Digital Commons Network^™

"Distinct And Separate Issues": Examining Us Adults' Attitudes Toward Abortion During Covid-19, Maria Montenegro, Danny Valdez, Frederica Jackson, Wen-Juo Lo, Ronna C. Turner, Brandon L. Crawford, Kristen N. Jozkowski

Counseling, Leadership, and Research Methods Faculty Publications and Presentations

BackgroundThe COVID-19 pandemic reshaped people's healthcare experiences and access to healthcare, including abortion. In response to the COVID-19 outbreak, some policymakers claimed that abortion is a nonessential service and should be restricted. In contrast, other policymakers contended that abortion is time-sensitive essential healthcare, and access to it should be protected. These efforts put access to abortion into the public arena during the onset of the pandemic. We examined whether people perceived the pandemic changed their attitudes toward abortion and their rationale for whether their support for abortion increased, decreased, or remained the same.MethodWe administered a web-based survey to US-based English …

Explainable Neural Networks With Guarantees: A Sparse Estimation Approach, Antoine Ledent, Peng Liu

Research Collection School Of Computing and Information Systems

Balancing predictive power and interpretability has long been a challenging research area, particularly in powerful yet complex models like neural networks, where nonlinearity obstructs direct interpretation. This paper introduces a novel approach to constructing an explainable neural network that harmonizes predictiveness and explainability. Our model is designed as a linear combination of a sparse set of jointly learned features, each derived from a different trainable function applied to a single 1-dimensional input feature. Leveraging the ability to learn arbitrarily complex relationships, our neural network architecture enables automatic selection of a sparse set of important features, with the final prediction being …

Varium: Variational Autoencoder For Multi-Interest Representation With Inter-User Memory, Nhu Thuat Tran, Hady W. Lauw

Research Collection School Of Computing and Information Systems

Frameworks for discovering multiple user interest factors based on Variational AutoEncoder (VAE) has demonstrated competitive recommendation performance. However, as VAE only considers one user as input at a time, sharing across like-minded users may not be adequately facilitated. Moreover, interest sharing between users is not always available and thus, poses a challenge for VAE to explicitly model this information. To resolve this, we introduce an inter-user memory-based mechanism to unsupervisedly discover latent interest sharing between users under VAE framework. Concretely, we design a memory including an array of prototypes, each hypothetically representing a group of users sharing a particular interest. …

Multisfl: Towards Accurate Split Federated Learning Via Multi-Model Aggregation And Knowledge Replay, Zeke Xia, Ming Hu, Dengke Yan, Ruixuan Liu, Anran Li, Xiaofei Xie, Mingsong Chen

Research Collection School Of Computing and Information Systems

Although Split Federated Learning (SFL) effectively enables knowledge sharing among resource-constrained clients, it suffers from low training performance due to the neglect of data heterogeneity and catastrophic forgetting problems. To address these issues, we propose a novel SFL approach named MultiSFL, which adopts i) an effective multimodel aggregation mechanism to alleviate gradient divergence caused by heterogeneous data and ii) a novel knowledge replay strategy to deal with the catastrophic forgetting problem. MultiSFL adopts two servers (i.e., the fed server and main server) to maintain multiple branch models for local training and an aggregated master model for knowledge sharing among branch …

Lightprof: A Lightweight Reasoning Framework For Large Language Model On Knowledge Graph, Tu Ao, Yanhua Yu, Yuling Wang, Yang Deng, Zirui Guo, Liang Pang, Pinghui Wang, Tat-Seng Chua, Xiao Zhang, Zhen Cai

Research Collection School Of Computing and Information Systems

Large Language Models (LLMs) have impressive capabilities in text understanding and zero-shot reasoning. However, delays in knowledge updates may cause them to reason incorrectly or produce harmful results. Knowledge Graphs (KGs) provide rich and reliable contextual information for the reasoning process of LLMs by structurally organizing and connecting a wide range of entities and relations. Existing KG-based LLM reasoning methods only inject KGs’ knowledge into prompts in a textual form, ignoring its structural information. Moreover, they mostly rely on close-source models or open-source models with large parameters, which poses challenges to high resource consumption. To address this, we propose a …

