Digital Commons Network^™

Effective Digital Presence Strategies For Certified Public Accountant Organization Leaders To Attract And Retain Clients, Ian Claude Pounall

Walden Dissertations and Doctoral Studies

Nonprofit professional associations often face challenges in sustaining organizational excellence and member engagement within resource-limited environments. Certified public accountant (CPA) organizational leaders are concerned with identifying effective strategies to enhance performance and ensure long-term organizational service relevance. Grounded in the Baldrige Excellence Framework and resource-based view theory, the purpose of this qualitative single case study research project was to identify and explore strategies that online CPA organizational leaders can use to develop a comprehensive digital presence framework to attract and retain organizational clients. The participant was a single Canadian CPA organizational leader. Data were collected through semistructured interviews and analysis …

Alignment Of Projects With Business Strategy, Lyndon Leathan Martin

Walden Dissertations and Doctoral Studies

Some organizations lack strategies to ensure that project outcomes are aligned with organizational objectives. Business leaders are concerned when project outcomes are misaligned with organizational objectives, as this can lead to decreased profitability and a loss of competitive advantage. Grounded in Porter’s Five Forces model, the purpose of this qualitative, pragmatic inquiry was to explore the strategies business leaders use to ensure project outcomes are profitable and aligned with organizational objectives. The participants were six executive leaders of real estate and development companies in the Caribbean, purposefully selected because their organizations had successfully fulfilled organizational objectives through project outcomes. Data …

Determining A Likely Mechanism Of Missingness In Repeated Measures Sleep Data From Wearable Fitness Trackers: Longitudinal Analysis, Kate Mobley, Kevin B. Gittner, Karen Nielsen, Lauren Matheny, Gita Taasoobshirazi, Charles Natuhamya, Monica H. Swahn

Faculty Articles

Background: Wearable fitness trackers have become a valuable tool in public health research due to their ability to collect large-scale, individual-level data at a low cost. Because of this, wearables have the potential to mitigate the urgent need for health research in low-resource settings. However, their use has been largely limited to high-income settings, and a major challenge remains: high rates of missing data. This problem may be exacerbated in low-resource environments where logistical and operational barriers further complicate data collection. Wearable sleep data collected in an urban informal settlement in Uganda during The Onward Project on Well-being and Adversity …

The Lawyer, The Law, The Case: Teaching Legal Readers To Co-Create The Law, Sara Cates

St. Mary's Law Journal

No abstract provided.

Who Wins The Fight To Protect The Right Of Publicity Through § 512(C) Of The Dmca?, Dillon Ruzich

Southern Illinois University Law Journal

Misrepresenting a copyright infringement claim when sending a takedown request under 17 U.S.C. § 512(c) is currently the most effective way to protect against the unauthorized use of names, images, and likenesses, or the right of publicity, on the Internet. With the absence of meaningful federal protection, who wins the fight to protect the right of publicity online? This Note examines tolerating the misapplication of § 512(c) for the right of publicity, considers a congressional amendment to the Digital Millenium Copyright Act (DMCA), and then evaluates incorporation of the right of publicity into the proposed NO FAKES Act before recommending …

Development And Service Performance Of Active Anti-Icing Pavement Materials For Energy Efficiency Optimization Of Low-Enthalpy Geothermal Deicing Systems, Junming Mo, Jiading Jiang, Ke Wu, Lei Qu, Wenbin Wei, Jinfu Zhu

Faculty Research, Scholarly, and Creative Activity

To address high thermal loads and energy costs in Geothermal Road Snow-Melting Systems (GRSSs) within cold regions, this study optimizes energy efficiency through material-level intervention. We developed a composite anti-icing modifier synergistic with low enthalpy geothermal systems, comprising slow-release agents, anti-corrosive components, reinforcing materials, and active chloride salts. By regulating the thermodynamic boundary of the pavement, the freezing point is suppressed to −21 °C. This eliminates the requirement for positive pavement temperatures, significantly reducing the design thermal power. Chloride ion release patterns were analyzed via dissolution and 20-day soaking tests to evaluate structural durability. Results show optimal performance at a …

