SFMattingNet: A Trimap-Free Deep Image Matting Approach for Smoke and Fire Scenes by Shihui Ma, Zhaoyang Xu, Hongping Yan

“…Since image matting algorithms compute these alpha values, the quality of the alpha composition directly depends on the performance of the smoke and fire matting methods. …”
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Embedded Anchors Coupled Low-Rank Tensor Learning for Multi-View Intrinsic Subspace Clustering by Yueyao Li, Yanying Mei, Zhenwen Ren, Bin Wu

“…The cubic time complexity of both graph construction and spectral clustering has greatly hindered the application of these algorithms to large-scale scenarios. Several research approaches have dramatically improved the clustering productivity by employing the anchor sampling mechanism. …”
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Robust EEG Characteristics for Predicting Neurological Recovery from Coma After Cardiac Arrest by Meitong Zhu, Meng Xu, Meng Gao, Rui Yu, Guangyu Bin

“…By integrating machine learning (ML) algorithms, such as Gradient Boosting Models and Support Vector Machines, with SHAP-based feature visualization, robust screening methods were applied to ensure the reliability of predictions. …”
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A Novel Hybrid Analysis Method of LLC Resonant Converter for High Accuracy and Low Computational Burden by Su-Seong Park, Rae-Young Kim

“…Recently, as the demand for LLC resonant converters has increased in various power electronics industry sectors, research on accurate analysis methods necessary for effectively designing converters has been conducted. …”
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Cloud-edge collaborative data anomaly detection in industrial sensor networks. by Tao Yang, Xuefeng Jiang, Wei Li, Peiyu Liu, Jinming Wang, Weijie Hao, Qiang Yang

“…Efficient and accurate anomaly detection of sensor data is essential for guaranteeing the system's operational reliability and security. However, existing research on sensor data anomaly detection for industrial sensor networks still has several inherent limitations. …”
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Real-time traffic monitoring system using IoT-aided robotics and deep learning techniques by Mohammed Qader Kheder, Aree Ali Mohammed

“…The data, which is collected by sensors and cameras, is processed using various image processing algorithms and it is sent to the cloud to be available for drivers and commuters through a mobile application. …”
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A Novel PNDA-MMNet Model for Evaluating Dynamic Changes in the Brain State of Patients with PTSD During Neurofeedback Training by Peng Ding, Lei Zhao, Anmin Gong, Wenya Nan, Yunfa Fu

“…Results: The proposed model achieves a brain state identification accuracy of 0.7428 ± 0.12 (area under the curve, AUC = 0.84), significantly outperforming conventional algorithms. Interpretations of the model indicate that continuous NFT reduces functional connectivity within the motor cortex, with stronger suppression in the right hemisphere compared to the left. …”
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Advances in ECG and PCG-based cardiovascular disease classification: a review of deep learning and machine learning methods by Asmaa Ameen, Ibrahim Eldesouky Fattoh, Tarek Abd El-Hafeez, Kareem Ahmed

“…The results of these predictions will help physicians make decisions and early diagnoses, decreasing the risk of patient death. This work compares and reports the classification, machine learning, and deep learning algorithms that predict cardiovascular illnesses. …”
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PULSE: A Fast Portable Unit for Lab-on-Site Electrochemistry by Cláudia Ferreira, Fiona Barry, Miomir Todorović, Patrick Sugrue, Sofia Rodrigues Teixeira, Paul Galvin

“…This study aims to develop and validate a novel fast-detection electrochemical sensing platform to enhance portable electrochemical sensor solutions. The research focuses on optimising analogue front-end circuits, developing data analysis algorithms, and validating the device through experiments to enhance measurement accuracy and detection speed, enabling on-site measurements across diverse applications. …”
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Understanding acceptance and resistance toward generative AI technologies: a multi-theoretical framework integrating functional, risk, and sociolegal factors by Priyanka Shrivastava

“…Ethical concerns, including algorithmic bias, data ownership, and the labor market impact of AI, are addressed to offer a more holistic understanding of resistance behavior. …”
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Machine Learning Approach to Model Soil Resistivity Using Field Instrumentation Data by Md Jobair Bin Alam, Ashish Gunda, Asif Ahmed

