• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.6
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• pp.655-660
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• 2005

This paper studied the feature parameters less affected by the emotional variation for the development of the robust speech recognition technologies. For this purpose, the effect of emotional variation on the speech recognition system and robust feature parameters of speech recognition system were studied using speech database containing various emotions. In this study, LPC cepstral coefficient, met-cepstral coefficient, root-cepstral coefficient, PLP coefficient, RASTA met-cepstral coefficient were used as a feature parameters. And CMS and SBR method were used as a signal bias removal techniques. Experimental results showed that the HMM based speaker independent word recognizer using RASTA met-cepstral coefficient :md its derivatives and CMS as a signal bias removal showed the best performance of $7.05\%$ word error rate. This corresponds to about a $52\%$ word error reduction as compare to the performance of baseline system using met - cepstral coefficient.

• The Korean Journal of Pesticide Science
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• v.17 no.3
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• pp.200-205
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• 2013

Mating disruption experiments were evaluated and compared in several pheromone traps and sex pheromone composition ratios at commercial chestnut garden for developing alternative control method of D. punctiferalis. The highest attractive was shown in Delta traps at the effective sex pheromone ratio of 75:25 (E10-16:A1:Z10-16:A1). Comparisons of domestic and imported pheromone constituents were not significant difference in 90:10 (E10-16:A1:Z10-16:A1). But, there was significant difference in sex pheromone ratio of 75:25. D. punctiferalis was caught the highest number in Gongju area for attractive test using pheromone trap. Attractive effects with dose of pheromone were showed the highest at 2.5 mg/lure and 1 mg/lure in Gongju area and Cheongyang area respectively. However, there was no significant difference among pheromone dose in Buyeo area. These data could be useful for eco-friendly managing of D. punctiferalis in the chestnut farm.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.5
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• pp.608-616
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• 2017

The purpose of this study was to compare how three kinds of emotionally different music impacted on the emotion and arousal by measuring EEG. The research method was to compare the measurement of the background EEG on Fp1 and Fp2 before, while and after listening using a 2-channel EEG device with various experimental groups aging from 20s to 50s. The results were as follows. 1) At both Fp1 and Fp2, the amplitude of alpha(8-13Hz), SMR(12-15Hz), low beta, high beta, and ${\alpha}/-{\beta}$significantly increased in all music, while at Fp2 only, theta and ??/SMR increased meaningfully.2) At right prefrontal cortex(Fp2), all bands of EEG predominated while and after listening to all songs over Fp1 except for the delta of funeral march which predominated while listening to Fp1.3) The music with a noticeably high alpha value and increased activity was Prelude. These results suggested that Prelude induced brain activity along with relaxation, and the emotionally heavy burden of funeral march decreased the activity of the left brain. This research revealed that feeling emotional change by listening to music was due to the fact that music influenced the brain activity inducing the change of emotion and arousal.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.8
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• pp.5336-5342
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• 2015

Although demand for scar treatment has been rising as our quality of life is improved, most scar treatment products rely on importation. Enkephalin is one of the neuropeptides secreted from neuronal ends. As both skin and neuron are derived from the exoderm during the development process, skin cells express opioid receptors as neuronal cells do. Opioid receptors are categorized into three types, mu(m)-, delta(d)-, and kappa(k)- opioid receptors, all of which are directly involved in the wound healing process. In this study, enkephalin derivatives are synthesized by Alanin Scan and their efficacy was evaluated and compared. In vitro wound healing effects, stimulatory effects of collagen synthesis, and skin hydration effects were also evaluated and confirmed. Among Enkephalin derivatives, AS13 showed highest wound healing effect.

• Sleep Medicine and Psychophysiology
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• v.15 no.1
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• pp.33-38
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• 2008

Introduction: It has been proposed that narcolepsy and REM sleep behavior disorder (RBD) have overlapped symptom profile and pathophysiology. This study was aimed at measuring and comparing changes in EEG frequency band of REM sleep in narcolepsy and RBD, applying EEG spectral analysis method. Methods: Nine patients diagnosed as narcolepsy and the same number of RBD patients were studied. Spectral analysis of the REM sleep EEG was performed in each patient on 9 epochs selected evenly from the first, second, and third REM periods. Then, we compared frequency band percentages of REM sleep EEG in narcolepsy and RBD. Results: Narcolepsy patients had significantly higher delta frequency ratio than RBD ones (p=0.00). In alpha and beta2 frequency bands, RBD patients showed higher percentage than narcolepsy ones. Slow wave sleep was more prevalent in narcolepsy patients. But, no difference of REM sleep percentage was found between the two groups (p=0.93). Conclusion: Higher delta frequency ratio in REM sleep of narcolepsy patients than RBD ones reflects that sleep-promoting mechanism is more dominant in narcolepsy than in RBD.

