Digital Commons Network^™

Dollar$ And $Ense Newsletter Summer 2026, Nova Southeastern University

Dollars & Sense Newsletter

No abstract provided.

Dataset To Analyzing Energy Use In 2 & 3d Imaging Systems And Workflows, Michael J. Bennett

Published Works

Analyzing Energy Use in 2D & 3D Imaging Systems and Workflows Dataset

CONTENTS: Z-WaveReportingProfiles; SessionInput; DroneFlights; SessionsComputed; Types; ByType; GrossSummaryUnweighted; WeightingSummary; Raw Sampling History Data

The Role Of Chatgpt In Higher Education: A Systematic Literature Review Of Applications, Perceptions And Ethical Implications, Mahmoud Abdelrahman, Shiyu Hu, Ons Al-Shamaileh, Ramy Hammady, Nishara Nizamuddin

All Works

Purpose – This study aims to systematically review the emerging literature on ChatGPT in higher education, focusing on its applications, impacts and ethical implications from the perspectives of students and academic staff. By synthesising evidence across disciplines and geographical contexts, the review identifies key benefits such as enhanced learning efficiency and artificial intelligence (AI) literacy, alongside challenges including academic integrity risks and unequal access. The purpose is to provide a comprehensive, student-centred understanding of ChatGPT’s role in higher education and to offer actionable insights for policy, practice and future research. Design/methodology/approach – This study adopts a systematic literature review (SLR) …

Social Network Assessment For Adult Protective Services (Snaaps), Version 1.0: A Network Canvas Data Collection Instrument, Rebecca L. Mauldin, Laura E. Carter

Social Networks for Social Good Collection-Archive

The Social Network Assessment Protocol for Adult Protective Services (SNAAPS) is a Network Canvas interview protocol designed to support the collection, organization, visualization, and interpretation of social network data from older adults. The protocol was developed for use by Adult Protective Services practitioners, social workers, first responders, and other service providers who assess, refer, and intervene on behalf of older adults' well-being. The protocol facilitates the identification of social network characteristics associated with risk and protection related to elder mistreatment, including support relationships, financial involvement, conflict within the network, frequency of contact, connections to formal services, and patterns of network …

Best Strategies To Teach Nutrition Courses In Graduate Programs: A Systematic Review, Zeina Hojeij, Suzan Haidar, Rana Rizk, Nadine Mahboub

All Works

Introduction – Graduate-level nutrition education requires innovative teaching strategies that foster advanced clinical competence, professional communication, cultural responsiveness, and self-directed learning. Methods – This systematic review synthesized evidence from fifteen peer-reviewed studies examining diverse teaching strategies in graduate nutrition programs. Results – Most interventions employed simulation-based learning, experiential placements, or flipped classrooms, often incorporating technology such as virtual simulations and online collaborative platforms. Simulation and experiential approaches improved clinical competence, communication skills, empathy, and self-efficacy by providing realistic, hands-on experiences that bridged theoretical knowledge with professional practice. Flipped classrooms, though less frequently implemented, promoted teamwork, problem-solving, and reflective learning, while …

Concordia Seminary Magazine Spring 2026, Ken Ohlemeyer

Concordia Seminary Magazine

Shaped for His Service

Shimmer Methodology: May 2026 Cultural Studies Association Of Australasia, Lola Montgomery

Staff Scholarship - Australia & Dubai

This webinar presents an overview of the contemporary state of creative-practice research and autotheory before introducing Shimmer, an emerging methodological framework developed through creative practice, postgraduate supervision, and reflective inquiry. The presentation argues that while creative-practice research has successfully established creative work as a legitimate form of knowledge production, and autotheory has legitimised lived experience as theoretical material, both traditions leave relatively under-theorised the embodied moment through which insight first emerges.

The significance of the work lies in its contribution to ongoing debates around embodiment, affect, intuition, and knowledge production within creative-practice research. Shimmer proposes a language for understanding …

Graduates List - May 2026, University Of Nebraska At Omaha

Commencement Lists

No abstract provided.

