Digital Commons Network^™

Artificial Intelligence In Higher Education: A Bibliometric And Science-Mapping Analysis From An Institutional And Management Perspective, Kürşat Taştan, Nalan Sabır Taştan

Khazar Journal of Humanities and Social Sciences

This article maps the field of artificial intelligence in higher education (HEI-AI) from an institutional and management perspective. We draw on 52,270 peer-reviewed articles and reviews indexed in Web of Science and Scopus between 1959 and 2025. Using the bibliometrix package and its biblioshiny interface in R, we combine descriptive indicators with science-mapping techniques, including co-authorship and co-citation networks, keyword co-occurrence, thematic mapping and thematic evolution. The initial corpus of 94,845 records was cleaned by merging the two databases, removing duplicates and restricting the sample to full-length journal articles and reviews that explicitly address AI in higher education.

The results …

Decision Framework For Enhancing The Adoption Of Alternative Infrastructure Funding Models In Ghana, Samuel Kojo Aidoo, Patricia Lindelwa Makoni

CSID Journal of Infrastructure Development

This paper examines the socio-economic and infrastructure conditions that determine Ghana’s readiness to adopt alternative infrastructure funding models (AIFMs) for sustainable road development. The objective of the study is to identify the macroeconomic and sectoral drivers of AIFMs’ adoption and to develop policy frameworks for the sustainable financing of infrastructure within Ghana’s context. Ordinary Least Squares (OLS) regression analysis is applied to annual data from 2003 to 2023 to examine the relationship between macroeconomic and infrastructure indicators and economic growth , which is used as a proxy for the viability of AIFMs. The results show that employment growth, educational attainment, …

Saudi Stock Market Prediction Using Majority Voting, Mobeen W. Alhalabi, Aiiad Albishri

Journal of King Abdulaziz University: Computing and Information Technology Sciences

Predicting the stock market via data analysis is an important research topic. Because the system implementing it seems to think and act like humans, for the last two decades’ machine learning got a lot of attention from developers, programmers, scientists, even from the general public. Due to their advantages, machine learning techniques can be used in many areas, including finance and stock markets. Although many studies were performed with excellent results for the investors, many researchers are still looking for better results that will help minimize risk with higher percentage. In this study, the state of the techniques to predict …

Ethics_ How To Discuss Electronic Security With Your Clients, Indiana Continuing Legal Education Forum (Iclef)

Indiana Continuing Legal Education Forum 2025

Meeting proceedings of a seminar by the same name, held February 11, 2025.

Getting Started With Artificial Intelligence In 2025, Indiana Continuing Legal Education Forum (Iclef)

Indiana Continuing Legal Education Forum 2025

Meeting proceedings of a seminar by the same name, held November 25, 2025.

Winning Your Case With A Better Memory, Indiana Continuing Legal Education Forum (Iclef)

Indiana Continuing Legal Education Forum 2025

Meeting proceedings of a seminar by the same name, held April 24, 2025.

Equity Vignettes: A Practice-Based Resource, Liza Bondurant, Jane Wilburne, Dana Franz

Publications

Mathematics teachers have the power and responsibility to center equity in their teaching practices. Yet their framings and mindsets about equity can impact whether and how they use equitable teaching practices. In this manuscript, we describe how secondary mathematics teacher candidates responded to two equity vignettes focused on (1) gender identity and (2) race and tracking. We wrote these vignettes to expose candidates to situations they may encounter and decisions they may need to make as mathematics teachers. The purpose of this study was to explore the teacher candidates’ beliefs. We use the FAIR Framework and the Educator Mindsets for …

2025 - Tennessee Climate Snapshot, Tennessee Climate Office, East Tennessee State University

Tennessee Climate Office Monthly Reports

No abstract provided.

Operating Fund Budget/ Expenditure Summary Report 2nd Quarter 2025-26, Csusb Budget Office

University Budget Office records

No abstract provided.

