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State-of-the-art in issues related to System-on-Chip (SoC) design by leading experts in the fields, covers IP development, verification, integration, chip implementation, testing and software. ![]() Ernst Schröder on Algebra and Logic English | 2022 | ISBN: 3031056701 | 355 Pages | PDF (True) | 4.23 MB This volume offers English translations of three early works by Ernst Schröder (1841-1902), a mathematician and logician whose philosophical ruminations and pathbreaking contributions to algebraic logic attracted the admiration and ire of figures such as Dedekind, Frege, Husserl, and C. S. Peirce. Today he still engages the sympathetic interest of logicians and philosophers. ![]() OECD, "Enhancing Access to and Sharing of Data Reconciling Risks and Benefits for Data Re-use across Societies" English | 2020 | pages: 138 | ISBN: 926476402X | PDF | 3,9 mb This report examines the opportunities of enhancing access to and sharing of data (EASD) in the context of the growing importance of artificial intelligence and the Internet of Things. It discusses how EASD can maximise the social and economic value of data re-use and how the related risks and challenges can be addressed. It highlights the trade-offs, complementarities and possible unintended consequences of policy action - and inaction. 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While ESNAM reflects the state-of-the-art in social network research, the field had its start in the 1930s when fundamental issues in social network research were broadly defined. These communities were limited to relatively small numbers of nodes (actors) and links. More recently the advent of electronic communication, and in particular on-line communities, have created social networks of hitherto unimaginable sizes. People around the world are directly or indirectly connected by popular social networks established using web-based platforms rather than by physical proximity. ![]() Encyclopedia of Machine Learning and Data Mining by Claude Sammut, Geoffrey I. Webb English | True PDF | 2017 | 1341 Pages | ISBN : 148997685X | 30.8 MB This authoritative, expanded and updated second edition of Encyclopedia of Machine Learning and Data Mining provides easy access to core information for those seeking entry into any aspect within the broad field of Machine Learning and Data Mining. 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