• Title/Summary/Keyword: mean absolute deviation

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Common Due-Data Determination and Sequencing on Parallel Processors (병렬 기계에 있어서 공통 납기 결정과 일정 계획)

  • 오명진;이상도
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.14 no.23
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    • pp.27-36
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    • 1991
  • This paper considers scheduling a set of n-jobs on m-paraller identical processors in which all jobs have the common due date. The objective of the problem is to minimize the weighted mean absolute deviation of job completion times about such common due dates under the assumption that each job has a different weight. and to determine the optimal value of a common due date. We propose four heuristic solution methods based on several dominance conditions, and its solution procedure is illustrated with numerical examples. The Performance comparison is made among four heuristic scheduling procedures.

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The Optimal Mean-Variance Portfolio Formulation by Mathematical Planning (Mean-Variance 수리 계획을 이용한 최적 포트폴리오 투자안 도출)

  • Kim, Tai-Young
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.32 no.4
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    • pp.63-71
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    • 2009
  • The traditional portfolio optimization problem is to find an investment plan for securities with reasonable trade-off between the rate of return and the risk. The seminal work in this field is the mean-variance model by Markowitz, which is a quadratic programming problem. Since it is now computationally practical to solve the model, a number of alternative models to overcome this complexity have been proposed. In this paper, among the alternatives, we focus on the Mean Absolute Deviation (MAD) model. More specifically, we developed an algorithm to obtain an optimal portfolio from the MAD model. We showed mathematically that the algorithm can solve the problem to optimality. We tested it using the real data from the Korean Stock Market. The results coincide with our expectation that the method can solve a variety of problems in a reasonable computational time.

A New Training System for Improving Postural Balance Using a Tilting Bed

  • Yu, Chang-Ho;Kwon, Tae-Kyu;Ryu, Mun-Ho;Kim, Nam-Gyun
    • Journal of Biomedical Engineering Research
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    • v.28 no.1
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    • pp.117-126
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    • 2007
  • In this paper, we propose an early rehabilitation training system for the improvement of postural balance with multi-modality on a tilting bed. The integration of the visual, somatosensory and vestibular functions is significant to for maintaining the postural control of the human body. However, conventional rehabilitation systems do not provide multi-modality to trainees. We analyzed the characterization of postural control at different tilt angles of an early rehabilitation training system, which consists of a tilting bed, a visual feedback, a computer interface, a computer, and a force plate. The software that we developed for the system consists of the training programs and the analysis programs. To evaluate the characterization of postural control, we conducted the first evaluation before the beginning of the training. In the following four weeks, 12 healthy young and 5 healthy elderly subjects were trained to improve postural control using the training programs with the tilting bed. After four weeks of training, we conducted the second evaluation. The analysis programs assess (center of pressure) COP moving time, COP maintaining time, and mean absolute deviation of the trace before and after training at different tilt angles on the bed. After 4 weeks, the COP moving time was reduced, the COP maintaining time was lengthened, and the mean absolute deviation of the trace was lowered through the repeated use of vertical, horizontal, dynamic circle movement training programs. These results show that this system improves postural balance and could be applied to clinical use as an effective training system.

Isobaric Vapor-Liquid Equilibrium of 1-propanol and Benzene System at Subatmospheric Pressures (일정압력하에서 1-propanol/benzene 계의 기-액 상평형)

  • Rho, Seon-Gyun;Kang, Choon-Hyoung
    • Korean Chemical Engineering Research
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    • v.56 no.2
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    • pp.222-228
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    • 2018
  • Benzene is one of the most widely used basic materials in the petrochemical industry. Generally, benzene exists as a mixture with alcohols rather than as a pure substance. Further, the alcohols-added mixtures usually exhibit an azeotropic composition. In this context, knowledge of the phase equilibrium behavior of the mixture is essential for its separation and purification. In this study, the vapor-liquid equilibrium data were measured in favor of a recirculating VLE apparatus under constant pressure for the 1 - propanol / benzene system. The measured vapor - liquid equilibrium data were also correlated by using the UNIQUAC and WILSON models and the thermodynamic consistency test based on the Gibbs/Duhem equation was followed. The results of the phase equilibrium experiment revealed RMSEs (Root Mean Square Error) and AADs (Average Absolute Deviation) of less than 0.05 for both models, indicating a good agreement between the experimental value and the calculated value. The results of the thermodynamic consistency test also confirmed through the residual term within ${\pm}0.2$.

