Graphics and Human Computer Interfaces Commons^™

From Data To Decision-Making: The Role Of Local Digital Twins In Cross-Domain Management Within Municipalities – A Research-In-Progress Study In Veenendaal, Diana M.E. Boekman, Koen Smit, Guido Ongena, Rob Peters

Communications of the IIMA

Municipalities are facing increasingly complex, interconnected challenges in areas like housing, climate adaptation, mobility, and social policy. Local Digital Twins (LDTs) are seen as a promising tool to make this complexity more understandable and support decision-making. At the same time, both literature and practice show that few initiatives get past the pilot phase, even though getting through that phase is essential for successful long-term adoption.

This paper presents a research-in-progress study on the development and application of an implementation method for LDT technology within the municipality of Veenendaal, based on human values rather than driven by technological possibilities. Based on …

Research On Image Feature Analysis Of Intangible Cultural Heritage Brocade Integrating Multi-Scale Visual Perception, Ruiyang Yuan, Hao Wang, Shu Zhou, Hui Zhu, Jingwen Qiu

Journal of Scientific Information Research

[Purpose/significance] Addressing the challenges posed by the complex semantic characteristics of intangible cultural heritage brocade imagery, the difficulty in extracting their profound connotations, and the inadequate utilisation of multi-scale features by traditional deep learning models, this paper aims to explore a method for analysing the characteristics of intangible cultural heritage brocade images that integrates multi-scale visual features. [Method/process] This paper constructs a multi-scale feature analysis framework for intangible cultural heritage brocade images (ICH_BC), integrating convolutional neural networks with Transformer architectures. The framework employs ResNet to extract local texture and detail features from brocade images, utilises VIT to capture global structural …

