Taurus: Towards A Unified Force Representation And Universal Solver For Graph Layout,
2023
Singapore Management University
Taurus: Towards A Unified Force Representation And Universal Solver For Graph Layout, Mingliang Xue, Zhi Wang, Fahai Zhong, Yong Wang, Mingliang Xu, Oliver Deussen, Yunhai Wang
Research Collection School Of Computing and Information Systems
Over the past few decades, a large number of graph layout techniques have been proposed for visualizing graphs from various domains. In this paper, we present a general framework, Taurus, for unifying popular techniques such as the spring-electrical model, stress model, and maxent-stress model. It is based on a unified force representation, which formulates most existing techniques as a combination of quotient-based forces that combine power functions of graph-theoretical and Euclidean distances. This representation enables us to compare the strengths and weaknesses of existing techniques, while facilitating the development of new methods. Based on this, we propose a new balanced …
Enabling Customization Of Discussion Forums For Blind Users,
2023
Old Dominion University
Enabling Customization Of Discussion Forums For Blind Users, Mohan Sunkara, Yash Prakash, Hae-Na Lee, Sampath Jayarathna, Vikas Ashok
Computer Science Faculty Publications
Online discussion forums have become an integral component of news, entertainment, information, and video-streaming websites, where people all over the world actively engage in discussions on a wide range of topics including politics, sports, music, business, health, and world affairs. Yet, little is known about their usability for blind users, who aurally interact with the forum conversations using screen reader assistive technology. In an interview study, blind users stated that they often had an arduous and frustrating interaction experience while consuming conversation threads, mainly due to the highly redundant content and the absence of customization options to selectively view portions …
Autodesc: Facilitating Convenient Perusal Of Web Data Items For Blind Users,
2023
Old Dominion University
Autodesc: Facilitating Convenient Perusal Of Web Data Items For Blind Users, Yash Prakash, Mohan Sunkara, Hae-Na Lee, Sampath Jayarathna, Vikas Ashok
Computer Science Faculty Publications
Web data items such as shopping products, classifieds, and job listings are indispensable components of most e-commerce websites. The information on the data items are typically distributed over two or more webpages, e.g., a ‘Query-Results’ page showing the summaries of the items, and ‘Details’ pages containing full information about the items. While this organization of data mitigates information overload and visual cluttering for sighted users, it however increases the interaction overhead and effort for blind users, as back-and-forth navigation between webpages using screen reader assistive technology is tedious and cumbersome. Existing usability-enhancing solutions are unable to provide adequate support in …
Mwirgan: Unsupervised Visible-To Mwir Image Translation With Generative Adversarial Network,
2023
Old Dominion University
Mwirgan: Unsupervised Visible-To Mwir Image Translation With Generative Adversarial Network, Mohammad Shahab Uddin, Chiman Kwan, Jiang Li
Electrical & Computer Engineering Faculty Publications
Unsupervised image-to-image translation techniques have been used in many applications, including visible-to-Long-Wave Infrared (visible-to-LWIR) image translation, but very few papers have explored visible-to-Mid-Wave Infrared (visible-to-MWIR) image translation. In this paper, we investigated unsupervised visible-to-MWIR image translation using generative adversarial networks (GANs). We proposed a new model named MWIRGAN for visible-to-MWIR image translation in a fully unsupervised manner. We utilized a perceptual loss to leverage shape identification and location changes of the objects in the translation. The experimental results showed that MWIRGAN was capable of visible-to-MWIR image translation while preserving the object’s shape with proper enhancement in the translated images and …
An Interactive System For Generating Music From Moving Images,
2023
Dartmouth College
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 …
Simulating Incompressible Thin-Film Fluid With A Moving Eulerian-Lagrangian Particle Method,
2023
Dartmouth College
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, …
Hybrid Life Cycles In Software Development,
2022
Grand Valley State University
Hybrid Life Cycles In Software Development, Eric Vincent Schoenborn
Masters Projects
This project applied software specification gathering, architecture, work planning, and development to a real-world development effort for a local business. This project began with a feasibility meeting with the owner of Zeal Aerial Fitness. After feasibility was assessed the intended users, needed functionality, and expected user restrictions were identified with the stakeholders. A hybrid software lifecycle was selected to allow a focus on base functionality up front followed by an iterative development of expectations of the stakeholders. I was able to create various specification diagrams that express the end projects goals to both developers and non-tech individuals using a standard …
Augmented Reality Fonts With Enhanced Out-Of-Focus Text Legibility,
2022
Mississippi State University
Augmented Reality Fonts With Enhanced Out-Of-Focus Text Legibility, Mohammed Safayet Arefin
Theses and Dissertations
