Digital Commons Network^™

Artificial Intelligence Frameworks To Detect And Investigate The Pathophysiology Of Spaceflight Associated Neuro-Ocular Syndrome (Sans), Joshua Ong, Ethan Waisberg, Mouayad Masalkhi, Sharif Amit Kamran, Kemper Lowry, Prithul Sarker, Nasif Zaman, Phani Paladugu, Alireza Tavakkoli, Andrew G Lee

Faculty, Staff and Student Publications

Spaceflight associated neuro-ocular syndrome (SANS) is a unique phenomenon that has been observed in astronauts who have undergone long-duration spaceflight (LDSF). The syndrome is characterized by distinct imaging and clinical findings including optic disc edema, hyperopic refractive shift, posterior globe flattening, and choroidal folds. SANS serves a large barrier to planetary spaceflight such as a mission to Mars and has been noted by the National Aeronautics and Space Administration (NASA) as a high risk based on its likelihood to occur and its severity to human health and mission performance. While it is a large barrier to future spaceflight, the underlying …

Accuracy Vs. Energy: An Assessment Of Bee Object Inference In Videos From On-Hive Video Loggers With Yolov3, Yolov4-Tiny, And Yolov7-Tiny, Vladimir A. Kulyukin, Aleksey V. Kulyukin

Computer Science Faculty and Staff Publications

A continuing trend in precision apiculture is to use computer vision methods to quantify characteristics of bee traffic in managed colonies at the hive's entrance. Since traffic at the hive's entrance is a contributing factor to the hive's productivity and health, we assessed the potential of three open-source convolutional network models, YOLOv3, YOLOv4-tiny, and YOLOv7-tiny, to quantify omnidirectional traffic in videos from on-hive video loggers on regular, unmodified one- and two-super Langstroth hives and compared their accuracies, energy efficacies, and operational energy footprints. We trained and tested the models with a 70/30 split on a dataset of 23,173 flying bees …

The Unstoppable Rise Of Ai: An Interview With Dr. John Sanford, Spencer Burrows, And Anna Birchler, Brandon Powell, Spencer Burrows

International Journal of Emerging and Disruptive Innovation in Education : VISIONARIUM

AI can both help and hurt the education field (higher education and secondary education). Despite Hollywood’s depiction of artificial intelligence solely in the form of killer death robots decades into the future, AI is much more versatile - and far more dangerous - than any killer robot could be. As artificial intelligence develops at a breakneck pace, its effect on our society will increase exponentially.

Emerging Technology And Pedagogical Application In Design Education, Ritesh Ranjan, Pooja Rana Ms.

International Journal of Emerging and Disruptive Innovation in Education : VISIONARIUM

This research paper investigates the emerging technologies and pedagogical applications in design education. The rapid development of technology has opened up new possibilities for design education, and it is important to explore how these emerging technologies can be used to enhance pedagogical practices. This paper aims to provide a comprehensive understanding of the potential of emerging technologies in design education and their impact on pedagogical practices.

The study employs a qualitative research methodology and draws on a range of literature sources, including academic articles, books, and reports. The research explores the use of emerging technologies such as virtual reality, augmented …

Design And Optimization Of Devices And Architectures For Neuromorphic Silicon Photonics, Matthew Van Niekerk

Theses

Neuromorphic photonics is an exciting field at the intersection of neuroscience, integrated photonics, and microelectronics. To realize large-scale neural network-inspired systems, we must have a toolbox of linear and nonlinear operators. Here, we review state of the art for integrated photonic linear operators, which can perform linear operations using interference or wavelength-division-multiplexing (WDM) techniques, and nonlinear operators, which perform nonlinear operations with a combination of photodetection and modulation. We present some devices that fit into the needed toolbox. A new type of directional coupler, using skin depth engineering of electromagnetic waves, suppresses optical crosstalk and eliminates the need for waveguide …

Chatgpt, Lamda, And The Hype Around Communicative Ai: The Automation Of Communication As A Field Of Research In Media And Communication Studies, Andreas Hepp, Wiebke Loosen, Stephan Dreyer, Juliane Jarke, Sigrid Kannengießer, Christian Katzenbach, Rainer Malaka, Michaela Pfadenhauer, Cornelius Puschmann, Wolfgang Schulz

Human-Machine Communication

The aim of this article is to more precisely define the field of research on the automation of communication, which is still only vaguely discernible. The central thesis argues that to be able to fully grasp the transformation of the media environment associated with the automation of communication, our view must be broadened from a preoccupation with direct interactions between humans and machines to societal communication. This more widely targeted question asks how the dynamics of societal communication change when communicative artificial intelligence—in short: communicative AI—is integrated into aspects of societal communication. To this end, we recommend an approach that …

