Hybrid machine learning for real-time prediction of edema trajectory in large middle cerebral artery stroke by Ethan Phillips, Odhran O’Donoghue, Yumeng Zhang, Panos Tsimpos, Leigh Ann Mallinger, Stefanos Chatzidakis, Jack Pohlmann, Yili Du, Ivy Kim, Jonathan Song, Benjamin Brush, Stelios Smirnakis, Charlene J. Ong, Agni Orfanoudaki

“…The HELMET models were trained on retrospective data from 623 patients and validated on 63 patients from a different hospital system, achieving mean areas under the receiver operating characteristic curve of 96.6% and 92.5%, respectively. By integrating transformer-based large language models with supervised ensemble learning, HELMET demonstrates the value of combining clinician expertise with multimodal health records in assessing patient risk. …”
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Enhancing Wind Turbine Efficiency: An Experimental Investigation of a Sensorless Three-Vector Finite Set Predictive Torque Control Approach for PMSG-Based Systems by Marouane Ahmed Ghodbane, Toufik Mohamed Benchouia, Mohamed Chebaani, Mohamed Becherif, Yassine Himeur, Amar Golea, Abdelmoumen Ghilani, Zakaria Alili, Shadi Atalla, Wathiq Mansoor

“…Additionally, the Tip Speed Ratio Maximum Power Point Tracking (TSR-MPPT) approach is used to maximize efficiency, achieving the power coefficient value at 0.48. Then the energy produced has been successfully integrated into the grid with low THD value of 3.5% and high power factor value of 0.99. …”
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Enhanced clash detection in building information modeling: Leveraging modified extreme gradient boosting for predictive analytics by Ali Shehadeh, Odey Alshboul, Madhar M. Taamneh, Aiman Q. Jaradat, Ahmad H. Alomari

“…This study introduces an intelligent system that involves the Modified Extreme Gradient Boosting (MXGBoost) algorithm to help improve clash detection in Building Information Modeling (BIM) processes. …”
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Morality on the road: the ADC model in low-stakes traffic vignettes by Michael Pflanzer, Dario Cecchini, Sam Cacace, Veljko Dubljević

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Distributed Cognitive Positioning System Based on Nearest Neighbor Association and Multi-Point Filter Initiation for UAVs Using DTMB and INS by Li Zha, Hai Zhang, Na Wang, Cancan Tao, Kunfeng Lv, Ruirui Zhang

“…The trigonometric geometry algorithm is proposed to estimate the pseudo-measurement, and the impact factors of the positioning error are analyzed. …”
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Leveraging Digital Twins for Stratification of Patients with Breast Cancer and Treatment Optimization in Geriatric Oncology: Multivariate Clustering Analysis by Pierre Heudel, Mashal Ahmed, Felix Renard, Arnaud Attye

“…Unlike traditional models that focus on isolated factors, this AI-based approach integrates multiple clinical and biological features to generate a comprehensive biomedical profile. …”
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Pelvic Kinematics during Gait Following Long-Segment Spinal Fusion Due to Adult Spinal Deformity: An Analysis Using a Smartphone-Based Inertial Measurement Unit by Masanari Takami, Daisuke Nishiyama, Shunji Tsutsui, Keiji Nagata, Yuyu Ishimoto, Kotaro Oda, Hiroshi Iwasaki, Hiroshi Hashizume, Hiroshi Yamada

“…Of 1043 features obtained, the top 20 features with the smallest p-value in a statistical comparison were selected. …”
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HyQ2: A Hybrid Quantum Neural Network for NextG Vulnerability Detection by Yifeng Peng, Xinyi Li, Zhiding Liang, Ying Wang

“…Our results demonstrate that HyQ2 achieves a high area under the curve (AUC) value of 0.9708 and an accuracy of 95.91%. …”
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A data driven approach to urban area delineation using multi source geospatial data by Chenyu Fang, Lin Zhou, Xinyue Gu, Xing Liu, Martin Werner

“…Abstract This study introduces a data-driven, bottom-up approach to urban delineation, integrating feature engineering with the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm, which represents a significant improvement in precision and methodology compared to traditional approaches that rely on simplistic OpenStreetMap (OSM) road node data aggregations. …”
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Manifold embeddings achieve comparable performance with multispectral imagery for time-series based land disturbance detection by Mengyao Li, Jianbo Qi, Su Ye, Qiao Wang

