system. And the important characteristics of reference oscillator, like phase noise and frequency short term stability, are satisfied with WCDMA(UMTS) system's requirement In this paper, however, 25MHz is used for reference frequency, similarly and practically, we think that it can be used from 10MHz to 40MHz.