Digital Commons Network^™

Stimulating Environmental And Health Protection Through Utilizing Statistical Methods For Climate Resilience And Policy Integration, Sanaa Kaddoura, Rafiq Hijazi, Nadia Dahmani, Reem Nassar

All Works

Climate change, a critical global challenge, is evident in rising global temperatures, shifting precipitation trends, and extreme weather events, including floods, heatwaves, and rising sea levels. The impacts of climate change not only endanger physical health but also affect mental well-being, particularly among populations experiencing frequent or severe climate-related events. Understanding individual perceptions of climate risks and adaptive capacities is crucial for developing strategies that promote health resilience and environmental protection. This paper examines how risk perceptions, direct experiences with extreme weather, and perceived adaptive capacities influence climate change protection measures and support for relevant policies. Data were gathered from …

Pathways To Chronic Disease Detection And Prediction: Mapping The Potential Of Machine Learning To The Pathophysiological Processes While Navigating Ethical Challenges, Ebenezer Afrifa-Yamoah, Eric Adua, Emmanuel Peprah-Yamoah, Enoch O. Anto, Victor Opoku-Yamoah, Emmanuel Acheampong, Michael J. Macartney, Rashid Hashmi

Research outputs 2022 to 2026

Chronic diseases such as heart disease, cancer, and diabetes are leading drivers of mortality worldwide, underscoring the need for improved efforts around early detection and prediction. The pathophysiology and management of chronic diseases have benefitted from emerging fields in molecular biology like genomics, transcriptomics, proteomics, glycomics, and lipidomics. The complex biomarker and mechanistic data from these “omics” studies present analytical and interpretive challenges, especially for traditional statistical methods. Machine learning (ML) techniques offer considerable promise in unlocking new pathways for data-driven chronic disease risk assessment and prognosis. This review provides a comprehensive overview of state-of-the-art applications of ML algorithms for …

Prevalence Of Low Back Pain Among Office Workers During The Covid-19 Pandemic In Various Countries: A Systematic Review, Yosephine Roma Intan, Ririn Arminsih Wulandari, Popy Yuniar

Kesmas

The COVID-19 pandemic has led to the implementation of work from home policies in almost all parts of the world. This policy has increased the onset of musculoskeletal disorders in workers, such as low back pain (LBP). This study aimed to examine the prevalence of LBP among office workers during the COVID-19 pandemic after implementing WFH policies. This study was performed using data from various countries to determine the relationship between LBP and several risk factors, specifically age, sex, physical activity, ergonomic factors, as well as work environment factors such as temperature, humidity, lighting, noise, and work duration. A systematic …

Executive Functioning, Diabetes Distress, And Diabetes Management Among Adolescents With Type 1 Diabetes: Youth And Parent Perspectives, Allison Choe, Emily M. Fredericks, Dana L. Albright, Joyce M. Lee, Julie M. Sturza, Hurley O. Riley, Niko Kaciroti, Katherine W. Bauer, Allison L. Miller

Health Services and Informatics Research

Objective: Most adolescents with Type 1 Diabetes (T1D) do not achieve recommended glycemic targets, placing them at risk for long-term complications. Executive functioning (EF), or the cognitive processes that support goal-directed action and management of behavior, emotion, and cognition, is proposed to support effective T1D management and contribute to glycemic stability. We sought to examine associations of EF with T1D management behaviors and diabetes-related distress in adolescents with T1D.