Du Undergraduate Showcase Abstracts: Research, Scholarship, And Creative Works, Sophia Wismar, Henry Staats, Allison Metzler, Chloe Puckett, Rachel Levine, Christa Kilpatrick, Scott Wolf, Joe Walsh, Grace Doolittle, John Engebreston, Zoe Lopez, Christopher Aaby, Audrey Duff, Timothy Sisk, Katelyn Lamberton, Angela Narayan, Gilkah Argueta, Habiba Samir, Girena Tesfazghi, Genet Kenore, Sinit Tesfamariam, Effley Brooks, Abi Newell, Megan Doherty, Natalie Baer, Lexi Blood, Talya Riciputi, Jessica Jimenez, Devin Hernandez, Lynn Clark, Taj Kumar, Sunil Kumar, Allen Rutman, Mira Pronobis, Tess Carson, Anna Sher, Frankie Stroud, Tamra Pearson D'Estree, Alyssa Wilson, Emily Melnick, Jenalee Doom, Yihang Gao, Gwendolyn Geiger, Noah Gettle, Scott Nichols, Clare Ayoub, Cara Dienno, Sunny Walker, Zoe Hansen, Maya Wheeler, Addison Rice, Patrick Martin, Sanjana Acharya, Daniel Mcintosh, Amanda Mckellips, Calli Cain, Justin Blake, Peter Sokol-Hessner, Natalie Miller, Max Weisbuch, Sophia Dellota, John Macikas, Charlotte Snow, Mark Siemens, Zoe Lynch, Alex Huffman, Prachi Shah, Jason Roney, Halcyon Levi, Nicole Herzog, Andrea Koly, Daniel Linseman, Annie London, Xi Yang, Avery Zwisler, Jane Smith, Chaz Contag, Michael Kerwin, Lucy Rand, Grace Schroeder, Michelle Rozenman, Nissa Tapper, Guiming Zhang, Mateo Mazariego-Halpern, Keith Meyer, Julie Do, Dakota Park-Ozee, Travis Herink, Kara Neu, Jonathan Plomin, Eve-Odine Duchaufour, Debbie Gale Mitchell, Tennyson Anderson-Stricklin, Lily Treitz, Samantha Rosenberger, Sierra Griffith, Finley Joseph, Daniel Sampson, Emmy Davis, Skyler Kasnoff, Evon Lopez, Vivian Nguyen, Cassy Young, Franklin Sellner, Martin Tobon, Ila Graham, Zach Billings, Holden Hedit, Decatur Boland, Paul Kosempel, Cory Chandler, Jay Mahoney, Sam Dragan, Susan Dagget, Yarrow Ator, Heidi Vuletich, Owen Weber, Andrew Kloeppel, Petersen Gray, Mandi Schaeffer-Fry, Razleen Bassra, Bryanna Rodriguez, Christina Blue, Taubie Sanders, Rachel Epstein, Luke Milburn, Camryn Evans, Ezra Martinez, Mary Westwood, Gabri Notov, Robin Tinghitella, Lilou Cabrol, Eli Barbour, Juliet Mendik, Selma Myers, Zac Wise, Noah Fahlin, Michelle Knowles, Abigail Hopper, Michael Greenberger, Romi Laclair, Sarah Watamura, Sabrina Efroymson, Casey Barker, Sydney Seltzer, Bryn Yehle, Jennifer Hoffman, Sara Garcia, Ryuka Nagamine, Trevor Briggs, Remy Le Boeuf, Elena Krone, Eileen Farrell, Regan O'Rourke, Elena Roel, Greg Mortimer, Ali Ayoub, Stefani Langehennig, Caitlin Turk, Logan Scmid, Stefan Chavez-Norgaard, Karen Kim, Tatiana Peccedi, Courtney Cassidy, John Sebesta, Rhianna Lewis, Janice Bening-Lacek, Vivian Lawless, Mckenna Hanson, Jeffrey Amidon, Riya Joshi, Ram Ambre, Brady Worrell, Perrin Schneider, Ali Azadani, Brooke Agulnek, Lyndsie Salvagio, Elise Siemanowki, Yan Qin, Andre Allen, Melodie Nguyen, Megan Livengood, Abby Reams, Saffron Hartreeve, Bri Wylie, Sarah Brookman, Mariah Loiacono, Green Russo, Abhia Lodhi, Gabrielle Welsh, Nika Spehar, Shahked Levin, Evrim Baykal, Kimberly Chiew, Jocelyn Torres, Kailey Hicks, Mykaela Tanino-Springsteen, Audrey Bellows, Akam Chahal, Madeline Tepper, Shannon Murphy, Alexa Fonseca, Deborah Han, Cassandra Perez, Oluwatoyin Alaba, Julia Roncoroni, Vy Nguyen, Nana Burn, Sarah Sasse, Rubin Tuder, Anthony Gerber, Nancy Lorenzon, Christine Vohwinkel, Camryn Gunter, Tristan Weber, Sam Rommel, Brian Michel, Muskan Fatima, Alannah Oleson, Kira Frey, Edward Garrido, Beckett Morris, Kerstin Haring, Drew Middleton, Abigail Walpert, Liam Dee, Gabby Ishaw, Cole Carnes, Maddie Weiser, Claire Fox, Valeriia Vlasenko, Kateri Mcrae, Riley Smith, Abigail Templin, Kushani Rajapaksha

DU Undergraduate Research Journal Archive

Abstracts from the DU Undergraduate Research Showcase.

Research On The Accessibility Elements Of Rural Public Digital Cultural Services Based On Aism-Fmicmac, Lihui Peng, Banruo Gu, Chuang Hong, Xisheng Hu

Journal of Scientific Information Research

[Purpose/significance] A structural analysis of the stratified dependencies among accessibility determinants in rural public digital cultural ecosystems enables identification of pivotal developmental nodes, thereby establishing theoretical foundations for optimizing service delivery mechanisms and achieving spatial equilibrium in digital cultural provision. [Method/process] This study applies grounded theory to conduct a comprehensive coding analysis of policy documents related to China's rural public digital cultural services. Through this process, five dimensions and fifteen sub-components of accessibility are identified. An index system for accessibility factors is then developed using the AISM approach. The identified elements are classified into three hierarchical levels. To further validate …

Drug Risk Knowledge Discovery For Western Medicines Based On Knowledge Graph Link Prediction, Jianxiang Wei, Ma Hengyuan Ma, Yuehong Sun, Wenwen Du, Letian Hu

