Digital Commons Network^™

Characterization And Evaluation Of Next-Generation Photon-Counting Image Sensors For Space Applications, Nicholas Shade, Gillian Kyne, Shouleh Nikzad, Edoardo Charbon, Eric R. Fossum

Dartmouth Scholarship

Astronomers’ pursuit of imaging light from increasingly faint and distant objects in the expanse of space necessitates continuous improvement in the signal-to-noise ratio of camera technology. Recent advancements in solid-state detector technologies have enabled the determination of photon number, including single-photon events, enabling observations at the fundamental limits of physics. We present an evaluation of three next-generation silicon-based detectors capable of photon-counting with deep-sub-electron input-referred read noise: the electron-multiplying charge-coupled device (EMCCD), the single-photon avalanche diode (SPAD), and the CMOS quanta image sensor (QIS). The EMCCD is built using a CCD sensor design that additionally employs repeated impact ionization to …

Experiential Learning And The Revitalization Of Manufacturing Education At The University Of Dayton, Sean Cahill

Research and Reflection on Learning and Teaching in Higher Education

This perspective paper explores the role of experiential learning in preparing future-ready manufacturing engineers at the University of Dayton, set against the backdrop of Dayton’s legacy as an industrial innovator and the broader national movement to revitalize domestic manufacturing. As automation, cyber-physical systems, and Industry 4.0 technologies reshape the manufacturing landscape, there is a growing need for engineers who possess both technical fluency and systems-thinking capabilities. To meet this need, the manufacturing engineering technology department implemented hands-on, integrated lab-and-lecture modules through support from the Experiential Learning Innovation Fund for Faculty (ELIFF). Grounded in Kolb’s Experiential Learning Theory and constructivist learning …

Microgrid Black Start Challenges: The Role Of Grid-Forming Inverters, Gab-Su Seo, Wenzong Wang, Behrooz Mirafzal

Faculty Publications

Grid-forming (GFM) inverters are becoming increasingly important for future power systems, particularly in establishing and restarting microgrids after blackouts. The use of GFM inverters enables microgrids to operate independently of utility power and provide key advantages over synchronous generators in black start scenarios, including rapid startup and stable voltage and frequency support for critical loads. However, inverter-driven black start introduces unique challenges and operational considerations. This article examines key challenges and solutions, emphasizing inverter design, control strategies, and microgrid system requirements. Drawing on analysis, simulation, and experimental results, this article highlights the central role of GFM inverters in ensuring reliable …

Recognition Of Bangla And English Words In Bengali Texts Using A Modified Bert-Base-Ner Model, Md Parvez Hossain, Ohidujjaman Ohidujjaman, Mohammad Shorif Uddin, Mohammad Nurul Huda, Tetsuya Shimamura

Iraqi Journal for Computer Science and Mathematics

A fusion of Bangla and English words is frequently utilized, especially on social media. This phenomenon significantly hampers the learning and preservation of the Bengali language among future generations. This paper proposes a model to recognize Bangla and English words in Bengali texts. In addition, this study converts the detected English words into standard Bangla words. In this work, we redesign the BERT-base-NER model using the training input dataset. BERT is chosen for its strong contextual representation capabilities, which are well-suited to noisy and informal text. BERT-base-NER provides strong contextual embeddings but treats token labels independently, lacking explicit modeling of …

Data-Centric Ai For Eeg-Based Emotion Recognition: Noise Filtering And Augmentation Strategies, Nadieh Moghadam, Rana Hegazy

School of Engineering: Faculty Scholarship

Research in the biomedical field often faces challenges due to the scarcity and high cost of data, which significantly limit the development and application of machine learning models. This paper introduces a data-centric AI framework for EEG-based emotion recognition that emphasizes improving data quality rather than model complexity. Instead of proposing a deep architecture, we demonstrate how participant-guided noise filtering combined with systematic data augmentation can substantially enhance system performance across multiple classification settings: binary (high vs. low arousal), four-quadrant emotions, and seven discrete emotions. Using the SEED-VII dataset, we show that these strategies consistently improve accuracy and F1 scores, …

Attitude Control Of Quadrotor Uav Based On Disturbance Observer And Command Filtering, Boning Li, Ming Chen, Shuchang Qi, Haoran Meng, Lei Wang

