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Optimal Resource Allocation Using Deep Learning-Based Adaptive Compression For Mhealth Applications
(Computing, 2018 , Master Thesis)
In the last few years the number of patients with chronic diseases that require constant monitoring increases rapidly; which motivates the researchers to develop scalable remote health applications. Nevertheless, transmitting ...
Accurate Classification of Partial Discharge Phenomena in Power Transformers in the Presence of Noise
(Computing, 2017 , Master Thesis)
The objective of this research is to accurately classify different types of Partial
Discharge (PD) phenomenon that occurs in transformers in the presence of noise. A PD is
an electrical discharge or spark that bridges a ...
Conceptual data sampling for image segmentation- an application for breast cancer images
(Engineering-Computer Science, 2017 , Master Thesis)
At the present time data analytics have become a buzzword for the in-
formation technology sector. In an attempt to analyze data; one may follow
various paths. Be it deploying sophisticated technologies to process big ...
Features Ranking Techniques for Single Nucleotide Polymorphism Data
(Engineering-Computer Science, 2017 , Master Thesis)
Identifying biomarkers like single nucleotide polymorphisms (SNPs) is an important topic in biomedical applications. Such SNPs can be associated with an individual’s metabolism of drugs, which make these SNPs targets for ...
Deanonymizing tor hidden service users through bitcoin transactions analysis
(Engineering-Computer Science, 2017 , Master Thesis)
With the rapid increase of threats on the Internet, people are continuously seeking privacy and anonymity. Services such as Bitcoin and Tor were introduced to provide anonymity for online transactions and Web browsing. Due ...
PERFORMANCE EVALUATION OF CROSS-LAYER DESIGN WITH DISTRIBUTED AND SEQUENTIAL MAPPING SCHEME FOR VIDEO APPLICATION OVER IEEE 802.11E
(Computer Science, 2016 , Master Thesis)
The rapid development of wireless communication imposes several challenges to support QoS for real-time multimedia applications such as video stream applications. Researchers tackled these challenges from different points ...
Segmentation of Tumor Regions in Microscopic Images of Breast Cancer Tissue
(Computing, 2016 , Master Thesis)
Nowadays, advances in the domain of digital pathology gave the means to replace the old optical microscopes by the Whole Slide Imaging (WSI) scanners. These scanners enable pathologists viewing conventional tissue slides ...
Building a Test Collection for Significant-Event Detection in Arabic Tweets
(Computing, 2016 , Master Thesis)
With the increasing popularity of microblogging services like Twitter, researchers discov-
ered a rich medium for tackling real-life problems like event detection. However, event
detection in Twitter is often obstructed ...
Bagged Randomized Conceptual Machine Learning Method
(Computing, 2018 , Master Thesis)
Formal concept analysis (FCA) is a scientific approach aiming to investigate, analyze and represent the conceptual knowledge deduced from the data in conceptual structures (lattice). Recently many researchers are counting ...
Equipment Criticality Classification Using Analytical Hierarchy Method
(Engineering Management, 2018 , Master Thesis)
The overall aim of this project is to use the analytical hierarchy process as new method in the equipment criticality process. The equipment criticality in the industrial sector is very essential part in the prioritizing ...