Journal of Scientific Information Research

[Purpose/significance] The risk information contained in drug instructions is usually incomplete, and some new adverse reactions can only be discovered in actual clinical use. This paper proposes an information organization and knowledge discovery method for pharmacovigilance, in order to timely and accurately identify missing risk knowledge in drug instructions. [Method/process] Drug instructions of 8 152 Western medicines are collected as the research data; On the basis of ontology construction, data annotation, and model training, the UIE model is used to jointly extract entity and relationship triplets from the research data; A new knowledge graph link prediction method CompGCN-RotatE, is proposed, …

Research On Temporal Knowledge Graph Completion Method For Emergent Events Based On Bigru And Graph Contrastive Learning, Peng Wu, Zhenyu Lu, Xuechen Zhang

Journal of Scientific Information Research

[Purpose/significance] During emergencies, social media short texts contain critical information but are heavily interfered with by noise. Traditional static knowledge graph completion techniques struggle to effectively address their dynamic evolution and data sparsity issues, making it imperative to introduce temporal modeling methods. [Method/process] This study proposes a dynamic completion framework that combines the temporal feature capture capability of Bidirectional Gated Recurrent Units (BiGRU) with the noise-resistant representation learning advantages of Graph Contrastive Learning (GCL). At the completion level, the ConBiTE method is introduced, which captures temporal dependencies through self-attention mechanisms and BiGRU, while leveraging GCL to enhance the completion of …

Enhancing Low-Light And Noisy Images Using Gaussian Denoising And Clahe (Contrast-Limited Adaptive Histogram Equalization)., Daniel Adesoji

SACAD: Scholarly Activities

Abstract

In digital imaging Low light image improvement is a crucial issue, with applications in medical imaging, surveillance and digital imaging. Images captured under substandard illumination usually appear dark and noisy: contrast is lower, hiding crucial details, while ISO (international Organization for Standardization) settings introduce grainy noise that devalue quality. These issues make images a problem for both human interpretation and automated vision system.

Traditional improvement methods such as histogram equalization and Retinex -based techniques enhance brightness but usually cause artifacts to boost noise. Deep learning approaches achieve strong results but require large datasets, heavy computation, and may fail to …

Creepy, Invasive, And Exploitative Algorithms: A Cpm Analysis Of Users' Privacy Breakdowns And Recalibration Practices With Social Media Algorithms, Matthew J. A. Craig, Jeffrey T. Child

Human-Machine Communication

Social media content filtering algorithms can both provide desired personalized content and ads for users. However, sometimes these recommendations can resemble individual private information. How might users navigate these experiences to best manage their private information? The present exploratory study utilizes the rules- and systems-based framework of communication privacy management (CPM) theory to explore social media users’ experiences of privacy breakdowns with social media algorithms and investigates what users do in response to said breakdowns. These responses were refined using content analysis and divided into different categories of privacy breakdowns and recalibration strategies. Implications for future research surrounding human-machine communication …

Relightable Neural Radiance Fields For Novel View Synthesis, Malena I. Mahoney

Scholarly Horizons: University of Minnesota, Morris Undergraduate Journal

This paper describes relighting neural radiance fields for novel view synthesis. View synthesis is the problem of using input images with corresponding camera angles to produce a photorealistic 3D model of an environment and its objects. Neural radiance fields (NeRFs) were created as a solution to view synthesis. Neural radiance field models work well for generating realistic 3D models from 2D image inputs; how-ever, they do not support changing the lighting or placing the objects from the input images into different environments. The problem comes from the fact that NeRFs rely on a neural network that is essentially overfitted to …

Classification Of Human Trust In Ai Using Brain Activity Data, Danushka Bandara, Ruhuan Liao, Fatima Chowdhury, Leslie Abbott

Northeast Journal of Complex Systems (NEJCS)

Trust plays a crucial role in human-computer interaction, particularly in scenarios involving artificial intelligence (AI) systems. This study explores the feasibility of using functional near-infrared spectroscopy (fNIRS) data to classify trust levels in human-AI interaction scenarios. A total of 18 participants completed an image classification task with an AI team member while their hemodynamic responses were recorded using fNIRS. Preprocessing of fNIRS data involved motion artifact removal, filtering, and normalization. Exploratory analysis identified significant associations between hemodynamic responses in the prefrontal cortex and trust levels. An across-subject binary trust classification model was developed using machine learning techniques, achieving an F1 …