Green Value Chain Analysis And Its Role In Improving Resource Allocation Decisions: A Case Study In Diwaniya Dairy Factory, Ail Abdul-Hussein Hani Al-Zameli, Nabaa Duaa Fakher

Muthanna Journal of Administrative and Economics Sciences

The purpose of this study is to justify the role of The green value chain as a modern technique of management accounting in facilitating investment decisions and optimizing the effectiveness in resources utilization at industrial units. The premise underlying the study is that green value serves as a frame of reference for analysing activities, which in turn allows to separate value-adding from non-value adding ones, leading to cost reduction and environmental soundness. Management is also not about finding faults for waste and allocating funds, it's all about tapping new ways of creating value by eliminating non-value adding activities. The deductive …

The Effectiveness Of Psychoeducation And Mind Mapping In Preventing Early Marriages In Central Java, Indonesia, Eviyati Aini Muriana, Mardiyono Mardiyono, Lanny Sunarjo, Melyana Nurul Widyawati

Jurnal Keperawatan Indonesia

During the COVID-19 pandemic, the number of early marriages increased. Early marriage causes biological and psychological problems in the mother and her baby. The combination of psychoeducation and mind mapping emerged as a preventive effort against early marriage. The aim of this study was to analyze the effectiveness of this combination in preventing early marriage in Central Java, Indonesia by influencing adolescents’ knowledge and intentions. This study was conducted using a convergent mixed-methods design. For the quantitative phase, the pre-test – post-test control group experimental design was used, while in the qualitative phase, a thematic analysis was performed using focus …

Implementation Of Direct Corpus Applications To L2 Collaborative Writing Pedagogy: The Impact On Learner Interaction, Written Output And Development, Ahmet Egemen Curuk

Electronic Theses and Dissertations Archive

This dissertation examines the implementation of direct corpus applications within L2 collaborative writing pedagogy and investigates their impact on learner interaction, as well as measurable gains in syntactic complexity, lexical complexity, and accuracy during collaborative writing and in subsequent individual writing. Although prior research has established the pedagogical value of corpus-based instruction and collaborative writing separately, little is known about how these approaches function when integrated, particularly with an emphasis on the learner experience and the interactional mechanisms that mediate learning. To address this gap, this dissertation adopts a mixed-methods design to explore how corpus-guided collaborative writing shapes dyadic interaction, …

Spacecube: Interactive Real-Time Uas Hyperspectral Processing, Thomas Pascarella Watson

Electronic Theses and Dissertations Archive

Hyperspectral cameras capture hundreds of data points per sample (pixel), thereby providing numerous advantages in remote sensing tasks. Many tasks can be effectively conducted with such a camera mounted on a small uncrewed aerial system (sUAS). However, obtaining results traditionally requires significant post-processing of captured data after flight, delaying insight. To mitigate the delay, this work proposes Spacecube, a program that implements a complete interactive hyperspectral processing pipeline. Spacecube's novel inverse georectification algorithm processes entire datasets in seconds, compared to hours for traditional methods, and eliminates pixel coverage artifacts. This allows immediate high-quality viewing and adjustment of captured flight data. …

Deep Learning-Based Structural Displacement Identification And Quantification Under Target Feature Loss, Lishuai Zhu, Guangcai Zhang, Qun Xie, Zhen Peng, Li Ai, Ruijun Liang, Taochun Taochun Yang

Civil Engineering Faculty Publications

Structural displacement monitoring faces significant challenges under complex environmental conditions due to the loss or degradation of target features, making it difficult for traditional methods to ensure high accuracy and robustness. Therefore, this study proposes a structural displacement identification and quantification method that integrates YOLOv8n with an improved edge-orientation gradient-based template matching algorithm. By combining deep learning techniques with traditional template matching methods, the accuracy and robustness of monitoring are enhanced under adverse conditions such as noise and extremely low illumination. Specifically, in the edge-orientation gradient matching stage, the Canny-Devernay sub-pixel edge detection technique and an improved ellipse-fitting method are …

