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Titlebook: Neurowissenschaften und Musikpädagogik; Klärungsversuche und Ludger Kowal-Summek Book 20171st edition Der/die Herausgeber bzw. der/die Auto

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Andrew Hinderliterfrom retail and service establishments to heavy manufacturers. Their sizes and revenues range from the smallest venture of a husband and wife roadside food stall in rural India to the largest multinational, highly diversified corporations in the United States and Europe. Many challenges, such as com
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Trisha Suppesing controversy in online discussions is a challenging task, but essential to stop these unhealthy behaviours..In this work, we develop a general pipeline to quantify controversy on social media through content analysis, and we widely test it on Twitter..Our approach can be outlined in four phases:
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TAM and E-learning Adoption: A Philosophical Scrutiny of TAM, Its Limitations, and Prescriptions forl holes as well as a number of limitations of TAM research have been pointed by several leading researchers in the recent years. In this paper, we discuss the philosophical holes and present our reflections and possible prescriptions about these holes while conducting research on e-learning adoption
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EC-ASEAN in the Context of Inter-regional Co-operation,lt integrated communities in order to play their part in the international system as one unit. In addition to the economic aspect, political reasons are of considerable significance. For many of the new regional groups the European Community (EC) seems to have become a model for regional economic Co
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https://doi.org/10.1007/978-1-4615-4701-3en thoroughly researched. This article addresses the need to develop a set of design principles, and presents some examples of these, through which the usability and longevity of reference models can be improved.
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Discovering and Loading Data with Get & Transform in Excel 2016,is using Excel 2016 without needing any other tools or utilities thanks to the Get & Transform function. What is more, you can feed the output from Get & Transform either into a spreadsheet (if the data is not too voluminous) or into the in-memory data model for larger—and even extremely large—data sets.
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