Digital Commons Network^™

A Near-Field Communication (Nfc) Multi-Sensor Node With Optimized Read Range And Adaptive Power Management For Remote Monitoring, Rishin Patra, Hilary Scott Nkimbeng Cho, Jin W. Choi

Michigan Tech Publications

This paper presents the design of a batteryless near-field communication (NFC) multi-sensor node with an integrated adaptive power-management system for sensing applications. The work focuses on harvesting energy from a 13.56 MHz NFC field to power an ultra-low power sensing platform. The design consists of the TI RF430FRL152H, an integrated NFC transponder with an embedded MSP430 microcontroller core and ferroelectric random-access memory (FRAM) non-volatile memory. The system combines an ISO/IEC 15693 NFC front end, a tuned loop antenna for optimized power harvesting, and multiple analog and digital sensor interfaces, and a firmware architecture for intermittent harvested energy operation. The aforementioned …

Deep Learning Approaches For Ctenophore Identification And Tracking, Anagha Bharadwaj

Theses

Ctenophores are translucent marine organisms with nearly invisible tentacles and pose significant challenges due to their transparent morphology and ambiguous structural features. This research addresses the classification and tracking of these organisms and evaluates the performance of current computer vision models under sparse-data environments.

A dataset from the NJIT Life History Lab consisting of microscopic laboratory videos and photographs of different growth stages is used to train and assess a number of convolutional neural network designs, including VGG16, ResNet, BioCLIP2, YOLO, and DeepLabCut. Additionally, a web-based interface is developed to evaluate expert-labeled ground truth with the model's performance.

The findings …

Retinomorphic Mid-Wave Infrared In-Sensor Processing Engine: Device-To-Architecture Co-Design, Hemalatha Nagaraju

Theses

Conventional frame-based CMOS image sensors acquire full-frame pixel data at discrete time intervals, resulting in substantial spatial redundancy and loss of temporal information between frames. The repeated conversion and transfer of redundant pixel data increases bandwidth and power consumption in machine vision systems. Retinomorphic sensing architectures address these limitations by enabling programmable, analog-domain processing directly at the sensor interface. A compact behavioral model of the PbSe device is developed in HSPICE based on calibrated TCAD simulation data to capture gate-controlled photocurrent modulation under varying illumination and gate bias conditions. Error analysis is performed to quantify the deviation between TCAD-generated photocurrent …

Robustness Of Ai-Driven Histopathology Under Real-World Adversarial Examples, Ruchik N. Yajnik

Theses

This robustness of histopathology classification models under adversarial and real-world perturbations resembling clinical artifacts is being investigated.

Using whole-slide images from the CAMELYON17 cohort, four representative architectures—ResNet-18, ResNet-50, HIPT-2MLP, and ViT-B/16 —are benchmarked across controlled pixel-level distortions and artifact-like transformations. Adversarial methods include iterative Fast Gradient Sign, Projected Gradient Descent, Salt-and-Pepper noise, and the Adversarial Watermark—Stain Shift (AWSS). Three defense strategies—Randomized Smoothing, Adversarial Training, and an Artifact Detector—are evaluated for their ability to preserve diagnostic accuracy and model reliability. Structured perturbations consistently degrade performance, with transformer-based models showing the greatest sensitivity. The benchmark developed here offers a reproducible framework for …

Evaluation Of Medical Instrument Reliability For The Heath And Maddox Components Of The Accommodative-Vergence System, Jacob Chabuel

Theses

Binocular vision relies on the coordination of near response triad composed in part by the vergence and accommodative systems. Binocular dysfunctions linked to these systems impact the quality of life of those affected by complicating day-to-day tasks and leading to further health concerns. Clinical evaluations that diagnose dysfunctions and tailor therapies rely on subjective methods, creating a need for a reliable, quantitative, measurement tool. This is achieved using a haploscope, a tool that quantitatively measures and observes binocular vision to identify deficiencies within the eye. Modernization of a haploscope system, measurement of the Heath and Maddox components of the visual …

