Machine Learning-Driven Prediction of CO₂ Solubility in Brine: A Hybrid Grey Wolf Optimizer (GWO)-Assisted Gaussian Process Regression (GPR) Approach by Seyed Hossein Hashemi, Farshid Torabi, Paitoon Tontiwachwuthikul

“…This demonstrates superior performance in capturing CO₂ solubility trends. The GWO algorithm effectively tuned the hyperparameters for all kernel configurations, while the ARD capability successfully quantified the influence of key physicochemical parameters on CO₂ solubility. …”
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ANALISIS JENIS BUDIDAYA TEBU MENGGUNAKAN ALGORITMA RANDOM FOREST (STUDI KASUS KECAMATAN TAJINAN, KABUPATEN MALANG) by Muhammad Nurhadi, Prima Widayani, Sandy Budi Wibowo

“…Indonesia's national sugar demand continues to increase, while domestic production is still limited due to the lack of accurate data on the area and type of sugarcane cultivation. …”
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Detection of Crack Sealant in the Pretreatment Process of Hot In-Place Recycling of Asphalt Pavement via Deep Learning Method by Kai Zhao, Tianzhen Liu, Xu Xia, Yongli Zhao

“…This algorithm integrates the RepViT (Representation Learning with Visual Tokens) network to reduce computational complexity while capturing the global context of images. …”
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Optimized Trajectory Tracking for ROVs Using DNN + ENMPC Strategy by Guanghao Yang, Weidong Liu, Le Li, Jingming Xu, Liwei Guo, Kang Zhang

“…In contrast to single-loop model predictive control, the proposed double closed-loop control system operates in two distinct phases: (1) The outer loop controller uses a DNN controller to replace the LMPC controller, overcoming the uncertainties in the kinematic model while reducing the computational burden. (2) The inner loop velocity controller is designed using a nonlinear model predictive control (NMPC) algorithm with its closed-loop stability proven. …”
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Heisenberg Group-Based Digital Signatures for Secure Communications by Najla Althuniyan, Ahmed Alamer, Awais Yousaf, Muhammad Waseem, Sarah Aljohani

“…This paper proposes a new digital signature algorithm that employs the Heisenberg group over a prime field and exploits its structure to provide strong cryptographic properties. …”
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Observation optimization for marine target tracking by airborne and maritime unmanned platforms cooperation using adaptive enhanced dung beetle optimization by Qiuyang Dai, Faxing Lu, Haoran Shi, Junfei Xu, Jianjing Qu

“…To address these limitations, this paper proposes a heterogeneous unmanned platform cooperative observation optimization method based on Adaptive Enhanced Dung Beetle Optimization (AEDBO) algorithm. First, we derive optimal observation configurations for the aerial unmanned platform, maritime cooperative unmanned platform, and targets under azimuth systematic error impacts using an attitude correction algorithm. …”
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Optimized YOLOv8 framework for intelligent rockfall detection on mountain roads by Peng Peng, Langchao Gao, Jiachun Li, Hongzhen Zhang

“…To enable efficient detection, this study proposes a rockfall detection system based on embedded technology and an improved Yolov8 algorithm, termed Yolov8-GCB. The algorithm enhances detection performance through the following optimizations: (1) integrating a lightweight DeepLabv3+ road segmentation module at the input stage to generate mask images, which effectively exclude non-road regions from interference; (2) replacing Conv convolution units in the backbone network with Ghost convolution units, significantly reducing model parameters and computational cost while improving inference speed; (3) introducing the CPCA (Channel Priori Convolution Attention) mechanism to strengthen the feature extraction capability for targets with diverse shapes; and (4) incorporating skip connections and weighted fusion in the Neck feature extraction network to enhance multi-scale object detection. …”
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Information-Driven Model Predictive Control With Adaptive Partitioning for Energy Optimization in Automated Electric Vehicles by Shahriar Shahram, Yaser P. Fallah

“…Results confirm that our algorithm effectively maintains desired speed following and distance coverage under varying packet error rates (PERs), ensuring safe and efficient operation while achieving a balanced trade-off between significant energy savings and acceptable passenger comfort.…”
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Kinematic Optimization of a Flexible Wing Undergoing Flapping and Pitching by Yue Wu, Changchuan Xie, Yang Meng, Chao Yang

“…In addition, the optimization algorithm maximizes the thrust efficiency while satisfying the required lift. …”
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Enhancing classification of a large lower-limb motor imagery EEG dataset for BCI in knee pain patients by Chongwen Zuo, Yi Yin, Haochong Wang, Zhiyang Zheng, Xiaoyan Ma, Yuan Yang, Jue Wang, Shan Wang, Zi-gang Huang, Chaoqun Ye

