Artificial Intelligence and Robotics Commons^™

Hack24f: Alzcare Ai Assist: Empowering Alzheimer's Care, Yao Zhang, Chengjie Zheng, Oliver Francois, Lingling Zhang

Paul English Applied Artificial Intelligence (AI) Institute Publications

AlzCare AI Assist is a groundbreaking solution that leverages the power of artificial intelligence to revolutionize Alzheimer's care. By delivering personalized assessments, psychological support, and caregiver assistance, we aim to transform the lives of those affected by this debilitating condition.

Hack24f: Painsync, Zihan Li, Zhen Lu, Ping Chen

Paul English Applied Artificial Intelligence (AI) Institute Publications

Pain is one of the most disruptive human experiences, influencing not only physical well-being but also emotional and mental health. The PainSync project proposes a technology-assisted framework for pain recognition, monitoring, and management, using AI-driven tools to bridge the gap between patient experiences and professional care. PainSync begins by recognizing an individual’s discomfort and offering immediate support through a chatbot that collects symptom information and provides preliminary guidance. The system then tracks vital signs and daily activities, generating data that is subsequently analyzed by custom-built AI models to detect patterns, assess severity, and identify potential causes of pain. This analysis …

Breaking The Cycle: Countering Popularity Bias For Diverse Content Discovery, Brandon J. Weaver

Master's Projects

The ways most people consume the media have become very much driven by some pre-set algorithms. It is increasingly important to examine the outcome of these artificial intelligence (AI) models and ensure that any potentially dangerous long-term effects are addressed before they have a significant negative impact in our society. Popularity bias is one of these potentially harmful impacts, which stemmed from the shift from human intelligence to AI, or machine intelligence/machine learning (ML), when one explores the media and receives recommendations (often without requesting). In ML, three key steps usually occur; i.e, pre-processing, in-processing, and post- processing steps. The …

Towards Algorithmic Justice: Human Centered Approaches To Artificial Intelligence Design To Support Fairness And Mitigate Bias In The Financial Services Sector, Jihyun Kim

CMC Senior Theses

Artificial Intelligence (AI) has positively transformed the Financial services sector but also introduced AI biases against protected groups, amplifying existing prejudices against marginalized communities. The financial decisions made by biased algorithms could cause life-changing ramifications in applications such as lending and credit scoring. Human Centered AI (HCAI) is an emerging concept where AI systems seek to augment, not replace human abilities while preserving human control to ensure transparency, equity and privacy. The evolving field of HCAI shares a common ground with and can be enhanced by the Human Centered Design principles in that they both put humans, the user, at …

Hack24f: Ai Attacking Ai, Emry Hankins, Sofia Escobar, Yinxin Wan

Paul English Applied Artificial Intelligence (AI) Institute Publications

As MLaaS gains popularity, it also attracts new threats, in particular, model extraction attacks. These attacks involve unauthorized attempts to access and replicate AI models by querying and analyzing the response. Not only do these attacks pose a threat to security and safety but also compromises valuable intellectual property. Because businesses are increasing accessibility to their models that contain sensitive data, it is crucial that they are able to keep them safe and secure.

Hack24f: Careplus: Ai Chatbot, Arianna Fernandez, Sophia Cherkaoui

Paul English Applied Artificial Intelligence (AI) Institute Publications

90% of patients Google symptoms before they talk to their doctor. What are we developing? An app that asks for user symptoms and personal information, users AI to determine medical conditions and provides a plan of action, including recommended medications and suggested doctors to visit.

Hack24f: Llms And World Knowledge Problems, Chengtaon Lin, Joseph Lobo, Huuthanhvy Nguyen, Brian Santos, Ting Xu

Paul English Applied Artificial Intelligence (AI) Institute Publications

While AI “hallucinations” have been widely publicized by the media as shortcomings of Large Language Models (LLMs), there is much less awareness about shortcomings that derive from the potential lack of understanding of the world, from a potential lack of commonsense knowledge. We want to raise awareness among our student body about the potential fallibility of LLMs when they the problems that they need to solve require a basic understanding of the world. We hope that this awareness will prompt everyone to question more carefully the outputs generated by LLMs.

