Social and Behavioral Sciences Commons^™

Artificial Intelligence And Film: A Journey In Public Perception From 1960 To The Present Day, Kayla Anderson, Andrew Roggeman, Joseph Fuller

Celebrating Scholarship and Creativity Day (2018-)

An analysis of accomplishments in film from the 1960s-2020s that feature Artificial Intelligence to give a full picture of how public perception has changed towards these technologies over time, supplemented by historical and technological context.

Ai-Powered Learning: Blending Ai With Active Learning In The Information Literacy Classroom, Kevin J. Reagan, Wilhelmina Randtke

Georgia International Conference on Information Literacy

In 2016, the ACRL Framework for Information Literacy in Higher Education launched in response to more voluminous, less-vetted online information, including misinformation and content farms. Subsequently, the ACRL Framework has been widely adopted, and numerous high-quality lesson plans and resources for teaching the frames already exist, including published lesson plans and textbooks. Now, generative AI tools, such as ChatGPT and other chat bots present new challenges for information literacy educators. For instance, in addition to teaching students how to identify issues such as fake news, the information literacy professional has to address topics such as ethical AI use, AI hallucination …

A Design Science Approach To Investigating Decentralized Identity Technology, Janelle Krupicka

Cybersecurity Undergraduate Research Showcase

The internet needs secure forms of identity authentication to function properly, but identity authentication is not a core part of the internet’s architecture. Instead, approaches to identity verification vary, often using centralized stores of identity information that are targets of cyber attacks. Decentralized identity is a secure way to manage identity online that puts users’ identities in their own hands and that has the potential to become a core part of cybersecurity. However, decentralized identity technology is new and continually evolving, which makes implementing this technology in an organizational setting challenging. This paper suggests that, in the future, decentralized identity …

Hgs-3 The Influence Of A Tandem Cycling Program In The Community On Physical And Functional Health, Therapeutic Bonds, And Quality Of Life For Individuals And Care Partners Coping With Parkinson’S Disease, Leila Djerdjour, Jennifer L. Trilk

SC Upstate Research Symposium

Purpose Statement: Several studies have shown that aerobic exercise can have a positive impact on alleviating symptoms experienced by individuals with Parkinson's disease (PD). Despite this evidence, the potential benefits of exercise for both PD patients and their care partners (PD dyad) remain unexplored. This research project investigates the effectiveness, therapeutic collaborations, and physical outcomes of a virtual reality (VR) tandem cycling program specifically designed for PD dyads.

Methods: Following approval from the Prisma Health Institutional Review Board, individuals with PD were identified and screened by clinical neurologists. The pre-testing measures for PD dyads (N=9) included emotional and cognitive status …

Immersive Japanese Language Learning Web Application Using Spaced Repetition, Active Recall, And An Artificial Intelligent Conversational Chat Agent Both In Voice And In Text, Marc Butler

MS in Computer Science Project Reports

In the last two decades various human language learning applications, spaced repetition software, online dictionaries, and artificial intelligent chat agents have been developed. However, there is no solution to cohesively combine these technologies into a comprehensive language learning application including skills such as speaking, typing, listening, and reading. Our contribution is to provide an immersive language learning web application to the end user which combines spaced repetition, a study technique used to review information at systematic intervals, and active recall, the process of purposely retrieving information from memory during a review session, with an artificial intelligent conversational chat agent both …

Artificial Sociality, Simone Natale, Iliana Depounti

Human-Machine Communication

This article proposes the notion of Artificial Sociality to describe communicative AI technologies that create the impression of social behavior. Existing tools that activate Artificial Sociality include, among others, Large Language Models (LLMs) such as ChatGPT, voice assistants, virtual influencers, socialbots and companion chatbots such as Replika. The article highlights three key issues that are likely to shape present and future debates about these technologies, as well as design practices and regulation efforts: the modelling of human sociality that foregrounds it, the problem of deception and the issue of control from the part of the users. Ethical, social and cultural …

