Seismic Performance and Moment–Rotation Relationship Modeling of Novel Prefabricated Frame Joints by Jiaqi Liu, Dafu Cao, Kun Wang, Wenhai Wang, Hua Ye, Houcun Zou, Changhong Jiang

Get full text

The Extent and Patterns of Digitalization in Proactive Land Acquisition Strategy (PLAS) Farms in South Africa by Sukoluhle Mazwane, Moraka Nakedi Makhura, Athula Ginige

“…Standardized digitalization index scores were extracted and fitted to a linear regression model to determine the factors affecting digitalization. …”
Get full text

Integrating near-infrared hyperspectral imaging with machine learning and feature selection: Detecting adulteration of extra-virgin olive oil with lower-grade olive oils and hazeln... by Derick Malavi, Katleen Raes, Sam Van Haute

“…No significant differences (p > 0.05) in model performance were found between those using full spectra and those based on key variable selection. …”
Get full text

Modeling and analysis of the effects of age hardening, magnesium dissolution, and SiC reinforcement on wear properties in eutectic Al-Si composites using full factorial techniques by Ashwin Shetty, Thirumaleshwara Bhat, Sathyashankara Sharma, Ravikantha Prabhu, Ananda Hegde, Nithesh K, Gajanan Anne

Get full text

From agricultural by-products to building materials: A spatial modelling approach to foster green construction sector by Monica C.M. Parlato, Francesca Valenti, Lorenzo Guerrini, Anna Perbellini, Andrea Pezzuolo

“…A GIS-based model was applied to estimate and map the ABP in the Veneto region (Italy). …”
Get full text

Authentication of honey origin and harvesting year based on Raman spectroscopy and chemometrics by Maria David, Dana Alina Magdas

“…The peaks and bands present in the Raman spectra were discussed based on honey composition. In order to increase the efficiency of the models, different preprocessing methods were used and a variable reduction step was employed. …”
Get full text

The Re-Modeling of a Polymeric Drug Delivery System Using Smart Response Surface Designs: A Sustainable Approach for the Consumption of Fewer Resources by Magdy M. Aly, Shaimaa S. Ibrahim, Rania M. Hathout

“…<b>Aim</b>: This study compares the effectiveness of two of the most commonly used response surface designs—Central Composite Design (CCD) and D-optimal Design (DOD)—in modeling a polymer-based drug delivery system. …”
Get full text

Future variation and uncertainty source decomposition in deep learning bias-corrected CMIP6 global extreme precipitation historical simulation by Xiaohua Xiang, Yongxuan Li, Xiaoling Wu, Zhu Liu, Lei Wu, Biqiong Wu, Chuanxin Jin, Zhiqiang Zeng

“…Implementation of CNNs as a BC method could significantly reduce model uncertainty but at the cost of increasing the proportion of scenario uncertainty and internal variability. …”
Get full text

Blood Glucose Concentration Prediction Based on Double Decomposition and Deep Extreme Learning Machine Optimized by Nonlinear Marine Predator Algorithm by Yang Shen, Deyi Li, Wenbo Wang, Xu Dong

“…The existing blood glucose concentration prediction models often overlook the impacts of residual components after multi-scale decomposition on prediction accuracy. …”
Get full text

Stochastic Fracture Analysis Using Scaled Boundary Finite Element Methods Accelerated by Proper Orthogonal Decomposition and Radial Basis Functions by Xiaowei Shen, Haowen Hu, Zhongwang Wang, Xiuyun Chen, Chengbin Du

“…The adoption of POD and RBF significantly reduces the model order and increases computation efficiency, while maintaining the versatility and accuracy of MCs. …”
Get full text

Wind speed prediction for trains on bridges using enhanced variational mode decomposition assisted feature extraction and physical auxiliary mechanism by Zhilan Zhu, Yuan Jiang, Haicui Wang, Shuoyu Liu

“…Finally, PAM is introduced into the above established model for realizing the desired deterministic and probabilistic predictions where the relationship among the wind speed data recorded at various time intervals and the data variability are considered. …”
Get full text

