Graphics and Human Computer Interfaces Commons^™

Are Academia And Industry Listening To Each Other? A Citation Analysis Of Ux Research Methods Resources, Abigail Bakke, Leonard Dibono

English Department Publications

Technical and Professional Communication (TPC) has been facing concerns of viability, in both its relationship with industry and its ability to build a relevant and valid body of research. TPC’s disconnection with industry may be reflected in its relationship to UX as well, despite both fields’ shared values. To better understand how TPC and User Experience (UX) are relating to each other, we conducted a citation analysis of a sample of SIGDOC papers and a sample of Nielsen Norman Group (NN/g) practitioner articles focused on research methods. The SIGDOC papers tended to cite TPC sources, while the NN/g articles cited …

Dung Dkar Cloak: Exploring Soft Interfaces For Sonic Interactions, Judit Eszter Kárpáti, Esteban De La Torre

Textile Society of America: Symposium Proceedings

The importance of crossmodal interaction within the contemporary cultural, technological and scientific panorama has evidently gained significant attention due to its remarkable advantages in creating a meaningful, interwoven, and integrated experience. The use and recontextualization of textiles in such exploratory quest into the human senses has proven to be critical. Computational science, algorithmic logic and digital devices have always been rooted and closely interwoven with textile crafts and practices. Recent technological advancements have further combined technology and textile, generating interactive textile surfaces, constructing endless possibilities for multisensorial experiences. In this presentation we will examine how we can weave a sensitive …

How Economically Marginalized Adolescents Of Color Negotiate Critical Pedagogy In A Computing Classroom, Jean Salac, Lena Armstrong, Megumi Kivuva, Jayne Everson, Amy J. Ko

Computer Science Faculty Work

Background and Context: With the growing movement to adopt critical framings of computing, scholars have worked to reframe computing education from the narrow development of programming skills to skills in identifying and resisting oppressive structures in computing. However, we have little guidance on how these framings may manifest in classroom practice. Objectives: To better understand the processes and practice of critical pedagogy in a computing classrooms, we taught a critically conscious computing elective within a summer academic program at a northwest United States university targeted at secondary students (ages 14–18) from low-income backgrounds and would be the first …

Advancing Policy Insights: Opinion Data Analysis And Discourse Structuring Using Llms, Aaditya Bhatia

Graduate Thesis and Dissertation 2023-2024

The growing volume of opinion data presents a significant challenge for policymakers striving to distill public sentiment into actionable decisions. This study aims to explore the capability of large language models (LLMs) to synthesize public opinion data into coherent policy recommendations. We specifically leverage Mistral 7B and Mixtral 8x7B models for text generation and have developed an architecture to process vast amounts of unstructured information, integrate diverse viewpoints, and extract actionable insights aligned with public opinion. Using a retrospective data analysis of the Polis platform debates published by the Computational Democracy Project, this study examines multiple datasets that span local …

Living Datasets: Towards Data-Centric Ai Explainability And Bias Mitigation, Akib Zaman

Computer Science and Engineering Dissertations - Archive

Benchmark datasets are critical to the evolution of AI efforts yet often embed unintended biases that influence the models that drive human-AI interactions. A deeper inspection and awareness of data is needed to understand the biases datasets may contain. In this dissertation, I introduce the Tag-and-Release method, inspired from wildlife research, that treats data as an organism and examines how different environments (i.e., CNNs) select for unique traits or characteristics that ultimately impact data's survival. Using the canonical MNIST handwritten digit dataset as a case study, I describe how the Tag-and-Release method can be used to analyze how dataset imbalance …

A Unified Cross-Modal Interactive System For Assisting Vision Impaired In Human Navigation And Indoor Based Human Robot Interaction, Harish Ram Nambiappan

Computer Science and Engineering Dissertations - Archive

People who are blind and vision impaired often require assistance in performing various tasks. With new technologies emerging in the recent years, vision impaired people either require assistance in accessing those technologies or in using those technologies to perform different tasks in real life. Previous works have focused on assisting vision impaired people in different scenarios such as navigation, accessing smartphone interfaces etc. With the recent developments in robotics, a new research has emerged where new systems can be developed for vision impaired people to interact with robots to perform various human robot interactive tasks. But with developing new and …

