Data-Driven Prediction Methods for Lithium-Ion Battery State of Health Based on Elbow Rule by Liu Zhang, Bo Xing, Yanbing Gao, Lei Yao, Dengfeng Zhao, Jinquan Ding, Yanyan Li

“…Lithium-ion batteries are extensively utilized in diverse sectors such as automotive applications. The imprecise estimation of the State Of Health (SOH) will significantly impact safe operations and cost reduction initiatives. …”
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A physics-informed neural network-based method for predicting degradation trajectories and remaining useful life of supercapacitors by Lixin E, Jun Wang, Ruixin Yang, Chenxu Wang, Hailong Li, Rui Xiong

“…To ensure efficient applications of supercapacitors, accurately predicting their degradation trajectories and remaining useful life (RUL) is crucial. …”
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Investigation on the Bearing Characteristics and Bearing Capacity Calculation Method of the Interface of Reinforced Soil with Waste Tire Grid by Jie Sun, Yuchen Tao, Zhikun Liu, Xiuguang Song, Wentong Wang, Hongbo Zhang

“…The average discrepancy between the calculated values of the established model and the theoretical values was merely 2.38% (maximum error < 5%). Overall, this research offers technical assistance for ensuring the safety of subgrade design and promoting environmental sustainability in engineering, enabling the effective utilization of waste tire grids in sustainable reinforcement applications.…”
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Grapevine inflorescence segmentation and flower estimation based on Computer Vision techniques for early yield assessment by Germano Moreira, Filipe Neves dos Santos, Mário Cunha

“…A statistical analysis confirmed the robustness of the framework, with the YOLOv8 model once again standing out, showing no significant differences in error rates across diverse grapevine morphologies and varieties, ensuring wide applicability. …”
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Steady-State Model Enabled Dynamic PEMFC Performance Degradation Prediction via Recurrent Neural Network by Qiang Liu, Weihong Zang, Wentao Zhang, Yang Zhang, Yuqi Tong, Yanbiao Feng

“…Proton exchange membrane fuel cells (PEMFC), distinguished by rapid refueling capability and zero tailpipe emissions, have emerged as a transformative energy conversion technology for automotive applications. Nevertheless, their widespread commercialization remains constrained by technical limitations mainly in operational longevity. …”
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OTFS: A Potential Waveform for Space–Air–Ground Integrated Networks in 6G and Beyond by Obinna Okoyeigbo, Xutao Deng, Agbotiname Lucky Imoize, Olamilekan Shobayo

“…This makes it particularly suitable for high-mobility applications such as satellites, UAVs, and high-speed terrestrial networks. …”
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Advanced beamforming and reflection control in intelligent reflecting surfaces with integrated channel estimation by Sakhshra Monga, Anmol Rattan Singh, Nitin Saluja, Chander Prabha, Shivani Malhotra, Asif Karim, Md. Mehedi Hassan

“…Specifically, the sum rate for GDNNet (GNN + DNN) improves by 12.57% over linear minimum mean square error (LMMSE) and by 12.42% over perfect CSI concerning the number of users, and by 28.57% over LMMSE and by 14.28% over perfect CSI concerning pilot length. …”
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Integrating IoT With Adaptive Beamforming for Enhanced Urban Sensing in Smart Cities by Sunday Enahoro, Sunday C. Ekpo, Mfonobong Uko, Fanuel Elias, Stephen Alabi

“…SmartBeam+ dynamically adjusts the beamforming weights using real-time Channel State Information (CSI) to maximize the Signal-to-Interference-and-Noise Ratio (SINR), minimize the bit error rate (BER), and suppress interference effectively. …”
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Numerical insights into enhanced heat transfer mechanisms in TiO2-Au ethylene glycol nanofluids within Darcy porous media using fractional calculus by Mumtaz Khan, Dianchen Lu, Mudassar Imran, Muhammad Shoaib Anwar

“…To confirm the validity of our approach, we conducted an error analysis by comparing the solutions with exact solutions to verify the accuracy of our results. …”
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Energy Consumption Modeling and Flight Time Analysis of Micro Drones by Nusin Akram, Mina Khoshrangbaf, Moharram Challenger, Orhan Dagdeviren

“…Autonomous aerial vehicles have emerged as revolutionary technology with a wide range of applications in different areas. One of the interesting drone types is miniature or lightweight micro drones which have palm-size small dimensions. …”
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A novel pressure control method for nonlinear shell-and-tube steam condenser system via electric eel foraging optimizer by Serdar Ekinci, Cebrail Turkeri, Davut Izci, Laith Abualigah, Mohit Bajaj, Vojtech Blazek, Lukas Prokop

