Inversion of Leaf Chlorophyll Content in Different Growth Periods of Maize Based on Multi-Source Data from “Sky–Space–Ground” by Wu Nile, Su Rina, Na Mula, Cha Ersi, Yulong Bao, Jiquan Zhang, Zhijun Tong, Xingpeng Liu, Chunli Zhao

“…Then, using grey relational analysis (GRA) and the maximum information coefficient (MIC) algorithm, we explored the complex relationship between the vegetation indices (VIs) and LCC, and further selected feature variables. …”
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Fuzzy Controller Design Optimized by the Grasshopper Algorithm to Realize Maximum Power in Photovoltaic Systems by Kamran Safaei, Aida Esmaeilian-Marnani, Hossein Emami, Amir Hossein Zaeri

“…In this paper, the ISE evaluation index is employed as the cost function of algorithm to verify the obtained results. …”
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A New Four‐Component L*‐Dependent Model for Radial Diffusion Based on Solar Wind and Magnetospheric Drivers of ULF Waves by Kyle R. Murphy, Jasmine Sandhu, I. Jonathan Rae, Thomas Daggitt, Sarah Glauert, Richard B. Horne, Clare E. J. Watt, Sarah Bentley, Adam Kellerman, Louis Ozeke, Alexa J. Halford, Sheng Tian, Aaron Breneman, Leonid Olifer, Ian R. Mann, Vassilis Angelopoulos, John Wygant

“…We investigate the performance of the new models by characterizing the model residuals as a function of each independent variable and by comparing to existing radial diffusion models during a quiet geomagnetic period and through a geomagnetic storm. …”
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An Effective AFNIS-MPPT-Based Method for Optimizing Hybrid Energy Harvesting Systems by Muhammad Saqib, Ghulam Sarwar Kaloi, Mehr Gul, Muhammad Shahzad Nazir, Mohsin Ali Koondhar, Lutfi Albasha, Faisal Alsaif

“…The increasing global demand for renewable energy, particularly from solar and wind sources, highlights the need for sophisticated control strategies to optimize power generation efficiency. Maximum Power Point Tracking (MPPT) techniques are essential for improving the performance of Hybrid Renewable Energy Systems by maximizing power extraction from variable sources. …”
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How Does Digital Banking-Driven Financial Inclusion Affect Income Inequality in Türkiye? by Ahmet Usta

“…As for the empirical evidence, the study employs the dynamic ordinary least squares method to obtain long-run coefficients, a vector autoregressive model to obtain short-run dynamics through impulse response functions with biascorrected bootstrap confidence intervals that account for the bias and skewness of the small sample, and a causality analysis. …”
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Dynamics of Nepalese Stock Market Performance: An Analysis of Macro-economic, Firm-specific, Size, and Event Factors by Rajesh Gurung

“…The ARDL bounds test (F-statistic = 8.378, df = 6, I(0) = 2.88, I(1) = 2.88, α = 1%) indicates the presence of long-run interrelationships among the variables of interest. Additionally, the significant negative coefficient of the error correction term (etc. (-1) = -0.527, p < 0.01) suggests a long-run convergence towards equilibrium. …”
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Digital Twin Control Method of Machine Tool Feed Rate Based on Fuzzy Neural Network by YIN Jia, BAI Lele, TIAN Hui, WU Shijie, Hou Guijin, TANG Yuyang, LIU Hongguang, ZHANG Jun

“…The fuzzy neural network is trained based on the machining data, and the corresponding fuzzy control rules and membership functions are obtained. The control rules are modified according to the actual machining conditions. …”
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带传动软启动装置蜗杆的优化设计 by 赵江平