Flexible Attenuation Fields: Tomographic Reconstruction From Heterogeneous Datasets, Clifford S. Parker

Theses and Dissertations--Computer Science

Traditional reconstruction methods for X-ray computed tomography (CT) are highly constrained in the variety of input datasets they admit. Many of the imaging settings -- the incident energy, field-of-view, effective resolution -- remain fixed across projection images, and the only real variance is in the detector's position and orientation with respect to the scene. In contrast, methods for 3D reconstruction of natural scenes are extremely flexible to the geometric and photometric properties of the input datasets, readily accepting and benefiting from images captured under varying lighting conditions, with different cameras, and at disparate points in time and space. Extending CT …

Escape The Planet: Revolutionizing Game Design With Novel Oop Techniques, Qusai Kamal Fannoun

All Graduate Theses, Dissertations, and Other Capstone Projects

Mobile devices are continuously evolving and greater computing power and graphics capabilities are being introduced every year. As a result, there is an increasing demand for challenging and engaging mobile games that leverage these advanced features. This project explores best design practices using the development of Escape the Planet, which is an intricate maze game for mobile devices in which players navigate using a spaceship that is trapped in a hostile planet’s maze while avoiding obstacles and enemy attacks. The goal is to safely guide the spaceship out of the maze without colliding into walls or taking bullets from defensive …

Poster, Performed: Understanding Public Opinions Of Authorship In Generative Artificial Intelligence Models Via Analogy, Wylie Z. Kasai

Dartmouth College Master’s Theses

Over the last decade, generative artificial intelligence models have advanced significantly and provided the public with several tools to create new works of art. However, the true authorship of these works has been debated due to their training on web-scraped data. Serving as an analogy to these larger models, Poster, Performed is an interactive artificial intelligence exhibition project that uses image assets submitted by the public to create poster compositions with custom image processing algorithms. During the course of a four-day exhibition, visitors were asked to identify the exhibition’s primary artist from five options: (1) participants who submitted image assets, …

Predicting An Optimal Medication/Prescription Regimen For Patient Discordant Chronic Comorbidities Using Multi-Output Models, Ichchha Pradeep Sharma, Tam Nguyen, Shruti Ajay Singh, Tom Ongwere

Computer Science Faculty Publications

This paper focuses on addressing the complex healthcare needs of patients struggling with discordant chronic comorbidities (DCCs). Managing these patients within the current healthcare system often proves to be a challenging process, characterized by evolving treatment needs necessitating multiple medical appointments and coordination among different clinical specialists. This makes it difficult for both patients and healthcare providers to set and prioritize medications and understand potential drug interactions. The primary motivation of this research is the need to reduce medication conflict and optimize medication regimens for individuals with DCCs. To achieve this, we allowed patients to specify their health conditions and …

The Process Of Video Game Development: Watermelon Willy, Jade Westgor

University Honors Program Senior Projects

Developing a video game requires and provides skills that can be very helpful for computer science students, as well as skills that relate to storytelling/worldbuilding, organization, and artistic expression. This paper goes over the process I have taken in order to design, develop, and evaluate the game Watermelon Willy from the very start to alpha testing. The process started some time ago with the idea being present in my head for a while, however the project started with some basic storyboards to map out some of the fundamental aspects of the game. Coding began with a simple template, which was …

Garbage In ≠ Garbage Out: Exploring Gan Resilience To Image Training Set Degradations, Nicholas Crino, Bruce A. Cox, Nathan B. Gaw

Faculty Publications

Generative Adversarial Networks (GANs) have received immense attention in recent years due to their ability to capture complex, high-dimensional data distributions without the need for extensive labeling. Since their conception in 2014, a wide array of GAN variants have been proposed featuring alternative architectures, optimizers, and loss functions with the goal of improving performance and training stability. This manuscript focuses on quantifying the resilience of a GAN architecture to specific modes of image degradation. We conduct systematic experimentation to empirically determine the effects of 10 fundamental image degradation modes, applied to the training image dataset, on the Fréchet inception distance …

(Meta-)Physical Artworks: Digital Augmentation In Art Observation, Macy A. Toppan

