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Titlebook: Morality and Justice; An Introduction John-Stewart Gordon Textbook 2024 The Editor(s) (if applicable) and The Author(s), under exclusive li

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樓主: Intimidate
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發(fā)表于 2025-3-25 06:14:07 | 只看該作者
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發(fā)表于 2025-3-25 08:27:46 | 只看該作者
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發(fā)表于 2025-3-25 11:48:53 | 只看該作者
Beyond 2020: Network Abundance, Data, and the Future of Organizing,es the factors that lead to change and disruption in the accelucted enterprise. This includes the emergence of networked abundance that goes beyond the Internet of Things. More generally, this chapter redefines the future as an asset for enterprises; it examines the impact of the various dimensions
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發(fā)表于 2025-3-25 16:19:56 | 只看該作者
Real Exchange Rate Policies for Economic Development: A Heterodox Interpretation in the recent experience of economic development. They have relied upon managed trade and targeted industrial policies to an extent that is not readily reconcilable with conventional views of development economics. Meanwhile, in developed countries latent tendencies for intervention and protectioni
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發(fā)表于 2025-3-25 21:04:34 | 只看該作者
Towards Ethical Judicial Analytics: Assessing Readability of Immigration and Asylum Decisions in the United Kingdomens of an assessment of readability of written judicial decisions. To that end the paper aims 1) to review and reproduce for the UK context previous work that assesses readability of legal texts, and 2) to reflect critically on the ethical implications of applied judicial analytics. Focusing on the
26#
發(fā)表于 2025-3-26 01:55:17 | 只看該作者
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發(fā)表于 2025-3-26 08:18:28 | 只看該作者
Edward Fursdon M.B.E., M.Litt., Ph.D.-Based Models can be used, as a mathematical tool, to analyse malware propagation. In this work, an ABM is created from three main elements: agents, environment and rules. This article presents a review of an agent-based model to simulate malware spreading in wireless sensor networks.
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發(fā)表于 2025-3-26 09:18:31 | 只看該作者
29#
發(fā)表于 2025-3-26 15:48:01 | 只看該作者
Automatic Segmentation and Classification of Thyroid Nodules in Ultrasound Images with Convolutional in segmentation task, and average F1 score of 83.22% in classification task. Finally, our method ranks the first place of segmentation task on the test set through the final online verification. The source code of the proposed methods is available at ..
30#
發(fā)表于 2025-3-26 19:50:11 | 只看該作者
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