Voltage Breakdown Strength And Energy Density Of Ceramic Srtio₃ At Cryogenic Temperatures From 295 K To 77 K, Hung Trinh, Alan Devoe, Fatih Dogan

Materials Science and Engineering Faculty Research & Creative Works

The low-temperature dependence of the DC dielectric breakdown strength (EBD) and the energy storage density (W) of capacitors, fabricated from high purity polycrystalline strontium titanate, were investigated in the temperature range from 295 K to 77 K. Test samples were constructed with a process similar to that used for multilayer ceramic capacitors (MLCCs). The permittivity, loss tangent, leakage current, and breakdown strength were measured as a function of temperature and voltage. Weibull statistical analysis was used to quantify breakdown distributions. Despite electric-field suppression of permittivity, breakdown strength increased significantly with decreasing temperatures, leading to enhanced energy density. The breakdown field …

The George-Anne Daily, Georgia Southern University

George-Anne Media Group: Newsletters & Magazines

No abstract provided.

Efficiency Comparison Of Reduced Graphene Oxide (Rgo) Composite-Incorporated Polyacrylonitrile Nanofibrous Filters For Respirable Crystalline Silica Dust And Coal Dust, Mahsa Moradi, Ashish Kakoria, Lina Zheng, Guang Xu

Mining Engineering Faculty Research & Creative Works

The health of miners working in underground mines is greatly threatened by their exposure to respirable crystalline silica (RCS) found in coal dust. While coal dust includes RCS, it is important to know the specific filtration efficiency for RCS particles compared to coal dust to improve protective measures. This study compares the filtration efficiency of reduced graphene oxide (rGO) composite-incorporated Polyacrylonitrile (PAN) nanofibrous filters at four different concentrations of rGO (0, 2, 6, and 10 wt.%) for RCS particles and coal dust. The filters were made using the electrospinning method. They were tested separately with RCS particles and coal dust …

Berkarya Seni Lukis Akrilik Pada Kanvas Dengan Tema 5 Stages Of Grief, Gregorius Renaldi Teja Permana, Ike Rahmawati

Journal of Language, Literature, and Arts

This study aims to visualize the concept of the five stages of grief into acrylic paintings on canvas and to analyze the relationship between visual elements and emotional expression. The concept, introduced by Kübler-Ross, consists of five stages: denial, anger, bargaining, depression, and acceptance. The study employs Alma Hawkins’ art creation method, which includes exploration, improvisation, and formation. The exploration stage involves literature review, visual reference analysis, and interviews with participants. The improvisation stage produces sketches as the basis for artwork development, while the formation stage involves the execution of acrylic paintings on canvas. The results consist of six artworks …

Using The Four-Quadrant Model Of Think/Feel/Fast/ Slow To Understand The Decision-Making Of Self-Managed Superannuation Fund Trustees, Roger Colbeck, Steven D’Alessandro, John Minas

Research outputs 2022 to 2026

This research focuses on decision-making by trustees of self-managed superannuation funds (SMSFs) in Australia. Behavioral attributes are examined using the four-quadrant model (FQM) developed by Lovric et al. (2010), comprising the cognitive, affective, controlled, and automatic quadrants. The FQM integrates two closely related dual-process theories (DPT). Both the DPT framework and the FQM draw on foundational principles from the cognitive and behavioral sciences. The result of the mixed methods study uses the FQM to explain investment decision-making. The dataset was examined using cluster analysis to identify underlying group structures, followed by regression modelling to assess the relationships between key variables. …

Bifurcation Exploration Of Ion Acoustic Solitons Formation Of A Nonlinear Beta Fractional Kadomtsev-Petviashvili Burger Model In Plasma State, Mst. Razia Pervin, Alrazi Abdeljabbar, Fahad Sameer Alshammari, Mst. Shekha Khatun, Harun Or-Roshid