In augmented reality, information is often distributed between real and virtual contexts, and often appears at different distances from the viewer. This raises the issues of (1) context switching, when attention is switched between real and virtual contexts, (2) focal distance switching, when the eye accommodates to see information in sharp focus at a new distance, and (3) transient focal blur, when information is seen out of focus, during the time interval of focal distance switching. This dissertation research has quantified the impact of context switching, focal distance switching, and transient focal blur on human performance and eye fatigue in …
Transfer Of Personality Through Text Style,
2022
Technological University Dublin
Transfer Of Personality Through Text Style, Michael O'Mahony, Robert Ross
Other resources
The style of generated text is how something is said rather than what is said. We hypothesize that changing the style of generated text can change the perceived personality of the text generation agent. Dialogue systems that aim to imitate a human agent can appear to have a consistent personality through a consistent, controllable style of conversation. Some recent work on the style of generated text [1] performs impressively in the small number of domains selected for their experiments using transformer and LSTM-based models. Lin et al. [1] used weak supervised learning as their data set lacks parallel data. The …
Movie Reviews Sentiment Analysis Using Bert,
2022
University of Arkansas, Fayetteville
Movie Reviews Sentiment Analysis Using Bert, Gibson Nkhata
Graduate Theses and Dissertations
Sentiment analysis (SA) or opinion mining is analysis of emotions and opinions from texts. It is one of the active research areas in Natural Language Processing (NLP). Various approaches have been deployed in the literature to address the problem. These techniques devise complex and sophisticated frameworks in order to attain optimal accuracy with their focus on polarity classification or binary classification. In this paper, we aim to fine-tune BERT in a simple but robust approach for movie reviews sentiment analysis to provide better accuracy than state-of-the-art (SOTA) methods. We start by conducting sentiment classification for every review, followed by computing …
Disease Recognition In X-Ray Images With Doctor Consultation-Inspired Model,
2022
University of Dayton
Disease Recognition In X-Ray Images With Doctor Consultation-Inspired Model, Kim Anh Phung, Thuan Trong Nguyen, Nileshkumar Wangad, Samah Baraheem, Nguyen D. Vo, Khang Nguyen
Computer Science Faculty Publications
The application of chest X-ray imaging for early disease screening is attracting interest from the computer vision and deep learning community. To date, various deep learning models have been applied in X-ray image analysis. However, models perform inconsistently depending on the dataset. In this paper, we consider each individual model as a medical doctor. We then propose a doctor consultation-inspired method that fuses multiple models. In particular, we consider both early and late fusion mechanisms for consultation. The early fusion mechanism combines the deep learned features from multiple models, whereas the late fusion method combines the confidence scores of all …
Make Your Own Sprites: Aliasing-Aware And Cell-Controllable Pixelization,
2022
South China University of Technology
Make Your Own Sprites: Aliasing-Aware And Cell-Controllable Pixelization, Zongwei Wu, Liangyu Chai, Nanxuan Zhao, Bailin Deng, Yongtuo Liu, Qiang Wen, Junle Wang, Shengfeng He
Research Collection School Of Computing and Information Systems
Pixel art is a unique art style with the appearance of low resolution images. In this paper, we propose a data-driven pixelization method that can produce sharp and crisp cell effects with controllable cell sizes. Our approach overcomes the limitation of existing learning-based methods in cell size control by introducing a reference pixel art to explicitly regularize the cell structure. In particular, the cell structure features of the reference pixel art are used as an auxiliary input for the pixelization process, and for measuring the style similarity between the generated result and the reference pixel art. Furthermore, we disentangle the …
Vr Computing Lab: An Immersive Classroom For Computing Learning,
2022
Singapore Management University
Vr Computing Lab: An Immersive Classroom For Computing Learning, Shawn Pang, Kyong Jin Shim, Yi Meng Lau, Swapna Gottipati
Research Collection School Of Computing and Information Systems
In recent years, virtual reality (VR) is gaining popularity amongst educators and learners. If a picture is worth a thousand words, a VR session is worth a trillion words. VR technology completely immerses users with an experience that transports them into a simulated world. Universities across the United States, United Kingdom, and other countries have already started using VR for higher education in areas such as medicine, business, architecture, vocational training, social work, virtual field trips, virtual campuses, helping students with special needs, and many more. In this paper, we propose a novel VR platform learning framework which maps elements …
Multi-Relation Extraction Via A Global-Local Graph Convolutional Network,
2022
Shandong University
Multi-Relation Extraction Via A Global-Local Graph Convolutional Network, Harry Cheng, Lizi Liao, Linmei Hu, Liqiang Nie
Research Collection School Of Computing and Information Systems
Relation extraction (RE) extracts the semantic relations among entities in a sentence, which converts the unstructured text into structured and easy-to-understand information. Although RE has been studied over decades, it still faces two kinds of research challenges that are not well addressed thus far: 1) joint consideration of the global sentence structure and the local entity interaction, and 2) effective solution to the overlapping triplets within the same sentence. To tackle these issues, in this paper, we present globallocal graph-based convolutional network towards multi-relation extraction, GAME for short. In particular, we devise two layers of graph convolutional network (GCN) with …
