Graphics and Human Computer Interfaces Commons^™

Relationships Between Willingness To Share Information For Benefits And Trust, Gaurav Bansal, Fiona Fui-Hoon Nah

Research Collection School Of Computing and Information Systems

This research examines the role of willingness to share one’s information for three benefits as tradeoffs – monetary gains, personalization, and national security – and their effects on trust in online businesses. Data were gathered from MTurk and the results indicate that willingness to share information for monetary gains and personalization is marginally associated with trust in online businesses, but willingness to share information for national security has no association with trust in online businesses. The paper also discusses implications, limitations, and future research directions.

Stay-At-Home Motor Rehabilitation: Optimizing Spatiotemporal Learning On Low-Cost Capacitive Sensor Arrays, Reid Sutherland

Graduate Theses and Dissertations

Repeated, consistent, and precise gesture performance is a key part of recovery for stroke and other motor-impaired patients. Close professional supervision to these exercises is also essential to ensure proper neuromotor repair, which consumes a large amount of medical resources. Gesture recognition systems are emerging as stay-at-home solutions to this problem, but the best solutions are expensive, and the inexpensive solutions are not universal enough to tackle patient-to-patient variability. While many methods have been studied and implemented, the gesture recognition system designer does not have a strategy to effectively predict the right method to fit the needs of a patient. …

Storage Management Strategy In Mobile Phones For Photo Crowdsensing, En Wang, Zhengdao Qu, Xinyao Liang, Xiangyu Meng, Yongjian Yang, Dawei Li, Weibin Meng

Department of Computer Science Faculty Scholarship and Creative Works

In mobile crowdsensing, some users jointly finish a sensing task through the sensors equipped in their intelligent terminals. In particular, the photo crowdsensing based on Mobile Edge Computing (MEC) collects pictures for some specific targets or events and uploads them to nearby edge servers, which leads to richer data content and more efficient data storage compared with the common mobile crowdsensing; hence, it has attracted an important amount of attention recently. However, the mobile users prefer uploading the photos through Wifi APs (PoIs) rather than cellular networks. Therefore, photos stored in mobile phones are exchanged among users, in order to …

A Distributed Model-View-Controller Design Pattern For A Graphical Remote Control Of A Multi-User Application, Dale E. Parson

Computer Science and Information Technology Faculty

The Model-View-Controller (MVC) is a design pattern for architecting the interactions among human users of graphical computing systems with the software Controller that manages user input, the Model that houses system state, and the View that projects the Model state into intelligible graphical form. The present work examines extending MVC into a Distributed Model-View-Controller pattern, starting with a stand-alone MVC system that is amenable to distribution over a local area network (LAN). Distribution takes the form of cloning a stand-alone MVC application into distinct client and server programs, and then altering each for its purpose while maintaining the initial graphical …

Poster Abstract: Data Communication Using Switchable Privacy Glass, Changshuo Hu, Dong Ma, Mahbub Hassan, Wen Hu

Research Collection School Of Computing and Information Systems

Switchable privacy glass can electronically change its state between opaque and transparent. In this work, we propose to exploit the electronic configurability of switchable glass to modulate natural light, which can be demodulated by a nearby receiver with light sensing capability to realise data communication over natural light. A key advantage is that no energy is used to generate light, as it simply modulates the existing light in the nature. We demonstrate that the proposed data communication using switchable glass modulation can achieve 33.33 bits per second communication with a bit rate below 1% under a wide range of ambient …

Techniques To Visualize Occluded Graph Elements For 2.5d Map Editing, Kazuyuki Fujita, Daigo Hayashi, Kotaro Hara, Kazuki Takashima, Yoshifumi Kitamura

Research Collection School Of Computing and Information Systems

We propose an interface with two novel techniques to visualize occluded graph nodes and edges that help the user edit map data with a 2.5D geographical structure (e.g., multi-floor indoor maps). We first design a visualization technique —Repel Signification— that employs micro-animation to signify the graph elements that are overlapping with each other (and potentially erroneous). We also design a technique that enables the user to edit the occluded components with Expansion Interaction, which simultaneously visualizes both in-floor and across-floor occluded connections between the map elements. The combination of the two methods would enable the map editors (non-experts) to effectively …