Mathematical Modelling and Numerical Simulation with Applications

This research presents an extensive investigation of Ion acoustic soliton dynamics governed by a Beta-fractional Kadomtsev-Petviashvili-Burgurs (KPB) model. By engaging the planar dynamical system scheme in aggregation with the extended $(\phi, \psi)$ expansion, Kudryashov expansion, and the NMKM analytic schemes, we create a broad class of exact nonlinear pattern wave solutions. The local stability edifice of the fractional plasma model is explored through bifurcation theory, enabling the far-reaching classification of all admissible phase diagrams. Conforming Ion acoustic wave structures allied with every detour alignment are systematically assembled. Owing to the fractional and dissipative appearances of the model, an all-embracing assortment …

Numerical Simulations And Hyers-Ulam Stability Of A Novel Nonlocal Anthropogenic Cutaneous Leishmaniasis Mathematical Model, Khalid Fanoukh Al Oweidi, Zakirullah -, Kamal Shah, Thabet Abdeljawad

Mathematical Modelling and Numerical Simulation with Applications

In this work, the fractal-fractional Atangana-Baleanu derivative with the Mittag-Leffler kernel is employed to capture the memory and hereditary effects inherent to anthropogenic cutaneous leishmaniasis transmission dynamics. The Banach fixed-point theorem and contraction mapping principle are used to prove the existence and uniqueness of solutions, while Hyers-Ulam stability of the system is analyzed to demonstrate the robustness of solutions with respect to small perturbations. Using a nonlinear least-squares approach, model parameters and fractional order are estimated using epidemiological data from the World Health Organization. The basic reproduction number $R_0 = 0.53$ indicates that the disease is under control after adding …

Markov-Modulated Queueing Network For Mobile Traffic Aggregation With Threshold-Controlled Buffers, Anton A. Esin, Elmira Yu. Kalimulina

Mathematical Modelling and Numerical Simulation with Applications

We study the problem of data transmission from mobile platforms operating in high-speed transit between cellular base stations, under conditions of unstable and intermittent connectivity. Conventional queueing and connectivity models often fail to capture the combined effects of rapidly changing signal conditions, finite buffer capacity, and dynamic topology. We aim to develop a tractable yet expressive model that integrates stochastic link availability, queue dynamics, and buffer control. We propose a mathematical framework based on queues whose service intensities are modulated by a continuous-time Markov chain (CTMC) representing signal conditions along a high-speed trajectory. The core subsystem is a two-stage (aggregation …

Optimal Control And Bifurcation Analysis Of A Predator–Prey Model With Self-Limiting Growth And Predator Disease, Dipo Aldila, Muhammad Akmal Fasya, Bevina D. Handari, Chidozie Williams Chukwu, Olumuyiwa James Peter

Mathematical Modelling and Numerical Simulation with Applications

We propose and analyze an eco-epidemiological predator–prey model that incorporates self-limitation and disease transmission within the predator population. The model is formulated as a system of ordinary differential equations describing logistic prey growth under the interspecific interaction with the predator. On the other hand, the predator population is divided into susceptible and infected classes, whose growth is constrained by prey availability. Three biologically relevant equilibria are identified: predator extinction, disease-free coexistence, and coexistence with endemic disease. The existence and stability of these equilibria are determined by key ecological and epidemiological thresholds, including the basic reproduction number. Using numerical continuation methods, …

The Role Of Transformable Facade Technologies In Enhancing The Architectural Environment Quality In Educational Buildings, Waad Marawan Elashry, Ahmed Eltantawy Elmaidawy, Esraa Elazab

Mansoura Engineering Journal

In recent times, Educational Buildings development has become an increasingly important issue at all locations, even in the areas with the least means. Progress in the field of technology has impacted the development of architecture and modern technologies have provided for the architect enormous possibilities in the formation and design of buildings. The facade of a building plays a crucial role in providing environmental comfort, depending on the type of envelope and design. Architects and engineers need to consider many issues when working with facade designs, including environmental issues, aesthetic appearance, comfort of building occupants, and the view; these aspects …

