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Bridging Content, Practice, And Pedagogy In K–12 Computing Education: A Review Of Computer Science In K–12: An A To Z Handbook On Teaching Programming, Matthew Priem

Essays in Education

This book review examines Computer Science in K-12: An A to Z Handbook on Teaching Programming, a resource designed to support K-12 computer science educators. Bringing together contributions from forty authors, the book integrates content knowledge, computational practices, and pedagogical strategies for teaching programming across grade levels. The review highlights the text’s emphasis on addressing student misconceptions, connecting research to practice, and balancing teacher guidance with student autonomy. Although the alphabetical organization may not always reflect pedagogical progression, the modular structure allows for flexible use. Overall, the handbook is a valuable professional resource for both aspiring and practicing computer …

Lightweight End-To-End Cryptographic Framework With Semantic Qos For Ar-Based Telesurgery, Pavan Kumar Satram

Masters Theses

This thesis presents the design, implementation, and evaluation of a lightweight end-to-end cryptographic framework integrated with a semantic quality-of-service classification system for augmented reality based telesurgery. Telesurgery can deliver expert surgical care to underserved populations, but adoption has been limited by unresolved cybersecurity, network performance, and resilience challenges. The core tension is that strong encryption adds latency that may exceed the clinical safety threshold, while unencrypted systems remain vulnerable to attacks that could endanger patients during live procedures.

The framework addresses this tension through a dual-edge security middlebox that performs per-flow encryption using semantically selected ciphers: AES-128-GCM for latency-critical haptic …

Explaining Safety Challenges And Their Relationships Using A Qualitative-Fuzzy Dematel Approach: A Surface Mine Case Study, Neda Molamehdizadeh, Gholam Hossein Halvani, Hossein Ebrahimi, Ali Asghar Farshad, Seyedeh Melika Kharghani Moghadam, Saber Moradi Hanifi

Journal of Sustainable Mining

Safety in surface mining operations is a major organizational management challenge due to the inherently hazardous nature of mining activities. This study aimed to explain safety challenges and identify their interrelationships through a combined qualitative-fuzzy DEMATEL approach in a surface mine in Yazd Province, Iran. The research was carried out in two sequential phases: first, key safety challenges were identified through qualitative interviews with employees, supervisors, and safety experts; then, the relationships among these challenges were analyzed and prioritized using the fuzzy DEMATEL technique. The main challenges identified included insufficient specialized training, inadequate safety equipment, weak organizational safety culture, and …

The Honored Children Of Adam: A Muslim Reading Of Magnifica Humanitas In The Age Of Artificial Intelligence, Iqbal Akhtar

The Journal of Social Encounters

No abstract provided.

Magnifica Humanitas And The Obsolescence Of Just War, Noreen Herzfeld

The Journal of Social Encounters

No abstract provided.

Artificial Intelligence And The Rediscovery Of The Human: An Islamic Reflection On Magnifica Humanitas, Mazhar Ali Bari, Biliana Popova

The Journal of Social Encounters

No abstract provided.

Electronic Structure Discretization And Compression Using Diagonal Basis Sets, Casey Lee Dowdle

Dartmouth College Ph.D Dissertations

Numerically solving the electronic structure problem is a fundamentally difficult problem due to the exponential growth in the dimension of the Hilbert space as the system size increases. In order to solve problems at a chemically relevant accuracy, both the choice of basis set and numerical method are important factors that are intrinsically connected.

In this thesis, we study the discretization and resulting compression of electronic Hamiltonians using diagonal basis sets. A diagonal basis set approximately diagonalizes the matrix and tensor representations of the one- and two-body potentials. This can reduce storage, simplify matrix-vector products, and lower the complexity of …

Re: Approval Letter For The Diggings East 100% Remedial Design Package Submittal (Dated July 23, 2026), The 100% Sbcca Programmatic Technical Specifications Submittal (Technical Specifications) (Dated May 29, 2026), The Final Revised Silver Bow Creek Conservation Area (Sbcca) Construction Quality Assurance Plan (Cqap) (Dated July 29, 2026), The Final Sbcca Construction Monitoring Quality Assurance Project Plan (Qapp) (Dated July 29, 2026), And The Final Sbcca Materials Management Plan (Mmp) (Dated July 29, 2026), Emma Rott

