• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.2A
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• pp.196-201
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• 2010

Measurement of Quality of Service (QoS) parameters and its statistical analysis becomes a key issue for Mobile WiMAX service providers to manage the converged network efficiently and to support end-to-end QoS. In this paper, we investigate the population distribution of end-to-end one-way delay which is the most important QoS parameter in Mobile WiMAX networks. The samples are analyzed with Chi-Square Goodness-of-Fit test, Kolmogorov-Smirnov (K-S), and Anderson-Darling (A-D) test to verify the distribution of parent population. The relation with confidence level and the minimum number of sample size is also performed for logistic distribution. The statistical analysis is a promising approach for measuring the performance Mobile WiMAX networks.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.9
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• pp.1809-1814
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• 2009

In this paper, the problem of stability analysis for neural networks with discrete and distributed time-varying delays is considered. By constructing a new Lyapunov functional, a new delay-dependent stability criterion for the network is established in terms of LMIs (linear matrix inequalities) which can be easily solved by various convex optimization algorithms. Two numerical example are included to show the effectiveness of proposed criterion.

• Journal of Korea Multimedia Society
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• v.10 no.4
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• pp.450-461
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• 2007

In this paper, we propose the method to use power-saving mode (PSM) applicable to non real-time traffic and PSM applicable to real-time traffic simultaneously, for VoIP traffic with silence suppression. The proposed method uses PSC II during talk-spurt interval of parties A and/or B and uses PSC I or probabilistic sleep interval decision (PSID) method during mutual silence interval, respectively. To evaluate the performance of hybrid PSM (HPSM) based on PSC II or PSID method, we present average buffering delay, energy consumption of mobile station and VoIP packet drop probability with simulation runs. Results shows that proposed HPSM decreases energy consumption of mobile station up to 25 % while satisfying the packet drop probability within QoS requirement in case of end-to-end VoIP connection.

• Journal of Electrical Engineering and Technology
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• v.12 no.2
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• pp.726-737
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• 2017

The use of energy storage systems (ESSs) has become a feasible solution to solve the wind power intermittency issue. However, the use of ESSs increases the system cost significantly. In this paper, an optimal power flow control scheme to minimize the ESS capacity is proposed by using the zero-phase delay low-pass filter which can eliminate the phase delay between the dispatch power and the wind power. In addition, the filter time constant is optimized at the beginning of each dispatching interval to ensure the fluctuation mitigation requirement imposed by the grid code with a minimal ESS capacity. And also, a short-term power dispatch control algorithm is developed suitable for the proposed power dispatch based on the zero-phase delay low-pass filter with the predetermined ESS capacity. In order to verify the effectiveness of the proposed power management approach, case studies are carried out by using a 3-MW wind turbine with real wind speed data measured on Jeju Island.

• Tunnel and Underground Space
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• v.16 no.4 s.63
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• pp.326-333
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• 2006

In this study, the vibration waveform of the single hole which is not interfered from the different blasting holes is separated, the each dominant frequency which is determinated through the Fast Fourier Transform(FFT) is measured. Also the separation waveform executed a superposition modeling which changes to delay time from 1ms to 80 ms in 1ms interval and controls the number of blasting holes from 2 holes to 15 holes in order to investigate the effect of PPV according to the duration time of the vibration and the number of blasting holes. As a result of analysis, the longer the duration time of the vibration, the longer the delay time which is not interfered from the different blasting holes and the effect regarding the number of blasting holes from inside identical delay time did not appear a lot.

• Journal of Preventive Medicine and Public Health
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• v.53 no.3
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• pp.164-167
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• 2020

Objectives: As of March 3, 2020, the Shincheonji religious group accounted for the majority of Korean cases of coronavirus disease 2019 (COVID-19). Nonetheless, the most likely cause of the broad spread of COVID-19 among members of the Shincheonji religious group remains largely unknown. Methods: We obtained data of laboratory-confirmed cases related to the Shincheonji religious group from press releases by Korean public health authorities and news reports. We measured the period from the date of illness onset to the date of COVID-19 confirmation. Results: We analysed data from 59 cases (median age, 30 years). The estimated median period between the date of symptom onset and the date of COVID-19 confirmation was 4 days (95% confidence interval, 1-12). Conclusions: There was a delay in COVID-19 confirmation from the date of illness onset among the cases linked to the Shincheonji religious group. This delay likely contributed to the occurrence of many cases of COVID-19 in the group.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.2
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• pp.534-540
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• 1996

This paper presents an Adaptive Time-Delay Recurrent Neural Network (ATRN) for learning and recognition of temporal correlations of temporal patterns. The ATRN employs adaptive time-delays and recurrent connections, which are inspired from neurobiology. In the ATRN, the adaptive time-delays make the ATRN choose the optimal values of time-delays for the temporal location of the important information in the input parrerns, and the recurrent connections enable the network to encode and integrate temporal information of sequences which have arbitrary interval time and arbitrary length of temporal context. The ATRN described in this paper, ATNN proposed by Lin, and TDNN introduced by Waibel were simulated and applied to the chaotic time series preditcion of Mackey-Glass delay-differential equation. The simulation results show that the normalized mean square error (NMSE) of ATRN is 0.0026, while the NMSE values of ATNN and TDNN are 0.014, 0.0117, respectively, and in temporal learning, employing recurrent links in the network is more effective than putting multiple time-delays into the neurons. The best performance is attained bythe ATRN. This ATRN will be sell applicable for temporally continuous domains, such as speech recognition, moving object recognition, motor control, and time-series prediction.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.3
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• pp.1-10
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• 2009

Bus delay time is occurred as the result of traffic condition and important factor to predict bus arrival time. In this paper, transition probability matrixes between bus stops are made by using Markov Chain and it is predicted bus delay time with them. As the results of study, it is confirmed a possibility of adapting the assumption which it has same bus transition probability between stops through paired-samples T-test and overcame the limitation of exiting studies in case there is no scheduled bus arrival time for each stops with using bus interval time. Therefore it will be possible to predict bus arrival time with Markov Chain.

• Journal of Korea Society of Industrial Information Systems
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• v.12 no.3
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• pp.19-30
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• 2007

In this paper, we propose low-complexity implementation of orthogonal frequency division multiple access (OFDMA) timing delay detector with multiple receive antennas for broadband wireless access (BWA). First, in order to reduce the computational complexity, the detection structure which rotates the phase of the received ranging symbols is introduced. Second, we propose the detection structure with the N-point/M-interval fast Fourier transform structure and a frequency-domain average-power estimator for complexity reduction without sacrificing the system performance. Finally, simulation results for the proposed structures and complexity comparison of the existing structure with the proposed detectors are presented.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.6
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• pp.390-395
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• 2005

Sunspots are dark areas that grow and decay on the lowest level of the sun that is visible from the Earth. Shot-term predictions of solar activity are essential to help plan missions and to design satellites that will survive for their useful lifetimes. This paper presents a parallel-structure fuzzy system(PSFS) for prediction of sunspot number time series. The PSFS consists of a multiple number of component fuzzy systems connected in parallel. Each component fuzzy system in the PSFS predicts future data independently based on its past time series data with different embedding dimension and time delay. An embedding dimension determines the number of inputs of each component fuzzy system and a time delay decides the interval of inputs of the time series. According to the embedding dimension and the time delay, the component fuzzy system takes various input-output pairs. The PSFS determines the final predicted value as an average of all the outputs of the component fuzzy systems in order to reduce error accumulation effect.