Digital Commons Network^™

Hs-Amm: Hierarchical Spatial Attention Mechanism Model For Facial Expression Recognition Based On Deep Learning, Ahmed Oday, Azizi Abdullah, Shahnorbanun Sahran

Baghdad Science Journal

Facial expression recognition (FER) is a significant challenge due to the complexity of multi-class categorization and the subtle differences between emotional factors, with existing deep learning models often struggling to leverage hierarchical local features for accurate distinction. To find a solution, this study proposes a two-method approach, aiming to enhance FER accuracy by refining classification through the arousal-valence dimension and improving feature extraction via an adaptive attention mechanism to resolve the difficulty of differentiating semantically close expressions. The proposed methodology combines (1) a two-level classification strategy, first, performing fine-grained classification, and second, multi-class categorization by grouping expressions into neutral, positive, …

Speeding Up Image-To-Art Transformation Using Pointillism And Dynamic Brush Techniques, Iman S. Mohammed

Baghdad Science Journal

It is a new digital process inspired by the pointillist technique of artist Georges Seurat and seeks to recreate Impressionist paintings in digital form in record time, as opposed to the long duration needed to create a painting by hand. The proposed algorithm breaks down the original image into the components of primary colors with the help of the Self-Organizing Maps algorithm. It's like how Seurat mixed his colours, which, when viewed from afar, creates a complete picture from small dots of color. The methodology has a number of technical improvements, such as a halo effect around the main components …

If You’Re Doing This Correctly, There Is A Cost: An Exploration Of The Work–Family Trade-Off Of Female Academics In Australia, Fleur Sharafizad

Research outputs 2022 to 2026

Purpose: This paper aims to explore how the gendered structures and expectations of neoliberal academic institutions inform and shape work–family trade-off considerations for women academics in Australia. It also sheds light on how these negotiations, and at times, the ensuing career or family gap, are experienced. In doing so, the paper deepens our understanding of the systematic barriers which do not only lead to gender inequalities in academia but also have broader individual and social implications. Design/methodology/approach: This exploratory study is based on qualitative semi-structured interviews, which were thematically analysed to identify how female academics navigate the expectations associated with …

T2b Gallbladder Adenocarcinoma Diagnosed By Frozen Section With High-Grade Dysplasia At The Cystic Duct Margin: Diagnostic And Prognostic Considerations, Christopher M. Ahmad, Rachana Tadakamalla, Rae-Anne Kastle, Salman Muqeet, Amer Abboud

Student Publications

Gallbladder adenocarcinoma is an uncommon gastrointestinal malignancy that is frequently discovered incidentally during cholecystectomy. Intraoperative frozen section is often used to guide surgical decision-making but has inherent limitations, particularly in assessing depth of invasion. We report the case of a 78-year-old female who underwent an elective laparoscopic cholecystectomy for a gallbladder mass. Intraoperative frozen section demonstrated a tubulovillous adenoma with at least carcinoma in situ. Subsequent permanent histologic evaluation revealed a moderately differentiated adenocarcinoma invading the hepatic-side perimuscular connective tissue, consistent with pT2b disease. Despite the advanced T stage, the tumor exhibited several relatively favorable histologic features, including negative margins …

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 …

Distributed File Carving, Brad J. Baudin

LSU Master's Theses

File carving is a fundamental technique in the digital forensics community, enabling analysts to recover deleted files from disk images without relying on filesystem metadata; however, as storage capacities continue to increase, modern file carving tools face significant scalability challenges, with carving time growing substantially alongside disk image size, particularly in the presence of file fragmentation. Fragmentation, a common behavior in modern filesystems, distributes file data across non-contiguous disk blocks to maximize space utilization, and in large disk images this distribution can span wide logical distances, increasing the search space and reducing carving efficiency, causing traditional approaches to struggle within …

Smartdesk: Automatic Ticket Classification And Resolution Prediction Using Data Analytics, Danarir Almuhairi