Semi-Supervised Learning For Annotation And Representation Of Single-Cell Rna Sequencing And Spatial Transcriptomics Data, Haoran Liu

Dissertations

Semi-supervised learning has emerged as a powerful paradigm for analyzing single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST) data, where full annotation is often costly or impractical. scRNA-seq technologies measure the expression of thousands of genes across tens of thousands of cells, whereas ST additionally captures the spatial coordinates of gene expression within intact tissue sections. Annotation is a key step in both scRNA-seq and ST analysis pipelines, aiming to identify cell types, spatial domains, and latent biological structures. However, most existing annotation approaches rely on separate clustering methods that are typically fully unsupervised and fail to leverage side information …

Beyond Words: A Systematic Multimodal Framework For Text, Images, And Extreme Helpfulness In Online Reviews, Alvaro J. Aguado Marin

Dissertations

Online product reviews have become increasingly multimodal, combining text with media-rich elements such as images. However, academic research has largely examined textual features in isolation, overlooking how visual content and its interaction with text shape perceived helpfulness. This dissertation addresses that gap by developing and empirically validating a comprehensive framework capturing how textual, visual, and contextual features collectively influence review evaluation. Grounded in the Elaboration Likelihood Model (ELM) and extended through the Text-Image Elaboration Likelihood Model (TI-ELM), the framework advances understanding of how consumers process content from both user- and business-generated sources. It also lays the foundation for examining emerging …

Computational Design Of Nanoporous Materials For The Adsorption Of Per- And Polyfluoroalkyl Substances, Daniel D. Mottern

Dissertations

Per- and polyfluoroalkyl substances (PFAS) are a large family of chemicals that have seen wide usage due to their fluorinated carbon backbone. The presence of strong C-F bonds in the backbone lends PFAS molecules high thermal and chemical stability, as well as strong hydrophobicity and lipophobicity. This combination of properties has led to heavy use of PFAS as surfactants, non-stick coatings, and aqueous foam forming films and flame retardants. However, these properties bring their own consequences. The high chemical and thermal stability of PFAS renders them persistent, with the C-F bonds resisting naturally occurring forms of degradation. Existing forms of …

Entropic Forces Near Fluctuating Surfaces, Rubayet Hassan

Dissertations

Nanoscale structures are inherently dynamic due to persistent thermal fluctuations. Even in solid materials, these random deformations, driven by ambient thermal energy, can become significant when their characteristic scale approaches that of the structure itself and strongly influence their overall mechanical behavior. Examples of such structures include crystalline membranes, appearing in diverse forms such as nanotubes, nanoribbons, and kirigami/origami structures. Similarly, biological nanostructures, including lipid membranes, microtubules, actin filaments, and DNA, exhibit extreme flexibility and responsiveness due to their low bending rigidity. Numerous physiological processes are intrinsically linked to these thermal fluctuations, including exocytosis and endocytosis, membrane fusion, pore formation, …

Computational Methods For Single-Cell And Multi-Omic Data Integration And Regulatory Network Inference, Jianlan Ren

Dissertations

Single-cell and multi-omic technologies have transformed the dissection of cellular heterogeneity and regulatory dynamics in health and disease. However, the high dimensionality, technical variability, and biological complexity of these datasets present significant challenges for integration, annotation, and interpretation. In this dissertation, a suite of computational approaches is introduced to address key problems in single-cell and multi-omic data analysis through model-based innovations and applied statistical frameworks.

First, a constrained deep learning framework for single-cell data integration, label transfer, and clustering is proposed. By incorporating biologically motivated constraints into the training process, robust performance is achieved across simulated and benchmark datasets spanning …

Data-Driven Analysis And Atomistic Simulations Of Next-Generation Materials For Energy Conversion And Storage, Yuliang Shi

Dissertations

Metal-organic frameworks (MOFs), with their modular architectures and tunable properties, represent an especially rich domain for accelerated material design and discovery for a range of diverse applications. Within this class of multifunctional materials, two-dimensional (2D) electrically conductive MOFs (EC MOFs) are of particular interest, as their 7r-stacked layered structures combine permanent porosity with electronic conductivity, enabling potential breakthroughs in energy storage, energy conversion, and quantum sensing. But the discovery and design of new EC MOFs based on expensive experimental screening is increasingly impractical due to the infinite chemical space. Furthermore, the practical implementation of EC MOFs for specific tasks depends …

Optimal Power Flow Control In The Iraqi Power Grid Using Artificial Intelligence Algorithms For Carbon Emission Reduction, Mohammed Shakir Juber

Al-Esraa University College Journal for Engineering Sciences

Iraq’s power sector remains in a protracted and severe crisis characterized by a significant mismatch between supply and demand, high levels of losses during transmission and distribution, as well as an increasing challenge to the resources base being largely unfavourably. These inefficiencies impose heavy costs on the national economy in excess of 40 billion annually and they also reinforce greenhouse gas emissions, and exacerbate environmental issues. To deal with these problems, we proposed in this paper that a new hybrid AI tool should be developed for the solution of multi-objective optimization problem based on purpose Genetic Algorithm (GA) merger with …

Applying Machine Learning Techniques For Early Detection Of Cyber Attacks On Iot Devices, Noor Adnan Allamy

