Supplier Selection and Order Allocation in A Pharmaceutical Wholesaler by Ryan Hikmah Fadilla, Cucuk Nur Rosyidi, Wakhid Ahmad Jauhari

“…As part of the system modeling, a sensitivity analysis was performed to explore the effects of specific parameters on the objective function and decision variables, assessing variations in inventory costs, shortage costs, and demand. …”
Get full text

Modeling of Thermal Distributions around a Barrier at the Interface of Coating and Substrate by Ali Sahin

“…Using integral transform method, two-dimensional steady-state diffusion equation with variable conductivity is turned into constant coefficient differential equation. …”
Get full text

Predicting biogas production in real scale anaerobic digester under dynamic conditions with machine learning approach by M. Erdem Isenkul, Sevgi Güneş-Durak, Yasemin Poyraz Kocak, İnci Pir, Mertol Tüfekci, Güler Türkoğlu Demirkol, Selçuk Sevgen, Aslı Seyhan Çığgın, Neşe Tüfekci

“…In recent years, the use of machine learning techniques (ML) has become widespread for analysing the effects of operational factors on anaerobic digestion efficiency. Among these, Support Vector Regression (SVR) with a Radial Basis Function (RBF) kernel has been used to predict biogas yield based on diverse operating parameters. …”
Get full text

Intelligent hybrid method to predict generated power of solar PV system by Prashant Singh, Navneet Kumar Singh, Asheesh Kumar Singh

“…The input solar PV power data are broken down into intrinsic mode functions (IMFs) using EMD technique is fed into the PSO-ANFIS, along with important meteorological variables. …”
Get full text

Application of machine learning and neural network models based on experimental evaluation of dissimilar resistance spot-welded joints between grade 2 titanium alloy and AISI 304 s... by Marwan T. Mezher, Alejandro Pereira, Rusul Ahmed Shakir, Tomasz Trzepieciński

“…The best prediction model was found to be the ANN model when training the conjugate gradient with the Polak-Ribiere updates (Traincgp) training function with the hyperbolic tangent sigmoid transfer function (Tansig) with the mean squared error (MSE) and correlation coefficient (R2) values recorded as 0.01886 and 0.94973, respectively. …”
Get full text

Topologic Reorganization of White Matter Connectivity Networks in Early-Blind Adolescents by Zhifeng Zhou, Long Qian, Jinping Xu, Yumin Lu, Fen Hou, Jingyi Zhou, Jinpei Luo, Gangqiang Hou, Wentao Jiang, Hengguo Li, Xia Liu

“…Moreover, decreased regional efficiency and increased nodal path length in some visual and default-mode areas were strongly associated with the period of blindness in EBA cohort, suggesting that the function of these areas would gradually weaken in the early-blind brains. …”
Get full text

Predicting and Mapping of Soil Organic Matter with Machine Learning in the Black Soil Region of the Southern Northeast Plain of China by Yiyang Li, Gang Yao, Shuangyi Li, Xiuru Dong

“…In terms of accuracy, the coefficient of determination of RF was 0.77, and the root mean square error was 2.85. …”
Get full text

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. …”
Get full text

Analysis of Mechanical and Thermal Material Characteristics of GPL-Reinforced Double-FG Composite Nanoplates under Temperature Load by Kerim Gökhan Aktaş

“…The analysis is conducted to evaluate the influence of variables like temperature rise, GPLs weight ratio and GPLs distribution patterns on the thermal and mechanical properties of the nanoplate such as effective modulus of elasticity, Poisson's ratio, coefficient of thermal expansion and coefficient of thermal conductivity. …”
Get full text

Collaborative Federated Learning of Unmanned Aerial Vehicles in Space–Air–Ground Integrated Network by Huibo Li, Peng Gong, Siqi Li, Weidong Wang, Yu Liu, Xiang Gao, Dapeng Oliver Wu, Duk Kyung Kim, Guangwei Zhang, Jihao Zhang

“…In addition, the closed-form solutions of the optimized variables are obtained. Simulation results demonstrate that the proposed collaborative training scheme based on D2D can reduce the impact of heterogeneity on FL model performance and IRA can effectively reduce energy consumption while simultaneously enhancing training efficiency of FL.…”
Get full text

