Dissipative Structures of the Kuramoto–Sivashinsky Equation by N. A. Kudryashov, P. N. Ryabov, B. A. Petrov

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Mask R-CNN aided fruit surface temperature monitoring algorithm with edge compute enabled internet of things system for automated apple heat stress management by Basavaraj R. Amogi, Rakesh Ranjan, Lav R. Khot

“…This limited CPSS applicability to monitor sunburn of red colored cultivars only and when fruits develop color, typically late growing season. This is a key research gap as recent weather patterns have shown that sunburn can occur during early growing season when fruits are green to yellow. …”
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Analysis of 19.9 million publications from the PubMed/MEDLINE database using artificial intelligence methods: approaches to the generalizations of accumulated data and the phenomen... by I. Yu. Torshin, O. A. Gromova, L. V. Stakhovskaya, N. P. Vanchakova, A. N. Galustyan, Zh. D. Kobalava, T. R. Grishina, A. N. Gromov, I. A. Ilovaiskaya, V. M. Kodentsova, A. G. Kalacheva, O. A. Limanova, V. A. Maksimov, S. I. Malyavskaya, E. V. Mozgovaya, N. I. Tapilskaya, K. V. Rudakov, V. A. Semenov

“…Based on the algorithms, a scale for assessing the sentiment quality of research (β-score) is proposed.Results. …”
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Synthesis of Amplitude-Phase Distribution in Quasiconcave an Antenna Array by M. R. Bibarsov, E. V. Gribanov, D. D. Gabrielyan, D. S. Fedorov, D. S. Fedorov

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An Internal Overvoltage Identification Method for Distribution Network Based on Transfer Learning by Hao XU, Liqiang LIU, Chao LV

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Sensitivity analysis of activity scheduling parameters with a parameter optimization framework by Matheus Moro Zamprogno, Domokos Esztergár-Kiss

“…Throughout the years, in the field of transportation several attempts were made to optimize travelers’ activity chains with different parameters to set, but there is a lack of comprehensive solutions. In this research, the activity chain optimization algorithm is applied, which requires high computational efforts. …”
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Clustering and Interpretability of Residential Electricity Demand Profiles by Sarra Kallel, Manar Amayri, Nizar Bouguila

“…Efficient energy management relies on uncovering meaningful consumption patterns from large-scale electricity load demand profiles. …”
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Research on low earth orbit constellation beam hopping resource scheduling based on multi-agent deep reinforcement learning by ZHANG Chen, XU Yangwei, LI Wanjing, WANG Wei, ZHANG Gengxin

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Etiology and management of urethral calculi: A systematic review of contemporary series by Andrew Morton, Arsalan Tariq, Nigel Dunglison, Rachel Esler, Matthew J. Roberts

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Utilizing LSTM-GRU for IOT-Based Water Level Prediction Using Multi-Variable Rainfall Time Series Data by Indrastanti Ratna Widiasari, Rissal Efendi

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Patterns of care for people presenting to Australian general practice with musculoskeletal complaints based on routinely collected data: protocol for an observational cohort study... by Alexandra Gorelik, Romi Haas, Ljoudmila Busija

“…Previous studies using routinely collected health data for research have not consistently reported the codes and algorithms used to describe the population, exposures, interventions and outcomes in sufficient detail to allow replication. …”
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Impact of a Novel Electronic Medical Record–Integrated Electronic Form (Provider Asthma Assessment Form) and Severe Asthma Algorithm in Primary Care: Single-Center, Pre- and Postob... by Matheson L McFarlane, Alison Morra, Delanya Podgers, David Barber, M Diane Lougheed

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Study on the Evolutionary Characteristics of Spatial and Temporal Patterns and Decoupling Effect of Urban Carbon Emissions in the Yangtze River Delta Region Based on Neural Network... by Xichun Luo, Chaoming Cai, Honghao Zhao

“…To improve the performance of neural network models, the Aquila Optimizer (AO) algorithm is introduced to optimize the hyper-parameter values in the back-propagation (BP) neural network model in this research due to the appealing searching capability of AO over traditional algorithms. …”
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Energy Efficiency in Measurement and Image Reconstruction Processes in Electrical Impedance Tomography by Barbara Stefaniak, Tomasz Rymarczyk, Dariusz Wójcik, Marta Cholewa-Wiktor, Tomasz Cieplak, Zbigniew Orzeł, Janusz Gudowski, Ewa Golec, Michał Oleszek, Marcin Kowalski

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Identification of PRKCQ-AS1 as a Keratinocyte-Derived Exosomal lncRNA That Promotes Th17 Differentiation and IL-17 secretion in Psoriasis Through Bioinformatics, Machine L... by Gao P, Gao X, Lin L, Zhang M, Luo D, Chen C, Li Y, He Y, Liu X, Shi C, Yang R

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Robust zero-watermarking for color images using hybrid deep learning models and encryption by Hager A. Gharib, Noha M. M. Abdelnapi, Khalid M. Hosny

“…Abstract Reliable zero-watermarking is a distortion-free approach to copyright protection, which has been a primary focus of digital watermarking research. Traditional zero-watermarking techniques often struggle to maintain resilience against geometric and signal processing attacks while ensuring high security and imperceptibility. …”
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Research on the correlation between retinal vascular parameters and axial length in children using an AI-based fundus image analysis system. by Chaoyang Zhao, Huilin Li, Ziyou Yuan, Zihan Yang, Tiantian Wang, Yan Wang, Qian Tong, Shaofeng Hao

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Simplifying Field Traversing Efficiency Estimation Using Machine Learning and Geometric Field Indices by Gavriela Asiminari, Lefteris Benos, Dimitrios Kateris, Patrizia Busato, Charisios Achillas, Claus Grøn Sørensen, Simon Pearson, Dionysis Bochtis

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Robust Classification of Intramuscular EMG Signals to Aid the Diagnosis of Neuromuscular Disorders by Shobha Jose, S. Thomas George, M. S. P. Subathra, Vikram Shenoy Handiru, Poornaselvan Kittu Jeevanandam, Umberto Amato, Easter Selvan Suviseshamuthu

“…Finally, the sequence of class labels is fed to the Boyer-Moore majority vote (BMMV) algorithm, which assigns a class to every iEMG signal. …”
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Metaheuristics and Large Language Models Join Forces: Toward an Integrated Optimization Approach by Camilo Chacon Sartori, Christian Blum, Filippo Bistaffa, Guillem Rodriguez Corominas

“…Since the rise of Large Language Models (LLMs) a couple of years ago, researchers in metaheuristics (MHs) have wondered how to use their power in a beneficial way within their algorithms. …”
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