Computer Engineering Commons^™

Fair Fault-Tolerant Approach For Access Point Failures In Networked Control System Greenhouses, Mohammed Ali Yaslam Ba Humaish

Theses and Dissertations

Greenhouse Networked Control Systems (NCS) are popular applications in modern agriculture due to their ability to monitor and control various environmental factors that can affect crop growth and quality. However, designing and operating a greenhouse in the context of NCS could be challenging due to the need for highly available and cost-efficient systems. This thesis presents a design methodology for greenhouse NCS that addresses these challenges, offering a framework to optimize crop productivity, minimize costs, and improve system availability and reliability. It contributes several innovations to the field of greenhouse NCS design. For example, it recommends using the 2.4GHz frequency …

User Profiling Through Zero-Permission Sensors And Machine Learning, Ahmed Elhussiny

Theses and Dissertations

With the rise of mobile and pervasive computing, users are often ingesting content on the go. Services are constantly competing for attention in a very crowded field. It is only logical that users would allot their attention to the services that are most likely to adapt to their needs and interests. This matter becomes trivial when users create accounts and explicitly inform the services of their demographics and interests. Unfortunately, due to privacy and security concerns, and due to the fast nature of computing today, users see the registration process as an unnecessary hurdle to bypass, effectively refusing to provide …

Mixed-Criticality Scheduling Using Reinforcement Learning, Omar Elseadawy

Theses and Dissertations

Mixed-criticality (MC) scheduling is necessary for many safety-critical real-time embedded systems, as a failure of high-criticality jobs could lead to fatal accidents. With the emergence of software technologies in software-defined vehicles in the automotive and avionics industries, studying Mixed-Critically (MC) systems is essential to their safety standards, similar to ISO26262. The real-time operation of MC systems makes it an inherently online problem, such that the scheduler is only aware of the jobs that are currently released at any point in time and has no knowledge of future jobs. Due to the overhead cost of preemption, this study focuses on enforcing …

A Component-Based Analysis For Online Proctoring, Salma Roshdy Ali

Theses and Dissertations

The switch to online learning due to the COVID-19 revealed flaws in the existing learning methods, especially with online proctored assessments. Hence, online proctoring using computers was needed for a fair evaluation. Many studies develop cheating detection systems using several approaches. However, to the best of our knowledge, none of the existing studies investigated the impact of their system components in detecting cheating behaviors. Combining system components, even if they do not significantly improve the system performance in cheating detection, can cause an overload on the system. Therefore, our goal is to investigate the system components’ impact, individually and combined, …

Camera And Lidar Fusion For Point Cloud Semantic Segmentation, Ali Abdelkader

Theses and Dissertations

Perception is a fundamental component of any autonomous driving system. Semantic segmentation is the perception task of assigning semantic class labels to sensor inputs. While autonomous driving systems are currently equipped with a suite of sensors, much focus in the literature has been on semantic segmentation of camera images only. Research in the fusion of different sensor modalities for semantic segmentation has not been investigated as much. Deep learning models based on transformer architectures have proven successful in many tasks in computer vision and natural language processing. This work explores the use of deep learning transformers to fuse information from …

Adding Temporal Information To Lidar Semantic Segmentation For Autonomous Vehicles, Mohammed Anany

Theses and Dissertations

Semantic segmentation is an essential technique to achieve scene understanding for various domains and applications. Particularly, it is of crucial importance in autonomous driving applications. Autonomous vehicles usually rely on cameras and light detection and ranging (LiDAR) sensors to gain contextual information from the environment. Semantic segmentation has been employed to process images and point clouds that were captured from cameras and LiDAR sensors respectively. One important research direction to consider is investigating the impact of utilizing temporal information in the domain of semantic segmentation. Many contributions exist in the field with regards to utilizing temporal information for semantic segmentation …

Extractive Text Summarization On Single Documents Using Deep Learning, Shehab Mostafa Abdel-Salam Mohamed

Theses and Dissertations

The task of summarization can be categorized into two methods, extractive and abstractive summarization. Extractive approach selects highly meaningful sentences to form a summary while the abstractive approach interprets the original document and generates the summary in its own words. The task of generating a summary, whether extractive or abstractive, has been studied with different approaches such as statistical-based, graph-based, and deep-learning based approaches. Deep learning has achieved promising performance in comparison with the classical approaches and with the evolution of neural networks such as the attention network or commonly known as the Transformer architecture, there are potential areas for …

Network Management, Optimization And Security With Machine Learning Applications In Wireless Networks, Mariam Nabil

Theses and Dissertations

Wireless communication networks are emerging fast with a lot of challenges and ambitions. Requirements that are expected to be delivered by modern wireless networks are complex, multi-dimensional, and sometimes contradicting. In this thesis, we investigate several types of emerging wireless networks and tackle some challenges of these various networks. We focus on three main challenges. Those are Resource Optimization, Network Management, and Cyber Security. We present multiple views of these three aspects and propose solutions to probable scenarios. The first challenge (Resource Optimization) is studied in Wireless Powered Communication Networks (WPCNs). WPCNs are considered a very promising approach towards sustainable, …

An Adaptive Hybrid Genetic-Annealing Approach For Solving The Map Problem On Belief Networks, Manar Hosny

Archived Theses and Dissertations

No abstract provided.

