Fibre-orientation-driven defect probability mapping for machining-induced delamination and burr minimisation in carbon fibre-reinforced polymer (CFRP) composites by Norbert Geier

“…Then, recursive convolution yielded a matrix whose minima identified the optimal hole position. First, edge trimming experiments were conducted to determine the arguments (critical fibre cutting angle and its range) of the developed algorithm. …”
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Energy and Reserve Scheduling of Distribution Network in Presence of Electric Vehicle Aggregators: A Decentralized Approach by Atena Tazikeh Lemeski, Reza Ebrahimi, Alireza Zakariazadeh, Keyvan Firuzi

“…The problem is solved using the fast alternating direction method of multipliers (FADMMs) which is well suited for independent-objective optimizations with a fast convergence rate. The proposed distributed algorithm is tested and evaluated on a standard distribution network consisting of AGG and DGs. …”
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The Path Planning Problem of Robotic Delivery in Multi-Floor Hotel Environments by Linghui Han, Junzhe Ding, Songtao Liu, Meng Meng

“…To solve this NP-hard problem, an Adaptive Large Neighborhood Search (ALNS) algorithm is proposed. The effectiveness of the algorithm is validated through comparative experiments with Gurobi, demonstrating its ability to handle complex three-dimensional delivery scenarios. …”
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Incremental Reinforcement Learning for Portfolio Optimisation by Refiloe Shabe, Andries Engelbrecht, Kian Anderson

“…To address this, an incremental recurrent PPO is developed, leveraging incremental learning to adapt to concept drift triggered by the pandemic. This enhanced algorithm not only learns from ongoing market data but also consistently identifies optimal portfolios despite significant market volatility, offering a robust tool for real-time financial decision-making.…”
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Research on Status Assessment and Operation and Maintenance of Electric Vehicle DC Charging Stations Based on XGboost by Hualiang Fang, Jiaqi Liao, Shuo Huang, Maojie Zhang

“…To address the effective operation and maintenance of charging stations, a method based on the XGBoost algorithm for electric vehicle DC charging stations is proposed. …”
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An Analog Sensor Signal Processing Method Susceptible to Anthropogenic Noise Based on Improved Adaptive Singular Spectrum Analysis by Zhengyang Gao, Shuangchao Ge, Jie Li, Wentao Huang, Kaiqiang Feng, Chenming Zhang, Chunxing Zhang, Jiaxin Sun

“…The singular spectrum decomposition (SSA) algorithm, while widely used, faces challenges such as the difficulty of determining the number of decomposition layers, requiring iterative adjustments that reduce precision and increase processing time. …”
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Sustainable Innovation: Harnessing AI and Living Intelligence to Transform Higher Education by Hesham Mohamed Allam, Benjamin Gyamfi, Ban AlOmar

“…These advancements also make education more inclusive, helping to bridge accessibility gaps for underserved communities. However, while AI has the potential to improve education significantly, it also introduces challenges, such as ethical concerns, data privacy risks, and algorithmic bias. …”
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Configuring Transmission Thresholds in IIoT Alarm Scenarios for Energy-Efficient Event Reporting by David E. Ruiz-Guirola, Onel L. A. Lopez, Samuel Montejo-Sanchez

“…We propose a threshold-based transmission-decision policy based on the sensing quality and the network spatial deployment. We optimize the transmission thresholds using several approaches such as successive convex approximation, block coordinate descent methods, Voronoi diagrams, explainable machine learning, algorithms based on natural selection and social behavior, and Q-learning. …”
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Artificial Intelligence Approaches to Energy Management in HVAC Systems: A Systematic Review by Seyed Abolfazl Aghili, Amin Haji Mohammad Rezaei, Mohammadsoroush Tafazzoli, Mostafa Khanzadi, Morteza Rahbar

“…Nevertheless, the effective implementation of artificial intelligence (AI)-based methods to optimize energy efficiency while ensuring occupant comfort in multifarious settings remains to be fully realized. …”
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Analysis of injured-skin SS-OCT images based on combined attention UNet. by Xiyu Zheng, Jingyuan Wu, Qiong Ma, Diantao Luo, Qingyu Cai, Haiyang Sun, Hongxing Kang

“…These models were used to segment the damaged skin regions, followed by a 3D reconstruction method to quantitatively evaluate the volume of skin damage while analyzing changes about laser dose and recovery time.The BM3D algorithm effectively suppressed high-noise components, significantly improving image clarity. …”
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Predicting Trip Duration and Distance in Bike-Sharing Systems Using Dynamic Time Warping by Ahmed Ali, Ahmad Salah, Mahmoud Bekhit, Ahmed Fathalla

