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Titlebook: Uncertainty in Entrepreneurial Decision Making; The Competitive Adva Panagiotis E. Petrakis,Dimitra P. Konstantakopoulo Book 2015 Palgrave

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樓主: deteriorate
11#
發(fā)表于 2025-3-23 09:59:40 | 只看該作者
e to the study of evolution and practical applications in the fields of medicine and plant and animal breeding. The more modern aspects of genetics, ., explore the biochemical pathways by which genes regulate the structure and metabolism of organisms. Bacteria, viruses and fungi are the chief organisms employed in biochemical genetics.
12#
發(fā)表于 2025-3-23 17:11:44 | 只看該作者
The Unknown Futureuture planning difficult or even impossible. However, change is very common. While some changes simply involve variations of existing trends, others are fundamental; change may even be destructive and result in devolution.
13#
發(fā)表于 2025-3-23 20:36:27 | 只看該作者
Entrepreneurship under Uncertaintyn making strategically important decisions. The importance, nature, and role of information exchanged, which can reduce uncertainty given proper evaluation of its reliability and the manner of its use, are particularly important for enterprises.
14#
發(fā)表于 2025-3-23 23:48:01 | 只看該作者
15#
發(fā)表于 2025-3-24 05:14:09 | 只看該作者
16#
發(fā)表于 2025-3-24 10:14:00 | 只看該作者
17#
發(fā)表于 2025-3-24 10:57:43 | 只看該作者
Panagiotis E. Petrakis,Dimitra P. Konstantakopoulouock extracting the lattice of most likely words using dynamic programming: this system “cut” corresponds to the minimal flow of data and besides separates blocks with different computational characteristics. The first block in fact is characterized by predictable execution times, cyclic computations
18#
發(fā)表于 2025-3-24 16:59:27 | 只看該作者
19#
發(fā)表于 2025-3-24 21:18:02 | 只看該作者
Panagiotis E. Petrakis,Dimitra P. Konstantakopoulou a new distance measure, (.) we introduce a search procedure for exceptional dynamic Bayesian networks optimized by properties of the proposed distance, and (.) the practical value of the proposed method is demonstrated based on simulated data and process data of funding applications and by comparis
20#
發(fā)表于 2025-3-25 01:47:26 | 只看該作者
an anomaly-free training subset. Relying on a contrastive learning-based robust loss function, RESIST automatically downweights atypical corrupted training data, to reduce their impact on the training optimization. Experiments on the CICIDS17 public benchmark dataset show an improved accuracy of ou
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