Simulation-Free Hierarchical Latent Policy Planning For Proactive Dialogues, Tao He, Lizi Liao, Yixin Cao, Yuanxing Liu, Yiheng Sun, Zerui Chen, Ming Liu, Bing Qin

Research Collection School Of Computing and Information Systems

Recent advancements in proactive dialogues have garnered significant attention, particularly for more complex objectives (e.g. emotion support and persuasion). Unlike traditional task-oriented dialogues, proactive dialogues demand advanced policy planning and adaptability, requiring rich scenarios and comprehensive policy repositories to develop such systems. However, existing approaches tend to rely on Large Language Models (LLMs) for user simulation and online learning, leading to biases that diverge from realistic scenarios and result in suboptimal efficiency. Moreover, these methods depend on manually defined, context-independent, coarse-grained policies, which not only incur high expert costs but also raise concerns regarding their completeness. In our work, we …

Evaluating Software Development Agents: Patch Patterns, Code Quality, And Issue Complexity In Real-World Github Scenarios, Zhi Chen, Lingxiao Jiang

Research Collection School Of Computing and Information Systems

In recent years, AI-based software engineering has progressed from pre-trained models to advanced agentic workflows, with Software Development Agents representing the next major leap. These agents, capable of reasoning, planning, and interacting with external environments, offer promising solutions to complex software engineering tasks. However, while much research has evaluated code generated by large language models (LLMs), comprehensive studies on agent-generated patches, particularly in real-world settings, are lacking. This study addresses that gap by evaluating 4,892 patches from 10 top-ranked agents on 500 real-world GitHub issues from SWE-Bench Verified, focusing on their impact on code quality. Our analysis shows no single …

Learning To Identify Seen, Unseen And Unknown In The Open World: A Practical Setting For Zero-Shot Learning, Sethupathy Parameswaran, Yuan Fang, Chandan Gautam, Savitha Ramasamy, Xiaoli Li

Research Collection School Of Computing and Information Systems

As vision-language models advance, addressing the Zero-Shot Learning (ZSL) problem in the open world becomes increasingly crucial. Specifically, a robust model must handle three types of samples during inference: seen classes with visual and semantic information provided in training, unseen classes with only the semantic information in training, and unknown samples with no prior information from training. Existing methods either handle seen and unseen classes together (ZSL) or seen and unknown classes (known as Open-Set Recognition, OSR). However, none addresses the simultaneous handling of all three, which we term Open-Set Zero-Shot Learning (OZSL). To address this problem, we propose a …

Token Turing Machines Are Efficient Vision Models, Purvish Jajal, Nick Eliopoulos, Benjamin Shiue-Hal Chou, George K. Thiruvathukal, James C. Davis, Yung-Hsiang Lu

Computer Science: Faculty Publications and Other Works

We propose Vision Token Turing Machines (ViTTM), an efficient, low-latency, memory-augmented Vision Transformer (ViT). Our approach builds on Neural Turing Machines (NTM) and Token Turing Machines (TTM), which were applied to NLP and sequential visual understanding tasks. ViTTMs are designed for non-sequential computer vision tasks such as image classification and segmentation. Our model creates two sets of tokens: process tokens and memory tokens; process tokens pass through encoder blocks and read-write from memory tokens at each encoder block in the network, allowing them to store and retrieve information from memory. By ensuring that there are fewer process tokens, we are …

Study Of Knowledge, Attitude, And Practice Of Self-Medication In Riobamba, Ecuador Based On An Indeterminate Likert Scale, Lizbeth Geovanna Silva-Guayasamín, Zully Mayra Romero-Orellana, Lisbeth Josefina Reales-Chacón, Isaac Germán Pérez-Vargas, Sulema De La Caridad Hernández-Batista, Carlos Antonio Escobar-Suárez, María López-Pino, Josselyn Gabriela Bonilla-Ayala