Enhancing Video-Based Learning Using Knowledge Tracing: Personalizing Students’ Learning Experience With Orbits, Shady Shehata, David Santandreu, Philip Purnell, Mark Thompson

Natural Language Processing Faculty Publications

As the world regains its footing following the COVID-19 pandemic, academia is striving to consolidate the gains made in students’ education experience. New technologies such as video-based learning have shown some early improvement in student learning and engagement. In this paper, we present ORBITS predictive engine at YOURIKA company, a video-based student support platform powered by knowledge tracing. In an exploratory case study of one master’s level Speech Processing course at the Mohamed Bin Zayed University of Artificial Intelligence (MBZUAI) in Abu Dhabi, half the students used the system while the other half did not. Student qualitative feedback was universally …

Face Readers: The Frontier Of Computer Vision And Math Learning, Beverly Woolf, Margrit Betke, Hao Yu, Sarah Adel Bargal, Ivan Arroyo, John J. Magee Iv, Danielle Allessio, William Rebelsky

Computer Science

The future of AI-assisted individualized learning includes computer vision to inform intelligent tutors and teachers about student affect, motivation and performance. Facial expression recognition is essential in recognizing subtle differences when students ask for hints or fail to solve problems. Facial features and classification labels enable intelligent tutors to predict students’ performance and recommend activities. Videos can capture students’ faces and model their effort and progress; machine learning classifiers can support intelligent tutors to provide interventions. One goal of this research is to support deep dives by teachers to identify students’ individual needs through facial expression and to provide immediate …

Balanced Blended Space: Foundational Human–Ai Dialogues In A Symmetry-Based Mediation Framework, David Smith

Publications and Research

This working paper documents the early development of the Balanced Blended Space (BBS) framework through a series of iterative interactions between a cognitive agent (human researcher) and a computational agent (AI system) conducted in 2023. The work is motivated by the need for a universal theoretical model capable of describing the integration of physical, virtual, and conceptual spaces, particularly in response to increasing fragmentation across contemporary communication systems.

BBS is proposed as a symmetry-based mediation framework in which relationships between domains—such as physical and virtual space, cognition and computation, and multiple sensory modalities—are treated as structurally equivalent and mappable. Central …

Analyzing The American Artificial Intelligence Researches Based On Ntis Technology Contracts, Lihang Wang, Guo Chen

Journal of Scientific Information Research

[Purpose/significance]Science and technology contract is an important form for the US government to fund relevant institutions to carry out basic and systematic research. The contract number field contained in the NTIS science and technology report can be used to reveal the continuous research of several science and technology reports around the same contract objective.[Method/process]This article takes the NTIS technology report contract number in the field of artificial intelligence as the entry point, identifies many of the important technology contracts and interprets their background information one by one, and further focuses on the four most important technology contracts to reveal their …

Artificial Intelligence Tool For The Study Of Covid-19 Microdroplet Spread Across The Human Diameter And Airborne Space, Hesham H. Alsaadi, Monther Aldwairi, Faten Yasin, Sandra C.P. Cachinho, Abdullah Hussein

All Works

The 2019 novel coronavirus (SARS-CoV-2 / COVID-19), with a point of origin in Wuhan, China, has spread rapidly all over the world. It turned into a raging pandemic wrecking havoc on health care facilities, world economy and affecting everyone’s life to date. With every new variant, rate of transmission, spread of infections and the number of cases continues to rise at an international level and scale. There are limited reliable researches that study microdroplets spread and transmissions from human sneeze or cough in the airborne space. In this paper, we propose an intelligent technique to visualize, detect, measure the distance …

A Comparative Effectiveness Study On Opioid Use Disorder Prediction Using Artificial Intelligence And Existing Risk Models, Sajjad Fouladvand, Jeffery Talbert, Linda Phyliss Dwoskin, Heather M. Bush, Amy L. Meadows, Lars E. Peterson, Yash R. Mishra, Steven K. Roggenkamp, Fei Wang, Ramakanth Kavuluru, Jin Chen

Markey Cancer Center Faculty Publications

Opioid use disorder (OUD) is a leading cause of death in the United States placing a tremendous burden on patients, their families, and health care systems. Artificial intelligence (AI) can be harnessed with available healthcare data to produce automated OUD prediction tools. In this retrospective study, we developed AI based models for OUD prediction and showed that AI can predict OUD more effectively than existing clinical tools including the unweighted opioid risk tool (ORT). Data include 474,208 patients’ data over 10 years; 269,748 were females with an average age of 56.78 years. Cases are prescription opioid users with at least …