Theses

Public and service-oriented organizations increasingly rely on digital ticketing systems to manage large volumes of citizen and customer requests. Despite this, many ticket management processes remain partially manual, leading to delays in case routing, inefficient resource allocation, and inconsistent resolution times. These challenges can negatively impact service quality, operational efficiency, and user satisfaction, particularly in large-scale public sector environments. This study proposes SmartDesk, a data-driven framework for automatic ticket classification and resolution time prediction using data analytics and natural language processing (NLP) techniques. The research leverages publicly available helpdesk and service ticket datasets to simulate real-world service environments where incoming …

Cardiac Resynchronization Therapy: A Review, Caique M Ternes, Jitae A Kim, Anirban Basu, Kenneth A Ellenbogen, Mihail G Chelu

Faculty, Staff and Students Publications

Importance: Heart failure (HF) affects more than 64 million individuals worldwide, and acute HF is associated with 1-year mortality rates of 23.6% in North America and Europe. Cardiac dyssynchrony from conduction system disease may cause HF progression, particularly in patients with left ventricular (LV) systolic dysfunction.

Observations: Electrical dyssynchrony in HF most commonly presents as left bundle-branch block and affects 20% to 30% of patients with reduced LV ejection fraction (LVEF). Cardiac resynchronization therapy, which includes biventricular pacing and conduction system pacing, restores synchronous ventricular contraction and is recommended for patients with symptomatic HF despite optimal medical therapy, LVEF of …

Mining And Sustainable Development In Sierra Leone: The Role Of Institutional Quality, Ibrahim Massaquoi

Journal of Sustainable Mining

While mining can drive economic growth, create jobs, and promote infrastructural development, it also poses risks to the environment, human health, and social well-being. Therefore, to achieve sustainable development, responsible mining is crucial. This study empirically examines the role of institutional quality in the mining-sustainable development nexus in Sierra Leone. With the use of the planetary pressures-adjusted human development index (PHDI) as a comprehensive measure of sustainable development, the study is able to integrate economic, social, and environmental dimensions. The autoregressive distributed lag (ARDL) model confirms the existence of both short-run and long-run dynamics. The results of the study show …

Distributed Self-Control Of Dynamical Networks By Adaptive Link Weight Adjustments, Hiroki Sayama

Northeast Journal of Complex Systems (NEJCS)

Conventional control theory considers controlling the behavior of a dynamical system toward a desired state by injecting externally designed inputs into the system. Meanwhile, most complex systems exhibit self-organization through local information exchanges among individual dynamical components that are embedded within a complex network of interactions. The self-organizing dynamics of those systems are realized in a highly distributed manner using locally available information only, and therefore, their behaviors have not been discussed much from a control theoretic viewpoint. Meanwhile, adaptive networks, i.e., dynamical networks whose states and topologies coevolve at similar time scales, can offer a promising theoretical framework in …

A-Badilisha Decentralized Economic Coordination Protocol, Joe Dulo

Defensive Publications Series

ABSTRACT

A-Badilisha: A Decentralized Asset-Anchoring and Service Coordination Protocol for Informal Economies

This disclosure introduces A-Badilisha, a decentralized economic coordination protocol engineered to mobilize idle capital within informal and under-banked jurisdictions. The protocol solves the systemic "cash drought" typical of these regions by deploying an Asset-Anchoring Mechanism, which programmatically converts stagnant physical inventory and underutilized labor into liquid Community Credit (CCC).

