Multi-photon neuron embedded bionic skin for high-precision complex texture and object reconstruction perception research by Hongyu Zhou, Chao Zhang, Hengchang Nong, Junjie Weng, Dongying Wang, Yang Yu, Jianfa Zhang, Chaofan Zhang, Jinran Yu, Zhaojian Zhang, Huan Chen, Zhenrong Zhang, Junbo Yang

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The Optimization of PID Controller and Color Filter Parameters with a Genetic Algorithm for Pineapple Tracking Using an ROS2 and MicroROS-Based Robotic Head by Carolina Maldonado-Mendez, Sergio Fabian Ruiz-Paz, Isaac Machorro-Cano, Antonio Marin-Hernandez, Sergio Hernandez-Mendez

“…A multivariate Gaussian function is employed to segment objects with complex color patterns, such as the body of a pineapple. The parameters of both the PID controller and the multivariate Gaussian filter are optimized using a genetic algorithm. …”
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Codebook Design for Parallel Dynamic Subarrays in Millimeter Wave Massive MIMO Systems by Qi Li, Fu-Chun Zheng, Ke Xu, Lianming Li

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Vessel Trajectory Data Mining: A Review by Alexandros Troupiotis-Kapeliaris, Christos Kastrisios, Dimitris Zissis

“…This survey offers a comprehensive review of contemporary research in trajectory data mining, with a particular focus on maritime applications. …”
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Enhancing Smart and Zero-Carbon Cities Through a Hybrid CNN-LSTM Algorithm for Sustainable AI-Driven Solar Power Forecasting (SAI-SPF) by Haytham Elmousalami, Felix Kin Peng Hui, Aljawharah A. Alnaser

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A comparative study of convolutional neural networks and traditional feature extraction techniques for adulteration detection in ground beef by Leila Bahmani, Saied Minaei, Alireza Mahdavian, Ahmad Banakar, Mahmoud Soltani Firouz

“…In order to identify the most appropriate feature extraction algorithm and classify samples having various levels of adulteration, Local Binary Pattern (LBP), Gray Level Co-occurrence Matrixes (GLCM) and Gabor filter were compared. …”
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Quantum Snowflake Algorithm (QSA): A Snowflake-Inspired, Quantum-Driven Metaheuristic for Large-Scale Continuous and Discrete Optimization with Application to the Traveling Salesma... by Zeki Oralhan, Burcu Oralhan

“…The Quantum Snowflake Algorithm (QSA) is a novel metaheuristic for both continuous and discrete optimization problems, combining collision-based diversity, quantum-inspired tunneling, superposition-based partial solution sharing, and local refinement steps. …”
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The SADRA Algorithm as a Framework for Sustainable Innovation: A Review of Case Studies on 3D‐Printed Reinforced Concrete Beam and Fiber‐Reinforced Concrete by Mohammad Hematibahar, Makhmud Kharun, Abhijit Bhowmik, Valentin Romanovski

“…ABSTRACT The absence of a structured and evolutionary approach in civil engineering research often leads to fragmented innovations and limited progress. …”
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Chiller power consumption forecasting for commercial building based on hybrid convolution neural networks-long short-term memory model with barnacles mating optimizer by Mohd Herwan Sulaiman, Zuriani Mustaffa

“…The study compares the proposed CNN-LSTM-BMO against other metaheuristic optimization algorithms, including Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), and Differential Evolution (DE). …”
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A Multi-Area Software-Defined Vehicular Network Control Plane Deployment Mechanism Oriented to Traffic Prediction by Hao Li, Hongming Li, Yuqing Ji, Ziwei Wang

“…A comprehensive comparison of various machine learning and deep learning algorithms is then conducted to evaluate their efficacy in forecasting SDVN traffic patterns, which is crucial for system efficiency. …”
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Study on Satisfaction Evaluation of Ecotourism Through Advanced Network Text Mining by Jia Gao, Leong Mow Gooi, Kim Mee Chong, Xiang Lyu, Jin Zhang

“…The primary objective was to enhance the analysis of tourist feedback by leveraging Long Short-Term Memory (LSTM) networks and Genetic Algorithms (GA). Text mining was conducted using LSTM to capture and analyze sequential patterns in unstructured feedback data, revealing insights into visitor satisfaction levels over different phases of their trips. …”
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Research on Network Handover Based on User Movement Prediction in Visible Light Communication and Wi-Fi Heterogeneous Networks by Chenghu Ke, Mengfan Wang, Huanhuan Qin, Xizheng Ke