“…By the mechanical analysis of the belt drives soft-start equipment,tow-objective function is established with the worm axial modulus and spiral angle as the independent variables.Based on self-locking constraint and fuzzy constraint conditions,constraint subset is established.Compared with the general design parameters,the rustle shows that the spiral angle is increased and the worm axial modulus is decreased.The test shows that the optimize design effectively improve the transmission efficiency,and reduce the minimum power of the speed adjustment motor.…”
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A New Multi-Parametric MRI-Based Scoring System for Degenerative Cervical Myelopathy: The Severity on Imaging Myelopathy Score (SIMS) by Alexis Morgado, Julien Berthiller, Fabien Subtil, Donato Creatura, Gildas Patet, Nathalie André-Obadia, Cédric Yves Barrey

“…<b>Background/Objectives:</b> Degenerative cervical myelopathy (DCM) is the leading cause of functional disabilities of spinal origin in people over 50 years old. …”
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Analysis of MAXIM Application Service Quality on User Satisfaction using the E-Service Quality Method by Putri Wulandari, Nur Rachman Dzakiyullah, Asti Ratnasari, Dadang Heksaputra

“…Overall, the quality of Maxim's service towards user satisfaction is not good in terms of the variables of efficiency, system availability, responsiveness, and contact. …”
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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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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. …”
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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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Predicting Wastewater Characteristics Using Artificial Neural Network and Machine Learning Methods for Enhanced Operation of Oxidation Ditch by Igor Gulshin, Nikolay Makisha

“…This study investigates the operational efficiency of the lab-scale oxidation ditch (OD) functioning in simultaneous nitrification and denitrification modes, focusing on forecasting biochemical oxygen demand (BOD₅) concentrations over a five-day horizon. …”
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Reconstructing Equatorial Electron Flux Measurements From Low‐Earth‐Orbit: A Conjunction Based Framework by D. L. Stumbaugh, J. Bortnik, S. G. Claudepierre

“…For each conjunction, we fit the equatorial pitch angle distribution (PAD) parameterized by the function JD=C⋅sinNα. The resulting conjunction data set contains the POES electron flux measurements, L and magnetic local time coordinates, geomagnetic activity Auroral Electrojet index, and C and N coefficients from the PAD fit for each conjunction. …”
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RP-18 HPLC Analysis of Drugs’ Ability to Cross the Blood-Brain Barrier by Anna W. Sobańska, Adam Hekner, Elżbieta Brzezińska

“…On the other hand, discriminant function analyses involving log k and (log k)/PSA as discriminating variables separated the CNS+ and CNS− compounds with the success rate ca. 90%. …”
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Polynomial Chaos Expansion Approach to Interest Rate Models by Luca Di Persio, Gregorio Pellegrini, Michele Bonollo

“…The Polynomial Chaos Expansion (PCE) technique allows us to recover a finite second-order random variable exploiting suitable linear combinations of orthogonal polynomials which are functions of a given stochastic quantity ξ, hence acting as a kind of random basis. …”
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Distributed generation plants multi-agent controlling system by YU. N. Bulatov, A. V. Kryukov

“…The adaptability of the system against variable conditions and applicability of the multi-agent technologies during creation of electric power supply smart grids was demonstrated.…”
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Enlightening the Critical Factors affecting the Solvency of Indian Construction Industry: An Empirical Analysis using Multivariate Discriminant Analysis and Logistic Regression by RAKESH SHARMA, Neba Bhalla

“…So one discriminant function is created and found significant at 5% levels for two different solvency parameters. …”
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Evaluation of the Characteristics of Short Acquisition Times Using the Clear Adaptive Low-Noise Method and Advanced Intelligent Clear-IQ Engine by Ryosuke Ogasawara, Akiko Irikawa, Yuya Watanabe, Tomoya Harada, Shota Hosokawa, Kazuya Koyama, Keisuke Tsuda, Toru Kimura, Koichi Okuda, Yasuyuki Takahashi

“…The images were evaluated based on the coefficient of variation, recovery coefficient, % background variability (N_10mm), % contrast-to-% background variability ratio (Q_H10mm/N_10mm), and contrast-to-noise ratio. …”
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