Showing 101 - 120 results of 907 for search '((( source OR sources) detection functions ) OR ( sources detection function ))', query time: 0.34s Refine Results
  1. 101

    MTAHG and MTBHG: Modified Approaches for Interpreting Gravity Data by Hazel Deniz Toktay, Hanbing Ai, Ahmad Alvandi, Kejia Su, Jinlei Li

    Published 2025-04-01
    “…This paper proposes two effective edge detection tools: one combining the balanced total horizontal gradient (BHG), and the hyperbolic tangent function, abbreviated as “MTBHG”; and the other combining the tilt angle of the total horizontal gradient (TAHG) and the hyperbolic tangent function, abbreviated as “MTAHG.” …”
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  2. 102

    Near-source wastewater surveillance of SARS-CoV-2, norovirus, influenza virus and RSV across five different sites in the UK. by Jay C Bullen, Mina Mohaghegh, Fatima Tahir, Charlotte Hammer, Jacob Sims, Frederico Myers, Lucas Eisinger, Ali Reza Kasmati, Claire F Trant

    Published 2025-01-01
    “…The key findings are (1) near-source wastewater detections were linked to local events (staff sickness, enhanced cleaning, changing populations); (2) wastewater detections decreased in the order norovirus GII > norovirus GI > SARS-CoV-2 ≈ influenza A ≈ RSV A > influenza B ≈ RSV B; (3) correlation between near-source wastewater data and national surveillance data increases as a function of catchment size and viral prevalence (examples include the SARS-CoV-2 BA.4/BA.5 variant peak at a museum and wastewater tracking the winter norovirus season); (4) strong weekday periodicity in near-source wastewater SARS-CoV-2 detections, with the correlation against COVID-19 case numbers increasing when modelling variable lag times between faecal shedding onset and clinical diagnosis (R2 = 0.45 increases to 0.84-0.86); (5) a log-linear relationship between the frequency of wastewater SARS-CoV-2 detection and log(catchment size⋅viral prevalence) (R2 = 0.6914-0.9066). …”
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  3. 103

    Failure Law of Sandstone and Identification of Premonitory Deterioration Information Based on Digital Image Correlation–Acoustic Emission Multi-Source Information Fusion by Zhaohui Chong, Guanzhong Qiu, Xuehua Li, Qiangling Yao

    Published 2025-02-01
    “…Additionally, by introducing the derivative functions of the multi-source information function for quantitative analysis, a comprehensive evaluation method was proposed based on the multi-source information fusion monitoring to forewarn red sandstone failure by levels during loading. …”
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  4. 104

    A spatial matrix factorization method to characterize ecological assemblages as a mixture of unobserved sources: An application to fish eDNA surveys by Letizia Lamperti, Olivier François, David Mouillot, Laëtitia Mathon, Théophile Sanchez, Camille Albouy, Loïc Pellissier, Stéphanie Manel

    Published 2024-12-01
    “…We present a spatial matrix factorization method that identifies optimal eDNA sample assemblages—called pools—assuming that taxonomic unit composition is based on a fixed number of unknown sources. These sources, in turn, represent taxonomic units sharing similar habitat properties or characteristics. …”
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  5. 105
  6. 106

    Loss Function Optimization Method and Unsupervised Extraction Approach D-DBSCAN for Improving the Moving Target Perception of 3D Imaging Sonar by Jingfeng Yu, Aigen Huang, Zhongju Sun, Rui Huang, Gao Huang, Qianchuan Zhao

    Published 2025-03-01
    “…Compared to 2D sonar images, 3D sonar images offer superior spatial positioning capabilities, although the data acquisition cost is higher and lacks open source references for data annotation, target detection, and semantic segmentation. …”
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  7. 107

    Development and validation of microwave-assisted extraction for phenolic compound profiling in diverse oyster mushrooms (Pleurotus spp.) sourced from various geographical regions by M Umar Harun, Miguel Palma, Widiastuti Setyaningsih

    Published 2025-04-01
    “…Seven phenolic compounds—p-coumaric acid, t-cinnamic acid, p-hydroxybenzaldehyde, p-hydroxybenzoic acid, quercetin-3-glucoside, gallic acid, and vanillic acid—were effectively extracted and quantified using ultra-performance liquid chromatography with photodiode array detection. Application of this method across oyster mushroom samples from different geographical sources revealed significant variation in phenolic compound concentrations, with Pleurotus pulmonarius exhibiting the highest level of gallic acid at 433.90 ± 7.77 μg g−1 (DM) and Pleurotus ostreatus var. …”
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  8. 108