“…The ability to infer these variables through a singular measurable soil property, soil resistivity, can potentially improve sub-surface characterization. This research leverages various machine learning algorithms to develop predictive models trained on a comprehensive dataset of sensor-based soil moisture, matric suction, and soil temperature obtained from prototype ET covers, with known resistivity values. …”
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Adaptive Multi-Scale Bayesian Framework for MFL Inspection of Steel Wire Ropes by Xiaoping Li, Yujie Sun, Xinyue Liu, Shaoxuan Zhang

“…This research not only advances signal processing and anomaly detection technology but also contributes to enhancing safety and maintenance efficiency in critical infrastructure.…”
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FastSLAM-MO-PSO: A Robust Method for Simultaneous Localization and Mapping in Mobile Robots Navigating Unknown Environments by Xu Bian, Wanqiu Zhao, Ling Tang, Hong Zhao, Xuesong Mei

“…Our empirical evaluation involves testing the proposed method on three distinct simulation benchmarks, comparing its performance against four other algorithms. …”
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BiLSTM-Based Parallel CNN Models With Attention and Ensemble Mechanism for Twitter Sentiment Analysis by Anas W. Abulfaraj

“…Due to the increased use of social networks, word-of-mouth analysis has become an effective tool in market research since firms can determine the users’ attitudes toward their brands. …”
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Approach to Enhancing Panoramic Segmentation in Indoor Construction Sites Based on a Perspective Image Segmentation Foundation Model by Juho Han, Sebeen Yoon, Mingyun Kang, Taehoon Kim

“…The proposed method iteratively executes SAM with adjusted input parameters to extract objects of varying sizes and subsequently applies filtering algorithms to retain valid objects. Then, label assignment and merging processes are performed based on the predictions from the target model to improve segmentation accuracy. …”
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Prevention of falls in hospitalized patients—evaluation of the effectiveness of a monitoring system (Verso Vision) developed with artificial intelligence by Corrado Gervasi, Erik Perego, Francesca Galli, Valter Torri, Massimo Castoldi, Emilio Bombardieri

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A Flexible Constrained ICA Approach for Multisubject fMRI Analysis by Hanlu Yang, Trung Vu, Ehsan Ahmed Dhrubo, Vince D. Calhoun, Tülay Adali

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Best practices and joint calling of the HumanExome BeadChip: the CHARGE Consortium. by Megan L Grove, Bing Yu, Barbara J Cochran, Talin Haritunians, Joshua C Bis, Kent D Taylor, Mark Hansen, Ingrid B Borecki, L Adrienne Cupples, Myriam Fornage, Vilmundur Gudnason, Tamara B Harris, Sekar Kathiresan, Robert Kraaij, Lenore J Launer, Daniel Levy, Yongmei Liu, Thomas Mosley, Gina M Peloso, Bruce M Psaty, Stephen S Rich, Fernando Rivadeneira, David S Siscovick, Albert V Smith, Andre Uitterlinden, Cornelia M van Duijn, James G Wilson, Christopher J O'Donnell, Jerome I Rotter, Eric Boerwinkle

“…., minor allele frequency [MAF] <0.01) is the difficulty that automated clustering algorithms have to accurately detect and assign genotype calls. …”
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The effectiveness of complex therapy in the treatment of nonspecific vaginitis in women of reproductive age by O.D. Ryazanova, G.I. Reznichenko

“…Research methods: general (collection of complaints and anamnesis, gynecological examination, assessment of microscopy of vaginal smears according to the Amsel, Nugent and Donders criteria), laboratory (determination levels of follicle-stimulating, luteinizing hormones, prolactin, estradiol, adrenaline, noradrenaline, cortisol, magnesium in the blood), statistical. …”
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Model Development for Estimating Sub-Daily Urban Air Temperature Patterns in China Using Land Surface Temperature and Auxiliary Data from 2013 to 2023 by Yuchen Guo, János Unger, Tamás Gál

“…Four model schemes were constructed and compared by combining different auxiliary data (time-related and space-related) with LST. …”
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