Methods: Participants were 13–17-year-olds (M = 15.44, SD = 1.38 years) from a randomized controlled trial (N = 88). We conducted secondary analyses of preintervention data. Youth and their …

Greening The Workplace: Can Sustainable Practices Reduce Anxiety And Enhance Meaningful Work Engagement?, Cyril Tom T. Sunny, Peter Muttungal, Benny G. Davidson

Northeast Journal of Complex Systems (NEJCS)

This academic research examines the relationship between job engagement, green work climate, job-related anxiety, meaningfulness at work within the organization. It draws attention to identify the significant relations among all these factors and highlights the role of a green work climate in promoting meaningful work and alleviating job-related anxiety. The research emphasizes a diverse sample of employees from various organisations using structural modelling to find the mediating roles of job engagement and work meaningfulness in the correlation between organizational practices, environmental sustainability, and employee satisfaction. The study finds that a green work climate significantly enhances meaningful work experiences and reduces …

Beyond The Blue Skies: A Comprehensive Guide For Risk Assessment In Aviation, Leila Halawi, Mark Miller, Sam Holley

Publications

Risk assessment in aviation is a critical process that safeguards the safety and reliability of operations. Aviation operations encompass inherent risks, from mechanical failures to human errors and environmental factors. The significance of these risks may be severe, leading to accidents, injuries, and loss of life. Recognizing and mitigating risks is supreme in this dynamic environment, where emerging technologies and innovation constantly reshape this industry. This chapter includes an in-depth explanation of risk management and analysis, leading to the core elements of risk assessment specifically for aviation operations. We will describe the process and explore some of the applications and …

Human-Ai Collaboration In Writing: A Multidimensional Framework For Creative And Intellectual Authorship, James Hutson

Faculty Scholarship

The integration of AI technologies into the writing process has significantly altered traditional notions of authorship, creativity, and intellectual labor. Historically, writing was seen as a human-driven cognitive and creative exercise, but with the rise of generative AI tools such as ChatGPT and Claude, the line between human and AI contributions has become increasingly ambiguous. This paper addresses the limitations of the current sliding scale model, which views AI involvement as ranging from “none” to “complete”. In its place, we propose a new multidimensional framework that more accurately reflects the complexity of human-AI collaboration in writing. The model includes axes …

Educating Students On The Behavioral And Psychological Aspects Of Romance Scam Victimization Via A Social Engineering Competition, Rachel Bleiman, Hwanhee Park, Aunshul Rege

Journal of Cybersecurity Education, Research and Practice

The online dating industry generated 2.98 billion USD in 2023 and is estimated to reach 3.6 billion USD by 2025. Not surprisingly, online dating platforms are rife with romance scams that cause financial damages, with estimated losses of 1.3 billion USD in 2022 alone. Additionally, victims suffer emotional and psychological harms. This paper shares findings from a 2023 Romance Scam and Social Engineering Competition (RSSEC) that introduced students to the behavioral and psychological aspects of romance scams. Specifically, the competition aimed to expose students to (i) understanding how victims experience social engineering (SE) - the psychological manipulation of human behavior, …

Integrating Quantum Computing In High-Frequency Trading: A Project Management Approach, Dhwani Patel, Dhwani Patel

Harrisburg University Dissertations and Theses

This thesis explores the integration of quantum computing in high-frequency trading (HFT) from a project management perspective. As quantum computing emerges as a transformative technology, its potential to revolutionize financial markets, particularly HFT, necessitates structured approaches to manage the associated complexities and risks. Agile methodologies are examined as a solution to bridge the gap between the rapid development cycles of quantum software and the high-speed requirements of trading algorithms. The study employs a qualitative research approach, incorporating expert interviews and literature analysis to identify the challenges and opportunities of implementing quantum computing in HFT. The research reveals that while quantum …

Quantifying The Role Of Active Listening And Reassurance In Virtual Health Coach Interactions, Ghulam Hussain, Brian Keegan, Robert Ross

Articles

Conversational Agents have the potential to support healthcare through coaching exercise routines, but are still lacking in demonstrating authentic social behaviours to support engagement. To this end, we present a series of experiments that we conducted in order to investigate how automated health care coaches can be more effective when their interaction style is tailored to demonstrate qualities associated with a good bedside manner, namely active listening and reassurance. To test this, we first developed a dataset of 135 dialogue excerpts from three distinct sources, i.e., original, handcrafted and LLMs, the latter two of which were tuned to demonstrate specific …