Dartmouth College Master’s Theses

Augmented art— the subgenre of art that incorporates physical and digital artwork— is a rapidly growing field driven by advancing technology and a new generation for whom that tech is a given. Yet the presence of media like augmented and virtual reality in exhibition remains a controversial subject. Rather than focusing on the many theoretical debates about whether digital pieces can qualify as "good" art, we study it in practice through the eyes of the casual art observer. This paper highlights the audience in a within-participant study that asked viewers to take in a physical sculpture intentionally built with virtual …

The Impact Of Eye-Tracking On Mixed Reality Typing, Cecilia Schmitz

Dissertations, Master's Theses and Master's Reports

Accuracy and speed are pivotal when typing. We hypothesized that the lack of tactile feedback on midair mixed reality keyboards may adversely impact typing performance, especially when ten fingers are used to type. We examined the differences in performance when participants typed on a virtual keyboard using just their index fingers versus all ten fingers. The keyboard was deterministic (without auto-correct), relied only on the headset's egocentric cameras for sensing, and included symbol keys. We used a novel eye-tracking technique to mitigate accidental key presses. The technique was successful at reducing error rates, though participants still typed faster using their …

Tension Control And Interproximation Techniques Forshape Design And Rgb-Depth Segmentation Reconstruction And Modeling, Anastasia Kazadi

Theses and Dissertations--Computer Science

Human eyes possess remarkable capabilities to perceive and interpret a wealth of information about our environment; from discerning colors and depths to identifying object boundaries and navigating obstacles, our eyes serve as invaluable guides in our daily lives. Ongoing research in the fields of computer vision and computer graphics continuously explore the ways to replicate extraordinary human vision abilities in order to develop systems and frameworks which would enable computers to capture, analyze, and act upon discerned information. In this context, this dissertation seeks to investigate and automate various shape control and data processing techniques for 3D modeling and shape …

Visual Analysis Of Enterprise Network Public Opinion Events And Research On Crisis Public Relations Strategy：Taking The “Haitian Soy Sauce Incident”As An Example, Danlin Xie, Xisheng Hu, Weishu Yang

Journal of Scientific Information Research

[Purpose/significance]In the information age with decentralized discourse power, the channels for the public to publicly express their opinions and participate in topic discussions are increasing. The exchange and dissemination of online public opinion on low-ignition events will undoubtedly increase the heat of the event and bring greater pressure and challenges to corporate crisis public relations. [Method/process]Taking "Haitian soy sauce event" as an example, this paper discusses the stage of network public opinion dissemination of the event, uses ROST CM to carry out high-frequency word statistics and public sentiment tendency analysis, and uses Ucinet and Gephi to analyze the social network …

Human-Centered Machine Learning With Interpretable Visual Knowledge Discovery, Lincoln Huber

All Master's Theses

This research advances interpretable machine learning (ML) by introducing hyperblocks (HBs) as a structured, rule-based approach for creating transparent and accurate models using meaningful numeric attributes directly interpretable to end users. Key techniques, including Parallel Hyperblock Creation, Interactive Hyperblock Creation, Level n Hyperblock Creation, and k-Nearest Neighbor Hyperblock, provide a framework that ensures domain experts can meaningfully engage with the model’s decision-making process through lossless visualizations using General Line Coordinates (GLC). Case studies with the Wisconsin Breast Cancer and MNIST datasets demonstrated HBs' effectiveness in handling high-risk and complex classification tasks, offering interpretable accuracy that traditional models struggle to achieve. …

Predicting Viral Rumors And Vulnerable Users With Graph-Based Neural Multi-Task Learning For Infodemic Surveillance, Xuan Zhang, Wei Gao

Research Collection School Of Computing and Information Systems

In the age of the infodemic, it is crucial to have tools for effectively monitoring the spread of rampant rumors that can quickly go viral, as well as identifying vulnerable users who may be more susceptible to spreading such misinformation. This proactive approach allows for timely preventive measures to be taken, mitigating the negative impact of false information on society. We propose a novel approach to predict viral rumors and vulnerable users using a unified graph neural network model. We pre-train network-based user embeddings and leverage a cross-attention mechanism between users and posts, together with a community-enhanced vulnerability propagation (CVP) …