Unlike traditional credit models dependent on fiat-based collateral or external banking reserves, A-Badilisha utilizes a self-repaying cycle where anchored physical assets—such as raw building materials, essential stock, or verified service hours—serve as the underlying collateral. The protocol maintains stability …

Biopolymer Fibre Production And Metal Free Circuitry, Natalie M. Durdle Miss

Defensive Publications Series

This paper details a decentralized, open-source manufacturing framework designed to produce structural textiles and metal-free electrical circuits using public-domain chemistry and low-cost, unregulated hardware. The platform utilizes expired late-nineteenth and early-twentieth-century patent methodologies, optimizing them for domestic, kitchen-scale replication with non-toxic, food-safe components. The primary structural substrate is derived from the acid-precipitation of casein proteins from dairy fractions, which are solubilized in a mild alkali solution to form a viscous spinning dope. To address the historical dependency on toxic cross-linkers like formaldehyde, this framework introduces three accessible micro-extrusion methodologies that utilize a non-toxic, ten percent aqueous potassium alum bath: (1) …

The Metric Field And Its Primitives, Steven Kirkland

Defensive Publications Series

The Metric Field and Its Primitives is the formal-mathematics layer of a research project whose popular-science companion, Inners Guide to the Hyper Loop, ships the story. This volume ships the mathematics: definitions, theorems, proofs, falsifier ladders, and the algebra the framework reads across substrates from atomic spectra to slime moulds to the cosmic substrate.

The framework. A candidate fundamental framing under Metric Field Ontology (MFO) commitments. The conventional readings of physics — general relativity, quantum field theory, the Standard Model, ΛCDM cosmology, M-theory's eleven-dimensional supergravity — are preserved at the mathematical level. What is shifted is the ontological framing: …

Computer Aided Field Investigation (Cafi): A Provenance-First Architecture For Real-Time Msme Credit Decisioning In India, Murali Krishnan

Defensive Publications Series

Computer Aided Field Investigation (CAFI) is a provenance-first architecture for real-time MSME credit decisioning in India, replacing the photographs-and-narrative output of conventional field visits with a hash-chained, tablet-captured, audit-defensible evidence graph. The five-layer architecture combines geo-fenced tablet field capture, DPDP-compliant consent-bound media acquisition, an append-only provenance data model in which every credit-decision fact links to immutable source artifacts, a deterministic real-time triangulation engine cross-validating borrower declarations against Goods and Services Tax (GST) returns and Account Aggregator (AA) bank statement data, a quality-assurance anomaly layer detecting photo perceptual hash collisions, GPS clustering, visit duration outliers, and field-officer response patterns, and a …

Offline‑First Transaction Buffering With Merkle‑Root Synchronization For Mobile Api Requests, Harshwardhan Tripathi

Defensive Publications Series

The present disclosure relates to a method and a system for synchronizing offline-generated Application Programming Interface (API) requests using Merkle roots between a client device and a server. The present disclosure suggests buffering one or more API requests in a persistent local storage queue responsive to unavailability of network connectivity. Thereafter, the present disclosure suggests generating, for each buffered API request, a cryptographic leaf hash based on a canonical representation of the corresponding API request. Upon generating the cryptographic leaf hash, the present disclosure suggests constructing, by the client device, a Merkle tree including the cryptographic leaf hashes as leaf …

Gaussian-Weighted K-Nearest Distribution Point Mapping For Smooth Probability Estimation, Ania Kacewicz, Jud Dagnall

Defensive Publications Series

Proposed herein is a method to map compressed data representations to smooth probability distributions by distributing each data point's weight across its k-nearest distribution bins using Gaussian decay, creating a natural exponential falloff where closer bins receive exponentially more weight than distant bins. Unlike traditional methods that either create spiky distributions (nearest-neighbor-only) or over-smooth local features (global kernel density estimation), a bounded Gaussian approach, as proposed herein, confines smoothing to local neighborhoods while maintaining smoothness within those regions. The algorithm includes circular distance support for temporal data (ensuring hour 23 is treated as 1 hour from hour 0, not 23 …

Multi-Agent Safety Architecture Using Geometric Projections And Cryptographic Egress Control, Neel Mohbe

