• The Bulletin of The Korean Astronomical Society
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• v.39 no.1
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• pp.75.2-75.2
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• 2014

We have developed a set of daily solar flare peak flux forecast models using the multiple linear regression (MLR), the auto regression (AR), and artificial neural network (ANN) methods. We consider input parameters as solar activity data from January 1996 to December 2013 such as sunspot area, X-ray flare peak flux, weighted total flux $T_F=1{\times}F_C+10{\times}F_M+100{\times}F_X$ of previous day, mean flare rates of a given McIntosh sunspot group (Zpc), and a Mount Wilson magnetic classification. We compute the hitting rate that is defined as the fraction of the events whose absolute differences between the observed and predicted flare fluxes in a logarithm scale are ${\leq}$ 0.5. The best three parameters related to the observed flare peak flux are as follows: weighted total flare flux of previous day (r=0.5), Mount Wilson magnetic classification (r=0.33), and McIntosh sunspot group (r=0.3). The hitting rates of flares stronger than the M5 class, which is regarded to be significant for space weather forecast, are as follows: 30% for the auto regression method and 69% for the neural network method.

• The Bulletin of The Korean Astronomical Society
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• v.36 no.1
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• pp.29.2-29.2
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• 2011

Although stellar flares have a long history of observations, there are few concrete understanding about underlying physical processes and meaningful correlations with other stellar properties. Most of previous observations dealt with only a small number of sample stars, and therefore not sufficient to support generalized statistical studies. Based on one-month long MMT time-series observations of the open cluster M37, we monitored light variations of nearly 2,500 M-dwarf stars and successfully identified 606 flare events from 422 stars. This is a rare attempt to estimate true flare rates and properties among many stars of the same age and mass group. For each flare, we considered both observational and physical parameters including flare shape, duration before and after the peak, baseline magnitude before and after the peak, peak magnitudes, total energy and peak energy, etc. We find significant correlations between some of key parameters over a wide range of energy ($Er=10^{32}{\sim}10^{36}ergs$). For instance, regardless of stellar luminosities, the energy power spectrum of flares can be approximated by a power law (${\beta}=0.83-0.97$). This suggests that flares follow similar physical mechanisms for atmospheric heating and cooling among these low-mass stars. From this MMT data set, we derived an average flaring rate of $0.019 hr^{-1}$ among flare stars and $0.003 hr^{-1}$ for all M-dwarf candidates. We will report the details of our analysis and discuss physical implications.

• Nuclear Engineering and Technology
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• v.53 no.12
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• pp.4179-4188
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• 2021

This study identifies efficient earthquake intensity measures (IMs) for seismic performances and fragility evaluations of the reactor containment building (RCB) in the advanced power reactor 1400 (APR1400) nuclear power plant (NPP). The computational model of RCB is constructed using the beam-truss model (BTM) for nonlinear analyses. A total of 90 ground motion records and 20 different IMs are employed for numerical analyses. A series of nonlinear time-history analyses are performed to monitor maximum floor displacements and accelerations of RCB. Then, probabilistic seismic demand models of RCB are developed for each IM. Statistical parameters including coefficient of determination (R²), dispersion (i.e. standard deviation), practicality, and proficiency are calculated to recognize strongly correlated IMs with the seismic performance of the NPP structure. The numerical results show that the optimal IMs are spectral acceleration, spectral velocity, spectral displacement at the fundamental period, acceleration spectrum intensity, effective peak acceleration, peak ground acceleration, A95, and sustained maximum acceleration. Moreover, weakly related IMs to the seismic performance of RCB are peak ground displacement, root-mean-square of displacement, specific energy density, root-mean-square of velocity, peak ground velocity, Housner intensity, velocity spectrum intensity, and sustained maximum velocity. Finally, a set of fragility curves of RCB are developed for optimal IMs.

