• 대한통합의학회지
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• 제8권2호
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• pp.53-61
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• 2020

Purpose : We investigated the correlation between body composition and lung function in healthy adults. Methods : This study included 204 healthy adults in whom all measurements were obtained once, and all data were analyzed using the SPSS software for Windows, version 22.0. Pearson's correlation analysis was performed to determine the correlation between body composition (represented by the total body water, protein mass, soft lean mass, mineral mass, basal metabolic rate, fat-free mass, skeletal muscle mass, and body fat percentage) and lung function (represented by the forced vital capacity [FVC], forced expiratory volume in 1 second [FEV₁], the FEV₁/FVC ratio, maximum voluntary ventilation [MVV], maximum expiratory pressure [MEP], and the maximum inspiratory pressure [MIP]). All measurements were obtained by two investigators to improve reliability. A significance level of α=.05 was used to verify statistical significance. Results : Among the lung function measurements obtained in both men and women, the FVC, FEV₁, MVV, and MIP were positively correlated with the total body water, protein mass, soft lean mass, mineral mass, basal metabolic rate, fat-free mass, and skeletal muscle mass in men (p<.05). The FEV₁/FVC ratio was negatively correlated with the total body water, soft lean mass, mineral mass, basal metabolic rate, fat-free mass and the body fat percentage (p<.05). Notably, the FVC, FEV₁, and MVV were positively correlated with the total body water, protein mass, soft lean mass, mineral mass, basal metabolic rate, fat-free mass, and skeletal muscle mass in women (p<.05). Conclusion : This study showed a significant correlation between body composition and lung function in healthy adults. In combination with future studies on lung function, our results can provide objective evidence regarding the importance of prevention of lung disease, and our data can be utilized in rehabilitation programs for patients with respiratory diseases.

• 말소리와 음성과학
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• 제3권3호
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• pp.91-98
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• 2011

In this paper, a multi-channel speech enhancement method using the linearly constrained minimum variance (LCMV) algorithm and a variable learning rate control is proposed. To control the learning rate for adaptive filters of the LCMV algorithm, the direction of arrival (DOA) is measured for each short-time input signal and the likelihood function of the target speech presence is estimated to control the filter learning rate. Using the likelihood measure, the learning rate is increased during the pure noise interval and decreased during the target speech interval. To optimize the parameter of the mapping function between the likelihood value and the corresponding learning rate, an exhaustive search is performed using the Bark's scale distortion (BSD) as the performance index. Experimental results show that the proposed algorithm outperforms the conventional LCMV with fixed learning rate in the BSD by around 1.5 dB.

• Journal of the Korean Data and Information Science Society
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• 제25권3호
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• pp.623-632
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• 2014

We shall consider the estimation for the parameter and the right tail probability in a general exponential distribution. We also shall consider the estimation of the reliability P(X < Y ) and the skewness trends of the density function of the ratio X=(X+Y) for two independent general exponential variables each having different shape parameters and known scale parameter. We then shall consider the estimation of the failure rate average and the hazard function for a general exponential variable having the density function with the unknown shape and known scale parameters, and for a bivariate density induced by the general exponential density.

• 한국화재소방학회논문지
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• 제33권6호
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• pp.20-27
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• 2019

본 연구는 화재 시 열출력 급상승 구간에 대한 정확한 열방출율을 예측하기 위한 새로운 함수를 개발하여 제안하는 것을 목적으로 하였다. 현재 화재공학에서 사용되고 있는 'αt²' 곡선은 화재시스템 공학 관점에서 비효율적이며 실효성 저하를 초래하므로 열방출율의 예측오차를 최소화시킬 필요가 있다. 'αt²'과 비교하여 보다 논리적인 배경과 형태적으로 유사성을 가진 로지스틱 함수 이론을 기반으로 화재 급성장 구간은 물론 화재 초기 단계까지 적용 가능한 새로운 예측 함수를 개발하였다. 개발된 함수는 더 넓은 화재성장 구간에서 정확도 높은 예측결과를 갖는 것으로 본 연구에서 증명되었다. 이 연구결과는 향후 화재성장패턴 연구의 개발과 함께 화재공학의 발전을 위해 적용될 것이다.

• International Journal of Reliability and Applications
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• 제2권1호
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• pp.49-56
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• 2001

In this paper we consider empirical Bayes estimation of the hazard rate and survival probabilities with right censored data under the assumption that the hazard function is constant over the period of observation and the prior distribution is gamma. We provide an estimator of the first derivative of the prior moment generating function that converges at each point to the true value in $L_2$ and use it to obtain, easy to compute, asymptotically optimal estimators under the squared error loss function.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2013년도 춘계학술발표대회
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• pp.972-975
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• 2013

This work developed a code analysis & extraction tool named Function Network Analyzer (FNA) to reduce the cost of software safety analysis. FNA analyzes functions and variables which a given function depends on, and extracts subset of code that can be compiled of automotive operating system, final resulting a well-ordered code sequence that can be compiled for model checking technique. And the experimental result illustrates that FNA can get 100% accurate rate and over 96% reduction rate by testing API functions from trampoline system.