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Clark Tailings Consolidated Waste Management Area Site Investigation Quality Assurance Project Plan (Qapp), Woodard & Curran

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Synthesis, Utilization And Biological Evaluation Of Β-Hairpin Peptides As Inhibitors Of Immune Checkpoints, Sarah Naylon

Electronic Theses and Dissertations 2020 - Present

Peptide therapeutics have emerged as promising alternatives to monoclonal antibodies because of their smaller size, improved tissue penetration, and synthetic versatility. Yet their broader application is often limited by poor structural stability, rapid clearance, and reduced target residence times. This dissertation describes the design, synthesis, structural characterization, and biological evaluation of β-hairpin peptides as inhibitors of immune checkpoints and as peptide vaccine scaffolds while developing strategies to overcome these limitations. At first a series of antibody-derived β-hairpin peptides (mimics of complementary determining region heavy-chain 3: CDR-H3s) as covalent inhibitors of the PD-1/PD-L1 immune checkpoint were investigated. Electrophilic warheads were incorporated …

The Effect Of Silica-Enriched Rice Husk Biochar And Npk Fertilizer On Soil Total Nitrogen, Nitrogen Uptake, And Yield Of Lowland Rice, Emma Trinurani Sofyan, Oviyanti Mulyani, Ania Citraresmini, Meddy Rachmadi, Kharmelia Sandra Livia

Jurnal Kultivasi

Rice production in Indonesia increasingly relies on agricultural intensification, which can accelerate soil degradation and reduce fertilizer-use efficiency. Therefore, sustainable soil management is needed to maintain soil fertility. Silica-enriched rice husk biochar (biochar-silica) is a promising soil amendment because it improves soil properties and nutrient retention. This study evaluated the effects of biochar-silica and NPK fertilization on soil total nitrogen, nitrogen uptake, and yield of lowland rice (Oryza sativa L.). The experiment was conducted from September 2025 to January 2026 using a two-factor randomized block design with nine treatment combinations and three replications. The treatment consisted of three levels of …

Development Of Robust Ratio Linear Fitting Method Of Temperature And Emissivity Separation For High-Temperature Data, Mitchell Manzardo, Michael L. Dexter, Shannon R. Young, John Bowlan, Anthony L. Franz

Faculty Publications

Accurate temperature and emissivity separation from thermal infrared radiance is essential for characterizing materials under high-temperature laboratory conditions. Existing temperature and emissivity separation methods have largely been developed for multispectral remote sensing applications, where long atmospheric path lengths require extensive atmospheric compensation. In contrast, the current work considers hyperspectral laboratory measurements acquired over a short optical path, where atmospheric effects are comparatively small but increased measurement uncertainty remains within portions of the measured spectrum. The ABB MR304 FTIR spectrometer used in this study exhibits reduced optical transmission below approximately 2.5 μm, producing increased measurement uncertainty within the spectral region containing …

Land-Use Transitions And Carbon Emissions Of Aquaculture Expansion In The Brazilian Amazon, Felipe S. Pacheco, Sebastian A. Heilpern, Rafael M. Almeida, Suresh A. Sethi, Marcela Miranda, Nicholas Ray, Laura Greenstreet, Joshua Fan, Brendan H. Rappazzo, Marcelo Gomes Da Silva

School of Earth, Environmental, & Marine Sciences Faculty Publications

Accounting for land-use change underlying food sector expansion is critical for conserving ecosystem integrity. This challenge is particularly acute in the Amazon, where the conversion of forests for food production is pronounced and has broad implications for global biodiversity and the cycling of water and carbon. Here, we analyze land-use transitions associated with aquaculture development in the Brazilian Amazon. We found that a 450-fold increase in aquaculture pond area from 1985 to 2022 occurred primarily on pasturelands (87%) but also included wetland conversion (4%) and deforestation (5%). Notably, continued growth can be sustained within already altered landscapes: In Rondônia, the …

Palmnet: Confidence-Calibrated Edge-Cloud Ai For Field Diagnosis Of Date Palm Diseases, Muntadher Kareem, Raed Majeed

