• Tuberculosis and Respiratory Diseases
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• 제45권3호
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• pp.536-545
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• 1998

Background: The studies on prediction equations of pulmonary function parameters for adults in Korea have been performed in a reference population mainly consisted of young and middle ages. So they included a relatively few elderly who conducted pulmonary function test frequently in clinic. We established prediction equations of pulmonary function parameters for healthy adults over 50 years old in rural area and compared this results with those of other studies. Therefore we attempted to consider normative values of pulmonary function tests for elderly in Korea. Method: Five hundred thirty-three women and men over 50 years old in rural area were participated. A "healthy" subgroup of 110 women and 32 men were identified by excluding those who had conditions that negatively influenced pulmonary function. We derived prediction equations for FVC, $FEV_1$ and $FEV_1%$ by multiple linear regression method from their age, heights and weights in each sex. Results: Prediction equations for FVC and $FEV_1$ in each sex were derived as follows Male; FVC (L)=0.02488Height(cm)-0.0269Age(years)+0.493 $FEV_1(L)$=0.01874Weight(kg)-0.0282Age(years)+2.906 Female; FVC(L)=0.02160Height(cm)-0.0192Age(years)-0.0125 $FEV_1(L)$=0.01720Height(cm)-0.0194Age(years)+0.3890 Prediction equations for $FEV_1%$ were not derived because $FEV_1%$ didn't have statistically significant terms. Comparing Predicted values that were calculated by substitution into the equations of various studies of mean values of age, heights and weights from this study, FVC and $FEV_1$ values in men of this study were lower than those of other studies. In women, FVC and $FEV_1$ values of this study were as similar as or lower than those of the study conducted for healthy elderly blacks in U.S.A respectively. Conclusion: We have got prediction equations of pulmonary function parameters which were driven from forced expiratory spirogram in adults over 50 years old in rural area. Predicted values of this study were lower than those of other studies which were conducted in Korea. So we consider that the study for spirometry reference values for elderly Korean using the method compatible with ATS recommendation need to be conducted more frequently forward.

• KIPS Transactions on Computer and Communication Systems
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• 제9권1호
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• pp.17-24
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• 2020

In this paper, we present a movie rating prediction architecture based on a convolutional neural network (CNN). Our prediction architecture extends TextCNN, a popular CNN-based architecture for sentence classification, in three aspects. First, character embeddings are utilized to cover many variants of words since reviews are short and not well-written linguistically. Second, the attention mechanism (i.e., squeeze-and-excitation) is adopted to focus on important features. Third, a scoring function is proposed to convert the output of an activation function to a review score in a certain range (1-10). We evaluated our prediction architecture on a movie review dataset and achieved a low MSE (e.g., 3.3841) compared with an existing method. It showed the superiority of our movie rating prediction architecture.

• Journal of Institute of Control, Robotics and Systems
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• 제18권10호
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• pp.940-946
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• 2012

This paper proposes a method to predict maximum traction for unmanned robots on rough terrain in order to improve traversability. For a traction prediction, we use a friction-slip model based on modified Brixius model derived empirically in terramechanics which is a function of mobility number $B_n$ and slip ratio S. A friction-slip model includes characteristics of various rough terrains where robots are operated such as soil, sandy soil and grass-covered soil. Using a friction-slip model, we build a prediction model for terrain parameters on which we can know maximum static friction and optimal slip with respect to mobility number $B_n$. In this paper, Mobility number $B_n$ is estimated by modified Willoughby Sinkage model which is a function of sinkage z and slip ratio S. Therefore, if sinkage z and slip ratio are measured once by sensors such as a laser sensor and a velocity sensor, then mobility number $B_n$ is estimated and maximum traction is predicted through a prediction model for terrain parameters. Estimation results for maximum traction are shown on simulation using MATLAB. Prediction Performance for maximum traction of various terrains is evaluated as high accuracy by analyzing estimation errors.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 한국윤활학회 2002년도 proceedings of the second asia international conference on tribology
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• pp.355-356
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• 2002

The dielectric permittance and the dielectric loss factor of several lubricating oils were measured at frequencies from 100 Hz to 1.5 MHz. The measurements were carried out under atmospheric pressure as a function of temperature and under fixed temperature as a function of pressure. Temperature and pressure dependence of dielectric relaxation time were investigated. The temperature dependence of relaxation time obeyed the Vogel-Fulcher-Tammann (VFT) law. We modified the VFT equation in order to express the dielectric relaxation time as a function of temperature and pressure. Furthermore. by taking into consideration the similarity of the temperature and pressure dependence between dielectric relaxation and mechanical relaxation. the prediction of high-pressure viscosity were conducted. The predicted results were compared with the viscosity data obtained from the falling-sphere type viscometer.

