Digital Commons Network^™

Assessment Of Dihedral Angle Contribution To Roll-Stability Derivatives Using Datcom And Vlm Methods, Tarik Hassan Elsonni, Emad Qasem Hussein, Balsam H. Abed

Al-Farahidi Expert Systems Journal

This study investigates the lateral stability of a fixed-wing aircraft through the roll-moment stability derivative (C_lβ ), treated as the primary indicator of dihedral effect and overall roll stability. A coupled DATCOM-based analytical formulation and lifting-line/VLM modeling framework has been used to quantify the influence of the key geometric and aerodynamic parameters on the roll-stability derivative. Specifically, the influences of dihedral angle, angle of attack, and sideslip have been explored separately, followed by geometric factors such as aspect ratio, taper ratio, and sweep angle in a systematic way. It is observed that there is an increase in the dihedral angle …

At-Gpsr: Adaptive Trajectory To Support Geographic Routing Protocol In Uav Assisted Vanet, Bassam Hasan

Al-Farahidi Expert Systems Journal

Connectivity and data delivery latency in vehicular networks are strongly affected by the high dynamism of vehicular traffic, which depend on many random factors. Under the inevitable constraints imposed by road paths and free-flowing vehicular traffic conditions (e.g., low to medium vehicle density, high mobility, high speeds), these networks suffer from fast topology variations that lead to frequent disconnections. Consequently, communications experience increased data delivery latency. Establishing a connection between source and destination vehicles depends heavily on vehicle density along the road. UAV assistance becomes more necessary as vehicle density along the road decreases. Moreover, when a road segment is …

Dynamic Analysis Of The Rotary System With Elastically Coupled Drive And Working Rotors, Hassan Jamil Kouzy

Al-Farahidi Expert Systems Journal

The problems of designing high-speed textile rotary systems are related to the search for new design schemes and the development of effective methods. This paper examines the issues of reducing loads in the supports of a rotary system, the design contains a drive rotor and a technological working rotor connected to it by means of an elastic spherical hinge, which, depending on the purpose, can be made in the form of a spindle or spinning chamber. A new design scheme was proposed for a rotary system with elastically coupled drive and working rotors, and a dynamic analysis methodology for the …

Solving Some Heat Problems In The Sense Of The Non-Conformable Fractional Derivative By Using Modified Fourier Transform, Sami Injrou, Wadii Ali

Al-Farahidi Expert Systems Journal

In this paper, we present two new concepts in Fourier analysis: the Fourier series and the Fourier transform in the sense of non-conformable fractional calculus. Some of their main properties are proven. Using this new Fourier series, new approximations of some functions are given, a frequency spectrum of a signal is plotted, and several cases of the heat equations involving the time non-conformable fractional derivative are solved and graphically presented. Furthermore, the introduced new Fourier transform is used to solve a homogeneous space-time non-conformable fractional heat equation.

Computational Analysis Of A Single Air Bubble Rising In Quiescent Water Under Temperature Variations, Mokdad Hayawi Rahman, Muna Khalil Shehan, Emad Qasem Hussein, Farhan Lafta Rashid

Al-Farahidi Expert Systems Journal

Two-phase fluid flow is widely encountered in petroleum, chemical, nuclear, and energy applications. Computational fluid dynamics (CFD) by ANSYS Fluent 17.2 has been employed in this work to simulate the rise of a single air bubble through stagnant water at different temperatures (0 °C, 25 °C, and 50 °C). In addition, a user-defined function(UDF)was developed and implemented to incorporate phase-change behavior and temperature-dependent properties. This study investigates how the buoyancy-driven bubble dynamics will be responsive to changes in liquid viscosity, surface tension, and density. The results demonstrated that increasing the temperature of water enhances the bubble rise velocity significantly; the …

Method And Device For Assessing The Quality Of Geometrical Features On A Component, Christian A. Mohr, Vmt Vision Machine Technic Bildverarbeitungssysteme Gmbh, Frank Höfts, Marc-André Otto, Carsten Dierig

Defensive Publications Series

A method for assessing the quality of geometrical features on a component comprising at least the steps: a step a) of generating a 3D point cloud of the component comprising geometrical features of the component;  a step b) of determining a trace line along a preferred direction of the geometrical features; a step c) of generating a plurality of virtual two-dimensional section lines along the trace line; a step d) of assessing at least one quality feature based on the plurality of virtual two-dimensional section lines from step c).