Karbala International Journal of Modern Science

Date palm (Phoenix dactylifera L.) is a cornerstone crop for Iraq and the wider MENA region, yet reliable in-field diagnosis of leaf disorders remains slow, labour-intensive, and constrained by a limited pool of agronomists. This paper presents PalmNet, a full-stack diagnostic system that classifies nine leaf conditions through a calibrated edge-cloud framework. The system is developed and evaluated on a public dataset of 3,089 field images spanning the nine classes, using a 70/15/15 stratified split. A ShuffleNetV2 student network, distilled from a ConvNeXt-Tiny teacher, is deployed on two complementary edge endpoints: a Raspberry Pi Zero 2 W field station …

Proactive Deep Q-Learning Approach For Anomaly Detection In Iot Idss, Hawraa A. Habeeb, Mehdi E. Manaa

Journal of Intelligent Informatics, Networking, and Cybersecurity

Breach rates and unparalleled vulnerabilities are a constant feature of the cyber landscape these days, and the increasing complexity of the proliferation of Internet of Things (IoT) nodes is to be expected. With these challenges, the conventional intrusion detection systems (IDS) are proven to be unable to deal with the extensive and varied data streams. Such systems can be fundamentally attributed to the classical nature of these systems, which are lacking in flexibility to analyze traffic in real-time and thus have no proactive capabilities of identifying patterns of unknown attacks. Considering these technical barriers, in this paper, an offensive-defensive system …

Scattering Phase Shift In Quantum Mechanics On Quantum Computers: Non-Hermitian Systems And Imaginary-Time Simulations, Peng Guo, Paul Levan, Frank Lee, Yong Zhao

Research & Publications

To overcome the fast oscillatory behavior of correlation functions for extracting scattering phase shift in real-time quantum simulations encountered in the work of Guo et al. [Phys. Rev. D 113, 054512 (2026)], we propose and test two solutions in the present work. One is to simulate Hermitian systems in imaginary time, and the other is to simulate non-Hermitian systems in real time. We demonstrate that both approaches lead to the problem of nonunitary quantum evolution that can be solved by combining two quantum algorithms: block encoding and Hadamard test. The combined quantum algorithm does not require midcircuit …

Machine Learning Applications To Physical Processes, William Charles

Arts & Sciences Graduate Student Theses and Dissertations

This thesis demonstrates how machine learning techniques can solve computationally challenging problems across diverse areas of physics, from high-energy astrophysics to condensed matter systems, accelerating traditional computation. My first contribution addresses the computational expense of Monte Carlo calculations for radiative processes in relativistic plasmas. I develop a neural network sampling method that enables fast sampling from an arbitrary probability density, and demonstrate the method on inverse Compton scattering, achieving a speedup of up to an order of magnitude beyond standard methods. My second contribution addresses the structure and radiation of neutron star magnetospheres. I use physics-informed neural networks to model …

X-Ray Emission From V1674 Her (Nova Her 2021) And Characterization Of Cebr3 Detectors For Gamma-Ray Spectrometry, Tekeba Olbemo

Arts & Sciences Graduate Student Theses and Dissertations

Novae are thermonuclear explosions on the surface of the white dwarf in a close binary system. They are multi-wavelength transients emitting across the electromagnetic spectrum from radio to gamma-rays. This thesis primarily focuses on the X-ray emission from one particular nova, V1674 Her. V1674 Her (Nova Her 2021) is known for its ultra-fast decline time of ��2 ∼ 1 day. This under normal circumstances implies massive white dwarf potentially approaching the Chandrasekhar limit. We test this for V1674 Her by measuring its mass via X-ray spectroscopy method. The method calculates X-ray emission from physically motivated model of post-shock accretion column …

Quantifying Grain Size In Scanning Electron Microscopy Images, Katherine Hoffsetz

Discovery Day - Daytona Beach

This project explores advanced image analysis techniques to assess the microstructure of highly strained austenitic stainless steel. Utilizing Python imaging libraries such as scikit-image and OpenCV, we aim to extract precise measurements for grain size from scanning electron microscopy (SEM) images. These metrics will be examined against the computed grain sizes of the sample from electron backscatter diffraction measurements. By automating the extraction of grain size measurements from SEM images, this study contributes to steamlining the quality assurance/ quality control of industrially processed materials.

