Digital Commons Network^™

Integrating Ai-Based Electricity Demand Forecasting With Solar Grid Planning To Enhance Sustainability And Reliability, Anas Thamer Mustafa, Omar Sharaf Al-Deen Al-Yozbaky

AUIQ Technical Engineering Science

Proper electricity-demand forecasting is essential for reliable power-system planning, particularly in urban networks facing rapid demand growth and transformer overloading. However, many previous studies have treated load forecasting and renewable-energy integration as separate tasks, which limits their usefulness for practical planning. This study develops an integrated forecasting–planning framework that links AI-based electricity-demand forecasting with photovoltaic (PV) system design and transformer-loading assessment. The framework is applied to real daily data from the Al-Intisar 132/33 kV substation in Mosul, Iraq, covering electrical load, temperature, population, and date-related variables for the period 2022–2024. Fourteen forecasting models from four methodological categories were evaluated: machine-learning …

Phytochemical Analysis And Safety Assessment Of Watercress Nasturtium Officinale: Antioxidant Capacity, Heavy Metal Profiling, And Toxicity Using Brine Shrimp Model, Qurrota A’Yunin, Chamini Kasun Hemachandra, Muhaimin Rifa’I, Yoga Dwi Jatmiko, Maftuch Maftuch, Rizky Fadilla Agustin Rangkuti, Cucun Herlina, Zulfa Mahdiatur Rasyida, Moh Dliyauddin

Karbala International Journal of Modern Science

Medicinal plants have attracted growing attention as sources of natural bioactive compounds for sustainable aquaculture and health. This study evaluated the phytochemical composition, antioxidant activity, heavy metal profile, and acute toxicity of watercress (Nasturtium officinale W.T. Aiton) methanol extract using maceration, qualitative and quantitative (TPC, TFC, antioxidant DPPH) phytochemical assay, XRF, and BSLA. Phytochemical screening of plant extracts showed the existence of flavonoids, alkaloids, phenols, tannins, triterpenoids, and saponins, but not steroidal. The TPC and TFC were 20.6 mg GAE/g and 10.8 mg QE/g, respectively. The extract displayed significant antioxidant activity (IC₅₀ = 64.78 µg/mL in DPPH assay). …

Transformative Climate Change Mitigation And Adaptation Policy Analysis In Medan City, Citra Tatius, Mega Anggraeni, Wiwandari Handayani, Rukuh Setiadi

Cities and Urban Development Journal

Background: Climate change is not only a global challenge but also a strategic issue of development in Indonesia. The Medan City Government has implemented various mitigation and adaptation efforts, yet it continues to produce greenhouse gas emissions and is exposed to climate change impacts. A transformative approach in mitigation and adaptation is needed to enable systemic change to comprehensively address climate change from its root causes.

Aims: This paper aims to elaborate on the extent to which mitigation and adaptation policies in Medan City can fulfill the principles of transformative climate actions.

Methods: Data collection for climate profiles and mitigation …

From Hesitation To Creation: Bookmaking, Language, And The Development Of Student Confidence In The Arts And Crafts, Kayla Rich

Theses and Dissertations

Many secondary students enter art classrooms believing that artistic ability is an innate talent rather than a skill that can be developed, often resulting in low confidence, perfectionist tendencies, and a reluctance to take creative risks. This action research study investigated how participation in a crafts-focused bookmaking curriculum affected students' engagement, divergent creativity, artmaking, and mindset in relation to success, failure, and creative risk-taking. Drawing on research in growth mindset, guided mastery, craft education, and artists' books, I designed and implemented a scaffolded curriculum that progressed from structured bookbinding techniques and process-based exploration to conceptually driven artists' books. The study …

Same Interdependent Risk, Different Valuation: How Risk Representation Shapes Ecosystem Investment Decisions, Shiyao Bao, Jiamin Zhao, En Yang, Llewellyn D. W. Thomas, Hansjörg Neth, Jan K. Woike, Sebastian Hafenbrädl

School of Psychology

Why do decision makers value the same risky opportunity differently when the underlying probability of success is unchanged? We study this question in ecosystem investment decisions, where success requires that none of the critical components fail, causing component risks to compound. We conducted a high-powered preregistered replication and extension of Adner and Feiler's key study (N = 3,600). Participants valued a $100,000 opportunity that required six independent components to succeed, each with a 75% chance of success, yielding an overall success probability of ≈18%. Replicating prior work, participants reported higher confidence and assigned higher valuations when they first saw the …

Type-2 And Type-N Rough Sets: A Hierarchical Generalization Of Pawlak Approximations With Some Applications", Takaaki Fujita, Ajoy Kanti Das, Suman Das, Sankar Prasad Mondal