• Journal of Broadcast Engineering
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• v.14 no.5
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• pp.573-588
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• 2009

In this paper, we propose a novel video quality degradation monitoring scheme titled VR-VQMS(Visual Rhythm based Video Quality Monitoring Scheme) over an IPTV service prone to packet losses during network transmission. Proposed scheme quantifies the amount of quality degradation due to packet losses, and can be classified into a RR(reduced-reference) based quality measurement scheme exploiting visual rhythm data of H.264-encoded video frames at a media server and reconstructed ones at an Set-top Box as feature information. Two scenarios, On-line and Off-line VR-VQMS, are proposed as the practical solutions. We define the NPSNR(Networked Peak-to-peak Signal-to-Noise Ratio) modified by the well-known PSNR as a new objective quality metric, and several additional objective and subjective metrics based on it to obtain the statistics on timing, duration, occurrence, and amount of quality degradation. Simulation results show that the proposed method closely approximates the results from 2D video frames and gives good estimation of subjective quality(i.e.,MOS(mean opinion score)) performed by 10 test observers. We expect that the proposed scheme can play a role as a practical solution to monitor the video quality experienced by individual customers in a commercial IPTV service, and be implemented as a small and light agent program running on a resource-limited set-top box.

• ETRI Journal
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• v.33 no.1
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• pp.99-109
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• 2011

This paper concerns a robust real-time voice activity detection (VAD) approach which is easy to understand and implement. The proposed approach employs several short-term speech/nonspeech discriminating features in a voting paradigm to achieve a reliable performance in different environments. This paper mainly focuses on the performance improvement of a recently proposed approach which uses spectral peak valley difference (SPVD) as a feature for silence detection. The main issue of this paper is to apply a set of features with SPVD to improve the VAD robustness. The proposed approach uses a weighted voting scheme in order to take the discriminative power of the employed feature set into account. The experiments show that the proposed approach is more robust than the baseline approach from different points of view, including channel distortion and threshold selection. The proposed approach is also compared with some other VAD techniques for better confirmation of its achievements. Using the proposed weighted voting approach, the average VAD performance is increased to 89.29% for 5 different noise types and 8 SNR levels. The resulting performance is 13.79% higher than the approach based only on SPVD and even 2.25% higher than the not-weighted voting scheme.

• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.295-297
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• 2007

We design a new rate-3/2 full-diversity orthogonal space-time block code (STBC) for QPSK and 2 transmit antennas (TX) and 4 transmit antennas (TX) by enlarging the signalling set from the set of quaternions used in the Alamouti[I] and extendedcode and using additional members of the set of orthogonal matrices or Quasi-orthogonal matrices and higher than rate-5/4. Selective power scaling of information symbols is used to guarantee full-diversity while maximizing the coding gain (CG) and minimizing the transmitted signal peak-to-minimum power ratio (PMPR). The optimum power scaling factor is derived analytically and shown to outpetform schemes based only on constellation rotation while still enjoying a low-complexity maximum likelihood (ML) decoding algorithm.

• Journal of Astronomy and Space Sciences
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• v.29 no.3
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• pp.245-251
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• 2012

Since the development of surface magnetic features should reflect the evolution of the solar magnetic field in the deep interior of the Sun, it is crucial to study properties of sunspots and sunspot groups to understand the physical processes working below the solar surface. Here, using the data set of sunspot groups observed at the ButterStar observatory for 3,364 days from 2002 October 16 to 2011 December 31, we investigate temporal change of sunspot groups depending on their Z$\ddot{u}$rich classification type. Our main findings are as follows: (1) There are more sunspot groups in the southern hemisphere in solar cycle 23, while more sunspot groups appear in the northern hemisphere in solar cycle 24. We also note that in the declining phase of solar cycle 23 the decreasing tendency is apparently steeper in the solar northern hemisphere than in the solar southern hemisphere. (2) Some of sunspot group types make a secondary peak in the distribution between the solar maximum and the solar minimum. More importantly, in this particular data set, sunspot groups which have appeared in the solar southern hemisphere make a secondary peak 1 year after a secondary peak occurs in the solar northern hemisphere. (3) The temporal variations of small and large sunspot group numbers are disparate. That is, the number of large sunspot group declines earlier and faster and that the number of small sunspot group begins to rise earlier and faster. (4) The total number of observed sunspot is found to behave more likewise as the small sunspot group does. Hence, according to our findings, behaviors and evolution of small magnetic flux tubes and large magnetic flux tubes seem to be different over solar cycles. Finally, we conclude by briefly pointing out its implication on the space weather forecast.

