Synthetic data in medicine: Legal and ethical considerations for patient profiling by Maja Nisevic, Dusko Milojevic, Daniela Spajic

“…Synthetic data is increasingly used in healthcare to facilitate privacy-preserving research, algorithm training, and patient profiling. By mimicking the statistical properties of real data without exposing identifiable information, synthetic data promises to resolve tensions between innovation and data protection. …”
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Research on fuzzy proportional–integral–derivative (PID) control of bolt tightening torque based on particle swarm optimization (PSO) by X. Cheng, Z. Guo, J. Ke

“…To enhance the precision of bolt tightening, this paper introduces a particle swarm optimization (PSO) algorithm to optimize a fuzzy proportional–integral–derivative (FPID) controller. …”
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Reinforcement Learning-Based UAV Swarm Fission–Fusion Approach With Real-World Data-Integrated Validation by Xiaorong Zhang, Dacheng Qi, Wenrui Ding, Xinrui Zhang, Qingyi Liu, Yufeng Wang

“…Second, we introduce a reinforcement learning–based fission–fusion confrontation algorithm designed to minimize resource consumption while effectively responding to multiple unknown dynamic disturbances. …”
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Reinforcement-Learning-Based Edge Offloading Orchestration in Computing Continuum by Ioana Ramona Martin, Gabriel Ioan Arcas, Tudor Cioara

“…We have chosen the Deep Q-Learning algorithm and adapted it to our workload offloading problem. …”
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Accurate Extraction of Rural Residential Buildings in Alpine Mountainous Areas by Combining Shadow Processing with FF-SwinT by Guize Luan, Jinxuan Luo, Zuyu Gao, Fei Zhao

“…However, existing deep learning models are hindered by insufficient datasets and suboptimal algorithm structures, resulting in blurred boundaries and inadequate extraction accuracy. …”
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Robust self supervised symmetric nonnegative matrix factorization to the graph clustering by Yi Ru, Michael Gruninger, YangLiu Dou

“…The symmetric factorization ensures the preservation of network structures, while the self-supervised approach allows the model to adaptively improve its clustering performance over successive iterations. …”
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A Geometric Approach to Efficient Modeling and Rendering of Opaque Ice With Directional Air Bubbles by Jong-Hyun Kim

“…As a result, the proposed method achieves approximately three times faster computation speed compared to previous techniques while providing visually enhanced opaque ice shapes in real-time. …”
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Methodology for Using Multi-Temporal Landsat Images to Monitor Urban Growth of Kirkuk Governorate by Tabark Y. Gehad, Nejat Q. Omer, Nada S. Abdulmajeed

“…The Supervised Maximum Likelihood algorithm was utilized to categorize images into urban and non-urban areas, with accuracy rates ranging from 91.25% to 96.66% between 1990 and 2020. …”
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Geometry optimization on the cross section of adhesively bonded thin-walled composite beam subjected to axial crushing load by Xiao Han, Jingru Ye, Shaoqiang Hou, Wenbin Hou

“…It was revealed that EA increased by 8.28%, while the total weight and cost decreased by 3.14% and 3.23%, respectively, and can thus provide a guidance in vehicle composite component design.…”
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Synergy and Effectiveness Evaluation of Carbon Policy and Government Subsidies: Variational Inequality Model Based on Supply Chain Network by Chao Wang, Hui Sun, Yuehu Wang

“…Numerical simulations were conducted with a modified projection algorithm, and the Borda method was applied to evaluate equilibrium outcomes, specifically production levels and emission reductions, under each policy combination, revealing synergies between policies. …”
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Numerical Solution of the Inverse Thermoacoustics Problem Using QFT and Gradient Method by Syrym E. Kasenov, Aigerim M. Tleulesova, Almas N. Temirbekov, Zholaman M. Bektemessov, Rysbike A. Asanova

“…The inverse problem was reduced to an optimization problem, where the objective function was minimized using gradient methods, including the accelerated Nesterov algorithm. The conjugate problem was constructed, and the functional gradient was computed, while the existence of the Frechet derivative was proved. …”
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Physics-Informed Decoupled Calibration for Fourier Ptychographic Microscopy by Mingdi Liu, Junzhao Liang, Yanxiong Wu, Zicong Luo, Rui Xie, Jiaxiong Luo, Lisong Yan

“…To address this, we propose a physically decoupled correction framework integrating convolutional neural network (CNN), simulated annealing (SA) algorithms, and GPU parallel acceleration. The CNN extracts frequency-domain circular features related to LED positioning errors as physical priors, while the GPU-accelerated SA algorithm accurately solves LED array spatial parameters during FPM forward propagation. …”
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Studying Pupil-Size Changes as a Function of Task Demands and Emotional Content in a Clinical Interview Situation by Daniel Gugerell, Benedikt Gollan, Moritz Stolte, Ulrich Ansorge

“…This was possible with an algorithmic online measure of cognitive load as well as with a conventional pupil-size measure, providing proof of the external validity of the algorithm/online measure.…”
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Numerical Simulation Study on the Response of Ship Engine Room Structure Under Fire Based on Thermo-Mechanical Coupling Model by Yuechao Zhao, Zeya Miao, Shouye Wang, Dihao Ai

“…To precisely assess the post-fire structural integrity of ships, in this study, a thermal–mechanical coupling data interface was created, employing a significant eddy simulation algorithm for fire dynamics and a technique to analyze the structural thermal–mechanical coupling reaction. …”
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Fast and Efficient Drone Path Planning Using Riemannian Manifold in Indoor Environment by Rohit Dujari, Brijesh Patel, Bhumeshwar K. Patle

“…This paper introduces an innovative dual-path planning algorithm rooted in a topological three-dimensional Riemannian manifold (T3DRM) to optimize drone navigation in complex environments. …”
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Standardized Extraction of Air Traffic Control Hazard Features Based on Expert Knowledge by Xianghua Tan, Zhipeng Cai, Zhibin Quan, Weili Zeng

“…Air traffic control (ATC) hazard feature extraction is a key information retrieval task for air traffic hazard records. While text-based feature extraction ranks term importance based solely on statistical results, we aim to use external knowledge to extract features that meet the definition of hazards. …”
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Spatial Pattern and Influencing Factor Analysis of Parcel Lockers in London by Kang Xinwei

“…The goal of this work is to satisfy urban consumers’ demand for online shopping while lowering CO2 emissions. However, few studies have focused on the parcel locker itself. …”
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Global Single-Shot Indoor Localization of Autonomous Flight Robots With Minimal Sensor Configuration by Timm von Bergen, Sascha Rock

“…Afterwards, one of two methods is employed: a randomized coarse-to-fine search, in which the search space is iteratively reduced, or a parallel differential evolution algorithm, which enhances pose estimates with evolutionary algorithms while avoiding premature convergence. …”
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An Explainable Machine Learning Model for Predicting Macroseismic Intensity for Emergency Management by Federico Mori, Giuseppe Naso

“…As damage severity increases, feature importance shifts from PGA to PGV, while site-specific variables (slope, Vs30) act as refiners rather than amplifiers of shaking. …”
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Fatigue-Aware Sub-Second Combinatorial Auctions for Dynamic Cycle Allocation in Human–Robot Collaborative Assembly by Claudio Urrea

“…Problem: Existing Human–Robot Collaboration (HRC) allocators cannot react at a sub-second scale while accounting for worker fatigue. Objective: We designed a fatigue-aware combinatorial auction executed every 100 ms. …”
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