Learning Casual Structures From Aviation Accident Narratives Using Natural Language Processing And Graph-Based Knowledge Representation, Stephanie Ramsey, Katherine Hoffsetz, Madeline Gorman, Logan Lambeth

Discovery Day - Daytona Beach

Understanding the complex causal relationships underlying aviation accidents is critical for improving safety and preventing future incidents. However, much of this information exists in unstructured narrative reports, making large-scale analysis difficult. This project aims to automatically extract and model causal chains from National Transportation Safety Board (NTSB) accident narratives using a combination of traditional natural language processing (NLP) techniques, transformer-based architectures, and graph-based knowledge representation. Traditional NLP methods, including named entity recognition, dependency parsing, and rule-based pattern matching, will be used to identify structured cause–effect relationships. These approaches will be compared with transformer-based models, including a lightweight encoder for classification …

Numerical Modeling Of A Secondary Breakup In The Veritas Asteroid Family, Jarrett Dieterle

Discovery Day - Daytona Beach

The Veritas asteroid family, located in the outer main belt, is believed to have formed from the catastrophic breakup of a parent body approximately 8.3 million years ago (e.g., Nesvorný et al., 2003). Larger fragments remained in the main belt, while smaller particles evolved inward under radiation forces, forming a toroidal dust structure observable in infrared data as paired bands. Previous studies (e.g., Dermott et al., 2001) have shown that these bands can be linked to their parent families and modeled from their initial disruptions. We propose that the 10° dust bands associated with Veritas may record evidence of a …

Geometry-Conditioned Adversarial Defense For Sar Automatic Target Recognition Via Regime-Specialist Classification Heads, Skyler Fabre

Discovery Day - Daytona Beach

This project, titled Geometry-Conditioned Adversarial Defense for SAR Automatic Target Recognition via Regime-Specialist Classification Heads, addresses the critical vulnerability of deep neural networks deployed in Synthetic Aperture Radar (SAR) Automatic Target Recognition (ATR) systems to adversarial perturbations. This is where imperceptible pixel-level modifications cause confident misclassification, posing serious risks in defense and aerospace applications. The objective is to develop and evaluate RegimeResNet, a geometry-conditioned classification architecture that exploits sensor metadata unique to SAR collection systems. Rather than treating all images uniformly, RegimeResNet partitions the SAR capture space into nine geometric regimes defined by depression angle and target azimuth angle extracted …

Energy-Aware Bimodal Contact Detection For Leg Odometry, Emre Girgin

Discovery Day - Daytona Beach

Autonomous exploration of extraterrestrial environments using legged robots requires robust GNSS-free 3D state estimation. Standard leg odometry relies on Zero-Velocity Updates (ZUPT), which assume a grounded foot remains completely stationary. This assumption consistently fails on deformable granular terrain due to unobservable slippage, rapidly degrading state estimation. To mitigate this critical failure mode, we propose a dual contact-detection framework designed to robustly gate an Error-State Extended Kalman Filter (ESEKF) tracking pose, velocity, and IMU biases.   The architecture isolates physical load and kinematics by modeling contact detection as two independent parallel Hidden Markov Models (HMMs). The Load HMM processes Ground Reaction Forces, …

Learning Motion Primitive Selection And Environment Abstraction, Edison Alberto Martinez Samaniego, Natalie Alexander, Kaelyn Weddle

Discovery Day - Daytona Beach

Learning Motion Primitive Selection and Environment Abstraction Advanced Air Mobility (AAM) is emerging as a transformative solution for short and medium range transportation; however, it introduces an operational model that differs significantly from conventional aviation. AAM vehicles are expected to operate closer to populated areas, with increased autonomy, in dense urban and suburban environments. These settings present constrained maneuvering conditions which highlights the importance of maintaining safe operation under degraded flight conditions. Abnormal conditions may endanger onboard passengers, people on the ground, and surrounding infrastructure, making rapid detection and mitigation essential to prevent loss of control. Recent research has explored …

Developing An Object Level Understanding Of Sine And Cosine As Ratios And A Coherent Trigonometry, Jeffrey Peter Nair