Reputation-Based Admission Control For Cryptographic Inventory Leases, N/A

Defensive Publications Series

In online shopping, autonomous agents can find items much faster than a person can confirm a purchase. However, simply letting these bots hold items can lead to "denial-of-inventory" attacks where bad actors lock up all the stock. This system uses a reputation score to manage these temporary holds. An agent's eligibility to reserve an item, such as through a cryptographic lease, depends on its history. The score is updated based on whether the agent actually completes its purchases or just lets reservations expire. By linking access to proven reliability, this approach helps stop malicious bots while still allowing helpful shopping …

Mitigate Structural Blindness In Code Translation Using A Graph-Based Representation, Suddhasatwa Bhaumik, Nilesh Jaiswal, Saurabh Garg, Aniket Agrawal, Divya Malhotra, Arjit Shukla, Suchit Puri

Defensive Publications Series

Conventional vector-based retrieval augmented generation systems exhibit structural blindness when used for code migration, severing critical architectural relationships like class inheritance and leading to the generation of non-functional code with high API hallucination rates. A described approach models a codebase as an interconnected property graph where source code is parsed into abstract syntax trees (ASTs) and mapped to a graph of code entities (nodes) and their dependencies (edges). A topological sort of this graph creates a dependency-aware translation queue, ensuring parent classes are processed before child classes. This method, which can be combined with a semantic vector search fallback for …

Unified Cognitive Architecture For Distributed Manifold Reasoning Systems, Donevin Frownfelter

Defensive Publications Series

Donevin Frownfelter ([email protected])

This disclosure describes a unified cognitive architecture that integrates three complementary systems—VESPER, NEPHILIM, and the Unified Agent Reasoning Model (UARM)—into a single operational framework for distributed reasoning, semantic computation, and multi‑device intelligence. The architecture introduces a manifold‑based cognitive substrate, enabling agents to perform reasoning as transformations across a non‑Euclidean semantic space rather than through traditional symbolic or statistical pipelines.

The system employs a tensor‑manifold representation for knowledge, a Majorana‑parity logic layer for reversible inference, and a distributed execution mesh that allows heterogeneous devices to participate in a shared cognitive topology. VESPER provides the laminar reasoning core, NEPHILIM …

Author Biographies, Obsculta Editors

Obsculta

No abstract provided.

A Holistic Framework For Enhancing Machine Learning Reliability: From Model Architecture And Algorithm Design To Human Interpretability, Kyle Naddeo

Theses and Dissertations

Modern machine learning systems can perform well on benchmarks yet fail in ways that are difficult for users to anticipate, interpret, or manage. This dissertation treats reliability as more than accuracy: a reliable system performs when it can, signals when it should not be trusted, and supports abstention, fallback, escalation, or human review. Unlike robustness, which emphasizes performance under shift, corruption, adversarial perturbation, or drift, reliability also requires recognizing limited competence, preserving useful semantic structure when fine-grained certainty is unjustified, and exposing mechanisms that make failures understandable. The dissertation develops this view through four contributions. Uncertainty-aware decision heads provide portable …

Non-Euclidean Geometries And Fairness Constraints In Advanced Clustering, Arnab Seal

Master’s Dissertations

A fundamental challenge in modern unsupervised learning is adapting classical clustering algorithms to handle complex, real-world data constraints. Traditional models often assume data resides in a flat, Euclidean space and optimize strictly for cluster cohesion, thereby failing to capture intrinsic hierarchical structures and ignoring sociotechnical demographic biases. This thesis addresses these critical limitations by extending generalized mean-shift dynamics into two novel clustering frameworks. First, to natively accommodate data with tree-like structures (e.g., taxonomies and social networks), we propose Hyperbolic Gaussian Blurring Mean Shift (HypeGBMS). By projecting data into the Poincar´e ball model and utilizing M¨obius vector space operations, HypeGBMS successfully …

