Fast 2D forward modeling of electromagnetic propagation well logs using finite element method and data-driven deep learning by A.M. Petrov, A.R. Leonenko, K.N. Danilovskiy, O.V. Nechaev

“…The proposed algorithm achieves a remarkable enhancement in performance, being up to 3000 times faster than the finite element method alone when utilizing a GPU. …”
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Heterogeneity-aware device selection for efficient federated edge learning by Yiran Shi, Jieyan Nie, Xingwei Li, Hui Li

“…To address these issues, this paper proposes a novel Quality-aware online Device Selection (QDS) algorithm. The QDS algorithm leverages a greedy selection method that guarantees the deadline restrictions and reflects upon their historical performance metrics, as indicated by their loss function values from preceding training rounds. …”
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Remote Target High-Precision Global Geolocalization of UAV Based on Multimodal Visual Servo by Xuyang Zhou, Ruofei He, Wei Jia, Hongjuan Liu, Yuanchao Ma, Wei Sun

“…We design a step-convergent target geolocation optimization algorithm. By adjusting the step size and the scale factor of the cost function, we achieve fast accuracy convergence for different UAV reconnaissance modes, while maintaining the geolocation accuracy without divergence even when the laser ranging sensor is turned off for a short period. …”
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Pseudolite Self-Interference Cancellation Without Additional GNSS Signal Distortion by Lichao Gao, Jin He, Yuanxin Wu, Wenxian Yu

“…The simulation test results show that the algorithm can filter self-interference without additional distortion of the satellite navigation signals. …”
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Longitudinal voice monitoring in a decentralized Bring Your Own Device trial for respiratory illness detection by Mar Santamaria, Yiorgos Christakis, Charmaine Demanuele, Yao Zhang, Pirinka Georgiev Tuttle, Fahimeh Mamashli, Jiawei Bai, Rogier Landman, Kara Chappie, Stefan Kell, John G. Samuelsson, Kisha Talbert, Leonardo Seoane, W. Mark Roberts, Edmond Kato Kabagambe, Joseph Capelouto, Paul Wacnik, Jessica Selig, Lukas Adamowicz, Sheraz Khan, Robert J. Mather

“…Algorithm testing on independent cohorts demonstrated that the algorithm’s sensitivity increased as symptoms increased, while specificity remained consistent. …”
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Increasing Neural-Based Pedestrian Detectors’ Robustness to Adversarial Patch Attacks Using Anomaly Localization by Olga Ilina, Maxim Tereshonok, Vadim Ziyadinov

“…The proposed method, based on anomaly localization, demonstrates high resistance to adversarial patch attacks while maintaining the high quality of object detection. …”
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Adversarial Range Gate Pull-Off Jamming Against Tracking Radar by Yuanhang Wang, Yi Han, Yi Jiang

“…The PSO-ER algorithm searches for optimal jamming strategies while utilizing a localized simulation of the tracking radar to evaluate the effectiveness of candidate jamming strategies. …”
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On-Board Content Caching With Dynamic Cache Reconfiguration in Multi-Layer Satellite Edge Networks by Haftay Gebreslasie Abreha, Ilora Maity, Houcine Chougrani, Christos Politis, Symeon Chatzinotas

“…We employ a greedy algorithm for an initial and fast solution for caching contents and enhance it with a Genetic Algorithm (GA)-based approach. …”
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Continuous and Unconstrained Tremor Monitoring in Parkinson’s Disease Using Supervised Machine Learning and Wearable Sensors by Fernando Rodriguez, Philipp Krauss, Jonas Kluckert, Franziska Ryser, Lennart Stieglitz, Christian Baumann, Roger Gassert, Lukas Imbach, Oliver Bichsel

“…We developed and implemented a supervised machine learning algorithm, trained and tested on tremor scores. We evaluated the algorithm on a 67-hour database comprising sensor data and clinical tremor scores for 24 Parkinson patients at four extremities for periods of about 3 hours. …”
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A decision-theoretic framework for wastewater treatment performance assessment based on a fuzzy parameterized fuzzy hypersoft set approach by Muhammad Haris Saeed, Fatima Razaq, Muhammad Saeed, Muhammad Salman Habib, Seung-June Hwang

