• 대한기계학회논문집A
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• 제25권10호
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• pp.1651-1658
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• 2001

It is necessary to evaluate fatigue strength and reliability of the connecting rod which is core part in automotive engine to assure the high level of durability of automobile. For this purpose, the loading conditions in automotive engine is obtained by the dynamic analysis. Based on these results, the critical section was identified by the finite element analysis. The fatigue strength under constant amplitude was evaluated and the mean of the fatigue limit at R = -2.27 derived from the staircase method was 311.2MPa. And the failure probability( F$\sub$p/ ) derived from the strength-stress interference model is 0.0003% at the 99.99% confidence level and the mean factor of safety was 4.2.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권8호
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• pp.3630-3656
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• 2018

Degree distribution can provide basic information for structural characteristics and internal relationship in social network. It is a critical procedure for social network topology analysis. In this paper, based on the mean-field theory, we study a special type of social network with exponential distribution of time intervals. First of all, in order to improve the accuracy of analysis, we propose a spreading coefficient algorithm based on intimate relationship, which determines the number of the joined members through the intimacy among members. Then, simulation show that the degree distribution of follows the power-law distribution and has small-world characteristics. Finally, we compare the performance of our algorithm with the existing algorithms, and find that our algorithm improves the accuracy of degree distribution as well as reducing the time complexity significantly, which can complete 29.04% higher precision and 40.94% lower implementation time.

• 한국신뢰성학회지:신뢰성응용연구
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• 제11권3호
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• pp.213-224
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• 2011

In this paper, we analyze statistically the data set of first leak time of water pipeline. We classify first the leak time data by pipe type, location, diameter of pipe and, length of pipe. We perform the analysis of variance to indicate that there are significant difference of mean of the time between levels of the factor and also compare the distribution of levels using the multiple box-plot. When there are the difference of the mean, we perform the least significant test to find out what levels of the facor has a different mean.

• The Journal of the Acoustical Society of Korea
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• 제16권1E호
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• pp.41-48
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• 1997

The very purpose of subband codec is the attainment of data rate compression through the use of quantizer and optimum bit allocation for each decimated signal. Yet the question of floating-point quantization effects in subband codec has received scant attention. There has been no direct focus on the analysis of quantization errors, nor on design with quantization errors embedded explicitly in the criterion. This paper provides a rigorous theory for the modelling, analysis and optimum design of the general M-band subband codec in the presence of the floating-point quantization noise. The floating-point quantizers are embedded into the codec structure by its equivalent multiplicative noise model. We then decompose the analysis and synthesis subband filter banks of the codec into the polyphase form and construct an equivalent time-invariant structure to compute exact expression for the mean square quantization error in the reconstructed an equivalent time-invariant structure to compute exact expression for the mean square quantization error in the reconstructed output. The optimum design criteria of the subband codec is given to the design of the analysis/synthesis filter bank and the floating-point quantizer to minimize the output mean square error. Specific optimum design examples are developed with two types of filter of filter banks-orthonormal and biorthogonal filter bank, along with their perpormance analysis.

• Asian-Australasian Journal of Animal Sciences
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• 제21권5호
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• pp.677-684
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• 2008

Accurate estimation of dry matter intake (DMI) is a prerequisite to meet animal performance targets without penalizing animal health and the environment. The objective of the current study was to evaluate some of the existing models in order to predict DMI when lactating dairy cows were offered a total mixed ration containing a high level of concentrates and locally produced agricultural by-products. Six popular models were chosen for DMI prediction (Brown et al., 1977; Rayburn and Fox, 1993; Agriculture Forestry and Fisheries Research Council Secretariat, 1999; National Research Council (NRC), 2001; Cornell Net Carbohydrate and Protein System (CNCPS), Fox et al., 2003; Fuentes-Pila et al., 2003). Databases for DMI comparison were constructed from two different sources: i) 12 commercial farm investigations and ii) a controlled dairy cow experiment. The model evaluation was performed using two different methods: i) linear regression analysis and ii) mean square error prediction analysis. In the commercial farm investigation, DMI predicted by Fuentes-Pila et al. (2003) was the most accurate when compared with the actual mean DMI, whilst the CNCPS prediction showed larger mean bias (difference between mean predicted and mean observed values). Similar results were observed in the controlled dairy cow experiment where the mean bias by Fuentes-Pila et al. (2003) was the smallest of all six chosen models. The more accurate prediction by Fuentes-Pila et al. (2003) could be attributed to the inclusion of dietary factors, particularly fiber as these factors were not considered in some models (i.e. NRC, 2001; CNCPS (Fox et al., 2003)). Linear regression analysis had little meaningful biological significance when evaluating models for prediction of DMI in this study. Further research is required to improve the accuracy of the models, and may recommend more mechanistic approaches to investigate feedstuffs (common to the Asian region), animal genotype, environmental conditions and their interaction, as the majority of the models employed are based on empirical approaches.

• 한국도로학회논문집
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• 제17권4호
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• pp.135-141
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• 2015

PURPOSES: This study has been conducted to determine a homogeneous segment and integration to improve the efficiency of short-term traffic count. We have also attempted to reduce the traffic monitoring budget. METHODS: Based on the statistical approach, a homogeneous segment in the same road section is determined. Statistical analysis using t-test, mean difference, and correlation coefficient are carried out for 10-year-long (2004-2013) short-term count traffic data and the MAPE of fresh data (2014) are evaluated. The correlation coefficient represents a trend in traffic count, while the mean difference and t-score represent an average traffic count. RESULTS : The statistical analysis suggests that the number of target segments varies with the criteria. The correlation coefficient of more than 30% of the adjacent segment is higher than 0.8. A mean difference of 36.2% and t-score of 19.5% for adjacent segments are below 20% and 2.8, respectively. According to the effectiveness analysis, the integration criteria of the mean difference have a higher effect as compared to the t-score criteria. Thus, the mean difference represents a traffic volume similarity. CONCLUSIONS : The integration of 47 road segments from 882 adjacent road segments indicate 8.87% of MAPE, which is within an acceptable range. It can reduce the traffic monitoring budget and increase the count to improve an accuracy of traffic volume estimation.