• International Journal of Reliability and Applications
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• 제17권2호
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• pp.149-158
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• 2016

We are enjoying a very comfortable life thanks to modern civilization, however, comfort is not guaranteed to us. Development of software system is a difficult and complex process. Therefore, the main focus of software development is on improving the reliability and stability of a software system. We have become aware of the importance of developing software reliability models and have begun to develop software reliability models. NHPP software reliability models have been developed through the fault intensity rate function and the mean value functions within a controlled testing environment to estimate reliability metrics such as the number of residual faults, failure rate, and reliability of the software. In this paper, we present a new NHPP software reliability model with Burr Type III fault detection rate, and present the goodness-of-fit of the fault detection rate software reliability model and other NHPP models based on two datasets of software testing data. The results show that the proposed model fits significantly better than other NHPP software reliability models.

• 무역학회지
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• 제46권6호
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• pp.191-209
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• 2021

In this paper, various time series analysis models and machine learning models are presented for long-term prediction of export growth rate, and the prediction performance is compared and reviewed by RMSE and MAE. Export growth rate is one of the major economic indicators to evaluate the economic status. And It is also used to predict economic forecast. The export growth rate may have a negative (-) value as well as a positive (+) value. Therefore, Instead of using the ReLU function, which is often used for time series prediction of deep learning models, the PReLU function, which can have a negative (-) value as an output value, was used as the activation function of deep learning models. The time series prediction performance of each model for three types of data was compared and reviewed. The forecast data of long-term prediction of export growth rate was deduced by three forecast methods such as a fixed forecast method, a recursive forecast method and a rolling forecast method. As a result of the forecast, the traditional time series analysis model, ARDL, showed excellent performance, but as the time period of learning data increases, the performance of machine learning models including LSTM was relatively improved.

• 한국환경과학회지
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• 제13권3호
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• pp.263-277
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• 2004

The purpose of this study is to analyze the characteristics of riverbed variation due to the sediment protection weir located on the estuary of the main stream of Taehwa river using I-D finite difference model, HEC-6 model, and the followings are the results of estimating sediment transport rate, amount of scour or deposition, and accumulated amount of deposit according to before and after of the sediment protection weir removal with various flow rates in the channel. Ackers-White transport function produced the greatest sediment transport rate while Meyer-Peter showed the smallest sediment transport rate at the most down stream area of the watershed through the sediment transport rate analyses for various flow rates according to the existence or nonexistence of the sediment protection weir. Toffaleti's and Colby transport function were closest to the average value, and the difference among the results of the sediment transport functions showed up to 8～9 times. Duboy's transport function produced the greatest riverbed variation while Toffaleti's showed the smallest variation through the riverbed variation analyses according to the existence or nonexistence of the sediment protection weir. Yang's was closest to the average value, and the difference among the results of the riverbed variation analyses ranged from 1.4 times to 11 times. It is thought that a sediment transport function must be selected very carefully with respect to the criteria of sediment yield estimation because the analysis results of the sediment transport rate and riverbed variation according to flow rates showed significant differences among the sediment transport functions, and the differences of sediment transport rate and riverbed variation according to the various sediment transport functions decreased as the flow rate increased.

• KSBB Journal
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• 제13권6호
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• pp.730-734
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• 1998

An이ew식과 Aiba삭을 조합하여 에탄올 생산단주인 Saccharomyces cerevisiae ATCC 24858의 비성장속도를 당농도와 에탄올 농도의 함수로 표현하였다. 기침의 저해영향을 받지 않는 최대 당농도 $S_m$은 150 g/L이며 기질의 저해영향은 기질농도 S와 $S-S_{max}$항의 함수로 표현되었다. 최대 비성장 속도 ${\mu}max 는 0.49 hr^{-1}, Monod상수 K_s$는 19 g/L, Andrew식의 기질저해상수 $K_1$는 139 g/L이였다. 또한 비성장속도에 영향을 마치지 앓는 최대알콜농도 Pm이 존재하였으며 그 값은 2 g/L 이였다. 따라서 Aiba식에서 비성장속도에 영향을 미치는 에탄올 농도항은 P-Pm으보 표현되었다. 본 연구의 알코올생산균주에 대한 비성장속도의 완성된 수식은 디음과 같으며 이 수식에 위한 계산값은 평균오차 6% 내외의 범위에서 실험값과 일치하였다.