    Non-Line-of-Sight Location With Gauss Filtering Algorithm Based on a Model of Photon Flight by Yu Ren, Zongliang Xie, Yihan Luo, Shaoxiong Xu, Haotong Ma, Yi Tan

    Published 2020-01-01
    “…Recently, non-line-of-sight (NLOS) detection based on time of flight (TOF) has been investigated. …”
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  9. 109

    QPPLab: A generally applicable software package for detecting, analyzing, and visualizing large-scale quasiperiodic spatiotemporal patterns (QPPs) of brain activity by Nan Xu, Behnaz Yousefi, Nmachi Anumba, Theodore J. LaGrow, Xiaodi Zhang, Shella Keilholz

    Published 2025-02-01
    “…To address these challenges, we present QPPLab, an open-source MATLAB-based toolbox for detecting, analyzing, and visualizing QPPs from fMRI time series. …”
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  10. 110

    Highly Efficient Biphoton Generation from Thin Dense Atomic Ensemble by Heewoo Kim, Hansol Jeong, Han Seb Moon

    Published 2025-04-01
    “…Strongly correlated bright biphotons are generated via spontaneous four‐wave mixing from a dense atomic ensemble based on the 6S1/2–6P3/2–6D5/2 transition of 133Cs. Biphoton source achieves a detected biphoton count rate of 100 kilo‐counts per second, a heralding efficiency of 15%, and a maximum normalized crosscorrelation function value of 100 between the signal and idler photons, despite the low detector efficiency of a silicon avalanche photodetector being less than 25% at 917 nm. …”
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  11. 111

    Neural network for step anomaly detection in head motion during fMRI using meta-learning adaptation by N.S. Davydov, V.V. Evdokimova, P.G. Serafimovich, V.I. Protsenko, A.G. Khramov, A.V. Nikonorov

    Published 2023-12-01
    “…Quality assessment and artifact detection in functional magnetic resonance imaging (fMRI) data is essential for clinical applications and brain research. …”
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  12. 112
  13. 113

    Fine-grained building function recognition with street-view images and GIS map data via geometry-aware semi-supervised learning by Weijia Li, Jinhua Yu, Dairong Chen, Yi Lin, Runmin Dong, Xiang Zhang, Conghui He, Haohuan Fu

    Published 2025-03-01
    “…In this work, we propose a geometry-aware semi-supervised method for fine-grained building function recognition, which effectively uses multi-source geoinformation data to achieve accurate function recognition in both single-city and cross-city scenarios. …”
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  14. 114

    Source Process Estimation for the 2024 Mw 7.1 Hyuganada, Japan, Earthquake and Forward Modeling Using N‐net Ocean Bottom Seismometer Data by R. Shibata, H. Kubo, W. Suzuki, S. Aoi, H. Sekiguchi

    Published 2025-05-01
    “…The N‐net seafloor seismograms of the mainshock with a frequency of ∼0.05 Hz recorded east of the source area were reproduced for several stations using the empirical Green's function approach based on the estimated source process data.…”
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  15. 115
  16. 116

    Intelligent Firefighting Technology for Drone Swarms with Multi-Sensor Integrated Path Planning: YOLOv8 Algorithm-Driven Fire Source Identification and Precision Deployment Strateg... by Bingxin Yu, Shengze Yu, Yuandi Zhao, Jin Wang, Ran Lai, Jisong Lv, Botao Zhou

    Published 2025-05-01
    “…This study aims to improve the accuracy of fire source detection, the efficiency of path planning, and the precision of firefighting operations in drone swarms during fire emergencies. …”
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  17. 117
  18. 118

    Yarn-electrospun PVDF-HFP/CNC smart textiles for self-powered sensor in wearable electronics by Jiawei Chen, Subhamoy Mahajan, Manisha Gupta, Cagri Ayranci, Tian Tang

    Published 2025-04-01
    “…The success of developing such sensor-integrated touchscreen gloves paves new avenues for human-technology interactions, highlights the dual functionality of these yarns as power sources and sensors, and represents a milestone in broadening the applications of wearable technologies.…”
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  19. 119
  20. 120

    Three-Dimensional Real-Scene-Enhanced GNSS/Intelligent Vision Surface Deformation Monitoring System by Yuanrong He, Weijie Yang, Qun Su, Qiuhua He, Hongxin Li, Shuhang Lin, Shaochang Zhu

    Published 2025-04-01
    “…The system integrates GNSS monitoring terminals and multi-source meteorological sensors to accurately capture minute displacements at monitoring points and multi-source Internet of Things (IoT) data, which are then automatically stored in MySQL databases. …”
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