Engineering Commons^™

Field Canals Improvement Projects Duration Prediction: A Comparative Analysis Of Machine Learning Models, Hania Ghouse, Ukaegbu Chinonso Ishmael, Edgar Dario Obando-Paredes, Hashem Shafik Shakir, Ali Al-Bayaty

Electrical and Computer Engineering Faculty Publications and Presentations

There are several essential elements in project construction management to be studied appropriately, and priority to these elements, such as cost and duration, is predominantly interesting to be investigated. In this research, the duration of field canal improvement projects (DFCIP) was predicted using two relatively new machine learning (ML) models - the Multivariate Adaptive Regression Spline (MARS) and Extreme Learning Machine (ELM). The targeted DFCIP was calculated using other dependent parameters, such as the length of the pipe, years of construction, the geographical zone of the network, the supplied area with water, and finally the actual cost of the field …

Yolo-Based Marine Search And Rescue Using Uav Multi-Dataset In Challenging Weather Conditions, Aysha Alshebli

Thesis/ Dissertation Defenses

Object detection models, powered by deep learning and computer vision, are revolutionizing marine search and rescue (SAR). By analyzing aerial imagery and live drone footage, these systems automatically identify critical targets like survivors, life rafts, and debris across vast and treacherous ocean areas. This capability enhances operational efficiency by reducing human workload and accelerating response times, even in challenging conditions such as poor light, high seas, or cluttered backgrounds. The result is continuous monitoring, faster decision-making, and a significantly improved probability of successful rescue.

Departing from prior methodologies, YOLO introduced a paradigm shift through its single-shot architecture, which concurrently predicts …

Investigate The Performance And Airtightness Of Short Carbon Fiber Reinforced Polypropylene Pressure Vessel Fabricated Via Fdm 3d Printing, Trad Abdallah Abualbandora

Thesis/ Dissertation Defenses

This work offers a thorough investigation into the performance of 3D-printed, short carbon fiber-reinforced polypropylene pressure vessels, specifically designed for gas storage in demanding sectors like aerospace, drones, and medical equipment, operating within a pressure range of 0-10 bar. A key challenge in FDM additive manufacturing of pressure vessels is achieving airtightness due to the inherent porosity and micro-gaps resulting from the printing process. To address this, the fabricated vessel models were coated with various commercially available materials to effectively fill these microscopic imperfections and ensure the necessary tightness. Spray coating and adhesion coating materials were applied to the outer …

Notes For Contributors, Editors Space And Defense

Space and Defense

No abstract provided.

Review Article: International Relations: State Of The Field. Paul R. Viotti’S Kenneth Waltz: An Intellectual Biography (Ny: Columbia University Press, 2023)., Damon Coletta

Space and Defense

In this review essay, Damon Coletta examines Paul R. Viotti’s Kenneth Waltz: An Intellectual Biography (Columbia University Press, 2023), positioning it as both a tribute to and a reexamination of one of International Relations’ most influential theorists. Viotti, a former student of Waltz, reconstructs the intellectual development of structural realism—tracing its philosophical and methodological roots from Man, the State, and War (1959) to Theory of International Politics (1979)—while situating Waltz’s scholarship within the geopolitical and academic transformations of the Cold War era. Coletta highlights Viotti’s skillful balance between biography and disciplinary analysis, showing how Waltz’s systemic approach to international politics …

Review Article: Monetary Power And National Security. A 10th Anniversary Review Of Paul R. Viotti’S The Dollar And National Security: The Monetary Component Of Hard Power (Stanford, Ca: Stanford University Press, 2014), Ricardo Crespo

Space and Defense

In this ten-year retrospective, Ricardo A. Crespo reassesses Paul R. Viotti’s The Dollar and National Security (2014) as a foundational text bridging the fields of monetary policy and national security. Viotti’s central thesis—that military power ultimately depends on a stable and privileged monetary foundation—has only grown more relevant amid today’s weaponization of finance and the geopolitics of sanctions. Crespo highlights Viotti’s argument that sustaining the U.S. dollar’s global dominance requires cooperative security and international consensus, noting how historical parallels—from the sterling gold standard to Bretton Woods—illustrate the fragility of monetary hegemony under fiscal mismanagement or political fragmentation. The review situates …

Plan To Fail By Failing To Plan: Deterring Prc Nuclear Force Expansion, Mark Tang, Grace Buettner

Space and Defense

This article argues that the United States must adapt its nuclear deterrence strategy to counter the People’s Republic of China’s (PRC) accelerating nuclear force expansion. As Beijing seeks to achieve nuclear parity with Washington—projecting up to 1,500 warheads by 2035—the authors contend that U.S. strategy must evolve from Cold War-era models to meet the Indo-Pacific’s unique strategic challenges. They propose the establishment of a Pacific Air Forces (PACAF) A-10 Strategic Deterrence and Nuclear Integration Division, modeled after its European counterpart, to enhance regional nuclear planning, integration, and allied assurance. The paper emphasizes the concept of escalation domination, arguing …