Differences In Student-Ai Interaction Process On A Drawing Task: Focusing On Students' Attitude Towards Ai And The Level Of Drawing Skills, Jinhee Kim, Yoonhee Ham, Sang-Soog Lee

STEMPS Faculty Publications

Recent advances and applications of artificial intelligence (AI) have increased the opportunities for students to interact with AI in their learning tasks. Although various fields of scholarly research have investigated human-AI collaboration, the underlying processes of how students collaborate with AI in a student-AI teaming scenario have been scarcely investigated. To develop effective AI applications in education, it is necessary to understand differences in the student-AI interaction (SAI) process depending on students' characteristics. The present study attempts to fill this gap by exploring the differences in the SAI process amongst students with varying drawing proficiencies and attitudes towards AI in …

‘I Know It When I See It’– Developing Quality Schedules Considering Subjective Or Unspecified Criteria, Douglas L. Moody

Publications and Research

Most timetabling problems have a given objective function to measure the quality of a solution. However, users may have a “I know it when I see it” recognition of a quality schedule, without specifying the complete basis for their judgment. In this situation, the objective function cannot be exclusively used as a solution quality measurement. This work presents an AI based approach to aid in categorizing the solution’s quality when the users have not explicitly defined all factors used in their criteria.

Demonstrating Canvas-Based Processing Of Multiple Camera Streams At The Edge, Ila Gokarn, Hemanth Sabbella, Yigong Hu, Tarek Abdelzaher, Archan Misra

Research Collection School Of Computing and Information Systems

We demonstrate criticality-aware canvas-based processing of multiple concurrent camera streams at the resource constrained edge to show substantial improvement in the accuracy-throughput trade-off. The proposed system focuses the available computation resources on select Regions of Interest (RoI) across all the camera streams by (i) extracting RoI from the input camera stream (ii) 2D bin packing the RoI on a canvas frame and (iii) batching and inferring upon these constructed composite canvas frames with a YOLOv5 object detection model. Our experiments show that such canvas-based processing can (i) sustain real-time processing throughput of 23 FPS per camera across 6 concurrent input …

Glance To Count: Learning To Rank With Anchors For Weakly-Supervised Crowd Counting, Zheng Xiong, Liangyu Chai, Wenxi Liu, Yongtuo Liu, Sucheng Ren, Shengfeng He

Research Collection School Of Computing and Information Systems

Crowd image is arguably one of the most laborious data to annotate. In this paper, we devote to reduce the massive demand of densely labeled crowd data, and propose a novel weakly-supervised setting, in which we leverage the binary ranking of two images with highcontrast crowd counts as training guidance. To enable training under this new setting, we convert the crowd count regression problem to a ranking potential prediction problem. In particular, we tailor a Siamese Ranking Network that predicts the potential scores of two images indicating the ordering of the counts. Hence, the ultimate goal is to assign appropriate …

Virtual Reality & Pilot Training: Existing Technologies, Challenges & Opportunities, Tim Marron, Niall Dungan, Brian Mac Namee, Anna Donnla O'Hagan

Journal of Aviation/Aerospace Education & Research

The introduction of virtual reality (VR) to flying training has recently gained much attention, with numerous VR companies, such as Loft Dynamics and VRpilot, looking to enhance the training process. Such a considerable change to how pilots are trained is a subject that warrants careful consideration. Examining the effect that VR has on learning in other areas gives us an idea of how VR can be suitably applied to flying training. Some of the benefits offered by VR include increased safety, decreased costs, and increased environmental sustainability. Nevertheless, some challenges ahead for developers to consider are negative transfer of learning, …

Bias-Aware Gaze Uniformity Assessment In Group Images, Omkar Kulkarni

Electronic Theses & Dissertations (2024 - present)

Today, more than 5 billion photos are captured every day, with smartphones generating over 94\% of these images. However, despite advancements in technology, achieving aesthetically pleasing group photos remains challenging, especially when it comes to aligning the direction of everyone’s gaze. While current methods focus on facial features, they often fail to ensure consistent gaze direction. The introduction of the iPhone's Live mode, which captures a 1.5-second video snippet along with still images, complicates the selection of the best key photo due to its subjective nature and a lack of publicly available data, especially during the pandemic.