Mechanics And Physical Attributes Of Nature-Based Alterations: Rock Reinforcement And Urban Heat Island Assessment, Mary Chikondi Ngoma

Dissertations

Ground improvement is critical to geotechnical and geo-engineering systems, where modification of the properties of geomaterials (rocks and soils) is required to maintain stability and prevent failure of infrastructure installed within and around them. This need has become increasingly important with rapid urbanization and population growth, which intensify demands on surface and subsurface systems and further challenge the performance of supporting geomaterials. As a result, there is growing interest in nature-based solutions, particularly biologically mediated processes such as biocementation, which can enhance the physical, hydraulic, and mechanical properties of geomaterials while offering environmentally sustainable alternatives to conventional ground improvement techniques. …

Enabling Ml/Ai In 6g And Future Wireless Communication With Privacy Preservation, Mec Offloading And Quantum Computing, Changshi Zhou

Dissertations

The forthcoming sixth-generation (6G) and future wireless networks are envisioned to support an unprecedented range of services, delivering ultra-low latency, massive connectivity, and intelligent real-time responsiveness. These capabilities will enable emerging applications such as extended reality (XR), autonomous vehicles (AVs), industrial robotics, and the Internet of Things (IoT) to reach their full potential. Achieving this vision requires the integration of enabling technologies such as artificial intelligence and machine learning (AI/ML) and quantum computing, which are poised to play central roles in shaping the landscape of wireless communication systems.

In AI-native, data-driven, and computing-centric 6G networks, ML models will be deeply …

A Generative Ai-Driven Computational Framework For Industry-Scale Discovery Of Novel Battery Materials, Joy Datta

Dissertations

The growing demand for sustainable, high-energy-density electrochemical storage has motivated the exploration of multivalent-ion batteries based on earth-abundant elements such as aluminum, calcium, magnesium, and zinc. While multivalent charge carriers offer higher theoretical energy density than lithium, their practical deployment is hindered by sluggish ion transport, strong ion-host interactions, and structural degradation of electrode materials. Identifying host materials that can reversibly accommodate multivalent ions while maintaining structural integrity remains a fundamental challenge. The dissertation develops a scalable, end-to-end computational framework that integrates density functional theory (DFT), machine learning (ML), and generative artificial intelligence (GenAI) to accelerate the discovery of next-generation …

Membrane-Engineered Nanotherapeutic Platforms For Drug Delivery: Hollow Fiber Membrane Synthesis Of Lipid Nanoparticles, Biomimetic Nanocarriers, And Nanobubbles, Zhixiang Liu

Dissertations

Lipid-based nanocarriers have emerged as a cornerstone technology for RNA therapeutics, enabling effective intracellular delivery for applications ranging from vaccination to gene regulation. However, current manufacturing approaches, particularly microfluidic-based platforms, face inherent limitations in scalability, throughput, and structural tunability due to their reliance on confined channel geometries and restricted mixing architectures. Addressing these challenges requires fundamentally new strategies that decouple nanoparticle formation from traditional microscale flow constraints while maintaining precise control over physicochemical properties.

This dissertation presents a comprehensive framework for the design, engineering, and application of advanced lipid-based nanocarriers, centered on a hollow fiber membrane (HFM)—assisted nanopore-mediated assembly platform. …

Omama-Db: The Oregon-Massachusetts Mammography Database, Avanih Kanamarlapudi

Graduate Masters Theses

Public datasets for training AI models in breast cancer screening are limited in size and quality, making it difficult to develop reliable systems. We introduce OMAMA-DB, an extensive publicly available collection of 2D mammograms and 3D tomosynthesis volumes. Starting from 967,991 images, we created a curated set of 231,080 images us ing a multi-stage filtering process that removes missing labels, uncommon dimensions, rare scanner types, duplicate studies, and invalid DICOM files. All 2D images then undergo additional outlier detection using histogram filtering and a variational autoen coder to remove low-quality outliers. OMAMA-DB includes pathology-based cancer labels and automated lesion annotations …