Hack24f: Using Ai To Support Teachers Working With Young Children With Challenging Behaviors, Muqing Zhang, Bennie Bendiksen, Songtian Zeng

Paul English Applied Artificial Intelligence (AI) Institute Publications

While coaching or mental health consultation can be a promising approach to support educators (Kang-Yi et al., 2018), the cost can be substantial and many school districts find it difficult to hire qualified personnel to coach the educators in need. Previous research has attempted to utilize mobile technology to support parents in addressing children with challenging behaviors (Meadan et al., 2016). There are few tools available to support teachers and that attempt to integrate AI technology in the program design and implementation. Our objective is to develop a prototype AI-based tool called Trick-or-Treat to support teachers in identifying and developing …

Hack24f: Beacon Pathway, Michael Agbesi, Ciara Santiago, David Martinez, Olivia Moos, Mohammed Mustafa

Paul English Applied Artificial Intelligence (AI) Institute Publications

The problem: There are a multitude of students from different backgrounds who are feeling lost in their academic journey at UMass Boston & need help with finding opportunities that fit their needs.

The solution: Developing Beacon Pathway, a user-centered platform designed to empower UMass Boston students from diverse backgrounds by streamlining their academic journey. This solution focuses on providing personalized resources, tailored opportunities, and community engagement, ensuring every student feels supported and connected as they navigate their unique paths to success

Hack24f: Tori Project: An Llm Powered Personal Assistant That Speaks, Inal Mashukov, Avi Felzenstein

Paul English Applied Artificial Intelligence (AI) Institute Publications

The problem: remember Jarvis from Iron Man? If not, Jarvis is an AI personal assistant to Tony Stark, aka Iron Man, which can speak in a human-like manner, and is in charge of the systems of the Iron Man suit. Tony Stark also relies on Jarvis for direct access to information, automation of his projects, and helping with work in general. Currently, the “best” real-world alternatives to Jarvis are Siri and Alexa. These are NOT particularly intelligent. Wouldn't it be nice to have a Jarvis-like assistant that is: actually intelligent and resourceful, sounds human, runs locally/offline on your phone or …

Hack24f: Ai And Mental Health: Addressing The Therapy Gap, Samatrai Piam, Digvijay Mahawar, Meric Kinali, Luxman Surentha, Jackson Comeau, Gail Rauch, Cody Turner

Paul English Applied Artificial Intelligence (AI) Institute Publications

Real-World Problem: There is a global shortage of mental health professionals, especially in underserved areas. AI-based chatbots could help fill this gap, but there are serious ethical concerns about the quality of care and efficacy of such chatbots.

Solution: This is a non-technical project that involved conversing with existing chatbots in an effort to develop a normative framework that could be used by future AI therapy bot developers. This framework seeks to build on, and operationalize, some of the insights from the recently published whitepaper on the ethics of chatbot therapy by the UMass Boston Applied Ethics Center. This presentation …

Hack24f: Examine The Human Creativity And Productivity In Ai Generated Content, Jongsoo Ha, Dante Barton, Onkar Khedkar, Neeti Shah, Yash Gondkar, Youxiang Zhu, Xiaohui Liang

Paul English Applied Artificial Intelligence (AI) Institute Publications

This project, presented at the Fall 2024 Hackathon, explores the balance between human creativity and productivity in the age of AI-generated content. With tools such as ChatGPT and Grammarly becoming integral to students’ academic workflows, questions surrounding originality, intellectual property, and academic integrity have grown increasingly urgent. The team addresses the challenge of distinguishing between human and AI contributions in content creation, particularly as current AI detection tools prove unreliable. Their proposed solution involves a system that not only detects AI-generated text using watermarking techniques but also quantifies contributions from humans and AI throughout the writing process.

