• The Korean Journal of Physiology
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• v.5 no.2
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• pp.15-27
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• 1971

Physiological analysis of the physical exercise was made on 9 subjects performing mountain climbing. The course between two points (256 and 516 meters altitude) was 1,300 meters in distance and difference of vertical height was 260 meters making the mean grade of 20%. In the field, the heart rates during uphill or downhill walk were recorded by EKG radio-telemetry. In the laboratory, oxygen consumption was obtained by the recorded heart rates, using individual heart rate vs oxygen consumption diagram obtained by treadmill test. the following results were obtained. 1. Uphill walk time was 36.5 minutes, and during this period the mean heart rate was 149.0 heats/min and peak heart rate was 169.2 beats/min. The total heart beats during the uphill walk was 5.433 beats. 2. The ratio of individual mean heart rate during the uphill walk to the maximal heart rate distributed between 66.6% and 98.3%, and the mean of the total group was 83.1%. The ratio of peak heart rate of uphill walk to the maximal heart rate was 94.5% in the group. Thus uphill walk of a 20% grade mountain course was an exhaustive exercise. 3. Oxygen consumption during uphill walk was 2.22 l/min (ranged between 1.79 and 2.70 l/min) and the ratio of this to the resting oxygen consumption was 8.31. The peak value of oxygen consumption during uphill walk was 2.73 l/min and the ratio of this to the resting oxygen consumption was 10.39. 4. Energy expenditure during uphill walk showed a mean of 11.1 kcal/min and the peak expenditure rate was 13.6 kcal/min. The total energy expenditure during 36.5 minutes of uphill walk was 396 kcal. 5. In downhill walk, the time was 31.7 minutes, mean heart rate was 118.4 (ranged between 100.1 and 142.7) beats/min, and the peak heart rate was only 129.4 beats/min. The ratio of mean heart rate to the maximal heart rate was 66.3%. Total heart beats during downhill walk was 3,710 beats. The ratio of downhill oxygen consumption to the resting consumption was 5.70. The rate of energy expenditure was 7.5 kcal/min, and the total onery expenditure during the 31.7 minutes of downhill walk was 228 kcal. 6. The effect of training was manifest in the uphill walk and not in the downhill walk. After training in mountain course walk, i) the uphill time was shortened, ii) mean heart rate increased, iii) time vs heart rate curve became smooth and showed less frequent zig-zag, i.e., the depth of trough on the curve decreased and the magnitude was less than 10 beats. In non-trained subject the depth of trough on the curve was greater than 50 beats and appeared more frequently. 7. Mountain climbing is a good health promotion exercise. For the promotion of health the reasonable amount of uphill mountain walk exercise in a 20% grade course is a walk for 40 or 50 minutes duration once a week.

• Journal of Soil and Groundwater Environment
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• v.6 no.3
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• pp.61-71
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• 2001

A regional master recession curve model to predict groundwater discharges in a given basin was presented. Considering a stream-aquifer system, both theoretical and experimental baseflow equations were compared and a practical groundwater discharge equation was derived, The groundwater discharge equation was expanded and transformed to the discharge equation at the basin exit. For practical use, the equation was expressed as a function of watershed area, the mean slope of basin and the recession constant. To verify the model, the model was applied to Ssang-chi basin where long-term and temporal hydrological data at the upper basin were collected. Our results show that a master recession curve of unmeasured area can be predicted.

• Journal of Korea Water Resources Association
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• v.43 no.3
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• pp.265-273
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• 2010

This study proposed the method that can calculate discharge using hydraulic characteristics that can acquire easily-comparatively such as hydraulic radius, bed slope, depth to improve the stage-discharge curve equation considering only stage. Roughness coefficient n value and C value that hydraulic characteristics of rivers is reflected from Manning's equation and Chezy's equation using the measured data of the natural open channel in the report of Albert University estimated and calculated discharge on the basis of this. The method proposed in this study was calculated stunningly to measured discharge. And that compared with discharge by existent stage-discharge curve.

• The korean journal of orthodontics
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• v.52 no.5
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• pp.354-361
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• 2022

Objective: To analyze the overall treatment effects in terms of the amount of uprighting with changes in the three-dimensional positions of the mandibular posterior teeth after applying the biocreative reverse curve (BRC) system. Methods: Thirty-four patients (mean age, 20.5 ± 8.56 years) were treated using the BRC system (mean period, 8.17 ± 2.19 months). Cone-beam computed tomography was performed before treatment and after treatment with the BRC system. The three-dimensional movement of each tooth was analyzed in the coordinate system at points on the crown and root apex. A paired t-test was used to analyze the treatment effects of the BRC system. Results: The application of the BRC system spanning from the first premolar to the second molar resulted not only in buccal and distal uprighting, but also in increased buccal and distal tipping of the teeth. The premolars and the first molar were extruded, and the second molar was intruded. Conclusions: When the BRC system is applied, simultaneous distal and buccal uprighting of the premolars and molars can be achieved bilaterally using a temporary skeletal anchorage device without unnecessary movement of the anterior teeth.