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Distinct brain atrophy progression subtypes underlie phenoconversion in isolated REM sleep behaviour disorderResearch in context by Stephen Joza, Aline Delva, Christina Tremblay, Andrew Vo, Marie Filiatrault, Max Tweedale, Jean-François Gagnon, Ronald B. Postuma, Alain Dagher, Johannes Klein, Michele Hu, Petr Dusek, Stanislav Marecek, Zsoka Varga, John-Paul Taylor, John T. O'Brien, Michael Firbank, Alan Thomas, Paul C. Donaghy, Stéphane Lehéricy, Marie Vidailhet, Jean-Christophe Corvol, ICEBERG Study Group, Richard Camicioli, Howard Chertkow, Simon Lewis, Elie Matar, Kaylena A. Ehgoetz Martens, Lachlan Churchill, Michael Sommerauer, Sinah Röttgen, Per Borghammer, Karoline Knudsen, Allan K. Hansen, Dario Arnaldi, Beatrice Orso, Pietro Mattioli, Luca Roccatagliata, Oury Monchi, Shady Rahayel, Isabelle Arnulf, Samir Bekadar, Eve Benchetrit, Alexis Brice, Vanessa Brochard, Alizé Chalançon, Benoit Colsch, Florence Cormier-Dequaire, Jean-Christophe Corvol, Virginie Czernecki, Bertrand Degos, Cécile Delorme, Pauline Dodet, Carole Dongmo-Kenfack, Marie-Odile Habert, Farid Ichou, Jonas Ihle, Cécile Galléa, Rahul Gaurav, Marie-Alexandrine Glachant, Manon Gomes, David Grabli, Elodie Hainque, Laetitia Jeancolas, Christelle Laganot, Stéphane Lehéricy, Suzanne Lesage, Smaranda Leu-Semenescu, Richard Levy, Valentine Maheo, Graziella Mangone, Louise Laure Mariani, Aurelie Méneret, Poornima Menon, Fanny Mochel, Vincent Perlbarg, Dijana Petrovska, Fanny Pineau, Nadya Pyatigorskaya, Sophie Rivaud-Pechoux, Emmanuel Roze, Sara Sambin, Julie Socha, Arthur Tenenhaus, Romain Valabregue, Marie Vidailhet, Lydia Yahia-Cherif

“…The unsupervised machine learning algorithm, Subtype and Stage Inference (SuStaIn), was used to reconstruct spatiotemporal patterns of brain atrophy progression. …”
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Using modern clustering techniques for parametric fault diagnostics of turbofan engines by I. J. Buraimah

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Research progress in predicting the conversion from mild cognitive impairment to Alzheimer’s disease via multimodal MRI and artificial intelligence by Min Ai, Yu Liu, Dan Liu, Chengxi Yan, Xia Wang, Xun Chen

“…Therefore, this paper systematically reviews the research progress of multimodal MRI techniques in capturing brain changes related to MCI conversion, as well as the practical experience of AI algorithms in constructing efficient prediction models, analyses the current technical challenges faced by the research, and discusses future directions, with the goal of providing a scientific reference for the early and accurate prediction of MCI conversion and the formulation of intervention strategies.…”
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MECHATRONIC SYSTEM OF GRAIN COMBINE ADAPTIVE DRIVING CONTROL by Dmitry Yakovlevich Parshin, Denis Gennadyevich Shevchuk

“…The basic external actions on the grain combine mechatronic control system, and their effect on the motion pattern and the production process are considered. …”
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The novel Vogel's approximation method integrated with a random forest algorithm in the vibration analysis of a two-directional functionally graded taper porous beam: Assessment by Ravikiran Chintalapudi, Geetha Narayanan Kannaiyan, Bridjesh Pappula, Seshibe Makgato

“…This approach adopts a rectangular cross-section in order to deal with the challenges related to fluctuating material characteristics and geometric tapering in both thickness and width dimensions. The research employs a novel approach that merges Vogel's approximation technique with the Random Forest algorithm, an approach that has not been used in analyzing structural vibrations, establish boundary conditions and solve equations of motion. …”
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Analysis of Customer Power Consumption Behavior Based on DPSO-Kmeans under the Ubiquitous Power Internet of Things by WANG Ying, XIANG Wen, ZHANG Qun, GAO Xiuyun

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Evaluating the Vulnerability of Hiding Techniques in Cyber-Physical Systems Against Deep Learning-Based Side-Channel Attacks by Seungun Park, Aria Seo, Muyoung Cheong, Hyunsu Kim, JaeCheol Kim, Yunsik Son

“…Despite the added complexity, DL models effectively distinguished real and dummy traces, highlighting limitations in existing hiding techniques. (4) Conclusions: These findings highlight the need for adaptive countermeasures against DL-SCAs. Future research should explore dynamic obfuscation techniques, adversarial training, and comprehensive evaluations of broader cryptographic algorithms. …”
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Research on Site Selection and Capacity Determination of Electric Vehicle Public Charging Stations by Integrating K-Means++ and Improved RODDPSO by B. Huang, Z. Wang, J. Chen, B. Zhou, Y. Zhu, Y. Liu

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