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Titlebook: Zielprognosen der Stadtentwicklung; Untersuchung am Beis Karl-Heinz Dehler Book 1976 Bundesinstitut für Bev?lkerungsforschung, Wiesbaden 19

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發(fā)表于 2025-3-23 12:06:49 | 只看該作者
https://doi.org/10.1007/978-981-10-4953-8Labour Ward; High risk pregnancy; Problems in obstetrics; Reduction in maternal mortality; Timely medica
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發(fā)表于 2025-3-23 13:58:53 | 只看該作者
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發(fā)表于 2025-3-23 20:31:51 | 只看該作者
Implementing a TMase locking protocol. We then describe a more sophisticated TM algorithm that better reflects most recent TM implementations. We discuss its advantages and issues as compared to “bare” 2-phase locking TM. Finally, we give an overview of common implementation techniques that go beyond the two TM algorithms we present in this chapter.
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發(fā)表于 2025-3-23 23:30:15 | 只看該作者
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發(fā)表于 2025-3-24 02:29:55 | 只看該作者
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發(fā)表于 2025-3-24 09:07:42 | 只看該作者
Aveek Dutta,Dola Saha,Dirk Grunwald,Douglas Sickerkus, die als eigenst?ndige Bereiche r?umlich au?erhalb von Konzernzentralen und Firmenniederlassungen etabliert worden sind. In dieser ersten Gruppe von Beispielen der Unternehmen Xerox, Google, Cisco Systems, BASF, Merck, Ikea, Procter & Gamble und SAP überwiegen die gestaltenden Think Tanks, bei d
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發(fā)表于 2025-3-24 11:39:36 | 只看該作者
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發(fā)表于 2025-3-24 16:52:27 | 只看該作者
Rong Wang,Brian T. Chaitd use cases of intelligent buildings in the context of smart city concept will be addressed—describing also the intended interaction with the primer users: (1) citizens, (2) residents either as home owners or tenants and (3) occupants in commercial and public buildings. Smart and user-oriented envir
19#
發(fā)表于 2025-3-24 22:24:23 | 只看該作者
Xiaogang Yu,Qi Wangpowerful approach to probabilistic modelling is to represent the observed variables in terms of a number of hidden, or latent, variables. One well-known example of a hidden variable model is the mixture distribution in which the hidden variable is the discrete component label. In the case of continu
20#
發(fā)表于 2025-3-25 03:06:58 | 只看該作者
Kit C. Chane a detailed account of some recent devel- ments in the ?eld of probability and statistics for dependent data. It covers a wide range of topics from Markov chains theory, weak dependence, dynamical system to strong dependence and their applications. The title of this book has been somehow borrowed f
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