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Titlebook: Intelligent Systems Design and Applications; 22nd International C Ajith Abraham,Sabri Pllana,Anu Bajaj Conference proceedings 2023 The Edit

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樓主: Glycemic-Index
51#
發(fā)表于 2025-3-30 08:31:03 | 只看該作者
52#
發(fā)表于 2025-3-30 14:34:30 | 只看該作者
,A Rapid Review on?Ensemble Algorithms for?COVID-19 Classification Using Image-Based Exams,he rapid spread and high-level mortality. The illness led to the rapid development of a vaccine that we know can fight against the virus; however, we do not know the actual vaccine’s effectiveness. Thus, the early detection of the disease is still necessary to provide a suitable course of action. To
53#
發(fā)表于 2025-3-30 19:27:36 | 只看該作者
,Indian Postal Service Quality Assessment Using Graph Theoretic Approach – A Quantitative Decision-Mtaka state, Southern India. In the postal service industry, measuring SQ performance in mail service operations is a major challenge. So, this paper attempts to explore the positive effect of postal SQ factors on Customer Satisfaction (CS) with the data collected from employees (n?=?148) to the Indi
54#
發(fā)表于 2025-3-30 22:07:24 | 只看該作者
Analyzing the Critical Success Factors of Lean System Implementation in India Post Using DEMATEL Metory (DEMATEL) method. In this way, LS elements were grouped together into four different categories such as, Technical Practices (TPs), Workplace Environment Practices (WEPs), Social Practices (SPs), Ergonomic Practices (EPs) have been analyzed through field survey and suitable literature support.
55#
發(fā)表于 2025-3-31 04:36:07 | 只看該作者
Application of Artificial Intelligence in Mental Health,tance including agriculture, education, and economic development. It is a multidisciplinary field that aims to automate activities within a machine similar to that of human intelligence. This advancement has created a huge revolution in the medical field. Various machine learning algorithms for pred
56#
發(fā)表于 2025-3-31 07:34:06 | 只看該作者
Cold Rolling Mill Energy Consumption Prediction Using Machine Learning,een given to this important consumable throughout the years. Machine learning techniques are becoming extremely common in the steel industry due to the high level of automation of the segment and the large databases available. This work proposes a complete system capable of handling input data, trai
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發(fā)表于 2025-3-31 12:11:25 | 只看該作者
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發(fā)表于 2025-3-31 13:56:15 | 只看該作者
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發(fā)表于 2025-3-31 23:45:51 | 只看該作者
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