IDENTIFICATION OF NOMINAL DYNAMIC CHARACTERISTICS OF AIRCRAFT GAS TEMPERATURE SENSORS by A. F. Sabitov, I. A. Safina

“…The heat transfer coefficient is calculated based on the expected operating conditions of the gas temperature sensors.The result of the study was that the parameters of the hyperbolic function of the nominal variables of the time constants for the dynamic model of the second order gas temperature sensors were found. …”
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Regression analysis and artificial neural networks for predicting pine species volume in community forests by Wenceslao Santiago-García

“…The regression approach employed seemingly unrelated nonlinear regression (NSUR) to fit simultaneous additive volume systems using both one- and two-variable models. In this approach, volume was modeled as a function of diameter at breast height (d) alone and as a function of both d and total tree height (h). …”
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An analytical optimal calibration framework of bonded particle model for rock strength envelop modelling by Xiaoxiong Zhou, Hongyi Xu, Qiuming Gong, Yanan Ma, Weiqiang Xie

“…Bond tensile strength, cohesion and local internal friction angle were identified as independent variables for calibration. …”
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The role of housing price mediation in transferring the effect of heterogeneous behavior of investors in the housing sector on Iran's economic growth by Aliakbar Gholizadeh, Shahla Samadipour

“…The housing price is also a variable of economic growth function transfer with a threshold equal to 0.0266 percent The estimated coefficients of the first and second regimes indicate the asymmetric behavior of investors on housing prices. …”
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Assessment of soil classification based on cone penetration test data for Kaifeng area using optimized support vector machine by Hanliang Bian, Zhongxun Sun, Jiahan Bian, Zhaowei Qu, Jianwei Zhang, Xiangchun Xu

“…In this study, Support Vector Machine (SVM) models were trained for soil classification using 649 Cone Penetration Test (CPT) datasets, specifically utilizing cone tip resistance ( $$q_c$$ ) and sleeve friction ( $$f_s$$ ) as input variables. Pearson correlation and sensitivity analysis confirmed that these variables are highly correlated with the classification results. …”
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THE TEMPERATURE DEPENDENCE OF UNSTEADY HEAT CONDUCTION IN SOLIDS by L. M. Ozherelkova, E. S. Savin

“…Both in the case of high and low temperatures, the temperature dependences of the heat capacity and the thermal conductivity coefficient are power-law, which allows us to bring the original heat conduction equation to a form that allows the use of the classical method of variable separation in solving the corresponding boundary value problems for the heat conduction equation. …”
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Probabilistic Analysis of Weathered Soil Slope in South Korea by Taeho Bong, Younghwan Son

“…The results showed that a probabilistic framework can be used to efficiently consider the spatial variability of soil properties, and various slope failure patterns were identified according to the spatial variability of the soil properties and the probabilistic rainfall intensity.…”
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An improved robust variance inflation factor: Reducing the negative effects of good leverage points by Osman Ufuk Ekiz

“…It is defined as the function of the coefficient of determination between the explanatory variables, and it is based on the maximum likelihood estimator of the regression coefficients. …”
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Torsional Vibration Suppression During Mode Transition Process in a Parallel Hybrid Electric Vehicle Based on Multiple Model Predictive Control by Cheng Huang, Changqing Du, Longjian Li, Xiangyu Gongye, Yifan Zhao

“…At the same time, the influence of the cost function, the weight coefficient, and the predictive time domain on the torsional vibration suppression effect during the mode transition process are explored in the mMPC strategy design, and the solution time is controlled within 10ms, which meet the real-time requirements. …”
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Evaluation of Face Stability for Mega Tunnel Under Varying Ground Strength Parameters by Deshpande Shilpa, Hedaoo Namdeo

“…This study investigates the impact of various geological strength variables, such as Young’s modulus and coefficient of lateral earth pressure, on Mega Tunnel face stability. …”
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A Lie Symmetry Classification of a Nonlinear Fin Equation in Cylindrical Coordinates by Saeed M. Ali, Ashfaque H. Bokhari, F. D. Zaman

