Digital Commons Network^™

Scene Decomposed Blind Deconvolution And Neural Network Based Multi-Frame Image Restoration Techniques For Astronomical Imagery, Joshua S. Sprang

Theses and Dissertations

Ground based astronomical imaging is an important method in gaining situational awareness of orbiting and far off objects in space. This method of imaging is accessible to everyone that can look up into the sky, but the accessibility to digital telescope systems allows for more exciting methods of extracting information. A use case for these telescopes is finding nearby objects to larger brighter known objects. The number satellites in low-earth orbit and geosynchronous earth orbit is becoming more congested as these orbits increase in population. Tens of thousands of satellites and debris now exist in this orbit, with the number …

An Analysis Of Electrical Energy Resilience Technologies As Applied To Air Force Operations, Eric D. Danko

Theses and Dissertations

An analysis of 46 Resilient Energy Devices and Technology Concepts was conducted to determine their suitability for use in supporting Air Force Operations both at home station and abroad. The research consisted of two endeavors: an extensive literature review and a rank-ordering matrix. The dual nature of the efforts was designed to maximize usability and understanding for the End User, who may not be familiar with some principles of energy technologies, resilience, or design. The results showed the superiority of novel Solid (Metal) Fuels and Lead-Acid Batteries for Energy Storage and Thermoelectric Generators, Solar Photovoltaic Panels, Geothermal Extraction, Diesel Generators, …

Machine Visual Perception For Autonomous Docking Maneuvers, Derek B. Worth

Theses and Dissertations

This dissertation presents a novel approach to autonomous docking using machine learning for visual perception, particularly during probe and drogue aerial refueling. Autonomous vehicles have become pervasive in both civilian and defense sectors, and their ability to interact with their surroundings and each other autonomously is critical for future operations. Traditional methods relying on signals or inertial sensors face significant limitations such as interference, jamming, and drift. This research focuses on developing a computer vision-based solution to overcome these limitations. A novel pipeline, termed relative vectoring, is introduced, which utilizes dual object detection and machine learning to estimate relative positions …

Performance Evaluation And Integration Of Distortion Mitigation Methods For Fisheye Video Object Detection, John Benedict Du, Gian Paolo Mayuga, Maria Leonora Guico

Electronics, Computer, and Communications Engineering Faculty Publications

The distortion observed in fisheye cameras has proven to be a persistent challenge for numerous state-of-the-art object detection algorithms, instigating the development of various techniques aimed at mitigating this issue. This study aims to evaluate various methods for mitigating distortion in fisheye camera footage and their impact on video object detection accuracy and speed. Using Python, OpenCV, and third-party libraries, the researchers modified and optimized said methods for video input and created a framework for running and testing different distortion correction methods and object detection algorithm configurations. Through experimentation with different datasets, the study found that undistorting the image using …

Deep Learning Technique For The Classification Of Stress Among The Students Using Physiological Biomarkers With A Hybrid Feature Approach, Rajendran Vg

Theses and Dissertations

Adolescence is a crucial part in life, and the presence of stress, anxiety, depression, and health issues during this stage is a great concern. This research aims to analyze and predict the cognitive stress in students during the examination period using EEG biomarkers. In this study, raw EEG data is acquired under two different experimental conditions, before and after examination, from 14 subjects with an eight-channel Enobio device. After preprocessing of the EEG signal, the brain rhythms such as theta, alpha, and beta sub-band energies and EEG band ratios such as neural activity, heart rate, arousal index, vigilance index and …

Remote Sensing Assessment Of Ionospheric Total Electron Content Over Thanjavur Gps Station Geomagnetic 2.91 N 152.22 E, Veera Kumar Maheswaran

Theses and Dissertations

A Global Positioning System (GPS) station for ionosphere studies was established during December 2019 in Thanjavur (Geographic 10.72◦ E, 79.01◦ N, Geomagnetic 2.91◦ N, 152.22◦ E). The study involved analysing Total Electron Content (TEC) data and correcting biases to estimate Slant Total Electron Content (STEC). STEC was then converted to Vertical Total Electron Content (VTEC), useful for space weather, navigation, surveying, and environmental monitoring.