“…Traditional decoding algorithms achieved accuracies of 51.43%, 55.71%, and 76.21%, while the proposed OTFWRGD algorithm reached an average accuracy of 86.41%. …”
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Using Graph Neural Networks in Reinforcement Learning With Application to Monte Carlo Simulations in Power System Reliability Analysis by Oystein Rognes Solheim, Boye Annfelt Hoverstad, Magnus Korpas

“…For the actor part of this architecture, we have implemented both a deterministic agent being a variant of the Twin Delayed DDPG-algorithm, and a stochastic agent with similarities to the Soft Actor Critic-algorithm. …”
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A Multi-Objective PSO-GWO Approach for Smart Grid Reconfiguration with Renewable Energy and Electric Vehicles by Tung Linh Nguyen, Quynh Anh Nguyen

“…Distribution network reconfiguration emerges as a pivotal strategy to mitigate power losses, facilitate the seamless assimilation of renewable generation, and regulate the charging and discharging dynamics of EVs, thereby constituting a critical endeavor in modern electrical engineering. While the Particle Swarm Optimization algorithm is renowned for its rapid convergence and effective exploitation of solution spaces, its capacity to thoroughly explore complex search domains remains limited, particularly in multifaceted optimization challenges. …”
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Tensor-Based Efficient Federated Reinforcement Learning for Cyber-Physical-Social Intelligence by Xin Nie, Laurence T. Yang, Fulan Fan, Zecan Yang

“…By leveraging tensor to model state-action values and employing tensor decomposition techniques for dimensionality reduction, this method effectively reduces model parameters and communication overhead while maintaining strong interpretability, accelerates algorithm convergence speed. …”
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Towards Optimizing the Downlink Transmit Power in UAV-Integrated IRS Wireless Systems by Ali Reda, Tamer Mekkawy, Ashraf Mahran

“…In interference scenarios and with different numbers of IRS meta-atoms, the proposed algorithm achieves a power reduction of approximately 8 and 13 dBm, while maintaining the same required signal-to-interference-plus-noise ratio. …”
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Bats of a feather: Range characteristics and wing morphology predict phylogeographic breaks in volant vertebrates by Sydney K. Decker, Kaiya L. Provost, Bryan C. Carstens

“…In bats, phylogeographic breaks are concentrated in biodiversity hotspots while breaks estimated in bird species are more widespread across temperate and tropical zones. …”
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AI based data-driven point cloud optimization strategy in cloud computing framework for improving rendering performance of virtual city scenes by Cao Zhongda

“…Comparison of the proposed method and model of the study revealed that the F1 value and accuracy of the proposed algorithm was 0.87 and 93.9% respectively, which is better than the comparison algorithm. …”
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Enhancing Pose Estimation Using Multiple Graphical Markers with Spatial and Temporal Outlier Detection by Doyoung Kim, Jae Hwan Bong, Seongkyun Jeong

“…Our approach incorporates two key mechanisms: spatial consistency verification to detect invalid markers within the marker array, and temporal stability analysis to identify and exclude outlier measurements. The algorithm enhances pose estimation accuracy by averaging measurements from valid markers while preventing any single marker from dominating the estimation process. …”
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Optimization of Electric Vehicle Charging and Discharging Strategies Considering Battery Health State: A Safe Reinforcement Learning Approach by Shuifu Gu, Kejun Qian, Yongbiao Yang

“…The algorithm filters out strategies that violate constraints by introducing a logarithmic barrier function. …”
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Optimizing ML models for cybercrime detection: balancing performance, energy consumption, and carbon footprint through multi-objective optimization by Romil Rawat

“…The research utilizes the Non-Dominated Sorting Genetic Algorithm II (NSGA-II), a multi-objective evolutionary algorithm (MOEA), to reduce data dimensionality and identify key features for traffic analysis related to global human trafficking (HTr). …”
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libBICOS – An Open Source GPU-Accelerated Library implementing BInary COrrespondence Search for 3D Reconstruction by C. Liebender, M. Bleier, A. Nüchter

“…Our GPU-accelerated implementation reduces the latency of disparity computation using 7MP images on modern hardware down to 20 milliseconds. Based on the algorithm introduced by Dietrich et al. (2019), we extend their approach by increasing the descriptor size while augmenting postprocessing to increase its applicability on other types of pattern projections. …”
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