Digital Commons Network^™

One Size Doesn’T Fit All: Towards Design And Evaluation Of Developmentally Appropriate Parental Control Tool, Prakriti Dumaru, Mahdi Nasrullah Al-Ameen

Computer Science Student Research

As children progress through developmental stages, they undergo substantial biological, cognitive, and social changes, creating unique needs for online safety across different age groups (e.g., young children, tweens, teens). The existing parental control tools fail to account for these differences, leaving a notable gap in the literature on parental mediation. To this end, we conducted 10 focus group sessions with a total of 20 parents to understand their preferences for age-appropriate design components that promote self-regulation and open communication, followed by an ideation workshop with four UX design experts to translate these preferences into customized features. We then evaluated these …

Exploring The Impacts Of An Adaptive Haptic Heartbeat Within A Socially Assistive Robot, Jade Thompson

Honors Theses

This research investigates the therapeutic effects of an adaptive haptic heartbeat within Therabot, a stuffed robotic dog. A simulated haptic heartbeat that adjusts its own speed based on user heart rate was developed for integration within Therabot. A user study evaluated the effects of various heartbeat behaviors on user experiences with Therabot, with respect to improvements in self-reported state anxiety, physiological improvements, and perceptions of the robot. A relationship was found between improvements in self-reported state anxiety and positive opinions of Therabot, regardless of condition. Additionally, differences were found between conditions with respect to improved aspects of state anxiety, with …

Autonomous Intelligence In Fashion: A Comprehensive Analysis Of Agentic Ai Across The Fashion Ecosystem, Andrew Burnstine

Faculty and Staff Publications & Presentations

The fashion industry is undergoing a paradigm shift with the emergence of agentic artificial intelligence (AI), a sophisticated class of intelligent systems exhibiting autonomous decision-making, continuous learning, and adaptive action with minimal human intervention. Moving beyond traditional AI applications in fashion focused on predictive analytics, generative tools, and supervised automation, agentic AI introduces a transformative paradigm wherein intelligent agents proactively navigate the complexities inherent in design, manufacturing, supply chain optimization, and consumer personalization. This paper presents a comprehensive exploration of the evolving role of agentic AI across the multifaceted fashion ecosystem, offering an in-depth analysis of its technological underpinnings, operational …

Trends And Transport Of Tropospheric Ozone From New York City To Connecticut In The Summer Of 2023, Michele Iraci

Honors Scholar Theses

Tropospheric Ozone, or O3, is a criteria pollutant contributing to most of Connecticut and New York City’s poor air quality days. It has adverse effects on human health, particularly for high-risk individuals. Ozone is produced by nitrogen oxides and volatile organic compounds from fuel combustion reacting with sunlight. The Ozone Transport Region (OTR) is a collection of states in the Northeast and Mid-Atlantic United States that experience cross-state pollution of O3. Connecticut has multiple days a year where O3 values exceed the National Ambient Air Quality Standards, requiring additional monitoring and standards because it falls in the OTR— partially due …

The Oaks Vs. Other University Dining Facilities: Does Architecture Affect Food Waste?, Sydney Bezich

Honors Projects

The purpose of this study was to find a connection between food waste and architecture and determine how food waste can be mitigated using architectural solutions and methods. Food waste is an important issue worldwide and is present in university dining facilities. This study focuses on university dining facilities’ preventable food waste at both the pre-consumer and post-consumer levels. Architecture, in this project, is defined as all aspects of the built environment. This includes, but is not limited to, design and layout, materials, systems, building operations, marketing displays, and sustainability. Methods for this study included researching sustainability, architecture, and food …

Mine Closure Planning Must Face The Challenge Of Delivering Nature Positive Outcomes, Luis E. Sanchez, Angus Morrison-Saunders