Earth’S Orbital Prison: Codifying Customary Law To Prevent Environmental Catastrophe In Space, Jacob Cook

Space and Defense

This article argues that the accelerating proliferation of space debris in low Earth orbit (LEO) poses an existential threat to the sustainability of the orbital environment—one comparable in strategic gravity to nuclear deterrence during the Cold War. Drawing on liberal internationalist theory and the concept of Mutually Assured Destruction (MAD), the paper asserts that deliberate satellite destruction through anti-satellite (ASAT) testing and negligent debris generation risk triggering a self-sustaining cascade of collisions known as the Kessler Syndrome. Existing treaties, including the Outer Space Treaty and the Artemis Accords, lack enforceable mechanisms to prevent such catastrophic harm. To fill this …

Enabling The Decisive Advantage, Mallory Stewart

Space and Defense

In her keynote address at the 2025 USSPACECOM Legal Conference, former Assistant Secretary of State Mallory Stewart argues that law, norms, and international cooperation are central to maintaining the United States’ “decisive advantage” in outer space. She emphasizes that rules and standards—far from constraining innovation or strategic flexibility—enhance predictability, reduce risk, and empower responsible competition. Stewart highlights the success of initiatives such as the Artemis Accords, the U.S. commitment to forgo destructive direct-ascent anti-satellite (ASAT) tests, and the global expansion of Space Situational Awareness (SSA) agreements as examples of how legal and normative frameworks reinforce stability and collaboration. She …

Space, Law, And National Security, Stephen Whiting

Space and Defense

In his address to the 2025 USSPACECOM Legal Conference, General Stephen Whiting underscores the indispensable role of legal professionals in shaping the future of military space operations and maintaining the rules-based international order in an increasingly contested domain. He outlines the rapid transformation of the space environment driven by commercial innovation, technological proliferation, and the accelerating threat landscape posed by adversaries such as China and Russia. The speech highlights U.S. Space Command’s three “moral responsibilities”: ensuring the delivery of space capabilities to the joint force and allies, protecting and defending critical space assets, and safeguarding the joint force from space-enabled …

Allied Abandonment And Nuclear Proliferation: Lessons From South Korea’S Secret Nuclear Program, Joseph W. Brown

Space and Defense

This article examines South Korea’s clandestine nuclear weapons program of the 1970s as a historical case study for understanding how perceptions of allied abandonment can drive nuclear proliferation. Drawing on alliance theory and archival evidence, the paper situates Seoul’s nuclear ambitions within the context of U.S. burden-shifting under the Nixon Doctrine, subsequent troop withdrawals, and diplomatic retrenchment across East Asia. Despite the continued U.S. military presence, South Korean leaders interpreted American rhetoric and policy actions as signaling a waning commitment to the alliance, prompting the initiation of a secret weapons program under President Park Chung-hee. The study identifies two enduring …

In Defense Of Space Offense, Alexander R. Kleitz

Space and Defense

This article argues that in the unique physical and operational environment of outer space, offensive operations hold intrinsic advantages over defensive ones. Drawing upon classical military theorists such as Clausewitz and Corbett, the author contends that the traditional dominance of the defensive form of war—rooted in terrestrial conditions—does not extend to celestial conflict. The transparency and remoteness of the space domain neutralize key defensive benefits, such as proximity to supply bases, concealment, and fortified positions, while also diminishing the factors that typically cause terrestrial offensives to culminate. Consequently, space conflict favors the side that seizes and maintains the initiative through …

Raising Public Awareness On Space Themes: Analysis Of Brazilian Space Policy Using Data From Google Trends, Andrea Felippe Cabello, Michele Melo

Space and Defense

This study examines whether Brazil’s national space policy goal of increasing public awareness of space activities has been met, using Google Trends data as a proxy for public interest. While public perception surveys are scarce outside the United States, web-based data provide a cost-effective and timely alternative for gauging public engagement. The authors analyzed two decades (2004–2024) of Brazilian search activity related to space topics, institutions, technologies, companies, and missions. Results show no clear upward trend in public interest, suggesting that Brazil’s stated policy objectives of raising awareness have not yet translated into measurable outcomes. Although searches related to government …

Costly Signals In Space: Increasing Credibility Via Strategic Disclosure, Wendy N. Whitman Cobb

Space and Defense

As space becomes an increasingly vital domain for national security, debates persist about how much secrecy should surround U.S. military space programs. This article argues that the strategic declassification and disclosure of selected space capabilities can strengthen U.S. deterrence by enhancing the credibility of deterrent threats. Drawing from theories of costly signaling and audience costs, the paper introduces strategic disclosure as a novel form of costly signal. Such disclosure imposes bureaucratic and operational costs while exposing capabilities to potential adversary countermeasures—thereby demonstrating resolve and seriousness of intent. In tandem, greater public transparency about space programs cultivates informed domestic audiences capable …

Space And Defense Vol. 16 No. 2 Editor's Note, Damon Coletta

Space and Defense

No abstract provided.

