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Articles 151 - 180 of 191
Full-Text Articles in Graphics and Human Computer Interfaces
Safe Space: To Help Minimize Cyberbullying And Support Social Well-Being, Eiman Rana
Safe Space: To Help Minimize Cyberbullying And Support Social Well-Being, Eiman Rana
CISLA Senior Integrative Projects
The perverseness of cyberbullying as a growing and serious form of abuse with the potential for harm among children and youth needs to be recognized. In a resource-limited setting such as South Asia where youth have very little access to counseling within schools, the implications for mental health should be recognized. This research study explores whether our youth is capable of using technology in the right way to minimize cyberbullying and support social well-being.
Index Terms - Cyberbullying, Social Well-being, User Experience Design, and Usability Study.
X-Disetrac: Distributed Eye-Tracking With Extended Realities, Bhanuka Mahanama, Sampath Jayarathna
X-Disetrac: Distributed Eye-Tracking With Extended Realities, Bhanuka Mahanama, Sampath Jayarathna
College of Sciences Posters
Humans use heterogeneous collaboration mediums such as in-person, online, and extended realities for day-to-day activities. Identifying patterns in viewpoints and pupillary responses (a.k.a eye-tracking data) provide informative cues on individual and collective behavior during collaborative tasks. Despite the increasing ubiquity of these different mediums, the aggregation and analysis of eye-tracking data in heterogeneous collaborative environments remain unexplored. Our study proposes X-DisETrac: Extended Distributed Eye Tracking, a versatile framework for eye tracking in heterogeneous environments. Our approach tackles the complexity by establishing a platform-agnostic communication protocol encompassing three data streams to simplify data aggregation and …
Co-Design Of An Interactive Wellness Park: Exploring Design Requirements For A Multimodal Outdoor Physical Web Installation With Older Adults, Fatima Badmos
Academic Posters Collection
The global demographic landscape is experiencing a notable shift, characterised by a growing proportion of adults over 60. According to projections, the proportion of individuals aged 60 and above is expected to reach one-sixth of the global population by 2030. Furthermore, by 2050, this demographic is projected to exceed a staggering two billion people. Amidst this shift, there is an urgent need to develop interactive and innovative solutions to address older adults' unique challenges, particularly in outdoor physical activity.
A co-design methodology involving older adults’ participation from the idea generation to the application development process will be adopted to address …
A Visual Tour Of Dynamical Systems On Color Space, Jonathan Maltsman
A Visual Tour Of Dynamical Systems On Color Space, Jonathan Maltsman
HMC Senior Theses
We can think of a pixel as a particle in three dimensional space, where its x, y and z coordinates correspond to its level of red, green, and blue, respectively. Just as a particle’s motion is guided by physical rules like gravity, we can construct rules to guide a pixel’s motion through color space. We can develop striking visuals by applying these rules, called dynamical systems, onto images using animation engines. This project explores a number of these systems while exposing the underlying algebraic structure of color space. We also build and demonstrate a Visual DJ circuit board for …
Visualization Teaching Tool For Computational Geometry Algorithms, Seth Spire
Visualization Teaching Tool For Computational Geometry Algorithms, Seth Spire
Honors Projects
Computational geometry is a branch of computer science dedicated to the study and development of algorithms that solve geometric problems. These algorithms are often complex, so this project involves the development of a teaching tool for various computational geometry algorithms. A Node app was developed which allows a user to create their own inputs for an algorithm and watch a visualization of how an algorithm solves one of the various problems. There is highlighted pseudocode matching the steps of the visualization along with more in-depth writeups of the inner workings of the algorithm. 4 algorithms have been implemented in the …