A Bibliometric Study Of Astronomy And Geoscience Doctoral Dissertations, Nora Boyle, Mary Schlembach

Faculty Journal Articles

A bibliometric analysis was conducted over the bibliographies of astronomy and geology doctoral dissertations written between 1970 and 2020 in order to review the document types that are utilized and cited. An investigation was made of various cited reference ages and how cited references in dissertations have evolved with the advent of electronic resources and preprint services. Our study examined 50 astronomy and 50 geology dissertations with 10 dissertations selected from each decade (n = 100). Results measured included 13,475 total references and the study found that references to journal articles increased, and book citations have decreased in both …

Modelling The Behavior Of Human Crowds As Coupled Active-Passive Dynamics Of Interacting Particle Systems, Thoa Thieu, Roderick Melnik

School of Mathematical & Statistical Sciences Faculty Publications

The modelling of human crowd behaviors offers many challenging questions to science in general. Specifically, the social human behavior consists of many physiological and psychological processes which are still largely unknown. To model reliably such human crowd systems with complex social interactions, stochastic tools play an important role for the setting of mathematical formulations of the problems. In this work, using the description based on an exclusion principle, we study a statistical-mechanics-based lattice gas model for active-passive population dynamics with an application to human crowd behaviors. We provide representative numerical examples for the evacuation dynamics of human crowds, where the …

Social Engineering Threat Analysis Using Large-Scale Synthetic Data, Sellappan Palaniappan, Rajasvaran Logeswaran, Shapla Khanam, Pulasthi Gunawardhana

Journal of Informatics and Web Engineering

We frequently hear news about compromised systems, virus attacks, spam emails, stolen bank account numbers, and loss of money. Safeguarding and protecting digital assets against these and other cyber-attacks are extremely important in our digital connected world today. Many organizations spend substantial amounts of money to protect their digital assets. One type of cyber threat that is rampant these days is social engineering attacks that work on human psychology. These attacks typically persuade, convince, trick and threaten naïve and innocent individuals to divulge sensitive information to the attackers. Consequently, traditional approaches have not been effective or successful in preventing these …

Early Identification Of Parkinson's Disease Using Time Frequency Analysis On Eeg Signals, Tanvir Hasib, V Vijayakumar, Ramakrishnan Kannan

Journal of Informatics and Web Engineering

Parkinson's Disease (PD) is a progressive neurological disorder. It affects movement and can significantly impact quality of life. Early and accurate diagnosis is crucial for effective management and intervention. Traditional diagnostic methods can be time-consuming and less effective in the early stages of the disease. This study aims to develop an automated approach for identifying PD using time-frequency image analysis of electroencephalogram (EEG) signals. The goal is to enhance diagnostic accuracy and efficiency, facilitating early detection. EEG signals, often contaminated with artifacts such as eye blinks and muscle movements etc., were first cleaned. Time-frequency images were then plotted from the …

Integrating Moral Values In Ai: Addressing Ethical Challenges For Fair And Responsible Technology, Khushboo Shah, Hiren Joshi, Hardik Joshi

Journal of Informatics and Web Engineering

Today, Artificial Intelligence (AI) has become an integral part of our day-to-day life. From personal task to professional life everywhere we need AI. All the sectors like - transport, education, healthcare, agriculture, we find AI everywhere. Each coin has two side, similarly AI has its own pros and cons. Main challenge with AI is ethics. There is no doubt in the work efficiency of AI but ultimately, it’s a machine without emotions hence whatever the decision it takes it purely without ethical values. Sometimes, this type of decision may lead to disasters, especially in the industry where human life is …

Path To A Healthy Work-Life Balance: Mobile Application For Work And Personal Life Mastery, Erfan Rahmani, Zarina Che Embi