Research outputs 2022 to 2026

The need to address and reverse global biodiversity decline is imperative across all of society including the practices of mine closure planning. Nature Positive is the latest global biodiversity-focused initiative which calls for at least 30% of biodiversity to be enhanced through effective restoration relative to the 2020 baseline. This paper conceptualizes and explains what is necessary in mine closure planning and implementation to meaningfully contribute to this and other nature-positive goals, with some illustrative examples. Issues considered include application of the mitigation hierarchy, rehabilitation in mining and the time lag challenge for restoring biodiversity, biodiversity offsetting, conserving nature while …

A Hybrid Deep Learning-Based Approach For Visual Field Test Forecasting, Ashkan Abbasi, Sowjanya Gowrisankaran, Wei-Chun Lin, Xubo Song, Bhavna Josephine Antony, Gadi Wollstein, Joel Schuman, Hiroshi Ishikawa

Wills Eye Hospital Papers

OBJECTIVE: Longitudinal assessment of visual field (VF) testing is essential in glaucoma management. Conventional VF forecasting methods require numerous prior tests, while deep learning techniques have shown promising results with fewer tests. This study introduces a hybrid deep learning framework to enhance flexibility and accuracy in VF test forecasting.

DESIGN: A retrospective longitudinal study using deep learning-based VF forecasting models.

SUBJECTS AND CONTROLS: A total of 1750 subjects (healthy and glaucoma patients) with 19 437 Humphrey VF (24-2 Swedish Interactive Threshold Algorithm) tests collected from longitudinal glaucoma cohorts at the University of Pittsburgh and New York University.

METHODS: Three deep …

Basketball Jump Shot Correction Using Computer Vision, Matthew Moran

Mathematics & Computer Science Student Scholarship

Matthew Moran ’25, Computer Science major

Faculty mentor: Dr. Martin Hellwig, Mathematics and Computer Science

Basketball has evolved significantly over the years, with players continuously striving to improve their shooting accuracy and efficiency. As the game becomes more data-driven, advancements in artificial intelligence and computer vision have provided new methods for analyzing and correcting shooting mechanics that allow players to improve their game. Using deep learning, this research aims to fill a gap in these advancements, which is looking at the position of the shooters fingers relative to the ball. Doing so can improve stability and overall shooting performance.

Diversity And Habitat Use Of Bats In Modified Suburban Landscapes, Brittany Morgera

Biology Presentations

Bats occupy critical ecological niches and perform important ecosystem services like controlling insect populations. However, humans have altered bat habitat substantially, resulting in the reduction of bat populations. The goals of this research are to assess bat diversity and habitat use across different levels of suburban habitat modification. To accomplish this, we deployed passive acoustic recorders at twelve locations with varying human impact in Montgomery County, Pennsylvania. In accordance with The North American Bat Monitoring Program’s standards, acoustic analysis software was used to identify bat species. Manual identification methods from The Canadian Wildlife Health Cooperative were used to verify these …

A Comparison And Investigation Of 2d Axisymmetric And 3d Models For The Wave Augmented Varicose Explosions Atomizer, Caleb Miller

Senior Honors Theses

Atomization of non-Newtonian, high-viscosity fluids is a challenging task with many applications. One method of atomizing these types of flows is the Wave Augmented Varicose Explosions (WAVE) atomizer. Using this framework, the study establishes an analysis methodology, investigates the relationship between 2D axisymmetric (2DA) and 3D models, and provides analysis of geometric, non-geometric, and non-dimensional parameter influences on the atomizer characterization in 2DA models. The study found that 2DA models can provide viable predictions of certain 3D model characteristics, established several mathematical models for parameter relationships among 2DA models, and identified certain metrics as inadequate predictors of atomizer characteristics in …

Inhibition Of Mif With An Allosteric Inhibitor Triggers Cell Cycle Arrest In Acute Myeloid Leukemia, Georgios Pantouris, Leepakshi Khurana, Pathricia Tilstam, Alison Benner, Thomas Yoonsang Cho, Martin Lelaidier, Mathieu Perrée, Zoe Rosenbaum, Lin Leng, Francine Foss, Vineet Bhandari, Amit Verma, Richard Bucala, Elias J. Lolis