Media Haze Classification In Retinal Images Using Deep Learning, Jonathan O'Berry

UNF Graduate Theses and Dissertations

Media Haze (MH) is a condition that affects an individual’s quality of life by affecting their eyes. Current practice is to detect MH by manually examining retinal fundus (retinal) images. The analysis of images being used as the prevalent technique for identifying the MH condition strongly suggests that automation of this process may be possible. In recent years, machine learning, specifically computer vision, has allowed for the automation of tasks relating to image analysis. This ability to automate has also recently been shown in the medical field for some eye conditions and diseases. This thesis centers around the problem of …

Hack24f: Ai Audio Extractor, David Wu, Tiffany Nham

Paul English Applied Artificial Intelligence (AI) Institute Publications

I want to make a next.js website locally and then be able to hopefully deploy on Vercel. Within the website I want to be able to use AI to separate the instruments (vocals, piano, guitar, drums, bass, etc.) and also identify which notes are being played. I was thinking that we might be able to use an AI stem splitter to separate the audio tracks and use another AI model for note detection.

Hack24f: Ai Conversations In Healthcare, Patrick Finger, Hannah Neale, Anthony Ferreira, Ayaz Mohammed

Paul English Applied Artificial Intelligence (AI) Institute Publications

Nursing students often complete clinical hours under the supervision of instructors in traditional hospital settings. However, obtaining individualized, consistent feedback from patients about their interactions with nursing students is often not feasible. This limits students' ability to fully understand how their communication skills are perceived and how they can improve. Currently, there are no models that represent realistic real life conversations with patients. Most virtual simulation models used for nursing students provide scripted responses that do not feel genuine.

Hack24f: The Empathy Architects, Michael Rejtig, Ajanee Igharo, Emma Kelminson, Jackson Comeau

Paul English Applied Artificial Intelligence (AI) Institute Publications

Problem Statement: We want to help patients from underserved communities feel more safe, respected and comfortable in interacting with healthcare providers during the initial in-person encounters while also helping providers build empathy and implement socio-emotionally competent communication behaviors. Solution: Empathy Evolution is an AI-powered role-playing game that helps patients simulate their ideal communication with healthcare providers.

Computer-Aided Craniofacial Superimposition Validation Study: The Identification Of The Leaders And Participants Of The Polish-Lithuanian January Uprising (1863–1864), Rubén Martos, Rosario Guerra, Fernando Navarro, Michela Peruch, Kevin Neuwirth, Andrea Valsecchi, Rimantas Jankauskas, Oscar Ibáñez

Faculty, Staff and Student Publications

In 2017, a series of human remains corresponding to the executed leaders of the "January Uprising" of 1863-1864 were uncovered at the Upper Castle of Vilnius (Lithuania). During the archeological excavations, 14 inhumation pits with the human remains of 21 individuals were found at the site. The subsequent identification process was carried out, including the analysis and cross-comparison of post-mortem data obtained in situ and in the lab with ante-mortem data obtained from historical archives. In parallel, three anthropologists with diverse backgrounds in craniofacial identification and two students without previous experience attempted to identify 11 of these 21 individuals using …

Outsourcing Voting To Ai: Can Chatgpt Advise Index Funds On Proxy Voting Decisions?, Chen Wang

Fordham Journal of Corporate & Financial Law

Released in November 2022, Chat Generative Pre-training Transformer (“ChatGPT”), has risen rapidly to prominence, and its versatile capabilities have already been shown in a variety of fields. Due to ChatGPT’s advanced features, such as extensive pre-training on diverse data, strong generalization ability, fine-tuning capabilities, and improved reasoning, the use of AI in the legal industry could experience a significant transformation. Since small passive funds with low-cost business models generally lack the financial resources to make informed proxy voting decisions that align with their shareholders’ interests, this Article considers the use of ChatGPT to assist small investment funds, particularly small passive …

An Empirical Study Of Machine Learning Techniques For Accurate Stock Price Forecasting, Daniel Paliulis, Hari Patchigolla

