Achievements of Rseslib KNN reported in independent reviewed publications

Rank Out of Task Reference
1
9
Environmental sound recognition Grama, L., & Rusu, C. (2017). Choosing an accurate number of mel frequency cepstral coefficients for audio classification purpose. In Proceedings of the 10th International Symposium on Image and Signal Processing and Analysis (pp. 225-230). IEEE.
2
8
Acoustic-based environment monitoring Rusu, C., & Grama, L. (2017). Recent developments in acoustical signal classification for monitoring. In 2017 5th International Symposium on Electrical and Electronics Engineering (ISEEE) (pp. 1-10). IEEE.
1
21
Facebook content recognition Dey, N., Borah, S., Babo, R., & Ashour, A. (2018). Social network analytics: computational research methods and techniques. Academic Press.
2
8
Context awareness of a service robot Grama, L., & Rusu, C. (2018). Adding audio capabilities to TIAGo service robot. In 2018 International Symposium on Electronics and Telecommunications (ISETC) (pp. 1-4). IEEE.
5
47
Student performance prediction Almasri, A., Celebi, E., & Alkhawaldeh, R. S. (2019). EMT: Ensemble meta-based tree model for predicting student performance. Scientific Programming, 2019.
2
47
Metabolic pathway prediction of plant enzymes de Oliveira Almeida, R., & Valente, G. T. (2020). Predicting metabolic pathways of plant enzymes without using sequence similarity: Models from machine learning. In The Plant Genome (Vol. 13, Issue 3). Wiley.
2
13
Phlebopathic patient screening D'Angelantonio, E., Lucangeli, L., Camomilla, V., & Pallotti, A. (2022). Smart sock-based machine learning models development for phlebopathic patient screening. IEEE International Workshop on Metrology for Industry 4.0 & IoT (MetroInd4.0&IoT) (pp. 137-142). IEEE.
2
5
Student performance prediction Niu, K., Jia, B. T., Zou, Y. H., & Lu, G. Q. (2022). A hybrid model for predicting academic performance of engineering undergraduates. International Journal of Modeling, Simulation, and Scientific Computing (Vol. 14, No. 02, 2350030).
2
10
Gait analysis for rehabilitation planning Galasso, S., Baptista, R., Molinara, M., Pizzocaro, S., Calabro, R. S., & De Nunzio, A. M. (2023). Predicting physical activity levels from kinematic gait data using machine learning techniques. Engineering Applications of Artificial Intelligence (Vol. 123, 106487).

Achievements of Local KNN reported in independent reviewed publications

Rank Out of Task Reference
5
47
Student performance prediction Almasri, A., Celebi, E., & Alkhawaldeh, R. S. (2019). EMT: Ensemble meta-based tree model for predicting student performance. Scientific Programming, 2019.
1
18
Driver stress prediction Al-Nashashibi, M. Y., El-Khalili, N., Hadi, W., Al-Banna, A. K., & Issa, G. (2023). Identifying the most significant features for stress prediction of automobile drivers: a comprehensive study. Journal of Information & Knowledge Management (2350064).
1
5
Clutch fault diagnosis Nair, S., Sridharan, N. V., Chakrapani, G., & Vaithiyanathan, S. (2024). Automotive clutch fault diagnosis through feature fusion and lazy family of classifiers. Journal of Vibration Engineering & Technologies, 2024 (pp. 1-14).

Achievements of Rough Set classifier reported in independent reviewed publications

Rank Out of Task Reference
1
5
Hotel quality prediction Cheng, C. H., Tsai, M. C., & Chang, Y. S. (2023). The relationship between hotel star rating and website information quality based on visual presentation. PLOS ONE (Vol. 18, No. 11, e0290629).