Ai-Augmented Financial Advisors: Comparing Ai And Human Analyst Investment Recommendations In Agreement, Performance, And Firm Size Effects, Crystal Chen

Honors College Theses

This study examines the level of agreement and performance between artificial intelligence (AI) generated investment recommendations and human analyst recommendations across U.S. publicly traded firms. Using a sample of twelve companies categorized by firm size (large, mid, and small), the study collects buy, hold, or sell recommendations from generative AI systems and human analysts. Agreement between AI-to-AI and AI-to-human recommendations is measured using Cohen’s Kappa agreement. Portfolio performance is evaluated by constructing equal-weighted portfolios for each recommendation source and size category. Risk-adjusted returns are measured using the Sharpe ratio over 1-, 2-, and 3-month periods. Furthermore, the study tests whether …

Software Engineering: Ai-Enhanced Full Stack Development, Huixin Wu, Haiying Xiao

Open Educational Resources

This course provides instruction in full‑stack web application development using modern JavaScript technologies. Students design, implement, and deploy web‑based solutions while applying AI‑assisted development tools in an ethical and effective manner. The curriculum emphasizes problem‑solving, system design, teamwork, and industry‑standard best practices, with dedicated focus on cloud‑native development—including containerization, distributed services, and modern deployment pipelines—as well as API‑first architecture, enabling students to build scalable, maintainable, and interoperable applications aligned with current industry expectations.

Debatrix, Vivienne Lu, Huy Ngo, Luke Ponssen, Jonathan Preiss, Ryan Rani

Computer Science and Engineering Senior Theses

Developing public-speaking skills remains a persistent challenge in formal education, constrained by limited instructional time and the lack of scalable, individualized feedback. Existing automated tools address only narrow aspects of this problem, offering text-based coaching against rigid rubrics that fail to capture argument quality, evidence use, or real-time rebuttal skill. This thesis presents Debatrix, an AI-powered platform that enables K-12 students, university learners, and independent self-studiers to debate an intelligent opponent. The system combines automatic speech recognition, large language model-driven rebuttal generation, and a multi-dimensional rhetorical analysis engine that evaluates argument structure, evidence integration, and persuasive technique. Users receive explainable …

Developing A Framework For Mooc Dropout: The Role Of Utilitarian And Hedonic Values In Student Retention, Bipllab Roy, Mave D'Souza, Madhura Laghane

Northeast Journal of Complex Systems (NEJCS)

Massive Open Online Courses (MOOCs) have expanded access to higher education but continue to face persistently high dropout rates, raising concerns about their long‑term effectiveness and sustainability. This study develops and empirically tests a structural framework that links utilitarian values (perceived usefulness, certificate value, time flexibility), hedonic values (enjoyment, variety and novelty, personal interest alignment), and individual characteristics (goal orientation, self‑efficacy, motivation type) to MOOC student retention. Data were collected through a structured questionnaire administered to 200 MOOC learners from Christ University, Lavasa Campus, and analyzed using Structural Equation Modelling (SEM) in AMOS. The results show that goal orientation, self‑efficacy …

Engineering: What Are We Doing?, Matthew Kuperus Heun

University Faculty Publications and Creative Works

Keynote speech at 2026 Christian Engineering Society Conference and 2026 Association for Christians in Mathematical Sciences Conference

Coupled Ferroelectricity And Phonon Chirality, Xiang-Bin Han, Cong Yang, Rui Sun, Xiaotong Zhang, Thuc Mai, Zhengze Xu, Aryan Jouneghaninaseri, Xiaoning Jiang, Rahul Rao, Yi Xia, Multople Additional Authors