Space And Defense Vol. 16 No. 2 Table Of Contents, Editors Space And Defense

Space and Defense

No abstract provided.

Space And Defense Vol. 16 No. 2 Front Matter, Editors Space And Defense

Space and Defense

No abstract provided.

Space & Defense Volume 16 Issue 2 Fall 2025 (Whole Issue), Editors Space And Defense

Space and Defense

No abstract provided.

Turboindex: Making A Page-Based Db Index Both Memory-Space And Disk-I/O Efficient, Sujit Maharjan, Shuaihua Zhao, Song Jiang

Computer Science and Engineering Faculty Publications - Archive

Traditional Database (DB) systems use a DB buffer, a page-based cache management system, to load data and indexes from block storage devices into byte-addressable main memory. However, this approach is inefficient in terms of space and I/O when key-value pair sizes are significantly smaller than the page size. Inserting a single key-value pair results in reading and writing an entire page, consuming a full page's worth of memory in the buffer. Moreover, the entire page is immediately loaded even when just a single key-value pair is inserted into the page. Also, an infrequently accessed page is likely to be evicted …

Mechanisms Of Correlated Neuronal Activity In The Globus Pallidus, Hamza Albawaliz

Electronic Theses and Dissertations

This thesis investigates the mechanisms of correlated neuronal activity in the globus pallidus externus (GPe), a key structure in the basal ganglia. Neuronal activity in the GPe is reportedly decorrelated in healthy subjects but can become highly correlated in Parkinson’s disease. However, high-density neuronal recordings in the GPe of healthy rats reveal a surprising degree of correlated activity. This raises the question of whether intrinsic properties or network connectivity alone can account for such patterns. To explore this, a computational model was developed in which GPe neurons are represented as coupled phase oscillators influenced by experimentally derived phase-response curves and …

Development Of A Non-Faradaic Impedimetric Biosensor Based On Reduced Graphene Oxide For The Detection Of Brain-Derived Neurotrophic Factor (Bdnf), Mariana N. Martins

Electronic Theses and Dissertations

Neurological disorders affect millions of people worldwide. In the case of Alzheimer’s disease (AD), the rising number of cases significantly increases global healthcare costs. Therefore, early detection of biomarkers at the onset of the disease is essential for early diagnosis. This study presents an electrochemical biosensor designed for the detection of Brain-Derived Neurotrophic Factor (BDNF) in human plasma, incorporating reduced graphene oxide (rGO) to enhance signal sensitivity. Dielectrophoresis (DEP) was employed to deposit rGO flakes on the electrode surface, improving conductivity and sensor performance. Electrochemical impedance spectroscopy (EIS) was used to monitor changes in impedance associated with BDNF binding events, …

High Frequency Dc-Dc Converter Design Optimization, Modeling And Control Based-Wbg Technology., Salah Ahmed Abdullah Eltief

Electronic Theses and Dissertations

The performance of DC-DC power converters is a cornerstone of modern electric vehicle (EV) powertrains, directly governing overall system efficiency, size, cost, and reliability. This dissertation presents a comprehensive performance analysis and optimization of DC-DC converter topologies to determine the most suitable design for high voltage EV applications. The evaluation rigorously compares efficiency, power losses, and physical size under a range of harsh operating conditions. A primary objective is to leverage Wide Bandgap (WBG) semiconductors, specifically Silicon Carbide (SiC), to push the performance boundaries of power conversion. While SiC devices are known for their superior material properties, a clear understanding …

Electronic Structure Prediction Of Medium And High Entropy Alloys Across Composition Space, Shashank Pathrudkar, Stephanie Taylor, Abhishek Keripale, Abhijeet S. Gangan, Ponkrshnan Thiagarajan, Shivang Agarwal, Jaime Marian, Susanta Ghosh, Amartya S. Banerjee

Michigan Tech Publications

We propose machine learning (ML) models to predict the electron density — the fundamental unknown of a material’s ground state — across the composition space of concentrated alloys. From this, other physical properties can be inferred, enabling accelerated exploration. A significant challenge is that the number of descriptors and sampled compositions required for accurate prediction grows rapidly with species. To address this, we employ Bayesian Active Learning (AL), which minimizes training data requirements by leveraging uncertainty quantification capabilities of Bayesian Neural Networks. Compared to the strategic tessellation of the composition space, Bayesian-AL reduces the number of training data points by …

Rail Anomalies Dataset For Semantic Segmentation Analysis, Saarah Majid, Arian Izadi, Paul Stanik

