Showing 1 - 20 results of 1,871 for search '(core OR scale) function generate', query time: 0.20s Refine Results
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    Integrating surveying, photogrammetric, and remote sensing data to generate large-scale maps by Przemysław Klapa, Pelagia Gawronek, Tadeusz Gargula, Agnieszka Sokołowska, Kamil Sajdak

    Published 2025-06-01
    “…Information acquired this way, supplemented with spatial data from official (state-controlled) surveying and cartographic resources, paves the way for generating large-scale maps, including the master map, in line with applicable legal and technical requirements. …”
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    Searching for Functional Simplicity of Stormflow Generation by Hamed Sharif, Ali A. Ameli

    Published 2025-03-01
    “…Abstract Our study proposes a data‐driven framework that identifies the level of functional simplicity of catchment's stormflow generation during dormant/growing seasons, using daily scale observations of streamflow and precipitation. …”
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    Improving the core functions of primary care in a Ugandan rural district by Innocent K. Besigye, Robert J. Mash

    Published 2025-05-01
    “…Community dialogues as form of community engagement were selected as an intervention to improve the core primary care functions. Conclusion: The PCAT can generate findings to guide the development of interventions at the facility and district level to potentially improve the core functions of primary care. …”
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    Scale symmetry breaking and generation of mass at quantum critical points by Charlie Cresswell-Hogg, Daniel F. Litim

    Published 2024-07-01
    “…Exactly at the endpoint, scale symmetry is broken spontaneously, leading to the generation of fermion mass. …”
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    Large-Scale Periodic Gust Generation and Spectral Analysis Approach for Characterization and Evaluation by Berk Zaloglu, Oksan Cetiner

    Published 2025-06-01
    “… Generating a periodic continuous gust in a controlled manner and at sufficiently large scales for the gust encounter studies on MAV applications is a challenge. …”
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    Time series generation model based on multi-discriminator generative adversarial network by Yanhui LU, Han LIU, Hang LI, Guangxu ZHU

    Published 2022-10-01
    “…Aiming at the problems of expensive collection cost and missing data due to the privacy and continuity of time series data set, a multi-discriminator generative adversarial network model based on recurrent neural network was proposed, which could synthesize time series dataset that were approximately distributed with real data of a small scale dataset.Multi-discriminator included four discriminators in time domain, frequency domain, time-frequency domain and autocorrelation.Different discriminators could effectively recognize the features of the time series in different domains.In the experiment, the convergence of loss function, principal component analysis and error analysis were performed to evaluate the performance of the model from qualitative and quantitative perspectives.The experimental results show that the proposed model has better performance than other reference models.…”
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    CREATIVE CORE WITHIN THE SCIENTIFIC RESEARCH OF EDUCATIONAL PROBLEMS by Vladimir I. Zagvyazinsky, Alfia F. Zakirova

    Published 2015-03-01
    “…The content of such notions as «concept», «creative core», «idea», «plot», and «research hypothesis» is revealed. …”
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    Core-Sheath Structured Yarn for Biomechanical Sensing in Health Monitoring by Wenjing Fan, Cheng Li, Bingping Yu, Te Liang, Junrui Li, Dapeng Wei, Keyu Meng

    Published 2025-05-01
    “…The rapidly evolving field of functional yarns has garnered substantial research attention due to their exceptional potential in enabling next-generation electronic textiles for wearable health monitoring, human–machine interfaces, and soft robotics. …”
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    Detecting Urban Mobility Structure and Learning Functional Distribution with Multi-Scale Features by Jia Li, Chuanwei Lu, Haiyan Liu, Jing Li, Dewei Zhou, Qingyun Liu

    Published 2025-06-01
    “…First, we designed a multi-scale contrastive learning strategy to effectively learn local human activity features and global spatial structure features, determine the community affiliation of regions, and generate regional embedding vectors. …”
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