Digital Commons Network^™

Embedded Solar Tracker Design Utilizing Solar Position Calculation With Sensor Correction, Austin Martinez

Theses

As renewable energy becomes more accessible, affordable optimization solutions have become a larger part of at home systems. Solar energy is one of the most common clean energy applications used by homeowners because of its increasing affordability. While many photovoltaic systems are statically mounted on roofs or in yards, many systems also employ some kind of solar tracking. Both single axis and dual axis solar tracking systems have been implemented and tested with multiple kinds of tracking methods. Two of the most accurate tracking strategies are utilizing light dependent resistors or using some kind of solar position calculation. This paper …

A Bit-Exact Hierarchical Systemc Model Of Ppim For Verification And Performance Modeling, Dhana Lavanya Balasubramanian

Theses

The semiconductor industry has seen tremendous advancement lately and is expected to continue to grow since multiple industries like automobile, health care, meteorology, etc are developing dedicated chips with advancements in Artificial Intelligence (AI). These improvements also come with increased complexities. Engineers now require advanced ways to model the designs in addition to existing Hardware Description Languages (HDLs) such as Very High-Speed Integrated Circuit Hardware Description Language (VHDL) and Verilog. One such way to model the designs is by using SystemC, which is a library of C++ classes and macros that can be used similar to an HDL for modeling …

Optimizing Voronoi Tessellation Façade’S Capability For Pollution Removal And Interior Daylighting In An Urban Environment, Simon Bai

Theses

Air pollutants are a major health concern in urban zones worldwide, and these unnoticeable air particulates and gases are detrimental to the individuals’ respiratory and cardiovascular wellbeing. Since buildings are the most abundant structure within these built environments, this study focuses on how to utilize the façade of these structures in an attempt to solve the escalating air pollution problem. In this case, titanium dioxide (TiO2) is introduced to give building façades the capability to deal with air pollution in addition to being inexpensive and chemically stable. A TiO2 surface makes use of photocatalysis under ultraviolet (UV) light to decompose …

An Examination Of The Effects Of The Cost Volume On Vision Transformer-Based Optical Flow Models, Andrew Thompson

Theses

The optical flow task is an active research domain in the machine learning community with numerous downstream applications such as autonomous driving and action recognition. Convolutional neural networks have often been the basis of design for these models. However, given the recent popularity of self-attention architectures, many optical flow models now utilize a vision transformer backbone. Despite the differing backbone architectures used, consistencies in model design, especially regarding auxiliary operations, have been observed. Perhaps most apparent is the calculation and use of the cost volume. While prior works have well documented the effects of the cost volume on models with …

Machine Learning Based Framework For Smart Contract Vulnerability Detection In Ethereum Blockchain, Qusai Omar Mustafa Hasan

Theses

Abstract

Blockchain technology is a disruptive technology that revolutionized digital payments and transactions of digital assets. Blockchain transactions operate using smart contracts which are automated software code that facilitates transactions between parties without the need for intermediary systems. Smart contracts have become an increasingly popular means of conducting transactions and executing code in a decentralized manner. As it can be written in various languages which have their flaws in terms of logic and vulnerabilities, also the immutability and autonomy of smart contracts also make them vulnerable to various security threats. Security for smart contracts is essential as exploiting bad logic …

The Use Of Digitalization And Internet Of Things To Help Alleviate Traffic Congestion In Addis Ababa, Ethiopia, Nujuma Ibrahim

Theses

Addis Ababa, the capital city of Ethiopia, has a population of just over 5 million people in 2021. This is 4.4% more than the population in 2020, and 8.8% more than the population in 2019 (Addis Ababa, Ethiopia Metro Area population 1950-2021). With rapid urbanization and economic growth Addis Ababa’s transportation infrastructure is unable to meet the demands of the population. As a result, the city is facing high rates of traffic congestion. Based on the research conducted by Wondwossen Taddesse for his paper on ‘Assessing & quantifying the level of traffic congestion at major intersections, the average traffic congestion …

A Comparative Analysis Of Malware Written In The C And Rust Programming Languages, Meghna Koorikkattil Praveen

Theses

The use of malware as a tool for cybercrime has become increasingly prevalent in recent years, resulting in significant economic losses and security threats. Conventionally, malware is written in C/C++. However, a recent trend has been observed where other languages are being used to write malware. One such language is the Rust programming language. This thesis aims to explore the aspects of the Rust programming language that contribute to its preference for the development of malware, limitations in current analysis tools and remediation for the same. A Systematic Literature Review (SLR) was conducted to identify the trends of current research …

The Automation Of Translation Between Sign Language Variants Through Artificial Intelligence, Mohammad Sultan Buafra