Dfseer: A Visual Analytics Approach To Facilitate Model Selection For Demand Forecasting, Dong Sun, Zezheng Feng, Yuanzhe Chen, Yong Wang, Jia Zeng, Mingxuan Yuan, Ting-Chuen Pong, Huamin Qu

Research Collection School Of Computing and Information Systems

Selecting an appropriate model to forecast product demand is critical to the manufacturing industry. However, due to the data complexity, market uncertainty and users’ demanding requirements for the model, it is challenging for demand analysts to select a proper model. Although existing model selection methods can reduce the manual burden to some extent, they often fail to present model performance details on individual products and reveal the potential risk of the selected model. This paper presents DFSeer, an interactive visualization system to conduct reliable model selection for demand forecasting based on the products with similar historical demand. It supports model …

Reinforced Negative Sampling Over Knowledge Graph For Recommendation, Xiang Wang, Yaokun Xu, Xiangnan He, Yixin Cao, Meng Wang, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Properly handling missing data is a fundamental challenge in recommendation. Most present works perform negative sampling from unobserved data to supply the training of recommender models with negative signals. Nevertheless, existing negative sampling strategies, either static or adaptive ones, are insufficient to yield high-quality negative samples — both informative to model training and reflective of user real needs. In this work, we hypothesize that item knowledge graph (KG), which provides rich relations among items and KG entities, could be useful to infer informative and factual negative samples. Towards this end, we develop a new negative sampling model, Knowledge Graph Policy …

The Effects Of Mixed-Initiative Visualization Systems On Exploratory Data Analysis, Adam Kern

McKelvey School of Engineering Graduate Student Theses & Dissertations

The main purpose of information visualization is to act as a window between a user and data. Historically, this has been accomplished via a single-agent framework: the only decisionmaker in the relationship between visualization system and analyst is the analyst herself. Yet this framework arose not from first principles, but from necessity: prior to this decade, computers were limited in their decision-making capabilities, especially in the face of large, complex datasets and visualization systems. This thesis aims to present the design and evaluation of a mixed-initiative system that aids the user in handling large, complex datasets and dense visualization systems. …

The Impact Of Changing The Size Of Aircraft Radar Displays On Visual Search In The Cockpit, Justin R. Marsh

Theses and Dissertations

Advances in sensor technology have enabled our fighter aircraft to find, fix, track, target, engage (F2T2E) at greater distances, providing the operator with more data within the battlefield. Modern aircraft are designed with larger displays while our legacy aircraft are being retrofitted with larger cockpit displays to enable display of the increased data. While this modification has been shown to enable improvements in human performance of many cockpit tasks, this effect is often not measured nor fully understood at a more generalizable level. This research outlines an approach to comparing human performance across two display sizes in future F-16 cockpits. …

Electronic Image Detectability Under Varying Illumination Conditions, Jeremy J. Miller

Theses and Dissertations

Light in the built environment plays an essential role in the vision and the health of humans through non-visual receptors in the eyes. Unfortunately, image analysts and other Air Force personnel who engage in the detection of objects on softcopy displays are often required to work in very dimly-lit or dark environments as higher illumination reduces the contrast of displayed information. Literature has shown that increases in light exposure improves circadian rhythm entrainment and reduces the negative health consequences of insufficient lighting. This research examines the effects of indoor lighting to determine if increases in ambient illumination or changes to …

Zero-Shot Ingredient Recognition By Multi-Relational Graph Convolutional Network, Jingjing Chen, Liangming Pan, Zhipeng Wei, Xiang Wang, Chong-Wah Ngo, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Recognizing ingredients for a given dish image is at the core of automatic dietary assessment, attracting increasing attention from both industry and academia. Nevertheless, the task is challenging due to the difficulty of collecting and labeling sufficient training data. On one hand, there are hundred thousands of food ingredients in the world, ranging from the common to rare. Collecting training samples for all of the ingredient categories is difficult. On the other hand, as the ingredient appearances exhibit huge visual variance during the food preparation, it requires to collect the training samples under different cooking and cutting methods for robust …