Journal of System Simulation

Abstract: A finite-time fault-tolerant control scheme based on backstepping was proposed for the attitude tracking control problem of quadrotor UAVs. A finite-time neural network disturbance observer was designed, which could quickly compensate for the impacts of actuator failures and external disturbances, thereby enhancing the system's robustness. A first-order command filter and a compensation mechanism were introduced, which could avoid the computational complexity caused by differentiating the virtual control law and eliminate the influence of filtering errors. The hyperbolic tangent function was selected as the constraint function for the input torque, which restricted the input signal to prevent excessive magnitude …

Implementation Strategies For Microservice Architecture In The Banking Sector, Gururaj Achar

Walden Dissertations and Doctoral Studies

Information technology (IT) leaders in regulated banking face significant risks related to system complexity and cybersecurity when implementing large-scale systems. Although microservice architecture (MSA) offers enhanced scalability and agility, IT leaders lack specific strategic guidance for its effective adoption within highly regulated banking environments. Grounded in the Technology Acceptance Model, the purpose of this qualitative, pragmatic study was to explore effective MSA adoption strategies for IT architects and managers transitioning legacy systems to support risk and compliance management. Data were collected through semistructured interviews with seven banking IT leaders and were analysed using thematic analysis. Three themes emerged: adoption drivers …

Cooperative Guidance Method Considering Impact Time And Area Sealing, Zheng Guo, Guofei Li, Hua Xiong, Yunjie Wu

Journal of System Simulation

Abstract: To address the problem of multi-vehicle cooperative strike against maneuvering targets, a cooperative guidance method considering impact time control and terminal area sealing was proposed. The distributed disturbance observer was utilized to estimate target maneuvers. Based on the consensus errors of the impact time, the cooperative guidance law in the line-of-sight direction was proposed to achieve simultaneous hits on targets at a specified time. By considering the motion states of targets, the instructions of the terminal area sealing were designed to construct the sliding mode surface and design the line-of-sight guidance law, so as to ensure the convergence of …

Robust Control Of Lcl-Filtered Three-Phase Grid-Tied Inverters Using H∞ Synthesis: Design, Analysis, And Experimental Validation, Mohammad Rousan

Thesis/ Dissertation Defenses

This thesis presents the design, development, and practical implementation of various robust current control strategies for LCL-filtered gridtied inverters, with the aim of maintaining robust stability over a range of plant perturbations, while ensuring high-quality current delivery to the utility grid. Chapter One presents the literature review, while Chapter Two focuses on the modeling of the system under study. In the third Chapter, the system dynamics are augmented with an appropriate servo-compensator to ensure that, at steady-state, the grid current accurately tracks its sinusoidal reference with zero steady-state error, even in the presence of model uncertainties. This augmented system serves …

Cybersecurity Risks Of Freight Rail As Critical Infrastructure, Kira Sun

Discovery Undergraduate Interdisciplinary Research Internship

Our project implements simulated train engineers to operate model train engines on a hybrid twin of a freight rail system. We can then use the model and simulate cyber-security attacks to demonstrate the risks and effects of the attacks. Using existing model train hardware and an Arduino running open-source software, DCC-EX and JMRI, we can control the train engines and various track components and sensors. We program each engine to make safe decisions about what speed and direction to take, using information provided by the various sensors and light signals around the track. When attacks occur, the engines can have …

Secret Key Generation Based On The Physical Layer Characteristics For Iot Networks, Abdullah Dakhlallah Alshamdayn

Doctoral Dissertations

The rapid expansion of low-resource devices, coupled with advances in telecommunications, has significantly increased the number of connected devices and enabled the development of affordable, energy-efficient, portable, and high-performance sensors for diverse applications. However, this convenience comes with security and privacy concerns related to the reliability of hardware, software, and communication infrastructure. The extensive interconnectivity of limited-resource devices and the transmission of large data volumes pose significant security challenges in wireless networks. The future wireless technologies, such as 5G, will enable the transfer of critical data, including personal, financial, military, and industrial information, necessitating secure communication in wireless networks. Generally, …

Towards Robust Autonomous Systems: Handling Multi-Modal Uncertainties In Gps-Denied Environments, Vivya Kalidindi