Neutrosophic Sets and Systems

Self-medication (SM) is a significant public health problem in Riobamba, Ecuador, characterized by the use of drugs without a prescription. This practice carries risks such as inappropriate drug use and antimicrobial resistance. This study assesses the prevalence, associated factors, and attitudes towards SM in Riobamba. To do so, data were collected from 383 city residents, who also responded to a survey. To ensure the accuracy of the results, we asked respondents to answer some questions based on an Indeterminate Likert Scale. In this way, people can evaluate each of the different opinions, thus obtaining a more reliable result of the …

Hypersoft Semi-Connected Spaces, Florentin Smarandache, V. Inthumathi, M. Amsaveni

Neutrosophic Sets and Systems

Neutrosophic sets are an important field of topology that deals with inconsistent, indeterminate, and uncertain circumstances in real life. Hypersoft sets have grown in popularity due to their ability to represent data as a collection of trait-valued disjoint sets that combine various attributes. Motivated by this concept, we introduce a new hyper-approach known as hypersoft semi-separated, which employs hypersoft semi-open sets [HSO]. This article presents several local properties of HSO sets, such as hypersoft semi-neighborhoods of hypersoft points and hypersoft semi-first countable spaces. Additionally, definitions of hypersoft semi-connected [HSCO] spaces, hypersoft locally semi-connected [HLSCO] spaces, and associated properties are provided. …

Predicting Customer Satisfaction Based On Neutrosophic Sets: Applied On Mobile Food Ordering Application, Walaa Elsanabary, Nouran M. Radwan

Neutrosophic Sets and Systems

Customers’ satisfaction prediction is a vital process for all business organizations to draw new customers and maintain existing customers. One of the most efficient methods to predict customers' satisfaction is classifying customers' feedback. In the real world, customer’s feedback is ambiguous, confusing and inconsistent. This option can be stated in neutrosophic logic as indeterminacy membership, associated with truth and falsity membership. In this study, a classification model based on neutrosophic sets to handle the inconsistency of customer responses is presented. Also, significant factors that impact customers' satisfaction are defined. In order to show the procedures and the application of the …

A Multi-Criteria Decision-Making Approach With Hyper Soft Set To Teaching Quality Assessment In English Language And Literature, Yuhua He

Neutrosophic Sets and Systems

The training ground for professional English speakers is the English departments of colleges and universities. Economic development and international interactions are impacted by the quality of their instruction. This study created an evaluation method with for evaluating the quality of English language and literature using questionnaire surveys, interviews, and a review of the literature. The multi-criteria decision making (MCDM) method is used in this study to evaluate the English langue and literature. Neutrosophic set is integrated with the MCDM method to deal with uncertainty and value information. This study uses the CRITIC method to compute the criteria weights. The CRITIC …

Neutrosophic Non-Newtonian And Geometric Measures: A Consistent Analytical Framework, Amer Darweesh, Kamel Al-Khaled, Mohammed Shakhatreh, Mahmood Shareef Ajeel, Nermin Abo Hasan

Neutrosophic Sets and Systems

The neutrosophic measure is a generalization of the classical measure in situations when the space contains some indeterminacy. In this paper, we introduce the concept of the Neutrosophic Geometric Measure, we also provide some results, and examples related to the Neutrosophic Geometric Measure. A classical measure of the objects determinate component, a classical measure of its indeterminate part, and a further classical measure of the objects opposite determinate part are the three classical measures that make up the neutrosophic measure. To de ne the Neutrosophic Geometric Measure, we introduce a new measure on R+ and call it the geometric Lebesgue …

University Mathematics Classroom Teaching Quality Assessment Based On Core Competencies Using The Dematel Approach And Single-Valued Neutrosophic Hypersoft Sets, Jingjing Qiao