“…Additionally, it is unclear whether reduced features retain temporal continuity and can integrate effectively with time series algorithms for disturbance detection. …”
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On the Convergence of Normal and Curvature Calculations with the Height Function Method for Two-Phase Flow by Antonio Cervone, Sandro Manservisi, Jieyun Pan, Ruben Scardovelli, Stéphane Zaleski

“…The height function (HF) method on a Cartesian grid integrates the volume fractions of a column of cells across the interface. …”
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Source-Grid-Load-Storage Synergistic Planning Considering Electricity-Carbon Coupling and Flexible Supply-Demand Balance by XIAO Bai, ZHANG Qingbai, QIN Weidong, QU Gaoqiang, KONG Yihui, ZHANG Xiaohua

“…Subsequently， a two-layer source-grid-load-storage cooperative planning model is proposed， with the upper layer aimed at minimizing the integrated cost of construction investment using the equal annual value method， while the lower layer seeks to minimize the sum of the annual operational cost of the power system and the annual carbon trading cost. …”
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Dual FOPID-neural network controller based on fast grey wolf optimizer: application to two-inputs two-outputs helicopter by Amar Rezoug, Jamshed Iqbal, Abdelkrim Nemra

“…The RBFNN is integrated to address the nonlinearities and uncertainties, while a dual block mitigates the coupling effects. …”
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Finding a New Balance Point: Intelligent Optimization of Multi-Target Cognitive Electronic Reconnaissance Strategy for Unmanned Aerial Vehicles by Yun Zhang, Shixun You, Yunbin Yan, Qiaofeng Ou, Xiang Zhu

“…By grouping radar positions, solving for multiple pseudo-targets, and integrating these pseudo-targets, we ultimately obtain an invisible pseudo-target that spans the entire radar detection range. …”
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Improvement of Network Traffic Prediction in Beyond 5G Network using Sparse Decomposition and BiLSTM Neural Network by Rihab Abdullah Jaber Al Hamadani, Mahdi Mosleh, Ali Hashim Abbas Al-Sallami, Rasool Sadeghi

“…The proposed method begins with preprocessing using K-SVD (K-means Singular Value Decomposition) to reduce dimensionality and enhance data representation. …”
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Shearing Performance of Lime-Reinforced Iron Tailing Powder Based on Energy Dissipation by Ping Jiang, Lingqi Qiu, Na Li, Wei Wang, Aizhao Zhou, Jingping Xiao

“…The back propagation (BP) neural network algorithm was used to fit the F-s curve, and the fitting equation that met the accuracy requirement was obtained. …”
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Predicting hydrocarbon reservoir quality in deepwater sedimentary systems using sequential deep learning techniques by Xiao Hu, Jun Xie, Xiwei Li, Junzheng Han, Zhengquan Zhao, Hamzeh Ghorbani

“…This research highlights the practical value of integrating artificial intelligence into reservoir evaluation, offering a powerful tool for improving decision-making in deepwater hydrocarbon exploration and development.…”
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Applying improved particle swarm optimization for dynamic service composition focusing on quality of service evaluations under hybrid networks by Honghao Gao, Kang Zhang, Jianhua Yang, Fangguo Wu, Hongsheng Liu

“…Second, the service composition is determined by the particle swarm optimization simulation process, which aims to identify an optimal plan based on the calculated value from quality of service. Third, considering a change of service repository, when the quality of a composite service is lower than a predefined threshold, the local greedy algorithm and global reconfiguration method are adopted to dynamically restructure composite services. …”
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An Improved LEACH Protocol for Optimizing Cluster Head Selection and In-cluster Selection by SHIBing, GAOZelin, SUNYueping, HUANJuan, SUNTao

“…Furthermore, these improvements confirm that the energy balance associated with the LEACH-enhance algorithm is superior, particularly in terms of cluster head selection and node entry.…”
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Use of ICT to Confront COVID-19 by Yousry Saber El Gamal

“…However, a comprehensive analysis of these factors integrated with AI techniques, can offer a more precise and reliable prevision of individual risk profiles. …”
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