Doctoral Dissertations

This dissertation focuses on designing a robust and uncertainty-aware framework for autonomous systems operating in GPS-denied environments, such as indoor infrastructures, underground tunnels, and lunar surfaces. The proposed framework addresses the challenges posed by multi-modal uncertainties, including sensor noise, distributional shifts under adverse conditions, and conflicting decision-making preferences. These challenges compromise the reliability and adaptability of autonomous platforms. To overcome these challenges, the proposed framework adopts a layered architecture that integrates advanced methodologies across the sensing, perception, and decision-making layers. At the sensing layer, an Edge-Kalman Filter combined with a density ratio-based update mechanism is employed to reduce aleatoric uncertainty …

How Can Smart Resilience Cities Provide Sdgs? An Integrative Framework Regarding Climate Change Mitigation, Asmaa M. Hassan, Manar A. Kotb

Mansoura Engineering Journal

Urbanization and climate change influence public health and wellbeing, which presents challenges facing architects and urban planners towards providing sustainable and resilient cities. In this context, smart city concept has been adopted to contribute to mitigating such influence. This study aims to conduct a bibliometric analysis within the previous scope. Then an integrative framework for climate change mitigation towards resilient smart cities based on SDGs is accomplished. The results indicate that further efforts are needed to develop “smart tools”, “urban economy”, and “carbon footprint. In addition, the proposed framework provides a significant paradigm shift towards mitigation of climate change impacts, …

A Novel Hybrid Intrusion Detection Model: A New Metaheuristic Approach For Feature Selection Based On Ai Techniques For Cyber Threat Detection, Maryam Mahdi Alhusseini, Alireza Rouhi

Iraqi Journal for Computer Science and Mathematics

The rapid increase in internet usage, digital transformation, and the rise of interconnected devices have greatly expanded the attack surface, introducing new and evolving cybersecurity challenges. Conventional security solutions frequently have difficulty adjusting to complex threats and the vast dimensionality of network traffic data, particularly in the case of imbalanced datasets. To tackle these challenges, this research introduces a Hybrid Intrusion Detection System (HyIDS-EVO) that combines the Energy Valley Optimizer (EVO) for feature selection and dimensionality reduction with machine learning classifiers, which include Support Vector Machine (SVM), Random Forest (RF), Decision Tree (DT), and K-Nearest Neighbors (KNN). The system’s effectiveness …

Promoting Leadership To Enhance Safety In Aircraft Maintenance: A Phenomenological Study Of Aviation Technical Operations, Komi Tete

Doctoral Dissertations and Projects

The purpose of this qualitative phenomenological study was to explore how leadership styles affect the safety practices and overall performance of aircraft maintenance technicians (AMTs) in aviation Technical Operations (TechOps) environments. The study built on previous research indicating that safe and efficient aircraft operations depend on numerous technical and social processes. It focused on the comprehensive lived experiences of AMTs as they related to leadership influence on safety. The transformational leadership theory and safety culture theory guided the study, aligning with the inquiry by explaining how leaders could influence the behavior, motivation, and safety practices of AMTs. Ensuring the safety …

Evaluating Perceived Ease Of Use Of Augmented Reality In Aviation Maintenance: A Technology Acceptance Model Approach, Russell Quenten Gardner Jr.

Doctoral Dissertations and Projects

This quantitative study examines the perceived ease of use (PEU) of augmented reality (AR) technology among two key groups: aviation maintenance students, representing workforce readiness, and professional aircraft maintenance technicians, representing field expertise. This approach offers a comprehensive understanding of AR’s role in maintenance training by accounting for varying levels of participant experience. Addressing the need for innovative methods to improve task accuracy, efficiency, and knowledge retention, this study emphasizes user acceptance as a critical factor for AR adoption. Guided by the Technology Acceptance Model (TAM), this research investigates how technician experience influences perceptions of AR’s usability and whether PEU …

User Interface And Watchstation Improvements Required For Multi-Vehicle Usv Operations, Val Schmidt, Joshua Bergeron

Faculty Publications

In October 2024, the University of New Hampshire and NOAA’s Uncrewed Systems Office embarked on a mapping mission in the Gulf of Maine, simultaneously operating two DriX Un-crewed Surface Vehicles. Goals of the project were focused on testing hypotheses related to concepts of operation, including the safety of operations, cognitive loading of operators, management of vehicle endurance, vehicle logistics, maintenance and field support, refueling and a host of others.

