• 제목/요약/키워드: GROWTH PREDICTION MODEL

검색결과 446건 처리시간 0.022초

A FRACTIONAL-ORDER TUMOR GROWTH INHIBITION MODEL IN PKPD

  • Byun, Jong Hyuk;Jung, Il Hyo
    • East Asian mathematical journal
    • /
    • 제36권1호
    • /
    • pp.81-90
    • /
    • 2020
  • Many compartment models assume a kinetically homogeneous amount of materials that have well-stirred compartments. However, based on observations from such processes, they have been heuristically fitted by exponential or gamma distributions even though biological media are inhomogeneous in real environments. Fractional differential equations using a specific kernel in Pharmacokinetic/Pharmacodynamic (PKPD) model are recently introduced to account for abnormal drug disposition. We discuss a tumor growth inhibition (TGI) model using fractional-order derivative from it. This represents a tumor growth delay by cytotoxic agents and additionally show variations in the equilibrium points by the change of fractional order. The result indicates that the equilibrium depends on the tumor size as well as a change of the fractional order. We find that the smaller the fractional order, the smaller the equilibrium value. However, a difference of them is the number of concavities and this indicates that TGI over time profile for fitting or prediction should be determined properly either fractional order or tumor sizes according to the number of concavities shown in experimental data.

저온 평판에서의 서리층 성장 예측 (Prediction of Frost Layer Growth on a Cold Plate)

  • 지성;이관수;여문수
    • 대한기계학회논문집B
    • /
    • 제26권9호
    • /
    • pp.1325-1331
    • /
    • 2002
  • This study presents a numerical model to predict the behavior of frost layer growth. The characteristics of the heat and mass transfer inside the frost layer are analyzed by coupling the air flow with the frost layer. The present model is validated by comparing with the several other analytical models. It has been known that most of the previous models cause considerable errors depending on the working conditions or correlations used in predicting the frost thickness growth, whereas the model in this work estimates the thickness of the frost layer more accurately within an error of 10% in comparison with the experimental data. Simulation results are presented for variations of heat and mass transfer during the frost formation and for the behavior of frost layer growth along the direction of air flow.

균열 형상비 변화에 따른 단일표면파로균열의 성장특성과 수명예측 (Growth Characteristics and Life Prediction of Single Surface Fatigue Crack with the Variation of crack Configuration Ratios)

  • 서창민;서덕영;정정수
    • 한국해양공학회지
    • /
    • 제7권2호
    • /
    • pp.173-181
    • /
    • 1993
  • This work has been investigated the ralationship between single surface crack length and crack depth have influence on the fatigue life. The simulation based on experimental results of 2.25 Cr-1Mo steel at various crack configuration ratios has enabled successful prediction of fatigue life at room temperature. The effect of crack depth should be considered for predicting fatigue crack growth rates as well as that of surface crack length. It is also shwn that the crack growth mechanisms are in good agreement with expreimental data according to the interaction of crack length and crack depth.

  • PDF

Developing a Quality Prediction Model for Wireless Video Streaming Using Machine Learning Techniques

  • Alkhowaiter, Emtnan;Alsukayti, Ibrahim;Alreshoodi, Mohammed
    • International Journal of Computer Science & Network Security
    • /
    • 제21권3호
    • /
    • pp.229-234
    • /
    • 2021
  • The explosive growth of video-based services is considered as the dominant contributor to Internet traffic. Hence it is very important for video service providers to meet the quality expectations of end-users. In the past, the Quality of Service (QoS) was the key performance of networks but it considers only the network performances (e.g., bandwidth, delay, packet loss rate) which fail to give an indication of the satisfaction of users. Therefore, Quality of Experience (QoE) may allow content servers to be smarter and more efficient. This work is motivated by the inherent relationship between the QoE and the QoS. We present a no-reference (NR) prediction model based on Deep Neural Network (DNN) to predict video QoE. The DNN-based model shows a high correlation between the objective QoE measurement and QoE prediction. The performance of the proposed model was also evaluated and compared with other types of neural network architectures, and three known machine learning methodologies, the performance comparison shows that the proposed model appears as a promising way to solve the problems.