Theses

Language is the method of communication between individuals and communities through either sounds, written symbols, or visual gestures. There is a variety of languages around the world. One significant language that is made up of hand gestures is sign language and it is the main method of communication between and with deaf people. Translation between languages is a practice that has been automated with the advancement of artificial intelligence, this has also allowed for the translation of sign language into written language. However, there remains a certain gap in translating between regional variants of sign language. The purpose of this …

Netzero Insight: The Role Of Data Analytics And Machine Learning In Combating Climate Change, Tariq Najar, Chrissie Aldo

Theses

Countries must act urgently to achieve the SDGs and make significant progress for the planet and people by 2030. But there are some key challenges that the world must address. Climate change is one of the most significant challenges of our time, and its impacts can undermine the ability of all countries to achieve sustainable development. However, countries committed to limiting global warming to 1.5°C above pre- industrial levels in the Paris Agreement. Member nations pledge to take urgent action on climate change to save the planet from global warming.

Using data analysis techniques and methodologies, such as CRISP-DM, and …

Demonstration Of A Virtual Reality Driving Simulation Platform, Mingming Wang

Theses

Modern autonomous driving is undergoing a period of rapid evolution. Image processing, computer vision, and remote sensing, among others, have played crucial roles in the creation of safe and reliable robotic automobiles. However, some robotic vehicles still have difficulties in their driving mechanisms even though the current mainstream autonomous driving approaches seem to be effective in fulfilling driving duties. There have been several high-profile incidents in the early years of testing that have prompted some to question whether or not all relevant domains have been explored in order to attain human-like driving. The current sensor technique based on machine learning …

Harnessing Crispr-Cas12a And Nanotechnology For The Rapid And Accurate Detection Of Dna Viruses, Mengdi Bao

Theses

In recent years, the world has faced numerous pandemics caused by viral diseases, leading to considerable morbidity, mortality, and economic disruptions. Developing vaccines for pandemics can be a challenging task due to the rapid mutation of viruses and the significant investment of time required for their development. While real-time polymerase chain reaction and immunoassay techniques are frequently utilized for viral diagnostics, they possess inherent limitations. Therefore, there is a pressing need to rapidly and accurately identify viral infections to manage diseases effectively. This work explores the use of nanotechnology and clustered regularly interspaced short palindromic repeats (CRISPR)-associated (Cas) proteins to …

Hardware Accelerators And Their Use In Computer Vision, Cameron Villone

Theses

The evolution of technology is impressive. Before digital, there was analog; before software, there needed hardware. This evolution is natural as we try and optimize technology for our needs. The shift to digital was fueled by the space saved from using digital systems compared to analog. When it came to software, the ability to use generic hardware in the forms of cen- tral processing units; CPUs, Graphics Processing Units; GPUs, and Random Access Memory; RAM allowed for complex software solutions to be able to run on many different devices with- out much need for translations. With software development getting so …

Memory Protection With Cached Authentication Trees, Andy Belle-Isle

Theses

The use of embedded systems and the amount of data they process is rapidly growing in the modern information age. Given physical access to a device, an attacker can monitor the signals between the CPU and Memory to intercept, and possibly even inject new data into the system. A variety of attacks are possible including, replay, spoofing, and splicing attacks, each one threatening the safety of the system. Ensuring this data is intact is imperative, and as physical protection is difficult, data protection hardware is a must. Protecting memory was researched in the past, and there are several methods of …

Online Fourier Analysis Of Time-Varying Signals In A Real-Time Embedded Environment, Ty Freeman

Theses

A software-based, constant-flow implementation of the radix-2 Cooley-Tukey fast Fourier transform (FFT) algorithm is presented in this paper. The program is built within a real-time embedded environment running FreeRTOS. The system is used for the online frequency anal- ysis of time-varying, one-dimensional signals of an arbitrary length. The system’s design is validated through testing to produce results accurately on signals within specific boundaries. The proposed system has a maximum transform size of 256 samples due to the memory limitations on the development board. The hardware in use is an STM32L476 Nucleo development board which simulates the lightweight, low power, and …

Quantum Acceleration Of Linear Regression For Artificial Neural Networks, Martin A. Hoffnagle

Theses

Through proofs and small scale implementations, quantum computing has shown potential to provide significant speedups in certain applications such as searches and matrix calculations. Recent library developments have introduced the concept of hybrid quantum-classical compute models where quantum processor units could be used as additional hardware accelerators by classical computers. While these developments have opened the prospect of applying quantum computing to machine learning tasks, there are still many limitations of near and midterm quantum computing. If implemented carefully, the advantages of quantum algorithms could be used to accelerate current machine learning models. In this work, a hybrid quantum-classical model …