Evaluation of dynamic muscle fatigue model to predict maximum endurance time during forearm isometric contraction (전완의 등척성 수축시 최대근지구력시간을 예측하기 위한 동적근피로모델의 평가)

  • Kiyoung, Lee
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.15 no.6
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    • pp.433-439
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    • 2022
  • Muscle fatigue models to predict maximum endurance time (MET) are broadly classified as either 'empirical' or 'theoretical'. Empirical models are based on fitting experimental data and theoretical models on mathematical representations of physiological process. This paper examines the effectiveness of dynamic muscle fatigue model as theoretical model to predict maximum endurance time during forearm isometric contraction. Forty volunteers (20 females, 20 males) are participated in this study. Empirical models (exponential model and power model) and theoretical model (dynamic muscle fatigue model) are used to compare. Mean absolute deviation (MAD), correlation coefficient (r) and intraclass correlation (ICC) are calculated between theoretical model and empirical models. MAD are below 3.5%p, r and ICC are above 0.93 and 0.87, respectively. This results demonstrate that dynamic muscle fatigue model as theoretical model is valid to predict MET.

Performance Comparison of Four-Parameter Correlation Equations of the Enthalpy of Vaporization

  • Lee, Kyoung-Youl;Park, Kyoung-Kuhn
    • International Journal of Air-Conditioning and Refrigeration
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    • v.14 no.3
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    • pp.118-123
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    • 2006
  • A few commonly used correlation equations of the enthalpy of vaporization essential to the analysis of refrigeration cycles are reviewed. A new four-parameter correlation equation is proposed assuming that the enthalpy of vaporization could be represented with a linear form of the temperature and an additional function which slowly decreases as the temperature increases. It is not a common practice to measure the enthalpy of vaporization by experiment; therefore, performance of the new correlation is examined using numeric data from the ASHRAE tables for 22 pure substance refrigerants. The new correlation equation and other existing ones are fitted to the data optimizing the root mean squared deviation. All data points are weighted equally and NBP (normal boiling point) is used as a fixed point since the NBP is important for refrigeration application. The new four-parameter equation yields an average absolute deviation of 0.05% for 22 refrigerants which is smaller than those of other four-parameter equations, such as Guermouche-Vergnaud (0.08%), Aerebrot (0.13%), Radoz-Lyderson (0.08%), and Somayajulu four-parameter equation (0.08%).

Covid19 trends predictions using time series data (시계열 데이터를 활용한 코로나19 동향 예측)

  • Kim, Jae-Ho;Kim, Jang-Young
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.25 no.7
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    • pp.884-889
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    • 2021
  • The number of people infected with Covid-19 in Korea seemed to be gradually decreasing thanks to various efforts such as social distancing and vaccines. However, just as the number of infected people increased after a particular incident on February 20, 2020, the number of infected people has been increasing rapidly since December 2020 by approximately 500 per day. Therefore, the future Covid-19 is predicted through the Prophet algorithm using Kaggle's dataset, and the explanatory power for this prediction is added through the coefficient of determination, mean absolute error, mean percent error, mean square difference, and mean square deviation through Scikit-learn. Moreover, in the absence of a specific incident rapidly increasing the cases of Covid-19, the proposed method predicts the number of infected people in Korea and emphasizes the importance of implementing epidemic prevention and quarantine rules for future diseases.