Sustainable Machine Intelligence Journal

Uncertainty is ubiquitous in real-world systems and has motivated the development of various generalized set-theoretic frameworks, including rough sets, fuzzy sets, intuitionistic fuzzy sets, and neutrosophic sets. In particular, rough set theory represents uncertainty by approximating a target subset of a universe through two crisp sets, namely the lower and upper approximations, which are induced by an equivalence, or indiscernibility, relation.
Motivated by the well-established hierarchy of Type-2 and, more generally, Type-(n) fuzzy sets, this paper proposes and studies analogous higher-order extensions of rough sets. First, we introduce Type-2 rough sets as a two-level parameterized framework in which each primary …

Ai-Driven Prognostics For Pem Fuel Cells Using Optimized Machine Learning And Deep Learning Models For Accurate Lifetime Prediction, Walid Abdullah, Reda Mohamed, Ibrahim Alrashdi, Mohamed Abdel-Basset, Mahmoud Mahdi

Sustainable Machine Intelligence Journal

Predicting how long proton exchange membrane (PEM) fuel cells will last is important for making them more reliable and reducing maintenance costs. However, most existing methods struggle to understand complex patterns in the data, leading to less accurate predictions. This paper introduces two new models to improve predictions. The first model, attention-based long short-term memory (ALSTM), is based on LSTM networks with an attention mechanism. This helps the model focus on the most important time steps in the data, making predictions more accurate. The second model, B-Ridge-JADE, selects the most useful features from the data using an adaptive differential evolution …

Measuring Maintainable Income Under Natural Capital Depletion: A Dynamic Sustainability-Weighted Cost Of Capital Framework, Khaled Aldhaferi

Journal of King Abdulaziz University: Economics and Administration

Sustainability reporting has improved the visibility of climate, resource, and safety risks, but it still does not provide a measurement mechanism for separating maintainable operating surplus from income generated by depleting finite natural capital. This paper develops Dynamic Sustainability-Weighted Cost of Capital (Dynamic SWACC) as a governed shadow-accounting architecture for estimating sustainability-adjusted maintainable income. The framework begins from the Hicksian capital-maintenance view of income and the El-Serafy user-cost method, derives the user-cost charge from a finite-horizon operating-surplus annuity, and endogenizes the discount rate through auditable state variables: reserve-life constraint intensity, carbon-budget utilization, and operational safety risk. The developed contribution extends …

Digital Transformation And Sme Economic Contribution In Saudi Arabia: A Critical Analysis Through The Dynamic Capabilities Lens, Rodrigo Bochner

Journal of King Abdulaziz University: Economics and Administration

This analytical essay examines the intersection between digital transformation initiatives and small-to-medium enterprise (SME) economic contribution within Saudi Arabia's Vision 2030 framework. Drawing upon dynamic capabilities theory and analysis of government data, academic literature, and policy documents, we explore how digital transformation intensity influences SME performance and their contribution to economic diversification objectives. Government reports reveal that SMEs in Saudi Arabia grew from 429,026 enterprises in 2016 to over 1.8 million in 2024, yet contribute only 30% to GDP versus the Vision 2030 target of 35%. Concurrently, Saudi Arabia has achieved fourth place globally in digital government services and sixth …

Final Unreclaimed Sites Quality Assurance Project Plan (Qapp), Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Machine Learning Integrated Designing And Screening Of 8-Hydroxyquinoline Based Metallo-Beta-Lactamase Inhibitors, Anthony M. Baudino, Kari Stone

Chemistry Department Faculty Articles

The rapid emergence of metallo-b-lactamase-mediated antibiotic resistance has created an urgent need for new inhibitor discovery strategies. In this work, a machine-learning-guided workflow was developed to generate and prioritize potential inhibitors targeting NDM-1. A SMILES-based variational autoencoder was first pretrained on a broad molecular dataset to learn general chemical syntax and latent molecular representations. The model was then fine-tuned on an 8-hydroxyquinoline-enriched dataset to bias molecular generation toward zinc-binding chemical space relevant to metallo-β-lactamase inhibition. Generated compounds were processed through structural filtering and docking-based evaluation to create training data for downstream predictive modeling. Molecular fingerprints and physicochemical descriptors were then …

Evaluating Machine Learning Models On Classification Of Novel Cyber Attacks In The Healthcare Domain, Promise Ehimen