Leveraging Spatial Statistics For Domain Adaptation Of Vision Language Models In Medical Vqa, Himanshu Raj

Master’s Dissertations

Recent advances in Vision–Language Models (VLMs) have demonstrated strong performance in Medical Visual Question Answering (Medical VQA) task. Although they perform very well within their domains, these models often experience issues with their generalization ability on unknown clinical distribution data because of different imaging technologies and patient groups used in various medical facilities. Generalization problems faced by these models make their practical application in the field of VLM-based medical VQA systems rather difficult. To overcome this limitation we proposed our method named Spatial Semantics Aware Domain Adaptation (SSADA), which is an integrated framework that combines both finetuning and prompt-based in-context …

Efficient Performance Recovery Of Pruned Llms For End Devices, Paul Vardhan Bethapudi

Master’s Dissertations

Large Language Models have shown strong performance across reasoning, language understanding, and generation tasks, but their computational and memory requirements make deployment on low resource devices difficult. This dissertation studies efficient performance recovery of pruned LLMs, focusing on whether a pruned model can regain useful task performance through parameter-efficient fine-tuning while preserving the benefits of compression. The work uses Llama-3.2-3B-Instruct as the dense reference model and applies activationaware Wanda pruning at multiple sparsity levels(20%, 30% and 50%). The pruned models are evaluated on language modeling and reasoning tasks using WikiText-2 perplexity and GSM8K (Grade School Math 8000 problems) accuracy. Adaptation …

Exploring Gene Regulatory Neural Network Biocomputing Of Bacteria, Adrian Merle Ratwatte

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

Artificial Intelligence (AI) has evolved from brain-inspired algorithms into a discipline that increasingly integrates with biological systems. While silicon-based platforms have advanced machine learning, they remain limited in energy efficiency and operation in environments beyond silicon. This motivates biological computing as an alternative, enabling efficient, resource-aware, and reconfigurable computing within living systems. This dissertation addresses these limitations by introducing a bacterial computing framework that models Gene Regulatory Networks (GRNs) as Gene Regulatory Neural Networks (GRNNs). The GRNN mirrors the structure and function of Artificial Neural Networks (ANNs) through gene-gene interactions across trans-omic layers, enabling natural, self-regulating information processing within living …

Passed Through Or Pushed Back? Exchange Rate Effects On Manufacturing Trade Prices In Indonesia And The Asean Plus Three, Fatikha Rizky Kurnia, Miguel Angel Esquivias, Wee-Yeap Lau, Unggul Heriqbaldi

Bulletin of Monetary Economics and Banking

This study analyzes the Exchange Rate Pass-Through (ERPT) on export and import prices in Indonesia’s manufacturing trade with ASEAN Plus-three countries (China, Japan, and South Korea) using monthly data from 2016 to 2022. Employing the Nonlinear (NARDL) models, we examine the degree and asymmetry of ERPT across five key manufacturing sectors for each partner. The NARDL model confirms asymmetric price responses to currency appreciation and depreciation in several sectors. The findings reveal significant sectoral and country-specific variations. Some export sectors experience complete pass-through in the short term but shift to negative complete passthrough in the long run. Meanwhile, imports from …

Predictive Importance Sampling Based Coverage Verification For Multi Uav Trajectory Planning, Snehashish Ghosh

Master’s Dissertations

In next-generation wireless networks, unmanned aerial vehicle (UAV) networks are emerging as a promising solution for ultra-reliable low-latency communication (URLLC). A key challenge in millimeter-wave UAV networks is ensuring that mobile users are always in line-of-sight (LoS) coverage, since the current snapshot-based trajectory planning approach does not consider the mobility of the users during the decision interval, resulting in disastrous LoS gaps. For continuous coverage verification, standard uniform sampling is too computationally expensive, as it would need a large number of samples to estimate rare failure events that have latencies that are not suitable for real-time requirements. In this work, …

Algorithmic Tax Ownership Young Ran (Christine) Kim &, Young Ran (Christine) Kim, Dmitry Erokhin

