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Titlebook: Papers and Correspondence of William Stanley Jevons; Volume 3: Correspond R. D. Collison Black Book 1977 Palgrave Macmillan, a division of

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樓主: deteriorate
21#
發(fā)表于 2025-3-25 06:56:25 | 只看該作者
22#
發(fā)表于 2025-3-25 09:27:25 | 只看該作者
QSAR/QSPR as an Application of Artificial Neural Networks,be and predict a particular activity/property of compounds. On the other hand, the Artificial Neural Network (ANN) is a tool that emulates the human brain to solve very complex problems. The exponential need for new compounds in the drug industry requires alternatives for experimental methods to dec
23#
發(fā)表于 2025-3-25 13:26:08 | 只看該作者
Benign Diseases of the Female Genital Tractngs are indeterminate, further evaluation is typically performed with magnetic resonance imaging (MRI), due to its excellent softtissue differentiation, multiplanar capabilities, and absence of ionizing radiation. MRI is thus well suited for imaging women of reproductive age, particularly during pre
24#
發(fā)表于 2025-3-25 15:58:47 | 只看該作者
25#
發(fā)表于 2025-3-25 20:16:53 | 只看該作者
26#
發(fā)表于 2025-3-26 03:02:53 | 只看該作者
27#
發(fā)表于 2025-3-26 06:09:37 | 只看該作者
28#
發(fā)表于 2025-3-26 11:20:24 | 只看該作者
Search Interfaces for Mathematiciansned people (ranging from senior professional mathematicians to non-mathematicians). From the interview data we elicited patterns for the user group “mathematicians” that can be applied when understanding design issues or creating new designs for mathematical search interfaces.
29#
發(fā)表于 2025-3-26 14:13:03 | 只看該作者
Stronger Reduction Criteria for Local First Searchlation to the previously established criterion, and discuss the algorithmics of the proposed improvement. Our contribution is both fundamental in providing better insights into LFS and practical in providing an improvement of high potential, as is illustrated by experimental results.
30#
發(fā)表于 2025-3-26 18:04:51 | 只看該作者
H.-D. Bolte,TH. v. Arnim,U. Tebbe,E. Erdmannues into the sensors themselves to analyze data in real time presents a promising solution. The objective of this work is to demonstrate edge computing for frequency-based structural health monitoring techniques to showcase the effectiveness of on-device data processing for the rapid assessment of i
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