Energy Optimization By Scratchpad Memory Banking For Embedded Systems, Noha Abuaesh

Archived Theses and Dissertations

No abstract provided.

Pervasive Open Spaces: An Intelligent And Scalable Pervasive Environment For Providing Contextual Resource Sharing, Amgad Magdy Madkour

Archived Theses and Dissertations

No abstract provided.

Texture Classification Using Transform Analysis, Mary Fouad Habib

Archived Theses and Dissertations

No abstract provided.

Off-Chain Transaction Routing In Payment Channel Networks: A Machine Learning Approach, Heba Kadry

Theses and Dissertations

Blockchain is a foundational technology that has the potential to create new prospects for our economic and social systems. However, the scalability problem limits the capability to deliver a target throughput and latency, compared to the traditional financial systems, with increasing workload. Layer-two is a collective term for solutions designed to help solve the scalability by handling transactions off the main chain, also known as layer one. These solutions have the capability to achieve high throughput, fast settlement, and cost efficiency without sacrificing network security. For example, bidirectional payment channels are utilized to allow the execution of fast transactions between …

Stock Markets Performance During A Pandemic: How Contagious Is Covid-19?, Yara Abushahba

Theses and Dissertations

Background and Motivation: The coronavirus (“COVID-19”) pandemic, the subsequent policies and lockdowns have unarguably led to an unprecedented fluid circumstance worldwide. The panic and fluctuations in the stock markets were unparalleled. It is inarguable that real-time availability of news and social media platforms like Twitter played a vital role in driving the investors’ sentiment during such global shock.

Purpose:The purpose of this thesis is to study how the investor sentiment in relation to COVID-19 pandemic influenced stock markets globally and how stock markets globally are integrated and contagious. We analyze COVID-19 sentiment through the Twitter posts and investigate its …

Enhanced Interest Aware Peoplerank For Opportunistic Mobile Social Networks, Yosra Saad Shahin

Theses and Dissertations

Network infrastructures are being continuously challenged by increased demand, resource-hungry applications, and at times of crisis when people need to work from homes such as the current Covid-19 epidemic situation, where most of the countries applied partial or complete lockdown and most of the people worked from home. Opportunistic Mobile Social Networks (OMSN) prove to be a great candidate to support existing network infrastructures. However, OMSNs have copious challenges comprising frequent disconnections and long delays. we aim to enhance the performance of OMSNs including delivery ratio and delay. We build upon an interest-aware social forwarding algorithm, namely Interest Aware PeopleRank …

Efficient End-To-End Autonomous Driving, Hesham Eraqi

Theses and Dissertations

Steering a car through traffic is a complex task that is difficult to cast into algorithms. Therefore, researchers turn to train artificial neural networks from front-facing camera data stream along with the associated steering angles. Nevertheless, most existing solutions consider only the visual camera frames as input, thus ignoring the temporal relationship between frames. In this work, we propose a Convolution Long Short-Term Memory Recurrent Neural Network (C-LSTM), which is end-to-end trainable, to learn both visual and dynamic temporal dependencies of driving. Additionally, We introduce posing the steering angle regression problem as classification while imposing a spatial relationship between the …

Dbknot: A Transparent And Seamless, Pluggable Tamper Evident Database, Islam Khalil

Theses and Dissertations

Database integrity is crucial to organizations that rely on databases of important data. They suffer from the vulnerability to internal fraud. Database tampering by internal malicious employees with high technical authorization to their infrastructure or even compromised by externals is one of the important attack vectors.

This thesis addresses such challenge in a class of problems where data is appended only and is immutable. Examples of operations where data does not change is a) financial institutions (banks, accounting systems, stock market, etc., b) registries and notary systems where important data is kept but is never subject to change, and c) …

Novel On-Chip Optical Modulator Designs, Mohamed Mahmoud Ibrahim Ibrahim Elsayed

Theses and Dissertations

The huge increments in data traffic and communication over the past few decades have pushed the conventional electronic communication systems to their physical limits in terms of data rate, bandwidth and capacity. The continuous shrinking of feature sizes, the increase in the microelectronic integrated circuits complexity, and the increasing demand for higher speeds and data rates have all stimulated seeking new technology to replace the currently present microelectronics industry rather than improving it. Photonics is one of the most likely candidates to answer this pursuit for its compatibility with the fiber optic industry, which has shown a great success in …