BYU Law Review

Tax ownership is a crucial concept for determining tax liabilities, compliance, and enforcement. However, neither the courts nor the IRS has provided clear guidance on how to analyze it. Since the Supreme Court first outlined a twenty-six-factor test for determining tax ownership in Frank Lyon Co. v. United States in 1978, this multifactor test has remained largely unchanged, and there has been no further guidance from the courts or the IRS to this day. Even tests with shorter lists of factors only add to the confusion regarding compliance and enforcement, as there is no clarity on which factors are most …

A Novel Cryptographic Technique Using Amino Acid Compositions Enhanced By Artificial Intelligence Models, Omar Fitian Rashid, Mohammed Ahmed Subhi, Humam Al-Shahwani, Mohammed Khaleel Hussein

Mesopotamian Journal of Computer Science

Encryption plays a vital role in securing sensitive digital data, and traditional cryptographic systems are usually not immune to high-level attackers. The current approaches often base on the use of traditional mathematical models that become more vulnerable to contemporary cyberattacks. The purpose of the current paper is to suggest a new cryptography method that would combine the properties of amino-acid based encoding with artificial intelligence to improve data security. The technique builds amino acid and binary encoding tables, and performs structured mappings along with using a secure key that is produced by permuting a cryptographically secure pseudorandom number generator. Randomized …

The Mascarene Archipelago, A Data-Poor Region For Mobulid Rays: First Records, Seasonal Patterns And Conservation Implications, Joanna Harris, Estelle Crochelet, Prashant Mohesh, Guy M.W. Stevens

School of Biological and Marine Sciences

The distribution and seasonal occurrence of manta and devil rays (mobulids) remain poorly understood across much of the Western Indian Ocean, particularly within remote island systems. Here, we present the first synthesis of species-level mobulid records for the Mascarene Archipelago (La Réunion, Mauritius and Rodrigues) using a combination of direct and passive citizen-science observations collected between 2014 and 2026. A total of 107 sightings were documented from 75 sighting events, comprising Mobula birostris (n = 29), M. thurstoni (n = 40), M. alfredi (n = 5), M. tarapacana (n = 2) and unidentified Mobula spp. (n = 31). One M. …

Transport And Interfacial Dynamics Of Electrochemical Formation Processes In Li-Based Batteries, Penghao Zhang

McKelvey School of Engineering Graduate Student Theses & Dissertations

Next-generation high-capacity batteries often rely on electrochemical formation processes rather than conventional intercalation alone. Such processes include lithium metal deposition and Li–O2 discharge-product formation, in which new phases form at the electrochemical interface during operation. As a result, the measured response reflects both electrochemical driving forces and the evolving product morphology. This coupling makes it difficult to interpret electrochemical data, microscopic observations, or model results in isolation. This dissertation examines this problem through three main studies and one preliminary extension on Li–O2 batteries and lithium metal deposition, each addressing a different factor that affects how electrochemical product formation is measured, …

Photoluminescent Studies Of Metal-Organic Frameworks For Small Molecule Sensing, Julia T. Dematteo

USF Tampa Graduate Theses and Dissertations

Metal–organic frameworks (MOFs) are highly tunable nanoporous materials with broad applications in gas separation, drug delivery, light harvesting, and chemical sensing. The incorporation of photoactive components into MOFs enables the development of optical sensors capable of detecting a wide range of analytes. Porphyrins and metalloporphyrins are particularly attractive for such applications due to their high molar absorptivity, strong emission quantum yields, and versatile interactions with chemical species.

In this work, two porphyrinic MOFs, PCN-222 and MOF1(Cd), are investigated. Both frameworks utilize tetrakis(4-carboxyphenyl)porphyrin (TCPP) as the organic linker, imparting optical functionality to the materials. Integration of TCPP into the framework induces …

Risk-Aware Deep Reinforcement Learning In Portfolio Optimization, Shimin Zhang

USF Tampa Graduate Theses and Dissertations

Portfolio optimization is important in investment, with the purpose of maximizing profit whilemanaging risk. The traditional portfolio optimization method, Modern Portfolio Theory, is based on the assumption that returns are normally distributed, which is always violated in practical financial market settings. In addition, traditional approaches to portfolio optimization are mostly designed as static optimizations and fail to account for the nonlinearity and non-stationarity of contemporary financial markets. Recent developments in deep reinforcement learning have attracted considerable attention for treating portfolio optimization as a sequential decision-making process. Traditional portfolio optimization methods usually evaluate risk based on the variance of the returns. …

