Graphics and Human Computer Interfaces Commons^™

D3still : Decoupled Differential Distillation For Asymmetric Image Retrieval, Yi Xie, Yihong Lin, Wenjie Cai, Xuemiao Xu, Huaidong Zhang, Yong Du, Shengfeng He

Research Collection School Of Computing and Information Systems

Existing methods for asymmetric image retrieval employ a rigid pairwise similarity constraint between the query network and the larger gallery network. However, these oneto-one constraint approaches often fail to maintain retrieval order consistency, especially when the query network has limited representational capacity. To overcome this problem, we introduce the Decoupled Differential Distillation (D3still) framework. This framework shifts from absolute one-to-one supervision to optimizing the relational differences in pairwise similarities produced by the query and gallery networks, thereby preserving a consistent retrieval order across both networks. Our method involves computing a pairwise similarity differential matrix within the gallery domain, which is …

Rethinking Multi-View Representation Learning Via Distilled Disentangling, Guanzhou Ke, Bo Wang, Xiaoli Wang, Shengfeng He

Research Collection School Of Computing and Information Systems

Multi-view representation learning aims to derive robust representations that are both view-consistent and view-specific from diverse data sources. This paper presents an in-depth analysis of existing approaches in this domain, highlighting a commonly overlooked aspect: the redundancy between view-consistent and view-specific representations. To this end, we propose an innovative framework for multi-view representation learning, which incorporates a technique we term 'distilled disentangling'. Our method introduces the concept of masked cross-view prediction, enabling the extraction of compact, high-quality view-consistent representations from various sources without incurring extra computational overhead. Additionally, we develop a distilled disentangling module that efficiently filters out consistency-related information …

More Human-Likeness, Less Self-Disclosure? Avatars' Form Realism And Job Applicants' Self-Disclosure In Ai Interviews, Yamin Xu, Keng Siau, Fiona Fui-Hoon Nah

Research Collection School Of Computing and Information Systems

The rise of AI in recruitment promises to revolutionize how organizations evaluate job candidates. The quality of AI evaluations is determined by the input data, which depends on job applicants' self-disclosure. However, little is known about how the design elements of AI interview systems, particularly avatar interviewers, influence job applicants' self-disclosure during these interactions. This study aims to address this gap by specifically focusing on how the form realism of avatar interviewers affects job applicants' self-disclosure through their perceptions. In addition, the study will examine the effects of job type as a moderator. Drawing on the Stimulus-Organism-Response (S-O-R) model, this …

Embodied Visions: Interactive Installations That Reimagine Bodily Presence In Digital Imaging Apparatuses As Shadows, Yunzi Shi

Dartmouth College Master’s Theses

Contextualized within a history of technological development, the evolution of imaging devices and technologies is accompanied by the abstraction of spatial relationships between the body of the observer, the apparatus, and physical reality, which leads to disembodying experiences for the observing subject. Compared with devices and interactive experiences, critical reflection on the epistemological impact of digital imaging devices has less priority in computational imaging and human-computer interaction research. Taking an artistic approach, this thesis describes Embodied Visions, an exhibition featuring three interactive installations exploring the technical infrastructure for imaging and reflecting on the (dis)embodied experiences in the digital age. …

Inchi Isotopologue And Isotopomer Specifications, Hunter N. B. Moseley, Philippe Rocca-Serra, Reza M. Salek, Masanori Arita, Emma L. Schymanski

Markey Cancer Center Faculty Publications

This work presents a proposed extension to the International Union of Pure and Applied Chemistry (IUPAC) International Chemical Identifier (InChI) standard that allows the representation of isotopically‑resolved chemi‑ cal entities at varying levels of ambiguity in isotope location. This extension includes an improved interpretation of the current isotopic layer within the InChI standard and a new isotopologue layer specification for representing chemical intensities with ambiguous isotope localization. Both improvements support the unique isotopically‑ resolved chemical identification of features detected and measured in analytical instrumentation, specifically nuclear magnetic resonance and mass spectrometry.

Scientific contribution

This new extension to the InChI standard …

Manipulative, Dark, And Unethical Design Practices In Ui & Ux Design, Ryan Edward Brown

Honors Theses

This thesis examines the pervasive and detrimental effects of manipulative user interface and user experience design (UI/UX) practices on individuals and society. Focusing on three critical areas – accessibility, dark patterns, and polarization – the study employs a mixed-methods approach, combining findings from a comprehensive literature review, an analysis of specific design patterns and methods, and a survey of user experiences.
The literature review covers topics such as the importance of accessibility in design education, the prevalence of dark patterns in mobile and desktop sites, the role of personalization algorithms in shaping user experiences, and the formation of echo chambers …

Companionship, Romance, And Self-Perception With Conversational Chatbots, Jonathan Windsor