• Nuclear Engineering and Technology
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• v.55 no.8
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• pp.2844-2853
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• 2023

A sophisticated Bayesian multilevel model for estimating group bias was developed to improve the utility of the ASTM E900-15 embrittlement trend curve (ETC) to assess the conditions of nuclear power plants (NPPs). For multilevel model development, the Baseline 22 surveillance dataset was basically classified into groups based on the NPP name, product form, and notch orientation. By including the notch direction in the grouping criteria, the developed model could account for TTS differences among NPP groups with different notch orientations, which have not been considered in previous ETCs. The parameters of the multilevel model and biases of the NPP groups were calculated using the Markov Chain Monte Carlo method. As the number of data points within a group increased, the group bias approached the mean residual, resulting in reduced credible intervals of the mean, and vice versa. Even when the number of surveillance test data points was less than three, the multilevel model could estimate appropriate biases without overfitting. The model also allowed for a quantitative estimate of the changes in the bias and prediction interval that occurred as a result of adding more surveillance test data. The biases estimated through the multilevel model significantly improved the performance of E900-15.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.13 no.1
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• pp.39-49
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• 2013

This paper presents a method of improving the performance of a day-ahead 24-h load curve and peak load forecasting. The next-day load curve is forecasted using radial basis function (RBF) neural network models built using the best design parameters. To improve the forecasting accuracy, the load curve forecasted using the RBF network models is corrected by the weighted sum of both the error of the current prediction and the change in the errors between the current and the previous prediction. The optimal weights (called "gains" in the error correction) are identified by differential evolution. The peak load forecasted by the RBF network models is also corrected by combining the load curve outputs of the RBF models by linear addition with 24 coefficients. The optimal coefficients for reducing both the forecasting mean absolute percent error (MAPE) and the sum of errors are also identified using differential evolution. The proposed models are trained and tested using four years of hourly load data obtained from the Korea Power Exchange. Simulation results reveal satisfactory forecasts: 1.230% MAPE for daily peak load and 1.128% MAPE for daily load curve.

• Journal of Information Technology Applications and Management
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• v.12 no.2
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• pp.1-13
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• 2005

This paper proposes a software-reliability growth model incoporating the amount of testing effort expended during the software testing phase after developing it. The time-dependent behavior of testing effort expenditures is described by a Logistic curve. Assuming that the error detection rate to the amount of testing effort spent during the testing phase is proportional to the current error content, a software-reliability growth model is formulated by a nonhomogeneous Poisson process. Using this model the method of data analysis for software reliability measurement is developed. After defining a software reliability, This paper discusses the relations between testing time and reliability and between duration following failure fixing and reliability are studied. SRGM in several literatures has used the exponential curve, Railleigh curve or Weibull curve as an amount of testing effort during software testing phase. However, it might not be appropriate to represent the consumption curve for testing effort by one of already proposed curves in some software development environments. Therefore, this paper shows that a logistic testing-effort function can be adequately expressed as a software development/testing effort curve and that it gives a good predictive capability based on real failure data.

• Journal of Animal Science and Technology
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• v.59 no.2
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• pp.3.1-3.7
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• 2017

Background: The modelling of lactation curve provides guidelines in formulating farm managerial practices in dairy cows. The aim of the present study was to determine the suitable non-linear model which most accurately fitted to lactation curves of five lactations in 134 Gir crossbred cows reared in Research-CumDevelopment Project (RCDP) on Cattle farm, MPKV (Maharashtra). Four models viz. gamma-type function, quadratic model, mixed log function and Wilmink model were fitted to each lactation separately and then compared on the basis of goodness of fit measures viz. adjusted $R^2$, root mean square error (RMSE), Akaike's Informaion Criteria (AIC) and Bayesian Information Criteria (BIC). Results: In general, highest milk yield was observed in fourth lactation whereas it was lowest in first lactation. Among the models investigated, mixed log function and gamma-type function provided best fit of the lactation curve of first and remaining lactations, respectively. Quadratic model gave least fit to lactation curve in almost all lactations. Peak yield was observed as highest and lowest in fourth and first lactation, respectively. Further, first lactation showed highest persistency but relatively higher time to achieve peak yield than other lactations. Conclusion: Lactation curve modelling using gamma-type function may be helpful to setting the management strategies at farm level, however, modelling must be optimized regularly before implementing them to enhance productivity in Gir crossbred cows.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.12
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• pp.1169-1172
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• 2006

The prices of chemical products are fluctuated by several factors. The chemical companies can't predict and be ready to all of these changes, so they are exposed to the risk of a profit fluctuation. But they can reduce this risk by making a well-diversified product portfolio. This problem can be thought as the optimization of the product portfolio. We assume that the profits come from the 'spread' between a naphtha and a chemical product. We calculate a mean and a variation of each spread and develop an automatic module to calculate the optimal portion of each product. The theory is based on the Markowitz portfolio management. It maximizes the expected return while minimizing the volatility. At last we draw an investment selection curve to compare each alternative and to demonstrate the superiority. And we suggest that an investment selection curve can be a decision-making tool.

• Communications for Statistical Applications and Methods
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• v.21 no.1
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• pp.105-114
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• 2014

In this paper we suggest an efficient method to estimate the distribution function using the Bezier curve, and compare it with existing methods by simulation studies. In addition, we suggest a robust version of cross-validation criterion to estimate the number of Bezier points, and showed that the proposed method is better than the existing methods based on simulation studies.