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Titlebook: Recent Trends in Information and Communication Technology; Proceedings of the 2 Faisal Saeed,Nadhmi Gazem,Fathey Mohammed Conference procee

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樓主: 閃爍
41#
發(fā)表于 2025-3-28 17:54:16 | 只看該作者
Experimental Performance Analysis of B+-Trees with Big Data Indexing PotentialsPartitioned Simple Prefix B+-tree. In the experiment, factors for index approach evaluation are used to evaluate and compare the performance of the data structures. The experimental results showed that Partitioned B+-tree has in sum performed better in terms of execution time than the remaining B+-t
42#
發(fā)表于 2025-3-28 22:43:17 | 只看該作者
43#
發(fā)表于 2025-3-29 00:41:32 | 只看該作者
44#
發(fā)表于 2025-3-29 05:59:37 | 只看該作者
Mobile Augmented Reality Tourism Application Frameworked are according to their needs and expectations. Descriptive and factor analysis were used to analyze the data. Based on the results, the components proposed have a high-reliability index, indicating that the components are acceptable. The findings provide a foundation into constructing mobile augm
45#
發(fā)表于 2025-3-29 09:33:34 | 只看該作者
Adaptive Memory Size Based Fuzzy Control for Mobile Pedestrian Navigationrent particle filter development processes. At the beginning of the operational process, the AMSFC selector is used to select a suitable resampling algorithm (for example, systematic resampling or rounding copy resampling) based on the physical memory of current computing devices. If systematic resa
46#
發(fā)表于 2025-3-29 13:09:34 | 只看該作者
47#
發(fā)表于 2025-3-29 16:26:17 | 只看該作者
Hasanin Mohammed Salman,Wan Fatimah Wan Ahmad,Suziah Sulaimanitten in an essayistic, readable style, which can be understood as an experimental form of writing..This book is a translation of the doctoral thesis ‘Experiment und Exploration. Bildung als experimentelle Form978-94-024-0056-4978-94-017-8709-3Series ISSN 2214-9759 Series E-ISSN 2214-9767
48#
發(fā)表于 2025-3-29 20:38:30 | 只看該作者
49#
發(fā)表于 2025-3-30 00:10:03 | 只看該作者
Prediction of Financial Distress for Electricity Sectors Using Data Miningd financial distress warning models based on the financial statement analysis method. The analysis reveal that neural networks with the accuracy of 80% and above in different scenarios were found to be relatively more accurate compared to decision trees and support vector machines. Additionally, in
50#
發(fā)表于 2025-3-30 07:45:51 | 只看該作者
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