Causal Interventional Training For Image Recognition, Wei Qin, Hanwang Zhang, Richang Hong, Ee-Peng Lim, Qianru Sun
Causal Interventional Training For Image Recognition, Wei Qin, Hanwang Zhang, Richang Hong, Ee-Peng Lim, Qianru Sun
Research Collection School Of Computing and Information Systems
Deep learning models often fit undesired dataset bias in training. In this paper, we formulate the bias using causal inference, which helps us uncover the ever-elusive causalities among the key factors in training, and thus pursue the desired causal effect without the bias. We start from revisiting the process of building a visual recognition system, and then propose a structural causal model (SCM) for the key variables involved in dataset collection and recognition model: object, common sense, bias, context, and label prediction. Based on the SCM, one can observe that there are “good” and “bad” biases. Intuitively, in the image …
Relation Preserving Triplet Mining For Stabilising The Triplet Loss In Re-Identification Systems, Adhiraj Ghosh, Kuruparan Shanmugalingam, Wen-Yan Lin
Relation Preserving Triplet Mining For Stabilising The Triplet Loss In Re-Identification Systems, Adhiraj Ghosh, Kuruparan Shanmugalingam, Wen-Yan Lin
Research Collection School Of Computing and Information Systems
Object appearances change dramatically with pose variations. This creates a challenge for embedding schemes that seek to map instances with the same object ID to locations that are as close as possible. This issue becomes significantly heightened in complex computer vision tasks such as re-identification(reID). In this paper, we suggest that these dramatic appearance changes are indications that an object ID is composed of multiple natural groups, and it is counterproductive to forcefully map instances from different groups to a common location. This leads us to introduce Relation Preserving Triplet Mining (RPTM), a feature matching guided triplet mining scheme, that …
An Interactive System For Generating Music From Moving Images, Hanlin Wang
An Interactive System For Generating Music From Moving Images, Hanlin Wang
Dartmouth College Master’s Theses
Moving images contain a wealth of information pertaining to motion. Motivated by the interconnectedness of music and movement, we present a framework for transforming the kinetic qualities of moving images into music. We developed an interactive software system that takes video as input and maps its motion attributes into the musical dimension based on perceptually grounded principles. The system combines existing sonification frameworks with theories and techniques of generative music. To evaluate the system, we conducted a two-part experiment. First, we asked participants to make judgements on video-audio correspondence from clips generated by the system. Second, we asked participants to …
Collaborative Consultation Doctors Model: Unifying Cnn And Vit For Covid-19 Diagnostic, Trong-Thuan Nguyen, Tam Nguyen, Minh-Triet Tran
Collaborative Consultation Doctors Model: Unifying Cnn And Vit For Covid-19 Diagnostic, Trong-Thuan Nguyen, Tam Nguyen, Minh-Triet Tran
Computer Science Faculty Publications
The COVID-19 pandemic presents significant challenges due to its high transmissibility and mortality risk. Traditional diagnostic methods, such as RT-PCR, have limitations that hinder timely and accurate screening. In response, AI-powered computer-aided imaging analysis techniques have emerged as a promising alternative for COVID-19 diagnosis. In this paper, we propose a novel approach that combines the strengths of Convolutional Neural Network (CNN) and Vision Transformer (ViT) to enhance the performance of COVID-19 diagnosis models. CNN excels at capturing spatial features in medical images, while ViT leverages self-attention mechanisms inspired by human radiologists. Additionally, our approach draws inspiration from subclinical diagnosis, a …
Model Checking Time Window Temporal Logic For Hyperproperties, Ernest Bonnah, Luan Viet Nguyen, Khaza Anuarul Hoque
Model Checking Time Window Temporal Logic For Hyperproperties, Ernest Bonnah, Luan Viet Nguyen, Khaza Anuarul Hoque
Computer Science Faculty Publications
