• Nuclear Engineering and Technology
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• v.55 no.5
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• pp.1533-1540
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• 2023

Self-Powered Neutron Detectors(SPNDs) are used to calculate core power distributions, an essential factor in the safe operation of nuclear power plants. Some detectors may fail during normal operation, and signals from failed detectors are isolated from intact signals. The calculated detailed power distribution accuracy depends on the number of available detector signals. Failed detectors decrease the operating margin by enlarging the power distribution measurement error. Therefore, a thorough reconstruction of the failed detector signals is critical. This note suggests a compressive sensing based methodology that rationally reconstructs the readings of failed detectors. The methodology significantly improves reconstruction accuracy by sorting signals and removing high-frequency components from conventional compressive sensing methodology.

• Journal of the Ergonomics Society of Korea
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• v.31 no.2
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• pp.271-279
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• 2012

Objective: This study classified three different emotional states(boredom, pain, and surprise) using physiological signals. Background: Emotion recognition studies have tried to recognize human emotion by using physiological signals. It is important for emotion recognition to apply on human-computer interaction system for emotion detection. Method: 122 college students participated in this experiment. Three different emotional stimuli were presented to participants and physiological signals, i.e., EDA(Electrodermal Activity), SKT(Skin Temperature), PPG(Photoplethysmogram), and ECG (Electrocardiogram) were measured for 1 minute as baseline and for 1~1.5 minutes during emotional state. The obtained signals were analyzed for 30 seconds from the baseline and the emotional state and 27 features were extracted from these signals. Statistical analysis for emotion classification were done by DFA(discriminant function analysis) (SPSS 15.0) by using the difference values subtracting baseline values from the emotional state. Results: The result showed that physiological responses during emotional states were significantly differed as compared to during baseline. Also, an accuracy rate of emotion classification was 84.7%. Conclusion: Our study have identified that emotions were classified by various physiological signals. However, future study is needed to obtain additional signals from other modalities such as facial expression, face temperature, or voice to improve classification rate and to examine the stability and reliability of this result compare with accuracy of emotion classification using other algorithms. Application: This could help emotion recognition studies lead to better chance to recognize various human emotions by using physiological signals as well as is able to be applied on human-computer interaction system for emotion recognition. Also, it can be useful in developing an emotion theory, or profiling emotion-specific physiological responses as well as establishing the basis for emotion recognition system in human-computer interaction.

• Journal of the Ergonomics Society of Korea
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• v.36 no.5
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• pp.459-466
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• 2017

Objective: This study examined two traffic signals with a countdown indicator in terms of driver's reaction time and subjective satisfaction score and their performance was compared with a standard traffic signal in driving simulation. Background: Dilemma zone is created when a traffic light changes at intersections. It often pushes drivers to rush in urgent and premature decision making whether to go or stop and thus induces unnecessary mental load among drivers, which may lead to sudden conflicts with following vehicles at intersections. Method: Forty college students (male: 20, female: 20) participated in this driving simulation study. Three traffic signals were employed: (1) standard traffic signal; (2) countdown-separated signal; and (3) countdown-overlaid signal. The countdown-separated and countdown-overlaid signals were designed to inform drivers of the remaining time of a green light before tuning to an amber light. Reaction times (sec) and satisfaction scores (7-point scale) for the two signals with a countdown indicator were compared with those for the standard traffic signal. Results: Reaction times of the countdown-separated (0.49 sec) and countdown-overlaid (0.43 sec) signals were significantly shorter than that of the standard signal (0.67 sec). Satisfaction scores of the countdown-separated (5.3 point) and countdown-overlaid (5.6 point) signals were greater than that of the standard signal (3.8 point). Lastly, the countdown-overlaid signal showed better performance than the countdown-separated signal, but their differences in reaction time (0.06 sec) and satisfaction score (0.3 point) were small. Conclusion: Traffic signals with a countdown indicator can improve drivers' reaction time and satisfaction score than the standard traffic signal. Application: Traffic signals with a countdown indicator will be useful for reducing the length of dilemma zone at intersections, by allowing drivers to predict the remaining time of a green light.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.12 no.2
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• pp.308-315
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• 2001

In this paper, a new power amplifier is proposed for reduction of amplified RX band noise signals as well as intermodulation distortion signals using feedforward technique. This power amplifier is implemented for IMT-2000 basestation TX frequency band. Both TX band intermodulation distortion signals and RX band noise signals are reduced by controlling variable attenuator, phase shifter and error amplifier. The proposed power amplifier, which contains two loops-intermodulation distortion signals cancellation loop and RX band noise signals cancellation loop, can provide duplexer with low TX path insertion loss for various wireless communication systems due to choice of loose RX attenuation characteristic. The principle of the proposed amplifier is described graphically based on the conceptual schematic diagram. A two-tone test for power amplifier is done at 2.14GHz with frequency spacing of 5MHz, and RX band rejection test is done over RX full band of 60MHz with 1.95GHz center frequency. Experimental results represent that the cancellation performance of intermodulation distortion signals and RX band noise signals are more than 3 1dB and 21dB, respectively.