Journal of Informatics and Web Engineering

Drawing insights from diverse organizational methods, this study endeavors to facilitate effective self-development and organization in the face of contemporary demands as solutions for integrating goal tracking, event coordination, and task management within a unified calendar framework in a mobile application. There are three primary objectives of this study: firstly, to explore essential functionalities crucial for addressing the multifaceted challenges of modern life; secondly, to design and develop a mobile application that seamlessly integrates these functionalities; and finally, to evaluate the usability of the application through rigorous testing and feedback mechanisms. Envisaged deliverables include a fully functional mobile application designed …

Locational Data And The Public Interest, William A. Herbert, Micahel Goodchild, Richard Appelbaum, Jeremy Crampton, Gary Langham, Krzysztof Janowicz, Mei-Po Kwan, Katina Michael, Lisa Schamess

Publications and Research

This article presents a paper developed by the AAG Organizing Committee on Locational Information and the Public Interest through a summit held in Santa Barbara, California in June 2022. The summit resulted in goals and ideas for addressing the issues that arise from the present environment for geodata, whereby public, private, and third-sector entities can tap into publicly available locational information with relatively little regulation on its access or use. The Committee articulates four goals: (1) develop a research agenda extending across disciplines, (2) outline educational resources and strategies to guide ethical practice, (3) devise a pathway to increase public …

Inclusive Space For Everyone Door Sign (Printable 8.5 X 11 Inch), Joan H. Robinson

Open Educational Resources

This is a printable 8.5 x 11 inch door sign for faculty, staff, and administrators to let people know it is an inclusive space for everyone. For improved visibility, print with a color printer and cut along the dotted line.

See also: 11 x 17 inch door sign.

Stochastic Games Of Parental Vaccination Decision Making And Bounded Rationality, Andras Balogh, Tamer Oraby

School of Mathematical & Statistical Sciences Faculty Publications

Vaccination is an effective strategy to prevent the spread of diseases. However, hesitancy and rejection of vaccines, particularly in childhood immunizations, pose challenges to vaccination efforts. In that case, according to rational decision-making and classical utility theory, parents weigh the costs of vaccination against the costs of not vaccinating their children. Social norms influence these parental decision-making outcomes, deviating their decisions from rationality. Additionally, variability in values of utilities stemming from stochasticity in parents' perceptions over time can lead to further deviations from rationality. In this paper, we employ independent white noises to represent stochastic fluctuations in parental perceptions of …

A Review Of Artificial Intelligence, Algorithms, And Robots Through The Lens Of Stakeholder Theory, Michael J. Matthews, Su Runkun, Lindsey Yonish, Shawn Mcclean, Joel Koopman, Kai Chi Yam

Management Faculty Publications

With the arrival of the Fourth Industrial Revolution, intelligent machines are affecting the daily lives of multiple organizational stakeholders. However, despite the continued expansion of intelligent machines in society, management scholarship has generally lagged, and current frameworks are under-equipped to offer meaningful guidance regarding the intersection of intelligent machines and organizations. We address this issue via a multidisciplinary review and a novel framework of intelligent machines and value creation. First, we discuss the characteristics of intelligent machines (i.e., autonomy, learning, inscrutability, and materiality) and how variation in these characteristics impacts their affordances and, subsequently, the value offered to stakeholders. We …

Classification Of Schizophrenia, Bipolar Disorder And Major Depressive Disorder With Comorbid Traits And Deep Learning Algorithms, Xiangning Chen, Yimei Lu, Joan Manuel Cue, Mira V Han, Vishwajit L Nimgaonkar, Daniel R Weinberger, Shizhong Han, Zhongming Zhao, Jingchun Chen

Faculty, Staff and Student Publications

Many psychiatric disorders share genetic liabilities, but whether these shared liabilities can be utilized to classify and differentiate psychiatric disorders remains unclear. In this study, we use polygenic risk scores (PRSs) of 42 traits comorbid with schizophrenia (SCZ), bipolar disorder (BIP), and major depressive disorder (MDD) to evaluate their utilities. We found that combining target specific PRS with PRSs of comorbid traits can improve the classification of the target disorders. Importantly, without inclusion of PRSs from targeted disorders, we can still classify SCZ (accuracy 0.710 ± 0.008, AUC 0.789 ± 0.011), BIP (accuracy 0.782 ± 0.006, AUC 0.852 ± 0.004), …

