Accelerating Wound Healing Through Deep Reinforcement Learning: A Data-Driven Approach to Optimal Treatment by Fan Lu, Ksenia Zlobina, Prabhat Baniya, Houpu Li, Nicholas Rondoni, Narges Asefifeyzabadi, Wan Shen Hee, Maryam Tebyani, Kaelan Schorger, Celeste Franco, Michelle Bagood, Mircea Teodorescu, Marco Rolandi, Rivkah Isseroff, Marcella Gomez

“…However, due to the complexities of human–drug interactions and a lack of predictive models, it is challenging to determine how one should adjust drug dosage to achieve the desired biological response. …”
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Improved Smart Power Socket for Monitoring and Controlling Electrical Home Appliances by Eslam Al-Hassan, Hussain Shareef, Md. Mainul Islam, Addy Wahyudie, Atef Amin Abdrabou

“…A 24-min implementation of the proposed energy management algorithm shows a reduction of 0.811 kWmin (0.0134 kWh) in energy usage after the use of the smart sockets as load controllers. …”
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Identification of water sources of mine water bursts based on the FPS-DT model by Kaide Liu, Yu xia, Xiaolong Li, Chaowei Sun, Wenping Yue, Qiyu Wang, Songxin Zhao, Shufeng Chen

“…The fuzzy C-means (FCM) clustering method is employed to classify water sample data, followed by principal component analysis (PCA) for dimensionality reduction to extract key features. The SMOTE algorithm is then applied to address the issue of class imbalance. …”
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Improved UAV Target Detection Model for RT-DETR by Yong He, Yufan Pang, Guolin Ou, Renfeng Xiao, Yifan Tang

“…In light of the shortcomings pertaining to UAV small target detection, the detection of complex scenes, and the detection of multi-scale targets, a time-frequency dual-domain feature extraction algorithm, TF-DETR, has been proposed. This algorithm has been optimized for RT-DETR.Firstly, a time-frequency domain feature extraction module, TF-CSPNet, has been introduced into the backbone network. …”
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Helicopter Turboshaft Engines’ Neural Network System for Monitoring Sensor Failures by Serhii Vladov, Łukasz Ścisło, Nina Szczepanik-Ścisło, Anatoliy Sachenko, Tomasz Perzyński, Viktor Vasylenko, Victoria Vysotska

“…Modules such as SensorFailClean and SensorFailNorm implement adaptive discretization and quantisation techniques, enhancing the data input quality and contributing to more accurate predictions. The developed system demonstrated anomaly detection accuracy at 99.327% after 200 training epochs, with a reduction in loss from 2.5 to 0.5%, indicating stability in anomaly processing. …”
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Evaluation of AI-Powered Routine Screening of Clinically Acquired cMRIs for Incidental Intracranial Aneurysms by Christina Carina Schmidt, Robert Stahl, Franziska Mueller, Thomas David Fischer, Robert Forbrig, Christian Brem, Hakan Isik, Klaus Seelos, Niklas Thon, Sophia Stoecklein, Thomas Liebig, Johannes Rueckel

“…<b>Results</b>: The algorithm demonstrates high sensitivities (100% for findings >4 mm in diameter), a 17.8% MRA alert rate and positive predictive values of 11.5–43.8% (depending on whether inconclusive findings are considered or not). …”
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Design and Development of an Omnidirectional Three-Wheeled Industrial Mobile Robot Platform by Johnny J. Yepez-Figueroa, Juan G. Victores, Edwin Daniel Oña, Carlos Balaguer, Alberto Jardón

“…In addition, a control algorithm and a command device ensure precise and versatile operation. …”
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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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L2R-MLP: a multilabel classification scheme for the detection of DNS tunneling by Emmanuel Oluwatobi Asani, Mojiire Oluwaseun Ayoola, Emmanuel Tunbosun Aderemi, Victoria Oluwaseyi Adedayo-Ajayi, Joyce A. Ayoola, Oluwatobi Noah Akande, Jide Kehinde Adeniyi, Oluwambo Tolulope Olowe

“…This highlights the effectiveness of L2 regularization in improving predictive capabilities and model generalization for unseen instances.…”
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Probabilistic daily runoff forecasting in high-altitude cold regions using a hybrid model combining DBO and transformer variants by Qiying Yu, Wenzhong Li, Yungang Bai, Zhenlin Lu, Yingying Xu, Chengshuai Liu, Lu Tian, Chen Shi, Biao Cao, Tianning Xie, Jianghui Zhang, Caihong Hu