Al-Esraa University College Journal for Engineering Sciences

This research designs, implements, and evaluates a machine learning-based framework for the early detection of cyber attacks targeting Internet of Things (IoT) devices, with a specific focus on the context and challenges present in Iraq. The study conducts a comparative analysis of three supervised learning algorithms—Support Vector Machine (SVM), Random Forest (RF), and Deep Neural Networks (DNN)—using a combination of benchmark datasets (NSL-KDD, CIC-IDS-2017, Bot-IoT) and a synthesized dataset adapted to simulate the Iraqi threat landscape. Key performance metrics, including accuracy, precision, recall, and F1-score, were used for evaluation. The proposed Random Forest model demonstrated superior performance, achieving an accuracy …

Ai-Enhanced Heat Transfer Optimization In Magnetic Bio-Nanofluids, Hasan Attyah Shaboot

Al-Esraa University College Journal for Engineering Sciences

This study presents a hybrid Artificial Intelligence–Computational Fluid Dynamics (AI-CFD) framework for optimizing heat transfer in magnetic bio-nanofluids subjected to external magnetic fields. Magnetic bio-nanofluids, composed of biocompatible base fluids containing superparamagnetic nanoparticles, exhibit tunable thermal and flow behavior, making them promising for biomedical and micro-cooling applications. Conventional optimization methods based on experiments or brute-force CFD are computationally expensive and limited in exploring the full design space. To overcome these challenges, an Artificial Neural Network (ANN) surrogate model was developed to predict two key performance indicators, the Nusselt number and the friction factor, with high accuracy (R² > 0.997). The surrogate …

The Role Of The Scenario In Formulating The Contemporary Architectural Text, Rounaq Arif Mohsin, Abbas Ali Hamza, Bashar Shamil Alkhafaji

Al-Esraa University College Journal for Engineering Sciences

In order to create an integrated architectural text, which is a complicated art that blends beauty and practical elements, a rigorous design procedure is necessary. In this situation, the scenario’s role becomes crucial in developing the current architectural text and directing architectural approaches. In order to better understand how the scenario influences the design process and the interactions between various architectural aspects, this project intends to explore and analyze the impact of the scenario in developing and refining architectural text formulation approaches.

The study looks at the idea of a scenario and how it has been used in architecture, as …

From Fashion To Electronics: Analyzing Shopee Indonesia Email Marketing Content Across Different Product Categories, Tri Anita Rahayu, Irmawan Rahyadi, La Mani La Mani

ASEAN Marketing Journal

This study explores the email marketing content employed by Shopee Indonesia across various product categories, including fashion, health & beauty, electronics, digital products, and home & living. By analyzing the variations in themes, messaging, and promotional tactics, the research aims to understand how Shopee Indonesia customizes its email content to optimize engagement and conversion rates across these diverse categories. The findings reveal that Shopee Indonesia employs distinct content strategies tailored to the specific characteristics and consumer preferences associated with each category, highlighting the platform's strategic approach to targeted marketing.

Wilhelm Von Humboldt And The Idea Of The Modern University: The Unity Of Bildung And Wissenschaft, Ken Udas

Graduate Masters Theses

Wilhelm von Humboldt and the Idea of the Modern University examines Wilhelm von Humboldt’s contribution to shaping a philosophical ideal that has profoundly influenced the concept and identity of the modern research university for over two centuries. It highlights Humboldt’s position as a key figure in the Prussian reform movement and as the founder of the University of Berlin. Specifically, it addresses a question raised in the late twentieth century as part of the Mythos Humboldt revision: why has the Humboldtian Ideal maintained such lasting influence over the German university system, even as its practical realities have increasingly strayed from …

Digital Transformation And Its Role In Achieving Sustainable Competitive Advantage: Entrepreneurial Capabilities As A Mediating Variable – An Analytical Study Of A Group Of Private Banks, Kamal Kadhim Al-Hassani, Ali Matar Abd

Muthanna Journal of Administrative and Economics Sciences

This study aims to explore the mediating role of entrepreneurial capabilities in the relationship between digital transformation and competitive advantage in the Iraqi banking sector. The study adopted a descriptive-analytical approach, and data were collected through questionnaires distributed to 235 managers in private banks in Iraq, using a structured survey instrument. Structural Equation Modeling (SEM) was employed via AMOS v.25 to analyze the data and test the hypothesized relationships. The results revealed a statistically significant positive relationship between digital transformation and competitive advantage, highlighting the pivotal role of digital transformation in enhancing banks’ ability to achieve competitive superiority. More importantly, …