Exploratory Study Of Semiconductor Nanomembranes In Em Applications, Grant D. Heileman

Electrical and Computer Engineering ETDs

Antenna systems are a cornerstone of modern technologies, playing an increasingly vital role in their advancement. As demand for compact, high-performance, and adaptable communication platforms grows reconfigurable antenna technologies are becoming essential. This research explores a novel front-end reconfigurable antenna system (FERAS) architecture that leverages the mechanical flexibility and photoconductive behavior of semiconductor nanomembrane (SNM) devices. By exploiting the emergent properties of ultra-thin silicon (Si) or gallium arsenide (GaAs) nanomaterials and optically exciting these samples using vertical-cavity surface-emitting laser (VCSEL) arrays, this study develops lightweight, low-cost, deployable antenna structures for satellite communications, remote sensing, GPS, and radar. Despite their significant …

Experience With The Stem For Success Internship, Ujwal S. Thirunagari

STEM Month

In this article, I discuss my experience working with the STEM for Success team. I detail some of the challenges I faced in completing the CRT and LED sections, how I addressed these challenges, and the widely applicable skills that I learned.

Evaluating Igf1 And Igf1-R Levels As Risk-Related Indicators And Early Detection Tools In Estrogen Receptor–Positive Breast Cancer, Randa M. Lua’I, Khawla A. Kasar, Marwa A. Hassan

AUIQ Technical Engineering Science

Breast cancer (BC) remains one of the most common malignancies in women, with its development strongly influenced by hormonal and growth factor signaling. The insulin-like growth factor 1 (IGF1) and its receptor (IGF1-R) are increasingly recognized as key contributors to breast carcinogenesis, particularly in relation to estrogen receptor (ER) status. This study aimed to evaluate circulating IGF1 and IGF1-R levels among Iraqi women with BC and to explore their diagnostic and biological relevance. A total of 90 participants were enrolled, including 65 patients with histologically confirmed BC (41 ER-positive and 24 ER-negative) and 25 healthy controls. Serum concentrations of IGF1 …

Cv: Young "Paul" Kim (Computer Engineering), Young "Paul" Kim

ECaMS Department Faculty Curricula Vitae

No abstract provided.

Heritage-Based City Branding Case Study Of Fayoum City, Menna Mounir, Sameir Hammad

Mansoura Engineering Journal

Uniqueness and distinction have become fundamental requirements in promoting and branding cities. Influencing people's perceptions is best achieved by reinforcing the city's identity. This identity is the main component that can transform any ‘space’ into a ‘place’. Promoting a city should extend to highlighting the Heritage, landscape, religious sites, pathways, cuisine, inhabitants, activities, and personal experiences. These elements collectively express the city spirit and enrich visitors’ experience.

This study aims to enhance the image of heritage-based cities by exploring the potential for city branding and leveraging heritage to boost the national economy.

Fayoum was selected as a case study for …

Microstrip Antenna Design Based On Ai And Machine Learning, Waleed Mohamed Sha Moulavi

Thesis/ Dissertation Defenses

Microstrip patch antennas (MPAs) rely on precise impedance matching for efficient power transfer between the antenna and feed line. This is often achieved using a number of different techniques, one of which is the quarter-wavelength transformer (QWT). However, optimizing the width of the QWT presents significant computational and analytical challenges due to the unknown antenna impedance and the absence of explicit design relationships. This thesis aims to overcome these limitations by developing and comparatively evaluating artificial intelligence (AI) models for QWT width optimization. Methods involved Random Forest (RF) and a novel Probabilistic Deep Neural Network (PDNN) on a custom dataset …

First-Principles Theory Of Five-And Six-Phonon Scattering, Yi Xia

Mechanical and Materials Engineering Faculty Publications and Presentations

igher-order phonon scatterings beyond fourth order remain largely unexplored despite their potential importance in strongly anharmonic materials at elevated temperatures. We develop a theoretical formalism for first-principles calculation of five- and six-phonon scatterings using Green’s function techniques based on a diagrammatic formalism, and systematically investigate multi-phonon interactions in Si, MgO, and BaO from room temperature to near melting points. Our calculations reveal dramatically different material-dependent behaviors: while five- and six-phonon processes remain negligible in Si even at high temperatures, they become increasingly important in MgO near its melting point (3100 K) and in BaO at intermediate temperatures (1200 K). Most …