During the course of our study, this Thanjavur station witnessed a Annular Solar eclipse of Dec-26, 2019. The Solar eclipses can impact ionospheric conditions, causing VTEC depletion. This study shows how the near-earth environment changes during …

Clustering Algorithm Based On Similarity Of Objects, Akhram Khasanovich Nishanov, Alisher Tulkunovich Tursunov, Fayzullo Farhod O'G'Li Ollamberganov

Chemical Technology, Control and Management

The article discusses the problem of drug clustering. Initially, k classes are randomly formed and the resulting training sample is preprocessed, then the similarity between objects of each class is assessed based on the proximity function and the criterion for assessing the contribution of objects to the formation of their own class. It is usually expressed as a percentage and represents the degree of mutual similarity of objects of each class. In the next steps of the algorithm, first one object is taken from the first class and by adding it to all k classes, the contribution of this object …

Developing Decision-Making Models And Algorithms To Help Prevent Emergencies, Mizaakbar Xakkulmirzayevich Hudayberdiyev, Oybek Zokirovich Koraboshev

Chemical Technology, Control and Management

The article is devoted to the solution of the scientific issue of decision-making support for the prevention and elimination of the consequences of emergency situations. The relevance of this issue is related to the need to develop a theoretical basis for optimizing the risk of adverse effects on human health and the environment in connection with emergency situations, and a predictive model for the development of emergency situations and their prevention or elimination of their consequences. The optimization of the importance measure of signs for predicting the values of the factors of fire conditions has been carried out. In addition, …

Scla 521 Ai In Society, Bert Chapman

Libraries Faculty and Staff Presentations

Provides access to information resources on societal impacts of artificial intelligence from multiple libraries databases covering multiple disciplines including government information resources.

Fpca-Setcn: A Novel Deep Learning Framework For Remaining Useful Life Prediction, Junde Chen, Yuxin Wen, Xuxue Sun, Adnan Zeb, Mohammad Saleh Meiabadi, Sasan Sattarpanah Karganroudi

Engineering Faculty Articles and Research

The accurate prediction of remaining useful life (RUL) can serve as a reliable foundation for equipment maintenance, thereby effectively reducing the incidence of failure and maintenance costs. In this study, a novel deep learning (DL) framework that incorporates functional principal component analysis (FPCA) and enhanced temporal convolutional network (TCN) is proposed for RUL prediction. Precisely, FPCA is employed to capture the changing patterns in multistream degradation trajectories. Subsequently, the reconstructed signals from FPCA are fed into a convolutional block for extracting deep-level features. An enhanced squeeze-and-excitation (ESE) block is then incorporated into the network for adaptive feature recalibration, enhancing the …

Unveiling The Indoor Performance Of Perovskite/Silicon Tan‑Dem Solar Cells: A Comprehensive Exploration Through Numerically Modelled Energy Band Diagrams, Ziad Khalifa, Sameh O. Abdellatif, Alexander De-Bernardinis, Muath Alkadi, Mostafa Ganoud, Saif Qaid

Chemical Engineering

This paper delves into the indoor performance analysis of Perovskite/Silicon Tandem Solar Cells (PSSTC) through a detailed exploration utilizing numerically modeled energy band diagrams. The primary objective is to uncover the potential of PSSTC for solar energy conversion in indoor settings. Various tandem cell configurations are scrutinized under diverse artificial lighting spectra, with an innovative Li4Ti5O12/ CsPbCl3/MAPbBr3/CH3NH3PbI3/ Si architecture achieving an exceptional maximum power conversion efficiency of 25.25%. This represents a substantial efficiency enhancement of nearly 7% compared to standalone Silicon cells. The study underscores the significance of design optimization in maximizing performance. The energy band diagram analysis reveals a …

Data Communication Over Power-Lines: A Review On Technical, And Applications Challenges, Abdi Abdalla

Tanzania Journal of Engineering and Technology (TJET)

This paper presents a review study on the data communication over power-lines, commonly referred to as power-line carrier, power-line communication (PLC), mains communications, or power-line digital subscriber line (PDSL). This study examines the technical and application advantages and challenges associated with adopting PLC as a preferred alternative technology for wideband or broadband data communication. The broader coverage area of the PLC network gives it a distinct advantage over other communication network technologies. Additionally, implementing a communication system using the existing power-line network is more cost-effective and less time-consuming compared to constructing a new network from scratch. However, the primary challenge …

