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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A Computational Approach to Increasing the Antenna System’s Sensitivity in a Doppler Radar Designed to Detect Human Vital Signs in the UHF-SHF Frequency Ranges by David Vatamanu, Simona Miclaus

“…In the context of Doppler radar, studies have examined the changes in the phase shift of the S₂₁ transmission coefficient related to minute movements of the human chest as a response to breathing or heartbeat. …”
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Patients' satisfaction, expectation, care, and maintenance of fixed prosthesis by Nada Kashbur, Iman Bugaighis

“…Descriptive statistics and Spearman rank correlation coefficient tests were undertaken between the examined variables. …”
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Performance of Machine Learning Classifiers for Diabetes Prediction by Mijala Manandhar, Shaikat Baidya, Babalpreet Kaur, Katia Atoji

“…The dataset included 768 instances with nine attributes, where the target variable indicated whether a patient tested positive for diabetes. …”
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Fiscal Sustainability in Iran A Markov-Switching Fiscal Regime Change and Time-Varying Parameter Models Approach by Hossein Aghilifar, Khosrow Piraei, Hashem Zare, Mehrzad Ebrahimi

“…Then the Markov-switching fiscal regime change model and the time-varying parameter fiscal reaction function are estimated. Among the constant parameter linear and non-linear models, only the linear model including control variables has a significant debt-to-GDP ratio coefficient, which its sign is negative. …”
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Process engineering by Ahmed Mohamed Farid Shaaban, Azza Ibrahim Hafez, Mona Amin Abdel-Fatah, Nabil Mahmoud Abdel-Monem, Mohamed Hanafy Mahmoud

“…The solution diffusion model was used to develop power correlations to calculate the permeate side solute mass transfer coefficient as a function of effective cross-flow Reynolds number. …”
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Statistical mechanics of dynamical system identification by Andrei A. Klishin, Joseph Bakarji, J. Nathan Kutz, Krithika Manohar

“…To establish this analogy, we define the hyperparameter optimization procedure as a two-level Bayesian inference problem that separates variable selection from coefficient inference and enables the computation of the posterior parameter distribution in closed form. …”
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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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First-principles investigation on structural, electronic, and optical properties of (Cd1-xZnx)3As2 by Yu Deng, Xun Ge, Rongxiu Feng, Yunye Liang, Xiaohao Zhou

“…Calculations on the optical properties (dielectric function, absorption coefficient) of (Cd1-xZnx)3As2 show that it behaves well in the near infrared and far infrared. …”
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Inversion and validation of soil water-holding capacity in a wild fruit forest, using hyperspectral technology combined with machine learning by Tingwei Song, Liang Guo, Qian Sun, Guizhen Gao, Jing Chen, Qikun Zhang

“…The results revealed a significant negative correlation between SWHC and the smoothed leaf spectral reflectance, with the best correlation coefficient was r = − 0.59. The use of third-order derivatives and logarithmic second-order derivatives further enhanced this correlation, yielding optimal coefficients of r = − 0.78 and r = − 0.72, respectively. …”
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Enhancing Thermal–Hydraulic Performance in Nuclear Reactor Subchannels with Al₂O₃ Nanofluids: A CFD Analysis by Mohammad A. I. Sardar, Mushfiqur Rahman, Philip Rubini

“…This analysis has been carried out using the RNG k-epsilon turbulence model with standard wall function in ANSYS FLUENT 2022R1. The impact of various flow conditions and nanofluid concentrations has been examined. …”
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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

“…For developing the SVM_Poly, SVM_RBK models, an extensive number of trials were conducted using various combinations of C and d for polynomial kernels and C and ∂ for radial basis function kernel-based support vector machines (SVMs) utilizing user-defined parameters. …”
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Analyzing Worn-Out Texture Regeneration from Urban Branding Perspective Using Structural Equation Modeling (SEM) (Case Study: Worn-Out Texture of Shahr-e-Kord) by Dvood Mahdavi, Ali Mohammadi Gojani, Waliullah Nazari

“…Furthermore, the findings demonstrated a strong, positive, and significant influence of the branding variable on the regeneration of the worn-out urban fabric with an impact coefficient of 0.833. …”
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Numerical and Experimental Study of a Hydrodynamic Analysis of the Periodical Fluctuation of Bio-Inspired Banded Fins by Chonglei Wang, Qihang Liu, Junhao Yang, Chunyu Guo

“…By using a method of controlling variables, such as wave number, swing angle, and frequency, where only one independent variable is changed at a time while the others remain constant, the impact on thrust coefficient function and the obtained periodic variation laws governing hydrodynamic performance are studied. …”
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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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Application of artificial neural network in deoxygenation of water by glucoseoxidase immobilized in calcium alginate/MnO2 composite by A. Abdi, M.Sh Izadkhah, A. Karimi, M. Razzaghi, H. Moradkhani

“…The linear regression between the network outputs and the corresponding targets were proven to be satisfactory with a correlation coefficient of 0.995 for three model variables used in this study.…”
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Fractional Dynamics of Laser-Induced Heat Transfer in Metallic Thin Films: Analytical Approach by M. A. I. Essawy, Reham A. Rezk, Ayman M. Mostafa

“…Dynamic profiles demonstrate the responsiveness of heat transfer to thermal and optical variables. The innovation resides in the meticulous analytical formulation utilizing a realistic laser source, the clear significance of the absorption parameter that enhances the temperature amplitude, the incorporation of the Mittag–Leffler function, and a comprehensive investigation of fractional photothermal effects in metallic nano-systems. …”
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Random First-Order Linear Discrete Models and Their Probabilistic Solution: A Comprehensive Study by M.-C. Casabán, J.-C. Cortés, J.-V. Romero, M.-D. Roselló

“…The study is based on Random Variable Transformation method. The obtained results are given in terms of the probability density functions of the data, namely, initial condition, forcing term, and diffusion coefficient. …”
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ANALYSIS AND OPTIMIZATION OF QUICK-RETURN CHARACTERISTICS OF THE BEATING⁃UP SLEY BASED ON MULTIVARIABLE DESIGN by QIU HaiFei

“…For improving the quick‑return characteristics of the sley movement,an optimal mathematical model for maximum curve displacement Sm of the connectingarm pin was proposed through beating‑up principle analysis and mechanism deduction.A multivariable design space was constructed by use of the component length(lc,lh,lr,lf)and crankangleα.The parametric functional model development of the four‑bar beating‑up with short connecting rod was realized,and its kinematic posture and centroid trajectory were analyzed and verified through mechanism simulation.The results of the case study indicate that the variable lc andαhave more greater influence on the sensitivity of the objective function F(X),and multivariable(DV_1,DV_2,DV_3)coupling can effectively enhance the design plasticity of the quick‑return characteristics of the sley.When the maximum curve displacement Sm of the connectingarm pin increases to 71.41 mm,the extreme position angleθand the travel speed ratio coefficient K are increased by 10.96°and 0.131 respectively,and the quick-return motion effect of the sley is obviously improved.The optimization results accord with the conditions of rod length and mechanism transmission requirement,which are conductive to the design innovation and performance improvement of the four‑bar beating‑up system.…”
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Modelling Geographically Weighted Truncated Spline Regression Using Maximum Likelihood Estimation for Human Development Disparities by Laode Muhammad Saris, Henny Pramoedyo, Adji Achmad Rinaldo Fernandes

“…Among these, the Bi-Square weighting function performed the best, achieving a coefficient of determination of 99.999%, demonstrating the model’s capability to explain nearly all data variability effectively. …”
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