Pacific Faculty Work

Macrophage migration inhibitory factor (MIF) is a key modulator of innate and adaptive immunity that has been extensively reported to promote tumor cell survival, proliferation, and metastasis. A recent study focusing on the microenvironment of acute myeloid leukemia (AML) showed that pharmacological inhibition of MIF signaling, in vitro as well as in vivo, reduces AML cell survival. Such data highlights the crucial role of MIF in AML pathogenesis and support the efforts for developing selective MIF modulators. Here, we report the identification and crystallographic characterization of a MIF inhibitor (compound 1) with an allosteric binding motif. Single point screening of …

Inquiry-Style Planetarium Activities, Emma Rasmussen Groberg

Theses and Dissertations

Introductory astronomy students often face challenges in exploring their own ideas and investigating astronomical phenomena due to the limitations of nighttime observation and weather conditions. Planetariums overcome these barriers by simulating the night sky, making it accessible during class sessions regardless of external conditions. This provides an opportunity to engage students in inquiry-based activities, where they are presented with a scenario and encouraged to use their own reasoning to reach conclusions. In this study, we implemented inquiry-based activities in PHSCS 127 using the planetarium as an investigative tool. We developed four activities designed to help students explore their ideas and …

Ontologies For Smart Agriculture: A Path Toward Explainable Ai-A Systematic Literature Review, Rima Grati, Najla Fattouch, Khouloud Boukadi

All Works

Smart agriculture has grown significantly over the last few years, particularly with the integration of advanced technologies (e.g., the Internet of Things, robots, artificial intelligence, etc.), leading to the development of intelligent agricultural systems. However, these systems often lack data integration, interoperability, and semantic explainability. Various approaches have been proposed to address these challenges. This study provides a comprehensive literature review that addresses, on the one hand, the use of semantic resources (e.g., semantic web technologies and ontologies) to tackle data integration and interoperability in smart agriculture systems and, on the other hand, the integration of explainable artificial intelligence into …

An Approach To Model Uncertainty In Fluid Behaviour With Navier-Stokes Equations In Neutrosophic Environment, Muhammad Saeed, Attia Hameed, Neha Andaleeb Khalid, Muhammad Salman Habib

Neutrosophic Systems with Applications

The complex discipline of fluid dynamics examines the behavior of fluids and their interactions with adjacent objects. The Navier-Stokes equations are very important for explaining how fluids move, but they are not linear and often give answers that depend on the starting point and the boundaries. Modeling fluid behavior is challenging due to the inherently chaotic and unpredictable character of fluid dynamics. To deal with unknown or uncertain values in this research, we used neutrosophic logic to look at the Navier-Stokes equations in a new way. Neosophic logic permits the existence of values that are partially true and partially false; …

Revisiting Bipolar Neutrosophic Graph And Interval-Valued Neutrosophic Graph, Takaaki Fujita

Neutrosophic Systems with Applications

Graph theory explores networks composed of nodes (vertices) and their connections (edges). A graph class is a collection of graphs that share common structural properties, defined by specific rules or constraints. This paper examines various models of uncertain graphs, including Fuzzy, Intuitionistic Fuzzy , Neutrosophic, Turiyam Neutrosophic, and Plithogenic Graphs. In particular, this study focuses on Bipolar Graphs and Interval-valued Graphs, analyzing them within the frameworks of Fuzzy, Neutrosophic, Turiyam Neutrosophic, and Plithogenic Graphs.