Mechanical and Materials Engineering Faculty Publications and Presentations

Recognizing the coupling between ferroelectricity and chirality in optically active ferroelectrics opens a route for manipulating chirality via ferroelectricity under an external electric field, enabling control over chirality-dependent quantum states. Here, we report the experimental demonstration of the coupling between ferroelectricity and phonon chirality in the molecular ferroelectric triglycine sulfate. By electrically switching the crystal chirality, we achieve reversible and device-compatible control of phonon chirality, as revealed by in situ time-resolved magneto-optical Kerr effect measurements. The Kerr rotation reverses with electric-field switching, while phonon chirality vanishes in the paraelectric phase and is tunable in the racemic ferroelectric state. Furthermore, density …

Are Single-Pilot Operations An Advantage Or A Disadvantage?, Ezgi Berte Erme

International Journal of Aviation, Aeronautics, and Aerospace

This study aims to investigate the potential benefits and drawbacks of Single-Pilot Operations (SPO) and to provide actionable insights for commercial airlines. A qualitative research design was employed, with data collected via online interviews and analyzed thematically and descriptively using MAXQDA 24. The findings indicate that pilots perceive several advantages of SPO, including the power of automation, learning artificial intelligence, minimizing human error, cockpit systems designed for artificial intelligence, more effective decision-making/speed-up in response time, reduced labor costs, reduced pilot fatigue, and reduced need for human factor/performance. Conversely, the perceived disadvantages include diminished lack of situational awareness, lack of communication …

Du Undergraduate Showcase Abstracts: Research, Scholarship, And Creative Works, Sophia Wismar, Henry Staats, Allison Metzler, Chloe Puckett, Rachel Levine, Christa Kilpatrick, Scott Wolf, Joe Walsh, Grace Doolittle, John Engebreston, Zoe Lopez, Christopher Aaby, Audrey Duff, Timothy Sisk, Katelyn Lamberton, Angela Narayan, Gilkah Argueta, Habiba Samir, Girena Tesfazghi, Genet Kenore, Sinit Tesfamariam, Effley Brooks, Abi Newell, Megan Doherty, Natalie Baer, Lexi Blood, Talya Riciputi, Jessica Jimenez, Devin Hernandez, Lynn Clark, Taj Kumar, Sunil Kumar, Allen Rutman, Mira Pronobis, Tess Carson, Anna Sher, Frankie Stroud, Tamra Pearson D'Estree, Alyssa Wilson, Emily Melnick, Jenalee Doom, Yihang Gao, Gwendolyn Geiger, Noah Gettle, Scott Nichols, Clare Ayoub, Cara Dienno, Sunny Walker, Zoe Hansen, Maya Wheeler, Addison Rice, Patrick Martin, Sanjana Acharya, Daniel Mcintosh, Amanda Mckellips, Calli