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Full-Text Articles in Engineering

Design And Implementation Of Uvm-Based Verification Framework For Deep Learning Accelerators, Randa Ahmed Hussein Aboudeif Jan 2025

Design And Implementation Of Uvm-Based Verification Framework For Deep Learning Accelerators, Randa Ahmed Hussein Aboudeif

Theses and Dissertations

Recent advancements in deep learning (DL) have made hardware accelerators, known as deep learning accelerators (DLAs), a preferred solution for numerous high-performance computing (HPC) applications, including speech recognition, computer vision, and image classification. DLAs are composed of hundreds of parallel processing engines to speed up computations and can gain access to pre-trained networks from the cloud or through on-chip memory to implement the DNN inference process. DLA verification is becoming an important and challenging phase. The verification process is required to handle the complex DLA design. Moreover, the reliability of DLAs is critical for assessment as they are involved in …


Shape Memory Alloy Capsule Micropump For Drug Delivery Applications, Youssef Mohamed Kotb Jun 2024

Shape Memory Alloy Capsule Micropump For Drug Delivery Applications, Youssef Mohamed Kotb

Theses and Dissertations

Implantable drug delivery devices have many benefits over traditional drug administration techniques and have attracted a lot of attention in recent years. By delivering the medication directly to the tissue, they enable the use of larger localized concentrations, enhancing the efficacy of the treatment. Passive-release drug delivery systems, one of the various ways to provide medication, are great inventions. However, they cannot dispense the medication on demand since they are nonprogrammable. Therefore, active actuators are more advantageous in delivery applications. Smart material actuators, however, have greatly increased in popularity for manufacturing wearable and implantable micropumps due to their high energy …


Physical Effects On The Worst-Case Delay Analysis And Signal Integrity Of Buses And Spirals, Mahmoud Mahany Jun 2024

Physical Effects On The Worst-Case Delay Analysis And Signal Integrity Of Buses And Spirals, Mahmoud Mahany

Theses and Dissertations

Physical effects have a significant impact on the IC design which will be investigated in this thesis. Moving toward advanced technology nodes, magnetic effects become more dominant than capacitive effects. As the dimensions of the devices go down and the interconnect manipulates the circuit behavior more and more. Cross talking and voltage drops are affecting the design heavily, however - going to the full electromagnetic point of view - current return path (CRP) adds significant parasitics to the performance of the chip. Neglecting the CRP gives wrong intuition and simulation of the designs, especially that the environment and surroundings can …


Fair Fault-Tolerant Approach For Access Point Failures In Networked Control System Greenhouses, Mohammed Ali Yaslam Ba Humaish Feb 2024

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 …


Development Of An Electromagnetic System For Wireless Magnetic Manipulation Of Soft Capsule Endoscope For Drug Delivery Applications, Nada Ashraf Hussein Mahmoud Jan 2024

Development Of An Electromagnetic System For Wireless Magnetic Manipulation Of Soft Capsule Endoscope For Drug Delivery Applications, Nada Ashraf Hussein Mahmoud

Theses and Dissertations

Wireless capsule endoscopy (WCE) is a remarkable diagnostic device that examines the gastrointestinal (GI) tract. The WCE is a small capsule integrated with a camera that is used to visualize the inner mucosa of the GI tract. WCE has been proven to be the most effective method to diagnose GI diseases and GI cancers. The procedure reduces the discomfort and risk compared to conventional endoscopy methods. However, current WCEs lack the ability to take a biopsy or deliver a drug to a specific location. Those therapeutic functions can be introduced by wirelessly controlled WCEs. This thesis introduces an electromagnetic system …


Stochastic Worst-Case Test Vectors For Asic Devices In Single Event Environment, Mostafa Hemeda Jun 2023

Stochastic Worst-Case Test Vectors For Asic Devices In Single Event Environment, Mostafa Hemeda

Theses and Dissertations

Charged particles and energetic particles can impact the integrated circuit, referred to as single event effects (SEE). Nuclear reactors and space radiation can produce these particles. These effects can negatively affect the reliability and performance of electronics. When SEE occurs, a transient current is created, which can cause electronic devices to have incorrect outputs and ultimately fail. As a result, ensuring the reliability of ASIC circuits is a significant concern.