End-To-End Network Slicing Using Hypergraph Theory, Omar Abdul-Latif

Theses

Network slicing is the practice of implementing multiple virtualized and independent architectures on a single physical network infrastructure, in a way that allows for multiplexing and efficient use of resources. Network slicing is based on the concept of network virtualization and, when it reaches maturity, is expected to result in complete softwarization of 5G, Beyond-5G (B5G) and 6G networks. This means that future networks will only need minimal physical infrastructure upgrades (mostly in the frontend of the network). Network slicing is identified as one of the key enablers of next generation wireless mobile networks due to its ability to multiplex …

Improved Grover’S Implementation Of Quantum Binary Neural Networks, Brody A. Wrighter

Theses

Binary Neural Networks (BNNs) are the result of a simplification of network parameters in Artificial Neural Networks (ANNs). The computational complexity of training ANNs increases significantly as the size of the network increases. This complexity can be greatly reduced if the parameters of the network are binarized. Binarization, which is a one bit quantization, can also come with complications including quantization error and information loss. The implementation of BNNs on quantum hardware could potentially provide a computational advantage over its classical counterpart. This is due to the fact that binarized parameters fit nicely to the nature of quantum hardware. Quantum …

Single-Mode Distributed-Feedback Lasing In Coupled Dissimilar Photonic Waveguides, Bryce A. Tennant

Theses

Distributed-feedback (DFB) lasers support a wide range of applications including fiber-optic and free-space optical communications, sensing and measurement, military warfare, and manufacturing and metrology. The desire for a reduction in size, weight, power, and cost (SWAP-C) for each of these applications continues to aggressively drive integrated- and silicon-photonic circuit development. Since DFB lasers based on uniform refractive-index diffraction gratings are naturally dual-mode, a variety of techniques have been introduced to impose single-mode operation, including the currently ubiquitous λ/4-grating phase-shift technique. This grating phase shift, however, creates an undesirable peaky-power profile within the laser cavity resulting in nonlinear behavior ultimately limiting …

Advanced Control Of Vapor Compression Liquid Chillers, Suliman Awad

Theses

Chillers are one of the most sophisticated and most important equipment in cooling plants. Due to its complexity and importance, a cost effective and accurate control technique is a necessity to ensure system reliability and longevity. As the chiller contains multiple inputs and outputs, two advanced multivariable control techniques were selected to control the chillers cooling capacity, exit chilled liquid temperature of the evaporator as well as to reject disturbances. The advanced techniques covered in this framework are the Linear Quadratic Integral (LQI) and Model Predictive Control (MPC). Both were successfully applied to the chiller’s model for multiple testing cases …

Exploring Search-By-Video Technology For Searching Structured Human Movements: Insights From Sign Language Look-Up Systems, Saad Hassan

Theses

Identifying unfamiliar human movements is crucial across several tasks and fields, including skill acquisition and human movement analysis research. With the advancements in computer vision technology, search systems can be developed that allow users to search for human movements by submitting a video sample. A clear example of such systems is search-by-video sign-language look-up systems. The advances in sign-language recognition technology have made it feasible to design these systems, which allow users to generate queries by either submitting a video of themselves performing the word or by submitting a video segment containing the unknown sign. These systems can be particularly …

Incorporating High Dynamic Range Into Multispectral Imaging For Cultural Heritage Documentation, Gabrielle Brogle

Theses

The dynamic range that can be captured using traditional image capture devices is limited. While an image sensor cannot capture the entire dynamic range that the human eye can see, imaging techniques have been developed to help accomplish this. High dynamic range imaging has been incorporated into digital photography pipelines to produce high-quality images with correctly exposed regions with varying illumination. The multiple exposures are fused together in post- processing. By capturing a broader dynamic range, the range of contrast captured is also increased, helping to improve color accuracy. Cultural heritage institutions face limitations when trying to capture color accurate …

Techniques To Create A Realistic Digital Collection Of Near Planar Cultural Heritage Objects, Snehal A. Padhye

Theses

Cultural heritage objects like paintings and manuscripts are a rich source of information about human history and a lot has been discovered through their study. A great collection of such artifacts is scattered around the globe in various libraries and research institutions. Digital images of the objects make them accessible to a greater audience, but images offer only a limited experience compared to observing the real thing. Public access to institutions got further limited during pandemic times, further increasing importance of techniques that enable rich access to such objects remotely. In addition, due to the physical nature of these often …

Lead Scoring Using Low Code Ml Library, Ayad Aziz

Theses

Scoring leads manually can be time-consuming and ineffective because it relies on subjective criteria and human biases. On the other hand, automated lead scoring uses advanced algorithms to analyse large datasets and accurately predict a lead's potential value to the business. It provides valuable insights into customer behaviour and preferences that inform marketing and sales strategies. Machine learning algorithms are trained on historical sales data to identify patterns and correlations that indicate a lead's likelihood to convert. They consider variables like demographic information, web behaviour, and marketing engagement to generate a lead score that reflects the probability of converting into …

