抛弃的货物
发表于 2025-3-26 21:45:51
Preeti Agrawal,Akash Patole,Yogesh Patil,Parminder Kaur
HPA533
发表于 2025-3-27 03:28:18
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衰老
发表于 2025-3-27 08:14:14
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ETHER
发表于 2025-3-27 12:18:23
D. R. Pratheeksha,R. P. Shreya Reddy,R. Jayashree This Academy is recognized worldwide to represent the highest standards in research on production engineering, which includes design, optimization, control, management of processes, machines, and systems. One key concept behind this Encyclopedia is that apart from covering fundamental concepts in t
mosque
发表于 2025-3-27 14:49:56
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Melanocytes
发表于 2025-3-27 20:50:47
Correlation Between Code Smells for Open Source Java Projects,eliver the product on time and without faults. Looking at applications built for bugs, and thus minimizing the faults becomes tedious. Different researchers have extensively studied the maintenance of software and prediction of vulnerabilities. Code smells, and bug prediction is one way to find and
deciduous
发表于 2025-3-27 23:09:53
Throughput Improvement in Energy Efficient Heterogeneous Wireless Sensor Network, node failure. An Energy Efficient Clustering (EEC) algorithm is proposed by combining the rotation based clustering and energy saving scheme for avoiding the node failure and prolonging the network lifetime. In EEC, network is partitioned in to clusters and cluster head is selected on rotation base
Entropion
发表于 2025-3-28 05:56:50
,Deep Learning Models for Rubik’s Cube with Entropy Modelling,ly one terminal state. Recently, there are few contemporary solutions to solve Rubik cube which exploit Machine Learning Techniques. Our goal is to explore and generate Reinforcement Learning, CNN and LSTM techniques for sequence learning of Rubik cube solution with entropy modelling. The entropy is
acquisition
发表于 2025-3-28 09:18:03
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勤劳
发表于 2025-3-28 13:24:45
,Restoration of Rician Corrupted MR Data Using Improved Hybrid Model,median filter are pre and post stages respectively. The results were calculated using standard parameters like PSNR, SSIM and RMSE. It was found that the hybrid mm gives acceptable results when compared with standard non-linear filters when applied to T1 weighted Thorax Images. For Brain MR Images,