The 12-Week Silence: A Scrollytelling Investigation Into Early Pregnancy Loss And The Case For Continuous Progesterone Monitoring, Audrey Gold

FHSS Mentored Research Conference

Opens with the scale of the problem (up to 1M miscarriages annually, all in the most data-poor window of pregnancy), describes the methodology (2 original surveys, 4 clinical interviews, peer-reviewed literature), walks through what the piece does visually (the distribution curve, the blind-spot timeline, the 5-phase progesterone chart, the intervention pathway), and closes with the central argument — that the silence is a gap in technology, not an inevitability.

Section 9 Of The Endangered Species Act (Esa): History Of Harm, Maxwell Lee Hirrill

University of Montana Conference on Undergraduate Research (UMCUR)

Since its passage, the Endangered Species Act (ESA) has held the unofficial title of the strongest law for environmental protections. This Act, passed in 1973, contains powerful language, with one word standing out among them all: "take" found in section 9. Section 16 U.S.C. § 1532(19) defines take as "to harass, harm, pursue, hunt, shoot, wound, kill, trap, capture, or collect, or attempt to engage in any such conduct." The definition of harm has been interpreted in different ways over the years, with some interpretations granting it more power and others limiting it. A particular point of contention within the …

Review On Data Privacy And Security For Iot-Based Multifunctional Layers Of Cyber-Physical Systems In Smart Grids, Mohammad Kamrul Hasan, Md Mehedi Hasan, Nabeel Al-Qirim, Siti Norul Huda Sheikh Abdullah, Shayla Islam, Md Abdur Razzaque

All Works

Smart grid cyber-physical systems (SG-CPS) are intelligent platforms that incorporate IoT-enabled multifunctional layers including the physical, perception, communication, cyber, and application layers. It includes supervisory control and data acquisition, wide-area measurement systems, and advanced metering infrastructure for remote data aggregation, monitoring, and control operations. From an environmental perspective, these green technologies support two-way operations, which generate and transmit data over wired and wireless communication systems. However, this critical infrastructure faces data privacy and cybersecurity challenges. Hence, extensive research is required to address data privacy and security gaps to strengthen national grid cybersecurity and reduce economic losses. Therefore, this review highlights …

In What Style Shall I Confront Them? The Role Of Social Relationships In Social Correction Of Misinformation Among The Uk And Arab Social Media Users, Muaadh Noman, Mohamed B. Almourad, Ala Yankouskaya, Firoj Alam, Raian Ali

All Works

This study investigates how social factors influence the likelihood of employing direct or indirect communication styles when correcting misinformation on social media in two different cultural contexts, the United Kingdom (UK) and the Arab Gulf Cooperation Council (GCC) countries. We conducted an online survey, supported by vignettes, that involved 686 participants, 367 from the UK and 319 from the Arab GCC countries. Participants were presented with a misinformation scenario and asked about their likelihood of using direct or indirect communication styles to correct their acquaintances. The survey captured variations in gender similarity (same vs. different gender), social status (lower vs. …

Hybrid 3d Modelling Framework For Indoor Navigation Using Federated Learning And Internet Of Things-Enabled Edge Devices, Noopur Tyagi, Jaiteg Singh, Saravjeet Singh, Ahmad Ali Alzubi, Farman Ali, Sukhjit Singh Sehra, Babar Shah

All Works

Background There has been a recent trend towards using three-dimensional (3D) models to enhance spatial awareness and maximize resource utilization in complex environments. 3D building model can be used in various applications, such as real-time guidance and tracking the positions of individuals in multi storied buildings. Cities are now being modeled and studied in three dimensions as an improved method of urban planning. Method This study proposes an advanced indoor navigation framework that combines 3D modelling, federated learning (FL), and Internet of Things (IoT) integration to deliver reliable floor-level localization and real-time guidance. In Phase 1, highly accurate 3D models …