Contact Graphs In Fuzzy And Neutrosophic Graphs, Takaaki Fujita

Neutrosophic Systems with Applications

Graph Theory is a branch of mathematics dedicated to studying graphs, which depict relationships between objects through vertices and edges. A significant focus in this field is the study of contact graphs, where vertices correspond to sets, and edges represent intersections between those sets. To better model uncertainties in real-world situations, several graph types---such as fuzzy, neutrosophic, and Plithogenic graphs---have been developed. This paper investigates the concept of contact graphs within these frameworks, offering insights into their behavior under various uncertain conditions.

Expanding The Horizons Of Nonagonal Neutrosophic Numbers As A Versatile Framework For Decision-Making And Scientific Applications In Covid-19, Muhammad Naveed Jafar, Kainat Muniba, Hamiden Abd El-Wahed Khalifa, Fahd Jarad

Neutrosophic Systems with Applications

In this article, the concept of nonagonal neutrosophic numbers has been introducing in the disjunctive frame of reference. We also proposed the dependency and independency of membership function in regards to nonagonal neutrosophic number. We also introduce a new score function and its computation also formulated in a distinct rational viewpoint. We developed the concept of weighted arithmetic averaging operator and weighted geometric averaging operator for nonagonal neutrosophic numbers. It will open new doors for MCDM and develop the concept with new approaches. Additionally, we analyze the effect of COVID-19 for different ages.

Assessing The Sustainable Blockchain-Metaverse-Iot Platform In The Healthcare Industry: An Intelligent Decision Support Model, Ibrahim M. Hezam, Ahmed M. Ali, Ibrahim A. Hameed, Karam Sallam, Mohamed Abdel-Basset

Neutrosophic Systems with Applications

Healthcare services must fulfill patients' desires for secure data sharing and high accessibility. Blockchain technology, through blockchain platforms (BPs), can overcome healthcare challenges. This study develops a decision-making methodology for selecting the best BP, by integrating blockchain with IoT and Metaverse, the proposed approach ensures data integrity, quality, privacy and security, secure data sharing, and interoperability. The decision-making methodology uses the multi-criteria decision-making (MCDM) methodology to handle conflicting criteria. Two MCDM methods are used in this study: CRiteria Importance Through Intercriteria Correlation (CRITIC) for weight computation, and Ranking of Alternatives with Weights of Criterion (RAWEC) for alternative ranking. To deal …

Appraisal Of Uncertainty-Driven Financial Performance: Bringing Multi-Criteria Decision Making Techniques With Neutrosophic Theory, Mona Mohamed, Nurhan Alaa, Eman Sayed

Neutrosophic Systems with Applications

Evaluating financial performance is essential yet challenging due to various factors, including ambiguity, insufficient information, and conflicting evaluation criteria. Conventional Multi-Criteria Decision-Making (MCDM) techniques often struggle to manage these complexities effectively. To address these limitations and enhance financial performance assessments, this research proposes an innovative approach integrating Single-Valued Neutrosophic Sets (SVNS) with established MCDM methodologies. SVNS uniquely manages uncertainty by concurrently quantifying degrees of truth, indeterminacy, and falsity within financial data. This research specifically employs entropy-based weighting methods integrated with Additive Ratio Assessment (ARAS) and Multi-Objective Optimization by Ratio Analysis (MOORA) methodologies in the SVNS environment to systematically rank enterprises …

Leveraging Hypersoft Set To Optimize Livestock In The Era Of Unmanned Aerial Vehicles, Alaa Salem, Mona Mohamed, Nebojsa Bacanin, Mohamed Abouhawwash

Neutrosophic Systems with Applications

Due to urbanization and industrialization, rapid global change and the potential loss of arable land, agricultural output must rise in production levels and harvest, distribute, and use resources more efficiently. It is believed that using technology on livestock would help meet the expanding population's demand for food. Internet of Things (IoT) and Unmanned Aerial Vehicle (UAV) integration in conventional farming has transformed operations, providing farmers with greater productivity, improved decision-making, and sustainability. We assume that there are enough UAVs to cover the entire pasture, and our goal is to identify the best UAVs. Accordingly, determining the best type of UAVs …