Departmental Honors & Graduate Capstone Projects

Serving as a metaphorical gateway transcending the communicative barriers of physical relationships in interpersonal dialogues, artificial imators of human behavior and speech, also known as conversational chatbots; a simulation of human knowledge and existence in a bi-directional conversation, functions as a rhetor of expression. Spanning from contexts of professional to romantic, I serve to dissect and critically analyze the nuances of human-machine relationships based on pre-established literature, inviting ethical considerations and biases in their design and marketing. Corporate influences spark pre-established servitude-esque relationships with conversational agents. Professional applications, both task-oriented and emotionally based alike, paint a mixed picture of …

Simulating Cross-Scale Solid-Fluid Interaction Phenomena, Jinyuan Liu

Dartmouth College Ph.D Dissertations

Solid-fluid interactions are ubiquitous in nature, and accurate simulation methods are essential for realistic animation, industrial design, and engineering analysis. Com- pared to large-scale coupling phenomena, simulating fine-scale interactions poses extra challenges due to factors such as surface tension, material wettability, and geometric complexity. In this thesis, we pursue novel methodologies to accurately model in- terfacial dynamics between surface-tension fluids and codimensional solids, involving capillary interactions, controllable wettability, and robust contact behaviors. Our ini- tial approach involves developing a novel three-way coupling method, which utilizes a thin liquid membrane, modelled as a simplicial mesh, to facilitate accurate momen- tum transfer, …

Research Project Review: Human-Computer Interactions, Kylie E. Garcia

The Agora

A review of a body of research conducted by Dr. Gain Park, an assistant professor in the Department of Journalism and Media Studies at New Mexico State University. This review contains a summary of Dr. Park's research on human-computer interactions, commentary on its contributions and significance, as well as insights from Dr. Park.

An Exploration Of Procedural Methods In Game Level Design, Hector Salinas

Computer Science and Computer Engineering Undergraduate Honors Theses

Video games offer players immersive experiences within intricately crafted worlds, and the integration of procedural methods in game level designs extends this potential by introducing dynamic, algorithmically generated content that could stand on par with handcrafted environments. This research highlights the potential to provide players with engaging experiences through procedural level generation, while potentially reducing development time for game developers.

Through a focused exploration on two-dimensional cave generation techniques, this paper aims to provide efficient solutions tailored to this specific environment. This exploration encompasses several procedural generation methods, including Midpoint Displacement, Random Walk, Cellular Automata, Perlin Worms, and Binary Space …

Diffusion-Based Negative Sampling On Graphs For Link Prediction, Yuan Fang, Yuan Fang

Research Collection School Of Computing and Information Systems

Link prediction is a fundamental task for graph analysis with important applications on the Web, such as social network analysis and recommendation systems, etc. Modern graph link prediction methods often employ a contrastive approach to learn robust node representations, where negative sampling is pivotal. Typical negative sampling methods aim to retrieve hard examples based on either predefined heuristics or automatic adversarial approaches, which might be inflexible or difficult to control. Furthermore, in the context of link prediction, most previous methods sample negative nodes from existing substructures of the graph, missing out on potentially more optimal samples in the latent space. …

Multigprompt For Multi-Task Pre-Training And Prompting On Graphs, Xingtong Yu, Chang Zhou, Yuan Fang, Xinming Zhan

Research Collection School Of Computing and Information Systems

Graph Neural Networks (GNNs) have emerged as a mainstream technique for graph representation learning. However, their efficacy within an end-to-end supervised framework is significantly tied to the availability of task-specific labels. To mitigate labeling costs and enhance robustness in few-shot settings, pre-training on self-supervised tasks has emerged as a promising method, while prompting has been proposed to further narrow the objective gap between pretext and downstream tasks. Although there has been some initial exploration of prompt-based learning on graphs, they primarily leverage a single pretext task, resulting in a limited subset of general knowledge that could be learned from the …

Instant3d: Instant Text-To-3d Generation, Ming Li, Pan Zhou, Jia-Wei Liu, Jussi Keppo, Shuicheng Yan, Xiangyu Xu

Research Collection School Of Computing and Information Systems

Text-to-3D generation has attracted much attention from the computer vision community. Existing methods mainly optimize a neural field from scratch for each text prompt, relying on heavy and repetitive training cost which impedes their practical deployment. In this paper, we propose a novel framework for fast text-to-3D generation, dubbed Instant3D. Once trained, Instant3D is able to create a 3D object for an unseen text prompt in less than one second with a single run of a feedforward network. We achieve this remarkable speed by devising a new network that directly constructs a 3D triplane from a text prompt. The core …

The Impact Of Avatar Completeness On Embodiment And The Detectability Of Hand Redirection In Virtual Reality, Martin Feick, Andre Zenner, Simon Seibert, Anthony Tang, Antonio Krüger

