Enhanced Stability and Control of Solar Powered EV Charging Stations Using Disturbance Observer-Based Adaptive Sliding Mode Control for DC Voltage Stabilization by Surabhi Bagherwal, Subhasish Mahapatra

“…To address the chattering issue, a barrier function based SMC (BFSMC) approach is proposed. The distinctive aspects of this BFSM control approach is its capability to stabilize the designed sliding variable to a predefined neighbourhood around the origin within a limited duration, eliminating the need for prior understanding of the maximum limit of the lumped disturbance. …”
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Autonomous obstacle avoidance of underground coal mine transport robots based on intrinsic motivation reinforcement learning algorithm by ZHAO Kebao, LI Lingfeng, CHEN Zhuo, HAN Jun, YIN Rui

“…Existing robot obstacle avoidance methods mostly rely on preset rules or external reward signals, making it difficult to adapt to the complex and variable underground environment in coal mines. To achieve autonomous and efficient obstacle avoidance for underground coal mine transport robots, an autonomous obstacle avoidance method for underground coal mine transport robot based on Intrinsic Motivation Reinforcement Learning (IM-RL) algorithm was proposed. …”
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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. …”
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Design and Simulation of Ornithopter based on Four-bar Mechanism by Zhao Zhifang, Qi Mingsi, Feng Jingkai, Zhang Wei, Wang Junyuan, Zhang Jiping

“…The brushless motor driving two stage reducer,provides input for four-bar mechanism. The robot has a function of the periodic flapping motion,the frequency change and size of the attitude angle adjustment. …”
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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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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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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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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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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 Komite Audit Terhadap Kinerja Keuangan Perusahaan Dengan Dewan Komisaris Sebagai Variabel Intervening by Yunita Kurnia Shanti

“…This result means that the board of Commissioners variable cannot be an intervening variable of the audit committee on financial performance, because the effective supervisory function in evaluating the results of internal and external audits on the presentation of financial statements becomes the role of the audit committee.…”
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Stochastic Transportation Problem with Multichoice Random Parameter by Talari Ganesh, K. K. Paidipati, Christophe Chesneau

“…This paper deals with the situation of multiple random choices along with multiple objective functions of the transportation problem. Due to the uncertainty in the environment, the choices of the cost coefficients are considered multichoice random parameters. …”
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Sinc-Chebyshev Collocation Method for a Class of Fractional Diffusion-Wave Equations by Zhi Mao, Aiguo Xiao, Zuguo Yu, Long Shi

“…This paper is devoted to investigating the numerical solution for a class of fractional diffusion-wave equations with a variable coefficient where the fractional derivatives are described in the Caputo sense. …”
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Research on Side Lobe Suppression of Time-Modulated Sparse Linear Array Based on Particle Swarm Optimization by Lei Liang, Jie Sun, Hailin Li, Jialing Liu, Yachao Jiang, Jianjiang Zhou

“…An efficient pattern synthesis approach is proposed for the synthesis of a time-modulated sparse linear array (TMSLA) in this paper. …”
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High-accuracy solution of pantograph differential equations subject to mixed boundary conditions via shifted Vieta–Lucas polynomials by R. M. Hafez, H. M. Ahmed

“…A Galerkin method (GM) is formulated for constant coefficient-type equations, and a spectral collocation method (SCM) is given for variable coefficient cases. …”
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A Bayesian-Weighted Inverse Gaussian Regression Model with Application to Seismological Data by Ehsan Mesdaghi, Afshin Fallah, Rahman Farnoosh, Gholam Hossein Yari

“…In the proposed model, the complementary reciprocal of the location parameter of response variable is considered to be a linear function of the explanatory variables. …”
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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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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.…”
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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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Comparative evaluation of machine learning models for enhancing diagnostic accuracy of otitis media with effusion in children with adenoid hypertrophy by Xiaote Zhang, Qiaoyi Xie, Ganggang Wu

“…Confusion matrix analysis further confirmed RF as the optimal model, achieving 0.875 accuracy and robust inter-rater agreement (Cohen's kappa coefficient = 0.696) in the testing cohort. SHAP analysis identified the adenoid-to-nasopharyngeal ratio as the predominant diagnostic indicator, followed by tympanometric type and history of recurrent respiratory infections.ConclusionAn RF-based diagnostic model effectively identifies OME in AH children by integrating anatomical, functional, and inflammatory parameters, providing a clinically applicable tool for enhanced diagnostic accuracy and evidence-based management decisions.…”
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