• Journal of Internet Computing and Services
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• v.21 no.5
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• pp.119-127
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• 2020

As the electric vehicle (EV) market in South Korea grows, it is required to expand charging facilities to respond to rapidly increasing EV charging demand. In order to conduct a comprehensive facility planning, it is necessary to forecast future demand for electricity and systematically analyze the impact on the load capacity of facilities based on this. In this paper, we design and develop a Long Short-Term Memory (LSTM) neural network model that predicts the daily peak electric load at each charging station using the EV charging data of KEPCO. First, we obtain refined data through data preprocessing and outlier removal. Next, our model is trained by extracting daily features per charging station and constructing a training set. Finally, our model is verified through performance analysis using a test set for each charging station type, and the limitations of our model are discussed.

• Physical Therapy Rehabilitation Science
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• v.10 no.3
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• pp.311-319
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• 2021

Objective: To investigate the effect of emphasized initial contact by using a wearable air-pressure insole to provide auditory-feedback with variations of maximum peak pressure (MPP) of the affected side on spatiotemporal gait parameters and gait symmetry of stroke patients Design: A cross-sectional study Methods: Eighteen stroke patients participated in this study. All subjects walked five trials using an air-pressure insole that provides auditory feedback with different thresholds set on the insole. First, subjects walked without any auditory feedback. Then, the MPP threshold on the affected side was set from 70% and increase threshold by 10% after each trial until 100%. They walked three times or more on the gait analyzer for each trial, and the average values were measured. Before starting the experiment, subjects measured body weight, initial gait abilities and affected side MPP without auditory feedback. Results: Temporal and spatial variables were significantly increased in trials with auditory feedback from air-pressure insole except for non-paralyzed single support time and spatial gait symmetry compared to trials without auditory feedback(p<0.05). Among the four different thresholds, the walking speed, unaffected side single support time, affected and unaffected side stride, and affected side step length were greatest at 80% threshold of maximum peak, while affected single support time, temporal gait symmetry, and unaffected step length were greatest at the maximum peak of 100% threshold. Conclusions: These results indicate that auditory feedback gait using air-pressure insoles can be an effective way to improve walking speed, single support time, step length, stride, and temporal gait symmetry in stroke patients.

• Progress in Medical Physics
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• v.31 no.4
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• pp.135-144
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• 2020

Purpose: Gafchromic films for proton dosimetry are dependent on linear energy transfers (LETs), resulting in dose underestimation for high LETs. Despite efforts to resolve this problem for single-energy beams, there remains a need to do so for multi-energy beams. Here, a bimolecular reaction model was applied to correct the under-response of spread-out Bragg peaks (SOBPs). Methods: For depth-dose measurements, a Gafchromic EBT3 film was positioned in water perpendicular to the ground. The gantry was rotated at 15° to avoid disturbances in the beam path. A set of films was exposed to a uniformly scanned 112-MeV pristine proton beam with six different dose intensities, ranging from 0.373 to 4.865 Gy, at a 2-cm depth. Another set of films was irradiated with SOBPs with maximum energies of 110, 150, and 190 MeV having modulation widths of 5.39, 4.27, and 5.34 cm, respectively. The correction function was obtained using 150.8-MeV SOBP data. The LET of the SOBP was then analytically calculated. Finally, the model was validated for a uniform cubic dose distribution and compared with multilayered ionization chamber data. Results: The dose error in the plateau region was within 4% when normalized with the maximum dose. The discrepancy of the range was <1 mm for all measured energies. The highest errors occurred at 70 MeV owing to the steep gradient with the narrowest Bragg peak. Conclusions: With bimolecular model-based correction, an EBT3 film can be used to accurately verify the depth dose of scanned proton beams and could potentially be used to evaluate the depth-dose distribution for patient plans.