Singapore's Hospital To Home Program: Raising Patient Engagement Through Ai, John Abisheganaden, Kheng Hock Lee, Lian Leng Low, Eugene Shum, Han Leong Goh, Christine Gian Lee Ang, Andy Wee An Ta, Steven M. Miller

Research Collection School Of Computing and Information Systems

Because of their complex care needs, many elderly patients are discharged from hospitals only to be readmitted for multiple stays within the following twelve months. John Abisheganaden and his fellow authors describe Singapore’s Hospital to Home program, a community care initiative fueled by artificial intelligence.

Ai In Drug Discovery And Its Clinical Relevance, Rizwan Qureshi, Muhammad Irfan, Taimoor Muzaffar Gondal, Sheheryar Khan, Jia Wu, Muhammad Usman Hadi, John Heymach, Xiuning Le, Hong Yan, Tanvir Alam

Faculty, Staff and Student Publications

The COVID-19 pandemic has emphasized the need for novel drug discovery process. However, the journey from conceptualizing a drug to its eventual implementation in clinical settings is a long, complex, and expensive process, with many potential points of failure. Over the past decade, a vast growth in medical information has coincided with advances in computational hardware (cloud computing, GPUs, and TPUs) and the rise of deep learning. Medical data generated from large molecular screening profiles, personal health or pathology records, and public health organizations could benefit from analysis by Artificial Intelligence (AI) approaches to speed up and prevent failures in …

Safe Mdp Planning By Learning Temporal Patterns Of Undesirable Trajectories And Averting Negative Side Effects, Siow Meng Low, Akshat Kumar, Scott Sanner

Research Collection School Of Computing and Information Systems

In safe MDP planning, a cost function based on the current state and action is often used to specify safety aspects. In real world, often the state representation used may lack sufficient fidelity to specify such safety constraints. Operating based on an incomplete model can often produce unintended negative side effects (NSEs). To address these challenges, first, we associate safety signals with state-action trajectories (rather than just immediate state-action). This makes our safety model highly general. We also assume categorical safety labels are given for different trajectories, rather than a numerical cost function, which is harder to specify by the …

The Internet Of Things (Iot) In Healthcare: Taking Stock And Moving Forward, Abderahman Rejeb, Karim Rejeb, Horst Treiblmaier, Andrea Appolloni, Salem Alghamdi, Yaser Alhasawi, Mohammad Iranmanesh

Research outputs 2022 to 2026

Recent improvements in the Internet of Things (IoT) have allowed healthcare to evolve rapidly. This article summarizes previous studies on IoT applications in healthcare. A comprehensive review and a bibliometric analysis were performed to objectively summarize the growth of IoT research in healthcare. To begin, 2,990 journal articles were carefully selected for further investigation. These publications were analyzed based on various bibliometric metrics, including publication year, journals, authors, institutions, and countries. Keyword co-occurrence and co-citation networks were generated to unravel significant research hotspots. The findings show that IoT research has received considerable interest from the healthcare community. Based on the …

Singapore's Ai Applications In The Public Sector: Six Examples, Steven M. Miller

Research Collection School Of Computing and Information Systems

Steven M. Miller describes six instances in which Singapore has applied AI in the public sector, illustrating different ways of improving its engagement with the public by making government services more accessible, anywhere, anytime, and speeding its responses to public processes and feedback. He illustrates how its leaders made the city a living lab for AI use, and what they learned.

Harnessing Artificial Intelligence For Early And Evolution Of Alzheimer’S Disease Detections And Enhancing Senior Mental Health Through Innovative Art-Singing Therapies: A Multidisciplinary Approach, Jocelyne Kiss, Geoffreyjen Edwards, Rachel Bouserhal, Elaine Champagne, Thierry Belleguic, Valéry Psyché, Charles Batcho, Carol Hudon, Sylsvie Ratté, Ingrid Verdruyckt, Marie-Hélène Parizeau, Aaron Liu-Rosenbaum, James Hudson, Marie-Louise Bourbeau, Marie Lemieux, Annik Charbonneau

