Real-Time Cloth Simulation in Extended Reality: Comparative Study Between Unity Cloth Model and Position-Based Dynamics Model with GPU by Taeheon Kim, Jun Ma, Min Hong

“…At a 64 × 64 resolution, the single-sided cloth achieved around 65 FPS, while the double-sided configuration recorded approximately 40 FPS, demonstrating scalable quality adaptation depending on application requirements. …”
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A Decentralized Multi-Venue Real-Time Video Broadcasting System Integrating Chain Topology and Intelligent Self-Healing Mechanisms by Tianpei Guo, Ziwen Song, Haotian Xin, Guoyang Liu

“…Specifically, our approach achieves substantial improvements in latency, video quality stability, and fault tolerance over existing P2P methods, along with over tenfold enhancements in frame rates compared with conventional RTMP-based solutions, thereby demonstrating its efficacy, scalability, and cost-effectiveness for real-time video streaming applications.…”
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Hinge-FM2I: an approach using image inpainting for interpolating missing data in univariate time series by Saad Noufel, Nadir Maaroufi, Mehdi Najib, Mohamed Bakhouya

“…Abstract Accurate time series forecasts are crucial for various applications, such as traffic management, electricity consumption, and healthcare. …”
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A Method to Assess Localized Impact of Better Floodplain Topography on Flood Risk Prediction by Guy J.-P. Schumann, Konstantinos M. Andreadis

“…We propose an analysis based on a targeted observation algorithm to evaluate potential data acquisition subregions in terms of their impact on the prediction of flood risk over the entire study area. …”
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Perioperative management of patients with rheumatic disorders: problems and solutions by A. A. Klimenko, A. A. Kondrashov

“…Currently management of patients with rheumatic disorders (RD) involves not only application of all of the known spectrum of mediations in accordance with current guidelines and algorithms but also timely use of high-tech medical care, for example, endoprosthesis of the large joints, spinal surgery, dental care, endovascular surgery, aimed at decreasing the level of disability and improving patients’ quality of life. …”
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A Multi-Objective Approach for Optimizing Virtual Machine Placement Using ILP and Tabu Search by Mohamed Koubàa, Rym Regaieg, Abdullah S. Karar, Muhammad Nadeem, Faouzi Bahloul

“…Furthermore, these three performance metrics are jointly optimized to ensure operational efficiency (OPEF) and minimal operational expenditure (OPEX). We rigorously evaluate the performance of the TS algorithm through extensive simulation scenarios and compare its results with those of the MOILP model, enabling us to assess the quality of the approximate solution relative to the optimal one. …”
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Diagnostic framework to validate clinical machine learning models locally on temporally stamped data by Maximilian Schuessler, Scott Fleming, Shannon Meyer, Tina Seto, Tina Hernandez-Boussard

“…Finally, feature importance and data valuation algorithms are applied for feature reduction and data quality assessment. …”
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Development and validation of a risk prediction model for depression in patients with chronic obstructive pulmonary disease by Tong Feng, PeiPei Li, Ran Duan, Zhi Jin

“…Nine machine learning models were trained and evaluated, with performance assessed via accuracy, area under the curve (AUC), calibration, and clinical utility metrics. …”
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Use of machine learning to predict creativity among nurses: a multidisciplinary approach by Rola H. Mudallal, Majd T. Mrayyan, Mohammad Kharabsheh

“…Clinical trial number Not applicable.…”
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Defect detection based on extreme edge of defective region histogram by Zouhir Wakaf, Hamid A. Jalab

“…Automatic thresholding has been used by many applications in image processing and pattern recognition systems. …”
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Generative design optimization of tree distribution for enhanced thermal comfort in communal spaces with special reference to hot arid climates by Ahmed Maged, Aly Abdelalim, Abdelaziz Farouk A. Mohamed