Ai Models By Boodlebox: Purpose-Built Intelligence, Kyle Horn

SACAD: Scholarly Activities

Generative AI has transformed the way we interact with technology, enabling dynamic and intelligent conversations through AI-driven bots. This project explores my experience with BoodleBox, a platform that hosts AI chatbots, offering users access to leading AI models such as ChatGPT, Gemini, DALL·E, and DeepSeek. Through the FHSU Generative AI Initiative, I was granted access to experiment with these models and create my own custom AI bot tailored to specific needs. This poster highlights the process of developing a custom bot, including defining instructions, enforcing rules, and sharing the bot for others to use. Additionally, it discusses the background of …

Promoting Digital Agriculture Adoption In Community-Based Agricultural Organizations, Jean Hardy, Abbey Palmer

Journal of Extension

Existing research and practice related to digital agriculture technology adoption is largely focused on large-scale producers. In this paper, we describe a case of adopting an advanced soil monitoring system in a community-based agricultural organization. We provide guidance for Extension professionals seeking to implement or promote digital agriculture technology adoption on: selecting appropriate technology, incorporating new technology into existing practices, harnessing local technology champions, and avoiding data-driven mission creep.

Interaction Mechanism Between Health Anxiety And Information Seeking Behavior From The Perspective Of Phenomenology, Yanfeng Zhang, Minqian Yu

Journal of Scientific Information Research

[Purpose/significance]To analyze the evolution characteristics of health anxiety before and after information search behavior from the perspective of phenomenological graph analysis, and to explain the internal mechanism of the interaction between health anxiety and information search behavior. [Method/process]By using the phenomenological qualitative research method, the interactive mechanism between health anxiety and information search behavior was deeply explored. Based on the I-PACE theoretical model framework, the model elements of users' health anxiety and information search behavior were analyzed from the four dimensions of "Person-Affect-Cognition-Execution". To construct a mechanistic relationship model between health anxiety and information search behavior. [Result/conclusion]The research results revealed …

Generalizing Classification Of Pilot Workload: Transfer Learning Versus A Jepa-Inspired Transformer Architecture, Naim Barnett, Shivani Nagrecha, Morgan Glover, Clayton Harper, Justin Wilson, James Maher, Eric C. Larson

International Journal of Aviation, Aeronautics, and Aerospace

Within the context of learning, there poses difficulty when objectively measuring human performance. In this work, we investigate the evaluation of human performance via its relation to the individual's mental capacity by classification of cognitive load within the domain of aviation. By utilizing a mixed virtual and physical flight simulation environment in conjunction with biometric sensing, we create and evaluate the predictive capabilities of a Joint-Embedding Predictive Architecture (JEPA) and compare the architecture and results to traditional methods for transfer learning and domain adaptation. We find that our JEPA inspired architecture can achieve more than 70% accuracy of cognitive workload, …

Construction And Application Of Multi-Dimensional Portrait System For Green Technology Innovation Enterprises In China: Taking The Green Transportation Technology Field As An Example, Wenke Hao, Jianlin Yang, Lei Miao

Journal of Scientific Information Research

[Purpose/significance]By constructing and applying the multi-dimensional portrait system of green technology innovation enterprises in China, this paper aims to comprehensively understand the status quo, advantages and obstacles of enterprises in specific fields in green technology innovation, so as to provide scientific references and suggestions for relevant government departments and decision makers of enterprises. [Method/process]Based on resource based view and environmental dependence theory, we select the internal and external labels of enterprises, and designs a multi-dimensional label system to objectively describe the performance of enterprises in terms of profitability,scientific research and innovation, public opinion and environmental responsibility. Then, the green technology …

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.