Novel Planar Wire-Grid Antenna Arrays For Automotive Radars Operating At 77 Ghz, Hossam Helaly

Theses and Dissertations

Automotive radars are the critical components for future driving assistance technologies. Nowadays, their usage is a constraint on the premium segment automobiles; however, there are intensive studies to facilitate these technologies to the lower segment. The main challenges that face automakers to develop new automotive radars are fabrication cost, compactness, bandwidth, and radiation properties. This research focuses on developing a novel class of planar antenna arrays, which operate at a frequency of 77 GHz. The proposed arrays can be fabricated using multilayered cheap printed circuit board lamination technology. The proposed antennas are arrayed using mixed wire-gridding and corporate arraying techniques, …

Development Of Iot Based Hybrid Autonomous Network Robots (Anr), Chimsom Isidore Chukwuemeka

Theses and Dissertations

The integration of wireless sensor networks (WSNs) and multirobot systems (MRS) represents an active research area supporting a wide range of applications. This is because it enables ubiquitous applications due to the robots' mobility and detection capabilities associated with its deployment. These systems have many benefits, such as perception with extended coverage that facilitate wider exploration and surveillance, efficiency in data routing, effective and reliable task environment management, etc. However, integrating two fields of research means dealing with a range of challenges such as using effective architecture for WSNs and MRS, efficient communication protocols within a network of sensors nodes …

Assessing Network Security Through Automated Attack Graph Based Multi-Level Penetration Testing, Ahmed Mohamed Hassan

Archived Theses and Dissertations

Assessing network security can be done in many different ways like applying penetration testing against target network. Penetration testing follows actual steps like reconnaissance, scanning, exploit and logical access to compromised hosts. When attacker compromises a machine, he uses it as a pivot for attacking other machines and getting access to them. An attacker continues in this process till he explores the entire target network or till he reaches his endeavor. This shows that attacks are not a single step but, to reach attackers' goal, the attacker has to go through multiple steps. Many of the available exploitation tools depend …

Measuring Atmospheric Scattering From Digital Images Of Urban Scenery Using Temporal Polarization-Based Vision, Tarek El-Gaaly

Archived Theses and Dissertations

Suspended atmospheric particles (particulate matter) are a form of air pollution that visually degrades urban scenery and is hazardous to human health and the environment. Current environmental monitoring devices are limited in their capability of measuring average particulate matter (PM) over large areas. Quantifying the visual effects of haze in digital images of urban scenery and correlating these effects to PM levels is a vital step in more practically monitoring our environment. Current image haze extraction algorithms remove all the haze from the scene and hence produce unnatural scenes for the sole purpose of enhancing vision. We present two algorithms …

An Extended Configurable Uml Activity Diagram And A Transformation Algorithm For Business Process Reference Modeling, Yosra Osama Badr

Archived Theses and Dissertations

Enterprise Resource Planning (ERP) solutions provide generic off-the-shelf reference models usually known as "best practices". The configuration !individualization of the reference model to meet specific requirements of business end users however, is a difficult task. The available modeling languages do not provide a complete configurable language that could be used to model configurable reference models. More specifically, there is no algorithm that monitors the transformation of configurable UML Activity Diagram (AD) models while preserving the syntactic correctness of the model. To fill these gaps we propose an extended UML AD modeling language which we named Configurable UML Activity Diagram (C-UML …

Software Quality Attribute Measurement And Analysis Based On Class Diagram Metrics, Dalia Rizk

Archived Theses and Dissertations

Software quality measurement lies at the heart of the quality engineering process. Quality measurement for object-oriented artifacts has become the key for ensuring high quality software. Both researchers and practitioners are interested in measuring software product quality for improvement. It has recently become more important to consider the quality of products at the early phases, especially at the design level to ensure that the coding and testing would be conducted more quickly and accurately. The research work on measuring quality at the design level progressed in a number of steps. The first step was to discover the correct set of …

Collaborative Filtering For Domain Independent Recommendation, Rami El-Gawly

Archived Theses and Dissertations

No abstract provided.

Label Oriented Clustering For Social Network Groups, Ahmed El Kholy

Archived Theses and Dissertations

No abstract provided.

Selective Summarization Of Online Discussions, Mohamed Al Tantawy

Archived Theses and Dissertations

No abstract provided.

Mobile User Movement And Service Usage Prediction Using Bayesian Learning For Neural Networks, Sherif Hany Akoush

Archived Theses and Dissertations

No abstract provided.

Aspectization Of Web Applications Quality Of Service Measures, Lamya Atef Othman Tantawy

Archived Theses and Dissertations

No abstract provided.

Threat-Driven Security Architecture Modeling And Analysis Of Web Services-Based Systems, Yomna Mostafa El-Sayed Aly

Archived Theses and Dissertations

No abstract provided.