미래 도시성장 시나리오에 따른 수도권 기후변화 예측 변동성 분석 (Analysis of Climate Variability under Various Scenarios for Future Urban Growth in Seoul Metropolitan Area (SMA), Korea)

  • 김현수;정주희;김유근
    • 한국대기환경학회지
    • /
    • 제28권3호
    • /
    • pp.261-272
    • /
    • 2012
  • In this study, climate variability was predicted by the Weather Research and Forecasting (WRF) model under two different scenarios (current trends scenario; SC1 and managed scenario; SC2) for future urban growth over the Seoul metropolitan area (SMA). We used the urban growth model, SLEUTH (Slope, Land-use, Excluded, Urban, Transportation, Hill-Shade) to predict the future urban growth in SMA. As a result, the difference of urban ratio between two scenarios was the maximum up to 2.2% during 50 years (2000~2050). Also, the results of SLEUTH like this were adjusted in the Weather Research and Forecasting (WRF) model to analysis the difference of the future climate for the future urbanization effect. By scenarios of urban growth, we knew that the significant differences of surface temperature with a maximum of about 4 K and PBL height with a maximum of about 200 m appeared locally in newly urbanized area. However, wind speeds are not sensitive for the future urban growth in SMA. These results show that we need to consider the future land-use changes or future urban extension in the study for the prediction of future climate changes.

Issues When Estimating Fatigue Life of Structures

  • Lee, Ouk-Sub;Chen, Zhi-wei
    • International Journal of Precision Engineering and Manufacturing
    • /
    • 제1권2호
    • /
    • pp.43-47
    • /
    • 2000
  • When estimating fatigue crack growth (FCG) life of structures, the use of crack growth models and knowledge of the values of their corresponding parameters are of vital importance. Inconsistency in using models with appropriate parameters can lead to enormous errors in FCG life prediction. In this paper examples are analyzed and compared with test results to show the possible problems, Consistency checks are necessary for avoiding some pitfalls, and also necessary for verifying the correct performance and accuracy of the used computer program.

  • PDF

한국 청소년(만 17세) 체격의 시대적 변천에 대한 통계적 모형 추정 -1983년부터 1993년까지- (Statistical Estimated Model of Chronological Change in Physical Growth and Development in Korean Youth(17 Years Old) - From 1983 To 1993 -)

  • 성웅현;윤석옥;윤태영;최중명;박순영
    • 보건교육건강증진학회지
    • /
    • 제12권2호
    • /
    • pp.36-47
    • /
    • 1995
  • This research was obtained from analyzing how the physiques of the 3rd grade students of high school for males and females and developed for the last eleven years(from 1983 to 1993). By the physiques and nutritional index of physical growth and development, Relative Body Weight of 36.62 exceeded the standard, on the other hand females showed lower records than the standard. Relative Chest Girth Index belonged to the normal type of males and females in all, in the comparison of the records between 1983 and 1993, males increased in average 0.29 and females in average 0.55. Relative Chest Girth Index of females was greater than that of females. By the results of Relative Sitting Height Index, growth of the lower body for males and females was greater than that of males. In case of Vervaeck Index, males increased in average 2.04 but females increased in average 1, 20 relatively less than males. These phenomena provided for the evidence of the deficient nutrition in females. In the regression models of body height and body weight within a certain period, statistical regression model types which best indicated chronological average changes of body height and body weight, took 3rd Order Polynomial Regression Model rather than linear regression model. In females, statistical regression model types which best is suitable for chronological average change of body height and body weight, took 4th and 2nd Order Polynomial Regression Model respectively. The prediction value of 1995 by estimated polynomial regression model anticipated that body height of 3rd grade year students of high school of males in 1993 went on increasing from 170.87cm to 171.79cm in average 0.92cm growth and that of females from 158.99cm to 160.79cm in average 1.80cm growth. In addition, body weight of males seemed to increase from 62.58kg to 64.52kg in average 1.94kg growth and that of females seemed to increase from 54.05kg to 54.19kg in average 0.14kg growth. Linear Regression Model was suitable for the regression model of body weight for body height. Prediction on increase of an average body weight for body height was that, according to growth of body height 1cm in males, body weight increased 1.41kg averagely and that of females 0.86kg. For that reason, we came to conclusion that body weight increase for body height 1cm in males was greater than that in females on average.

