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Shaiful Jahari Hashim
Researcher at Universiti Putra Malaysia
Publications - 138
Citations - 910
Shaiful Jahari Hashim is an academic researcher from Universiti Putra Malaysia. The author has contributed to research in topics: Computer science & Cognitive radio. The author has an hindex of 13, co-authored 125 publications receiving 674 citations. Previous affiliations of Shaiful Jahari Hashim include Cardiff University.
Papers
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Journal ArticleDOI
ECG biometric authentication based on non-fiducial approach using kernel methods
Maryamsadat Hejazi,Syed Abdul Rahman Al-Haddad,Yashwant Prasad Singh,Shaiful Jahari Hashim,Ahmad Fazli Abdul Aziz +4 more
TL;DR: A new non-fiducial framework for ECG biometric verification using kernel methods to reduce both high autocorrelation vectors' dimensionality and recognition system after denoising signals of 52 subjects with Discrete Wavelet Transform (DWT).
Proceedings ArticleDOI
An efficient authentication and key agreement protocol for 4G (LTE) networks
TL;DR: The proposed Efficient EPS-AKA protocol is based on the Simple Password Exponential Key Exchange (SPEKE) protocol and is faster, since it uses a secret key method which is faster than certificate-based methods.
Journal ArticleDOI
IoT and Big Data Applications in Smart Cities: Recent Advances, Challenges, and Critical Issues
Marieh Talebkhah,Aduwati Sali,Mohsen Marjani,Meisam Gordan,Shaiful Jahari Hashim,Fakhrul Zaman Rokhani +5 more
TL;DR: In this paper, the concept of smart cities is briefly overviewed; then, their properties and specifications as well as generic architecture, compositions, and real-world implementations are addressed.
Journal ArticleDOI
Additive noise reduction in natural images using second-generation wavelet transform hidden Markov models
TL;DR: A new adaptive denoising framework based on second‐generation wavelet domain using hidden Markov models (SGWD‐HMMs) with some new local structure is proposed, utilizing the fact that the images are nonstationary with singularities and some smooth areas that can be considered as stationary.
Journal ArticleDOI
Performance Evaluation of Time-Frequency Distributions for ECG Signal Analysis
Ahmed Faeq Hussein,Shaiful Jahari Hashim,Ahmad Fazli Abdul Aziz,Fakhrul Zaman Rokhani,Wan Azizun Wan Adnan +4 more
TL;DR: The performance evaluation of five TFDs in term of ECG abnormality detection shows that Choi-Williams distribution is most reliable to be used for heart problem detection especially in automated systems that provide continuous monitoring for long time duration.