Prompting For Multimodal Hateful Meme Classification,
2022
Singapore Management University
Prompting For Multimodal Hateful Meme Classification, Rui Cao, Roy Ka-Wei Lee, Wen-Haw Chong, Jing Jiang
Research Collection School Of Computing and Information Systems
Hateful meme classification is a challenging multimodal task that requires complex reasoning and contextual background knowledge. Ideally, we could leverage an explicit external knowledge base to supplement contextual and cultural information in hateful memes. However, there is no known explicit external knowledge base that could provide such hate speech contextual information. To address this gap, we propose PromptHate, a simple yet effective prompt-based model that prompts pre-trained language models (PLMs) for hateful meme classification. Specifically, we construct simple prompts and provide a few in-context examples to exploit the implicit knowledge in the pretrained RoBERTa language model for hateful meme classification. …
Developing And Facilitating Temporary Team Mental Models Through An Information-Sharing Recommender System,
2022
Clemson University
Developing And Facilitating Temporary Team Mental Models Through An Information-Sharing Recommender System, Geoffrey Musick
All Dissertations
It is well understood that teams are essential and common in many aspects of life, both work and leisure. Due to the importance of teams, much research attention has focused on how to improve team processes and outcomes. Of particular interest are the cognitive aspects of teamwork including team mental models (TMMs). Among many other benefits, TMMs involve team members forming a compatible understanding of the task and team in order to more efficiently make decisions. This understanding is sometimes classified using four TMM domains: equipment (e.g., operating procedures), task (e.g., strategies), team interactions (e.g., interdependencies) and teammates (e.g., tendencies). …
Design And Comparison Of Asynchronous Fft Implementations,
2022
University of Arkansas, Fayetteville
Design And Comparison Of Asynchronous Fft Implementations, Julie Bigot
Graduate Theses and Dissertations
Fast Fourier Transform (FFT) is a widely used digital signal processing technology in a large variety of applications. For battery-powered embedded systems incorporating FFT, its physical implementation is constrained by strict power consumption, especially during idle periods. Compared to the prevailing clocked synchronous counterpart, quasi-delay insensitive asynchronous circuits offer a series of advantages including flexible timing requirement and lower leakage power, making them ideal choices for these systems. In this thesis work, various FFT configurations were implemented in the low-power Multi-Threshold NULL Convention Logic (MTNCL) paradigm. Analysis illustrates the area and power consumption trends along the changing of the number …
Electrical Modeling For Dynamic Performance Prediction And Optimization Of Mcpms Layout,
2022
University of Arkansas, Fayetteville
Electrical Modeling For Dynamic Performance Prediction And Optimization Of Mcpms Layout, Quang Minh Le
Graduate Theses and Dissertations
In recent years, the fast development of Multichip Power Modules (MCPM) packaging and Wide Bandgap (WBG) technology has enabled higher voltage and current ratings, better thermal performance, lower parasitic parameters, and higher mechanical reliability. However, the design of the MCPM layout is a multidisciplinary problem leading to many time-consuming analyses and tedious design processes. Because of these challenges, the design automation tool for MCPM layout has become an emerging research area and gained much attention from the power electronics community. The two critical objectives of a design automation tool for MCPM layout are fast and accurate models for design insights …
Multivariate Fairness For Paper Selection,
2022
University of Arkansas, Fayetteville
Multivariate Fairness For Paper Selection, Reem Alsaffar
Graduate Theses and Dissertations
Peer review is the process by which publishers select the best publications for inclusion in a journal or a conference. Bias in the peer review process can impact which papers are selected for inclusion in conferences and journals. Although often implicit, race, gender and other demographics can prevent members of underrepresented groups from presenting at major conferences. To try to avoid bias, many conferences use a double-blind review process to increase fairness during reviewing. However, recent studies argue that the bias has not been removed completely. Our research focuses on developing fair algorithms that correct for these biases and select …
Appearance-Preserved Portrait-To-Anime Translation Via Proxy-Guided Domain Adaptation,
2022
Singapore Management University
Appearance-Preserved Portrait-To-Anime Translation Via Proxy-Guided Domain Adaptation, Wenpeng Xiao, Cheng Xu, Jiajie Mai, Xuemiao Xu, Yue Li, Chengze Li, Xueting Liu, Shengfeng He
Research Collection School Of Computing and Information Systems
Converting a human portrait to anime style is a desirable but challenging problem. Existing methods fail to resolve this problem due to the large inherent gap between two domains that cannot be overcome by a simple direct mapping. For this reason, these methods struggle to preserve the appearance features in the original photo. In this paper, we discover an intermediate domain, the coser portrait (portraits of humans costuming as anime characters), that helps bridge this gap. It alleviates the learning ambiguity and loosens the mapping difficulty in a progressive manner. Specifically, we start from learning the mapping between coser and …