Emerging Threats In Ai: A Detailed Review Of Misuses And Risks Across Modern Ai Technologies, Niyat Seghid, Farkhund Iqbal, Khalifa Al-Room, Áine Macdermott

All Works

The swift evolution of artificial intelligence (AI) has enabled unprecedented capabilities across domains, while simultaneously introducing critical vulnerabilities that can be maliciously exploited or cause unintended harm. Although multiple initiatives aim to govern AI-related risks, a comprehensive and systematic understanding of how AI systems are actively misused in practice remains limited. This paper presents a systematic review of AI misuse across modern AI technologies. We analyze documented incidents, attack mechanisms, and emerging threat vectors, drawing from existing AI risk repositories, prior taxonomies, and empirical case reports. These sources are synthesized into a unified analytical framework that categorizes AI misuse across …

Critical Tourism Studies In Business Journals, Paolo Mura, Heather Jeffrey, Martin Sposato

All Works

Business is commonly understood as a parent discipline of tourism research, making business journals essential for epistemological inquiry. This paper reviews tourism literature in business journals, analysing the presence of Critical Tourism Studies, which addresses limitations of management-oriented approaches. Our analysis reveals limited engagement with Critical Tourism Studies in business journals, only 27% of reviewed articles aligning with its tenets. We propose a framework for Critical Tourism Business Studies that identifies knowledge gaps and highlights future directions for scholars publishing tourism-related topics in business journals. This framework aims to bridge disciplinary gaps and enhance interdisciplinary research. The article contributes to …

The Voices Of Play- Understanding Children’S Perspectives Of Naturalized And Forested Outdoor Play Environments, Kimberly Squires, Kim Barton, Madi Stubbs, Mandy English

IALS Journal

is qualitative participatory study explored young children's perspectives of naturalized and forested outdoor play environments at an early learning laboratory school in Ontario, Canada. Drawing on the Mosaic Approach, photo-elicitation, and the Reggio Emilia concept of the hundred languages of children, researchers invited preschool children to communicate their perspectives through photography, drawing, and discussion. Findings revealed that both naturalized and forested environments supported meaningful connections with nature, although children engaged with each setting in distinct ways. Forested environments encouraged broader and more action-oriented interactions with natural materials, while naturalized environments fostered more diverse and specific connections with environmental features. The …

Terrence Dean, Mark Naison, Steven Payne, Pastor Crespo Jr., Akilah Shedrick

Oral Histories

No abstract provided.

An Ai Tool Recreates Some Of The Friction Of Academic Search. Is That Actually Helpful?, Jasmine S. Kirby

Libraries Faculty & Staff Publications

Keenious mitigates some of the educational risks of AI search. But its limitations will frustrate some users.

Usaid Grant Recipient Data Fy2002-2025, Susan Turner Haynes

Faculty Works

Grant recipient data from USAID from fiscal years 2002-2025.

Optimizing Proaftn Classifier With Ant Colony Algorithm: Enhanced Diabetes Detection Benchmarking, Feras Al-Obeidat

All Works

The increasing global prevalence of diabetes highlights the need for accurate diagnostic tools to improve early detection and effective treatment planning. Traditional classification models often struggle to achieve optimal performance due to limitations in parameter tuning and adaptability to complex datasets. To address these limitations, this article introduces PROAnt, an innovative learning approach designed to enhance the robustness and efficiency of the PROAFTN multicriteria classification method. PROAnt leverages the computational power of ant colony optimization (ACO) to dynamically fine-tune and optimize the key parameters, such as intervals and weights, at the core of the PROAFTN classification process. This learning methodology …

Anonymized Survey Dataset On Road Safety Assessment During Construction Of Bus Rapid Transit (Brt) Corridors In Dar Es Salaam, Tanzania, Lorain Salufu

Open Data

This dataset contains anonymized survey responses collected for a study on road safety assessment during construction of the Dar es Salaam Bus Rapid Transit (BRT) Phase 3 corridor. The dataset includes responses from 400 participants, together with the survey. The data were collected to assess perceived safety conditions, adequacy of construction-phase safety measures, effectiveness of traffic diversions, and the effects of construction activities on road users and nearby communities. No personally identifiable information is included in the shared files.