Cain, Justin Blake, Peter Sokol-Hessner, Natalie Miller, Max Weisbuch, Sophia Dellota, John Macikas, Charlotte Snow, Mark Siemens, Zoe Lynch, Alex Huffman, Prachi Shah, Jason Roney, Halcyon Levi, Nicole Herzog, Andrea Koly, Daniel Linseman, Annie London, Xi Yang, Avery Zwisler, Jane Smith, Chaz Contag, Michael Kerwin, Lucy Rand, Grace Schroeder, Michelle Rozenman, Nissa Tapper, Guiming Zhang, Mateo Mazariego-Halpern, Keith Meyer, Julie Do, Dakota Park-Ozee, Travis Herink, Kara Neu, Jonathan Plomin, Eve-Odine Duchaufour, Debbie Gale Mitchell, Tennyson Anderson-Stricklin, Lily Treitz, Samantha Rosenberger, Sierra Griffith, Finley Joseph, Daniel Sampson, Emmy Davis, Skyler Kasnoff, Evon Lopez, Vivian Nguyen, Cassy Young, Franklin Sellner, Martin Tobon, Ila Graham, Zach Billings, Holden Hedit, Decatur Boland, Paul Kosempel, Cory Chandler, Jay Mahoney, Sam Dragan, Susan Dagget, Yarrow Ator, Heidi Vuletich, Owen Weber, Andrew Kloeppel, Petersen Gray, Mandi Schaeffer-Fry, Razleen Bassra, Bryanna Rodriguez, Christina Blue, Taubie Sanders, Rachel Epstein, Luke Milburn, Camryn Evans, Ezra Martinez, Mary Westwood, Gabri Notov, Robin Tinghitella, Lilou Cabrol, Eli Barbour, Juliet Mendik, Selma Myers, Zac Wise, Noah Fahlin, Michelle Knowles, Abigail Hopper, Michael Greenberger, Romi Laclair, Sarah Watamura, Sabrina Efroymson, Casey Barker, Sydney Seltzer, Bryn Yehle, Jennifer Hoffman, Sara Garcia, Ryuka Nagamine, Trevor Briggs, Remy Le Boeuf, Elena Krone, Eileen Farrell, Regan O'Rourke, Elena Roel, Greg Mortimer, Ali Ayoub, Stefani Langehennig, Caitlin Turk, Logan Scmid, Stefan Chavez-Norgaard, Karen Kim, Tatiana Peccedi, Courtney Cassidy, John Sebesta, Rhianna Lewis, Janice Bening-Lacek, Vivian Lawless, Mckenna Hanson, Jeffrey Amidon, Riya Joshi, Ram Ambre, Brady Worrell, Perrin Schneider, Ali Azadani, Brooke Agulnek, Lyndsie Salvagio, Elise Siemanowki, Yan Qin, Andre Allen, Melodie Nguyen, Megan Livengood, Abby Reams, Saffron Hartreeve, Bri Wylie, Sarah Brookman, Mariah Loiacono, Green Russo, Abhia Lodhi, Gabrielle Welsh, Nika Spehar, Shahked Levin, Evrim Baykal, Kimberly Chiew, Jocelyn Torres, Kailey Hicks, Mykaela Tanino-Springsteen, Audrey Bellows, Akam Chahal, Madeline Tepper, Shannon Murphy, Alexa Fonseca, Deborah Han, Cassandra Perez, Oluwatoyin Alaba, Julia Roncoroni, Vy Nguyen, Nana Burn, Sarah Sasse, Rubin Tuder, Anthony Gerber, Nancy Lorenzon, Christine Vohwinkel, Camryn Gunter, Tristan Weber, Sam Rommel, Brian Michel, Muskan Fatima, Alannah Oleson, Kira Frey, Edward Garrido, Beckett Morris, Kerstin Haring, Drew Middleton, Abigail Walpert, Liam Dee, Gabby Ishaw, Cole Carnes, Maddie Weiser, Claire Fox, Valeriia Vlasenko, Kateri Mcrae, Riley Smith, Abigail Templin, Kushani Rajapaksha