Investigations Of Cell Tower Antennas Parameters On Reduction Of Radio Frequency Radiation Levels From Radio Base Stations, Florence U. Rashidi

Tanzania Journal of Engineering and Technology (TJET)

The widespread deployment of mobile cellular base stations in populated areas has raised public health concerns due to increased exposure to radio frequency (RF) radiation emissions. Exposure to high levels of RF radiation can have potential thermal and non-thermal biological effects. Optimizing the configuration of cell tower antenna parameters is crucial for mitigating these radiation levels. This study therefore aims at systematically investigating the influence of different cell tower antenna parameters on reducing the RF radiation levels from mobile base stations. Field measurements were conducted at two cell sites shared by multiple mobile operators. Electric field strengths were measured at …

Evaluation Of Business-Driven Reference Architecture For Big Data Analytics Implementation By Public Sector Organizations In Resource-Constrained Setting: A Case Study Of Uganda, Matendo Didas

Tanzania Journal of Engineering and Technology (TJET)

Big Data Analytics (BDA) is a new area at the nexus of agenda, public sector organizations, and government business. It may satisfy the growing need for trustworthy, cost-effective services in the public sector for better, more informed decision-making processes. BDA has been proposed on the planning schedules of several public sector organizations and the government. Therefore, from the previous work, using Uganda as a case study, specifically the Uganda Bureau of Statistics (UBOS), Ministry of Health (MoH), and Ministry of Education and Sports (MoES), this study aims to evaluate a designed Business-Driven Reference Architecture for Big Data Analytics Implementation (BRABDAI) …

Assessment Of The Factors Affecting The National Ict Broadband Backbone (Nictbb) Systems Restoration Time, Victoria Mahabi

Tanzania Journal of Engineering and Technology (TJET)

This study investigates the factors affecting the prolonged system restoration time when national ICT broadband backbone (NICTBB) services are affected by breakdown incidents. NICTBB is the government-owned backbone infrastructure constructed nationally by the Republic of Tanzania to increase the usage of ICT for equitable and sustainable socio-economic development and accelerate poverty reduction. This study utilised a mixture of exploratory and descriptive study approaches. The sample size determination was executed using purposing and simple random sampling, thus involving 289 respondents. The data reliability test was undertaken. It was followed by factor analysis, analysis of variances (ANOVA), linear regression analysis, and confirmed …

Assessment Of Web Security Vulnerabilities For Common Open Source Virtualization Software, Said Ally

Tanzania Journal of Engineering and Technology (TJET)

Open-source hypervisors have emerged as an integral technology for virtualizing server resources in cloud and data center computing. Hypervisor security efficiency is determined by virtual machine isolation, which is a de facto adoption factor in the selection process, as well as its ability to respond to web attacks. This paper assesses the security performance of Proxmox VE and XenServer for type 1 hypervisors, and Kernel Virtual Machine and Oracle Virtual Box for type 2 hypervisors. Security analysis was conducted using common exposures extracted from vulnerability databases and mapped against the OWASP 2013 and 2017 projects. For clarity, experiments were carried …

Developing A Hierarchical Digital Twin Framework For Dc Microgrid Implementation, Khari Sado

Theses and Dissertations

This research introduces a hierarchical digital twin framework for DC microgrids implementation, particularly those utilized in naval power systems. Unlike traditional digital twins, this hierarchical digital twin structure offers a layered perspective. Hierarchical digital twin design promotes computational efficiency by distributing computational burden across a layered configuration that integrates lower-level digital twin blocks with a system digital twin. The layered approach breaks down complex systems into smaller manageable units that can be examined individually and collectively. Central to this strategy is the adoption of a multi-domain and multi-functional technique through the integration of the digital image framework. This allows the …

Extended Time, Elevated Expectations: The Unappreciated Downsides Of Pausing The Tenure Clock, Maria A. Holland, Katharina Maisel, Carolyn B. Ibberson, Laura K. Wiley, David C. Burnett, Emily M. Mace, Mary Williard Elting

Electrical and Computer Engineering Faculty Publications and Presentations

In 1971, Stanford became the first university to introduce tenure clock extensions in academia for new mothers. The American Association of University Professors (AAUP) began recommending such policies a few years later, and in 2001, modified their recommendation to include primary or coequal caregivers, following either the birth or adoption of a child (1). By 2004, 43% of 255 surveyed institutions had formal clock-stop policies...

