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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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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Comparing the Effect of Beractant (Beraksurf™) with That of Poractant Alfa (Curosurf®) on the Need for Intermittent Positive Pressure Ventilation in Neonatal Respiratory Distress S... by Yosra Khazani, Sirous Fathi Manesh, Elnaz Shaseb, Parvin Sarbakhsh

“…Performing appropriate adjusted analysis leads to a more interpretable and efficient estimation of treatment effects. Semiparametric adjustment approach modifies the estimating equations solved by the marginal treatment effect estimator by adding an augmentation function, which makes use of the baseline covariates and estimate the unbiased marginal treatment effect with improved precision. …”
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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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Enhancing wireless applications through reconfigurable electro-mechanical reflectarray antenna design for beam steering by Behrokh Beiranvand, Rashid Mirzavand

“…The proposed design involves multiple reflective strips at variable heights, enabling significant adaptability to incident waves at various angles. …”
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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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Comparative evaluation of machine learning models for enhancing diagnostic accuracy of otitis media with effusion in children with adenoid hypertrophy by Xiaote Zhang, Qiaoyi Xie, Ganggang Wu

“…Confusion matrix analysis further confirmed RF as the optimal model, achieving 0.875 accuracy and robust inter-rater agreement (Cohen's kappa coefficient = 0.696) in the testing cohort. SHAP analysis identified the adenoid-to-nasopharyngeal ratio as the predominant diagnostic indicator, followed by tympanometric type and history of recurrent respiratory infections.ConclusionAn RF-based diagnostic model effectively identifies OME in AH children by integrating anatomical, functional, and inflammatory parameters, providing a clinically applicable tool for enhanced diagnostic accuracy and evidence-based management decisions.…”
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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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p53 transactivation and the impact of mutations, cofactors and small molecules using a simplified yeast-based screening system. by Virginia Andreotti, Yari Ciribilli, Paola Monti, Alessandra Bisio, Mattia Lion, Jennifer Jordan, Gilberto Fronza, Paola Menichini, Michael A Resnick, Alberto Inga

“…<h4>Methodology/principal findings</h4>Given the many factors that might influence p53 function, including expression levels, mutations, cofactor proteins and small molecules, we expanded our previously described yeast-based system to provide the opportunity for efficient investigation of their individual and combined impacts in a miniaturized format. …”
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Improvement of medical images with multi-objective genetic algorithm and adaptive morphological transformations by Sadeq Moradzadeh, Vahid Mehrdad

“…Additionally, variable coefficients for these transformations are incorporated into the improved image formula, unlike previous studies that utilized constant coefficients. …”
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Sinc-Chebyshev Collocation Method for a Class of Fractional Diffusion-Wave Equations by Zhi Mao, Aiguo Xiao, Zuguo Yu, Long Shi

“…This paper is devoted to investigating the numerical solution for a class of fractional diffusion-wave equations with a variable coefficient where the fractional derivatives are described in the Caputo sense. …”
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Proposing Optimized Random Forest Models for Predicting Compressive Strength of Geopolymer Composites by Feng Bin, Shahab Hosseini, Jie Chen, Pijush Samui, Hadi Fattahi, Danial Jahed Armaghani

“…We present a comparative analysis of two hybrid models, Harris Hawks Optimization with Random Forest (HHO-RF) and Sine Cosine Algorithm with Random Forest (SCA-RF), against traditional regression methods and classical models like the Extreme Learning Machine (ELM), General Regression Neural Network (GRNN), and Radial Basis Function (RBF). Using a comprehensive dataset derived from various scientific publications, we focus on key input variables including the fine aggregate, GGBS, fly ash, sodium hydroxide (NaOH) molarity, and others. …”
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Cognitive performance classification of older patients using machine learning and electronic medical records by Monika Richter-Laskowska, Ewelina Sobotnicka, Adam Bednorz

“…The nonlinear Support Vector Machine (SVM) with a Radial Basis Function (RBF) kernel achieve the best performance for MCI classification, with an accuracy of 69%, an AUC of 0.75, and a Matthews Correlation Coefficient (MCC) of 0.43. …”
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Modal Analysis of QP and LP Solution in Steady-state Optimization Layer of Two-layer Structure MPC by WANG Hongrui, ZHANG Xin, LIU Bowen, LIN Na, ZOU Tao

“…Simulation results prove that QP had better continuity than LP when the weight coefficient of decision variables are changed, and the weight coefficient of QP can more accurately adjust the bias of decision variables. …”
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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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The Design and Analysis of a Lightweight Robotic Arm Based on a Load-Adaptive Hoisting Mechanism by Ruchao Wang, Zhiguo Lu, Yiru Wang, Zhongqing Li

“…The proposed design integrates a spring-loaded rope and a variable radius reel into the gripper, enabling efficient load adaptability with minimal structural complexity. …”
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THE USE OF CORRELATION ANALYSIS OF TWO-DIMENSION STOCHASTIC PROCESS FOR HELICOPTER MAINTENANCE WORKABILITY ESTIMATION by Y. M. Chinyuchin, A. S. Solov’ev

“…The linear correlated dependence is considered as linear or anyconnection close to it between two variables for which the correlated analysis theorem is true.The algorithm of calculated program complex for helicopter maintenance workability estimation consists of five steps: choice of equipment that needs to be installed on the helicopter; correlation coefficient calculation for helicopters having this equipment and revealing of optimal variants of location; zone partition of the developed helicopter and analysis of possi- ble disposal of clusters in optimal order; disposal of clusters on the designed helicopter; correlation coefficient calculation, direct regression construction for the designed helicopter and comparison of these readings with helicopters-analogues. …”
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Development of a Plant-Based Beverage with Tarwi (<i>Lupinus mutabilis</i>) Milk, Polysaccharides from Cushuro (<i>Nostoc sphaericum</i>), and Blueberry Extract by Santos Calderón, Renzo Bañón

“…The response variables were protein (%) content and viscosity coefficient (mPa·s). …”
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The estimation of correlation between milk and reproductive traits in holstein by canonical correlation analysis by İsmet Doğan

“…The process ot maximizing the correlation between two linear function ot two sets of random variables is known as Canonical Correlation Analysis, Canonical Correlation Analysis is a statistical method which has been used to describe the re latıonshıp between a set o! …”
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Mechanical Impedance Control in the Human Arm While Manually Transporting an Open-Top Fluid Filled Dish by Navit Roth, Rami Seliktar, Joseph Mizrahi

“…The results revealed that the wrist joint was found to have constant stiffness and damping and no regulation of these coefficients was necessary during gait. Both in the elbow and shoulder joints stiffness included a constant coefficient as well as an angular velocity-dependent coefficient. …”
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