• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.1
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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.

• Asian-Australasian Journal of Animal Sciences
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• v.19 no.7
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• pp.915-921
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• 2006

Various random regression models with different order of Legendre polynomials for permanent environmental and genetic effects were constructed to predict future milk yield of Holstein cows in Korea. A total of 257,908 test-day (TD) milk yield records from a total of 28,135 cows belonging to 1,090 herds were considered for estimating (co)variance of the random covariate coefficients using an expectation-maximization REML algorithm in an animal mixed model. The variances did not change much between the models, having different order of Legendre polynomial, but a decreasing trend was observed with increase in the order of Legendre polynomial in the model. The R-squared value of the model increased and the residual variance reduced with the increase in order of Legendre polynomial in the model. Therefore, a model with $5^{th}$ order of Legendre polynomial was considered for predicting future milk yield. For predicting the future milk yield of cows, 132,771 TD records from 28,135 cows were randomly selected from the above data by way of preceding partial TD record, and then future milk yields were estimated using incomplete records from each cow randomly retained. Results suggested that we could predict the next four months milk yield with an error deviation of 4 kg. The correlation of more than 70% between predicted and observed values was estimated for the next four months milk yield. Even using only 3 TD records of some cows, the average milk yield of Korean Holstein cows would be predicted with high accuracy if compared with observed milk yield. Persistency of each cow was estimated which might be useful for selecting the cows with higher persistency. The results of the present study suggested the use of a $5^{th}$ order Legendre polynomial to predict the future milk yield of each cow.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.40 no.8
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• pp.751-757
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• 2016

The aim of this study is to estimate the reliability of fatigue limit of the material used for crank throw components according to the staircase method. The material used for crank throw components is forged S34MnV grade steel, which is heat treated by normalizing and tempering. In this work, to predict the reliability of the design fatigue strength, axially loaded constant amplitude fatigue testing was conducted. The test specimens were loaded with an axial push/pull load with a mean stress of 0 MPa, which corresponds to a stress ratio of R=-1. The fatigue test results were evaluated by Dixon-Mood formulas. The values of mean fatigue strength and standard deviation predicted by the staircase method were 296.3 MPa and 10.6 MPa, respectively. Finally, the reliability of the fatigue limit in some selected probability of failure is predicted. The proposed method can be applied for the determination of fatigue strength for design optimization of the forged steel.

• Asian-Australasian Journal of Animal Sciences
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• v.14 no.11
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• pp.1511-1515
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• 2001

A prediction of 305 d milk production from early records using an empirical Bayes method (EBM) was performed. The EBM was compared with the best predicted estimation (BPE), test interval method (TIM), and the linearized Wood's model (LWM). Daily milk yields were obtained from 606 first lactation Japanese Holstein cows in three herds. From each file of 305 daily records, 10 random test day records with an interval of approximately one month were taken. The accuracies of these methods were compared using the absolute difference (AD) and the standard deviation (SD) of the differences between the actual and the estimated 305 d milk production. The results showed that in the early stage of the lactation, EBM was superior in obtaining the prediction with high accuracy. When all the herds were analyzed jointly, the AD during the first 5 test day records were on average 373, 590, 917 and 1,042 kg for EBM, BPE, TIM, and LWM, respectively. Corresponding SD for EBM, BPE, TIM, and LWM were on average 488, 733, 747 and 1,605 kg. When the herds were analyzed separately, the EBM predictions retained high accuracy. When more information on the actual lactation was added to the prediction, TIM and LWM gradually achieved better accuracies. Finally, in the last period of the lactation, the accuracy of both of the methods exceeded EBM and BPM. The AD for the last 2 samples analyzing all the herds jointly were on average 141, 142, 164, and 214 kg for LWM, TIM, EBM, and BPE, respectively. In the current practices of collecting monthly records, early prediction of future milk production may be more accurate using EBM. Alternatively, if enough information of the actual lactation is accumulated, TIM may obtain better accuracy in the latter stage of lactation.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.2
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• pp.791-793
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• 2013

Colorectal cancer is one of the most common cancers. The aim of this study is determination its trends in Kerman province and individual cities separately until year 2016. This analytical and modeling study was based of cancer registry data of Kerman University of Medical Sciences, collected during 2001-2010. Among 20,351 cancer case, 792 were colorectal cancer cases in age group 18-93 years with a mean of 59.4 and standard deviation of 15.1. By applying time series and data trends, incidences were predicted until 2016 for the province and each city, with adjustment for population size. In colorectal cases, 413 (52%) were male, and 379 (48%) were female. The annual increasing rate in Kerman province overall was and can be expected to be 6%, and in the cities of the province Rafsanjan, Bardsir, Bam, Kerman, Baft, Sirjan, Jiroft, Kahnuj and Manujan had an increasing range from 5 to 14% by the year 2016. But in Ravar, Zarand and Shahrbabak reduction in rates of at least 2% could be predicted. The time series showed that the trend of colorectal cancer in female will increase 15% and in male 7% by year 2016. Given the trend of this cancer is increasing so that resources will be consumed in the treatment of the patients, efforts shoudlbe focused on prevention and early diagnosis of the disease. Screening could have an important role leading to improved survival.