Dissertations, Theses, and Projects

The increasing adoption of the Internet of Medical Things (IoMT) has improved healthcare delivery through connected medical devices while simultaneously expanding the cybersecurity risks facing healthcare organizations. Although machine learning based intrusion detection systems have demonstrated high detection accuracy, their ability to respond reliably to previously unseen cyberattacks remains uncertain. This study investigated how a Neural Network model and a Logistic Regression model classified novel cyberattacks within the IoMT environment. The Neural Network and Logistic Regression models were both trained and tested using a subset of the CICIoMT2024 benchmark dataset. The Neural Network achieved 99.82% test accuracy and a 0.94 …

Psychological Needs And Ai Delegation Across Four Social Domains - A Cross-Cultural Analysis Of 35 Nations, Magnus Liebherr, Ala Yankouskaya, Mohamed Basel Almourad, Justin Thomas, Guandong Xu, Raian Ali

All Works

As artificial intelligence (AI) systems increasingly assume roles with social, educational, and emotional significance, understanding the psychological drivers behind individuals' readiness to delegate such roles to AI is crucial. Drawing on Self-Determination Theory (SDT), this study examines how the satisfaction of basic psychological needs (autonomy, competence, and relatedness) predicts individuals' readiness to delegate socially significant roles to AI across four domains (education, healthcare, mental health, and companionship) and 35 nations. Using data from over 35,000 participants in the 2023 Global Digital Wellbeing Survey, we applied Bayesian multilevel multivariate modelling to assess both global and culture-specific motivational associations. Results revealed that …

Ethnographic Insights Into Community-Based Circular Economy: The Case Of Waste Banks In Semarang, Rahoyo Rahoyo, Teti Susilowati, Sri Purwantini, Darto Sachius, Wilson M. A. Therik

ASEAN Journal of Community Engagement

The linear economy model has led to severe environmental degradation, prompting a shift toward the circular economy (CE) framework to promote sustainability. However, CE literature often overlooks grassroots, community-based initiatives in urban contexts, particularly in the Global South. This study addresses that gap by examining waste banks in Semarang, Indonesia, highlighting the critical importance of these grassroots initiatives within the broader discourse of community engagement. Using an ethnographic approach, data were collected through in-depth interviews, field observations, and open-ended survey responses across multiple community waste banks. The findings reveal the complex interdependence of four key actors—waste banks, itinerant collectors, scavengers, …

Systematic Review Of The Institutionalization Of Service Learning In Higher Education, Wilmer Hernan Cruz Gutierrez

ASEAN Journal of Community Engagement

An increasing number of universities are integrating service-learning (SL) to fulfill their social mission. However, sustainable institutionalization of SL remains a persistent challenge. This study identifies and analyzes the factors, actors, and strategies that drive and inhibit SL institutionalization in higher education. Using the PRISMA 2020 guidelines, a systematic literature review analyzed 52 documents from seven academic databases (including WoS, Scopus, and ERIC). The findings were grouped into three sections: cultural (integration into institutional values/missions), process (articulation within teaching, research, and outreach), and structural dimensions (dedicated support entities). The results obtained reveal a reciprocal relationship where cultural alignment enables processual …

Foundations Of Neutrosophic N-Semirings Theory And Structural Properties, Raja Muhammad Hashim, Muhammad Gulistan, Muhammad Shahzad

Neutrosophic Systems with Applications

In this paper the concept of neutrosophic n-semirings (S∪ I, ∗ ₁, ∗ _2, ∗ ₃,..., ∗ _n, ∗ _n+1) has been introduced. The substructure of n-semirings (S∪ I, ∗ ₁, ∗ _2, ∗ ₃,..., ∗ _n, ∗ _n+1) has been defined and some useful results have been proved. Moreover, in order to familiarize the readers with these concepts some worthy examples have been coined. The left, right and two sided ideals of neutrosophic n-semirings have been paid a special heed. Finally we have turned our discussion towards the compatible and congruence …

A Fuzzy–Neutrosophic Suitability Index For Selecting An Appropriate Reasoning Model Under Vagueness, Incompleteness, And Conflict, Nada A. Nabeeh, Ahmed Samy

Neutrosophic Systems with Applications

Fuzzy reasoning and neutrosophic reasoning are both used to handle uncertainty, but they are not intended for the same uncertainty structure. Fuzzy reasoning is suitable when uncertainty appears mainly as gradual vagueness, where a value may belong to a concept such as ``high risk'' or ``good performance'' to a certain degree. In this case, a membership value is often sufficient. Neutrosophic reasoning is more suitable when the problem also contains incomplete information, undecided evidence, or conflict between sources. In such cases, one membership degree may be too limited because it cannot represent support, rejection, and indeterminacy separately. This study introduces …