Artificial Sense-Making Dataset, Jason A. Bengtson, John Sandstrom, Nathan Camp

NMSU Library: Datasets

No abstract provided.

Slm With Swarm Intelligence For Efficient Representation Of Medical Claims, Mohamed Ahmed Abo El-Enen, Ravi S. Sharma, Mustafa Abdulrazek, Amril Nazir, Reem Muhammad, Ahmed Talat Sahlol

All Works

Healthcare industry faces significant challenges due to fraudulent medical insurance claims, which result in substantial financial losses. We propose an automated system using domain-specific Small Language Models (SLMs) with a narrower scope and smaller parameter count than general-purpose Large Language Models (LLMs), combined with optimization algorithms to improve fraud detection. Our approach integrates numerical features, such as age and claim amount, with textual descriptions, including diagnoses and procedures, into a unified textual representation for each medical activity. This representation captures complex patterns, enhancing the model’s predictive ability. SLMs fine-tuned on medical corpora transform these textual inputs into fixed-dimensional numerical embeddings, …

Optimized Hybrid Beamforming For Ris-Assisted Multi-User Mimo In 6g Mmwave Networks: A Low-Complexity Approach To Spectral Efficiency And Interference Mitigation, Safiya Nasser Al-Jaradi, Mohammad Kamrul Hasan, Nabeel Al-Qirim, Shayla Islam, Thippa Reddy Gadekallu, Hana Mujlid, Hashim Elshafie, Rashid A. Saeed

All Works

The joint optimization of hybrid beamforming and reconfigurable intelligent surface (RIS) phase shifts in multi-user millimeter-wave (mmWave) MIMO systems is a challenging problem, mainly due to high computational complexity and the lack of adaptive interference management. Existing approaches typically rely on fixed Zero-Forcing (ZF) or Maximum-Ratio Transmission (MRT) designs or require iterative optimization with high overhead, limiting their practical use in dense 6G environments. To overcome these challenges, this research proposes a RIS-Aided Adaptive Zero-Forcing and Maximum-Ratio Transmission Hybrid Precoding (RA-ZMHP) framework for 6G mmWave multi-user MIMO systems. The main novelty of the method lies in an adaptive ZF–MRT mixing …

Edge-Aware Ris-Assisted Dynamic Channel Allocation With Lightweight Llm Decision Agent For Interference Mitigation In Low-Altitude Remote Sensing Networks, Safiya Nasser Al-Jaradi, Mohammad Kamrul Hasan, Nabeel Al-Qirim, Shayla Islam, Muhammad Attique Khan, Rashid A. Saeed, Hashim Elshafie, Bishwajeet Kumar Pandey, Khairul Akram Zainol Ariffin

All Works

Low-altitude remote sensing networks are increasingly important for applications, such as environmental monitoring, disaster response, infrastructure inspection, and real-time sensing services. However, when many sensing nodes share limited spectrum resources, severe cochannel interference can degrade communication reliability and delay sensing-data delivery. This challenge becomes more critical in edge-enabled deployments, where control decisions must be made under strict latency, memory, and computational constraints. To address this issue, this article proposes a large language model (LLM)-enhanced edge-aware lightweight reconfigurable intelligent surface (RIS)-assisted dynamic channel allocation (EL-RIS-DCA) framework for interference mitigation in dense low-altitude remote sensing networks. The novelty of the proposed framework …

Lightweight Tinyml-Enhanced Task Offloading In Vanets For Next-Generation Intelligent Transportation Systems, Muhammad Ali, Tariq Qayyum, Asadullah Tariq, Zouheir Trabelsi, Irfan Ud Din, Shabir Ahmed