Neutrosophic Sets In Neural Networks: Theory, Applications, And Challenges, Vladimir Simic, Dragan Pamucar, Hafiz Muhammad Athar Farid

Neutrosophic Systems with Applications

The integration of neutrosophic sets into neural networks presents a novel approach to handling uncertainty, indeterminacy, and falsity in data. Traditional neural networks typically operate under the assumption of precise and complete data, but real-world applications often involve noisy, incomplete, or ambiguous information. Neutrosophic sets extend fuzzy logic by incorporating three components: truth, indeterminacy, and falsity, allowing for a more nuanced representation of uncertain data. This paper explores the theoretical foundations of neutrosophic sets and their integration with neural networks, highlighting the challenges in computational complexity, training, and optimization. The paper also discusses the potential applications of neutrosophic neural networks …

Emergent Operator Logic: A Foundational Framework For Dynamic Reasoning And Generative Intelligence, Mona Gharib, Abduallah Gamal, Muhammad Nawaz, Basma Nasir

Neutrosophic Systems with Applications

This paper introduces Emergent Operator Logic (EOL), a framework that treats propositions as continuous operators $F_p:X \rightarrow X$ on a complete metric state space $( X,d )$ and evaluates truth after action via a continuous valuation $V:X \rightarrow [ 0,1 ]$. Logical composition is realized by three operator-level connectives: sequential $p \circ q$(causal order), parallel $p\parallel q$(1-Lipschitz cooperative blend), and the emergent synthesis $E( p,q ) = \frac12( F_p \circ F_q + F_q \circ F_p )$, which symmetrizes non-commuting actions. We provide a Hilbert-style proof system (sound), an algebraic semantics via E-algebras, and show that the category of E-algebras is …

Impact Of Tropical Cyclones On Food And Nutrition Security: A Global Scoping Review And Thematic Analysis, Patience M. Chiotha, Budi Haryanto

Jurnal Epidemiologi Kesehatan Indonesia

The increasing frequency and intensity of tropical cyclones driven by climate change pose growing threats to food and nutrition security. Globally, an estimated 80–90 tropical cyclones occur annually, affecting approximately 119 million people. Evidence regarding their impact on food systems, dietary patterns, and nutritional status remains fragmented. This scoping review aimed to map global evidence on the impacts of tropical cyclones on food and nutrition security, identify key pathways of impact, and examine affected indicators at household and individual levels. The review followed Joanna Briggs Institute guidelines and PRISMA-ScR. Searches were conducted in PubMed/MEDLINE, Web of Science, Scopus, and Google …

Joint Channel–Spatial Attention With Curriculum Learning For Robust Crowd Density Estimation, Heba M. El-Hoseny, Heba F. Elsepae, Ehab K. I. Hamad, El-Sayed M. El-Rabaie

Mesopotamian Journal of Big Data

Accurate crowd counting remains a major challenge in computer vision due to perspective distortion, background clutter, occlusion, and poor illumination, which degrade feature representation and limit model generalization. This study introduces a robust and well-structured approach that integrates hybrid attention mechanisms with curriculum learning to enhance accuracy and stability in complex crowd scenarios. Gamma correction and CLAHE preprocessing enhance image visibility, facilitating the reliable detection of small and distant individuals under challenging lighting conditions. A mixed attention mechanism further enhances feature discrimination by emphasizing crowd-relevant regions while suppressing background noise. In addition, curriculum learning, guided by scoring and pacing functions, …

Automatic Classification Of Orange Fruit Diseases Using Multilayer Deep Features And Traditional Machine Learning Classifiers, Maha A. Rajab, Faris Ali Jasim Shaban, Kadhim Mahdi Hashim

Mesopotamian Journal of Big Data

Citrus diseases are the main issue for agricultural productivity, which cause a reduction in yield and quality, thus causing economic loss; also, we see that traditional methods of diagnosis, which are very subjective and prone to error, and thus we need to suggest accurate automated detection systems. In this study, we present a hybrid model that integrates conventional machine learning with deep learning models. We used the Gray Level Co-occurrence Matrix (GLCM) for feature extraction, which is classified via machine learning algorithms like k-Nearest Neighbors (KNN), Decision Tree (DT), Linear Discriminant Analysis (LDA), and Random Forest (RF). At the same …