Factors Influencing The Perceptions Of Human-Computer Interaction Curriculum Developers In Higher Education Institutions During Curriculum Design And Delivery, Cynthia Augustine, Salah Kabanda

The African Journal of Information Systems

Computer science (CS) and information systems students seeking to work as software developers upon graduating are often required to create software that has a sound user experience (UX) and meets the needs of its users. This includes addressing unique user, context, and infrastructural requirements. This study sought to identify the factors that influence the perceptions of human-computer interaction (HCI) curriculum developers in higher education institutions (HEIs) in developing economies of Africa when it comes to curriculum design and delivery. A qualitative enquiry was conducted and consisted of fourteen interviews with HCI curriculum developers and UX practitioners in four African countries. …

Digitizing Delphi: Educating Audiences Through Virtual Reconstruction, Kate Koury

The Journal of Purdue Undergraduate Research

Implementing a 3D model into a virtual space allows the general public to engage critically with archaeological processes. There are many unseen decisions that go into reconstructing an ancient temple. Analysis of available materials and techniques, predictions of how objects were used, decisions of what sources to reference, puzzle piecing broken remains together, and even educated guesses used to fill gaps in information often go unobserved by the public. This work will educate users about those choices by allowing the side-by-side comparison of conflicting theories on the reconstruction of the Tholos at Delphi, which is an ideal site because of …

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 …

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, …

Breaking Down Computer Networking Instructional Videos: Automatic Summarization With Video Attributes And Language Models, Totok Sukardiyono, Muhammad Irfan Luthfi, Nisa Dwi Septiyanti

Elinvo (Electronics, Informatics, and Vocational Education)

Instructional videos have become a popular tool for teaching complex topics in computer networking. However, these videos can often be lengthy and time-consuming, making it difficult for learners to obtain the key information they need. In this study, we propose an approach that leverages automatic summarization and language models to generate concise and informative summaries of instructional videos. To enhance the performance of the summarization algorithm, we also incorporate video attributes that provide contextual information about the video content. Using a dataset of computer networking tutorials, we evaluate the effectiveness of the proposed method and show that it significantly improves …

Differences In Software Usability Level Based On User Background, Abdur Rohman Sholeh, Agung Fatwanto

Elinvo (Electronics, Informatics, and Vocational Education)

The development of software must consider usability as one of its key success indicators. Relatively few studies discuss the factors influencing usability, including users' backgrounds. The purpose of this research was to investigate the impact of user background, specifically gender, class (year of college admission), and frequency of use on the rating of usability. This research utilized a descriptive quantitative method with instruments: the usability matrix of the Computer System Usability Questionnaire (CSUQ), the System Usability Scale (SUS), the Usability Metric for User Experience (UMUX), and the Net Promoter Score (NPS). The research object was the Learning Management System (LMS) …

Usability Of Mobile Application For Implementing Genetic Counselling Intervention Among Thalassemia Patients And Caregivers: A Case Study Of Cyber Gen, Henri Setiawan, Nur Hidayat, Atun Farihatun, Marlina Indriastuti, Rudi Kurniawan, Andan Firmansyah, Esti Andarini, Yudisa Diaz Lutfi Sandi

Elinvo (Electronics, Informatics, and Vocational Education)

Utilization of communication and information technology has been widely used in the health sector, especially nursing. As one of the nursing interventions for thalassemia patients and caregivers, genetic counseling is not only done face to face but can use android-based telenursing facilities through the complete features available in the Cyber Gen application. This study aims to measure the usability level of Cyber Gen application as an indirect genetic counseling medium for thalassemia patients. This application was developed with four main services: basic information about diseases, consultation rooms, social support, and direct surveys. This application is built using the Flutter Framework, …

Reducing Food Scarcity: The Benefits Of Urban Farming, S.A. Claudell, Emilio Mejia

Journal of Nonprofit Innovation

Urban farming can enhance the lives of communities and help reduce food scarcity. This paper presents a conceptual prototype of an efficient urban farming community that can be scaled for a single apartment building or an entire community across all global geoeconomics regions, including densely populated cities and rural, developing towns and communities. When deployed in coordination with smart crop choices, local farm support, and efficient transportation then the result isn’t just sustainability, but also increasing fresh produce accessibility, optimizing nutritional value, eliminating the use of ‘forever chemicals’, reducing transportation costs, and fostering global environmental benefits.