• Journal of Korean Society of Transportation
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• v.32 no.6
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• pp.686-693
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• 2014

This study presents a model that enables to predict road surface temperature using neural network theory. Historical road surface temperature data were collected from Road Weather Information System. They used for the calibration of the model. The neural network was designed to predict surface temperature after 1-hour, 2-hour, and 3-hour from now. The developed model was performed on Cheongwon-Sangju highway to test. As a result, the standard deviation of the difference of the predicted and observed was $1.27^{\circ}C$, $0.55^{\circ}C$ and $1.43^{\circ}C$, respectively. Also, comparing the predicted surface temperature and the actual data, R2 was found to be 0.985, 0.923, and 0.903, respectively. It can be concluded that the explanatory power of the model seems to be high.

• Magazine of the Korean Society of Agricultural Engineers
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• v.36 no.2
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• pp.96-110
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• 1994

The purpose of this study is to develop soil salt prediction model for the estimation of irrigation water requirements for dry field crops in reclaimed tidelands. The simulation model based on water balance equation, salt balance equation, and salt storage equation was developed for daily prediction of sa]t concentration in root zone. The data obtained from field measurement during the growing period of tomato were used to evaluate the applicability of this model. The results of this study are summarized as follows: 1.The optimum irrigation point which maximizes the crop yield in reclaimed tidelands of silt loam soil while maintaining the salt concentration within the tolerance level, ws found to be pF 1.6, and total irrigation requirement after transplanting was 602mm(6.7 mm/day)for tomato. 2.When the irrigation point was pF 1.6, the deviation between predicted and measured salt concentration was less than 4 % at the significance level of 1 7% 3.Since the deviations between predicted and measured values data decrease as the amount of irrigation water increases, the proposed model appear to be more suitable for use in reclaimed tidelands. 4.The amount of irrigation water estimated by the simulation model was 7.2mm/day in the average for cultivating tomato at the optimum irrigation point of pF 1.6.The simulation model proposed in this study can be generalized by applying it to other crops. This, model, also, could be further improved and extended to estimate desalinization effects in reclaimed tidelands by including meteorological effect, capillary phenomenon, and infiltration.

• Fire Science and Engineering
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• v.33 no.4
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• pp.9-15
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• 2019

The flash points of DMF based organic solvent mixtures used in the synthetic leather manufacturing process were measured. The test group was composed of seven types of solvent mixtures, which included DMF, toluene, and MEK. Each flash point was tested according to the international standard test methods of KS M 2010. The flash points were then predicted using some prediction models and compared with the measured data. From the analysis results, the binary mixtures with a mole ratio of less than approximately 0.7 showed that the measured values were under 25 ℃. This showed that the expectation for the flammable risk lowering effects due to the mixing of high flash point materials was reduced. In addition, the predicted values were evaluated using the average absolute deviation (A.A.D). The results showed that the Le Chatelier's models had an "A.A.D" of 1.95 ℃ and were the closest to the measured values.

• The Journal of Korean Physical Therapy
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• v.29 no.5
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• pp.281-286
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• 2017

Purpose: The purpose of this study was to examine the correlations among the resting physical factors related to a six-minute walk test (6MWT) and to determine the effects of the resting physical factors on the distance and intensity related to the 6MWT in healthy female subjects. Methods: A total of 43 healthy female subjects ($22.84{\pm}3.90yrs$) participated in this study. They performed the 6MWT, and the physical factors related to the 6MWT were assessed. SPSS 20.0 was used to analyze the data, and the mean and standard deviation were calculated, and the collected data were analyzed by the Pearson's correlation coefficient (among physical factors related to 6MWT) and independent t-test (between six-minute walk distance [6MWD] groups and six-minute walk intensity [6MWI] groups). Results: The 6MWD had a significant negative correlation with the resting HR (beat/min) in healthy female subjects (r=-0.49, p<0.05). The 6MWI had a significant negative correlation with the resting systolic blood pressure (SBP) (r=-0.45, p<0.01). A comparison of the 6MWD revealed the long distance group (LDG, 700-799 m) to be significantly higher than the middle distance group (MDG, 600-699 m) in the 6MWI (%), %predicted distance (%), predicted VO2max (mL/kg/min), resting HR (beat/min), and resting SBP (mmHg)(p<0.05). In the comparison of 6MWI, the moderate intensity group (MIG, 64-75%HRmax) was significantly lower than the low intensity group (LIG, 50-63%HRmax) in the resting SBP (mmHg) (p<0.05). Conclusion: These results suggest that the resting physical factors are related to the 6MWD and 6MWI of the 6MWT in healthy females. In particular, SBP is associated with not only the 6MWD but also the 6MWI in 6MWT.

• Journal of Advanced Navigation Technology
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• v.17 no.6
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• pp.638-645
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• 2013

For the efficient use of the insufficient frequency resources, a precise prediction of field strength based on various propagation environments should be set up to design of radio stations with reliable transmit power and service coverage. Therefore, many countries have tried to secure the propagation models suitable for their each geographical environments, and also, some models like BCAST were developed by Korea, but these models give the different results compared to measured values. In this paper, based on the measurements of DTV broadcasting services in domestic rural area, analysis and comparison of ITU-R P.1546 and BCAST models provide errors between measured and predicted values, and some points for improving SMI system has been proposed. As a result, P.1546 model provides the valid predicted data similar to measured data, but BCAST model has some problems of large deviation and higher prediction to measured data. In future, these problems and fading loss due to a forest or group of trees, and reflection loss due to a lake or sea need to be studied carefully.