Thermoelastic damping in piezothermoelastic nanobeam resonators under the strain gradient theory with micro-inertia and non-fourier heat conduction by Olha Hrytsyna, Maryan Hrytsyna

“…To account for small-scale effects, the Helmholtz free energy density is defined as a function of the strain tensor, strain gradient tensor, electric field vector, and temperature field, considering these parameters as independent state variables. …”
Get full text

Impact of viscous dissipation, chemical reaction over a Carreau hybrid nanofluids flow across a permeable curved Riga surface by R. Mahesh, U.S. Mahabaleshwar, Basma Souayeh

“…The current work examines the significant impact of Carreau hybrid nanofluid, particularly in enhancing thermal conductivity and heat transfer efficiency, which is discussed through the integration of aluminium oxide (Al2O3) and titanium dioxide (TiO2) nanoparticles into a base fluid made of 50 % water and 50 % ethylene glycol solution. …”
Get full text

Enhancing Urban Heat Island Analysis Through Multisensor Data Fusion and GRU-Based Deep Learning Approaches for Climate Modeling by Ning Tang, Muhammad Farhan, Pir Mohammad, M. Abdullah-Al-Wadud, Saddam Hussain, Umair Hamza, Rana Muhammad Zulqarnain, Nazih Yacer Rebouh

“…The GRU-based model achieved a coefficient of determination (R²) of 0.90 with an RMSE value of 0.09, indicating robust predictive performance. …”
Get full text

Accelerating charge estimation in molecular dynamics simulations using physics-informed neural networks: corrosion applications by Aditya Venkatraman, Mark A. Wilson, David Montes de Oca Zapiain

“…This demonstrates the excellent accuracy, computational efficiency, and validity of the developed model. Lastly, even though developed for corrosion, these protocols are formulated in a phenomenon-agnostic manner, allowing application to various variable-charge interatomic potentials and related fields.…”
Get full text

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. …”
Get full text

Introducing the MESMER-M-TPv0.1.0 module: spatially explicit Earth system model emulation for monthly precipitation and temperature by S. Schöngart, S. Schöngart, L. Gudmundsson, M. Hauser, P. Pfleiderer, Q. Lejeune, S. Nath, S. I. Seneviratne, C.-F. Schleussner, C.-F. Schleussner, C.-F. Schleussner

“…Owing to their runtime efficiency, emulators are especially useful when large amounts of data are required, for example, for in-depth exploration of the emission space, for investigating high-impact low-probability events, or for estimating uncertainties and variability. …”
Get full text

Analysis of factors influencing the increase of extracellular water ratio in tumor patients without edema signs by Heling Zhu, Panpan Gan, Hao Jiang, Liangliang Bao, Chengjiang Liu, Jiawen Yu, Jiawen Yu

“…ECW/TBW increased with age (partial regression coefficient B = 0.009, p = 0.001), was higher in males than in females (B = −0.349, p < 0.001), and was negatively affected by hemoglobin (Hgb) (B = −0.003, p = 0.039). …”
Get full text

PileBetaGR: An R-based integrative tool for predicting the geometric reliability index of piles using load-displacement curves by Xing Zheng Wu

“…The PileBetaGR enables users to construct three- and four-dimensional environmental contours by treating the dead and live load as random variables and to understand the roles various correlation coefficients, marginal distributions, and loading ratios play in the reliability index evaluation. …”
Get full text

Variations in Creatinine Generation Among Patients With Glomerular Disease: Evidence From the NEPTUNE and CureGN Studies by Shalini S. Ramachandra, Melody Chiang, Michael Arbit, Dorey A. Glenn, Laura H. Mariani, Jarcy Zee

“…Analytical Approach: The intraclass correlation coefficient illustrated crG variability within individuals. …”
Get full text

Slow and Quick Flow Models Explain the Temporal Dynamics of Daily Salinity in Streams by Thomas G. Westfall, Tim J. Peterson, Anna Lintern, Andrew W. Western

“…Compared to the simple C‐Q equation, this equation explained the temporal dynamics with an average increase of 0.17 in the Nash‐Sutcliffe efficiency coefficient. Global parameter estimation gave an objective estimate of baseflow with a plausible baseflow index ranging between 0.05 and 0.40 across catchments. …”
Get full text