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Detection of Double and Triple Compression in Videos for Digital Forensics Using Machine Learning
(2020-12)
Digital video forensics is the process of analysing, examining and comparing a video for use in legal matters and court cases. In digital video forensics, the main aim is to detect and identify video forgery and manipulation ...
Data Embedding and Extraction in Scrambled Video using Machine Learning
(2020-12)
Data embedding in videos and images has various important applications such as digital rights management (DRM), content authentication, copyright protection, error resiliency and concealment as well as law enforcement. ...
Isolating Physical Replacement of Identical IoT Devices Using Machine and Deep Learning Approaches
(2021-04)
Many Internet of Things (IoT) applications deploy identical end devices like sensor nodes or surveillance cameras in an organization. The purpose of this thesis was to determine if a malicious physical substitution of one ...
Improvement of Dialysis Dosing Using Big Data Analytics
(2021-04)
Data is transforming the healthcare sector and making it more dependent on data science. Data science is becoming a critical tool that allows looking at the data generated from various sources, such as patient health ...
Machine Learning-Based Approach for EV Charging Behavior
(2021-04)
As smart city applications are moving from conceptual models to the development phase, smart transportation, of smart cities’ applications, is gaining ground nowadays. Electric vehicles (EVs) are considered to be one of ...
An Intelligent System Approach for RF Energy Harvesting
(2021-08)
RF energy harvesting has emerged as a viable energy source for low-powered devices in wireless sensor networks. It also acts as a replacement for conventional power sources such as batteries. RF energy harvest uses an ...