This thesis discusses the different fault types, then discuss the soft error and, in particular, the Single Event Transient (SET) and its causes and models. Then, this thesis proposes a …


An Epileptic Seizure Detection Method From Eeg Signals Based On A Classifier-Driven Feature Reduction Technique, Raymond N. Kamel Jan 2023

An Epileptic Seizure Detection Method From Eeg Signals Based On A Classifier-Driven Feature Reduction Technique, Raymond N. Kamel

Theses and Dissertations

Epileptic seizure detection can improve the quality of life of epileptic patients, allow for more accurate medication, and minimize the risk of sudden unexpected death in epilepsy (SUDEP). This thesis work aims to develop a robust and stable algorithm for epileptic seizure detection through the classification of EEG signals. To achieve this aim, a methodology is proposed to develop a classifier that can differentiate between the healthy (normal), interictal, and ictal states of EEG signals, while maximizing the classification accuracy and minimizing the computational redundancy. The main pillar upon which this methodology is designed is using a problem-specific classifier-driven feature …


In-Field Solar Panel Assessment And Fault Diagnosis, Muhammad Elgamal Jan 2023

In-Field Solar Panel Assessment And Fault Diagnosis, Muhammad Elgamal

Theses and Dissertations

Photovoltaic energy is a green energy that suit from small houses to high-power stations spanning large areas. In such large areas, monitoring individual panels can be a tedious task, especially if it was required to identify operational faults of these panels. Photovoltaic 4.0 technology depend on collecting data from each station and feeding them to a central processing system that can analyze operation data and hopefully locate when a fault happens. In such method, it is crucial to be accurate as much as possible and for measuring device to be accurate as well to have a clear judgement. In this …


Novel Photonic Structures And Materials, Samar Fawzy Oct 2022

Novel Photonic Structures And Materials, Samar Fawzy

Theses and Dissertations

Plasmonic materials provide the ability to confine light in metallic structures in the nanometre scale, enabling their use in a wide range of applications, including metamaterials, energy conversion, biomedical applications, and transformation optics. Conventional plasmonic materials such as Silver and Gold suffer from two problems: very large negative real permittivity (𝜀1), preventing their integration with low-permittivity dielectrics, and large losses associated with conduction electrons such as: electron-electron scattering, electron-phonon scattering or scattering by crystal defects. Therefore, the search for alternative structures and materials that overcome these obstacles is indeed an essential task. Metamaterials, three dimensional (3D) periodic subwavelength metallic/dielectric structures, …


Machine Learning Applications To Static Timing Analysis, Waseem Mohamed Raslan Jun 2022

Machine Learning Applications To Static Timing Analysis, Waseem Mohamed Raslan

Theses and Dissertations

Modeling complex cell behavior is critical for accurate static timing analysis. Effective current source model, ECSM, and composite current source, CCS, waveform data compression became a necessity to reduce the size of technology files and increase the accuracy of the cell characterization data. We used deep learning nonlinear Autoencoders to compress voltage and current waveforms and compared them with singular value decomposition, SVD, approach. Autoencoders gave ~1.67x compression ratio for voltage waveforms better than SVD approach and gave 45x to 55x better compression ratio compared to other lossless techniques like bz2 and gzip. Autoencoders achieved ~1.7x compression ratio for complex …


Integrated Circuits Parasitic Capacitance Extraction Using Machine Learning And Its Application To Layout Optimization, Mohamed Saleh Abouelyazid Saleh May 2022

Integrated Circuits Parasitic Capacitance Extraction Using Machine Learning And Its Application To Layout Optimization, Mohamed Saleh Abouelyazid Saleh

Theses and Dissertations

The impact of parasitic elements on the overall circuit performance keeps increasing from one technology generation to the next. In advanced process nodes, the parasitic effects dominate the overall circuit performance. As a result, the accuracy requirements of parasitic extraction processes significantly increased, especially for parasitic capacitance extraction. Existing parasitic capacitance extraction tools face many challenges to cope with such new accuracy requirements that are set by semiconductor foundries (< 5% error). Although field-solver methods can meet such requirements, they are very slow and have a limited capacity. The other alternative is the rule-based parasitic capacitance extraction methods, which are faster and have a high capacity; however, they cannot consistently provide good accuracy as they use a pre-characterized library of capacitance formulas that cover a limited number of layout patterns. On the other hand, the new parasitic extraction accuracy requirements also added more challenges on existing parasitic-aware routing optimization methods, where simplified parasitic models are used to optimize layouts.