“…Accurate prediction of ride duration allows a better estimate of bike availability at stations, while distance predictions assist in maintenance planning based on bike usage patterns. …”
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Damage Identification in Large-Scale Structures Using Time Series Analysis and Improved Sparse Regularization by Huihui Chen, Xiaojing Yuan

“…Compared to the moth-flame optimization (MFO) algorithm and traditional regularization methods, for both noise-free and noise polluted data, the iteration curves illustrate that the proposed method can achieve convergence within about 200 iterations, while the MFO algorithm is always trapped into local optima; meanwhile, the traditional regularization method needs more iterations or even cannot meet the preset tolerance. …”
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Pavement pothole detection system based on deep learning and binocular vision by Tian Guan, Jianyuan Cai, Yu Wang, Wei Yang, Xiaobo Chang, Yi Han

“…Finally, vehicle experiments were conducted to verify the effectiveness of the algorithm in meeting detection requirements while considering long-range perception accuracy. …”
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A novel flexible near-infrared endoscopic device that enables real-time artificial intelligence fluorescence tissue characterization. by Gareth Gallagher, Ra'ed Malallah, Jonathan P Epperlein, Jeffrey Dalli, Niall Hardy, Abhinav Jindal, Pol G MacAonghusa, Ronan A Cahill

“…Jaccard Index comparison of the AI -generated flow regions against manually delineated flow regions resulted in 79% accuracy. While further clinical validation of the AI-NIR polyp classification method is on-going (in the Horizon Europe Awarded CLASSICA project), other use case applications of NIR colonoscopy include simpler perioperative perfusion assessment in patients undergoing colorectal resection and combination with targeted agents in development thus encouraging continuing development and design optimization of this flexible NIR imaging probe to enable clinical and commercial translation.…”
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Low resolution remote sensing object detection with fine grained enhancement and swin transformer by Zhijing Xu, Xin Wang, Kan Huang, Ren Chen

“…Finally, we incorporate the Shape-IoU loss function to optimize bounding box regression, significantly improving small target detection accuracy while maintaining computational efficiency. …”
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Multi-Scale Contextual Coding for Human-Machine Vision of Volumetric Medical Images by Jietao Chen, Weijie Chen, Qianjian Xing, Feng Yu

“…Different from the existing 3D convolutional compression algorithms oriented only for human vision, this paper proposes a Multi-scale Contextual Autoencoder (MCAE) architecture that recurrently incorporates anatomical inter-slice context to optimize the compression of the current slice for both human and machine vision. …”
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Mission Sequence Model and Deep Reinforcement Learning-Based Replanning Method for Multi-Satellite Observation by Peiyan Li, Peixing Cui, Huiquan Wang

“…Both phases are formulated as Markov Decision Processes (MDPs) and optimized using the PPO algorithm. Extensive simulations demonstrate that our method significantly outperforms state-of-the-art approaches, achieving a 15.27% higher request insertion revenue rate and a 3.05% improvement in overall mission revenue rate, while maintaining a 1.17% lower modification rate and achieving faster computational speeds. …”
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Comparison between Logistic Regression and K-Nearest Neighbour Techniques with Application on Thalassemia Patients in Mosul by Mohammed Al jbory, Hutheyfa Taha

“… The experimental results showed that the logistic regression model performed better than the nearest neighbor algorithm with a precision of 96%, recall of 98%, and F1- score of 97% in the thalassemia intermedia category, while it had a precision of 97%, recall of 95%, and F1- score of 96% in the thalassemia major category, indicating that logistic regression performed well in distinguishing between these two categories. it has been shown that logistic regression is more effective than the K-nearest neighbor algorithm in classifying thalassemia patients, especially those with thalassemia major. …”
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Assessing tafenoquine implementation in Brazil: a qualitative evaluation of perceptions of healthcare providers and Plasmodium vivax patients (QualiTRuST Study) by Alicia P. C. Santos, Marcelo A. M. Brito, Ana P. S. Oliveira, Rafaela N. Dávila, Hiran S. S. Gama, Evellyn A. R. T. Silva, Hélio A. Amazonas Jr., Patrícia C. S. Balieiro, Rosilene Rufatto, Penny Grewal Daumerie, Cássio R. L. Peterka, Dhélio Batista Pereira, Marcus V. G. Lacerda, Felipe L. G. Murta

“…The findings underscore the importance of adaptive training to optimize P. vivax radical cure implementation.…”
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Inflammation Biomarker-Driven Vertical Visualization Model for Predicting Long-Term Prognosis in Unstable Angina Pectoris Patients with Angiographically Intermediate Coronary Lesio... by Zhou B, Tan W, Duan S, Wang Y, Bian F, Zhao P, Wang J, Yao Z, Li H, Hu X, Wang J, Liu J

“…Various inflammatory markers are employed in clinical practice to predict patient prognosis and optimize clinical decision-making in the management of ACS. …”
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