Søgeresultater - sciences data processing programmes construction

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  1. 1

    GRAPEVNE - Graphical Analytical Pipeline Development Environment for Infectious Diseases [version 1; peer review: 2 approved] af Samir Bhatt, John-Stuart Brittain, Houriiyah Tegally, Rhys Inward, Joseph Tsui, Gaspary Mwanyika, Bernardo Gutierrez, Sofonias Kifle Tessema, Tuyen Huynh, Abhishek Dasgupta, John T. McCrone, George Githinji, Moritz U.G. Kraemer, Stephen Ratcliffe

    Udgivet 2025-05-01

    The increase in volume and diversity of relevant data on infectious diseases and their drivers provides opportunities to generate new scientific insights that can support ‘real-time’ decision-making in public health across outbreak contexts and enhance pandemic preparedness. However, utilising the w...

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  2. 2

    BGIR: A Low-Illumination Remote Sensing Image Restoration Algorithm with ZYNQ-Based Implementation af Zhihao Guo, Liangliang Zheng, Wei Xu

    Udgivet 2025-07-01

    When a CMOS (Complementary Metal–Oxide–Semiconductor) imaging system operates at a high frame rate or a high line rate, the exposure time of the imaging system is limited, and the acquired image data will be dark, with a low signal-to-noise ratio and unsatisfactory sharpness. Therefore, in order to...

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  3. 3

    Improving health-promoting workplaces through interdisciplinary approaches. The example of WISEWORK-C, a cluster of five work and health projects within Horizon-Europe af Deborah De Moortel, Michelle C Turner, Ella Arensman, Alex Binh Vinh Duc Nguyen, Víctor Gonzalez

    Udgivet 2025-07-01

    Digitalization, green transitions, and demographic change are transforming societies and economies across Europe. These shifts are giving rise to new forms of work (eg, hybrid work, gig economy jobs) and reshaping management and work organization practices (eg, through algorithmic decision-making or...

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    “...By collaborating on data management and analysis, WISEWORK-C enhances the reproducibility and comparability of findings across countries and sectors—an important step for epidemiological rigor. ...”
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