Hyperproperties extend trace properties to express properties of sets of traces, and they are increasingly popular in specifying various security and performance-related properties in domains such as cyber-physical systems, smart grids, and automotive. This paper introduces HyperTWTL, which extends Time Window Temporal Logic (TWTL)-a domain-specific formal specification language for robotics, by allowing explicit and simultaneous quantification over multiple execution traces. We propose two different semantics for HyperTWTL, synchronous and asynchronous, based on the alignment of the timestamps in the traces. Consequently, we demonstrate the application of HyperTWTL in formalizing important information-flow security policies and concurrency for robotics applications. Furthermore, we …
Uit-Adrone: A Novel Drone Dataset For Traffic Anomaly Detection, Tung Minh Tran, Tu N. Vu, Tam Nguyen, Khang Nguyen
Uit-Adrone: A Novel Drone Dataset For Traffic Anomaly Detection, Tung Minh Tran, Tu N. Vu, Tam Nguyen, Khang Nguyen
Computer Science Faculty Publications
Anomaly detection plays an increasingly important role in video surveillance and is one of the issues that have attracted various communities, such as computer vision, machine learning, and data mining in recent years. Moreover, drones equipped with cameras have quickly been deployed to a wide range of applications, starting from border security applications to street monitoring systems. However, there is a notable lack of adequate drone-based datasets available to detect unusual events in the urban traffic environment, especially in roundabouts, due to the density of interaction between road users and vehicles. To promote the development of anomalous event detection with …
Exploring The Integration Of Patient Generated Health Data In A Fair Digital Health System In Low-Resourced Settings: A User-Centered Approach, Abdullahi Abubakar Kawu, Rens Kievit, Adamu Abubakar, Mirjam Van Reisen, Dympna O'Sullivan, Lucy Hederman
Exploring The Integration Of Patient Generated Health Data In A Fair Digital Health System In Low-Resourced Settings: A User-Centered Approach, Abdullahi Abubakar Kawu, Rens Kievit, Adamu Abubakar, Mirjam Van Reisen, Dympna O'Sullivan, Lucy Hederman
Conference papers
This article presents the initial user-centered research exploring the opportunities in the collection of Patient-Generated Health Data (PGHD) within the context of a project aimed at improving health management and outcomes among residents in African countries. Through interviews with a doctor, a patient and two data managers, the local status and opinions regarding PGHD collection, integration and use are investigated. The findings suggest that PGHD have only been encountered in paper forms - and are mostly patient driven, however opportunities for PGHD for the facility and patient were identified and included supporting the treatment of whitecollar hypertension, treatment planning and …
Directional Speaker Poster, Eugene Ng, Bryan Wong, Ruhaan Das
Directional Speaker Poster, Eugene Ng, Bryan Wong, Ruhaan Das
Student Works
Changi Airport is set to expand with a new terminal, Terminal 5. Currently, many of the airport's processes are manual, requiring a high dependence on staff. This proposal aims to incorporate automation and AI for a smoother passenger experience.
Multimodal Game-Based Learning In Post-Secondary Education, Nathan A. Vanos
Multimodal Game-Based Learning In Post-Secondary Education, Nathan A. Vanos
EWU Masters Thesis Collection
In this age of unprecedented technological proliferation, educators have been given a unique opportunity to enhance classroom engagement. That opportunity is multimodal game-based learning (MGBL): classroom instruction through a combination of games and multiple modalities of information. Using today’s 3D systems and virtual reality tools, this concept can be explored to depths never before possible. The aim of this project was to design and implement an application that could be used to evaluate how MGBL could impact student engagement and learning, specifically at the post-secondary level. The application implemented during this work was a 3D and virtual reality Simulator for …
Digital Nudges: An Investigation Of Both Consumer And Designer Perspectives, Ja-Naé Duane
Digital Nudges: An Investigation Of Both Consumer And Designer Perspectives, Ja-Naé Duane
2023