• Journal of Advanced Navigation Technology
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• v.10 no.1
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• pp.41-47
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• 2006

In this paper, a predistortion linearizer using the in-phase modulator is proposed. The harmonic generator of the proposed predistorter extracts a second harmonic signals. These signals are divided in-phase and quadrature-phase signals, and then amplifying each signals using variable gain amplifier. An in-phase modulator, modulate fundamental signal with second harmonic signals, generates the predistortion intermodulation distortion (IM) signals and controls amplitude and phase of them with modulation factors. As a result, this predistorter is suppressed intermodulation distortion signals of power amplifier effectively. The proposed linearizer has been implemented to operate in Cellular-band. The test results show that the third order IM is cancelled more than 20dB in case of CW 2-tone signals with ${\Delta}f$=1MHz. Also, it's improved the adjacent channel power ratio (ACPR) more than 7dB for IS-95 CDMA 1FA signals.

• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2002.11a
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• pp.461-467
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• 2002

Signals reduced from the brain had been considered as a noise that is caused by the stochastic process until 1980. The recent non-linear dynamic theory researches, however, reported that these signals are meaningful and deterministic chaos signals in which they show how the brain deals with various information Since this report, a wide range of researches has been carried out and still in progress. Thus, by using the correlational dimension, one of the non-linear analytical methods, the characteristics of the brain signals can be analyzed. In this thesis, the scent of lavender, which stimulates the olfactory sense, is introduced to measure EEG with the International 10-20 electrode system on 16 channels, and to analyze the interrelationship between the original signals before the stimulation and the changed signals after the stimulation. Finally, the effect of the scent stimulation to the brain is analyzed. The purpose of this thesis is to apply these analyzed results to the computerized mapping of the brain signals and possible ways of specifying the source of the brain signals through various medical applications.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.1
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• pp.85-93
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• 2007

In case that multichannel blind deconvolution (MBD) applies to signals of which autocorrelation has a high level, separated signals are temporally whitened by diagonal elements of a separation filter matrix. In order to reduce this distortion, the algorithms, which are based on either constraining diagonal elements of a separation filter matrix or estimating a separation filter matrix by using linear prediction residual signals, are presented. Still, some problems are generated in these methods, when we separate reverberation of signals themselves or interference signals from mixed signals. To solve these problems, this paper proposes the multichannel blind deconvolution method which divides processing procedure into the stage to separate interference signals and the stage to eliminate a reverberation of signals themselves. In simulation results, we confirm that the proposed algorithm can solve the problems.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2002.11a
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• pp.461-467
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• 2002

Signals produced from the brain had been considered as a noise that is caused by the stochastic process until 1980. The recent non-linear dynamic theory researches, however, reported that these signals are meaningful and deterministic chaos signals in which they show how the brain deals with various information Since this report a wide range of researches has been carried out and still in progress. Thus, by using the correlational dimension, one of the non-linear analytical methods, the characteristics of the brain signals can be analyzed. In this thesis, the scent of lavender, which stimulates the olfactory sense, is introduced to measure EEG with the International 10-20 electrode system on 16 channels, and to analyze the interrelationship between the original signals before the stimulation and the changed signals after the stimulation. Finally, the effect of the scent stimulation to the brain is analyzed. The purpose of this thesis is to apply these analyzed results to the computerized mapping of the brain signals and possible ways of specifying the source of the brain signals through various medical applications.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2004.03a
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• pp.380-384
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• 2004

A fuel spiking test was performed to measure the surge margin of the compressor in a gas turbine engine. During the test, fuel spiking signal was superimposed on the engine controller demand and the mixed signals were used to control a fuel line servo-valve. For the superimposition, a subsystem composed of a fuel controller and a function generator was used. During the fuel spiking test, the original scheduled fuel signals and the modified signals were compared to guarantee the consistency excluding the spiking signals. The spiking signals were carefully selected to maintain the engine speed constant. The fuel spiking effects were checked by three dynamic pressure sensors. Sensors were placed before the servo-valve, after the servo-valve, and after the compressor location, respectively. The modulations of the spiking signal duration and fuel flow rate were examined to make the- operating point approach the surge region. The real engine test was performed at the Altitude Engine Test Facility (AETF) in Korea Aerospace Research Institute (KARI). In the real engine test, fuel spiking signals with 25~50 ㎳ of spiking signal time and 17~46 % of base fuel flow rate condition were used. The dithering signal was 5~6 ㎃ at 490 Hz. The test results showed good agreement between the fuel spiking signals and the fuel line pressure signals. Also, the compressor discharge pressure signals showed fuel spiking effects and the changes of the operating point on the compressor characteristic map could be traced.

• Journal of the Korean Society for Nondestructive Testing
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• v.24 no.1
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• pp.8-14
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• 2004

Model-based inversion tools for eddy current signals have been developed by combining neural networks and finite element modeling, for quantitative flaw characterization in steam generator tubes. In the present work, interpretation of experimental eddy current signals was carried out in order to validate the developed inversion tools. A database was constructed using the synthetic flaw signals generated by the finite element model. The hybrid neural networks composed of a PNN classifier and BPNN size estimators were trained using the synthetic signals. Experimental eddy current signals were obtained from axisymmetric artificial flaws. Interpretation of flaw signals was conducted by feeding the experimental signals into the neural networks. The interpretation was excellent, which shows that the developed inversion tools would be applicable to the Interpretation of real eddy current signals.