An Exploration Of Companion Robots, Annelyse Lockhart

2024 Student Academic Showcase

Japan and the United States have a drastically different view towards artificial intelligence and smart machines. Within my project, I did an exploratory analysis of robotics within the United States and Japan, and posed the question as to why Japan has substantially more robotics within their day-to-day life. I took an in-depth look at Japanese robotics that do not exist within the United States, as well as explored the biases behind smart machines in both cultures. Judging Category: Exploratory

Nowcasting Heavy Rainfall With Convolutional Long Short-Term Memory Networks: A Pixelwise Modeling Approach, Yi Victor Wang, Seung Hee Kim, Geunsu Lyu, Choeng-Lyong Lee, Soorok Ryu, Gyuwon Lee, Ki-Hong Min, Menas C. Kafatos

Institute for ECHO Articles and Research

The recent decades have seen an increasing academic interest in leveraging machine learning approaches to nowcast, or forecast in a highly short-term manner, precipitation at a high resolution, given the limitations of the traditional numerical weather prediction models on this task. To capture the spatiotemporal associations of data on input variables, a deep learning (DL) architecture with the combination of a convolutional neural network and a recurrent neural network can be an ideal design for nowcasting rainfall. In this study, a long short-term memory (LSTM) modeling structure is proposed with convolutional operations on input variables. To resolve the issue of …

Lyraquist: Language Learning Via Music App, Vivian D'Souza, Siri Avula, Mahi Patel, Tanvi Singh, Ashley Bickham

Senior Theses

Lyraquist is a new language learning mobile app that encourages the practice of a foreign language through music. Language learners can connect their Spotify Premium account to Lyraquist to listen to music in their target languages and utilize tools such as translation and vocabulary lists to facilitate language practice. Through integration with Spotify, users can import and create Spotify playlists and search the service’s entire catalog. By combining daily listening habits with several tasks associated with language learning in one place, Lyraquist hopes to be a useful language learning tool.

Unearthing The Past: A Comprehensive Study Of Natural And Anthropogenic Changes At An Archaeological Site Through Hydrogeologic Connectivity Utilizing Gis, Mehlich Ii Phosphorus Extractant, And Ph, Dana L. F. Herren

Theses

This thesis aims to thoroughly analyze the Mehlich II Phosphorus Extractant and pH levels at the Bains Gap Village Site in Anniston, AL., while examining the impact of various environmental factors and human activities on them. Phosphorus is often used in archaeology as an indicator of human activity. Soil core samples were collected to analyze anomalies in phosphorus levels.

To establish any relationships, phosphorus and pH levels from soil cores were correlated with findings from past excavation units and features. The potential effects of hydrogeologic connectivity on soil phosphorus and pH levels were investigated. Geospatial technologies were used to manage …

W4-Groups: Modeling The Who, What, When And Where Of Group Behavior Via Mobility Sensing, Akansha Atrey, Camellia Zakaria, Rajesh Krishna Balan, Prashant Shenoy

Research Collection School Of Computing and Information Systems

Human social interactions occur in group settings of varying sizes and locations, depending on the type of social activity. The ability to distinguish group formations based on their purposes transforms how group detection mechanisms function. Not only should such tools support the effective detection of serendipitous encounters, but they can derive categories of relation types among users. Determining who is involved, what activity is performed, and when and where the activity occurs are critical to understanding group processes in greater depth, including supporting goal-oriented applications (e.g., performance, productivity, and mental health) that require sensing social factors. In this work, we …

Smu Libraries – An Enabling Partner In Ai Information Literacy, Samantha Seah, Zhe Benedict Yeo, Lukas Tschopp

Research Collection Library

SMU Libraries plays a pivotal role in advancing AI information literacy within the larger need for digital literacy skills in the SMU community. In this presentation, participants will get an overview of SMU Libraries' engagement and partnerships with the academic community and will showcase initiatives and resources supporting AI literacy. This includes a discussion of insights from the scholarly literature, research findings and critical perspectives to inform teaching and learning practices related to AI. Speakers will share SMU Libraries’ contributions towards awareness and adoption of AI through a portfolio of successful collaborations and initiatives with partners and stakeholders within and …

