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Now showing items 61-70 of 76
SMART HARDWARE TROJAN DETECTION SYSTEM
(Computing, 06-2 , Master Thesis)
The IoT has become an indispensable part of our lives at work and in our home applications. Due to the need for many IoT devices, IoT manufacturers are least concerned about security vulnerabilities during designing and ...
AI FOR MELTDOWN DETECTION IN AUTISM USING WEARABLE SENSORS.
(Computing, 06-2 , Master Thesis)
Autism spectrum disorder is a neurodevelopmental disorder that is associated with many symptoms, such as impairments in social skills, communication, and abnormal behaviors. Children on the spectrum exhibit atypical, ...
REINFORCEMENT LEARNING BASED APPROACHES FOR RESOURCE ALLOCATION IN SMART HEALTH SYSTEMS.
(Computing, 2022 , Master Thesis)
With the emergence of smart health (s-health) applications and services, several requirements for quality have arisen to foresee and react instantaneously to emergency circumstances. Such conditions demand adaptive fast-acting ...
A conceptual heuristic for solving the maximum clique problem
(Computing, 2017 , Master 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 ...
Time-Aware Workload Charactrization And Prediction For Proactive Auto-Scaling Of Web Applications
(Computing, 2019 , Master Thesis)
Proactive auto-scaling techniques aim to predict the future workload of web
applications to provision the required resources, such as virtual machines (VMs), ahead
of time. Nevertheless, deciding the optimal number of ...
MULTI-ZONAL VEHICLE SURVEILLANCE SYSTEM ENABLED BY A PRIVATE PERMISSIONED BLOCKCHAIN
(Computing, 2023 , Master Thesis)
Privacy, security, accessibility, and reliability are the most essential characteristics of a public security system. Existing surveillance systems provide monitoring and surveillance-based security. However, their inference ...
EXPERIMENTAL INVESTIGATION OF THE PERFORMANCE OF TRANSFORMER-BASED PREDICTION MODELS FOR REMAINING USEFUL LIFE
(Computing, 2023 , Master Thesis)
Remaining Useful Life (RUL) prediction is an essential task in predictive maintenance. This study aims to improve the performance of deep learning models for predicting the RUL of turbojet engines using the C-MAPSS dataset. ...
USING CONTEXT SPECIFIC GENERATIVE ADVERSARIAL NETWORKS FOR AUDIO DATA COMPLETION: MUSICAL INSTRUMENTS CASE STUDY
(Computing, 2023 , Master Thesis)
Audio quality plays an essential role in several applications ranging from music to voice conversations. Sound information is subject to quality loss caused by reasons such as intermittent network connections, or storage ...
USING EMBEDDED MACHINE LEARNING IN THE PHYSICAL WORLD TO DETECT TOXICITY IN SPOKEN LANGUAGE
(Computing, 2023 , Master Thesis)
Toxicity is a prevalent social behavior that involves the use of hate speech, offensive language, bullying, and abusive speech. While text-based approaches for toxicity detection are common, there is limited research on ...
Detecting Non-Technical Losses in Smart Grids Using Statistical Distances of Forecasting Residuals
(Computer Science & Engineering, 2024 , Master Thesis)
Energy theft poses a significant challenge to the sustainability of smart grids, affecting the financial stability of electrical utilities and the overall management of resources. In this thesis, we present a novel load ...