Defensive Publications Series

Decentralized, multi-agent artificial intelligence (AI) systems can introduce structural vulnerabilities, such as emergent toxicity and alignment erosion, that existing safety paradigms may not fully address. A multi-agent safety architecture is described that can treat safety as a geometric and cryptographic property of a network's communication and consensus fabric. A method can involve mathematically defining a safety concept as a subspace within a model’s activation manifold to create an orthogonal projection operator. This operator may filter agent states to help mitigate harmful emergent content, a cryptographic egress layer with low-rank proofs can be used to verify the filter's application before messages …

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 …

Generative Model-Based Object Detection Using Concurrent Candidate Generation And Consensus, Leonid Kuligin, Thomas Zettl

Defensive Publications Series

Conventional object detection techniques can require extensive, task (specific) retraining to adapt to new domains or evolving conditions, which may be inefficient for certain applications. A system and method are described that can utilize a generative model-based workflow to perform context-aware object detection. For a given input, such as an image, and a textual prompt, a generative model may be invoked multiple times concurrently to produce a diverse set of candidate detections. A consensus mechanism can then process this set of candidates, for example, by filtering for duplicates and synthesizing the varied information to create a consolidated set of results. …

Ambient Pre-Conscious Intelligence (Api), Johny Manuel-Devadoss, Deepthi Prasad, Jayden Jack Johnson

Defensive Publications Series

Current artificial intelligence systems are, in practice, still largely reactive in nature. Even the most advanced assistants typically require explicit user prompts, clearly observable interaction events, or high-confidence inference of user intent before they engage in meaningful computational support. As a result, there is an inherent delay between the moment a cognitive need begins to emerge and the moment a system is able to respond. This delay is not merely a technical limitation; it introduces measurable friction into everyday human–computer interaction. In complex, information-dense environments, this friction accumulates, contributing to increased task-switching costs, reduced continuity of thought, and elevated cognitive …

Crime-Related Media Consumption And Fear Of Crime Victimization: The Moderating Roles Of Stress And Coping, Katelyn Elizabeth Byers

Walden Dissertations and Doctoral Studies

No abstract provided.

An Emotional Intelligence Staff Education Program For Patient-Aligned Care Team (Pact) Members, Linda Rogers

Walden Dissertations and Doctoral Studies

No abstract provided.

Perspectives Of Formerly Incarcerated African American Males On Prison Vocational Work Programs On Reducing Recidivism, Mark Steven Frazier

Walden Dissertations and Doctoral Studies

No abstract provided.

Popgenhelpr: An R Package To Streamline And Facilitate Informed Population Genomic Analyses And Visualization Of Genetic Ancestry, Diversity And Differentiation, Keaka Farleigh, Mason O. Murphy, Christopher Marie Blair, Tereza Jezkova

Publications and Research

Analysing large population genomic datasets requires an interdisciplinary skillset. Beyond a knowledge base in genetics and population biology, population genomic analyses involve computer science and statistics, representing a barrier for researchers without experience in those fields. PopGenHelpR seeks to lower this barrier by enabling researchers to perform population genomic analyses and generate near-publication quality figures in a streamlined and informed fashion. PopGenHelpR allows users to estimate genetic diversity within populations as well as differentiation among populations and individuals from single nucleotide polymorphism data. PopGenHelpR includes commonly used measures such as observed heterozygosity and FST. PopGenHelpR also provides five …

Advances In Research On Eco-Geological Environment Monitoring Of Underground Coal Mining Areas Based On Airborne Remote Sensing, Li Jun, Zou Zhaohui, Zhang Chengye, Wang Yi, Cheng Yang, Xu Lianhang, Zhang Jinhe, Liu Chuanrui, Liang Lixia

Coal Geology & Exploration

Background Timely and effective monitoring of the current status of eco-geological environment holds great significance for scientific decision-making regarding both geological environment protection and ecological restoration in underground coal mining areas. Owing to its advantage of large-scale and rapid monitoring, airborne remote sensing technology has emerged as an important approach to the eco-geological environment monitoring of mining areas. Advances This study first clarifies relevant concepts of eco-geological environment monitoring, as well as the monitoring requirements and contents specific to underground coal mining areas. Accordingly, it presents a summary of the advances in research on airborne remote sensing technology for the …