• Journal of computational fluids engineering
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• 제6권4호
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• pp.15-25
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• 2001

Numerical prediction of the diffusion controlled transition in a turbine gas pass is important because it can change the local heat transfer rate over a turbine blade as much as three times. In this study, the gas flow over turbine blade is simplified to the flat plate boundary layer, and an adaptive grid scheme redistributing grid points within the computation domain is proposed with a great emphasis on the construction of the grid control function. The function is sensitized to the second invariant of the mean strain tensor, its spatial gradient, and the interaction of pressure gradient and flow deformation. The transition process is assumed to be described with a κ-ε turbulence model. An elliptic solver is employed to integrate governing equations. Numerical results show that the proposed adaptive grid scheme is very effective in obtaining grid independent numerical solution with a very low grid number. It is expected that present scheme is helpful in predicting actual flow within a turbine to improve computation efficiency.

• Journal of Korean Institute of Industrial Engineers
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• 제41권1호
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• pp.10-16
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• 2015

In this study, we suggest a method to predict probability distribution of a new customer's degree of loyalty using C-CRF that reflects the RFM score and similarity to the neighbors of the customer. An RFM score prediction model is introduced to construct the first feature function of C-CRF. Integrating demographical similarity, purchasing characteristic similarity and purchase history similarity, we make a unified similarity variable to configure the second feature function of C-CRF. Then parameters of each feature function are estimated and we train our C-CRF model by training data set and suggest a probabilistic distribution to estimate a new customer's degree of loyalty. An example is provided to illustrate our model.

• Transactions of Materials Processing
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• 제25권3호
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• pp.189-194
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• 2016

In the current study, spring-back of DP980 steel sheet was numerically evaluated for U-bending using a yield function with a hardening model. For spring-back prediction, two types of yield functions - Hill'48 and Yld2000-2d - were considered. Additionally, isotropic hardening and the Yoshida-Uemori model were used to investigate the spring-back behavior. The parameters for each model were obtained from uniaxial tension, uniaxial tension-compression, uniaxial tension-unloading and hydraulic bulging tests. The numerical simulations were performed using the commercial software, PAM-STAMP 2G. The results were compared with experimental data from a U-bending process.

• Proceedings of the KOSOMBE Conference
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• 대한의용생체공학회 1995년도 춘계학술대회
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• pp.265-269
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• 1995

In this study, we present a training method of radial basis function networks based on recursive modified Gram-Schmidt algorithm for single step prediction of chaotic time series. With single step predictions of Mackey-Glass time series and alpha-rhythm EEG which has chaotic characteristics, the radial basis function network trained by this method is compared with one trained by a classical non-recursive method and the radial basis function model proposed by X.D. He and A. Lapedes. The results show the effectiveness of the training method.

• The korean journal of orthodontics
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• 제37권1호통권120호
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• pp.16-28
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• 2007

Objective: Evaluation of individual growth is important in orthodontics. The aim of this study was to develop a convenient software that can evaluate current growth status and predict further growth. Methods: Stature data of 2 to 20 year-old Koreans (4893 boys and 4987 girls) were extracted from a nationwide data. Age-sex-specific continuous functions describing percentile growth curves were constructed using natural cubic spline function (NCSF). Then, final stature prediction algorithm was developed and its validity was tested using longitudinal series of stature measurements on randomly selected 200 samples. Various accuracy measurements and analyses of errors between observed and predicted stature using NCSF growth curves were performed. Results: NCSF growth curves were shown to be excellent models in describing reference percentile stature growth curie over age. The prediction accuracy compared favorably with previous prediction models, even more accurate. The current prediction models gave more accurate results in girls than boys. Although the prediction accuracy was high, the error pattern of the validation data showed that in most cases, there were a lot of residuals with the same sign, suggestive of autocorrelation among them. Conclusion: More sophisticated growth prediction algorithm is warranted to enhance a more appropriate goodness of model fit for individual growth.

• Journal of Preventive Medicine and Public Health
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• 제32권1호
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• pp.60-64
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• 1999

Objectives. Changes in lung function are frequently used as biological markers to assess the health effects of criteria air pollutants. We tried to formulate the prediction models of pulmonary functions based on height, weight, age and gender, especially for children aged 12 years who are commonly selected for the study of health effects of the air pollution. Methods. The target pulmonary function parameters were forced vital capacity(FVC) and forced expiratory volume in one second(FEV1). Two hundreds and fifity-eight male and 301 female 12-year old children were included in the analysis after excluding unsatisfactory tests to the criteria recommended by American Thoracic Sosiety and excluding more or less than 20% predicted value by previous prediction equations. The weight prediction equation using height as a independent variable was calculated, and then the difference of observed weight and predicted weight (i.e. residual) was used as the independent variable of pulmonary function prediction equations with height. Results. The prediction equations of FVC and FEV1 for male are FVC(ml) = $50.84{\times}height(cm)+7.06{\times}weight$ residual 4838.86, FEV1(ml) = $43.57{\times}height(cm)+3.16{\times}weight$ residual - 4156.66, respectively. The prediction equations of FVC and FEV1 for female are FVC(ml) = $42.57{\times}height(cm)+12.50{\times}weight$ residual - 3862.39, FEV1(ml) = $36.29{\times}height(cm)+7.74{\times}weight$ residual - 3200.94, respectively.