A Novel Neutrosophic Decision-Making Approach For Optimizing Metaverse Headphone Design: Balancing Technical Performance And User Emotional Needs, Mai Mohamed, Amira Salam, Karam Sallam, Bilal Arain

Neutrosophic Systems with Applications

The concept of the metaverse, which combines various technologies to create a wide range of virtual experiences, has gained significant popularity in recent years. To fully engage in these metaverse environments, users rely on access devices such as virtual reality (VR) headsets and smartphones for augmented reality (AR). These devices must be lightweight, compact, and user-friendly to ensure comfort and enhance customer satisfaction. There is a growing focus on innovating and designing products that not only meet technical requirements but also address the emotional needs of users, ultimately improving the overall experience. Selecting the ideal design for Metaverse headphones is …

A Comprehensive Intelligent Traffic Monitoring System Based On A Novel Integration Of Neutrosophic Multi-Criteria Decision-Making Techniques, Mai Mohamed, Amira Salam, Rana Muhammad Zulqarnain, Muhammad Gulistan

Neutrosophic Systems with Applications

With the spread of road accidents and traffic congestion that costs countries and governments a lot of money in addition to the loss of human lives, and since traditional methods of monitoring traffic have not been as effective as desired, attention has been drawn to the search for more effective solutions to the problem of monitoring and regulating traffic. With the spread of technology and the Internet of Things, UAVs have emerged as a promising tool for monitoring traffic, as they can fly for a sufficient period and operate in difficult climatic conditions, in addition to their ability to monitor …

Nash Equilibrium Solutions For Continuous Static Games Under Neutrosophic Environment, M. G. Brikaa

Neutrosophic Systems with Applications

Neutrosophic set theory plays an important role in dealing with the impreciseness and inconsistency in data encountered in solving real life problems. This paper presents a novel approach to solving a new class of continuous static games within a neutrosophic framework. In the proposed methodology, the neutrosophic continuous static games are redefined into two separate crisp problems: the lower problem and the upper problem. The study further establishes the necessary conditions for determining equilibrium strategies in neutrosophic continuous static games. To demonstrate its effectiveness and practical applicability, the proposed method is validated through a numerical example.

Building Climate Resilience Through Food Recovery, San Diego Regional Climate Collaborative, Alexander Pourfard, Aranza Ruvalcaba

San Diego Regional Climate Collaborative

In an effort to combat GHG emissions from food waste, California passed Senate Bill 1383 (SB 1383) into law in 2016. The bill contains key provisions aimed at increasing edible food recovery. By rescuing food that would otherwise go to the landfill, California entities have been able to help save precious food and advance sustainable solutions to address climate change in their local communities. Since the food recovery requirements took effect in January of 2022, over 217,000 tons of unsold food have been recovered annually, providing more than 700 million meals to food-insecure Californians.

Synthesis Of Novel Five-Membered Heterocycles As Bioactive Agents, Subrata Roy

Student Theses and Dissertations

This dissertation outlines the synthesis of various types of heterocyclic small molecules across three chapters. The first chapter discusses the efficient synthesis of seventy-one fluorinated pyrazole molecules and thirty-five 3,4-dihydroxy and 4-hydroxy phenyl-substituted thiazole molecules. These molecules were designed and synthesized for their potential antibacterial properties. The second chapter discusses the synthesis of fused thiazole molecules with enone-based steroidal natural products. This chapter reports on sixty-five novel fused thiazole molecules distributed across three libraries featuring different steroidal natural products: ethisterone, bisnoralcohol, and diosgenin. These molecules were designed and synthesized as potential anticancer agents. The third chapter comprises the development of …

Technology Anxiety In Virtual Reality Adoption: Examining The Impact Of Age, Past Experience, And Cybersickness, Eman Al Khalifah, Ramy Hammady, Mahmoud Abdelrahman, Ons Al-Shamaileh, Mostafa Marghany, Hatana El-Jarn, Alyaa Darwish, Yusuf Kurt

