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Titlebook: Innovative Data Communication Technologies and Application; Proceedings of ICIDC Jennifer S. Raj,Khaled Kamel,Pavel Lafata Conference proce

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樓主: T-cell
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發(fā)表于 2025-3-23 12:16:09 | 只看該作者
Innovative Data Communication Technologies and ApplicationProceedings of ICIDC
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發(fā)表于 2025-3-23 16:16:34 | 只看該作者
S. Harini,Aswathy Ravikumar,Nailesh Keshwanilett, Dr. Heinrich Kersten Vorwort zur 1. Auflage Das vorliegende Buch richtet sich an Leser, die sich in das int- essante Gebiet der Informationssicherheit einarbeiten m?chten. Dieses Gebiet ist z. T. unter anderen überschriften wie IT-Sich- heit (IT Security), Datensic978-3-8348-9239-3Series ISSN 2522-0551 Series E-ISSN 2522-056X
13#
發(fā)表于 2025-3-23 18:31:59 | 只看該作者
M. C. S. Sreejitha,P. Sai Priyanka,S. Meghana,Nalini Sampathlett, Dr. Heinrich Kersten Vorwort zur 1. Auflage Das vorliegende Buch richtet sich an Leser, die sich in das int- essante Gebiet der Informationssicherheit einarbeiten m?chten. Dieses Gebiet ist z. T. unter anderen überschriften wie IT-Sich- heit (IT Security), Datensic978-3-8348-9239-3Series ISSN 2522-0551 Series E-ISSN 2522-056X
14#
發(fā)表于 2025-3-24 00:18:20 | 只看該作者
15#
發(fā)表于 2025-3-24 02:37:35 | 只看該作者
Wrapper-Naive Bayes Approach to Perform Efficient Customer Behavior Prediction,one-dependence estimators, correlation-based feature weighting NB, NBTREE, and DTNB. Experimental results divulge the variable selection with NB achieves higher accuracy of 86.8116 and 86.087 customer prediction compared to other existing approaches like standard Naive Bayes, averaged one-dependence
16#
發(fā)表于 2025-3-24 09:44:22 | 只看該作者
Enhanced Security of User Authentication on Doctor E-Appointment System,aff. This proposed technique solved existing methods and improved user authentication within a healthcare system. Our proposed method provides an effective and secure outpatient appointment queuing model for appropriate appointment scheduling, reducing patient wait times, doctors’ idle time, and ove
17#
發(fā)表于 2025-3-24 11:46:32 | 只看該作者
18#
發(fā)表于 2025-3-24 16:51:01 | 只看該作者
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發(fā)表于 2025-3-24 21:04:47 | 只看該作者
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發(fā)表于 2025-3-25 01:00:54 | 只看該作者
An Efficient Email Spam Detection Utilizing Machine Learning Approaches,lassifier execution and length of the selected highlight vector as a classifier input are considered for executing the assessment by utilizing UCI spambase dataset. Exploratory outcomes show that the PSO-based element choice calculation was introduced to create incredible component determination res
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