Evaluating Generative Ai-Based User Interfaces Using An Integrated Neutrosophic Multi-Criteria Decision-Making Framework, Nada Mohamed, Alshaimaa A. Tantawy

Neutrosophic Systems with Applications

User Interface (UI) design can be seen as an essential aspect of human-computer interaction (HCI) and makes communication easier between people and technology. In today's digital economy, interface quality has become one of the most important business concerns, since it has a direct impact on customer satisfaction and retention while affecting revenue. Although creating user-centered and accessible interfaces is crucial, doing so is a difficult and time-consuming process, which leads to burnout for many usability professionals. Although conventional artificial intelligence (AI) was utilized for design assessment and automation, the arrival of generative AI technology has created new possibilities for automated …

Art In Laparoscopy: A Fun Way Of Training In Minimally Invasive Surgery, Michael Dennis I. Dela Paz

DLSU Arts Congress Conference Proceedings

Paramount to the safety and efficiency of any surgical procedures warrants the enhancement of skills of the surgeon whether in training or practice. In minimally invasive surgery, one should inherently have excellent depth perception, consistent hand-eye coordination, and skillful use of the dominant and non-dominant hands to be able to perform operations with precision, efficiency, and safety. For most surgeons, sustaining or even improving these laparoscopic surgical skills through traditional drills would sometimes reach a point that it seems to be monotonous, and repetitive. Breaking away from the traditional skills will make the training and honing of minimally invasive surgical …

Enhanced Transdermal Immunization Via Solid-In-Oil Nanodispersions Incorporating Dendritic Cell-Targeting Peptide, Md Samiul Islam, Md. Shahin Ekka Sarker, Yoshirou Kawaguchi, Rie Wakabayashi, Noriho Kamiya, Muhammad Moniruzzaman, Masahiro Goto

Publications and Research

Transdermal immunization represents a promising needle-free alternative to conventional vaccination. However, efficient antigen delivery and robust immune activation remain major challenges. In this study, a solid-in-oil (S/O) nanodispersion system comprising a dendritic cell-targeting peptide (HR8), ovalbumin (OVA), and an adjuvant was developed for transdermal immunization. The HR8 peptide along with OVA was successfully incorporated into an S/O nanodispersion with an optimal hydrodynamic diameter of particles (< 200 nm) and exhibited stable physical properties for up to 90 days. In vitro and in vivo studies demonstrated enhanced antigen delivery with insignificant skin irritation in C57BL/6N mice. Moreover, in vivo transdermal immunization studies demonstrated that the addition of the HR8 peptide enhanced OVA-specific IgG responses (~1.5-fold). Notably, the HR8 peptide also promoted an approximately 2.5-fold increase in IgG2c levels, suggesting a shift toward a more T helper type 1-biased immune response, as reflected by an increased IgG2c/IgG1 ratio. Overall, these findings demonstrate that the incorporation of HR8 peptide into an S/O nanodispersion enables efficient transdermal antigen delivery and improved immunogenicity, highlighting its potential as a simple, non-invasive, and patient-friendly immunization strategy.

2026 Final Unreclaimed Sites Quality Assurance Project Plan (Qapp), Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Final Insufficiently Reclaimed Sites Quality Assurance Project Plan (Qapp), Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Recoverable Agentic Ai For Communication Networks: A Survey Of Architectures, Trust Regulation, And Failure Recovery, Omar K. Dawoud, Osama A. Ghoneim

Sustainable Machine Intelligence Journal

Agentic artificial intelligence is increasingly integrated into communication networks, enabling systems that perceive network state, reason over conditions, and execute actions on live infrastructure. As these systems act directly on operational environments, their behavior after failure remains insufficiently characterized: existing evaluation emphasizes throughput, latency, and accuracy, without capturing how systems recover after actions that affect network state. This survey examines agentic artificial intelligence in communication networks through the lens of recoverability, based on a systematically coded corpus of the recent literature. The paper introduces the MATR-R framework, which organizes recoverability around memory awareness, action governance, trust regulation, and recovery capability. …

Adasel: Adaptive Attention-Based Stacked Ensemble Learning With Explainable Ai Framework For Earthquake Alert Level Classification System, Alaa Desukey, Ahmed M. Abdelmouty

Sustainable Machine Intelligence Journal

Earthquakes are one of the most life-threatening natural events, and scientists are always concerned about their forecast. Standard machine learning (ML) algorithms have difficulty earthquake alert level classification (EALC) problem. The study presents an ADASEL framework for EALC. The data is merged using a stacked ensemble learning approach, including base learners and meta-models. The basic learners include Extra Tree, random forest (RF), lightGBM, XGBoost, CatBoost, and Gradient Boosting. The outputs are optimized using an attention-based multilayer perceptron meta-model (MLP), LSTM, and Transformer. The technique was tested using earthquake dataset. The data preprocessing steps are applied to enhance quality of the …

