Classification of petroleum origin and integrity by FTIR by FJ. Guzmán-Osorio, VI. Domínguez-Rodríguez, RH. Adams, CE. Lobato-García, A. Guerrero-Peña, JR. Barajas-Hernández

“…The canonic functions derived from the discriminate analysis had correlation coefficients of 0.994, 0.900, and 0.867, among the variables studied and the classification factor. …”
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Parameter Calculation and Rotor Structure Optimization Design of Solid Rotor Induction Motors by Hao Xu, Jinghong Zhao, Sinian Yan

“…On this basis, with efficiency, power factor, starting torque and starting current as the optimization objectives, and the number of slots, slot depth, slot width, squirrel cage material and end ring thickness as the optimization variables, the optimization schemes of slotted rotor and squirrel cage rotor are obtained by using the three-dimensional finite element method. …”
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Sustitución parcial de alimento balanceado comercial por saccharina rústica en pollo de engorde by Dixon Fabián Flórez-Delgado, Jesús Esteban Fonseca-García, Dubel Reinaldo Cely-Leal

“…Polynomial regression and the derivative of a quadratic function were used to determine the optimal saccharina level. …”
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Enlightening the Critical Factors affecting the Solvency of Indian Construction Industry: An Empirical Analysis using Multivariate Discriminant Analysis and Logistic Regression by RAKESH SHARMA, Neba Bhalla

“…So one discriminant function is created and found significant at 5% levels for two different solvency parameters. …”
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Experimental Study and Damage Model Study of Rock Salt Subjected to Cyclic Loading and Cyclic Creep by Baoyun Zhao, Tianzhu Huang, Liu Dongyan, Dongsheng Liu, Yang Liu, Xiaoping Wang

“…The damage model is obtained by inverse functioning the s function, and then the correction coefficient is added to the model to obtain the modified damage model. …”
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Experimental Studies of Heat and Moisture Exchange in the Process of Convective Drying of Thin Wet Materials by A. I. Ol’shanskii, S. V. Zhernosek, A. M. Gusarov

“…New ways of experimental data processing by generalized complex variables that are characteristic of the drying process are presented. …”
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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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Encapsulation Based Method for Natural Frequency Identification of Deployable Solar Arrays with Multiple Plates by Chunjuan Zhao, Xiangyu Zhao, Shanbo Chen, Jisong Yu, Lei Zhang

“…However, for the batch production of small satellites, the accuracy and efficiency of traditional ground modal testing methods are limited. …”
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A Data-Driven Approach Based on Deep Neural Network Regression for Predicting the Compressive Strength of Steel Fiber Reinforced Concrete by Nhat-Duc Hoang, Van-Duc Tran

“…Experimental results show that the L1 regularization helps achieve the most desired performance, with a coefficient of determination (R2) of roughly 0.96. Notably, an asymmetric loss function is used along with Nadam to decrease the percentage of overestimated cases from 50.83% to 27.08%. …”
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Optimally controlled heating of solid particles in a fluidised bed with a dispersive flow of the solid by Poświata Artur, Szwast Zbigniew

“…The mixing rate was described by the axial dispersion coefficient. As any economic values of variables describing analysing process are subject to local and time fluctuations, the accepted objective function describes the total cost of the process expressed in exergy units. …”
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Color image hybrid noise filtering algorithm based on deep convolution neural network by Yongfei Yu, Yuanjian Yan

“…Then, the probability density function and noise probability density function of Gaussian noise are calculated to determine the hybrid noise feature points of color image. …”
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Ridge regression and its applications in genetic studies. by M Arashi, M Roozbeh, N A Hamzah, M Gasparini

“…On the other hand, the efficiency of the rank ridge regression estimator is highly dependent on the ridge parameter. …”
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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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System Modeling to Optimize the Production Quantity of Men's and Women's Jackets and Achieve Maximum Profit: A Case Study at Konveksi ABC Cikarang Using Linear Programming by Wisnu Aji

“…The objective function is designed to maximize profit, and the model is solved using IBM ILOG CPLEX software. …”
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Estimation of Stochastic Frontier Models with Fixed Effects through Monte Carlo Maximum Likelihood by Grigorios Emvalomatis, Spiro E. Stefanou, Alfons Oude Lansink

“…This paper proposes a procedure for choosing appropriate densities for integrating the incidental parameters from the likelihood function in a general context. The densities are based on priors that are updated using information from the data and are robust to possible correlation of the group-specific constant terms with the explanatory variables. …”
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IRAQ'S AGRICULTURAL ECONOMY AND THE REALITY OF THE VARIABLRS AND THE RESULTS OBJECTIVE CURRICULUM AND QUANTITATIVE ANALYSIS FOR THE PERIOD (1990-2011) by Salim Al-Nuaimy, Mahasen. M Al-Jeboury

“…The research aims to formulate sober policies and practical actions contribute to adjust the course of the agricultural sector and to achieve its goals, which will make it easier to raise production and productivity, Variables of agricultural sector were agricultural work, capital accumulation agricultural, technical mechanism, technical chemical, agricultural loans, agricultural export, import of agricultural, national income, domestic consumption, the cultivatedareas, that have been expressed as (policies of productivity and investment, marketing and price) where its impact was deare on the growth of the agricultural sector and overall productivity during (1990-2010) and the development process and increase production and productivity in the agricultural sector associated with economic, social and institutional multiple and overlapping factors that effects the forms and varying proportions in its impact on agricultural output, which had been measured under function producing an aggregate of variables agricultural policy and its contribution to productivity growth as well as measuring productivity elements total (TFP) by using index (Malmaquist) depending on the (DEAP). …”
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Quality control of DEMs using check surfaces by Francisco Javier Ariza-López, José Rodríguez-Avi

“…Using the Kolmogorov–Smirnov statistic, the observed distribution functions of the results for different sample sizes (20, 50, 100) and different patch sizes (3 × 3, 5 × 5, 9 × 9, 11 × 11, 15 × 15, 19 × 19) and for a sample of points are compared against the true population distribution function. …”
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Neuroscience-informed nomogram model for early prediction of cognitive impairment in Parkinson's disease by Sudharshan Putha, Swaroop Reddy Gayam, Bhavani Prasad Kasaraneni, Krishna Kanth Kondapaka, Sateesh Kumar Nallamala, Praveen Thuniki

“…The least absolute shrinkage and selection operator (LASSO) algorithm was applied to identify highly correlated clinical variables influencing cognitive function. Subsequently, these variables were integrated into a visualized nomogram model to facilitate early prediction of cognitive impairment (CI) risk. …”
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Importance Analysis of Vegetation Change Factors in East Africa Based on Machine Learning by Zhang Xiumei, Ma Bo, Zhang Yijie

“…The independent treatment variables were two climatic factors and five human activity factors affecting vegetation changes in East Africa. …”
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Magnetic Field Effects on Convective Heat Transfer of Ferrofluid from a Heated Sphere in Porous Media by Ayesha Aktar, Sharaban Thohura, Md. Mamun Molla

“…For increasing Ha, the figure of streamlines seems to depict functions with more gradual changes, and for isotherms, it represents functions with sharper, exponential-like increases. …”
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