MULTIDIMENSIONAL PROXIMITIES AND INTERORGANIZATIONAL COINNOVATION PERFORMANCE: THE ROLES OF INTRAORGANIZATIONAL COLLABORATION NETWORK INEFFICIENCY

Multidimensional proximities and interorganizational coinnovation performance: The roles of intraorganizational collaboration network inefficiency

In a gradually more interlinked world, the formation of collaborations with partners is increasingly regarded as an important driver for generating innovation.Although multidimensional proximities are important factors influencing interorganizational coinnovation performance, relevant empirical studies have not reached consistent conclusions.By foc

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Fake Banknote Recognition Using Deep Learning

Recently, some state-of-the-art works have used deep learning-based architectures, specifically convolutional neural networks (CNNs), for banknote recognition and copyright detection with promising results.However, it is not clear which design strategy is more appropriate (custom or by transfer learning) in terms of classifier performance and infer

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The effects of flame orientation and mean shear on flame stretch in highly turbulent premixed flames using DNS

In the present work, direct numerical simulation data of a laboratory-scale high Karlovitz number (Ka) jet flame with a strong mean shear enchanted taylor swift perfume and a high Ka freely propagating planar flame without a mean shear were analyzed to explore the influence of flame orientation and mean shear on flame stretch in highly turbulent fl

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