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Titlebook: Higher Education Learning Methodologies and Technologies Online; First International Daniel Burgos,Marta Cimitile,Christian M. Stracke Con

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書目名稱Higher Education Learning Methodologies and Technologies Online
副標(biāo)題First International
編輯Daniel Burgos,Marta Cimitile,Christian M. Stracke
視頻videohttp://file.papertrans.cn/427/426856/426856.mp4
叢書名稱Communications in Computer and Information Science
圖書封面Titlebook: Higher Education Learning Methodologies and Technologies Online; First International  Daniel Burgos,Marta Cimitile,Christian M. Stracke Con
描述This book constitutes the thoroughly refereed post-conference proceedings of the?First International Workshop?on Higher Education Learning Methodologies and Technologies Online,?HELMeTO 2019, held in Novedrate, Italy, in June 2019.?.The 15 revised full papers and 2 short papers presented were carefully reviewed and selected from a total of 39 submissions. The papers are organized in topical sections on online pedagogy and learning methodologies; learning technologies, data analytics and educational big data mining as well as their applications; the challenge of online sport and exercise sciences university programs..
出版日期Conference proceedings 2019
關(guān)鍵詞computer aided instruction; e-learning; higher education; learning algorithms; learning environments; lea
版次1
doihttps://doi.org/10.1007/978-3-030-31284-8
isbn_softcover978-3-030-31283-1
isbn_ebook978-3-030-31284-8Series ISSN 1865-0929 Series E-ISSN 1865-0937
issn_series 1865-0929
copyrightSpringer Nature Switzerland AG 2019
The information of publication is updating

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Loredana Perla,Laura Sara Agrati,Viviana Vincited by two 32x32 pressure sensor arrays (seat- and backrest), is classified according to features defined based on cornering driving situations. Experimental results verify an increased readiness to compensate lateral acceleration with increasing driving speed, but only beyond a certain driver speci
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Massimiliano Barattuccited by two 32x32 pressure sensor arrays (seat- and backrest), is classified according to features defined based on cornering driving situations. Experimental results verify an increased readiness to compensate lateral acceleration with increasing driving speed, but only beyond a certain driver speci
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Mario Giampaolo,Loretta Fabbrited by two 32x32 pressure sensor arrays (seat- and backrest), is classified according to features defined based on cornering driving situations. Experimental results verify an increased readiness to compensate lateral acceleration with increasing driving speed, but only beyond a certain driver speci
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Consuelo Garcia,Jesús Privadoted by two 32x32 pressure sensor arrays (seat- and backrest), is classified according to features defined based on cornering driving situations. Experimental results verify an increased readiness to compensate lateral acceleration with increasing driving speed, but only beyond a certain driver speci
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e benefits of the individual implementations and show how both approaches can be used to establish code compatibility between different heterogeneous, reconfigurable, and parallel architectures. Further we will show, that both approaches are exposing an insignificant overhead.
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