Browsing Computer Science & Engineering by Title
Now showing items 1-20 of 59
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Accurate Classification of Partial Discharge Phenomena in Power Transformers in the Presence of Noise
(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 ... -
An efficient PPG Compression Technique for Wearable Health Devices
(2021 , Master Thesis)Photoplethysmography is a simple, widely used, low-cost technique to acquire important diagnostic information for assessing significant physiological parameters of the human body based on the amount of light reflected from ... -
Application of Machine Learning Techniques for The Prediction of Decompressive Hemicraniectomy Prognosis in Acute Ischemic Stroke
(2019 , Master Thesis)Stroke is one of the leading causes of death in the world with the number of people suffering from it increasing every year. Ischemic strokes, one of the two main types of stroke, occur when blood clots block brain ... -
Automated Segmentation of Cerebral Aneurysm Using a Novel Statistical Multiresolution Approach
(2018 , Master Thesis)Cerebral Aneurysm (CA) is a vascular disease that threatens the lives of many adults. It a ects almost 1:5 - 5% of the general population. Sub- Arachnoid Hemorrhage (SAH), resulted by a ruptured CA, has high rates ... -
Bagged Randomized Conceptual Machine Learning Method
(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 ... -
Blockchain Technology and Reputation System for Smart Grids to Address Cyber-Attacks
(2021 , Master Thesis)The smart grid model has made a big technological leap over the traditional electrical grid. This model contributes to protecting the physical environment as it provides many benefits such as improved quality of services, ... -
Building a Test Collection for Significant-Event Detection in Arabic Tweets
(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 ... -
A COMPREHENSIVE FRAMEWORK FOR DESIGN AND EVALUATION OF M-LEARNING APPLICATIONS
(2016 , Master Thesis)Human-computer interaction (HCI) communities and Mobile Learning Communities (MLCs) are well aware of the challenges that mobile devices impose when it comes to conducting proper usability and user experience evaluations ... -
Conceptual Based Hidden Data Analytics and Reduction Method for System Interface Enhancement Through Handheld devices
(2016 , Master Thesis)With the increasing demand placed on online systems by users, many organizations and companies are seeking to enhance their online interfaces to facilitate the search process on their hidden databases. Usually, users issue ... -
Conceptual data sampling for image segmentation- an application for breast cancer images
(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 ... -
A conceptual heuristic for solving the maximum clique problem
(2017 , Thesis)The maximum clique problem (MCP) is the problem of finding the clique with maximum cardinality in a graph. It has been intensively studied for years by computer scientists and mathematicians. It has many practical applications ... -
DDI: Drones Detection and Identification using Deep Learning Techniques
(2021 , Master Thesis)Drones are becoming increasingly popular not only for recreational purposes but in day-to-day applications in engineering, medicine, logistics, security and others. Besides their useful applications, an alarming concern ... -
DDoS: DeepDefence and Machine Learning for identifying attacks
(2020 , Master Thesis)Distributed Denial of Service (DDoS) attacks are very common type of computer attack in the world of internet today. Automatically detecting such type of DDoS attack packets & dropping them before passing through the ... -
Deanonymizing tor hidden service users through bitcoin transactions analysis
(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 ... -
Deep Learning Based Approach For Prediction Of Cloud Resource Needs
(2018 , Professional Masters Project)Cloud computing allows scaling applications to serve dynamic and time-varying workloads and to avoid application performance degradation, while keeping low provisioning costs. But, resource demand of applications need to ... -
A Deep Learning Based Approach To Detect Covert Channels Attacks and Anomaly In New Generation Internet Protocol IPv6
(2020 , Master Thesis)The increased dependence of internet-based technologies in all facets of life challenges the government and policymakers with the need for effective shield mechanism against passive and active violations. Following up ... -
Deep Learning IoT Malware Detection Model for IoMT Edge Devices
(2021 , Master Thesis)Internet of Things (IoT) is defined as the massive collection of physical devices being connected to the Internet. IoT has a positive impact in multiple fields, such as health, agriculture, and power management sectors by ... -
Deep Reinforcement Learning for Efficient Uplink NOMA SWIPT Transmissions
(2021 , Master Thesis)A key rival technology in radio access strategies for next generation cellular communications is non-orthogonal multiple access (NOMA) due to its enhanced performance compared to existing multiple access techniques such ... -
Detecting market manipulation in stock market data
(2017 , Master Thesis)Anomaly Detection is an extensively researched problem that has diverse applications in many domains. Anomaly detection is the process of finding data points or patterns that do not conform to expected behavior within a ... -
Diabetic Reinopathy Classification using Deep Learning
(2020 , Master Thesis)With diabetes growing at an alarming rate, changes in the retina of diabetic patients causes a condition called diabetic retinopathy which eventually leads to blindness. Early detection of diabetic retinopathy is the best ...
