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Titlebook: Innovation Policy in the Knowledge-Based Economy; Maryann P. Feldman,Albert N. Link Book 2001 Springer Science+Business Media New York 200

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楼主: T-cell
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Maryann P. Feldman,Irwin Feller,Janet L. Bercovitz,Richard Burtonpplications, DEXA 2021, held in a virtual format in September 2021: The 12.th.  International Workshop on Biological Knowledge Discovery from Data (BIOKDD 2021), the 5.th.  International Workshop on Cyber-Security and Functional Safety in Cyber-Physical Systems (IWCFS 2021), the 3.rd.  International
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Irwin Fellerhes, ad-hoc models of local data are built instead of one large model on the overall data set. Micro-learning is typically useful for incremental, what-if/prospective scenarios, where one has to perform step-by-step decisions based on local properties. A common feature of these applications is that
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hes, ad-hoc models of local data are built instead of one large model on the overall data set. Micro-learning is typically useful for incremental, what-if/prospective scenarios, where one has to perform step-by-step decisions based on local properties. A common feature of these applications is that
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that this technology can provide, added to its link with key green targets such as the reduction of emissions or materials waste, makes AM a very attractive vehicle towards the transition to more adaptive and sustainable manufacturing. However, such a level of customization and this fast acceptance
发表于 2025-3-26 01:45:02 | 显示全部楼层
Darrene Hackler smart data discovery, a suitable system needs to be developed in a multi-stage process - starting with data acquisition and storage, data processing and analysis, suitable definition of use cases and project goals, and finally utilization and integration of the analysis results to the productive sy
发表于 2025-3-26 06:13:09 | 显示全部楼层
Priscilla M. Regan smart data discovery, a suitable system needs to be developed in a multi-stage process - starting with data acquisition and storage, data processing and analysis, suitable definition of use cases and project goals, and finally utilization and integration of the analysis results to the productive sy
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The Best and Brightest for Science theory holds that within the scientific enterprise it is less the many worker bees than the few genuinely creative minds who make the most critical contributions (Kuhn 1962). In any case, few would argue but that the health of the enterprise requires a steady inflow of top-flight talent.
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