M
Mansaf Alam
Researcher at Jamia Millia Islamia
Publications - 122
Citations - 1364
Mansaf Alam is an academic researcher from Jamia Millia Islamia. The author has contributed to research in topics: Cloud computing & Big data. The author has an hindex of 18, co-authored 109 publications receiving 1001 citations. Previous affiliations of Mansaf Alam include Amity University & University of South Alabama.
Papers
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Journal ArticleDOI
A survey on scholarly data
TL;DR: This research paper investigates the current trends and identifies the existing challenges in development of a big scholarly data platform, with specific focus on directions for future research and maps them to the different phases of the big data lifecycle.
Journal ArticleDOI
BAMHealthCloud: A biometric authentication and data management system for healthcare data in cloud
TL;DR: In this article, a behavioral biometric signature-based authentication mechanism is proposed to ensure the security of e-medical data access in cloud-based healthcare management system, which achieves high accuracy rate for secure data access and retrieval.
Journal ArticleDOI
A Lightweight Deep Learning Model for Human Activity Recognition on Edge Devices
Preeti Agarwal,Mansaf Alam +1 more
TL;DR: In this article, the authors proposed a Lightweight Deep Learning Model for Human Activity Recognition (HAR) requiring less computational power, making it suitable to be deployed on edge devices.
Posted Content
A Lightweight Deep Learning Model for Human Activity Recognition on Edge Devices
Preeti Agarwal,Mansaf Alam +1 more
TL;DR: A Lightweight Deep Learning Model for HAR requiring less computational power, making it suitable to be deployed on edge devices is proposed and results show that the proposed model outperforms many of the existing machine learning and deep learning techniques.
Book ChapterDOI
Cloud-Based Big Data Analytics—A Survey of Current Research and Future Directions
TL;DR: The existing research, challenges, open issues, and future research direction for cloud-based analytics are explored, with a view to practical applications of this synergistic model can be popularly used.