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1. |
Record Nr. |
UNISA996385284203316 |
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Autore |
Parker Henry <1604-1652.> |
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Titolo |
The Trojan horse of the Presbyteriall government vnbowelled [[electronic resource] ] : wherein is contained, I. The power of the Presbyterian government, II. The persons in whom this power is placed, III. The exercise of the Presbyterian power in Scotland, and the lawes there imposed on the peoples necks |
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Pubbl/distr/stampa |
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Descrizione fisica |
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Soggetti |
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Presbyterian Church - Government |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Attributed to Henry Parker. Cf. DNB, McAlpin Coll. |
Reproduction of original in Huntington Library. |
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Sommario/riassunto |
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2. |
Record Nr. |
UNINA9910760256003321 |
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Autore |
Pasricha Sudeep |
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Titolo |
Embedded Machine Learning for Cyber-Physical, IoT, and Edge Computing : Use Cases and Emerging Challenges / / edited by Sudeep Pasricha, Muhammad Shafique |
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Pubbl/distr/stampa |
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Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 |
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ISBN |
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Edizione |
[1st ed. 2024.] |
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Descrizione fisica |
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1 online resource (571 pages) |
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Altri autori (Persone) |
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Disciplina |
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Soggetti |
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Embedded computer systems |
Electronic circuits |
Cooperating objects (Computer systems) |
Embedded Systems |
Electronic Circuits and Systems |
Cyber-Physical Systems |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Sommario/riassunto |
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This book presents recent advances towards the goal of enabling efficient implementation of machine learning models on resource-constrained systems, covering different application domains. The focus is on presenting interesting and new use cases of applying machine learning to innovative application domains, exploring the efficient hardware design of efficient machine learning accelerators, memory optimization techniques, illustrating model compression and neural architecture search techniques for energy-efficient and fast execution on resource-constrained hardware platforms, and understanding hardware-software codesign techniques for achieving even greater energy, reliability, and performance benefits. Discusses efficient implementation of machine learning in embedded, CPS, IoT, and edge computing; Offers comprehensive coverage of hardware design, software design, and hardware/software co-design and co-optimization; Describes real applications to demonstrate how |
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embedded, CPS, IoT, and edge applications benefit from machine learning. |
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3. |
Record Nr. |
UNINA9910709900203321 |
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Autore |
Scott Kevin M. <1935-> |
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Titolo |
Sedimentology, behavior, and hazards of debris flows at Mount Rainier, Washington / / by K.M. Scott, J.W. Vallance, and P.T. Pringle |
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Pubbl/distr/stampa |
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Washington : , : U.S. Department of the Interior, U.S. Geological Survey, , 1995 |
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Descrizione fisica |
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1 online resource (vii, 56 pages) : illustrations, maps + + 1 plate |
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Collana |
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U.S. Geological Survey professional paper ; ; 1547 |
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Soggetti |
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Debris avalanches - Washington (State) - Rainier, Mount |
Lahars - Washington (State) - Rainier, Mount |
Volcanic hazard analysis - Washington (State) - Rainier, Mount |
Lahars |
Volcanic hazard analysis |
Rainier, Mount (Wash.) |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Title from title screen (viewed October 16, 2014). |
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Nota di bibliografia |
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Includes bibliographical references (pages 53-56). |
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