Cybersecurity, Image-Based Control, And Process Design And Instrumentation Selection, Dominic Messina, Akkarakaran Francis Leonard, Ryan Hightower, Kip Nieman, Renee O'Neill, Paloma Beacham, Katie Tyrrell, Muhammad Adnan, Helen E. Durand

Chemical Engineering and Materials Science Faculty Research Publications

Within an Industry 4.0 framework, a variety of new considerations are of increasing importance, such as securing processes against cyberattacks on the control systems or utilizing advances in image processing for image-based control. These new technologies impact relationships between process design and control. In this work, we discuss some of these potential relationships, beginning with a discussion of side channel attacks and what they suggest about ways of evaluating plant design and instrumentation selection, along with controller and security schemes, particularly as more data is collected and there is a move toward an industrial Internet of Things. Next, we highlight …

Perovskites Informatics: Studying The Impact Of Thicknesses, Doping, And Defects On The Perovskite Solar Cell Efficiency Using A Machine Learning Algorithm, Zahraa Ismail, Eman Sawires, Fathy Amer, Sameh O. Abdellatif

Electrical Engineering

No abstract provided.

Healthcare Assistance Challenges-Driven Neurosymbolic Ai, Kaushik Roy

Publications

Although Artificial Intelligence technology has proven effective in providing healthcare assistance by analyzing health data, it still falls short in supporting decision-making. This deficiency largely stems from the predominance of opaque neural networks, particularly in mental health care AI applications, which raise concerns about their unpredictable and unverifiable nature. This skepticism hinders the transition from information support to decision support. This presentation will explore neurosymbolic approaches that combine neural networks with symbolic control and verification mechanisms. These approaches aim to unlock AI’s full potential by enhancing information analysis and decision-making support for healthcare assistance.

A Measure Of Interactive Complexity In Network Models, Will Deter

Northeast Journal of Complex Systems (NEJCS)

This work presents an innovative approach to understanding and measuring complexity in network models. We revisit several classic characterizations of complexity and propose a novel measure that represents complexity as an interactive process. This measure incorporates transfer entropy and Jensen-Shannon divergence to quantify both the information transfer within a system and the dynamism of its constituents’ state changes. To validate our measure, we apply it to several well-known simulation models implemented in Python, including: two models of residential segregation, Conway’s Game of Life, and the Susceptible-Infected-Susceptible (SIS) model. Our results reveal varied trajectories of complexity, demonstrating the efficacy and sensitivity …

Feasibility Study Of Using Energy Extracted From The Process Of Electrochemically Consumed Of Al 2024 For Powering Daily Used Electric Car, Yanuar Mohamad Marda, Rini Riastuti, Muhammad Hamka Ibrahim

Journal of Materials Exploration and Findings

Usage of green energy for transportation has become important due to the contribution of transportation activity to climate change. Electrochemical energy has been used as a source of green energy. The objective of this work is to evaluate sufficiency of energy provided by electrochemically consumed Al 2024 for supplying energy to daily used PHEV electric car. Study of previous articles, observation of typical amount of energy required, electrochemical galvanic cell experiments, and simple calculations have been conducted to determine produced energy feasibility. Electrical energy produced by consuming 340 gr of Al 2024 in galvanic cells has the total lifetime of …

Enhancing Fundraising Strategies In Higher Education Through Machine Learning, Laith Alatwah

Electrical Engineering Theses

This thesis presents a comprehensive application of machine learning techniques, namely Fine Gaussian SVM and RUS Boosted Trees, to enhance fundraising strategies in higher education institutions. Analyzing a rich dataset from Blackbaud Raiser's Edge NXT, spanning 2012 to 2022, the study focuses on donor profiles, including demographics, donation history, and engagement patterns. Key demographic insights include the increasing engagement of younger donors (20-29 age group) and significant contributions from older donors (70-99 age group). Geographical trends are also examined, revealing distinct patterns based on donors' city, state, and ZIP code. The Fine Gaussian SVM model demonstrates moderate discriminatory power, with …