Neutrosophic Sets and Systems

This study proposes a multi-criteria decision-making (MCDM) approach to evaluate the quality of University Mathematics Classroom Teaching based on core competencies. The MCDM approach is applied within the framework of the neutrosophic set to address vague and uncertain data. Unlike the hypersoft set, which handles multiple disjoint attribute-valued sets corresponding to various characteristics, the soft set operates with a single set of attributes. This study introduces the concept of Single-Valued Neutrosophic Hypersoft Expert Sets (SVNS), which integrate single-valued neutrosophic sets and hypersoft expert sets. Eight criteria were employed to construct the pairwise comparison matrix. The Decision-Making Trial and Evaluation Laboratory …

Intuitionistic Quadri-Partitioned Neutrosophic Sets With Extended Operators, Sai Anu P, Arulselvam A, Bobin A

Neutrosophic Sets and Systems

We present the concept of intuitionistic quadri-partitioned neutrosophic sets (IQ-PNSs) and extend it to intuitionistic quadri-partitioned neutrosophic soft sets (IQ-PNSSs). These sets introduce a constraint where the combined membership values for truth and falsity must not exceed one, while the indeterminacy and contradiction membership values are restricted to the interval [01], ensuring the total sum of all membership values remains below three. In addition, we de ne necessity and possibility operators, along with two novel operators, ( and ), on IQ-PNSSs and explore their properties. Furthermore, we introduce and analyze the operators , , and , as well as the …

Neutrosophic Analysis Of The Cultural Impact Of The Pinkullo In Llata: Integrating Chatgpt And Fsqca, Fredy Romulo Marcellini Morales, Betty Leon Trujillo, Esio Ocana Igarza, Roberto Carlos Cardenas Viviano

Neutrosophic Sets and Systems

This study explores the cultural impact of the Pinkullo, a traditional Andean aerophone, on the community of Llata, Peru, through an innovative approach that integrates neutrosophic set theory with computational methods. By employing fuzzy-set Qualitative Comparative Analysis (fsQCA) and a novel application of ChatGPT for neutrosophic sentiment analysis, the research investigates the complex interplay between the Pinkullo and various aspects of community life, including cultural participation, social impact, and cultural preservation. Textual data collected from surveys was analyzed using the "ChatGPT Constructor" add-on in Orange Data Mining to generate neutrosophic scores, representing the truth, indeterminacy, and falsity of expressed sentiments …

Non-Destructive Detection Of Fillet Fish Quality Using Mq135 Gas Sensor And Neutrosophic Logic-Enhanced System, M. Y. Shams, M. R. Darwesh, Roheet Bhatnagar, N. S. A. Al-Sattary, A. A. Salama, M. S. Ghoname

Neutrosophic Sets and Systems

This paper demonstrates the feasibility of using an electronic nose to assess fish quality by analyzing air quality and examining volatile organic compounds (VOCs) alongside physical variables, with pH, protein content, and VOCs serving as chemical reference points. Artificial intelligence algorithms were employed to predict quality and calculate regression coefficients. Using the reference neural network algorithm based on chemical and physical compounds, regression coefficients (R values) achieved were 0.99, 0.98, and 0.97, respectively. Additionally, ANFIS (Adaptive Neuro-Fuzzy Inference System) produced R values of 0.99, 0.85, and 0.98. Both fuzzy logic and ANFIS proved effective for predicting fish quality. Image processing …

Quality Evaluation In Hospital Operations Management Using Multi-Criteria Decision-Making With Plithogenic Approach To Address Uncertainty And Enhance Decision-Making Processes, Meng Zhang, Yafang Li

Neutrosophic Sets and Systems

Coordination of medical facilities' operations depends on operations management. Hospitals must function effectively to meet the medical demands of their patients, who get critical and emergency treatment. The decision support system for Quality Evaluation in Hospital Operations Management is created in this study. Plithogenic sets and multicriteria decision-making (MCDM) form the foundation of this decision assistance system. The study presents a novel approach to evaluating and rating Hospital Operations Management. Alternatives are ranked using the plithogenic reference-based normalization alternative ranking (RBNAR) technique. Thus, the algorithm for plithogenic-RBNAR is constructed and presented. An analysis of Hospital Operations Management is conducted using …