Imagine Doris, who is …

Deep Learning Image Analysis To Isolate And Characterize Different Stages Of S-Phase In Human Cells, Kevin A. Boyd, Rudranil Mitra, John Santerre, Christopher L. Sansam

SMU Data Science Review

Abstract. This research used deep learning for image analysis by isolating and characterizing distinct DNA replication patterns in human cells. By leveraging high-resolution microscopy images of multiple cells stained with 5-Ethynyl-2′-deoxyuridine (EdU), a replication marker, this analysis utilized Convolutional Neural Networks (CNNs) to perform image segmentation and to provide robust and reliable classification results. First multiple cells in a field of focus were identified using a pretrained CNN called Cellpose. After identifying the location of each cell in the image a python script was created to crop out each cell into individual .tif files. After careful annotation, a CNN was …

Evocative And Provocative Image-Making In The Age Of Generative Ai, Julian Kilker

Tradition Innovations in Arts, Design, and Media Higher Education

Editorial for inaugural AI-focused special issue of Tradition-Innovations in Arts, Design, and Media Higher Education, published under the auspices of the Alliance for the Arts in Research Universities (a2ru). Discusses three articles by five authors in this issue: (1) Choreographing Shadows: Interdisciplinary collaboration to orchestrate ethical image-making by Mark Burchick and Diana Pasulka; (2) Giving Up Control: Hybrid AI-augmented workflows for image-making by Joshua Vermillion; and (3) Hands are Hard: Unlearning how we talk about machine learning in the arts by Adam Hyland and Oscar Keyes.

Editing this special issue explored several key questions: What does “innovation” mean when …

Robust And Parallel Segmentation Model (Rpsm) For Early Detection Of Skin Cancer Disease Using Heterogeneous Distributions, Nancy Zreika, Ali El-Zaart, Abdallah El Chakik

BAU Journal - Science and Technology

Melanoma is the most common dangerous type of skin cancer; however, it is preventable if it is diagnosed early. Diagnosis of Melanoma would be improved if an accurate skin image segmentation model is available. Many computer vision methods have been investigated, yet the problem of finding a consistent and robust model that extracts the best threshold value, persists. This paper suggests a novel image segmentation approach using a multilevel cross entropy thresholding algorithm based on heterogeneous distributions. The proposed strategy searches the problem space by segmenting the image into several levels, and applying for each level one of the three …

Deep-Learning Realtime Upsampling Techniques In Video Games, Biruk Mengistu

Scholarly Horizons: University of Minnesota, Morris Undergraduate Journal

This paper addresses the challenge of keeping up with the ever-increasing graphical complexity of video games and introduces a deep-learning approach to mitigating it. As games get more and more demanding in terms of their graphics, it becomes increasingly difficult to maintain high-quality images while also ensuring good performance. This is where deep learning super sampling (DLSS) comes in. The paper explains how DLSS works, including the use of convolutional autoencoder neural networks and various other techniques and technologies. It also covers how the network is trained and optimized, as well as how it incorporates temporal antialiasing and frame generation …

Exploring Methods Used In Face Swapping, Joshua Eklund

Scholarly Horizons: University of Minnesota, Morris Undergraduate Journal

Face swapping involves replacing the face in one image (the target) with a face in a different image (the source) while maintaining the pose and expression of the target face. Previous methods of face swapping required extensive computer power and man hours. As such, new methods are being developed that are quicker, less resource intensive, and more accessible to the non-expert. This paper provides background information on key methods used for face swapping and outlines three recently developed approaches: one based on generative adversarial networks, one based on linear 3D morphable models, and one based on encoder-decoders.

A Roller Coaster For The Mind: Virtual Reality Sickness Modes, Metrics, And Mitigation, Dalton C. Sparks

The Cardinal Edge

Understanding and preventing virtual reality sickness(VRS), or cybersickness, is vital in removing barriers for the technology's adoption. Thus, this article aims to synthesize a variety of academic sources to demonstrate the modes by which VRS occurs, the metrics by which it is judged, and the methods to mitigate it. The predominant theories on the biological origins of VRS are discussed, as well as the individual factors which increase the likelihood of a user developing VRS. Moreover, subjective and physiological measurements of VRS are discussed in addition to the development of a predictive model and conceptual framework. Finally, several methodologies of …