Faculty Scholarship

The well-documented therapeutic potential of group singing for patients living with Alzheimer’s disease (PLAD) has been hindered by COVID-19 restrictions, exacerbating loneliness and cognitive decline among seniors in residential and long-term care centers (CHSLDs). Addressing this challenge, the multidisciplinary study aims to develop a patient-oriented virtual reality (XR) interaction system facilitating group singing for mental health support during confinement and enhancing the understanding of the links between Alzheimer’s disease, social interaction, and singing. The researchers also propose to establish an early AD detection system using voice, facial, and non-invasive biometric measurements and validate the efficacy of selected intervention practices. The …

Reco.Ai: Using Generative Pre-Trained Transformer 3 Model For A Chatbot In Answering Grade 10 Mathematics Questions, Prince Travis S. Amado, Lhord Cedrick T. Delos Santos, Misxa Bien D. Germino, Aaron Gabriel G. Nolo, Vincent Ace C. Fronteras, Robyn Lauren C. Tria, Kent Patrick T. Congreso, Dalziel Oriol

DLSU Senior High School Research Congress

Over the years, several studies have explored AI's ability in terms of education. This study aims to investigate how ReCo.ai performs in terms of accuracy in answering mathematical concepts about Grade 10 Mathematics. Using the Generative Pre-trained Transformer 3 (GPT-3) model to create a chatbot specifically within the grade 10 Mathematics curriculum, and used the GPT-3 Generated Text dataset for machine learning and natural language processing. The researchers tested the accuracy by evaluating its accuracy, precision and recall, and F1 score. F1 score test was used as a performance metric to evaluate the precision and recall of the chatbot's responses. …

Stability-Based Generalization Analysis For Mixtures Of Pointwise And Pairwise Learning, Jiahuan Wang, Jun Chen, Hong Chen, Bin Gu, Weifu Li, Xin Tang

Machine Learning Faculty Publications

Recently, some mixture algorithms of pointwise and pairwise learning (PPL) have been formulated by employing the hybrid error metric of “pointwise loss + pairwise loss” and have shown empirical effectiveness on feature selection, ranking and recommendation tasks. However, to the best of our knowledge, the learning theory foundation of PPL has not been touched in the existing works. In this paper, we try to fill this theoretical gap by investigating the generalization properties of PPL. After extending the definitions of algorithmic stability to the PPL setting, we establish the high-probability generalization bounds for uniformly stable PPL algorithms. Moreover, explicit convergence …

National Telecommunications And Information Administration: Comments From Researchers At Boston University And The University Of Chicago, Ran Canetti, Aloni Cohen, Chris Conley, Mark Crovella, Stacey Dogan, Marco Gaboardi, Woodrow Hartzog, Rory Van Loo, Christopher Robertson, Katharine B. Silbaugh

Faculty Scholarship

These comments were composed by an interdisciplinary group of legal, computer science, and data science faculty and researchers at Boston University and the University of Chicago. This group collaborates on research projects that grapple with the legal, policy, and ethical implications of the use of algorithms and digital innovation in general, and more specifically regarding the use of online platforms, machine learning algorithms for classification, prediction, and decision making, and generative AI. Specific areas of expertise include the functionality and impact of recommendation systems; the development of Privacy Enhancing Technologies (PETs) and their relationship to privacy and data security laws; …

Aisha: A Custom Ai Library Chatbot Using The Chatgpt Api, Yrjo Lappalainen, Nikesh Narayanan

All Works

This article focuses on the development of a custom chatbot for Zayed University Library (United Arab Emirates) using Python and the ChatGPT API. The chatbot, named Aisha, was designed to provide quick and efficient reference and support services to students and faculty outside the library's regular operating hours. The article also discusses the benefits of chatbots in academic libraries, and reviews the early literature on ChatGPT's applicability in this field. The article describes the development process, perceived capabilities and limitations of the bot, and plans for further development. This project represents the first fully reported attempt to explore the potential …

Ai Art: Artists’ Best Friend Or Mortal Enemy?, Ethan Gabrys

Tredway Library Prize for First-Year Research

This paper analyzes the impacts and implications of generative AI software on art and examines the ethics of using such tools. Through the argument that careless use of these tools presents a danger to the art world as they risk devaluing human expression, Gabrys states that “as what it means to be human changes with each generation, new artists express sentiment through their art. Art has the ability to tell us about the human experience.” He concludes that the use of AI tools takes the skill and sentiment of human artists out of the equation, begging the question: if the …

Human-Ai Collaboration For Smart Education: Reframing Applied Learning To Support Metacognition, James Hutson, Daniel Plate