“…With proper fuzzy parameterization of each sub-attribute, novel specialized FPFHSS based Technique of Ordered Preference Similar to Ideal Solution (TOPSIS) and Multi-Objective Optimization on the basis of a Ratio Analysis (MULTIMOORA) approaches are developed that provide a versatile analysis in addition to the newly developed algorithm. With these 3 specialized systems, 4 case studies were developed based on 19 pseudo-realistic environmental, social, technical, and economic factors each simulating a different scenario faced by nations highlighting sustainability, technical performance and the environment allowing for informed decision-making while addressing uncertainty making them highly suitable as a computational AI solution for real-data analysis. …”
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Demand-Adapting Charging Strategy for Battery-Swapping Stations by Benjamín Pla, Pau Bares, Andre Aronis, Augusto Perin

“…Battery tests were conducted to assess charging time variability, and traffic density measurements were collected in the city of Valencia across multiple days to provide a realistic scenario, while real-time data of the electricity cost is integrated into the control proposal. …”
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A Machine Learning-Based Computational Methodology for Predicting Acute Respiratory Infections Using Social Media Data by Jose Manuel Ramos-Varela, Juan C. Cuevas-Tello, Daniel E. Noyola

“…The first two stages focuses on identifying the best-performing predictive models, while the third stage includes Natural Language Processing (NLP) algorithms for tweet selection. …”
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Oral cancer detection via Vanilla CNN optimized by improved artificial protozoa optimizer by Yulong Chai, Xiuqing Chai, Lan Zhang, Gang Ye, Fatima Rashid Sheykhahmad

“…Due to its effectiveness in search space exploration while avoiding local optimal points, the IAPO algorithm is chosen to optimize the convolutional neural network. …”
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Machine Learning-Based Computer Vision for Depth Camera-Based Physiotherapy Movement Assessment: A Systematic Review by Yafeng Zhou, Fadilla ’Atyka Nor Rashid, Marizuana Mat Daud, Mohammad Kamrul Hasan, Wangmei Chen

“…Key challenges included limited real-world validation, insufficient dataset diversity, and algorithm generalization issues, while machine learning-based computer vision systems demonstrated effectiveness in movement assessment tasks, further research is needed to address validation in clinical settings and improve algorithm generalization. …”
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Mapping the landscape of machine learning in chronic disease management: A comprehensive bibliometric study by Shiying Shen, Wenhao Qi, Sixie Li, Jianwen Zeng, Xin Liu, Xiaohong Zhu, Chaoqun Dong, Bin Wang, Qian Xu, Shihua Cao

“…Logistic regression (n = 459) remains the most widely used algorithm, while neural networks (n = 183) show promising potential. …”
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Improved Variational Mode Decomposition in Pipeline Leakage Detection at the Oil Gas Chemical Terminals Based on Distributed Optical Fiber Acoustic Sensing System by Hongxuan Xu, Jiancun Zuo, Teng Wang

“…This paper employs a distributed fiber optic sensing system to collect pipeline leakage signals and processes these signals using the traditional variational mode decomposition (VMD) algorithm. While traditional VMD methods require manual parameter setting, which can lead to suboptimal decomposition results if parameters are incorrectly chosen, our proposed method introduces an improved particle swarm optimization algorithm to automatically determine the optimal parameters. …”
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The interpretable machine learning model for depression associated with heavy metals via EMR mining method by Site Xu, Mu Sun

“…The optimal model was selected after parameter tuning with a Genetic Algorithm (GA). To enhance the interpretability of the model’s predictions, we applied SHapley Additive exPlanation (SHAP) and Local Interpretable Model-Agnostic Explanations (LIME) algorithms. …”
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Constipation in Children: Assisting Paediatricians by I. N. Zakharova, N. G Sugyan, I. D. Maykova, I. V. Berezhnaya, I. М. Kolobashkina

“…Only 1.6% of all cases occur due to organic disorders, while the rest are purely functional. The article describes risk factors for juvenile constipation and an algorithm for differential diagnosis of chronic constipation and Hirschprung’s disease. …”
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Performance evaluation of perceptible impulsive noise detection methods based on auditory models by Arda Özdoğru, František Rund, Karel Fliegel

“…We compared the results of eight algorithms, hypothesizing that computationally simpler algorithms could perform as well as more complex ones. …”
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An Improved Crop Disease Identification Method Based on Lightweight Convolutional Neural Network by Tingzhong Wang, Honghao Xu, Yudong Hai, Yutian Cui, Ziyuan Chen

“…In order to improve the training learning rate, Adam optimizer combining momentum algorithm and RMSprop algorithm is used to dynamically adjust the learning rate; the combination of the two algorithms makes the loss function converge to the lowest point faster. …”
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