Educator Perspectives Of Available Special Education Transition Programming Through High School Career And Technical Education Organizations For Female Students In Self-Contained Classrooms, Cassandra L. Aungst

Theses and Dissertations

The problem addressed in this study was that there is a lack of research regarding alignment between special education student transition assessments, transition goals, and transition programming and specifically those who identify as female students. While career readiness programs are accessible to all students, regardless of gender, female students in special education remain underrepresented in career and technical education programs. The purpose of this research was to review educational practices that influence female students with disabilities in relation to their individualized education plan transition goals and programming by addressing (a) educators’ perceptions, (b) systemic challenges, and (c) policy gaps influencing …

Decision Making For Community Resilience: Applications In Flooded Transit Systems And Shared Housing, Mubarak Iddrisu

Graduate Doctoral Dissertations

Addressing climate-induced flooding and housing insecurity requires decisions that are technically sound, locally meaningful and feasible to implement. In public transit systems, flooding can damage infrastructure, increase travel time and reduce access to essential destinations, especially for older adults. Shared housing offers an alternative housing model where staff must balance affordability, compatibility, service exchange and participant choice when pairing home providers with housing seekers. In this dissertation, I examine how analytics and decision modeling can support community resilience across these two domains. I use spatial analysis, machine learning, optimization and matching theory to develop practical decision-support workflows. Chapter 2 proposes …

Leveraging Generative Artificial Intelligence To Effectively Implement School Counseling Interventions And Programs, Jeffrey M. Warren

Journal of Technology in Counselor Education and Supervision

Academic and mental health concerns persist in K-12 schools across the country. School counselors play a central role in addressing these issues and supporting the academic success, social/emotional development, and college and career readiness of all students. However, school counselors face numerous barriers when promoting student success. Making matters worse, emerging literature suggests that school counselors lack a clear understanding of how to implement programs and interventions effectively. Artificial intelligence can play a vital role in helping school counselors deliver effective and efficient services. This article provides overviews of implementation science and generative artificial intelligence. A case example and analysis …

Digraphicsoft Sets And Bidigraphicsoft Sets: Directed And Bidirected Extensions Of Graphicsoft Modeling, Takaaki Fujita, Ajoy Kanti Das, Suman Das, Sankar Prasad Mondal, Volkan Duran, Mithun Datta

Neutrosophic Systems with Applications

Uncertainty has been modeled through a wide variety of mathematical frameworks, including fuzzy sets, neutrosophic sets, rough sets, and plithogenic sets. Among these approaches, soft sets offer a parameterized representation of uncertain information and have inspired numerous extensions, such as multisoft sets, double-framed soft sets, hypersoft sets, SuperHyperSoft sets, TreeSoft sets, ForestSoft sets, IndetermSoft sets, and IndetermHyperSoft sets.
This paper focuses on GraphicSoft Sets, which extend the classical soft-set framework by assigning a subset of the universe to each subgraph of an attribute graph. In this way, relationships among attributes are incorporated directly into the parameterized model. Building on …

Neutrosophic Time-Truncated Acceptance Sampling Plans Based On The Exponentiated Weibull Distribution For Reliability Applications, Divya P.R., Preethi John

Neutrosophic Systems with Applications

Classical acceptance sampling plans require precisely specified parameter values, an assumption routinely violated by measurement uncertainty and gauge imprecision in practice. This article develops Neutrosophic Time-Truncated Acceptance Sampling Plans (N-TTASP) for the Exponentiated Weibull (EW) distribution by representing the scale parameter as a neutrosophic interval. The neutrosophic sample size n_N ∈ [n_L, n_U] and acceptance number c_N ∈ [c_L, c_U] are obtained by minimizing n_U subject to dual producer and consumer risk constraints on the neutrosophic Operating Characteristic interval. A new indeterminacy ratio η is introduced as a …

“We Are Writers At The End Of The Day”: Institutional Support, Accountability, And Community In Writing Groups For Faculty Of Color, María P. Carvajal Regidor

The Writing Center Journal

This article provides insight into how an accountability writing group for faculty of color supports faculty writers. It argues that targeted programming for faculty of color can serve as a modest anti-racist intervention into the white supremacist structures that often harm BIPOC faculty and their success in academia. Examining interview, survey, and registration data from a writing group for faculty of color, the article shows how the writing group functions as a counterspace, enabling participants not only to spend more time on their writing but to bring their full selves into an academic space and to form community. The article …