All Works

Vehicular Ad Hoc Networks (VANETs) face resource constraints, high node mobility, and stringent latency requirements, especially in safety-critical applications such as collision avoidance, path planning, and emergency braking. Task offloading to nearby vehicles or Roadside Units (RSUs) mitigates local computational limits, but dynamic conditions, unreliable nodes, and rapid topology changes complicate dependable node selection. This paper proposes a Tiny Machine Learning (TinyML)-enhanced, credibility-based task offloading framework for real-time decision-making in vehicular networks. RSUs evaluate vehicle reliability through a three-component Credibility Assessment Module: a Task Assignment Component that distributes lightweight test tasks and filters unreliable nodes via TinyML inference; a Verification …

Aoi-Aware Agentic Federated Mixture-Of-Digital-Twin Experts For 6g Vehicular Edge Intelligence, Asadullah Tariq, Mohamed Adel Serhani, Ikbal Taleb, Shayma Alkobaisi, Tariq Qayyum, Irfan Ud Din

All Works

Digital twin-enabled vehicular edge intelligence is expected to become a fundamental service paradigm for sixth-generation (6G) intelligent transportation systems. However, the performance of such systems depends not only on model accuracy, but also on the freshness of digital twin states, timeliness of inference, privacy-preserving model training, and efficient use of heterogeneous edge resources. Existing DT-assisted federated learning and edge mixture-of-experts solutions optimize digital twin synchronization, distributed learning, and sparse inference largely independently, without allowing digital twin states to actively govern expert specialization, expert refreshing, and distributed orchestration. Nevertheless, the joint problem of how digital twins should guide federated expert specialization, …

Integrative Machine Learning Of Genetic And Lifestyle Factors For Personalized Skin Health, Yassine Benachour, Lina Maloukh, Barbara Geusens

All Works

Objective: To develop an AI framework that combines genetic, phenotypic, and lifestyle data for profiling skin-health patterns and generating hypothesis-supporting summaries for potential decision support. Methods and procedures: A dataset of 5,254 individuals integrates six genes (FLG, AQP3, MMP-1, MMP-3, SOD2, GPX), six phenotype severities, and 20+ lifestyle factors. Mutation burden and interactions are tested by ANOVA. K-modes clustering identifies four interpretable dermatological profiles within the cohort and is embedded in leakage-free nested cross-validation (train-only selection; test labels from training centroids). Subtypes are predicted from genetics plus lifestyle using an XGBoost (XGB) classifier; explainability uses gain, permutation importance, and SHAP …

Human Factors In Visual Attention: Gender Differences In Engagement With Male-Oriented Ads, Mohamed Basel Almourad, Emad Bataineh, Zelal Wattar, Mohammed Hussain

All Works

In today's competitive market, it is increasingly important to understand how visual design shapes customer behaviour. This study examines the decision drivers influencing female customers' purchase choices when buying male-oriented products as gifts, identifying the visual components of advertisements that attract them by analysing the relationship between purchase intention and visual attention. Results show that participants with higher purchase intent focused more on product imagery and branding, indicating that visual appeal, perceived quality, and brand familiarity significantly guide their decisions, with brand awareness speeding up decision-making by reducing the need for repeated visual checks. Conversely, those with low purchase intent …

Observation Of Altermagnetic Spin-Splitting In An Intercalated Transition Metal Dichalcogenide, Milo X. Sprague, Madhab Neupane

Research Data and Datasets

Altermagnetism is a novel magnetic phase combining characteristics of both antiferromagnetism and ferromagnetic ordering. Despite growing theoretical interest in altermagnetic materials, reports of experimentally verified high-Néel-temperature layered compounds are limited or remain to be firmly established. In our manuscript, Observation of Altermagnetic Spin-Splitting in an Intercalated Transition Metal Dichalcogenide by M. Sprague et al, we present an angle-resolved photoemission spectroscopy and density functional theory study of Co1/4TaSe2, a compound we identify as a layered altermagnetic material. Our spin-resolved and spin-integrated angle-resolved photoemission spectroscopy measurements reveal an electronic band structure in excellent agreement with density functional theory calculations, demonstrating clear signatures …