Discovering Significant Topics From Legal Decisions With Selective Inference, Jerrold Tsin Howe Soh

Research Collection Yong Pung How School Of Law

We propose and evaluate an automated pipeline for discovering significant topics from legal decision texts by passing features synthesized with topic models through penalized regressions and post-selection significance tests. The method identifies case topics significantly correlated with outcomes, topic-word distributions which can be manually interpreted to gain insights about significant topics, and case-topic weights which can be used to identify representative cases for each topic. We demonstrate the method on a new dataset of domain name disputes and a canonical dataset of European Court of Human Rights violation cases. Topic models based on latent semantic analysis as well as language …

Assessing The Usability And Feasibility Of Digital Assistant Tools For Direct Support Professionals: Participatory Design And Pilot-Testing, Patrice Dolhonde Tremoulet, Andrea Lobo, Christina A. Simmons, Ganesh Baliga, Matthew Brady

Faculty Scholarship for the College of Science & Mathematics

Background: The United States is experiencing a direct support professional (DSP) crisis, with demand far exceeding supply. Although generating documentation is a critical responsibility, it is one of the most wearisome aspects of DSPs’ jobs. Technology that enables DSPs to log informal time-stamped notes throughout their shift could help reduce the burden of end-of-shift documentation and increase job satisfaction, which in turn could improve the quality of life of the individuals with intellectual and developmental disabilities (IDDs) whom DSPs support. However, DSPs, with varied ages, levels of education, and comfort using technology, are not likely to adopt tools that detract …

Editorial: Emerging On-Demand Passenger And Logistics Systems: Modelling, Optimization, And Data Analytics, Jintao Ke, Hai Wang, Neda Masoud, Maximilian Schiffer, Goncalo H. A. Correia

Research Collection School Of Computing and Information Systems

The proliferation of smart personal devices and mobile internet access has fueled numerous advancements in on-demand transportation services. These services are facilitated by online digital platforms and range from providing rides to delivering products. Their influence is transforming transportation systems and leaving a mark on changing individual mobility, activity patterns, and consumption behaviors. For instance, on-demand transportation companies such as Uber, Lyft, Grab, and DiDi have become increasingly vital for meeting urban transportation needs by connecting available drivers with passengers in real time. The recent surge in door-to-door food delivery (e.g., Uber Eats, DoorDash, Meituan); grocery delivery (e.g., Amazon Fresh, …

Auditory Vigilance Decrement In Drivers Of A Partially Automated Vehicle: A Pilot Study Using A High-Fidelity Driving Simulator, Luca Brooks, Jeffrey Glassman, Yusuke Yamani

Undergraduate Research Symposium

Vigilance decrement is the decline in the ability to monitor and detect behaviorally important signals over time, a phenomenon that can arise even after 30 minutes of watch (Mackworth, 1948). Recently, McCarley & Yamani (2021) found bias shifts, sensitivity losses, and attentional lapses contribute to vigilance decrement, but when each effect is isolated, there was little evidence that sensitivity loss affected vigilance decrement. With the introduction of partially autonomous vehicles, vigilance decrement may be problematic for drivers who must monitor the autonomous system for failures and takeover requests. Thus, this pilot study aims to extend McCarley and Yamani (2021) and …

Improving Educational Delivery And Content In Juvenile Detention Centers, Yomna Elmousalami

Undergraduate Research Symposium

Students in juvenile detention centers have the greatest need to receive improvements in educational delivery and content; however, they are one of the “truly disadvantaged” populations in terms of receiving those improvements. This work presents a qualitative data analysis based on a focus group meeting with stakeholders at a local Juvenile Detention Center. The current educational system in juvenile detention centers is based on paper worksheets, single-room style teaching methods, outdated technology, and a shortage of textbooks and teachers. In addition, detained students typically have behavioral challenges that are deemed "undesired" in society. As a result, many students miss classes …

Automated Identification And Mapping Of Interesting Mineral Spectra In Crism Images, Arun M. Saranathan