Continuous Deep Learning With Elastic Weight Consolidation For Robust Multi-Class Lung Cancer Diagnosis, Zainab Muhammed, Belal Al-Khateeb

Mesopotamian Journal of Big Data

Lung cancer is the leading cause of death by cancer in the world, thus demanding an urgent requirement for reliable and reproducible diagnostic tools for its early detection and differentiation into subtypes. Most classical deep learning methods suffer from catastrophic forgetting and have trouble with continuous learning, especially with an increasing amount of clinical data. This work investigates these issues by introducing a best multi-class lung cancer classification framework consisting of Residual Network architecture (Resnet-50) and Continuous Deep Learning (CDL), and Elastic Weight Consolidation (EWC). The proposed model was trained sequentially using two tasks: Task1 consisted of 6,800 histopathological images …

Vision Transformer Model For Multiclass Classification And Localization Of Thoracic Abnormalities In Chest X-Rays, Mohammed Ahmed Talab, Sumia Abdulhussien Razooqi Al-Obaidi, Othman I. Hammadi, Suryanti Awang, Nur Syafiqah Mohd Nafis, Hasan Kahtan

Mesopotamian Journal of Big Data

Chest X-rays (CXRs) have been utilized as an important tool for diagnosing thoracic diseases because of their cost-effectiveness and accessibility. However, subtle signs of diseases, anatomical overlap and lack of expert radiologist in certain areas lead to difficulty in reading the CXRs. This indicates the needs of automated diagnostic systems to be accurate. Existing deep learning methods have shortcomings because they require pixel-level annotations to train models well. To address this problem, this study proposes Vision Transformers (ViT) with transfer learning for multiclass classification and weakly supervised localization of thoracic diseases in chest X-ray images. The technique uses patching, positional …

High-Power Dual-Channel Chamber For High-Frequency Magnetic Neuromodulation, Xiaoyang Tian, Hui Wang, Boshuo Wang, Jinshui Zhang, Dong Yan, Jeannette Ingabire, Samantha Coffler, Guillaume Duret, Quoc-Khanh Pham, Gang Bao, Junzhe Wang, Ashok Veeraraghavan, Jacob T Robinson, Stefan M Goetz, Angel V Peterchev

Faculty, Staff and Students Publications

Objective. Several novel methods, including magnetogenetics and magnetoelectric stimulation, use high frequency alternating magnetic fields to precisely manipulate neural activity. To quantify the behavioral effects of such interventions in a freely moving mouse, we developed a dual-channel magnetic chamber, specifically designed for rate-sensitive magnetothermal-genetic stimulation, and adaptable for other uses of alternating magnetic fields.

Approach. Through an optimized coil design, the system allows independent control of two spatially orthogonal uniform magnetic fields delivered at different frequencies within a 10 × 10 × 6 cm3 chamber suitable for mouse studies. The two channels have nominal frequencies of 50 and 550 kHz …

Proactive Resilience Enhancement Through Optimal Allocation Of Fast Voltage Support Devices Under Critical Multi-Bus Contingencies, Sunday O. Adetona, Habib A. Adetona, Adeola O. Balogun, Frank N. Okafor, Samson A. Alayande

Engineering and Technology Journal

In this paper, a two-stage optimization scheme of proactive resilience of the transmission system to severe multi-bus contingencies is developed. A hybrid PSO-GSA-Quantum metaheuristic is used to find the 4-bus reactive fault clusters in the IEEE 118-bus system in stage 1. The cluster identified with the performance index (PI) of 1.8875 × 10³ has the 91.6th percentile of 10000 random Monte Carlo samples and 1.78 times worse than the worst N-1 contingency. The results of the Monte Carlo analysis indicate that the PI distribution is essentially bimodal (skewness = 0.5188, kurtosis = 3.2394) and the distribution is concentrated around …