Psychometric Characteristics of Smartphone-Based Gait Analyses in Chronic Health Conditions: A Systematic Review by Tobias Bea, Helmi Chaabene, Constantin Wilhelm Freitag, Lutz Schega

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A design-based framework for optimal stratification using super-population models with application on real data set of breast cancer. by Faizan Danish

“…This study investigates the determination of stratification points for two study variables within the framework of simple random sampling, with a focus on estimating the population mean using a closely related auxiliary variable. …”
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基于modeFRONTIER的离合器碟形弹簧多目标优化设计 by 潘金坤

“…Based on the analysis of the working characters of disc springs in clutch,the mathematical model of multi-objective optimal design of disc springs is established with unified objective function method,which regards the minimization of the disc spring volume and its average variable quantity of working compress force within the scope of friction lining wear as optimal objectives.The optimization calculation is presented by using the software modeFRONTIER.The results indicate that the relevant performance of disc springs is significantly improved after optimal design,with the objective function values reduced by 36% and 6% respectively.The software modeFRONTIER,with its simplicity and efficient algorithm,solves optimization problems and improves design efficiency.…”
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A Bayesian-Weighted Inverse Gaussian Regression Model with Application to Seismological Data by Ehsan Mesdaghi, Afshin Fallah, Rahman Farnoosh, Gholam Hossein Yari

“…In the proposed model, the complementary reciprocal of the location parameter of response variable is considered to be a linear function of the explanatory variables. …”
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GDP per capita vs foreign direct investment: key drivers of a country's technological leadership by Aleksy Kwilinski

“…A true fixed-effects stochastic frontier model was applied to panel data, based on the Cobb-Doug- las production function and the translogarithmic function, to evaluate the determinants of technological development and identify technical efficiency. …”
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Transfer Robustness Optimization for Urban Rail Transit Timetables by Liqiao Ning, Peng Zhao, Wenkai Xu, Ke Qiao

“…Next, to improve the computational efficiency, we propose an approximate linearization approach for the EETC function and introduce two types of binary variables and auxiliary substitution variables to convert the nonlinear model to a mixed-integer linear model. …”
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Analysis the Impact of Covid-19 on Green Accounting and Its Implications on Profitability by Reschiwati Reschiwati, Fran Sayekti, Tasia Veronica

“…The next difference is that the Performance and Environmental Disclosure variables function as both Y variables and X variables (intervening). …”
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Pareto Optimal Solutions for Stochastic Dynamic Programming Problems via Monte Carlo Simulation by R. T. N. Cardoso, R. H. C. Takahashi, F. R. B. Cruz

“…Instead of using the expected values of the objective function, the randomness nature of the decision variables is kept along the process, while Pareto fronts weighted by all quantiles of the objective function are determined. …”
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Domain knowledge-driven decomposition-based large-scale optimization for ship cabin structures by Puyu JIANG, Jun LIU, Qiangjun LUO, Yuansheng CHENG

“…Each girder size variable is separately grouped, and the corresponding subproblem's objective function is the weight of the cabin structure. …”
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Optimal Control Problem of Converter Steelmaking Production Process Based on Operation Optimization Method by Jun Zhang

“…The optimal control indicator is determined via current state of converter smelting production process, and the set values of operation variable would control converter production. Relationship between various operating variables, current temperature, and carbon content is constructed through operation analysis of a great deal of actual production data; then, the dynamic optimal control indicator is derived from historical excellent smelting data; finally, the dynamic operation optimization model is built by taking the minimum deviation between the current data—molten steel temperature and carbon content—and optimal data which are determined by the optimal control indicator as objective function. …”
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Assessing the Effectiveness of DL-Clustering for Energy Optimization in Wireless Sensor Networks by Shailaja S. Halli, Poornima G Patil

“…Determining the fitness function allows us to estimate the player's stability over these variables. …”
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行星变速器的模糊可靠性多目标优化设计 by 鲁成瑞, 张进生, 王志

“…An objective function for increasing the transmission efficiency and reliability of the planetary system and trying our best to reduce the weight is set up,through the linear weighted function method,the mathematical model of objective function is established.The weighting factors is determined by using the method of design variables normalization.Based on the fuzzy mathematics theory of reliability constraints and geometric constraint,the optimal design is carried out by using optimization toolbox in Matlab.To ensure the optimal parameter to meet the global optimal solution of objective function,stack calculation of the three local optimal solution are carried out.Through an example show that,by using multi-objective optimization method of fuzzy reliability design,the transfer efficiency and stability of the system are improved,the quality of the planet gear train is also reduced.…”
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Estimation of micro-extraction process hippuric acid for toluene exposure monitoring in urine samples by Behnaz Sarani, Mashaallah Rahmani, Ahmad Reza Abbasian

“…The independent variables for the micro-extraction process of hippuric acid were examined, while the response from the HA monitoring acted as the dependent variable. …”
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Kernel Density Estimation for Joint Scrambling in Sensitive Surveys by Alvan Caleb Arulandu, Sat Gupta

“…Randomized response models aim to protect respondent privacy when sampling sensitive variables but consequently compromise estimator efficiency. …”
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Optimization Design of the Transmission System of Small-size Shrub Brush Cutter based on MATLAB by Yang Chunmei, Guo Minghui, Ma Yan, Liu Qianjun, Yang Tie

“…By determining the objective function of the transmission system,selecting the independent design variables,determining the constraints,the mathematical model of transmission system is established.The analysis and optimization of the design variables,objective function and the boundary conditions are carried out,the complex method optimization program of MATLAB is written,and by using its powerful ability of optimization design to optimize the transmission system of the brush cutter. …”
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Investigation, Optimization of Energy Consumption and Yield Modeling of Two Paddy Cultivars with Genetic-Artificial Bee Colony Algorithm by S. Sharifi, N. Hafezi, M. H. Aghkhani

“…In the first step, energy consumption and production were calculated by multiplying the variables by their corresponding coefficients. In the second step, all the variables that maximize paddy yield were entered into MATLAB software. …”
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Analysis Method of Agricultural Total Factor Productivity Based on Stochastic Block Model (SBM) and Machine Learning by Yanzi Li, Cai Chen, Fuqiang Liu, Jian Wang

“…It uses the SBM direction distance function and the Luenberger productivity index to measure the agricultural efficiency, total factor productivity, and their components. …”
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Economics production buffalo breeding farms in the province of Nineveh (Badush area a case stady) by Salim AL- Nuaimy, Zwaid, F. Abd, Mahasen, M, Sultan

“…Results of the estimation showed that the double logarithmic formula is the best formula for the representation of production function and that the function and all the explanatory variables are statistically significant except for green feed and veterinary services.The most significant effect of the employment variable was on the production process، with  elasticity of 0.277 and  positive indication، and the results of the cost function estimate the best formulas to represent the relationship. …”
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Evaluation of Multiparameter Likelihoods through Iteration of Two-dimensional Slices by Joel S. Jayson

“…Markov Chain Monte Carlo (MCMC) computation has been the dominant instrument for evaluating multiparameter functions. For applications with a quasi-linear variable such as, A _s , the 2D iterative method is orders of magnitude more efficient than MCMC.…”
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Multi-objective design optimization of a transonic axial fan stage using sparse active subspaces by Richard Amankwa Adjei, Chengwei Fan

“…Active subspace was used to compute the active variables via singular value decomposition and a hybrid polynomial correlated function expansion was used to construct a surrogate model on the active subspace. …”
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