All Works

This study examines the role of Technology Anxiety (TA), age, past use, and cybersickness in the adoption of Virtual Reality (VR) technology. Using an extended Technology Acceptance Model (TAM), the research integrates age and past use as antecedents of TA and evaluates their influence on perceived ease of use (PEoU), perceived enjoyment (PENJ), and user attitudes. Data from 206 participants were analyzed using Partial Least Squares Structural Equation Modelling (PLS-SEM) following a VR pilgrimage experience. The findings challenge conventional assumptions, revealing that past VR use increased TA, contradicting prior studies that associate familiarity with reduced anxiety. Additionally, older users exhibited …

From Food To Fashion: Bio-Based Textiles Advancing Sustainability And Socioeconomic Growth In Emerging Markets, Andrew Burnstine

Faculty and Staff Publications & Presentations

The global fashion industry is undergoing a profound shift towards sustainability, driven by innovations in bio-based textiles derived from agricultural byproducts such as cactus, pineapple, banana, coconut, fungi, and bacterial cultures. This article comprehensively explores the technological advancements, industry adoption trends, socioeconomic impact on emerging markets, and barriers to widespread adoption of bio-based textiles. The alignment of these innovations with global sustainability initiatives, key industry collaborations, and policy interventions are also examined.

Application For Prediction Of Heart Failure; The Next Step In Machine Learning For Healthcare, Amy Adyanthaya, Dawn Bowerman, Rachel Liercke, Robert Slater

SMU Data Science Review

Heart failure (HF) is a serious medical condition affecting approximately 6.7 million U.S. adults and is expected to impact 8.5 million Americans by 2030 [1]. Heart failure is a complicated clinical ailment and characterizes the final course of numerous heart diseases [2]. This paper introduces a machine-learning-based application that utilizes Support Vector Machine (SVM), Multi-Layer Perceptron (MLP), and XGBoost models, implemented through the Python Flask framework, to predict HF risk using clinical data. The results indicate high model performance, with precision and recall metrics underscoring the application’s reliability in identifying at-risk patients. By providing real-time, accessible insights, this tool aims …

Enhancing Animal Shelter Operations With Time Series And Machine Learning, Sakava L. Kiv, Donald L. Anderson, Shivam Negi, Jacquelyn Cheun

SMU Data Science Review

Enhancing animal shelter operations through machine learning involves employing a variety of advanced techniques aimed at increasing efficiency, promoting animal welfare, and optimizing resource allocation. This paper explores predictive analytics for adoption rates using regression models to estimate the likelihood of adoption based on historical data, encompassing variables such as breed, health status, and previous adoption trends. Additionally, classification algorithms are utilized to categorize animals by adoption probability, facilitating better resources and marketing prioritization. Clustering algorithms are employed to group animals according to behavior patterns and/or physical health, enabling tailored medical care and enrichment activities that improve their mental and …

Seg-Swin: A Dual-Attention Transformer Model For Advanced Amd Classification And Lesion Detection Using Color Fundus Imaging, Niveen Nasr El-Den, Mohamed Elsharkawy, Ibrahim Saleh, Ali H. Mahmoud, Mohammed Ghazal, Ashraf Khalil, Ashraf Sewelam, Hani Mahdi, Ayman El-Baz

All Works

Age-related macular degeneration (AMD) is a prevalent retinal disorder in the elderly, often leading to significant vision impairment. The diagnosis of AMD is confirmed through various medical imaging modalities, with color fundus photography (CFP) being a primary tool. The detection and staging of AMD-severity depend on several factors, including the number and size of drusen, the presence of pigmentary changes, geographic atrophy, and neovascularization, all of which are identifiable through CFP. In this study, we introduce an innovative dual-vision transformer-based network designed to automatically detect AMD and classify its severity into either dry AMD or wet AMD using CFP. Early …