Analysis Method of Agricultural Total Factor Productivity Based on Stochastic Block Model (SBM) and Machine Learning by Yanzi Li, Cai Chen, Fuqiang Liu, Jian Wang

“…It uses the SBM direction distance function and the Luenberger productivity index to measure the agricultural efficiency, total factor productivity, and their components. …”
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Tomato quality based on colorimetric characteristics of digital images by Thaísa B. Bello, Anderson G. Costa, Thainara R. da Silva, Juliana L. Paes, Marcus V. M. de Oliveira

“…The correlation between colorimetric and physico-chemical variables was analyzed using the Pearson’s coefficient. …”
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Machine learning projection of climate and technology impacts on crops key to food security by Dan Li, Vassili Kitsios, David Newth, Terence John O’Kane

“…Here we introduce a multivariate autoregressive econometrics model that includes a time-varying non-linear variable to account for the decreasing impact of technology on crop yields. …”
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On the Modular Design Application for the Gas Turbine Sector: A Performance Optimization Approach in the Context of Industry 4.0 by Lucas Chavanel-Precloux, Roland Maranzana, Lucas A. Hof

“…Indeed, this study presents the functioning of the novel application, the different deployed components and their variables, such as the compressor efficiency, heat exchangers, or turbine stages, and the decision variable, e.g., the costs of generated energy. …”
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Locomotive Syndrome Digital Therapeutics Provided via a Smartphone App: Protocol for a Single-Group Trial by Tatsuru Sonobe, Yoshihiro Matsumoto

“…We evaluated the participants’ objective motor function using the timed up and go (TUG) test, and we compare the results using a 3-way ANOVA with the TUG test at the 3 evaluation time points as the dependent variable. …”
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Machine learning-based prediction of pervaporation permeation using physicochemical properties of permeant-membrane and process conditions by Muhammad Mujiburohman, Marwen Elkamel, Farzad Hourfar, Ali Elkamel

“…Two types of inputs were evaluated: regular variables (Type I) and dimensionless groups derived from these regular variables (Type II). …”
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Comparison and System Development of a Two-Coil and Three-Coil Inductive Link for Transcutaneous Power Transfer by Maarten Schelles, Ward Lievens, Laurens Goyvaerts, Frederik Ceyssens, Rikky Muller, Michael Kraft

“…Keeping all geometric constraints constant, we investigated the differences between a two-coil and three-coil inductive link, showing that the two-coil system has a higher peak efficiency of the inductive link of 84%, while the three-coil system displays a flatter efficiency curve with a peak of 78%, as a function of the variable power consumption. …”
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Root‐Zone Water‐Storage Capacity and Uncertainty: An Intrinsic Factor Affecting Agroecosystem Resilience to Drought by Nunzio Romano, Caterina Mazzitelli, Paolo Nasta

“…Root‐zone water‐storage capacity (SR) is a commonly used variable of agroecosystem functioning, representing the maximum value of water stored within the root zone and accessible to vegetation for its productive growth. …”
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PENGARUH MUTASI TERHADAP SEMANGAT KERJA PEGAWAI NEGERI SIPIL PADA KANTOR PELAYANAN PAJAK PRATAMA KOTA PEMATANG SIANTAR by Arnimisari Juliana Ambarita, Hatta Ridho

“…The data processed by the correlation coefficient and the determinant Moment Product to see the great influence of the variable X against Y variable. …”
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Multivariate predictive modeling of compressive strength in ground granulated blast furnace slag/fly ash-based alkali-activated concrete by Dina A. Emarah

“…Using a comprehensive dataset of 1590 samples with 14 input variables, it captures the complex, multi-variable dependencies affecting AAC's mechanical behavior. …”
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A novel unified variational finite difference (VFD) solution method for optimal control problems by Amir Norouzzadeh, Nader Nariman-zadeh, Reza Ansari

“…To do so, the general form of quadratic performance index function and nonlinear state equations are considered first. …”
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Utilizing a Transient Electromagnetic Inversion Method with Lateral Constraints in the Goaf of Xiaolong Coal Mine, Xinjiang by Yingying Zhang, Bin Xie, Xinyu Wu

“…Through an OCCAM inversion approach, the regularization factor is dynamically determined by evaluating the norms of the data objective function and model objective function in each iteration, thereby reducing the reliance of inversion results on the initial model. …”
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Proportional Topology Optimization algorithm for two-scale concurrent design of lattice structures by Minh Ngoc Nguyen, Duy Vo, Tinh Quoc Bui

“…Here, the objective function is reformulated such that the contribution of each micro-scale design variable can be determined, facilitating the employment of PTO. …”
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Estimation of Stochastic Frontier Models with Fixed Effects through Monte Carlo Maximum Likelihood by Grigorios Emvalomatis, Spiro E. Stefanou, Alfons Oude Lansink

“…This paper proposes a procedure for choosing appropriate densities for integrating the incidental parameters from the likelihood function in a general context. The densities are based on priors that are updated using information from the data and are robust to possible correlation of the group-specific constant terms with the explanatory variables. …”
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Fast Möbius transform: An algebraic approach to information decomposition by Abel Jansma, Pedro A. M. Mediano, Fernando E. Rosas

“…The partial information decomposition (PID) and its extension integrated information decomposition (ΦID) are promising frameworks to investigate information phenomena involving multiple variables. An important limitation of these approaches is the high computational cost involved in their calculation. …”
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Predicting the onset of chronic kidney disease (CKD) for diabetic patients with aggregated longitudinal EMR data. by Neda Aminnejad, Michelle Greiver, Huaxiong Huang

“…This research focuses on developing a predictive model to classify diabetic patients showing signs of kidney function impairment based on their CKD development risk. …”
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Mitigating Load Imbalance and Enhancing Distribution Transformer Performance via Fuzzy Inference System by Althoff Hibban, Azriyenni Azhari Zakri, Dirman Hanafi, Boy Ihsan, Umair Ali

“…To address this issue, this study proposes a fuzzy logic-based approach using a Mamdani-type Fuzzy Inference System (FIS). The input variables, current magnitudes in phases R, S, and T, are represented by trapezoidal membership functions classified into several categories. …”
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Decomposed Linear Dynamical Systems (dLDS) models reveal instantaneous, context-dependent dynamic connectivity in C. elegans by Eva Yezerets, Noga Mudrik, Adam S. Charles

“…Abstract Mounting evidence indicates that neural “tuning” can be highly variable within an individual across time and across individuals. …”
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Physics-augmented deep learning models for improving evapotranspiration estimation in global land regions by Binrui Liu, Xinguang He, Wenkai Lyu, Lizhi Tao

“…A Physics-Data Learning (PDL) model is first formed by adding a complementary physical variable generated by Penman–Monteith (PM) equation to a deep learning (DL) model along with driving variables to regress latent heat flux. …”
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Jacobian-Free Newton Krylov Methods for Steady and Transient Neutron Transport Models by ZHANG Yangyi, ZHANG Tiancheng, ZHOU Xiafeng

“…To further improve computational efficiency of comeSn_JFNK, in the JFNK solution, neutron scalar fluxes instead of neutron angular fluxes were chosen as the global solution variables. …”