• Pediatric Infection and Vaccine
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• v.31 no.1
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• pp.83-93
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• 2024

Purpose: Since the start of the coronavirus disease 2019 (COVID-19) pandemic, various variants of concern have emerged. We divided the representative COVID-19 mutation period into four waves and aimed to analyze the clinical and laboratory features of children with COVID-19 from pre-mutation wave to the middle of omicron wave. Methods: We retrospectively reviewed the medical records of hospitalized patients aged ≤19 years with laboratory confirmed COVID-19. Clinical and laboratory findings during pre-mutation (February 1st 2020 to September 30th 2020), alpha/beta (October 1st 2020 to May 31st 2021), delta (June 1st 2021 to October 31st 2021), and omicron (November 1st 2021 to May 31st 2022) waves were compared. Results: Among total 827 patients, 163 (19.7%) were asymptomatic, and the frequency of fever and cough was 320 (38.7%) and 399 (48.2%), respectively. The proportion of fever ≥38.5℃ was observed to be high during the omicron wave in the age group under 12 years. Lymphopenia was observed highly in the omicron wave in the age group under 12 years, and in the delta wave in the age group older than 12 years. Neutropenia was highly observed in the delta wave in the 0-4 years age group. Conclusions: There were distinct characteristics during all epidemic waves of COVID-19. Children with COVID-19 had more frequent persistent fever during delta wave and children during the omicron wave had a higher peak fever.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.9
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• pp.1905-1912
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• 2009

Clustering results based on the FCM algorithm sometimes produces undesirable clustering result through data distribution in the clustered space because data is classified by comparison with membership degree which is calculated by the Euclidean distance between input vectors and clusters. Symmetrical measurement of clusters and fuzzy theory are applied to the classification to tackle this problem. The enhanced FCM algorithm has a low impact with the variation of changing distance about each cluster, middle of cluster and cluster formation. Improved hybrid network of applying FCM algorithm is proposed to classify patterns effectively. The proposed enhanced FCM algorithm is applied to the learning structure between input and middle layers, and normalized delta learning rule is applied in learning stage between middle and output layers in the hybrid network. The proposed algorithms compared with FCM-based RBF network using Max_Min neural network, FMC-based RBF network and HCM-based RBF network to evaluate learning and recognition performances in the two-dimensional coordinated data.

• Journal of Biomedical Engineering Research
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• v.24 no.2
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• pp.99-106
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• 2003

In this paper, a method of discriminating EEG for diagnoses of mental activity is proposed. The proposed method for classification of schizophrenia and normal EEG is based on the wavelet transform and the artificial neural network. The wavelet coefficients of $\alpha$ band, $\beta$ band, $\theta$ band, and $\delta$ band are obtained using the wavelet transform. The magnitude, mean, and variance of wavelet coefficients for each EEG band are applied to the input data of the system's ANN. The architecture of the ANN s a four layered feedforward network with two hidden layer which implements the error back propagation learning algorithm. Through the classification of schizophrenia composed of 19 ANNs corresponding to 19 channels, the classifying system show that it can classify the 100% of the normal EEG group and the 86.67% of the schizophrenia EEG group.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.1
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• pp.114-122
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• 2014

For an efficient finite-difference time-domain(FDTD) analysis of coaxial-probe feeding structures in radio frequency(RF) and microwave bands, an interrelation between equivalent source modeling techniques is investigated. In existing literature, equivalent source models with delta-gap or magnetic-frill concepts have been developed by many researchers. It is well known that FDTD implementation and computational accuracy of these source models are slightly different. In this paper, the interrelation between FDTD equivalent source models for coaxial feeding structures under the quasi-static approximation(QSA) is presented. As a function of FDTD equivalent source models, time-domain and frequency-domain responses of a coaxial-probe fed conical monopole antenna are calculated numerically. And comparison results of computational accuracy and efficiency are provided.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.12
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• pp.197-203
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• 2014

When the lightning current is injected to the ground system of information and communication facilities, analysis of the transient potential rise in the ground system is one of main factors to effectively design the ground system. The performance of grounding systems is normally estimated with the grounding impedance and the transient potential rise which represents the electrical characteristics of the grounding system. The method for calculating the grounding impedance depending on the injection point of the lightning current was proposed. The delta-gap source model was proposed to calculate the grounding impedance in the case that the lightning current is injected to the center of the horizontal ground electrode. A new program which is possible to apply the frequency-dependent soil parameters using the Debye model was developed, because a commercial program for analyzing the performance of the grounding system can not apply to the frequency-dependent soil parameters. The experiment was carried out to confirm the availability of the simulation results with the same condition. Finally, the transient potential rises of a horizontal ground electrode depending on the lightning current waveforms were analyzed by using the results of the grounding impedance which is associated with the frequency-dependent soil parameters.