Entropy-Constrained Closure For Steady, Quasi-One-Dimensional Flow Of Ideal Gases, Andrew A. Oliva

Michigan Tech Publications

An entropy-constrained closure is developed for steady quasi-one-dimensional flow of a calorically perfect ideal gas. Net irreversibility is represented by a prescribed entropy change between the inlet and outlet or, equivalently, by a stagnation pressure ratio together with the stagnation temperature ratio implied by the energy balance equation. The thermodynamic constraint, enforced through Gibbs relation together with conservation of mass and energy, yields an algebraic mapping from the inlet flow state, area ratio and prescribed stagnation property ratios to the outlet flow state. The momentum balance is retained only as an auxiliary post-processing relation and may be used to infer …

Distinguishing Drought Experiences: From Perception To Measurement And Their Significance On Productivity Value In Uganda, Parisa Pakrooh, Fabio Gaetano Santeramo, Giuseppe Maggio

Fondazione Eni Enrico Mattei Working Papers

Weather shocks increasingly threaten agricultural productivity in Sub-Saharan Africa. While the negative effects of drought on production have been documented in numerous studies, the behavioral dimension of adaptation, particularly how households perceive drought and what shapes these perceptions, remains less explored. The study focuses on Uganda to distinguish between self-reported drought (subjective) and data-driven drought (objective) and how their divergence is associated with agricultural outcomes. The study relies on four waves of household surveys (UNPS for 2009/10, 2010/11, 2011/12, and 2013/14) with historical re-analysis data on temperature and precipitation from 1981 to 2015. Log-linear and logit models are applied to …

Reconstruction And Repatriation Of Looted Cultural Heritage Property Ownership Mechanism, Yichi Zhang

Pepperdine Policy Review

The displacement of cultural artifacts through conflict, colonization, and illicit trafficking has created profound gaps in humanity's shared heritage. This paper examines the systemic barriers to cultural property restitution and proposes a structured dispute resolution framework as the primary remedy. Drawing on the social, nonmarket, and economic values of cultural heritage, the study establishes why repatriation extends beyond legal formality into questions of identity, sovereignty, and collective memory. A review of existing international instruments, including the 1954 Hague Convention, the 1970 UNESCO Convention, and the ICPRCP, reveals persistent enforcement gaps and jurisdictional inconsistencies that impede meaningful restitution. Comparative case studies …

The Capital Gap: Mitigating Banking Barriers For Nonprofit Providers In Mental Health And Educational Systems, Jinhee Lee, Josefina Martinez

Pepperdine Policy Review

Nonprofit organizations are vital contributors to public welfare, yet they are systematically excluded from conventional banking systems, creating a liquidity crisis that undermines their capacity to deliver essential services. This paper discusses the structural issues of the banking sector that hinder nonprofits in acquiring credit and explains how this problem can be solved. Specifically, it aims at investigating liquidity constraints faced by schools providing mental health services and education programs. With the help of information asymmetry and relationship lending theories, the paper explains why traditional credit approaches cannot work, considering the distinctive features of the financial model of mission-oriented institutions. …

Epileptic Seizure Prediction From Eeg Using Continual Learning With Cnns, Adnan Amin, Ammar Bathich, Feras Al-Obeidat, Safa Naes, Maria Jose Sousa

All Works

Epilepsy is a persistent neurological disorder that affects over 50 million people worldwide, with nearly one-third of patients remaining unresponsive to conventional therapeutic treatments. This study introduces a progressively adaptive seizure prediction framework designed to enhance early detection and clinical decision-making. The proposed model employs a deep learning strategy grounded in continual learning (CL) principles, using Convolutional Neural Networks (CNNs) in combination with knowledge distillation techniques. This enables the model to assimilate new data while retaining previously learned information. The approach was evaluated on the publicly available Bonn University EEG dataset, following a sequential learning process in which each successive …