Malik, G.K., Nainwal, A., Amrish, Bijalwan, V., Semwal, V.B. (2023). Arm Fracture Detection Using Deep Convolution Neural Network. In: Nayak, R.K., Pradhan, M.K., Mandal, A., Davim, J.P. (eds) Recent Advances in Materials and Manufacturing Technology. ICAMMT 2022. Lecture Notes in Mechanical Engineering. Springer, Singapore. https://doi.org/10.1007/978-981-99-2921-4_19

Sain, M. K., Singha, J., & Bijalwan, V. (2023, May). Dynamic Hand Gesture Recognition Using mYOLO-CSRT and HGCNN for Human–Machine Interaction. In Machine Intelligence Techniques for Data Analysis and Signal Processing: Proceedings of the 4th International Conference MISP 2022, Volume 1 (pp. 631-642). Singapore: Springer Nature Singapore.

Anzola, J., Jiménez, A., Espada, J. P., Semwal, V. B., & Bijalwan, V. (2017). Analysis of TCP streaming over VANETs. In RICE (pp. 39-43).

Bijalwan, V., Kumari, P., Pascual, J., & Semwal, V. B. (2014). Machine learning approach for text and document mining. arXiv preprint arXiv:1406.1580.

Bijalwan, V., Kumar, V., Kumari, P., & Pascual, J. (2014). KNN based Machine Learning Approach for Text and Document Mining. International Journal of Database Theory and Application, 7(1), 61-70.

Semwal, V. B., Mazumdar, A., Jha, A., Gaud, N., & Bijalwan, V. (2021). Speed, cloth and pose invariant gait recognition-based person identification. In Machine learning: theoretical foundations and practical applications (pp. 39-56). Singapore: Springer Singapore.

H. Baek, A. M. Khan, V. Bijalwan, and Y. Kim, “Shape Memory Alloy Based Soft Gripper,” ser. Information Storage and Processing Systems, vol. ASME 2023 32nd Conference on Information Storage and Processing Systems, Aug. 2023, V001T07A001. doi: 10.1115/ISPS2023-109566. eprint: https://asmedigitalcollection.asme.org/ISPS/proceedings- pdf/ISPS2023/87219/V001T07A001/7047215/v001t07a001-isps2023-109566.pdf. 2

Hangyeol Baek ,Abdul Manan Khan, Vishwanath Bijalwan,and Youngshik Kim, “Tensegrity-inspired Multi-axis Positioning SMA Actuator”, Accepted for presentation at 2023 IEEE International Symposium on Robotic and Sensors Environments (ROSE) Hosei University, Tokyo, Japan.

Sangmin Jeon , Vishwanath Bijalwan,and Youngshik Kim, “Design of an SMA-based flat actuator with a pat- tern inspired by Amphibian lungs’”, Accepted for presentation at 2023 IEEE International Symposium on Robotic and Sensors Environments (ROSE) Hosei University, Tokyo, Japan.

M. Sati, V. Vikash, V. Bijalwan, et al., “A fault-tolerant mobile computing model based on scalable replica,” IJIMAI, vol. 2, no. 6, pp. 58–68, 2014.

V. Bijalwan, V. Kumar, P. Kumari, and J. Pascual, “Knn based machine learning approach for text and document mining,” International Journal of Database Theory and Application, vol. 7, no. 1, pp. 61–70, 2014.

V. Bijalwan et al., “Machine learning approach for text and document mining." arxiv preprint,” arXiv preprint arXiv:1406.1580, 2014.

V. Mehta, D. Punetha, and V. Bijalwan, “A real-time approach to theft prevention in the field of transportation system,” 2016 IJIMAI

P. Bagwari, B. Saxena, M. Balodhi, and V. Bijalwan, “Comparison of feedforward network and radial basis function to detect leukemia,” International Journal of Interactive Multimedia and Artificial Intelligence, vol. 4, no. 5, p. 55, 2017. doi: 10.9781/ijimai.2017.4510.

V. B. Semwal, P. Lalwani, M. K. Mishra, V. Bijalwan, and J. S. Chadha, “An optimized feature selection using bio-geography optimization technique for human walking activities recognition,” Computing, vol. 103, no. 12, pp. 2893–2914, 2021.

V. Bijalwan, V. B. Semwal, and T. Mandal, “Fusion of multi-sensor-based biomechanical gait analysis using vision and wearable sensor,” IEEE Sensors Journal, vol. 21, no. 13, pp. 14 213–14 220, 2021.

V. B. Semwal, N. Gaud, P. Lalwani, V. Bijalwan, and A. K. Alok, “Pattern identification of different human joints for different human walking styles using inertial measurement unit (imu) sensor,” Artificial Intelligence Review, vol. 55, no. 2, pp. 1149–1169, 2022.

V. Bijalwan, V. B. Semwal, G. Singh, and R. G. Crespo, “Heterogeneous computing model for post-injury walking pattern restoration and postural stability rehabilitation exercise recognition,” Expert Systems, vol. 39, no. 6, e12706, 2022.

V. Bijalwan, V. B. Semwal, and V. Gupta, “Wearable sensor-based pattern mining for human activity recognition: Deep learning approach,” Industrial Robot: the international journal of robotics research and application, vol. 49, no. 1, pp. 21–33, 2022.

V. B. Semwal, Y. Kim, V. Bijalwan, et al., “Development of the lstm model and universal polynomial equation for all the sub-phases of human gait,” IEEE Sensors Journal, vol. 23, no. 14, pp. 15 892–15 900, 2023. doi: 10.1109/JSEN.2023.3281401

A. M. Khan, V. Bijalwan, B. Shin, and Y. Kim, “Adaptive neural network control design and analysis for SMA actuators having dominant shape memory effect,” Sensors and actuators: A physical, 2023

A. M. Khan, V. Bijalwan, H. Baek, B. Shin, and Y. Kim, “Integral sliding mode control (ismc) with an extended state Observer (eso) for an arc-shaped memory alloy actuator,” Microsystem Technologies, Aug. 2023, issn: 1432-1858. doi: 10.1007/s00542-023-05516-8.

V. Bijalwan, V. B. Semwal, G. Singh, and T. K. Mandal, “Hdl-Psr: Modelling spatio-temporal features using hybrid deep learning approach for post-stroke rehabilitation,” Neural Processing Letters, vol. 55, no. 1, pp. 279–298, 2023.

H. Baek, N. A. Mansour, A. M. Khan, V. Bijalwan, H. F. Ali, and Y. Kim, “Sma-based caterpillar robot using antagonistic actuation,” Microsystem Technologies, pp. 1–15, 2023.

H. Baek, A. M. Khan, V. Bijalwan, S. Jeon and Y. Kim, "Dexterous Robotic Hand Based on Rotational Shape Memory Alloy Actuator-Joints," in IEEE Transactions on Medical Robotics and Bionics, vol. 5, no. 4, pp. 1082-1092, Nov. 2023, doi: 10.1109/TMRB.2023.3315783.