Honors Scholar Theses

This paper presents a comprehensive approach to predicting future stock prices of companies using machine learning and time series analysis. The research problem is centered around addressing the complexity and emotion-driven nature of stock investment decisions. To create an objective determinant in stock decisions, we propose a machine learning model utilizing time series data from major companies, including Amazon, Apple, Google, Nvidia, Meta, Tesla, Salesforce, Intel, and Microsoft. We explore the use of Long Short-Term Memory (LSTM) neural networks, to capture the temporal dynamics of stock prices. These models are designed to process sequential data, maintaining short term and long …

Study Of Augmentations On Historical Manuscripts Using Trocr, Erez Meoded

Theses and Dissertations

Historical manuscripts are an essential source of original content. For many reasons, it is hard to recognize these manuscripts as text. This thesis used a state-of-the-art Handwritten Text Recognizer, TrOCR, to recognize a 16^th-century manuscript. TrOCR uses a vision transformer to encode the input images and a language transformer to decode them back to text. We showed that carefully preprocessed images and designed augmentations can improve the performance of TrOCR. We suggest an ensemble of augmented models to achieve an even better performance.

Decoding Usage And Adoption Behavior Of The Low-Carbon Transportation Market: An Ai-Driven Exploration, Vuban Chowdhury

Graduate Theses and Dissertations

The transportation sector stands as a significant contributor to greenhouse gas emissions in the United States, with its environmental impact steadily escalating over the past few decades. This has prompted government agencies to facilitate the adoption and usage of low-carbon transportation (LCT) options as alternatives to fossil-fuel-powered transportation. LCTs include modes of transportation that minimize the overall carbon footprint of the transportation sector by relying on energy sources that are environmentally sustainable. These sustainable transportation options have also garnered significant interest in the transportation research community. For government agencies and researchers alike, a comprehensive understanding of the adoption and usage …

Demystifying Artificial Intelligence (Ai) For Early Childhood And Elementary Education: A Case Study Of Perceptions Of Ai Of State Of Missouri Educators, Kathryn Arnone, James Hutson, Karen Woodruff

Faculty Scholarship

Artificial intelligence (AI) and its impact on society have received a great deal of attention in the past five years since the first Stanford AI100 report. AI already globally impacts individuals in critical and personal ways, and many industries will continue to experience disruptions as the full algorithmic effects are understood. However, with regard to education, adopting in disciplines remains limited largely to Computer Science and Information Technology in postsecondary education. Recent advances with technology are especially promising for their potential to create and scale personalized learning for students, to optimize strategies for learning outcomes, and to increase access to …

Dropped Objects Recognition In Offshore Operations Based On Computer Vision And Artificial Intelligence, Xiaochuan Yu

LSU New Orleans Theses and Dissertations

We are more interested in recovering and salvaging containers which may be loaded with either valuable or harmful substances. Therefore, we designed various container models to account for different loading conditions and then exported them to a 3D printer. Six small container models were dropped into the trailer pool at the University of New Orleans (UNO) as planned at angles of 0°, 45°, and 90°.

After collecting all the videos using a high-definition camera set outside the tank, we perform pre-processing tasks on the videos in preparation for model training. The two-phase angle classification method uses a pretrained ResNet50 model …

Exploring Students' Adoption Of Chatgpt As A Mentor For Undergraduate Computing Projects: Pls-Sem Analysis, Gottipati Swapna, Kyong Jin Shim, Shankararaman, Venky

Research Collection School Of Computing and Information Systems

As computing projects increasingly become a core component of undergraduate courses, effective mentorship is crucial for supporting students' learning and development. Our study examines the adoption of ChatGPT as a mentor for undergraduate computing projects. It explores the impact of ChatGPT mentorship, specifically, skills development, and mentor responsiveness, i.e., ChatGPT's responsiveness to students' needs and requests. We utilize PLS-SEM to investigate the interrelationships between different factors and develop a model that captures their contribution to the effectiveness of ChatGPT as a mentor. The findings suggest that mentor responsiveness and technical/design support are key factors for the adoption of AI tools …

Data-Driven Decision Support Tool Co-Development With A Primary Health Care Practice Based Learning Network, Jacqueline K. Kueper, Jennifer Rayner, Sara Bhatti, Kelly Angevaare, Sandra Fitzpatrick, Paulino Lucamba, Eric Sutherland, Daniel J. Lizotte

Epidemiology and Biostatistics Publications

Background: The Alliance for Healthier Communities is a learning health system that supports Community Health Centres (CHCs) across Ontario, Canada to provide team-based primary health care to people who otherwise experience barriers to care. This case study describes the ongoing process and lessons learned from the first Alliance for Healthier Communities’ Practice Based Learning Network (PBLN) data-driven decision support tool co-development project.