Ecological Efficiency Evaluation In Petrochemical Enterprises Using Plithogenic-Artasi Model, Hailing Chen, Dingqun Zhang

Neutrosophic Sets and Systems

The application of the ecological carrying capacity theory to the assessment of petrochemical companies' eco-efficiency is the main goal of this article. This study deviates from previous research that examines company eco-efficiency from a strategic and behavioral incentive standpoint. This study uses the multiple-criteria decision-making (MCDM) approach, considering both qualitative and quantitative factors. Plithogenic sets are used to compute expert importance levels in a decision support system for choosing Petrochemical Enterprises. The suggested plithogenic-based alternative ranking methodology based on adaptive standardized intervals (ARTASI) method is used to determine the ranking of Petrochemical Enterprises. The plithogenic-ARTASI model is a combination of …

Conjugation Of Hypersoft Set And Triangular Neutrosophic To Evaluate Cognitive Digital Twins' Contribution To Smart Manufacturing, Mona Mohamed, Nurhan Alaa

Neutrosophic Sets and Systems

The latest innovation in digital twin technology is called Cognitive Digital Twins (CDT). The sophisticated and autonomous activities made possible by this technology have the potential to revolutionize manufacturing. An overview of CDT in manufacturing is given in this paper, along with an examination of their main features, components, and possible uses. CDT can learn from data, reason about difficult circumstances, and make well-informed judgments by combining artificial intelligence, machine learning, and knowledge representation approaches. The advantages of CDT in smart manufacturing are covered in the paper. Hence, the objective of this paper is evaluating the smart manufacturing that adopts …

Stock Price Predictions With Lstm-Arima Hybrid Model Under Neutrosophic Treesoft Sets With Mcdm Interaction, G. Dhanalakshmi, Dr. S. Sandhiya, Florentin Smarandache

Neutrosophic Sets and Systems

The stock market is regarded as volatile, complex, tumultuous, and dynamic. Forecasting stock performance has proven to be a challenging endeavour due to its increasing need for investment and growth prospects. At the forefront of machine learning, deep learning models facilitate the straightforward and efficient exploration and identification of optimal stocks, the hybrid forecasting models (LSTM and ARIMA) are used in the prediction of stock increase. This paper incorporated the MCDM technique to determine the optimal stocks for investment. The Analytic Hierarchy Process (AHP) is used to assign weights to various financial factors. These weights are then used by the …

A Neutrosophic Perspective On Enhancing Quality Virtual Simulation Experimental Education Of Integrated Circuits: A New Approach, Lihua Dai, Ben Wang, Xuemin Cheng, Junyi Xu, Hao Wang

Neutrosophic Sets and Systems

With rapid advancements in technology-related industries, integrated circuits come to be the core of modern electronics (IC). This in turn highlights the indispensable need to figure out advanced techniques for delivering high-quality experimental education in integrated circuits (IC). To that end, this work presents a neutrosophic framework to enhance the quality of education based on the selection of simulation-based tools that best improve the experimental skills of students. Given the inherent challenges of uncertainty, ambiguity, and subjectivity of virtual simulation, we propose to incorporate Interval-Valued Neutrosophic Sets (IVNS) to model uncertainty inherent to virtual simulation scenarios and adapt to encode …

Mapping Barriers To Sustainable Fashion Consumption: Insights From Neutrosophic-Z Number And Delphi-Dematel Integration, Phi-Hung Nguyen, Lan-Anh Thi Nguyen, The-Vu Pham, Tra-Giang Vu, Duc-Minh Vu, Thu-Hoai Thi Nguyen, Hong-Quan Le, Huong-Giang Hoang Le