Advanced reference crop evapotranspiration prediction: a novel framework combining neural nets, bee optimization algorithm, and mode decomposition by Ahmed Elbeltagi, Okan Mert Katipoğlu, Veysi Kartal, Ali Danandeh Mehr, Sabri Berhail, Elsayed Ahmed Elsadek

“…In this context, our study aimed to enhance the accuracy of ETo prediction models by combining a variety of signal decomposition techniques with an Artificial Bee Colony (ABC)–artificial neural network (ANN) (codename: ABC–ANN). …”
Get full text

Improving the Estimates of County-Level Forest Attributes Using GEDI and Landsat-Derived Auxiliary Information in Fay–Herriot Models by Okikiola M. Alegbeleye, Krishna P. Poudel, Curtis VanderSchaaf, Yun Yang

Get full text

Optimizing Vehicle Scheduling Based on Variable Timetable by Benders-and-Price Approach by Zekang Lan, Shiwei He, Rui Song, Sijia Hao

“…A Benders-and-Price algorithm by combining the Benders decomposition and column generation is proposed to solve the LP-relaxation of the path-based model, and a bespoke Branch-and-Price is used to obtain the integer solution. …”
Get full text

The effect of macroeconomic variables on non performance financing of Islamic Banks in Indonesia by Latifah Dian Iriani, Imamudin Yuliadi

“…Research methodology used at this study is Vector Error Correction Model (VECM). Following these procedures, it applies Unit Roots Test, Augmented Dickey Fuller Test, Lag Length Criteria Test, Correlation Matrix – Johansen Julius Co-integration Test, VECM Estimation, Impulse Response and Variance Decomposition Test. …”
Get full text

The effect of macroeconomic variables on non performance financing of Islamic Banks in Indonesia by Latifah Dian Iriani, Imamudin Yuliadi

“…Research methodology used at this study is Vector Error Correction Model (VECM). Following these procedures, it applies Unit Roots Test, Augmented Dickey Fuller Test, Lag Length Criteria Test, Correlation Matrix – Johansen Julius Co-integration Test, VECM Estimation, Impulse Response and Variance Decomposition Test. …”
Get full text

Taxonomic variability and functional stability across Oregon coastal subsurface microbiomes by Hengameh H. Soufi, Robert Porch, Masha V. Korchagina, Joseph A. Abrams, Jared S. Schnider, Ben D. Carr, Mark A. Williams, Stilianos Louca

“…In contrast, taxonomic composition was highly variable, especially at the level of amplicon sequence variants (ASVs) and operational taxonomic units (OTUs). …”
Get full text

Efficiency multi-agent model assisted Moea/D algorithm for optimization design for building taking into account annual energy consumption and annual user discomfort hours by Hua Deng, Kai Zhou

“…Then it introduces a multi-agent model auxiliary mechanism to improve the decomposition based multi-objective evolutionary optimization algorithm, and then solves the multi-objective optimization model for building energy efficiency. …”
Get full text

The impact of gradient variable temperature fermentation on the quality of cigar tobacco leaves by Qianying Zhang, Qianying Zhang, Yang Huang, Yang Huang, Hongyue An, Hongyue An, Shuanghong Yang, Shuanghong Yang, Jinshan Lei, Jinshan Lei, Yue Wang, Yue Wang, Pinhe Li, Pinhe Li, Hongfei Zhang, Wen Cai, Wen Cai, Wen Cai, Yun Jia, Yun Jia, Yongqiang Pang, Dongliang Li, Dongliang Li

“…The gradient variable temperature fermentation process underwent a three-phase model to characterize the alterations of CTLs. …”
Get full text

Crustal Heterogeneity of Antarctica Signals Spatially Variable Radiogenic Heat Production by L. Li, A. R. A. Aitken

“…To define this at continent‐scale we use 3D gravity inversion constrained by seismic Moho estimates to identify variations in crustal composition and geometry beneath thick ice. Geochemically‐defined empirical relationships between density and heat production capture the global average trend and its variability, and allow to estimate from upper‐crust density spatial variations in radiogenic heat production. …”
Get full text