This dissertation provides new solutions for interconnect parasitic capacitance extraction and parasitic-aware routing optimization methodologies in order to cope with the new accuracy requirements of advanced process nodes as follows. …


Single Event Transient Sensitivity Measurement And Worst-Case Test Vector Exploration For Asic Devices Exposed To Space Single Event Environment, Mohamed Wael Jan 2022

Single Event Transient Sensitivity Measurement And Worst-Case Test Vector Exploration For Asic Devices Exposed To Space Single Event Environment, Mohamed Wael

Theses and Dissertations

Space radiation and nuclear reactors produce single event effects (SEE) in electronic circuits and impact their performance. The SEE phenomena cause circuits and electronic devices to fail by producing faulty results. Therefore, today’s circuit’s reliability is a significant concern for all circuit designers.

This thesis suggests a new automated flow to measure the single-event-transient (SET) effects in combinational circuits in application-specific integrated circuits (ASIC) while reaching full fault coverage. The developed flow characterizes the whole circuit nodes by identifying the most sensitive paths to the propagated SET pulses from the node under test to an observable primary output, causing single …


Machine Learning Based Critical Resource Allocation In Mixed-Traffic Cellular Networks, Mohamed Nomeir Dec 2021

Machine Learning Based Critical Resource Allocation In Mixed-Traffic Cellular Networks, Mohamed Nomeir

Theses and Dissertations

The proliferation of cellular networks over the past two decades has encouraged the expansion of their use in many modern applications. These applications involve the use of data traffic of different quality of service (QoS) requirements. Some of these requirements are quite stringent such as in the case of critical Internet of Things (IoT) health care, military and homeland security applications. This situation resulted in imposing a variety of resource allocation requirements on the cellular network operation in a simultaneous manner.

In this thesis, we consider the challenging problem of mixed-traffic resource allocation, or scheduling, in cellular networks. We focus …


Network Management, Optimization And Security With Machine Learning Applications In Wireless Networks, Mariam Nabil Dec 2021

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, …


On-Chip Nanoscale Plasmonic Optical Modulators, Abdalrahman Mohamed Nader Abdelhamid Jun 2021

On-Chip Nanoscale Plasmonic Optical Modulators, Abdalrahman Mohamed Nader Abdelhamid

Theses and Dissertations

In this thesis work, techniques for downsizing Optical modulators to nanoscale for the purpose of utilization in on chip communication and sensing applications are explored. Nanoscale optical interconnects can solve the electronics speed limiting transmission lines, in addition to decrease the electronic chips heat dissipation. A major obstacle in the path of achieving this goal is to build optical modulators, which transforms data from the electrical form to the optical form, in a size comparable to the size of the electronics components, while also having low insertion loss, high extinction ratio and bandwidth. Also, lap-on-chip applications used for fast diagnostics, …


Cross-Junction Based Metasurfaces: A Roadmap To Fano Resonances, Mirna Soliman Jun 2021

Cross-Junction Based Metasurfaces: A Roadmap To Fano Resonances, Mirna Soliman

Theses and Dissertations

The first part of the thesis presents a summary of the classification of materials, followed by the development of metamaterials and their salient role. Then, a study of metamaterials and the evolution of these 3D structures to 2D, known as metasurfaces, have been discussed. Moreover, the physics and practical interest behind Fano resonance have been discussed. Furthermore, the physical fundamentals guiding the performance of both the metamaterials and metasurfaces, including the temporal coupled-mode theory and the generalized laws of reflection and refraction, have been intensely investigated, along with some of the outstanding properties of the metamaterials. Then, a comparison between …


Fault Modeling And Test Vector Generation For Asic Devices Exposed To Space Single Event Environment, Ahmed Mohamed May 2021

Fault Modeling And Test Vector Generation For Asic Devices Exposed To Space Single Event Environment, Ahmed Mohamed

Theses and Dissertations

This work aims at providing a concise automated flow to predict the effect of Single Event Transients (SETs) on ASIC chips by developing a method to characterize the circuit susceptibility to SET pulses propagation and then generation of the required input vectors that sensitize the victim paths. A new enhanced method for SET electrical propagation modeling is proposed and compared to a previously published analytical model. The method was applied on different standard cells libraries built over XFAB Xh018 technology and verified for accuracy against simulations. The new method showed enhancement in accuracy compared with previous work in literature. Industrial …