Zombie-Auras: Genai And Hybrid Text Production, Joshua Nieubuurt

English Faculty Publications

This paper explores the iterative evolutions of textual production and their impact on the “aura” of texts, as conceptualized by Walter Benjamin. The study identifies three key phases of textual production: the natural, the mechanized, and the digitized, each progressively displacing the “cult value” of texts. This cult value is lost through increased ease of creation, reproduction, dissemination, and dislocation of creators and audiences in time and space. The advent of Generative AI (GenAI) marks the latest evolution, transforming the “aura” into a memetic “zombie” form—familiar yet opaque, evoking both the sublime and fear. By examining Benjamin’s notion of “aura” …

Childhood Sexual Trauma, Substance Use, And Antiretroviral Therapy Adherence Among Older Adults Living With Hiv: A Mediational Analysis, Monique J. Brown, Josie Zhang, Prince Nii Ossah Addo, Amandeep Kaur, Daniel Amoatika, Elizabeth L. Crouch Ph.D., Steven A. Cohen

Faculty Publications

Childhood sexual abuse (CSA) is linked to substance use and lower antiretroviral therapy (ART) adherence. However, studies examining the mediational role of substance use between CSA and ART adherence are lacking. Therefore, the aim of this study was to determine the potential mediational role of substance use between CSA and ART adherence among older adults living with HIV (OALH) (n = 91). Mediation analyses assessed the direct and indirect relationships between CSA, substance use, and ART adherence. Statistically significant differences existed in substance use by gender (male vs. female: 12.3 vs. 9.97) and ART adherence by race (Black vs. …

Proactive Conversational Ai: A Comprehensive Survey Of Advancements And Opportunities, Yang Deng, Lizi Liao, Wenqiang Lei, Grace Hui Yang, Wai Lam, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Dialogue systems are designed to offer human users social support or functional services through natural language interactions. Traditional conversation research has put significant emphasis on a system's response-ability, including its capacity to understand dialogue context and generate appropriate responses. However, the key element of proactive behavior-a crucial aspect of intelligent conversations-is often overlooked in these studies. Proactivity empowers conversational agents to lead conversations towards achieving pre-defined targets or fulfilling specific goals on the system side. Proactive dialogue systems are equipped with advanced techniques to handle complex tasks, requiring strategic and motivational interactions, thus representing a significant step towards artificial general …

Vaxbot-Hpv: A Gpt-Based Chatbot For Answering Hpv Vaccine-Related Questions, Yiming Li, Jianfu Li, Manqi Li, Evan Yu, Danniel Rhee, Muhammad Amith, Lu Tang, Lara S Savas, Licong Cui, Cui Tao

Faculty, Staff and Student Publications

OBJECTIVE: Human Papillomavirus (HPV) vaccine is an effective measure to prevent and control the diseases caused by HPV. However, widespread misinformation and vaccine hesitancy remain significant barriers to its uptake. This study focuses on the development of VaxBot-HPV, a chatbot aimed at improving health literacy and promoting vaccination uptake by providing information and answering questions about the HPV vaccine.