Undergraduate Research Symposium Posters

Rail maintenance is a core necessity of upkeep, maintenance, deterioration, and safety implications of large rail systems. Doing so in an orderly and uniform way, however, has proven difficult with the thousands of miles that railways span. Use of computer vision on locomotives during normal operation can allow for a more streamlined process that would eliminate the need for costly specialized equipment and disruptions of normal operations. This project aims to efficiently detect vegetation overgrowth, mud-pumping, and standing water on railways. With the use of machine learning algorithms and dataset curation, models can be trained, allowing them to gain a …

Spatiotemporal Feature Extraction From Vertical Grf Signals For Parkinson’S Disease Severity Assessment Using Physionet And Gaitpd, Nitya Jadeja

Undergraduate Research Symposium Posters

Parkinson’s Disease (PD) is a progressive neurodegenerative disorder that impairs motor coordination, often resulting in measurable gait disturbances. Vertical ground reaction force (VGRF) signals provide a quantitative means of capturing these abnormalities and monitoring disease progression. This study focuses on the extraction and analysis of spatiotemporal gait features such as stride variability, stance duration, and force imbalance, from the PhysioNet Gait dataset to better understand their correlation with PD severity. Using gait analysis and machine learning techniques, recent computational models are reviewed and evaluated for their ability to assess PD progression through VGRF data. The analysis compares data-driven approaches with …

Real-Time Ai-Enabled Therapeutic Device For Improving Peripheral Perfusion And Glucose Regulation In Type 2 Diabetes, Torryana Tanis

Undergraduate Research Symposium Posters

Type 2 Diabetes Mellitus is frequently accompanied by peripheral microvascular disease, leading to impaired lower limb perfusion, impaired healing, and vulnerability to ulcers and amputation. The existing medical devices are predominantly aimed at systemic glucose control and do not have local therapeutic intervention to improve circulation or allow muscular glucose delivery. To meet this crucial demand, we have developed a portable, two-in-one biofeedback device that combines non-invasive blood glucose monitoring and Electronic Muscle Stimulation (EMS) therapy for the calf muscle. The glucose monitoring subsystem implements near-infrared (NIR) spectroscopy to measure skin light absorptance on the index finger. Real-time blood glucose …

Digital Twin Of The Unlv Campus For Safe Autonomous Vehicle Simulation, Carlos Funes

Undergraduate Research Symposium Posters

With the rise of artificial intelligence and machine learning algorithms, self-driving cars are becoming increasingly prevalent on our roads. By utilizing these technologies, we can reduce the number of accidents caused by distracted driving. Before implementing these systems in vehicles, however, it is essential to conduct numerous tests. Traditional evaluation of driverless cars on real-world roads can be both expensive and hazardous. To address this, creating a digital twin of an actual road minimizes unexpected hazards, allowing researchers to safely and efficiently test self-driving car programs in high-risk scenarios using computer simulations. This research outlines the process of generating a …

Diving Video Analysis Using Multitask Learning Action Quality Assessment (Mtl-Aqa), Taylor Gauthier

Undergraduate Research Symposium Posters

In many sports, videos are being used to assist in judging. For example, they are being used to review quick actions or confirm the actions being performed. For diving specifically, the videos of a dive can be at most 3 seconds long, and divers can perform a range of somersaults and twists within that time frame, all of which affect the score, classification, and dive number. Using these videos, a Multitask Learning Action Quality Assessment (ML-AQA) program, based on machine learning, from a vast dataset, is able to produce an Action Quality Score out of 100, Factorized Action Recognition (classifications), …

Capacity, Allocation And Update Dynamics Of Human Memory Systems, Shaoying Wang

Electronic Theses and Dissertations

Information is encoded and stored in three types of memory: sensory memory (SM), short-term memory (STM), and long-term memory (LTM). SM has a large capacity but retains information for only a brief period. When information transfers to STM, only a limited amount can be stored. Information in STM can then be transferred to LTM, which has a much larger capacity and longer retention time. STM is often conceptualized as working memory (WM) to highlight its role in active information processing. Due to the limited capacity of STM, it is commonly believed that STM serves as the bottleneck for information processing. …

Reproducibility In Modeling Of Knee Joint Mechanics, Maryam Nazem

Electronic Theses and Dissertations

Computational modeling of knee joint biomechanics can provide valuable insights into joint function, injury mechanisms, and patient outcomes, and can support surgical planning and informed clinical decision-making. However, achieving consistent and repeatable results, or reproducibility, is a significant challenge that affects the credibility of these models. This thesis addresses reproducibility through two studies related to the KneeHub Project, which is a multi-institutional collaboration designed to investigate reproducibility in finite-element modeling of the knee.

The first study involved model benchmarking, where predicted results of the calibrated models were compared with the experimental data to evaluate model reproducibility. While all models replicated …