“…Simulation results confirm that EEFO reduces settling time by 22.7%, overshoot by 78.7%, steady-state error by three orders of magnitude, and ITAE by 81.2% compared to metaheuristic based methods. …”
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Predicting strength in polypropylene fiber reinforced rubberized concrete using symbolic regression AI techniques by Ahmed A. Alawi Al-Naghi, Kinza Aamir, Muhammad Nasir Amin, Bawar Iftikhar, Kashif Mehmood, Muhammad Tahir Qadir

“…Among the two, the MEP model demonstrated stronger predictive capability, achieving a coefficient of determination of 0.90 and a mean absolute error of 3.83 MPa. Analysis using sensitivity techniques and Shapley Additive exPlanations values further identified superplasticizer, cement, and crumb rubber as the most critical variables influencing strength outcomes. …”
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Audio Watermarking Algorithm Against Speed Attack based on Amplitude Rearrangement by WANG Xin, HUANG Ying, NIU Baoning, WU Shiqiang, LAN Fangpeng, GUAN Hu

“…This technology has important applications in copyright protection, content authentication, and secure communication. …”
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Characterization of the Collagen Extraction Manufacturing Process Using Markov Chains and Artificial Neural Networks by Rosa Trasvina-Osorio, Sergio Alonso-Romero, Juan de Anda-Suarez, Valentin Calzada-Ledesma, Javier Yanez-Mendiola, Luis Fernando Villanueva-Jimenez, Erick Rojas-Mancera

“…In the second stage, the predictive model MCMC-ANN presented a mean square error (MSE) of 0.00171, and a standard deviation (SD) of 0.00133. …”
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Food Cooking Process Modeling With Neural Networks by Javier Fananas-Anaya, Gonzalo Lopez-Nicolas, Carlos Sagues, Sergio Llorente

“…FEM models, although being very accurate, have a high computational cost making them unfeasible for real-time applications. To solve this problem, we consider neural networks (NN) trained from FEM simulations. …”
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Enhancing water management in Northern European lowland chalk streams: A parsimonious, high-resolution hydrological model using groundwater level as a proxy for baseflow by Thomas Homan, Nicholas J.K. Howden, Ruth Barden, Barbara Kasprzyk-Hordern, Jan Hofman

“…Due to its simplicity and few parameters to calibrate, this modelling approach has broad applicability in lowland permeable catchments. Management implications include expeditious investigations of high-resolution freshwater quality responses to pollution and informing abstraction limits to sustain robust ecological conditions.…”
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Data-Driven Battery Remaining Life Prediction Based on ResNet with GA Optimization by Jixiang Zhou, Weijian Huang, Haiyan Dai, Chuang Wang, Yuhua Zhong

“…In order to reduce the usage of the dataset, only the first 100 cycles of the battery data were used, and the prediction error was about 9%. Secondly, the deep feature extraction capability of ResNet is utilized to effectively capture the complex patterns and subtle changes during battery decline to alleviate the problem of gradient disappearance. …”
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Adsorption Performance of La(III) and Y(III) on Orange Peel: Impact of Experimental Variables, Isotherms, and Kinetics by Li Liu, Yunzhang Rao, Changshun Tian, Tao Huang, Jiacheng Lu, Meidao Zhang, Min Han

“…Thus, natural orange peel as a recyclable biosorbent has potential economic and applicative benefits to remove La(III) and Y(III) from aqueous solutions.…”
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Neural-enhanced motion-to-EMG: refining simulated muscle activity from musculoskeletal models using a Seq2Seq approach by Tatsuya Teramae, Takamitsu Matsubara, Takamitsu Matsubara, Tomoyuki Noda, Jun Morimoto, Jun Morimoto

“…These findings demonstrate the potential of the NEM2E framework to refine OpenSim-generated muscle activity estimates and advance personalized applications in muscle activity analysis.…”
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Development and Psychometric Properties of a Scale of Teachers’ Coping Strategies Towards the Evaluation of Performance in Public Schools by Jocabeth Nohemi Chambilla-Apaza, Ailyn Yicela Merchan-Fuentes, Denis Frank Cunza-Aranzábal, Carlos D. Abanto-Ramírez

“…Internal reliability was high for the full scale and dimensions (α and ω > 0.8), indicating that it was free of random error, yielding the same results across multiple applications for the same sample. …”
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