<b>Robot_gripper_design</b> by Ma Haohao (19780875)

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Prime Number Source Code with Dataset by Ayman Mostafa (19839867)

The lowest reconstruction errors and optimal parameters of the five algorithms. by Jing Wang (6206297)

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The highest classification accuracies and optimal parameters of the five algorithms. by Jing Wang (6206297)

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Source code, protocol, and Input/Output data. from Towards an information theoretic framework for MSA sub-sampling by Christopher Barrett (206055)

Reconstruction errors of the five algorithms with different numbers of projection vectors. by Jing Wang (6206297)

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Comparison of grayscale conversion algorithms. by Tianke Fang (22648035)

Comparison of noise reduction algorithms. by Tianke Fang (22648035)

The reconstruction error and classification accuracy of the five algorithms on the six face databases. by Jing Wang (6206297)

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Convergence curve of the DBO algorithm. by Ma Haohao (22177538)

“…The improved Dung Beetle Optimization algorithm, Back Propagation Neural Network, Finite Element Analysis, and Response Surface Methodology provide a strong guarantee for the selection of robot polishing process parameters. …”

Element model generation method with geometric distribution errors by Yiqi Liu (21357815)

“…The product surface geometric distribution error is directly attached to the element nodes of the product ideal element model using the error surface reconstruction method and the replacement algorithm of the element node vector height based on the product’s point cloud data. …”

Investigation on the accuracy and convergence speed of different swarm optimization algorithms. by Zixi Wang (459102)

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File includes code "Transfer learning.R" and "updatebeta.cpp" for implementing transfer learning methods. by Lulu Pan (8977979)

Flowchart of hybrid genetic algorithm combining simulated annealing and greedy methods. by Zixi Wang (459102)

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Performance of machine learning algorithms. by Wenxue Liu (6877754)

Algorithmic experimental parameter design. by Chuanxi Xing (20141665)

“…Furthermore, the estimation of the DOA can be accurately carried out under low signal-to-noise ratio conditions. This method effectively utilizes the degrees of freedom provided by the virtual array, reducing noise interference, and exhibiting better performance in terms of positioning accuracy and algorithm stability.…”

Spatial spectrum of the 100th frame under array distortion conditions (20 elements). by Gaoxiang Xing (21755689)

ML algorithms in cyber security. by Abdullah Asım Yılmaz (20715311)

Schematic diagram of the end iterations of the genetic solution after the calculation of the greedy algorithm. by Zixi Wang (459102)

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Schematic diagram of the end iteration of the genetic solution after the calculation of the greedy algorithm. by Zixi Wang (459102)

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