Items where Author is "Zahid, M.S.M."

Article

Husain, K. and Zahid, M.S.M. and Hassan, S.U. and Hasbullah, S. and Mandala, S. (2021) Advances of ECG sensors from hardware, software and format interoperability perspectives. Electronics (Switzerland), 10 (2). pp. 1-36.

Daha, M.Y. and Zahid, M.S.M. and Isyaku, B. and Alashhab, A.A. (2021) CDRA: A Community Detection based Routing Algorithm for Link Failure Recovery in Software Defined Networks. International Journal of Advanced Computer Science and Applications, 12 (11). pp. 712-722.

Abdullah, T.A.A. and Zahid, M.S.M. and Ali, W. (2021) A review of interpretable ml in healthcare: Taxonomy, applications, challenges, and future directions. Symmetry, 13 (12).

Abdullah, T.A.A. and Zahid, M.S.M. and Ali, W. (2021) A review of interpretable ml in healthcare: Taxonomy, applications, challenges, and future directions. Symmetry, 13 (12).

Isyaku, B. and Bakar, K.A. and Zahid, M.S.M. and Yusuf, M.N. (2020) Adaptive and hybrid idle�hard timeout allocation and flow eviction mechanism considering traffic characteristics. Electronics (Switzerland), 9 (11). pp. 1-18.

Isyaku, B. and Bakar, K.A. and Zahid, M.S.M. and Yusuf, M.N. (2020) Adaptive and hybrid idle�hard timeout allocation and flow eviction mechanism considering traffic characteristics. Electronics (Switzerland), 9 (11). pp. 1-18.

Zahid, M.S.M. and Wahab, N.N.A. (2020) Plant watering system using mobile application. International Journal of Advanced Trends in Computer Science and Engineering, 9 (1.1 Sp). pp. 370-373.

Zahid, M.S.M. and Isyaku, B. and Fadzil, F.A. (2018) Recovery of software defined network from multiple failures: Openstate vs openflow. Proceedings of IEEE/ACS International Conference on Computer Systems and Applications, AICCSA, 2017-O. pp. 1178-1183.

Conference or Workshop Item

Isyaku, B. and Bakar, K.B.A. and Ghaleb, F.A. and Zahid, M.S.M. (2021) Path Selection With Critical Switch-Aware For Software Defined Networking. In: UNSPECIFIED.

Hassan, S.U. and Zahid, M.S.M. and Husain, K. (2020) Performance comparison of CNN and LSTM algorithms for arrhythmia classification. In: UNSPECIFIED.