  • PDF

Application of Bootstrap Method to Primary Model of Microbial Food Quality Change

  • Lee, Dong-Sun;Park, Jin-Pyo
    • Food Science and Biotechnology
    • /
    • 제17권6호
    • /
    • pp.1352-1356
    • /
    • 2008
  • Bootstrap method, a computer-intensive statistical technique to estimate the distribution of a statistic was applied to deal with uncertainty and variability of the experimental data in stochastic prediction modeling of microbial growth on a chill-stored food. Three different bootstrapping methods for the curve-fitting to the microbial count data were compared in determining the parameters of Baranyi and Roberts growth model: nonlinear regression to static version function with resampling residuals onto all the experimental microbial count data; static version regression onto mean counts at sampling times; dynamic version fitting of differential equations onto the bootstrapped mean counts. All the methods outputted almost same mean values of the parameters with difference in their distribution. Parameter search according to the dynamic form of differential equations resulted in the largest distribution of the model parameters but produced the confidence interval of the predicted microbial count close to those of nonlinear regression of static equation.

Effect of Heterogeneous Variance by Sex and Genotypes by Sex Interaction on EBVs of Postweaning Daily Gain of Angus Calves

  • Oikawa, T.;Hammond, K.;Tier, B.
    • Asian-Australasian Journal of Animal Sciences
    • /
    • 제12권6호
    • /
    • pp.850-853
    • /
    • 1999
  • Angus postweaning daily gain (PWDG) was analyzed to investigate effects of the heterogeneous variance and the genotypes by sex interaction on prediction of EBVs with data sets of various environmental levels. A whole data (16,239 records) was divided into six data sets according to averages of the best linear unbiased estimator (BLUE) of herd environment. The results comparing prediction models showed that single-trait model is adequate for most of the data sets except for the data set of poor environment for both of the bulls and the heifers where the heterogeneity of variance and the genotypes by sex interaction exists. In the prediction with the data set of the low environment level, the bull's EBVs by single-trait models had high product moment correlations with male EBVs of the bulls by the multitrait model. Whereas the heifer's EBVs had moderate correlations with female EBVs by the multitrait model. This moderate correlation seems to be resulted by the heterogeneity of variance and low heritability of the heifer's PWDG. The prediction models with heterogeneity of variance had little effect on the prediction of EBVs for the data sets with moderate to high genetic correlations.

지도학습 기반 수출물량 및 수출금액 예측 모델 개발 (Development of Export Volume and Export Amount Prediction Models Based on Supervised Learning)

  • 나동길;유영웅
    • 산업경영시스템학회지
    • /
    • 제46권2호
    • /
    • pp.152-159
    • /
    • 2023
  • Due to COVID-19, changes in consumption trends are taking place in the distribution sector, such as an increase in non-face-to-face consumption and a rapid growth in the online shopping market. However, it is difficult for small and medium-sized export sellers to obtain forecast information on the export market by country, compared to large distributors who can easily build a global sales network. This study is about the prediction of export amount and export volume by country and item for market information analysis of small and medium export sellers. A prediction model was developed using Lasso, XGBoost, and MLP models based on supervised learning and deep learning, and export trends for clothing, cosmetics, and household electronic devices were predicted for Korea's major export countries, the United States, China, and Vietnam. As a result of the prediction, the performance of MAE and RMSE for the Lasso model was excellent, and based on the development results, a market analysis system for small and medium sellers was developed.