• 대한물리의학회지
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• 제16권1호
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• pp.33-39
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• 2021

PURPOSE: This study compared the body composition according to the sport of short-distance and middle & long-distance athletes to identify the factors that affect the body composition. METHODS: Forty-eight athletes selected as youth national athletes in 2019 participated in the study. The study participants measured the length of the lower extremities, body composition, and anaerobic ability. An independent sample t-test was conducted to compare the body composition according to the event. In addition, the Pearson correlation was performed to identify the factors that influence the body composition. RESULTS: The leg length of the Short and Middle & long-distance athletes were similar (p = .584). On the other hand, there were differences in the body fat percentage (p = .001), lean percentage (p = .001), and BMI (p = .001). In addition, the body fat percentage was correlated with the lean body mass (r = .419) and BMI (r = .447). Furthermore, the lean body mass was correlated with the BMI (r = .849) and the peak power (r = .662) and mean power (r = .686) of the anaerobic capacity. Moreover, the BMI was correlated with the peak power (r = .490) and mean power (r = .543) of the anaerobic capacity. The peak power of the anaerobic ability was correlated with the mean power (r = .931). CONCLUSION: The body composition differed according to the sport. The body fat percentage correlated with the lean body mass and the BMI. The lean body mass correlated with the BMI, peak power of anaerobic ability, and mean power. The BMI correlated with the anaerobic capacity.

• 한국안전학회지
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• 제14권2호
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• pp.155-162
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• 1999

reliability from components reliability. In this case, it assumes that components failure is mutually independent, but it may not true in real systems. In this study, the mean cost per unit time is computed as the ratio of mean life to the mean cost. The mean life is obtained by the reliability function under power rule model. The mean cost is obtained by the mathematical model based on the inspection interval. A heuristic method is proposed to determine the optimal number of redundant units and the optimal inspection interval to minimize the mean cost per unit time. The assumptions of this study are as following : First, in the load-sharing k-out-of-n:G system, total loads are applied to the system and shared by the operating components. Secondly, the number of failed components affects the failure rate of surviving components as a function of the total load applied. Finally, the relation between the load and the failure rate of surviving components is set by the power rule model. For the practical application of the above methods, numerical examples are presented.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2001년도 제14회 신호처리 합동 학술대회 논문집
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• pp.915-918
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• 2001

In this paper we study a new convergence behavior of the least mean fourth (LMF) algorithm where the error raised to the power of four is minimized for a multiple sinusoidal input and Gaussian measurement noise. Here we newly obtain the convergence equation for the sum of the mean of the squared weight errors, which indicates that the transient behavior can differ depending on the relative sizes of the Gaussian noise and the convergence constant. It should be noted that no similar results can be expected from the previous analysis by Walach and Widrow.

• 한국광학회지
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• 제8권4호
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• pp.320-326
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• 1997

Erbium 첨가 광섬유를 이용하여 광섬유 자이로스코프용 광대역폭 광원을 구성하였다. 광원의 구성방식을 달리하며 펌프 power에 따른 광원의 출력 power, 파장선폭, 중심파장을 측정하여 방식간에 이를 비교하였다. 시도된 4가지의 구성방식 중에서 'double pass'방식의 경우에 25 mW의 비교적 낮은 펌핑(파장 1.48.mu.m)으로 5.5 mW의 가장 큰 출력 power를 얻었으며, 충분히 펌핑하는 경우에 펌프 power 변화에 대한 중심파장 변화율이 거의 0에 가까운 안정된 특성을 얻을 수 있었다. 'Amplifier/source'방식은 광원의 출력은 가장 작았으나, 자이로 검출기에 입사되는 power면에서 다른 방식에 비해 최소한 100배 이상 큰 결과를 얻었다. 광원으로의 귀환 수준이 증가함에 따라 파장선폭은 증가했으나 출력 power는 감소했으며 귀환 수준 변화에 따른 중심파장의 변화가 크게 나타나서 귀환광이 자이로의 scale factor에 큰 영향을 미칠 것임을 예측할 수 있었다.

• 산업경영시스템학회지
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• 제39권1호
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• pp.64-72
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• 2016

In this paper, we utilize a Gaussian process to predict the power consumption in the air-conditioning system. As the power consumption in the air-conditioning system takes a form of a time-series and the prediction of the power consumption becomes very important from the perspective of the efficient energy management, it is worth to investigate the time-series model for the prediction of the power consumption. To this end, we apply the Gaussian process to predict the power consumption, in which the Gaussian process provides a prior probability to every possible function and higher probabilities are given to functions that are more likely consistent with the empirical data. We also discuss how to estimate the hyper-parameters, which are parameters in the covariance function of the Gaussian process model. We estimated the hyper-parameters with two different methods (marginal likelihood and leave-one-out cross validation) and obtained a model that pertinently describes the data and the results are more or less independent of the estimation method of hyper-parameters. We validated the prediction results by the error analysis of the mean relative error and the mean absolute error. The mean relative error analysis showed that about 3.4% of the predicted value came from the error, and the mean absolute error analysis confirmed that the error in within the standard deviation of the predicted value. We also adopt the non-parametric Wilcoxon's sign-rank test to assess the fitness of the proposed model and found that the null hypothesis of uniformity was accepted under the significance level of 5%. These results can be applied to a more elaborate control of the power consumption in the air-conditioning system.