The Resonance Of Desire: A Sonic Exploration And Guide To Recreating Disney’S Signature ‘I Want’ Songs, Aiyanna E. Riley

Electronic Theses and Dissertations

This thesis explores the sonic architecture of Disney’s Renaissance-era “I Want” songs and develops a framework for recreating their signature production style. This study analyzes how vocal timbre, microphone choices, layering, stereo placement, and mixing strategies contribute to the immersive qualities that define the Disney sound. Drawing from historical accounts, interviews with industry professionals, and technical literature, the thesis documents production practices unexamined in scholarly work. Inspired by David Gibson’s The Art of Mixing, my analyses prioritize spatial and textural qualities in Disney mixes, highlighting how sound design shapes narrative impact. The study culminates in two original compositions modeled …

Framework And Methodology For Risk-Based Bridge And Tunnel Asset Management: Risk-Based Asset Ranking And Corridor Prioritization, David Y. Yang, Arash Khosravifar, Diane Moug, Avinash Unnikrishnan

Civil and Environmental Engineering Faculty Publications and Presentations

This report presents the results of Phase II of the project, "Framework and Methodology for Risk-based Bridge and Tunnel Asset Management". The research was carried out at Portland State University in collaboration with engineers and officials at the Oregon Department of Transportation (ODOT) and Federal Highway Administration (FHWA). Using the framework and methodology developed in Phase I of the project, the primary goal of Phase II is to showcase the practical application in risk-based asset management. In particular, the report includes the following two case studies: Case Study I — Weighted hazard scenarios for seismic risk assessment of Oregon Highway …

Design And Implementation Of Home Energy Management System (Hems) In Smart Grid Through Demand Side Management (Dsm), Nirmala Jegadeesan Ms

Theses and Dissertations

The rising global energy demand, combined with environmental concerns and the depletion of conventional energy sources, has driven the need for the development of smarter and more sustainable energy systems. This research focuses on Home Energy Management System (HEMS) using soft computing techniques to optimize load scheduling, enhance energy efficiency, and integrate Renewable Energy Sources (RES) such as solar and battery storage. The primary goal is to balance supply and demand, reduce peak loads, and minimize energy costs while ensuring consumer comfort and system reliability.

Smart grids provide enhanced capabilities compared to conventional grids by enabling bidirectional flows of energy …

Comprehensive Risk Evaluation Framework For Reducing Errors In Critical Airport Systems, Arshad Hameed, Muhammad Umer Farooq

Neutrosophic Systems with Applications

Airports are intricate systems that are subject to a number of operational hazards that might impair safety and cause service interruptions. There is a dearth of thorough approaches designed specifically for airport operations, despite a wealth of research on risk management in several industries. In order to anticipate and prevent breakdowns in vital airport systems, we offer a thorough risk assessment approach that combines quantitative evaluation and human factor analysis. This study uses the decision-making methodology such as MARCOS method to rank the alternatives. The criteria weights are computed in this study. This study uses six criteria and 14 alternatives.

From The Editors, Rully Karim Dr.

Journal of Project Management & Construction

The Journal of Project Management and Construction (JPMC) is a peer-reviewed publication dedicated to advancing the field of project management and construction, grounded in the principles outlined in the PMBOK 6th Edition. Our focus encompasses the ten knowledge areas essential to successful project management: Integration, Scope, Schedule, Cost, Quality, Resource, Communications, Risk, Procurement, and Stakeholder Management.

JPMC publishes original research papers written in English that provide deeper insights into these knowledge areas and contribute to the development of best practices in project management and construction. Submissions may include theoretical analyses, computational models, experimental observations, or a combination of both theoretical …

Critical Success Factors Of Lean Construction Implementation To Improve Construction Project Efficiency In Indonesia, Onal Putra, Rossy Armyn Machfudiyanto

Journal of Project Management & Construction

Inefficiency is still a problem in the construction industry in Indonesia and in the world. Inefficiency leads to delayed deadlines, budget overruns, and inappropriate quality. It is caused by a lot of waste in the form of activities that use resources but do not produce the expected value. Lean construction is one approach to address this problem by eliminating waste and maximizing value for users or customers. This research aims to identify and determine the critical success factors that most influence the implementation of lean construction to improve the efficiency of construction projects in Indonesia as well as the development …