DU Undergraduate Research Journal Archive

Abstracts from the DU Undergraduate Research Showcase.

A Distinctly Christian Understanding Of The Technical Details In Engineering, Paul Griffioen

Faculty Work Comprehensive List

Within engineering disciplines, much attention has been given to developing pedagogical techniques and practical applications that are distinctly Christian. However, not as much attention has been given to understanding technical engineering content from a distinctly Christian perspective. The main reason is that the technical details of engineering seem to be the same for both Christians and non-Christians. After all, does being a Christian have any impact on the content of specific technical details like integration and finite element analysis? Since the vast majority of time in engineering jobs, research, and teaching is spent on specific technical details, this is a …

An Ai-Integrated Methodology For Secure Software And System Development, Ian Matthew Campbell Coston

Electronic Theses and Dissertations 2020 - Present

Securing interconnected software systems requires more than layering existing frameworks on top of each other. Most current Secure Software and System Development Lifecycle (S-SDLC) models treat security as a phase rather than a design condition, leaving real gaps in governance, access control, and automated enforcement that become critical failure points in Internet of Things (IoT) environments where devices are resource-constrained, long-lived, and frequently insecure by default.

This dissertation introduces the Automated Zero Trust Risk Management with DevSecOps Integration (AZTRM-D) methodology, a novel approach that unifies DevSecOps automation, the National Institute of Standards and Technology (NIST) Risk Management Framework (RMF), and …

Measuring Stock Market Inefficiency Using A Multilayer Composite Efficiency Index: A Case Of The Egyptian Exchange, Patrick K. Owido, Hiroki Sayama

Northeast Journal of Complex Systems (NEJCS)

Financial markets play a critical role in resource allocation. Their performance depends on the decisions of millions of independent investors constantly reacting to one another. Their informational efficiency remains a subject of debate across economic systems. When informational efficiency is present at the weak form, historical price information should not consistently predict future returns. Several empirical tests of this hypothesis often focus on the behavior of aggregate market indices, and use individual efficiency proxies such as autocorrelation, GARCH-type volatility, or entropy-based measures to measure efficiency. This has often yielded mixed results, particularly in emerging markets. Here we show that testing …

Wake-On-Anomaly Federated Architecture For Privacy-Preserving Poultry Health Early Warning, Mahmoud Aziz Louati

Masters Theses

Highly pathogenic avian influenza outbreaks, respiratory disease, heat stress, and silent equipment failures share one operational reality: they are detected too late because today’s poultry-health workflow is reactive, manual, and dependent on producers volunteering commercially sensitive data. This thesis presents a wake-on-anomaly federated architecture that addresses both the detection-latency problem and the privacy–adoption deadlock that has so far prevented cross-farm collaboration. The architecture is organized in two tiers. Tier 1 is a lightweight LSTM autoencoder that continuously screens four routine telemetry channels (water, feed, house temperature, activity proxy) and emits a per-window reconstruction-error score. A debounced k-of-m trigger with cooldown …

Isometric Force Characterization Of Braided Pneumatic Actuators, Ben Bolen, Mohammad Elzein, Lawrence Pang, Alexander Hunt

Mechanical and Materials Engineering Faculty Publications and Presentations

Artificial muscles such as braided pneumatic actuators (BPAs) offer many advantages for robotic systems, including high durability and strength-to-weight ratios. However, their use in robotic systems is still extremely limited, in part due to their poor force, length, and pressure characterization. In this work, a test setup is created to compare force produced by Festo fluidic BPAs with leading models. Our analysis of the data has resulted in (1) the development of new equations to calculate force as functions of pressure and contraction for Festo BPAs with uninflated diameters of 10 mm and 20 mm, and (2) a novel equation …

Enhancing Social Activity Through Climate-Adaptive Design In Hot-Humid Campus Open-Spaces: A Case Study Of The University Of Basrah In Iraq, Noor A. Almansor, Farah Ahmed Thiab, Riyam Rajab Fenjan

HBRC Journal

Outdoor open spaces between university buildings support students' community interactions and academic achievements. However, in hot-humid climate zones, some of these spaces lack activity and experience social withdrawal due to thermal discomfort. This is seen on the University of Basrah campus. To address this, the study aimed to identify the most suitable climate-adaptive design pattern to improve thermal comfort and, in turn, enhance students' social presence in the University of Basrah's neglected, peripheral outdoor campus spaces. A convergent mixed-method case study was applied. First, measurable environmental and social factors were identified from related studies. Next, two open spaces in the …

A Hybrid Deep Learning Framework For Multi-Class Retinal Disease Classification, Ali M. Duhaim, Abbas M. Al-Bakry

AUIQ Technical Engineering Science

Ocular diseases such as diabetic retinopathy, glaucoma, and cataract remain major causes of vision loss worldwide, creating an increasing demand for accurate and reliable automated diagnostic systems. Although deep learning techniques have demonstrated strong performance in retinal image analysis, their clinical adoption is still limited by challenges related to predictive reliability, robustness, and interpretability. This study presents HEFR-Net (Hybrid EfficientNet-B3 and ResNet-50 Feature-Fusion Network), a hybrid deep learning framework designed for multi-class classification of retinal fundus images. The proposed architecture integrates EfficientNet-B3 and ResNet-50 through feature-level fusion, enabling the model to capture both fine-grained texture patterns and high-level structural characteristics …