Assessment Of Economic Viability Of Direct Current Fast Charging Infrastructure Investments For Electric Vehicles In The United States, Daniel Bernal, Adeeba A. Raheem, Sundeep Inti, Hongjie Wang

Electrical and Computer Engineering Faculty Publications

As the global transportation sector increasingly adopts electric vehicles, the demand for advanced and accessible charging infrastructure is rising. In addition to at-home electric vehicle (EV) charging, there is a growing need for the swift development of commercial direct current fast charging (DCFC) stations to meet on-the-go EV charging demands. While government funds are available to support the expansion of the EV charging network in the United States, the establishment of a robust nationwide EV charging infrastructure requires significant private sector investment. This study was conducted to assess the economic feasibility of various business models for fast charging stations in …

Design Of A Portable Fast Scan Cyclic Voltammetry Device Utilizing Pulse Width Modulation For Waveform Generation, Nora Szymkowski

Masters Theses

Fast Scan Cyclic Voltammetry (FSCV) is a widely used electrochemical technique for real-time measurement of the brain’s chemical messengers, including the molecule dopamine, with high temporal resolution. Currently the financial burden of performing FSCV is quite high, ranging from $8,000 to $20,000+ making the barrier to entry nearly insurmountable for laboratories and classrooms at small institutions. The purpose of this project was to develop a Do-It-Yourself (DIY), portable, and cost-effective FSCV system for use in laboratory and classroom settings. The project aimed to create a compact and cost-effective system that could be used by researchers and educators to study dopamine …

Multivariate Analysis Of The Temporal And Spatial Correlations Of The Global Human Rights Dataset, Amanda Goodrick, Skip Mark, Mikhail G. Filippov, David Cingranelli, Hiroki Sayama

Northeast Journal of Complex Systems (NEJCS)

We propose an extension of a previously proposed method for lead-lag analysis of multivariate time series to include the analysis of spatial correlations. We applied the extended spatial and temporal method to CIRIGHTS, a large global human rights dataset, in order to determine the most influential and most influenced indicators of human rights, freedoms, and atrocities over time. We consider four target countries, each from a different continent. The previously proposed method used a weighted directed network with several lags of each variable as nodes and with edges weighted by transfer entropy. In this study, that method is extended to …

Novel Sensors, Algorithms And Metrics For Human-Robot Interaction., Henry Lee Reynolds

Electronic Theses and Dissertations

The increased presence and deployment of robotics in sectors such as the medical field results in the demand for robots to, directly and indirectly, interface with people and their environment, making human-robot interaction (HRI) a vital thrust of robotics research. Assistive robots, for example, aid humans in accomplishing tasks or by providing support in the workforce. As the demand for nurses and the aging population increases, the assistive robots deployed will be deeply rooted in environments that require constant interaction with humans. This work contributed to improving aspects of HRI through 1) Expanding accessibility of the methods used for interfacing …

Reinforcement Learning Assisted Communication Resources Optimization In Advanced Air Mobility., Ruixuan Han

Electronic Theses and Dissertations

Advanced air mobility (AAM), which envisages a safe and efficient aviation transportation system, has drawn significant attention to support the increasing mobility demand in metropolitan areas. Communication services for AAM aerial vehicles (AVs) are crucial for ensuring flight safety. This dissertation explores three research topics on communication resource allocation problems in AAM applications. The first topic, addressed in Chapter II, investigates the joint velocity selection and spectrum allocation problem for AAM applications to enhance spectrum utilization efficiency (SUE). In the AAM scenario, multiple AVs travel along predefined paths for passenger and cargo deliveries. Given that AAM aims to provide fast …

Federated Learning In Wireless Networks, Xiang Ma

All Graduate Theses and Dissertations, Fall 2023 to Present

Artificial intelligence (AI) is transitioning from a long development period into reality. Notable instances like AlphaGo, Tesla’s self-driving cars, and the recent innovation of ChatGPT stand as widely recognized exemplars of AI applications. These examples collectively enhance the quality of human life. An increasing number of AI applications are expected to integrate seamlessly into our daily lives, further enriching our experiences.

Although AI has demonstrated remarkable performance, it is accompanied by numerous challenges. At the forefront of AI’s advancement lies machine learning (ML), a cutting-edge technique that acquires knowledge by emulating the human brain’s cognitive processes. Like humans, ML requires …