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11篇 您的检索式:作者名="Kevin Page"
    题名 作者 年代 出处 被引量
1Changes in Climate Extremes Over the Australian Region and New Zealand During the Twentieth Century显示文摘Neil Plummer M. James Salinger Neville Nicholls Ramasamy Suppiah Kevin J. Hennessy Robert M. Leighton Blair Trewin Cher M. Page Janice M. Lough 1999Climatic Change1999,,1:2
2QT interval prolongation and the risk of torsades de pointes: essentials for clinicians显示文摘Katy E. Trinkley Robert Lee Page Hoang Lien Kevin Yamanouye James E. Tisdale 2013Current Medical Research & Opinion2013,,:1
3Hybridization in freshwater fishes:a review of case studies and cytonuclear methods of biological inference显示文摘SCRIBNER KIM T PAGE KEVIN S BARTRON MEREDITH L 2001Review in Fish Biology and Fisheries2001,10,:1
4The Global Boundary Stratotype Section and Point (GSSP) for the base of the Pliensbachian Stage (Lower Jurassic), Wine Haven, Yorkshire, UK显示文摘Christian Meister Martin Aberhan Joachim Blau Jean-Louis Dommergues Susanne Feist-Burkhardt Ernie A. Hailwood Malcom Hart Stephen P. Hesselbos Mark W. Hounslow Mark Hylton Nicol Morton Kevin Page Greg D. Price 2006Episodes2006,29,2:1
5Cyber risk at the edge:current and future trends on cyber risk analytics and artificial intelligence in the industrial internet of things and industry 4.0 supply chains显示文摘Digital technologies have changed the way supply chain operations are structured.In this article,we conduct systematic syntheses of literature on the impact of new technologies on supply chains and the related cyber risks.A taxonomic/cladistic approach is used for the evaluations of progress in the area of supply chain integration in the Industrial Internet of Things and Industry 4.0,with a specific focus on the mitigation of cyber risks.An analytical framework is presented,based on a critical assessment with respect to issues related to new types of cyber risk and the integration of supply chains with new technologies.This paper identifies a dynamic and self-adapting supply chain system supported with Artificial Intelligence and Machine Learning(AI/ML)and real-time intelligence for predictive cyber risk analytics.The system is integrated into a cognition engine that enables predictive cyber risk analytics with real-time intelligence from IoT networks at the edge.This enhances capacities and assist in the creation of a comprehensive understanding of the opportunities and threats that arise when edge computing nodes are deployed,and when AI/ML technologies are migrated to the periphery of IoT networks.Petar Radanliev David De Roure Kevin Page Jason R.C.Nurse Rafael Mantilla Montalvo Omar Santos La’Treall Maddox Pete Burnap 2020Cybersecurity2020,3,1:1
6Changes in Climate Extremes Over the Australian Region and New Zealand During the Twentieth Century显示文摘Neil Plummer M. James Salinger Neville Nicholls Ramasamy Suppiah Kevin J. Hennessy Robert M. Leighton Blair Trewin Cher M. Page Janice M. Lough 1999Climatic Change1999,,1:1
7Hybridization in freshwater fishes: a review of case studies and cytonuclear methods of biological inference显示文摘Kim T. Scribner Kevin S. Page Meredith L. Bartron 2000Reviews in Fish Biology and Fisheries2000,,3:1
8Changes in the Probability of Heavy Precipitation: Important Indicators of Climatic Change显示文摘Pavel Ya. Groisman Thomas R. Karl David R. Easterling Richard W. Knight Paul F. Jamason Kevin J. Hennessy Ramasamy Suppiah Cher M. Page Joanna Wibig Krzysztof Fortuniak Vyacheslav N. Razuvaev Arthur Douglas Eirik F?rland Pan-Mao Zhai 1999Climatic Change1999,,1:1
9Hybridization in freshwater fishes : a review of case studies and cytonuclear methods of biological inference显示文摘Scribner Kim T Page Kevin S Bartron M L 2001Reviews in Fish Biology and Fisheries2001,10,:1
10Cyber risk at the edge:current and future trends on cyber risk analytics and artificial intelligence in the industrial internet of things and industry 4.0 supply chains显示文摘Digital technologies have changed the way supply chain operations are structured.In this article,we conduct systematic syntheses of literature on the impact of new technologies on supply chains and the related cyber risks.A taxonomic/cladistic approach is used for the evaluations of progress in the area of supply chain integration in the Industrial Internet of Things and Industry 4.0,with a specific focus on the mitigation of cyber risks.An analytical framework is presented,based on a critical assessment with respect to issues related to new types of cyber risk and the integration of supply chains with new technologies.This paper identifies a dynamic and self-adapting supply chain system supported with Artificial Intelligence and Machine Learning(AI/ML)and real-time intelligence for predictive cyber risk analytics.The system is integrated into a cognition engine that enables predictive cyber risk analytics with real-time intelligence from IoT networks at the edge.This enhances capacities and assist in the creation of a comprehensive understanding of the opportunities and threats that arise when edge computing nodes are deployed,and when AI/ML technologies are migrated to the periphery of IoT networks.Petar Radanliev David De Roure Kevin Page Jason R.C.Nurse Rafael Mantilla Montalvo Omar Santos La’Treall Maddox Pete Burnap 2018Cybersecurity2018,1,1:0
11十大体育高难度动作显示文摘本文是一篇体育报道,文中涉及了 较多的体育术语和英制度量衡。在 此,小编列出换算公式供大家参 考:1英里=1.609千米、1英尺 =0.305米、1英寸=2.54厘 米、1磅:0.Kevin Page 方嘉乐 2006疯狂英语(初中天地)2006,,1:0
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