“…Accordingly, more comprehensive methodologies are highly needed to improve the research-based design of landscape parameters and components for developing outdoor thermal comfort performance using an iterative design exploration process that employs AI-driven software. These applications, help designers in solving multi-objective design quandaries through the generation and evaluation of numerous design options. …”
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Gas adsorption meets geometric deep learning: points, set and match by Antonios P. Sarikas, Konstantinos Gkagkas, George E. Froudakis

“…These are typically built in a descriptor-based manner, meaning that the structure must be first coarse-grained into a 1D fingerprint before it is fed to the ML algorithm. As such, the latter can not fully exploit the 3D structural information, potentially resulting in a model of lower quality. …”
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Research on automatic identification method for pipeline girth weld defects based on X-ray images and sparse representation by Shaohui JIA, Yaping LI, Weixin GAO, Yunchao PENG, Xinjian ZHANG, Yuxia WANG

“…Conclusion The proposed defect identification method demonstrates its capability to greatly improve the detection quality and efficiency of potential safety hazards in pipeline girth welds, underscoring its promising prospects in industrial applications.…”
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Machine learning enables legal risk assessment in internet healthcare using HIPAA data by Shixian Liu, Hailing Liu, Siyu Fan, Leming Song, Zeyu Wang

“…Secondly, to address missing values and noise in the data, preprocessing methods such as denoising, normalization, and feature extraction are employed to ensure data quality and model accuracy. Finally, in the selection of ML models, this study experiments with several common algorithms, including extreme gradient boosting (XGBoost), support vector machine (SVM), random forest (RF), and deep neural network (DNN). …”
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HOLa: HoloLens Object Labeling by Schwimmbeck Michael, Khajarian Serouj, Holzapfel Konstantin, Schmidt Johannes, Remmele Stefanie

“…As segmentation foundation models like the Segment Anything Model (SAM) begin to emerge, zero-shot segmentation requires only minimal human participation obtaining high-quality object masks. We introduce a HoloLens-Object-Labeling (HOLa) Unity and Python application based on the SAM-Track algorithm that offers fully automatic single object annotation for HoloLens 2 while requiring minimal human participation. …”
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Incentive Mechanism for Cloud Service Offloading in Edge–Cloud Computing Environment by Chendie Yao, Junjie Xie, Zhong Liu

“…In such edge–cloud computing environments, many cloud providers intend to offload cloud services to the edge nodes to offer high-quality services for data-intensive and latency-sensitive applications. …”
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Machine learning analysis of cardiovascular risk factors and their associations with hearing loss by Ali Nabavi, Farimah Safari, Ali Faramarzi, Mohammad Kashkooli, Meskerem Aleka Kebede, Tesfamariam Aklilu, Leo Anthony Celi

“…The accurate models identify high-risk groups, enabling timely intervention to improve quality of life. The subtle changes in hearing often go unnoticed, presenting a challenge for early hearing loss detection. …”
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Comparative analysis of single-view and multiple-view data collection strategies for detecting partially-occluded grape bunches: Field trials by Mar Ariza-Sentís, Hilmy Baja, Sergio Vélez, Rick van Essen, João Valente

“…This study compares two data acquisition methodologies for grape bunch detection and tracking in a commercial vineyard where leaf removal was not performed: a traditional single-view approach and a multiple-viewing method designed to mitigate fruit occlusion issues. The PointTrack algorithm, trained and validated using MOTS annotations, was employed to evaluate detection and tracking performance through metrics of three trials. …”
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Streaming LiDAR Scene Flow Estimation by Mazen Abdelfattah, Z. Jane Wang, Rabab Ward

“…This achieves substantial speedups while maintaining, and in some cases surpassing, full-scan accuracy. We rigorously evaluate our approach on the challenging Waymo and Argoverse datasets, demonstrating significant latency reduction without compromising scene flow quality. …”
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Use machine learning to predict treatment outcome of early childhood caries by Yafei Wu, Maoni Jia, Ya Fang, Duangporn Duangthip, Chun Hung Chu, Sherry Shiqian Gao

“…The aim of this study is to explore the application of machine learning in predicting the treatment outcome of ECC. …”
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