Neutrosophic Sets and Systems

This study investigates the barriers to sustainable consumption within the Vietnamese fashion industry, a critical issue given the sector’s significant environmental impact and growing consumer awareness. The research employs an innovative combination of Neutrosophic Z-number sets (NZN), Delphi, and Decision-Making Trial and Evaluation Laboratory (DEMATEL) methodologies to systematically identify and analyze 47 barriers across five key dimensions: Social and Cultural Factors, Pricing and Affordability, Policy and Education, Perception and Image, and Supply Chain and Industry Practices. Through expert evaluations and causal analysis, the study reveals that Policy and Education are the most influential factors, highlighting the need for robust policy …

Neutrosophic Sets And Systems, Vol. 80,2025, Florentin Smarandache, Mohamed Abdel-Basset, Maikel. Leyva Vazquez

Neutrosophic Sets and Systems

No abstract provided.

Speech-In-Noise Testing For Adults, Cecilia Talarico

Doctoral Scholarly Projects & Capstones

Speech perception is defined as a process “between the reception of the acoustic signal at the eardrum and any conscious introspection about the quality of the percept it evokes or the mnemonic, affective, or semantic associates it arouses.” (Phillips, 1998). Several factors can affect an individual’s perception of speech: the type of speech, type of noise, binaural versus monaural listening, age, male or female speaker, listener or speaker of a non-native language, cognition, central nervous system neuroanatomical differences, and hearing loss. While just a single one of these factors in isolation can create adverse conditions to perceive speech, it is …

Examining The Dangers Of The Digital Age, A Book Review Of Online Child Sexual Grooming Discourse, Olivia L. Villeneuve

Dignity: A Journal of Analysis of Exploitation and Violence

No abstract provided.

Integrated Mental Health Care In Specialty Clinics For Children With A Diagnosis Of Asthma Or Diabetes: A Mixed Methods Study, Joan P. Totka, Maria Peña, Joshua A. Steinberg, Peter M. Wolfgram

College of Nursing Faculty Research and Publications

Introduction

Using patient-reported outcome measures (PROM) in a shared-space mental health-integrated specialty clinic, we explored the feasibility, acceptance, and experience of youth with asthma and diabetes, their families, and the healthcare team.

Method

Using mixed methods, we examined feasibility, acceptability, and experience of PROM inclusion in caring for youth with asthma (n = 7) and diabetes (n = 11), their families (n = 18), and healthcare providers (n= 13). Completion and receipt of PROM (feasibility), postvisit surveys (acceptance), and structured interviews (experience) between June 2019 and February 2020.

Results

Targeted PROM met feasibility goals (80%) …

Why Jack Daniel's Can't Stop #Westelmcaleb, And What Now?, Irina D. Manta, Kavita D. Balchand

William & Mary Bill of Rights Journal

This Article proceeds in four Parts. Part I provides a basic overview of trademark law and brand protection. It explains the key components of the Lanham Act, the central federal legislation in this area—including the two federal causes of action, trademark infringement and trademark dilution—and explores the law’s role in brand protection. Next, Part II discusses the area of social media and brand promotion. It begins with examining the rise of social media and the emergence of hashtags, in addition to trademarks used within hashtags and the registration of hashtags by the United States Patent Trademark Office (USPTO) as well …

Ukrainian Internally Displaced Persons And Their Journey Of Christian Hope, Pamela A. Tuason

Loyola Papers

This paper examines eighteen narratives of Ukrainian internally displaced persons (IDPs) during the ongoing war and interprets them through the lens of Christian hope as articulated by Jürgen Moltmann. Using Paul Ricoeur’s threefold mimetic theory—prefiguration, configuration, and refiguration—the study analyzes how personal stories reveal theological meanings embedded in experiences of suffering, trauma, and displacement. The narratives highlight the role of history in displacement, the capacity of traumatized persons to reinterpret suffering through hope, and the longing to regain home. The study also proposes a model for the theological study of migrant narratives, contributing to migration theology and to discussions on …