To address these …

Consistent Monte Carlo Methods For Non-Linear Applications In Light Transport, Zackary T. Misso

Dartmouth College Ph.D Dissertations

The study of light transport focuses on describing the propagation of light from emitters to sensors through accurately describing the interactions light can undergo with everything in between. Physically-based rendering is the process of applying the laws of light transport to formulate practical algorithms which simulate the flow of light for the purpose of synthesizing images of virtual environments.

Unfortunately, there are very few interesting scene configurations which can be computed analytically. Instead, modern solutions predominantly rely on Monte Carlo integration to stochastically estimate the transfer of light since the process is both unbiased and consistent. Meaning, it is expected …

Towards Dynamic Context Detection From Voice Commands And Conversations With Smart Assistants In Smart Homes, Jeniya Sultana

Graduate Theses/Dissertations

Voice-enabled interactions have become increasingly popular with the rise of voice assistants. Identifying contexts or meanings from voice commands and conversations with smart assistants can contribute to the autonomous control of smart home devices and appliances. To improve automation, there is a growing need for efficient context detection that eliminates the need to memorize voice commands. To address this need, I followed a two-step approach in my research. In the first step, I developed a unique context recognition model using a transformer, an attention mechanism, and a fully connected neural network. I trained this model on a conversational dataset of …

Scene Understanding And Spatial Analysis Using Scene Graph Enhanced By Hall's Proxemics Zones In Smart Homes, Debaleen Das Spandan

Graduate Theses/Dissertations

Voice-controlled smart assistants have received widespread popularity. It plays a pivotal role in smart homes by providing a natural and convenient interface for interacting with smart devices. However, these assistants are unable to serve persons with physical disabilities and speech impairments. Therefore, non-verbal communication methods, such as eye tracking, gesture recognition, and context awareness can complement and overcome some of these limitations to enhance user experience in smart homes. To address this issue, I am investigating non-verbal communication methods to make smart home technology more accessible and intuitive. In this research, I focus on proxemics, i.e., the study of distance …

Programming By Voice, Sadia Nowrin

Dissertations, Master's Theses and Master's Reports

Programmers typically rely on a keyboard and mouse for input, which poses significant challenges for individuals with motor impairments, limiting their ability
to effectively input programs. Voice-based programming offers a promising alternative,
enabling a more inclusive and accessible programming environment. Insights from interviews with motor-impaired programmers revealed that memorizing unnatural commands in existing voice-based programming systems led to frustration. In this work, we explore how programmers naturally speak a single line of code and present a comprehensive methodology for a voice programming system aimed at making programming more accessible for diverse users. To achieve this, we adopted a two-step pipeline. …

Enhancing Students’ User Experience With A Code Critiquer, Laura E. Albrant

Dissertations, Master's Theses and Master's Reports

This thesis explores the role of human factors in the realm of code critiquers and students’ experiences with them. Across three studies, the work utilized Design Thinking to improve the user experience of WebTA for introductory engineering students learning MATLAB. The first two studies gathered observational and interview data to empathize, define, and ideate a new user interface (UI). Said UI was prototyped and then tested with the third study. Overall, the surveys’ data suggests that most students found the new design to be more appealing, useful, and purposeful; however, there is still plenty of room for improvement. Additionally, analysis …

Tracking People Across Ultra Populated Indoor Spaces By Matching Unreliable Wi-Fi Signals With Disconnected Video Feeds, Quang Hai Truong, Dheryta Jaisinghani, Shubham Jain, Arunesh Sinha, Jeong Gil Ko, Rajesh Krishna Balan

Research Collection School Of Computing and Information Systems

Tracking in dense indoor environments where several thousands of people move around is an extremely challenging problem. In this paper, we present a system — DenseTrack for tracking people in such environments. DenseTrack leverages data from the sensing modalities that are already present in these environments — Wi-Fi (from enterprise network deployments) and Video (from surveillance cameras). We combine Wi-Fi information with video data to overcome the individual errors induced by these modalities. More precisely, the locations derived from video are used to overcome the localization errors inherent in using Wi-Fi signals where precise Wi-Fi MAC IDs are used to …