Faculty Scholarship

This chapter investigates the profound influence of intelligent virtual assistants (IVAs) on the educational domain, specifically in the realm of individualized learning and the instruction of writing abilities and content creation. IVAs, incorporating generative AI technologies such as ChatGPT and Stable Diffusion, hold the potential to bring about a paradigm shift in educational programs, emphasizing the enhancement of advanced metacognitive capacities rather than the fundamentals of communication. The subsequent recommendations stress the need to cultivate enduring proficiencies and ascertain tailored learning approaches for each learner, which will be indispensable for success in the evolving job market. In this context, prompt …

Generative Ai Tools In Art Education: Exploring Prompt Engineering And Iterative Processes For Enhanced Creativity, James Hutson, Peter Cotroneo

Faculty Scholarship

The rapid development and adoption of generative artificial intelligence (AI) tools in the art and design education landscape have introduced both opportunities and challenges. This timely study addresses the need to effectively integrate these tools into the classroom while considering ethical implications and the importance of prompt engineering. By examining the iterative process of refining original ideas through multiple iterations, verbal expansion, and the use of OpenAI’s DALL E2 for generating diverse visual outcomes, researchers gain insights into the potential benefits and pitfalls of these tools in an educational context. Students in the digital at case study were taught prompt …

Life, Death, And Ai: Exploring Digital Necromancy In Popular Culture—Ethical Considerations, Technological Limitations, And The Pet Cemetery Conundrum, James Hutson, Jay Ratican

Faculty Scholarship

This article explores the rise of generative AI, particularly ChatGPT, and the combination of large language models (LLM) with robotics, exemplified by Ameca the Robot. It addresses the need to study the ethical considerations and potential implications of digital necromancy, which involves using AI to reanimate deceased individuals for various purposes. Reasons for desiring to engage with a disembodied or bodied replica of a person include the preservation of memories, emotional closure, cultural heritage and historical preservation, interacting with idols or influential figures, educational and research purposes, and creative expression and artistic endeavors. As such, this article examines historical examples …

Replaced By Ai: Developing A Kuyperian Philosophy Of Work In The Face Of Advancing Artificial Intelligence, Erin Holmberg

Pro Rege

Erin Holmberg, a Dordt University junior and Kuyper Honor Student majoring in Computer Science, submitted this essay to the Lambertus Verberg Prize for Excellence in Kuyperian Scholarship competition, 2023.

Neuroevolution Application To Collaborative And Heuristics-Based Connected And Autonomous Vehicle Cohort Simulation At Uncontrolled Intersection, Frederic Jacquelin, Jungyun Bae, Bo Chen, Darrell Robinette

Michigan Tech Publications

Artificial intelligence is gaining tremendous attractiveness and showing great success in solving various problems, such as simplifying optimal control derivation. This work focuses on the application of Neuroevolution to the control of Connected and Autonomous Vehicle (CAV) cohorts operating at uncontrolled intersections. The proposed method implementation’s simplicity, thanks to the inclusion of heuristics and effective real-time performance are demonstrated. The resulting architecture achieves nearly ideal operating conditions in keeping the average speeds close to the speed limit. It achieves twice as high mean speed throughput as a controlled intersection, hence enabling lower travel time and mitigating energy inefficiencies from stop-and-go …

Patient Movement Monitoring Based On Imu And Deep Learning, Mohsen Sharifi Renani

Electronic Theses and Dissertations

Osteoarthritis (OA) is the leading cause of disability among the aging population in the United States and is frequently treated by replacing deteriorated joints with metal and plastic components. Developing better quantitative measures of movement quality to track patients longitudinally in their own homes would enable personalized treatment plans and hasten the advancement of promising new interventions. Wearable sensors and machine learning used to quantify patient movement could revolutionize the diagnosis and treatment of movement disorders. The purpose of this dissertation was to overcome technical challenges associated with the use of wearable sensors, specifically Inertial Measurement Units (IMUs), as a …

Tracing The Twenty-Year Evolution Of Developing Ai For Eye Screening In Singapore: A Master Chronology Of Sidrp, Selena+ And Eyris, Steven M. Miller

Research Collection School Of Computing and Information Systems

This working paper is entirely comprised of a timeline table that begins in 2002 and runs through mid-2023. Across these two decades, this timeline traces the evolutionary development of the following:

• The early Singapore R&D efforts to apply software-based image analysis algorithms and methods to analyse eye retina images for diabetic retinopathy and other eye diseases. This was based on a collaboration between the Singapore Eye Research Institute (SERI) and its parent organization, the Singapore National Eye Centre (SNEC), with faculty from the School of Computing at National University of Singapore.
• The establishment and operation of the Singapore Integrated Diabetic …