This dissertation explores how knowledge of digital nudges impacts consumer decisions, and how consumer preferences based on that knowledge impacts design decisions. Paper 1 presents a systematic narrative literature review on the evolution of digital nudge literature. This investigation uncovers several themes and provides a basis for a revised definition of digital nudges and a taxonomy wheel of digital nudges. Paper 2 (co-authored with Jeffrey Livingston, Jonathan Ericson, and Patrick McHugh) investigates how knowledge about digital nudges impacts consumer preferences to have them within the digital experiences they use. This paper highlights how knowledge of digital nudges impact consumer online …
Simulating Incompressible Thin-Film Fluid With A Moving Eulerian-Lagrangian Particle Method, Yitong Deng
Simulating Incompressible Thin-Film Fluid With A Moving Eulerian-Lagrangian Particle Method, Yitong Deng
Dartmouth College Master’s Theses
In this thesis, we introduce a Moving Eulerian-Lagrangian Particle (MELP) method, a mesh-free method to simulate incompressible thin-film fluid systems: soap bubbles, bubble clusters, and foams. The realistic simulation of such systems depends upon the successful treatment of three aspects: (1) the soap film's deformation due to the tendency to minimize the surface energy, giving rise to the bouncy characteristics of soap bubbles, (2) the tangential fluid flow on the thin film, causing the thickness to vary spatially, which in conjunction with thin-film interference creates evolving and highly sophisticated iridescent color patterns, (3) the topological changes due to collision, separation, …
The Basil Technique: Bias Adaptive Statistical Inference Learning Agents For Learning From Human Feedback, Jonathan Indigo Watson
The Basil Technique: Bias Adaptive Statistical Inference Learning Agents For Learning From Human Feedback, Jonathan Indigo Watson
Theses and Dissertations--Computer Science
We introduce a novel approach for learning behaviors using human-provided feedback that is subject to systematic bias. Our method, known as BASIL, models the feedback signal as a combination of a heuristic evaluation of an action's utility and a probabilistically-drawn bias value, characterized by unknown parameters. We present both the general framework for our technique and specific algorithms for biases drawn from a normal distribution. We evaluate our approach across various environments and tasks, comparing it to interactive and non-interactive machine learning methods, including deep learning techniques, using human trainers and a synthetic oracle with feedback distorted to varying degrees. …
Digital Transformation, Applications, And Vulnerabilities In Maritime And Shipbuilding Ecosystems, Rafael Diaz, Katherine Smith
Digital Transformation, Applications, And Vulnerabilities In Maritime And Shipbuilding Ecosystems, Rafael Diaz, Katherine Smith
VMASC Publications
The evolution of maritime and shipbuilding supply chains toward digital ecosystems increases operational complexity and needs reliable communication and coordination. As labor and suppliers shift to digital platforms, interconnection, information transparency, and decentralized choices become ubiquitous. In this sense, Industry 4.0 enables "smart digitalization" in these environments. Many applications exist in two distinct but interrelated areas related to shipbuilding design and shipyard operational performance. New digital tools, such as virtual prototypes and augmented reality, begin to be used in the design phases, during the commissioning/quality control activities, and for training workers and crews. An application relates to using Virtual Prototypes …
The Implementation Of Augmented Reality And Low Latency Protocols In Musical Instrumental Collaborations, Qixiao Zhu
The Implementation Of Augmented Reality And Low Latency Protocols In Musical Instrumental Collaborations, Qixiao Zhu
Honors Theses
Past projects involving musical software have been completely virtual, while these software do well in entertainment and education, there is the question of whether these software are playable to the same extent as physical musical instruments. The software presented in this paper, "AR Jam", utilizes various software and hardware tools to form a networked mixed reality system for the users to play music on. The intention of this project is to seek new ways to explore more playable musical instruments in the digital world. The paper presents the software's implementation, challenges such as optimization problems of the synthesizer, and the …