METHODS: We constructed the knowledge base (KB) for VaxBot-HPV, which consists of 451 documents from biomedical literature and web sources on the HPV vaccine. We extracted 202 question-answer pairs from the KB and 39 questions generated by GPT-4 for training and …

Ai As Your Ally: The Effects Of Ai-Assisted Venting On Negative Affect And Perceived Social Support, Meilan Hu, Xavier Cheng Wee Chua, Shu Fen Diong, K. T. A. Sandeeshwara Kasturiratna, Nadyanna M. Majeed, Andree Hartanto

Research Collection School of Social Sciences

In recent years, artificial intelligence (AI) chatbots have made significant strides in generating human-like conversations. With AI's expanding capabilities in mimicking human interactions, its affordability and accessibility underscore the potential of AI chatbots to facilitate negative emotional disclosure or venting. The study's primary objective is to highlight the potential benefits of AI-assisted venting by comparing its effectiveness to venting through a traditional journaling platform in reducing negative affect and increasing perceived social support. We conducted a pre-registered within-subject experiment involving 150 participants who completed both traditional venting and AI-assisted venting conditions with counterbalancing and a wash-out period of 1-week between …

Exploring Key Factors Influencing Depressive Symptoms Among Middle-Aged And Elderly Adult Population: A Machine Learning-Based Method, Ngoc Doan Thu Tran, Yi Zhen Tan, Sapphire Lin, Fang Zhao, Yee Sien Ng, Dong Ma, Jeonggil Ko, Rajesh Krishna Balan

Research Collection School Of Computing and Information Systems

Objective: This paper aims to investigate the key factors, including demographics, socioeconomics, physical wellbeing, lifestyle, daily activities and loneliness that can impact depressive symptoms in the middle-aged and elderly population using machine learning techniques. By identifying the most important predictors of depressive symptoms through the analysis, the findings can have important implications for early depression detection and intervention. Participants: For our cross-sectional study, we recruited a total of 976 volunteers, with a specific focus on individuals aged 50 and above. Each participant was requested to provide their demographic, socioeconomic information and undergo several physical health tests. Additionally, they were asked …

Seven Hci Grand Challenges Revisited: Five-Year Progress, Constantine Stephanidis, Gavriel Salvendy, Margherita Antona, Vincent G Duffy, Qin Gao, Waldemar Karwowski, Fiona Nah, Stavroula Ntoa, Pei-Luen Patrick Rau, Keng Siau, Jia Zhou

Research Collection School Of Computing and Information Systems

Motivated by the rapid technological advancements achieved in the last five years, and the pervasiveness of Artificial Intelligence, the paper investigates the evolving role of Human-Computer Interaction and revisits the seven grand challenges outlined in 2019: human-technology symbiosis, human-environment interactions, ethics, privacy and security, well-being, health and eudaimonia, accessibility and universal access, learning and creativity, and social organization and democracy. Through literature analysis, the paper reevaluates the status of each challenge and highlights emerging requirements. Key findings reveal the widespread impact of Artificial Intelligence across all domains and emphasize the need for improved AI transparency, alignment with human values, and …

Human-Ai Synergy In Survey Development: Implications From Large Language Models In Business And Research, Ping Fan Ke, Ka Chung Ng

Research Collection School Of Computing and Information Systems

This study examines the novel integration of Large Language Models (LLMs) into the survey development process in business and research through the development and evaluation of the Behavioral Research ASSistant (BRASS) Bot. We first analyzed the traditional scale development process to identify tasks suitable for LLM integration, including both human-in-the-loop and automated LLM data collection methods. Following this analysis, we developed the details of BRASS Bot, incorporating design principles of falsifiability and reproducibility. We then conducted a comprehensive evaluation of the BRASS Bot across a diverse set of LLMs, including GPT, Claude, Gemini, and Llama, to assess its usability, validity, …

Testing Toxicity: Two Approaches To Toxicity Detection, Nelson E. Jarrin

Dissertations, Theses, and Capstone Projects

The current online environment is increasingly being polluted by polarization, echo chambers, and a lack of constructive dialogue between individuals with differing viewpoints. Social media algorithms, while intended to personalize user experiences and marketing areas, have been heavily criticized for inadvertently amplifying extremist content and contributing to the spread of toxic commentary. The current state of the internet hinders productive conversations, fuels misinformation, entices disinformation and contributes to online and offline societal division. This is fueled by algorithms that can create echo chambers and by the anonymity given by online platforms. While tools like the Perspective API exist to identify …