Dataset for Fine-Tuning Code Generation Models: Kannada-English Algorithmic Statements and Python Code حسب Goutami Sooda (20714729)

The method for determining the chemical constituents of unknown materials in the algorithm. حسب Dong Hyeok Choi (12562048)

Data and code resources. حسب Sam Hall-McMaster (10343795)

Review of recent relevant studies along with the present study. حسب Kuiyuan Pan (21145338)

The relevant data file for this article. حسب Linsha Liu (20378293)

Relevant Parameters. حسب Dongyan Wang (195482)

Scatter diagram of different principal elements. حسب Jizhong Wang (7441697)

Calculation algorithm implementing the proposed model. حسب Landry Djopkop Kouanang (17131748)

Calculation algorithm implementing the proposed model. حسب Landry Djopkop Kouanang (17131748)

The parameter setting of the evolutionary neural network. حسب Wenbing Shi (5806160)

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The genome coding scheme. حسب Wenbing Shi (5806160)

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The relevant code used in this study. حسب Jiaxin Jiang (10656134)

Algorithmic experimental parameter design. حسب 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.…"

Element model generation method with geometric distribution errors حسب 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. …"

Spatial spectrum estimation for three algorithms. حسب 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.…"

The optimal number of clusters identified using the GMM clustering algorithm. حسب Dinh K. Tang (20469082)

Optimal number of clusters identified using the GMM clustering algorithm. حسب Dinh K. Tang (20469082)

Comparison of PSNR values of different algorithms. حسب Xiaojun Wang (50332)

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Changes in FID values of different algorithms. حسب Xiaojun Wang (50332)

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Comparison of SSIM values of different algorithms. حسب Xiaojun Wang (50332)

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