Sleepmore: Inferring Sleep Duration At Scale Via Multi-Device Wifi Sensing, Camellia Zakaria, Gizem Yilmaz, Priyanka Mammen, Michael Chee, Prashant Shenoy, Rajesh Krishna Balan
Sleepmore: Inferring Sleep Duration At Scale Via Multi-Device Wifi Sensing, Camellia Zakaria, Gizem Yilmaz, Priyanka Mammen, Michael Chee, Prashant Shenoy, Rajesh Krishna Balan
Research Collection School Of Computing and Information Systems
The availability of commercial wearable trackers equipped with features to monitor sleep duration and quality has enabled more useful sleep health monitoring applications and analyses. However, much research has reported the challenge of long-term user retention in sleep monitoring through these modalities. Since modern Internet users own multiple mobile devices, our work explores the possibility of employing ubiquitous mobile devices and passive WiFi sensing techniques to predict sleep duration as the fundamental measure for complementing long-term sleep monitoring initiatives. In this paper, we propose SleepMore, an accurate and easy-to-deploy sleep-tracking approach based on machine learning over the user's WiFi network …
An Ambiguous Technique For Nonvisual Text Entry, Dylan C. Gaines
An Ambiguous Technique For Nonvisual Text Entry, Dylan C. Gaines
Dissertations, Master's Theses and Master's Reports
Text entry is a common daily task for many people, but it can be a challenge for people with visual impairments when using virtual touchscreen keyboards that lack physical key boundaries. In this thesis, we investigate using a small number of gestures to select from groups of characters to remove most or all dependence on touch locations. We leverage a predictive language model to select the most likely characters from the selected groups once a user completes each word.
Using a preliminary interface with six groups of characters based on a Qwerty keyboard, we find that users are able to …
Modelling The Relationship Between Personality Traits And Basic Emotions: A Multi-Modal And Affective Computing Approach, Brendan Ryan Donovan
Modelling The Relationship Between Personality Traits And Basic Emotions: A Multi-Modal And Affective Computing Approach, Brendan Ryan Donovan
Theses
In the field of Psychology, it has long been assumed that one’s personality traits are linked to one’s emotional states. Yet there is a scarce amount of research that has directly quantified the relationships between basic emotional states and Big Five personality traits. Most empirical research has investigated how attributes of emotional states map to a narrow selection of personality traits (Extraversion and Neuroticism) via a single modality (questionnaires). This narrow focus restricts the field’s understanding of the relationship between emotional states and personality traits.
In this research, the Personality Emotion Mapping (PEM) model was developed to map the relationships …
Exploration Of Digital Synthesis, Angelo Indre
Exploration Of Digital Synthesis, Angelo Indre
Williams Honors College, Honors Research Projects
“An Exploration of Digital Synthesis” is a comprehensive investigation into the world of digital audio and music production. The paper explores the fundamental concepts of sound synthesis, including MIDI, virtual instruments (VSTs), and the JUCE framework. The central focus of the paper is the implementation of a custom synthesizer, which serves as a case study for the practical application of digital synthesis. The paper addresses the key question of how to create a functioning synthesizer from scratch, providing detailed insights into the programming and design process. Overall, the paper represents a significant contribution to the fields of digital audio and …
Fridge Tracker And Recipe Provider : Fridgechamp, Matt Dudek
Fridge Tracker And Recipe Provider : Fridgechamp, Matt Dudek
Williams Honors College, Honors Research Projects
FridgeChamp is a website to allow people to track their fridge/pantry contents while providing them recipes they can make with said ingredients. Currently there are few ingredient trackers and recipe matchers that exist as websites, and of those many lack simplistic recipes that a home chef would use. In addition to lacking some recipes, many tracker/recipe apps do not have a function to remove from your stock what a recipe requires, making you tediously update the stock every time you cook/use something.