Doctoral Dissertations

The Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) has proven to be an invaluable tool for the mineralogical analysis of the Martian surface. It has been crucial in identifying and mapping the spatial extents of various minerals. Primarily, the identification and mapping of these mineral spectral-shapes have been performed manually. Given the size of the CRISM image dataset, manual analysis of the full dataset would be arduous/infeasible. This dissertation attempts to address this issue by describing an (machine learning based) automated processing pipeline for CRISM data that can be used to identify and map the unique mineral signatures present in …

Development Demand, Power Energy Consumption And Green And Low-Carbon Transition For Computing Power In China, Xiaohong Chen, Liaoying Cao, Jiaolong Chen, Jinghui Zhang, Wenzhi Cao, Yangjie Wang

Bulletin of Chinese Academy of Sciences (Chinese Version)

As a critical digital infrastructure, computing power has become the core productivity and a new engine driving economic growth in the digital economy. Nevertheless, the power-hungry nature of computing/data centers, representing the computing infrastructure, consumes a significant amount of electrical energy. Currently, China’s economy is transitioning from high-speed growth to high-quality development. It is imperative to study how to coordinate the development of computing power while ensuring its safety and achieving green and low-carbon goals. Based on an overview of the current status of computing power development, this study predicts the future demand for computing power in China, analyzes the …

Using Chatgpt To Generate Gendered Language, Shweta Soundararajan, Manuela Nayantara Jeyaraj, Sarah Jane Delany

Conference papers

Gendered language is the use of words that denote an individual's gender. This can be explicit where the gender is evident in the actual word used, e.g. mother, she, man, but it can also be implicit where social roles or behaviours can signal an individual's gender - for example, expectations that women display communal traits (e.g., affectionate, caring, gentle) and men display agentic traits (e.g., assertive, competitive, decisive). The use of gendered language in NLP systems can perpetuate gender stereotypes and bias. This paper proposes an approach to generating gendered language datasets using ChatGPT which will provide data for data-driven …

T-Pickseer: Visual Analysis Of Taxi Pick-Up Point Selection Behavior, Shuxian Gu, Yemo Dai, Zezheng Feng, Yong Wang, Haipeng Zeng

Research Collection School Of Computing and Information Systems

Taxi drivers often take much time to navigate the streets to look for passengers, which leads to high vacancy rates and wasted resources. Empty taxi cruising remains a big concern for taxi companies. Analyzing the pick-up point selection behavior can solve this problem effectively, providing suggestions for taxi management and dispatch. Many studies have been devoted to analyzing and recommending hotspot regions of pick-up points, which can make it easier for drivers to pick-up passengers. However, the selection of pick-up points is complex and affected by multiple factors, such as convenience and traffic management. Most existing approaches cannot produce satisfactory …

Developing Singapore As A Smart Nation, Josephine Teo

Asian Management Insights

Mrs Josephine Teo, Singapore’s Minister for Communications and Information, and Minister-in-charge of Smart Nation and Cybersecurity, speaks about leading the country’s Smart Nation drive.

Maximizing The Ai Revolution In Southeast Asia, Shoeb Kagda

Asian Management Insights

For that, the region must narrow the digital divide.

Eyris: From The Lab To The Market, Steven Miller, David Gomulya, Mahima Rao-Kachroo

Asian Management Insights

Singapore’s trailblazer AI algorithm for detecting diabetes-related eye diseases. Can you imagine getting the results of your eye disease screening within minutes rather than days? This capability is what EyRIS, a Singapore-based start-up that uses the AI (Artificial Intelligence)-driven Singapore Eye LEsion Analyzer (SELENA+) algorithm to screen for diabetes-related eye diseases, set out to productise and commercialise.