Theses and Dissertations

Solving right-triangle problems as well as integrating right-triangle and circular trigonometry into a coherent understanding are documented challenges for students. Prior research has deeply investigated students constructing ratio meanings for sine and cosine using a circle-first approach, which then can be extended to right triangles. Also, past work has separately documented distinct meanings that are useful for sine and cosine, in addition to the ratio meaning, including as lengths in a unit circle and coordinate points. This study took these existing ideas and put them together into one possible developmental progression, based on APOS theory, where students can learn length, …

Multi-Band Extinction Modeling In Early-Type Galaxies With Circumnuclear Disks, Nonnie Bash

Theses and Dissertations

In this thesis, we present a spatially resolved, multi-band dust-attenuation method for correcting the stellar luminosity models used in dynamical supermassive black hole (BH) mass measurements. If uncorrected, dust extinction effects may dominate over other systematic uncertainties when determining the BH mass ($M_\mathrm{BH}$). We expand on a simple dust-attenuation method that treats the circumnuclear disk as a thin dust layer embedded in the galaxy midplane. Using a Multi-Gaussian Expansion, we create a three-dimensional stellar luminosity model to calculate the fractions of stellar light originating in front of and behind the disk along each line of sight. We infer the pixel-by-pixel …

Temperature And Hydrologic Context Influence Methane Variability In A Low-Salinity Marsh, Zoie Brauser

Dissertations and Theses

Coastal wetlands are biogeochemical hotspots that capture and transform carbon and nutrients. Wetland restoration is increasingly used as a climate mitigation strategy because of wetlands' capacity to sequester large amounts of carbon. However, low-salinity tidal marshes exhibit high variability in methane (CH₄) emissions, which could partially offset carbon sequestration under certain conditions. Understanding the drivers of CH₄ variability is crucial for restoration and conservation work. This project uses an observational research approach to assess the relationships between environmental factors and carbon dioxide (CO₂) and CH₄ soil gas fluxes in a restored low-salinity tidal marsh …

Numerical Methods For Nonlinear Problems Using The Finite Element Method, Logan Price

Discovery Day - Daytona Beach

Numerical Methods for Nonlinear Problems Using the Finite Element Method is a computational mathematics capstone that builds and tests finite element method (FEM) workflows for nonlinear partial differential equations in FreeFEM++, with ParaView used for visualization. Two nonlinear model problems are used to demonstrate the approach. The first is a semilinear reaction-diffusion equation with a cubic nonlinearity. A manufactured solution is used so accuracy can be checked at a fixed final time, and refinement studies in both time step and mesh size are run while nonlinear iteration counts are tracked to show solver effort. The second problem is the steady …

Low-Complexity Polynomial Ring Learning For Quantum Space Assets, Lola Torres

Discovery Day - Daytona Beach

Secure communication for space-based systems requires cryptographic methods that remain both reliable and efficient under strict computational constraints. This work investigates a low-complexity polynomial ring learning algorithm designed for quantum space assets, including satellite–ground communication systems. The project focuses on post-quantum cryptographic principles, where encryption and decryption rely heavily on repeated polynomial operations; this can be computationally expensive with constrained platforms. This is addressed with reformulating polynomial multiplication as a structured linear transformation on coefficient vectors. By representing these operations as matrices with a cyclic structure, the structure allows the use of the discrete Fourier transform (DFT); this will simplify …

Quantitative Mapping And Mitigation Of Light Pollution At Erau, Desireé Robinson, Marcus Flesher, Axon Deadrick, Conner Callahan, Jarrett Usui, Josef Kaelin, Douglas Griswold, Raiden Keefer, Harrison A. Zimmermann, Cole Gresham, Maya Curtis, Ahnika Gee

Discovery Day - Daytona Beach

Light pollution is an increasingly urgent environmental and public safety concern that affects energy costs, astronomical research, ecological systems, human health, and aviation. At Embry-Riddle Aeronautical University (ERAU), artificial lighting from campus infrastructure and adjacent airport operations contributes to elevated skyglow, limiting the performance of the university’s 1-meter telescope and degrading the nighttime environment. This project seeks to quantitatively map and analyze light pollution across the ERAU Daytona Beach campus using custom-built Sky Quality Meters (SQMs) integrated with environmental sensors and mounted on an unmanned aerial system (UAS). By collecting calibrated sky brightness measurements at multiple altitudes and geospatial coordinates, …