Video Sign Language Recognition Using Pose Extraction And Deep Learning Models, Shayla Luong
Video Sign Language Recognition Using Pose Extraction And Deep Learning Models, Shayla Luong
Master's Projects
Sign language recognition (SLR) has long been a studied subject and research field within the Computer Vision domain. Appearance-based and pose-based approaches are two ways to tackle SLR tasks. Various models from traditional to current state-of-the-art including HOG-based features, Convolutional Neural Network, Recurrent Neural Network, Transformer, and Graph Convolutional Network have been utilized to tackle the area of SLR. While classifying alphabet letters in sign language has shown high accuracy rates, recognizing words presents its set of difficulties including the large vocabulary size, the subtleties in body motions and hand orientations, and regional dialects and variations. The emergence of deep …
Driving Simulator : Driving Performance Under Distraction, Kaushik Pilligundla
Driving Simulator : Driving Performance Under Distraction, Kaushik Pilligundla
Master's Projects
This pilot study used a driving simulator experiment to look into how podcast consumption affects driving performance as a continuous distraction. Three volunteers conducted three trials in the study, each with a different driving scenario. Data analysis was done to compare two conditions. The first condition is the Audio, where volunteers listen to podcasts while driving. The second condition is no-audio condition.. The no-audi condition had nothing to play in the background. We used eye-tracking technology to gather gaze data. The study's findings using the post survey and eye fixation data indicate that listening to podcasts leads to continuous distraction …
3d Ar Reconstruction, Sneh Arvind Kothari
3d Ar Reconstruction, Sneh Arvind Kothari
Master's Projects
The goal of the project is to improve the shopping experience for users by using augmented reality technology. People generally want opinions from others when buying shoes offline. Clicking and sending images of a shoe is not an ideal solution as it does not give the complete feel of the shoe. We developed the 3D AR Reconstruction app to make this process better. A user of our app clicks photos of the shoe. This image data is converted to form a mesh that can be shared. On receiving a model the user can open it in the app and interact …
Sensor Relationship Inference In Single Resident Smart Homes Using Time Series, Samuel Nack
Sensor Relationship Inference In Single Resident Smart Homes Using Time Series, Samuel Nack
Graduate Theses/Dissertations
Determining sensor relationships in smart environments is complex due to the variety and volume of time series information they provide. Moreover, identifying sensor relationships to connect them with actuators is difficult for smart home users who may not have technical experience. Yet, gathering information on sensor relationships is a crucial intermediate step towards more advanced smart home applications such as advanced policy generation or automatic sensor configuration. Therefore, in this thesis, I propose a novel unsupervised learning approach, named SeReIn, to automatically group sensors by their inherent relationships solely using time series data for single resident smart homes. SeReIn extracts …
On The Pursuit Of Developer Happiness: Webcam-Based Eye Tracking And Affect Recognition In The Ide, Tamsin Rogers
On The Pursuit Of Developer Happiness: Webcam-Based Eye Tracking And Affect Recognition In The Ide, Tamsin Rogers
Honors Theses
Recent research highlights the viability of webcam-based eye tracking as a low-cost alternative to dedicated remote eye trackers. Simultaneously, research shows the importance of understanding emotions of software developers, where it was found that emotions have significant effects on productivity, code quality, and team dynamics. In this paper, we present our work towards an integrated eye-tracking and affect recognition tool for use during software development. This combined approach could enhance our understanding of software development by combining information about the code developers are looking at, along with the emotions they experience. The presented tool utilizes an unmodified webcam to capture …
The Impact Of Pre-Experiment Walking On Distance Perception In Vr, Soheil Sepahyar
The Impact Of Pre-Experiment Walking On Distance Perception In Vr, Soheil Sepahyar
Dissertations, Master's Theses and Master's Reports
While individuals can accurately estimate distances in the real world, this ability is often diminished in virtual reality (VR) simulations, hampering performance across training, entertainment, prototyping, and education domains. To assess distance judgments, the direct blind walking method—having participants walk blindfolded to targets—is frequently used. Typically, direct blind walking measurements are performed after an initial practice phase, where people become comfortable with walking while blindfolded. Surprisingly, little research has explored how such pre-experiment walking impacts subsequent VR distance judgments. Our initial investigation revealed increased pre-experiment blind walking reduced distance underestimations, underscoring the importance of detailing these preparatory procedures in research—details …