• 한국인터넷방송통신학회논문지
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• 제19권4호
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• pp.161-167
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• 2019

최근 안정적인 전력수급과 급증하는 전력수요를 예측하는 수요예측 기술에 대한 관심과 실시간 전력측정을 가능하게 하는 스마트 미터기의 보급의 증대로 인해 수요예측 기법에 대한 연구가 활발히 진행되고 있다. 본 연구에서는 실제 측정된 가정의 전력 사용량 데이터를 학습하여 예측결과를 출력하는 딥 러닝 예측모델 실험을 진행한다. 그리고 본 연구에서는 데이터 전처리 기법으로써 이동평균법을 도입하였다. 실제로 측정된 데이터를 학습한 모델의 예측량과 실제 전력 측정량을 비교한다. 이 예측량을 통해서 전력공급 예비율을 낮춰 사용되지 않고 낭비되는 예비전력을 줄일 수 있는 가능성을 제시한다. 또한 본 논문에서는 같은 데이터, 같은 실험 파라미터를 토대로 세 종류의 기법: 다층퍼셉트론(Multi Layer Perceptron, MLP), 순환신경망(Recurrent Neural Network, RNN), Long Short Term Memory(LSTM)에 대해 실험을 진행하여 성능을 평가한다. 성능평가는 MSE(Mean Squared Error), MAE(Mean Absolute Error)의 기준으로 성능평가를 진행했다.

• 한국전문물리치료학회지
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• 제6권2호
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• pp.16-31
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• 1999

The purpose of this study was to assess the fatigue in lumbar and abdominal muscles in patients with chronic low back pain compared with normal subjects using spectral analysis with mean power frequency and median power frequency. The experimental group consisted of twenty subjects who had experienced chronic low back pain for over one year after the onset day. A control group consisted of twenty normal subjects with no history of low back pain. All subjects stood in an apparatus to perform sustained contraction in the lumbar and abdominal muscles for 30 seconds with 60% maximal voluntary isometric contraction (MVIC). The resulting electromyographic (EMG) recorded time serial data were transformed into frequency serial data by Fast Fourier Transformation (FFT). The results were as follows: 1) lumbar muscles measured, the frequency change ratio of both median power frequency and mean power frequency was significantly greater for experimental group compared with control group group (p<0.05). In measured two abdominal muscles (inferior rectus abdominis, obliquus externus abdominis) except superior rectus abdominis, the frequency change ratio of both median power frequency and mean power frequency was significantly greater for experimental group compared with control group (p<0.05). 2) In all three (longissimus thoracis, iliocostalis lumborum, multifidus) lumbar muscles measured, the initial frequency value of both median power frequency and mean power frequency was significantly lower for the experimental group compared with the control group (p<0.05). In the two (inferior rectus abdominis, obliquus externus abdominis) abdominal muscles measured (superior rectus abdominis not included), the initial frequency value of both median power frequency and mean power frequency was significantly lower for the experimental group compared with the control group (p<0.05). These results suggest that in patients with chronic low back pain there is a trend for more fatigue to occur in both lumbar and abdominal muscles than in the normal control group. This would seem to suggest that in treatment programs for patients with chronic low back pain, improvement of endurance in all trunk muscles should be considered.

• 한국통계학회:학술대회논문집
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• 한국통계학회 2003년도 추계 학술발표회 논문집
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• pp.253-256
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• 2003

In ecological studies, animal science, or entomology, the variance of count is considered to have the power of the mean relationship with the mean count as Taylor (1961) presented his famous 'Taylor's Power Law'. In this talk, we are going to review the development of TPL and its extension toward pest management sampling scheme. Different estimation methods are compared. Quasilikelihood approach is suggested to incorporate covariate information. Possible extensions will be discussed.

• 전기학회논문지P
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• 제59권2호
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• pp.154-157
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• 2010

In this paper, the Time-varying Failure Rates(TFR) of power distribution system components are extracted from the recorded failure data of KEPCO(Korea Electric Power Corporation) and the reliability of power distribution system is evaluated using Mean Failure Rate(MFR) and TFR. The TFR is approximated to bathtub curve using the exponential and Weibull distribution function. In addition, Kaplan-Meier estimation is applied to TFR extraction because of incomplete failure data of KEPCO. Also the reliability of the real power distribution system of Korea is evaluated using the MFR and TFR extracted from real failure data, respectively and the results of each case are compared with each other. As a result, it is proved that the reliability evaluation using the TFR is more realistic than MFR. In addition, it is presented that the application method at power distribution system maintenance and repair using the result of TFR.

• Journal of Power Electronics
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• 제15권6호
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• pp.1619-1627
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• 2015

This paper presents a power system harmonic elimination using the mixed adaptive linear neural network and variable step-size leaky least mean square (ADALINE-VSSLLMS) control algorithm based active power filter (APF). The weight vector of ADALINE along with the variable step-size parameter and leakage coefficient of the VSSLLMS algorithm are automatically adjusted to eliminate harmonics from the distorted load current. For all iteration, the VSSLLMS algorithm selects a new rate of convergence for searching and runs the computations. The adopted shunt-hybrid APF (SHAPF) consists of an APF and a series of 7^th tuned passive filter connected to each phase. The performance of the proposed ADALINE-VSSLLMS control algorithm employed for SHAPF is analyzed through a simulation in a MATLAB/Simulink environment. Experimental results of a real-time prototype validate the efficacy of the proposed control algorithm.