• 기본간호학회지
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• 제1권2호
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• pp.193-205
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• 1994

The Study was carried out for the purpose of investigating the degree of perception in nursing activities. The data of this study were collected by self-reported questionnaire composed of 5 point rating scale measure the ideal level and the performance level of nurses activity. For the analysis of the data, percentage, MANOVA and ANOVA were 231 nurses in 3 general hospitals in Taegu. Data was administrated from October 4 through 14, 1994. The results were as follow : 1. The average mean score for the ideal level was 4.19 with a maximum possible score 5points. The highest mean score was Infection Controll and the lowest mean score was nutrition The average mean score for the performance level was 3.75, the highest mean score was fluid and electrolyte, the lowest mean score was nutrition. In the desirable nursing pergormance, Education was found the highest response above charge nurse, Medication was found the highest response above General nurse, environment was found the highest response above aide. 2. In the analysis of the relationship between the ideal level and th performance level, significant defference was found in age, position, career, marital status, occupation satisfaction, Nursing unit, parent. 3. In the analysis of the relationship between the ideal level and the performance level and the general characteristics, significant difference was found in marital status in the ideal level of direct nursing care, significant difference was found in age, position, marital status, nursing unit in the ideal level of indirect nursing care, significant difference was found in age, position, career, marital status, occupation satisfaction, nursing unit in the performance level of direct nursing care. significant difference was found in age (25-29) and above 30 career(4-7 and 7), occupation satisfaction(good and moderate, good and poor) in scheffe test of the performance level of direct nursing care.

• 대한토목학회논문집
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• 제31권1B호
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• pp.21-27
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• 2011

유출예측량을 모의할 때 과거와 현재의 수문자료를 이용한다는 측면에서 미래 예측결과의 불확실성을 완전히 제거할 수는 없겠지만, 다양한 기법별 분석에 의하여 불확실성을 감소시킬 수 있다. 본 연구에서는 유출예측의 정확성 향상을 위해 다양한 유출예측 기법을 적용 및 평가하였으며 확률론적 예측을 가능하게 하는 예측기법인 ESP와 관측 시계열 자료를 이용한 통계기법으로 공주지점의 유출예측을 수행하였다. 각 기법에 따른 유출예측 결과의 신뢰성 평가는 MAE(Mean Absolute Error), RMSE(Root Mean Squared Error), RRMSE(Relative Root Mean Squared Error), Mean Absolute Percentage Error (MAPE), TIC(Theil Inequality Coefficient)를 이용하였다. ESP 확률을 이용하여 예측한 유출결과와 통계적 시계열 분석에 의해 예측된 유출결과를 MAE, RMSE, RRMSE, MAPE, TIC를 이용하여 비교 분석하였으며 유출예측의 개선효과를 확인해본 결과, ESP 확률을 이용한 예측이 MAE(10.6), RMSE(15.14), RRMSE(0.244), MAPE(22.74%), TIC(0.13)으로 평가되었으며 MAE(23.2), RMSE(37.13), RRMSE(0.596), MAPE(26.69%), TIC(0.30)으로 평가된 ARMA와 MAE(26.4), RMSE(34.44), RRMSE(0.563), MAPE(47.38%), TIC(0.25)으로 평가된 Winters 에 비해 신뢰성이 높게 나타났다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권6호
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• pp.2450-2469
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• 2018

In this paper, we develop a spatiotemporal model to analysis of cellular user in underlay D2D communication by using stochastic geometry and queuing theory. Firstly, by exploring stochastic geometry to model the user locations, we derive the probability that the SINR of cellular user in a predefined interval, which constrains the corresponding transmission rate of cellular user. Secondly, in contrast to the previous studies with full traffic models, we employ queueing theory to evaluate the performance parameters of dynamic traffic model and formulate the cellular user transmission mechanism as a M/G/1 queuing model. In the derivation, Embedded Markov chain is introduced to depict the stationary distribution of cellular user queue status. Thirdly, the expressions of performance metrics in terms of mean queue length, mean throughput, mean delay and mean dropping probability are obtained, respectively. Simulation results show the validity and rationality of the theoretical analysis under different channel conditions.

• 대한의용생체공학회:의공학회지
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• 제27권2호
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• pp.47-52
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• 2006

The purpose of this study was to predict successful defibrillation in ventricular fibrillation using parameters extracted by wave analysis method and neuro-fuzzy. Total 15 dogs were tested for predicting successful defibrillation. Feature parameters were extracted for return of spontaneous circulation (ROSC) and non-ROSC by wave analysis method, and these parameters are an irregularity factor, spectral moments, mean power of level-crossing spectrum, and mean of alpha-significant value. Additionally, two parameters by analyzing method of frequency were extracted into a mean of power spectrum and a mean frequency. Then extracted parameters were analyzed in which parameters result to have high performance of discriminating ROSC and non-ROSC by a statistical method of t-test. The average of sensitivity and specificity were 62.5% and 75.0%, respectively. The average of positive predictive factor and negative predictive factor were 61.2% and 75.8%, respectively.