Comparison of three midsagittal planes for three-dimensional cone beam computed tomography head reorientation

  • Lee, Eon-Hwa;Yu, Hyung-Seog;Lee, Kee-Joon;Han, Sang-Sun;Jung, Hwi-Dong;Hwang, Chung-Ju
    • The korean journal of orthodontics
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    • v.50 no.1
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    • pp.3-12
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    • 2020
  • Objective: This study compared three prominent midsagittal planes (MSPs) to identify the MSP that best approximates the true symmetrical MSP. Methods: Forty-three patients (mean age, 23.0 ± 8.20 years) were grouped as follows: group 1 consisted of 10 patients with skeletal Class I and a menton (Me) deviation of < 2 mm; group 2, 11 patients with skeletal Class III and a Me deviation < 2 mm; group 3, nine patients with skeletal Class III and a Me deviation of 2 to less than 4 mm; and group 4, 13 patients with skeletal Class III and an Me deviation ≥ 4 mm. The candidate MSPs were established by three-dimensional (3D) cone beam computed tomography (CBCT) reorientation methods (RMs): (1) the MSP perpendicular to the Frankfort horizontal (FH) plane while passing through the crista galli and basion; (2) the MSP including the nasion, incisive foramen, and basion; (3) the MSP including the nasion, anterior nasal spine, and posterior nasal spine. The mean absolute distances (MADs) to the MSPs were calculated from the coordinates of 1,548 points on 129 CBCT images. The differences in the values of the 3D coordinates among RMs were compared. Results: The MADs of the three RMs showed significant differences (p < 0.05). Most of the differences in values of the coordinates were not significant among RMs. Conclusions: Although the differences in distance among the three MSPs were minor, the MSP perpendicular to the FH plane while passing through the crista galli and basion best approximated the true symmetrical MSP.

Penalized variable selection in mean-variance accelerated failure time models (평균-분산 가속화 실패시간 모형에서 벌점화 변수선택)

  • Kwon, Ji Hoon;Ha, Il Do
    • The Korean Journal of Applied Statistics
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    • v.34 no.3
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    • pp.411-425
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    • 2021
  • Accelerated failure time (AFT) model represents a linear relationship between the log-survival time and covariates. We are interested in the inference of covariate's effect affecting the variation of survival times in the AFT model. Thus, we need to model the variance as well as the mean of survival times. We call the resulting model mean and variance AFT (MV-AFT) model. In this paper, we propose a variable selection procedure of regression parameters of mean and variance in MV-AFT model using penalized likelihood function. For the variable selection, we study four penalty functions, i.e. least absolute shrinkage and selection operator (LASSO), adaptive lasso (ALASSO), smoothly clipped absolute deviation (SCAD) and hierarchical likelihood (HL). With this procedure we can select important covariates and estimate the regression parameters at the same time. The performance of the proposed method is evaluated using simulation studies. The proposed method is illustrated with a clinical example dataset.

Automatic Calibration of SWAT Model Using LH-OAT Sensitivity Analysis and SCE-UA Optimization Method (LH-OAT 민감도 분석과 SCE-UA 최적화 방법을 이용한 SWAT 모형의 자동보정)

  • Lee Do-Hun
    • Journal of Korea Water Resources Association
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    • v.39 no.8 s.169
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    • pp.677-690
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    • 2006
  • The LH-OAT (Latin Hypercube One factor At a Time) method for sensitivity analysis and SCE-UA (Shuffled Complex Evolution at University of Arizona) optimization method were applied for the automatic calibration of SWAT model in Bocheong-cheon watershed. The LH-OAT method which combines the advantages of global and local sensitivity analysis effectively identified the sensitivity ranking for the parameters of SWAT model over feasible parameter space. Use of this information allows us to select the calibrated parameters for the automatic calibration process. The performance of the automatic calibration of SWAT model using SCE-UA method depends on the length of calibration period, the number of calibrated parameters, and the selection of statistical error criteria. The performance of SWAT model in terms of RMSE (Root Mean Square Error), NSEF (Nash-Sutcliffe Model Efficiency), RMAE (Relative Mean Absolute Error), and NMSE (Normalized Mean Square Error) becomes better as the calibration period and the number of parameters defined in the automatic calibration process increase. However, NAE (Normalized Average Error) and SDR (Standard Deviation Ratio) were not improved although the calibration period and the number of calibrated parameters are increased. The result suggests that there are complex interactions among the calibration data, the calibrated parameters, and the model error criteria and a need for further study to understand these complex interactions at various representative watersheds.