Re: Conditional Approval Letter For Butte Priority Soils Operable Unit Draft Final Leak Detection Monitoring Plan (Dated May 13, 2026), Emma Rott

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Improved Method Of Evaluating Gas-Phase Air Cleaners Considering Adsorption And Desorption Mechanisms To And From Internal Test Chamber Surfaces, Casey Douglas Coffland

Dissertations and Theses

Portable air cleaners are playing an increasingly important role in managing indoor air quality in response to pressing issues like wildfire smoke events. Smoke is a complex mixture of gases and particulate matter; while established test methods exist for particulate matter, the dynamic behavior of gaseous pollutants is not well accounted for in current test methods. This is because prevailing air cleaner testing methods typically treat background losses as irreversible, whereas gases can engage in partitioning to and from test chamber surfaces. Ignoring these sorption interactions causes inaccurate estimation of an air cleaner's impact.

A new approach has been developed …

Preparing Preservice Teachers: Developing Skills For Working With Students With Disabilities In The Social Studies Classroom, Melissa Waugh

USF Tampa Graduate Theses and Dissertations

This study was aimed towards investigating the extant research, best practices, and teacher preparation standards related to working with students with disabilities in the social studies classroom. The study was guided using three research questions: Are students with disabilities’ learning needs reflected in the National Council for Social Studies National Standards for the Preparation of Social Studies Teachers?; How do preservice social studies teacher programs prepare their candidates for teaching students with disabilities as evidenced by Social Science Education methods course syllabi?; and, What might a college-level course aimed towards social studies teaching methods centering around students with disabilities’ learning …

Movement Ecology And Population Dynamics Of Box-Nesting Black-Bellied Whistling-Ducks (Dendrocygna Autumnalis) In Louisiana, Katie E. Miranda

LSU Master's Theses

Understanding demographic and behavioral processes underlying population dynamics is essential for effective wildlife management, especially for species subject to harvest pressure or experiencing population shifts. Black-bellied Whistling-Ducks (Dendrocygna autumnalis) are currently undergoing a notable northward range expansion and are increasing in abundance across the southeastern United States, raising management concerns for both ecological and economic reasons. As a result, there is growing public support for a special Black-bellied Whistling-Duck-specific harvest season, yet little research has been conducted on this species, particularly within newly-established populations. To address this gap, I conducted this study with the goal of evaluating seasonal …

Ooottafagvah = ???, Matthew Storm Dds

Virginia Dental Journal

No abstract provided.

An Analysis Of Teacher Quality And Primary School Students’ Learning Achievements In Cambodia, Sreymech Hoeun

International Journal of Emerging and Disruptive Innovation in Education : VISIONARIUM

The relationship between teacher quality and student learning achievement remains complex and somewhat inconsistent across the literature. For example, Roorda et al. found that the association between teacher–student relationship quality and student achievement was positive in most studies, but negative in others. Similarly, Yang and Kaiser reported that teaching quality showed significantly positive, non-significant, and even significantly negative relationships with student learning outcomes. In the Cambodian context, Chhin and Tabata examined the relationship between teacher quality and student achievement and found that teacher economic status, job satisfaction, and teaching experience significantly influenced student learning outcomes; however, these variables explained only …

Metacognition As Disciplinary Infrastructure In Ai-Mediated Learning, Tina R. Austin, Jason Gulya, Nick Potkalitsky

International Journal of Emerging and Disruptive Innovation in Education : VISIONARIUM

Metacognition is often presented as a response to generative AI’s disruption of teaching and learning, yet the term has become too generalized to guide practice. In AI-mediated environments, asking students merely to “reflect on your thinking” is insufficient. Because AI tools can redistribute cognitive labor, their educational value depends on how students use them and whether that use supports disciplinary forms of reasoning. This essay argues that metacognition must be understood as disciplinary infrastructure: students cannot effectively monitor their thinking without understanding the epistemological and ontological demands of the field in which they are working. Classrooms therefore become sites where …