Investigating The Impact Of Baselines On Integrated Gradients For Explainable Ai, Ajay Shewale

Theses

Deep Neural Networks have rapidly developed over the last few years, demonstrating state-of-the-art performances on various machine learning tasks such as image classification, natural language processing, and speech recognition. Despite their remarkable performance, deep neural networks are often criticized for their need for more interpretability, which makes it difficult to comprehend their decision-making process and get insights into their workings. Explainable AI has emerged as an important area of study that aims to overcome this issue by providing understandable explanations for deep neural network predictions. In this thesis, we focus on one of the explainability methods called Integrated Gradients (IG) …

A Graph-Based Approach To Studying The Spread Of Radical Online Sentiment, Le Nguyen

Theses

The spread of radicalization and extremism through the Internet is a growing problem. We are witnessing a rise in online hate groups, inspiring the impressionable and vulnerable population towards extreme actions in the real world. Though the body of research to address these issues is growing in kind, they lack a key understanding of the structure and behavior of online extremist com- munities. In this thesis, we study the structure and behavior of extremist online communities and the spread of hateful sentiments through them to address this gap in the research. We propose a novel Graph-Based Approach to Studying the …

The State Of Accessibility In Blackboard: Survey And User Reviews Case Study, Mohamed Wiem Mkaouer, Wajdi Aljedaani, Stephanie Ludi, Mohammed Alkahtani, Marcelo M. Eler, Marouane Kessentini, Ali Ouni

Articles

Context: Nowadays, mobile applications (or apps) have become vital in our daily life, particularly within education. Many institutions increasingly rely on mobile apps to provide access to all their students. However, many education mobile apps remain inaccessible to users with disabilities who need to utilize accessibility features like talkback or screen reader features. Accessibility features have to be considered in mobile apps to foster equity and inclusion in the educational environment allowing to use of such apps without limitations. Gaps in the accessibility to educational systems persist.

Objective: In this paper, we focus on the accessibility of the Blackboard mobile …

Physiological Signals And The Effects On Prediction Of Future Blood Glucose Values In A Deep Learning Model, Andrew Rearson

Theses

Diabetes is a chronic disease that currently has no cure. However, in the last decade, life- changing technology for people with diabetes has advanced primarily due to new sensors that continuously measure glucose. Individuals with diabetes manually use this data for diabetes management, but the artificial intelligence community has seen the increase in data as an opportunity to work towards automating diabetes control. The project developed deep-learning neural networks incorporating blood glucose measurements measured by a continuous glucose monitor (CGM) and physical activity data from a wearable health sensor (WHS) to predict future glucose values and compare how different configuration …

Implementation Of Model-Free Sliding Mode Control On A Multi-Input Multi-Output System, Walker Hare

Theses

Bioinspired flight serves to balance the advantages of fixed-wing flight as well as traditional rotary systems. A flapping wing aerial system exhibits high maneuverability at low speeds like a rotary system and the higher efficiency that fixed-wing systems exhibit in forward flight. A method to actuate a flapping wing structure is using piezoelectric elements. Using flapping wings to perform aerial maneuvers and facilitate stable flight will require precise control of the piezoelectric elements and control surfaces. The focus of the research is the construction of a feedback control platform for the flapping wing aerial system. For any type of feedback …

Care: Towards Customized Assistive Robot-Based Education, Nafisa Abdul Razak Maaz

Theses

Purpose of the Study The aim of this paper is to propose a solution for enhancing the learning experience of elementary school students by combining Artificial Intelligence (AI) and robotics in education. Our AI-powered system aims to classify students according to their intellectual abilities and offer personalized educational materials to assist their progress. Summary We propose using a personalized tutor robot to aid students in their learning. The robot categorizes students into three groups – High-Ability Student (HAS), Average-Ability Student (AAS), or Low-Ability Student (LAS) - based on their performance, facial expressions, and subjective feedback. The robot then displays educational …

The De-Indigenisation Of The English Language: On Linguistic Idiosyncrasy, Fayssal Bensalah

Journal of Creative Writing Studies

This paper introduces and explains a fresh adaptation of linguistic hybridity. This creative strategy is common among postcolonial, transnational and transcultural writers, who would import linguistic features from their first languages to hybridise their prose and paint it with a distinctive identity. I aim, however, to demonstrate that my English text can be hybridised without looking outside the English language, but rather by looking within it. The English language, as I argue, is already a hybrid language, populated by thousands of words borrowed from various languages, including Arabic. The words of this latter, if used intelligently and selectively in my …