Latency Optimization In Smart Meter Networks, Amr Kassab Feb 2021

Latency Optimization In Smart Meter Networks, Amr Kassab

Theses and Dissertations

In this thesis, we consider the problem of smart meter networks with data collection to a central point within acceptable delay and least consumed energy. In smart metering applications, transferring and collecting data within delay constraints is crucial. IoT devices are usually resource-constrained and need reliable and energy-efficient routing protocol. Furthermore, meters deployed in lossy networks often lead to packet loss and congestion. In smart grid communication, low latency and low energy consumption are usually the main system targets. Considering these constraints, we propose an enhancement in RPL to ensure link reliability and low latency. The proposed new additive composite …


Enhanced Interest Aware Peoplerank For Opportunistic Mobile Social Networks, Yosra Saad Shahin Jan 2021

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 …


Reinforcement Learning-Based Access Schemes In Cognitive Radio Networks, Ehab Maged Elguindy Jan 2021

Reinforcement Learning-Based Access Schemes In Cognitive Radio Networks, Ehab Maged Elguindy

Theses and Dissertations

In this thesis, we propose different MAC protocols based on three Reinforcement Learning (RL) approaches, namely Q-Learning, Deep Q-Network (DQN), and Deep Deterministic Policy Gradient (DDPG). We exploit the primary user (PU) feedback, in the form of ARQ and CQI bits, to enhance the performance of the secondary user (SU) MAC protocols. Exploiting the PU feedback information can be applied on the top of any SU sensing-based MAC protocol. Our proposed model relies on two main pillars, namely, an infinite-state Partially Observable Markov Decision Process (POMDP) to model the system dynamics besides a queuing-theoretic model for the PU queue; the …


An Optimized Lte-Based Technique For Drone Base Station 3d Placement And Resource Allocation In Delay-Sensitive M2m Networks, Ahmed Fahim Jan 2021

An Optimized Lte-Based Technique For Drone Base Station 3d Placement And Resource Allocation In Delay-Sensitive M2m Networks, Ahmed Fahim

Theses and Dissertations

The deployment of drone-mounted communication systems has received increasing interest and attention recently as it allows significant improvement to the network access capacity and coverage. Many applications can benefit from such deployments in particular machine-to-machine (M2M) communications. Drones are expected to facilitate extending wireless network access for both human users and the smart machine-type-communication devices (MTCDs) that have strict and diverse quality of service (QoS) requirements. In this thesis, we propose an optimal solution for the dynamic placement of an LTE drone-mounted base station to maximize the coverage of MTCDs deployed over a large geographical area in disaster situations or …


Exploiting Feedback Information In Cognitive Radio Systems, Sara Abozeid Attlla Jan 2020

Exploiting Feedback Information In Cognitive Radio Systems, Sara Abozeid Attlla

Theses and Dissertations

In this thesis, we consider a cognitive radio (CR) network where the primary network's feedback information is utilized to design access schemes for the secondary network, to exploit the underutilized primary spectrum resources. Secondary users (SUs) identify the spectrum opportunities by sensing the spectrum for primary users (PUs) activities and by listening to the PUs feedback. The feedback signals monitored in this research work are the channel quality indicator (CQI) and automatic repeat request (ARQ) available in the PUs network. For detecting the PUs activities, SUs employ hard/soft energy sensing. The secondary access decisions are optimized to maximize the SUs …


Novel On-Chip Applications Using Silicon Photonics, Rania Gamal Oct 2014

Novel On-Chip Applications Using Silicon Photonics, Rania Gamal

Theses and Dissertations

The emerging field of silicon photonics offers solutions to designing CMOScompatible optical devices. By taking advantage of the immense fabrication infrastructure offered by the silicon industry, it would be possible to design optical structures that are smaller, faster, less-power consuming and cheaper than traditional, non-silicon-based optical devices. In this dissertation, the design and performance testing of two novel silicon photonic structures are presented: 1) Silicon nanowire ridge waveguide for sensing applications at the optical transmission frequency. 2) Doped silicon plasmonic structures for negative-index, epsilon-near-zero and sensing applications at the mid-infrared. For the first design, silicon nanowires are arranged in a …