Mobile QR Code QR CODE

2024

Acceptance Ratio

21%

REFERENCES

1 
Y. Han and W. Yin, ``The effect of multimedia teaching platform based on virtual technology on students' English learning motivation,'' International Journal of Electrical Engineering Education, vol. 7, no. 9, pp. 453-467, 2021DOI
2 
L. Wang, X. Jia, H. Cui, and B. Zhang, ``An interactive practice platform of English mobile teaching in colleges and universities based on open API,'' International Journal of Continuing Engineering Education and Life-long Learning, vol. 3, no. 2, pp. 78-89, 2022.DOI
3 
H. Mohanty, S. Champati, B. L. P. Barik, and A. Panda, ``Cluster quality analysis based on SVD, PCA-based k-means and NMF techniques: An online survey data,'' International Journal of Reasoning-based Intelligent Systems, vol. 15, no. 1, pp. 86-95, 2023.DOI
4 
Z. Li, C. Tang, X. Zheng, W. Zhang, and L. Cao, ``Unified K-means coupled self-representation and neighborhood kernel learning for clustering single-cell RNA-sequencing data,'' Neurocomputing, vol. 9, no. 11, pp. 89-101, 2022.DOI
5 
R. T. Philips, S. J. Torrisi, A. X. Gorka, and E. Monique, ``Dynamic time warping identifies functionally distinct fMRI resting state cortical networks specific to VTA and SNc: A proof of concept, Cerebral Cortex, vol. 6, pp. 6-17, 2021.DOI
6 
A. Das, A. Namtirtha, and A. Dutta, “Lévy–Cauchy arithmetic optimization algorithm combined with rough K-means for image segmentation,'' Applied Soft Computing, vol. 5, no. 6, pp. 345-362, 2023.DOI
7 
I. Nio-Adan, I. Landa-Torres, E. Portillo, and D. Manjarres, ``Influence of statistical feature normalisation methods on K-Nearest Neighbours and K-Means in the context of industry 4.0,'' Engineering Applications of Artificial Intelligence, vol. 111, no. 2, pp. 104-117, 2022.DOI
8 
X. Tian, L. Gai, Y. Xu, and G. Zhao, ``Approximation algorithms for spherical k-means problem with penalties using local search techniques,'' Asia-pacific Journal of Operational Research, vol. 8, no. 12, pp. 656-668, 2023.DOI
9 
H. Guo, B. Xu, S. Zhao, and Y. Yue, ``CUDA-based parallelization of time-weighted dynamic time warping algorithm for time series analysis of remote sensing data,'' Computers & Geosciences, vol. 7, no. 11 pp. 231-243, 2022.DOI
10 
Z. Chen and J. Gu, ``High-throughput dynamic time warping accelerator for time-series classification with pipelined mixed-signal time-domain computing,'' IEEE Journal of Solid-State Circuits, vol. 4, no. 9, pp. 16-27, 2020.DOI
11 
X. Hou and Z. Zhang, ``Multi-interaction English teaching platform based on internet of things,'' International Journal of Continuing Engineering Education and Life-long Learning, vol. 6, no. 3, pp. 67-78, 2022.DOI
12 
S. Chen, ``Design of internet of things online oral English teaching platform based on long-term and short-term memory network,'' International Journal of Continuing Engineering Education and Life-Long Learning, vol. 31, no. 1, pp. 104-115, 2021.DOI
13 
Z. Sun, M. Anbarasan, and D. P. Kumar, ``Design of online intelligent English teaching platform based on artificial intelligence techniques,'' Computational Intelligence, vol. 12, no. 1, pp. 233-245, 2020.DOI
14 
Y. Zhang, N. Li, and T. Zhou, ``Analysis of multimedia combination-assisted English teaching mode based on computer platform,'' Advances in Multimedia, vol. 9, no. 8, pp. 786-794, 2022.DOI
15 
M. Wang and Y. Wang, ``Research on English teaching information pushing method based on intelligent adaptive learning platform,'' International Journal of Continuing Engineering Education and Life-long Learning, vol. 2, pp. 31-45, 2021.DOI
16 
W. E. Alberth and L. Uden, ``Whats app with English language teaching? Some practical ideas and strategies,'' International Journal of Applied Mechanics, vol. 12, no. 3, pp. 123-136, 2020.DOI
17 
Y. Burstyn, A. Gazit, and O. Dvir, ``Hierarchical dynamic time warping methodology for aggregating multiple geological time series,'' Computers & Geosciences, vol. 150, no. 8, pp. 104-124, 2021.DOI
18 
C. J. Hagen, B. T. Reilly, J. S. Stoner, and J. R. Creveling, ``Dynamic time warping of palaeomagnetic secular variation data,'' Geophysical Journal International, vol. 1, pp. 23-34, 2020.DOI
19 
H. Li, ``Time works well: Dynamic time warping based on time weighting for time series data mining,'' Information Sciences, vol. 547, pp. 592-608, 2021.DOI
20 
S. Choudhuri, S. Adeniye, and A. Sen, ``Distribution alignment using complement entropy objective and adaptive consensus-based label Refinement for partial domain adaptation,'' Artificial Intelligence and Applications, vol. 1, no. 1, pp. 43-51, 2023.DOI