Research Collection School Of Computing and Information Systems

To enhance interactions in VR, many techniques introduce offsets between the virtual and real-world position of users’ hands. Nevertheless, such hand redirection (HR) techniques are only effective as long as they go unnoticed by users—not disrupting the VR experience. While several studies consider how much unnoticeable redirection can be applied, these focus on mid-air floating hands that are disconnected from users’ bodies. Increasingly, VR avatars are embodied as being directly connected with the user’s body, which provide more visual cue anchoring, and may therefore reduce the unnoticeable redirection threshold. In this work, we studied more complete avatars and their effect …

Swapvid: Integrating Video Viewing And Document Exploration With Direct Manipulation, Taichi Murakami, Kazuyuki Fujita, Kotaro Hara, Kazuki Takashima, Yoshifumi Kitamura

Research Collection School Of Computing and Information Systems

Videos accompanied by documents—document-based videos—enable presenters to share contents beyond videos and audience to use them for detailed content comprehension. However, concurrently exploring multiple channels of information could be taxing. We propose SwapVid, a novel interface for viewing and exploring document-based videos. SwapVid seamlessly integrates a video and a document into a single view and lets the content behaves as both video and a document; it adaptively switches a document-based video to act as a video or a document upon direct manipulation (e.g., scrolling the document, manipulating the video timeline). We conducted a user study with twenty participants, comparing SwapVid …

Vaid: Indexing View Designs In Visual Analytics System, Lu Ying, Aoyu Wu, Haotian Li, Zikun Deng, Ji Lan, Jiang Wu, Yong Wang, Huamin Qu, Dazhen Deng, Yingcai Wu

Research Collection School Of Computing and Information Systems

Visual analytics (VA) systems have been widely used in various application domains. However, VA systems are complex in design, which imposes a serious problem: although the academic community constantly designs and implements new designs, the designs are difficult to query, understand, and refer to by subsequent designers. To mark a major step forward in tackling this problem, we index VA designs in an expressive and accessible way, transforming the designs into a structured format. We first conducted a workshop study with VA designers to learn user requirements for understanding and retrieving professional designs in VA systems. Thereafter, we came up …

Exploring Diffusion Time-Steps For Unsupervised Representation Learning, Zhongqi Yue, Jiankun Wang, Qianru Sun, Lei Ji, Eric I-Chao Chang, Hanwang Zhang

Research Collection School Of Computing and Information Systems

Representation learning is all about discovering the hidden modular attributes that generate the data faithfully. We explore the potential of Denoising Diffusion Probabilistic Model (DM) in unsupervised learning of the modular attributes. We build a theoretical framework that connects the diffusion time-steps and the hidden attributes, which serves as an effective inductive bias for unsupervised learning. Specifically, the forward diffusion process incrementally adds Gaussian noise to samples at each time-step, which essentially collapses different samples into similar ones by losing attributes, e.g., fine-grained attributes such as texture are lost with less noise added (i.e., early time-steps), while coarse-grained ones such …

Next-Generation Crop Monitoring Technologies: Case Studies About Edge Image Processing For Crop Monitoring And Soil Water Property Modeling Via Above-Ground Sensors, Nipuna Chamara

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

Artificial Intelligence (AI) has advanced rapidly in the past two decades. Internet of Things (IoT) technology has advanced rapidly during the last decade. Merging these two technologies has immense potential in several industries, including agriculture.

We have identified several research gaps in utilizing IoT technology in agriculture. One problem was the digital divide between rural, unconnected, or limited connected areas and urban areas for utilizing images for decision-making, which has advanced with the growth of AI. Another area for improvement was the farmers' demotivation to use in-situ soil moisture sensors for irrigation decision-making due to inherited installation difficulties. As Nebraska …

Automated Cinematographer For Vr Viewing Experiences, Zihan Wu

Dartmouth College Master’s Theses

As the virtual reality (VR) industry continues to evolve, the question of how to effectively capture VR experiences for an audience remains a challenge. The predominant method of showcasing VR applications through first-person recordings lacks cinematic interest, failing to capture other viewpoints and the essence of the moment. Meanwhile, manually setting up cameras and editing videos requires technical expertise on behalf of the user. In this paper, we propose the use of machine learning (ML) to automatically select the most compelling predefined viewpoint in a VR environment, at any given moment. Our models, trained on actor motion and voice volume, …

Vr Circuit Simulation With Advanced Visualization For Enhancing Comprehension In Electrical Engineering, Elliott Wolbach

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

As technology advances, the field of electrical and computer engineering continuously demands innovative tools and methodologies to facilitate effective learning and comprehension of fundamental concepts. Through a comprehensive literature review, it was discovered that there was a gap in the current research on using VR technology to effectively visualize and comprehend non-observable electrical characteristics of electronic circuits. This thesis explores the integration of Virtual Reality (VR) technology and real-time electronic circuit simulation with enhanced visualization of non-observable concepts such as voltage distribution and current flow within these circuits. The primary objective is to develop an immersive educational platform that makes …