Methods: We employ an iterative approach to problem identification and methods development for the decision support tool, moving between discussion sessions and case studies with CHC electronic health record (EHR) data. We summarize our work to date in …

Smartphone Based Object Detection For Shark Spotting, Darrick W. Oliver

Master's Theses

Given concern over shark attacks in coastal regions, the recent use of unmanned aerial vehicles (UAVs), or drones, has increased to ensure the safety of beachgoers. However, much of city officials' process remains manual, with drone operation and review of footage still playing a significant role. In pursuit of a more automated solution, researchers have turned to the usage of neural networks to perform detection of sharks and other marine life. For on-device solutions, this has historically required assembling individual hardware components to form an embedded system to utilize the machine learning model. This means that the camera, neural processing …

Ethics And Social Justice For Ai In Data Science, Arya Ramchander, Kylene Nicole Landenberger

College of Engineering Summer Undergraduate Research Program

The advances of AI raise several critical questions about human values and ethics, highlighting the need for researchers and developers to consider the ethical implications and the risks of neglecting them. In the past few years, student researchers have developed an AI model that allows users to test their surveys for possible breaches of subject confidentiality. This allows the users to gauge the ethicality of their proposal. This summer, we have expanded on this research and launched an interactive model for students and researches to assess their current work for ethical and social justice implications. Using Langchain and Figma, we …

Ai For Search And Rescue - Locating A Missing Person, David Hernandez, Sai Rama Balakrishnan, Timmy Chin, Aditya Manikonda, Vasanth Pugalenthi

College of Engineering Summer Undergraduate Research Program

Building on the work done initially as a SURP 2021 project and continued through 2021-23, the focus for this summer project will be on the use of computer technology for locating a missing person. Over the last year, we developed the digital equivalents of about 30 paper-based S&R forms and the infrastructure to collect the respective information. In their current use, these paper forms are filled out by search teams, collected in a command post, and reviewed by search coordinators. This process is time-consuming, prone to errors and loss of information, and relies heavily on the experience, skills, and mental …

Online Aircraft System Identification Using A Novel Parameter Informed Reinforcement Learning Method, Nathan Schaff

Doctoral Dissertations and Master's Theses

This thesis presents the development and analysis of a novel method for training reinforcement learning neural networks for online aircraft system identification of multiple similar linear systems, such as all fixed wing aircraft. This approach, termed Parameter Informed Reinforcement Learning (PIRL), dictates that reinforcement learning neural networks should be trained using input and output trajectory/history data as is convention; however, the PIRL method also includes any known and relevant aircraft parameters, such as airspeed, altitude, center of gravity location and/or others. Through this, the PIRL Agent is better suited to identify novel/test-set aircraft.

First, the PIRL method is applied to …

Balanced Blended Space: Proposing A Universal Theoretical Framework For Combinative Reality, David Smith, Frederick Bianchi

Publications and Research

In today's fragmented societies, a unified framework for communication and collaboration across different realities is crucial. We introduce Balanced Blended Space (BBS) as a framework for describing combinative reality, encompassing virtual, physical, and conceptual realms, all intrinsically connected. Interactions within these environments shape our perceptual space. This paper outlines key axiomatic assumptions, criteria for a universal framework, and fundamental terminology. We identify deep symmetries enabling the BBS framework, including Cognitive and Computational Symmetry, Physical and Virtual Symmetry, Mediation Pathway Symmetry, Space-Time Symmetry, and Sensory Symmetry. We propose tests to determine its viability, emphasizing virtual intelligence as a collaborative partner. We …