“…The nonlinear fin equation in cylindrical coordinates is considered. Assuming a radial variable heat transfer coefficient and temperature dependent thermal conductivity, a complete classification of these two functions is obtained via Lie symmetry analysis. …”
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True amplitude migration in constant gradient velocity media by Castillo López Luis Antonio

“…<p class="MsoNormal" style="line-height: normal; margin: 0cm 0cm 0pt; mso-layout-grid-align: none;"><span style="font-family: ";Arial";,";sans-serif";; font-size: 12pt; mso-ansi-language: EN-US;" lang="EN-US">The kirchhoff conventional algorithm using ray tracing is based on a constant velocity function. This solution, where is incorporated ray path information into conventional algorithm, can be extended to a variable velocity medium. …”
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Developing data driven framework to model earthquake induced liquefaction potential of granular terrain by machine learning classification models by Kennedy C. Onyelowe, Viroon Kamchoom, Tammineni Gnananandarao, Krishna P. Arunachalam

“…The high precision and Phi Correlation Coefficient further affirm the reliability and accuracy of the model’s predictions. …”
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Optimization Design of CO2 Air Cooler by Liu Bin, Su Yun, Dong Xiaoyong, Wang Congfei, Cai Jinghui

“…Volume and the heat transfer coefficient of the heat exchanger are taken as an object function respectively, and fin-pitch, tube distance, tube rows, row numbers, diameter of heat pipe and the lengths of single pipe are selected as decision variables. …”
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Bearing Fault Diagnosis under Transient Conditions: Using Variational Mode Decomposition and the Symmetrized Dot Pattern-Based Convolutional Neural Network Model by Jide Jia, Jianmin Mei, Chuang Sun, Fengjuan Yang

“…To eliminate the noise components, VMD was used to decompose the vibration signal into different frequency bands to obtain the intrinsic mode functions (IMFs), which were further represented by SDP images, and feature images were extracted according to the noncorrelation coefficient. …”
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Lattice Boltzmann Method for the Generalized Black-Scholes Equation by Fangfang Wu, Duoduo Xu, Ming Tian, Yingying Wang

“…The proposed lattice Boltzmann model can also be applied to a class of partial differential equations with variable coefficients and source terms.…”
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A United Probabilistic Approach to Minimising the Sum of Absolute Values by Changyong Feng, Honghong Liu, Ethan Poon, Ge Feng

“…Methodology: The sum of absolute values can be standardized so that the sum of the coefficients equals 1. In this case, the sum of absolute values takes the form 𝐸𝐸|𝑋𝑋−𝑎𝑎|, where 𝑋𝑋 is a random variable. …”
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Quantitative comparison between single-photon emission computed tomography and positron emission tomography imaging of lung ventilation with 99mTc-technegas and 68Ga-gallgas in pat... by Enrique Gustavo Cuna, Juan Pablo Gambini, Liliana Servente, Eduardo Savio, Henry William Engler, Gabriel Adrián González, Omar Alonso

“…The aim of this study was quantitative comparison between 68Ga-Gallgas positron emission tomography (PET) and 99mTc-Technegas single photon emission computed tomography (SPECT) for lung ventilation function assessment in patients with moderate-to-severe obstructive pulmonary disease and to identify image-derived texture features correlating to the physiologic parameters. …”
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Establishment of an evaluation system for conversion to laparotomy in laparoscopic cholecystectomy and exploration of surgical grading management by ZHANG Nannan, GUO Jinxing, WU Gang, YI Hui, ZHOU Yuanhang, LIAO Zhiwei, HUANG Qi, DONG Jian

“…Then, the risk factors were analyzed by multiple Logistic regression, and the pre-coefficient of each variable of the risk factors was assigned according to the established conversion to laparotomy possibility function. …”
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The Relationship between Optimism and Mindfulness with Cognitive Performance in Older Adults by Sanaz Ghannadi, Morteza Tarkhan

“…Furthermore, 34% of the variance in cognitive function was explained by optimism and mindfulness.Conclusion: Therefore, based on the findings of the present study, it can be concluded that optimism and mindfulness are important variables in predicting cognitive function (p < 0.05).…”
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