Biogeochemical Mechanisms Behind Water Quality Evolution And Valuable Element Reutilization Of Abandoned Mine Drainage: A Review, Wu Pan, Huang Jiangxun, Li Qingguang, Zhang Ruixue, Li Bo

Coal Geology & Exploration

Background Abandoned mine drainage, also known as acidic mine drainage (AMD), represents a major pollution source in mining areas while also serving as an important carrier of strategic critical metals and underground space utilization. In China, water pollution stemming from coal mining is more severe in the south than in the north. This spatial pattern is jointly shaped by climatic conditions, geological settings, and mining history. Advances From the perspective of the environmental geochemical frontier, this study presents a systematic review of AMD formation and evolution mechanisms, as well as technologies for water pollution prevention and control, resource recovery, and …

Underground Tunnel Drilling Technology And Equipment For Coal Mines In China: A 50-Year Retrospective And Prospects, Tian Hongliang, Li Wangnian, Li Quanxin, Yao Ke, Liu Jianlin, Chang Jianghua

Coal Geology & Exploration

Bcakground Underground tunnel drilling in coal mines represents an indispensable key means for the safe and efficient coal mining, precise disaster prevention and control, and geological transparency of coal mines. This study presents a systematic review of the development history of underground tunnel drilling technology and equipment for coal mines in China over the past 50 years, during which the technology and equipment have evolved from technology introduction to independent innovation and from following to keeping pace with and even to overtaking international counterparts.Advances Initially, this study expatiates on both the important position of coal resources in the national …

Key Techniques And Application Of The Zdy15000ldk High-Power Automatic Directional Drilling Rig, Li Quanxin, Zhang Gang, Fang Peng, Xing Wang, Yao Ke, Zhang Rui, Zhang Boyang, Zhao Xuefeng, Shi Yang, Sun Hanyu, Jia Qian

Coal Geology & Exploration

Objective For deep mining of coal mines, conventional directional drilling rigs face challenges including high labor intensity, limited control accuracy, a low intelligence level, and failure to meet the demand for efficient gas drainage. Meanwhile, high-power automatic drilling rigs encounter technical bottlenecks in automation, control accuracy, and process intelligence in this context. To address these issues, this study proposed an integrated and systematic solution—the ZDY15000LDK high-power automatic directional drilling rig. Methods Using a compact structural layout, a drill rod handling system was developed, consisting of a drill rod loading/unloading manipulator with four degrees of freedom and an automatic drill rod …

Construction Project Administration: Course Portfolio, Andre Messner

UNL Faculty Course Portfolios

This portfolio presents a structured framework for the design and implementation of a construction project administration course within a Construction Management program. Emphasis is placed on aligning student learning objectives, instructional strategies, and assessment methods with current industry expectations and professional standards. The course is intentionally designed to bridge the gap between theoretical knowledge and practical application by incorporating real-world scenarios, collaborative learning environments, and experiential activities that mirror industry practices.

In addition to outlining the course structure, this paper examines the pedagogical foundations that support student-centered learning, including constructivism, scaffolding, and project-based learning. These approaches are used to foster …

Electrical Grid Architectures For Smart Cities From Digitalized Power Systems To Ai-Enabled Urban Energy Ecosystems, Ehab Bayoumi

Mechanical Engineering

Smart cities increasingly depend on electrical grid infrastructures capable of operating under high levels of digitalization, decentralization, and intelligence while maintaining reliability, security, and governance at the city scale. However, conventional power systems, historically designed for centralized generation and passive operation, are poorly aligned with the operational complexity, multi-actor coordination, and cross-sector integration characteristic of urban energy systems. This review develops an architecture-first perspective on smart-city electrical grids, tracing their evolution from digitalized power networks to decentralized and AI-enabled urban energy ecosystems. Rather than focusing on individual technologies, the study evaluates grid architectures using a multi-layer framework that integrates physical …