Computer Science & Engineering
Recent Submissions
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Optimizing Cloud Virtual Machine Migration: Minimizing Downtime and Migration Time Using Machine Learning
(2024 , Dissertation)Cloud computing has revolutionized the way services are delivered to users, offering unparalleled flexibility and scalability. However, cloud services can become temporarily unavailable due to maintenance, resource allocation, ... -
Phenotaxis: Localization of The Source of Phenomena Using Mobile Searchers
(2024 , Master Thesis)Over the years, the use of robotic searchers in times of disaster and dangerous incidents, such as toxic gas leakage, has become of higher significance. Using robot searchers instead of humans or animals in such dangerous ... -
Enhancing Knowledge Distillation for Text Summarization
(2024 , Master Thesis)In the realm of natural language processing, recent advancements have been significantly shaped by the development of large pretrained Seq2Seq Transformer models, including BART, PEGASUS, and T5. These models have ... -
Enhancing Autonomous Robot Perception Via Slam Coupled With AI-Driven Selective Obstacle Object Detection
(2024 , Master Thesis)Autonomous mobile robots are changing various industries, making them more efficient and adaptable. They are used in critical sectors such as manufacturing, healthcare, logistics, and infrastructure to make operations ... -
Domain Specific Transformers-Based Prioritization of Readmission for Patients in Healthcare
(2024 , Master Thesis)Hospital re-admissions are not only resource-intensive but also a key indicator of healthcare quality. Therefore, there is a critical need to enhance the efficiency of healthcare systems by accurately identifying patients ... -
Detecting Non-Technical Losses in Smart Grids Using Statistical Distances of Forecasting Residuals
(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 ... -
Mixed-Reality Surgical Simulator for Minimally Invasive Surgery
(2024 , Master Thesis)Modern medical practice relies on minimally invasive surgery (MIS), which has revolutionized surgery. Understanding complicated anatomical features and improving hand-eye coordination for instrument-tissue interactions ... -
Enhancing Fuzzy Rule-Based Anfis Neuronal Fuzzy Architecture Through Integration with Binary Particle Swarm Optimization Technique for Low-Dimensional Data Modeling
(2024 , Dissertation)Fuzzy rule-based systems are instrumental in data interpretation, especially in scenarios dominated by low-dimensional data. While deep learning has revolutionized areas like image and speech recognition, its effectiveness ... -
IMPROVING INTERNET OF THINGS NETWORK STABILITY USING A HIERARCHICAL HYPERLEDGER FABRIC MODEL
(2023 , Master Thesis)Smart contracts in the blockchain have enabled the technology to find its way beyond the financial uses in which it originally operated. As such, it has quickly found its way into the Internet of Things (IoT) networks, ... -
LOCATION MENTION PREDICTION FROM DISASTER TWEETS
(2023 , Dissertation)While utilizing Twitter data for crisis management is of interest to different response authorities, a critical challenge that hinders the utilization of such data is the scarcity of automated tools that extract and resolve ... -
EXPERIMENTAL INVESTIGATION OF THE PERFORMANCE OF TRANSFORMER-BASED PREDICTION MODELS FOR REMAINING USEFUL LIFE
(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
(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
(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 ... -
ARABIC QUESTION ANSWERING ON THE HOLY QUR'AN
(2023 , Dissertation)In this dissertation,we address the need for an intelligent machine reading at scale (MRS) Question Answering (QA) system on the Holy Qur'an, given the permanent interest of inquisitors and knowledge seekers in this sacred ... -
MULTI-ZONAL VEHICLE SURVEILLANCE SYSTEM ENABLED BY A PRIVATE PERMISSIONED BLOCKCHAIN
(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 ... -
REINFORCEMENT LEARNING BASED APPROACHES FOR RESOURCE ALLOCATION IN SMART HEALTH SYSTEMS.
(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 ... -
AI FOR MELTDOWN DETECTION IN AUTISM USING WEARABLE SENSORS.
(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, ... -
INTERPRETABLE DEEP LEARNING MODELS FOR PREDICTION OF CLINICAL OUTCOMES FROM ELECTRONIC HEALTH RECORDS
(06-2 , Dissertation)The rapid adoption of electronic health records (EHRs) has generated tremendous amounts of valuable clinical data on complex diseases and health trajectories. Yet, achieving successful secondary use of this EHR data for ... -
INTRUSION RESPONSE FOR CYBER-PHYSICAL SYSTEMS: A MODEL-FREE DEEP REINFORCEMENT LEARNING APPROACH
(06-2 , Master Thesis)Cyberattacks on Cyber-Physical Systems (CPSs) are on the rise due to CPS increased networked connectivity, which may cause costly environmental hazards as well as human and financial loss. Although the connectivity of CPSs ... -
ENERGY-EFFICIENT USER-EDGE ASSOCIATION AND RESOURCE ALLOCATION IN IOT-BASED HIERARCHICAL FEDERATED LEARNING
(06-2 , Master Thesis)The proliferation of data as part of the Internet of Things (IoT) systems needs to be efficiently utilized while respecting data privacy and scalability. Edge computing is an emerging paradigm that mandates efficient ...