A Novel Mathematical Model Of Hiv Transmission Incorporating The Effects Of Treatment And Pre-Exposure Prophylaxis: Sensitivity Analysis And Numerical Simulations, Erick Manuel Delgado Moya

Mathematical Modelling and Numerical Simulation with Applications

Human immunodeficiency virus (HIV) continues to be a public health problem in many countries of the world, and Pre-exposure prophylaxis (PrEP) is a preventive method for HIV, which has shown great efficacy and is in use worldwide. This work presents a new mathematical model for HIV transmission incorporating PrEP use and evaluates the impact of PrEP along with its increasing use in a population. The construction of the model takes into account three forms of diagnosis: diagnosis of individuals in risky sexual contact, diagnosis after risky contact (diagnosis in the undiagnosed infected compartment), and diagnosis associated with attempting to enter …

Pdf Of Full Issue: 17(6) 2025, Rosalind L. Raby

Journal of Comparative & International Higher Education

No abstract provided.

Editors’ Reflections: Insights On The Role Of Approximations In Practice-Based Mathematics Teacher Education, Bima Sapkota, Heather Howell, Liza Bondurant, Carrie Wilkerson Lee

Publications

In this colloquium, we will present six years of collaborative research on approximations of practice in mathematics teacher education, exploring how these approximations shape teacher preparation and addressing issues of equity and authenticity in instructional design. Foci include past findings, current challenges, and future directions, drawing from the recently published book edited by the colloquium leaders: Promoting Equity in Approximations of Practice for Mathematics Teachers. Participants will engage in critical conversations on bridging research and practice, with opportunities to join ongoing collaborations.

Evaluating Stormwater & Carbon Benefits Of Urban Street Trees, Anthony J. Rodriguez Diaz

Theses

Urban areas experience a multitude of environmental challenges, including flooding and air pollution. In response to these pressures, urban forests have emerged as an essential nature-based strategy to enhance resilience and reduce climate-related risks. The implementation and expansion of urban street trees further contribute to this effort by mitigating stormwater runoff and reducing atmospheric carbon emissions.

Fortunately, advances in environmental modeling have made it increasingly possible to quantify these ecosystem services using specialized software. The United States Department of Agriculture (USDA) Forest Service's i-Tree suite exemplifies this progress. The software provides a comprehensive set of tools designed to quantify environmental …

A Novel Rheological Technique To Measure The Yield Stress In Equibiaxial Elongation, Asher Segal

Theses

Yield stress measurement in non-Newtonian fluids, particularly under complex flow conditions such as equibiaxial elongation, remains a significant challenge in experimental rheology. This work presents the development of a novel method, Continuous Lubricated Squeezing Flow (CLSF), designed to quantify the normal yield stress of viscoelastic materials while minimizing boundary artifacts.

The CLSF method was implemented and validated using Carbopol 940, a model yield-stress gel, at concentrations of 1 wt% and 2 wt%. Comparative shear rheology was first performed to establish baseline yield stresses and verify sample integrity. CLSF experiments were then conducted over controlled flow rate increments and gap distances …

Real-Time Deep Learning Detection Of Toraja Carving Motifs Using Yolo11m For Cultural Heritage Preservation, Herman Herman, Farid Wajdi Mufti, Abdul Rachman Manga, Haidawati Nasir

Knowledge Engineering and Data Science

Toraja carvings are an important part of Indonesia’s cultural heritage, rich in symbolic, aesthetic, and philosophical meaning. However, the identification and preservation of carving motifs still rely on subjective, time-consuming manual processes, limiting scalability and inconsistent knowledge transmission. From a Knowledge Engineering and Cognitive Data Science perspective, this challenge highlights the need for mechanisms that can transform visual cultural artifacts into structured, machine-interpretable knowledge. This study investigates the use of the YOLO11m model as a data-driven approach for modeling cultural knowledge through automated detection of three Toraja carving motifs: pa_tedong, pa_kapu_baka, and pa_manu_londongan using original images collected directly from traditional …

Re: Conditional Approval For The Butte Priority Soils Operable Unit (Bpsou) Revised Unreclaimed Sites Ur-08 (Anderson Shaft) – Remedial Action Work Plan (Rawp) (Dated October 24, 2025), Molly Roby

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Re: Approval Letter For The Butte Priority Soils Operable Unit (Bpsou) Revised Draft Final 2022 Insufficiently Reclaimed Sites Sampling: Bres No. 37 – Josephine Shaft Site Evaluation Summary Report (Dated October 16, 2025), Molly Roby

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.