“…Across various forecast periods, the model’s NSE values are 6.9–26.9 % higher than those of the TCN and Transformer models, offering more reliable short-term and long-term predictions. Furthermore, the Bootstrap algorithm’s probabilistic approach provides valuable insights into forecast uncertainty, a crucial feature for managing water resources and mitigating flood risks in high-altitude cold regions with complex hydrological dynamics.…”
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Optimizing Distribution Grid Performance through Electric Vehicle Integration and Stochastic Modeling in Extreme Weather Conditions by A. Niknami, M. Askari, M. Amirahmadi, M. Babaeinik

“…Monte Carlo simulation is employed to model uncertainties, while a multi-objective optimization algorithm is used to solve the problem. This algorithm aims to maximize the profits of network operators and the private sector while minimizing unsupplied energy and its associated penalties. …”
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A Framework for Segmentation and Classification of Cervical Cells Under Long-tailed Distribution by YANG Xiao na, LI Chao wei, SHAO Hui li, HE Yong jun

“…Experiments show that the segmentation algorithm in this paper improves 3. 52% compared with the original method, and the classification algorithm that incorporates all features improves 1. 2% . …”
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UAV-based inspection of wind turbine blade surface defects detection technology by TAN Xingguo, ZHANG Gaoming

“…According to the characteristics of images collected by UAV, this paper adopts the weighted average method to realize gray processing, and then, the median filtering is applied to realize image noise reduction; the image enhancement is realized by CLAHE algorithm, which makes the details of target area and defect more clear and complete, and improves the detection efficiency. …”
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Research on Data-Driven Optimal Operation of Slurry Circulation Pump by Zunyi XU, Wenhui LIU, Xuran ZHANG, Haiyan ZHANG

“…Then by using the genetic algorithm for parameter optimization and the real-time operation data as input, to implement the recommended operations of the slurry circulation pump, the optimization of its operation can be achieved. …”
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Camera Absolute Pose Estimation Using Hierarchical Attention in Multi-Scene by Xinhua Lu, Jingui Miao, Qingji Xue, Hui Wan, Hao Zhang

“…Compared to the baseline algorithm PoseNet, our algorithm has achieved a 41.1% reduction in translation error and a 61.1% decrease in rotation error, demonstrating superior performance in multi-scene absolute camera pose regression.…”
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Multisensor Fused Fault Diagnosis for Rotation Machinery Based on Supervised Second-Order Tensor Locality Preserving Projection and Weighted k-Nearest Neighbor Classifier under Ass... by Fen Wei, Gang Wang, Bingyin Ren, Jianghua Ge, Yaping Wang

“…Second-order tensor representation of multisensor fused conditional features is employed to replace the prevailing vector description of features from a single sensor. Then, an SSTLPP algorithm under AMDM (SSTLPP-AMDM) is presented to realize dimensional reduction of original high-dimensional feature tensor. …”
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Color Dominance-Based Polynomial Optimization Segmentation for Identifying Tomato Leaves and Fruits by Juan Pablo Guerra Ibarra, Francisco Javier Cuevas de la Rosa, Alicia Linares Ramirez

“…This results in an 80% reduction in computation time.…”
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Multi-Objective Optimization of Pressure-Reducing Valves Operation in Extreme Water Consumption Scenarios (Case Study: Najaf Abad Urban Water Distribution Network) by Seyed Pedram Jazayeri Farsani, Ramtin Moeini

“…The multi-objective optimization problem was solved using the NSGA-II algorithm under two extreme water consumption scenarios-maximum and minimum water withdrawal during warm and cold seasons. …”
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Optimizing Medical IoT Disaster Management with Data Compression by Nunudzai Mrewa, Athirah Mohd Ramly, Angela Amphawan, Tse Kian Neo

“…Comparative tests highlight the algorithm's prowess, achieving savings of 72% and compression factor of 3.53. …”
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Multi-Energy Microgrid Data-Driven Distributionally Robust Optimization Dispatch Considering Uncertainty Correlation by LI Jiawei, SUN Qinghe, WANG Qiong, YE Yujian, HU Heng, ZHANG Xi

“…[Results] Case simulations demonstrate that the proposed distributionally robust model effectively eliminates unrealistic distributions in the ambiguity set，resulting in an 8.16% reduction in out-of-sample costs. The proposed sample-pruning algorithm further reduces the out-of-sample costs by 3.33%. …”
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