Application of the Salp Swarm Algorithm to Optimal Design of Tuned Inductive Choke by Łukasz Knypiński, Milena Kurzawa, Rafał Wojciechowski, Michał Gwóźdź

“…A lumped-parameters model of a tuned inductive choke was developed, with the device’s structure described by three design variables. As an optimality criterion, the multi-objective compromise function was adopted. …”
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A Model-Driven Approach for Estimating the Energy Performance of an Electric Vehicle Used as a Taxi in an Intermediate Andean City by Jairo Castillo-Calderón, Daniel Cordero-Moreno, Emilio Larrodé Pellicer

“…The results demonstrated a Pearson correlation coefficient of 0.93, indicating a strong positive linear dependence between the variables. …”
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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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Hybrid data-driven and physics-informed regularized learning of cyclic plasticity with neural networks by Stefan Hildebrand, Sandra Klinge

“…The mean squared error is assumed as the loss function which stipulates several restrictions: deviatoric character of internal variables, compliance with the flow rule, the differentiation of elastic and plastic steps and the associativity of the flow rule. …”
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HEART AND VESSEL REMODELING IN DIFFERENT AGE GROUPS OF PATIENTS WITH ARTERIAL HYPERTENSION by V. N. Kandilova

“…The Spearman rank correlation coefficient (r) was used to estimate the relationship between these variables. …”
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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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Trajectory Planning Based on Screw Theory with Consideration of the Optimal Berth Position for a Space Robot by Yong Wang, Ying Liao, Kejie Gong

“…First, the berth position is transformed into the desired position of the end-effector, and its constraints are described. Joint variables are parameterized using a sinusoidal function combined with a five-order polynomial function. …”
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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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Sensory profiles in older adults with orthopedic conditions during quiet stance: a cross-sectional study by Marine Brika, France Mourey, Alexandre Kubicki

“…Methods Fifty-one older adults (76.9 ± 7.6 years) were divided into 2 Functional Groups (FG-/FG+) according to a composite score that included 3 variables (gait speed, grip strength and fear of falling). …”
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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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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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Underactuated Spatial Mechanism of Vehicle Door Latch with Force Constraint by Sulong Li, Lubin Hang, Mingyuan Wang, Xiaojie Huang

“…Aiming at less space occupation，efficient driving and high-end multi-function of the door latch release branch chain，the type synthesis of single loop spatial mechanism is carried out，and the RRRSR mechanism which could realize power release is obtained. …”
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A Quality Soft Sensing Method Designed for Complex Multi-process Manufacturing Procedures by Kaixiang PENG, Xin QIN, Jiahao WANG, Hui YANG

“…Objective Accurately perceiving key quality variables in complex manufacturing processes is essential for achieving system optimization control and ensuring safe and stable operation. …”
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Bayesian inference of structured latent spaces from neural population activity with the orthogonal stochastic linear mixing model. by Rui Meng, Kristofer E Bouchard

“…The brain produces diverse functions, from perceiving sounds to producing arm reaches, through the collective activity of populations of many neurons. …”
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A robust deep learning approach for photovoltaic power forecasting based on feature selection and variational mode decomposition by Mokhtar Ali, Abdelkerim Souahlia, Abdelhalim Rabehi, Mawloud Guermoui, Ali Teta, Imad Eddine Tibermacine, Abdelaziz Rabehi, Mohamed Benghanem

“…To further enhance model inputs, Variational Mode Decomposition (VMD) is applied to extract informative Intrinsic Mode Functions (IMFs) from the selected features. A comparative evaluation of the models indicates that recurrent neural networks, particularly GRU and LSTM, deliver superior performance across various metrics, including RMSE, MAE, nRMSE, nMAE, R², and the correlation coefficient. …”
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EM Algorithm in the Modified Slash Power Maxwell Distribution with an Application by Francisco A. Segovia, Yolanda M. Gómez, Héctor J. Gómez, Inmaculada Barranco-Chamorro, Héctor W. Gómez

“…We study its probability density function and some properties, such as moments, asymmetry and kurtosis coefficient. …”
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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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Research and development of thick plate shape prediction system based on industrial big data by Yufei MA, Changxin LIU, Wei KONG, Jinliang DING

“…Thick plate shape is one of the important indicators to measure the quality of thick plate products.The timely prediction of the final plate shape in production is of great significance for adjusting the operation and control of thick plate production.In actual industrial production, thick plate data has many characteristics, such as multiple coupling information, large amount of redundant information, and multi-source heterogeneity of data.Combining the needs of thick plate shape prediction, a thick plate shape prediction system was designed and developed.The data dump function was used to filter and preprocess the industrial big data to remove the coupling information and redundant variables in the data.LSTM neural network, convolutional neural network and 3D convolutional neural network were used to extract data features from data of different dimensions, and the features were fused based on the maximum mutual information coefficient to establish an integrated learning prediction model, which effectively solved the modeling difficulties caused by multi-source heterogeneous data.The actual industrial data of a domestic thick plate production line was used for verification, and the results showed the effectiveness of the developed system.…”
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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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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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