Conditional Neural Heuristic For Multiobjective Vehicle Routing Problems, Mingfeng Fan, Yaoxin Wu, Zhiguang Cao, Wen Song, Guillaume Sartoretti, Huan Liu, Guohua Wu

Research Collection School Of Computing and Information Systems

Existing neural heuristics for multiobjective vehicle routing problems (MOVRPs) are primarily conditioned on instance context, which failed to appropriately exploit preference and problem size, thus holding back the performance. To thoroughly unleash the potential, we propose a novel conditional neural heuristic (CNH) that fully leverages the instance context, preference, and size with an encoder–decoder structured policy network. Particularly, in our CNH, we design a dual-attention-based encoder to relate preferences and instance contexts, so as to better capture their joint effect on approximating the exact Pareto front (PF). We also design a size-aware decoder based on the sinusoidal encoding to explicitly …

Relocating Lubra Village And Visualizing Himalayan Flood Damages With Remote Sensing, Ronan Wallace, Yungdrung Tsewang Gurung, Ryan Kastner

Journal of Critical Global Issues

As weather patterns change worldwide, isolated communities impacted by climate change go unnoticed and we need community-driven solutions. In Himalayan Mustang, Nepal, indigenous Lubra Village faces threats of increasing flash flooding. After every flood, residual muddy sediment hardens across the riverbed like concrete, causing the riverbed elevation to rise. As elevation increases, sediment encroaches on Lubra’s agricultural fields and homes, magnifying flood vulnerability. In the last monsoon season alone, the Lubra community witnessed floods swallowing several agricultural fields and damaging two homes. One solution considers relocating the village to a new location entirely. However, relocation poses a challenging task, as …

Navigating The Digital Frontier: The Intersection Of Cybersecurity Challenges And Young Adult Life, Hannarae Lee

International Journal of Cybersecurity Intelligence & Cybercrime

Papers from this issue advocate for empowering young adults with knowledge and tools to navigate cyberspace safely, emphasizing the necessity of heightened cybersecurity measures and proactive education. As we advance into the digital abyss, this call becomes imperative, ensuring that the young adults' experience remains a journey of growth and enlightenment, unaffected by the shadows of unseen online threats.

The Need For A Cybersecurity Education Program For Internet Users With Limited English Proficiency: Results From A Pilot Study, Fawn T. Ngo, Rustu Deryol, Brian Turnbull, Jack Drobisz

International Journal of Cybersecurity Intelligence & Cybercrime

According to security experts, cybersecurity education and awareness at the user level are key in combating cybercrime. Hence, in the U.S., cybersecurity and Internet safety workshops, classes, and resources targeting children, adolescents, adults, and senior citizens abound. However, most cybercrime prevention programs are only available in English, thus, ignoring a substantial proportion of Internet users and potential cybercrime victims—Internet users with limited English proficiency (LEP). Yet, successfully combating cybercrime requires that all computer and Internet users, regardless of their language abilities and skills, have access to pertinent cybersecurity information and resources to protect themselves online. This paper presents the results …

Book Review: Tracers In The Dark: The Global Hunt For The Crime Lords Of Cryptocurrency, Marion Jones

International Journal of Cybersecurity Intelligence & Cybercrime

Doubleday released Andy Greenberg’s Tracers in the Dark: The Global Hunt for the Crime Lords of Cryptocurrency in November 2022. Through vivid case studies of global criminal investigations, the book dispels myths about the anonymizing power of cryptocurrency. The book details how the ability to identify cryptocurrency users and payment methods successfully brought down several large criminal empires, while also highlighting the continuous cat-and-mouse game between law enforcement officials and criminal actors using cryptocurrency. The book is an excellent resource for law enforcement officials, academics, and general cybersecurity practitioners interested in cryptocurrency-related criminal activities and law enforcement techniques.

Improving Belonging And Connectedness In The Cybersecurity Workforce: From College To The Profession, Mary Beth Klinger

Journal of Cybersecurity Education, Research and Practice

This article explores the results of a project aimed at supporting community college students in their academic pursuit of an Associate of Applied Science (AAS) degree in Cybersecurity through mentorship, collaboration, skill preparation, and other activities and touch points to increase students’ sense of belonging and connectedness in the cybersecurity profession. The goal of the project was focused on developing diverse, educated, and skilled cybersecurity personnel for employment within local industry and government to help curtail the current regional cybersecurity workforce gap that is emblematic of the lack of qualified cybersecurity personnel that presently exists nationwide. Emphasis throughout the project …