Image Enhanced Event Detection In News Articles, Meihan Tong, Shuai Wang, Yixin Cao, Bin Xu, Juaizi Li, Lei Hou, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Event detection is a crucial and challenging sub-task of event extraction, which suffers from a severe ambiguity issue of trigger words. Existing works mainly focus on using textual context information, while there naturally exist many images accompanied by news articles that are yet to be explored. We believe that images not only reflect the core events of the text, but are also helpful for the disambiguation of trigger words. In this paper, we first contribute an image dataset supplement to ED benchmarks (i.e., ACE2005) for training and evaluation. We then propose a novel Dual Recurrent Multimodal Model, DRMM, to conduct …

Example-Based Colourization Via Dense Encoding Pyramids, Chufeng Xiao, Chu Han, Zhuming Zhang, Jing Qin, Tien-Tsin Wong, Guoqiang Han, Shengfeng He

Research Collection School Of Computing and Information Systems

We propose a novel deep example-based image colourization method called dense encoding pyramid network. In our study, we define the colourization as a multinomial classification problem. Given a greyscale image and a reference image, the proposed network leverages large-scale data and then predicts colours by analysing the colour distribution of the reference image. We design the network as a pyramid structure in order to exploit the inherent multi-scale, pyramidal hierarchy of colour representations. Between two adjacent levels, we propose a hierarchical decoder–encoder filter to pass the colour distributions from the lower level to higher level in order to take both …

Gdface: Gated Deformation For Multi-View Face Image Synthesis, Xuemiao Xu, Keke Li, Cheng Xu, Shengfeng He

Research Collection School Of Computing and Information Systems

Photorealistic multi-view face synthesis from a single image is an important but challenging problem. Existing methods mainly learn a texture mapping model from the source face to the target face. However, they fail to consider the internal deformation caused by the change of poses, leading to the unsatisfactory synthesized results for large pose variations. In this paper, we propose a Gated Deformable Face Synthesis Network to model the deformation of faces that aids the synthesis of the target face image. Specifically, we propose a dual network that consists of two modules. The first module estimates the deformation of two views …

Accessibility Of Deepfakes, Andrew L. Collings

Cybersecurity Undergraduate Research Showcase

The danger posed by falsified media, commonly referred to as deepfakes, has been well researched and documented. The software Faceswap to was used to swap the faces of two politician (Joe Biden and Donald Trump). The testing was performed using an affordable consumer GPU (an AMD Radeon RX 570) over 100,000 iterations. The process and results for the two attempts with the best results (and largest differences) were recorded. The result was ultimately unconvincing, while the software was able to recreate the facial structure the lighting and skin tone did not blend at all.

Building Something With The Raspberry Pi, Richard Kordel

Harrisburg University Presidential Research Grants

In 2017 Ryan Korn and I submitted a grant proposal in the annual Harrisburg University President’s Grant process. Our proposal was to partner with a local high school to install a classroom of 20 Raspberry Pi’s, along with the requisite peripherals. In that classroom students would be challenged to design something that combined programming with physical computing. In our presentation to the school we suggested that this project would give students the opportunity to be “amazing.”

As part of the grant, the top three students would be given scholarships to HU and the top five finalists would all be permitted …

Svat4: A Computer Program For Visualization And Analysis Of Crystal Structures, Xingzhong Li

Nebraska Center for Materials and Nanoscience: Faculty Publications

SVAT4 is a computer program for interactive visualization of three-dimensional crystal structures, including chemical bonds and magnetic moments. A wide range of functions, e.g. revealing atomic layers and polyhedral clusters, are available for further structural analysis. Atomic sizes, colors, appearance, view directions and view modes (orthographic or perspective views) are adjustable. Customized work for the visualization and analysis can be saved and then reloaded. SVAT4 provides a template to simplify the process of preparation of a new data file. SVAT4 can generate high-quality images for publication and animations for presentations. The usability of SVAT4 is broadened by a software suite …

Nnv: The Neural Network Verification Tool For Deep Neural Networks And Learning-Enabled Cyber-Physical Systems, Hoang-Dung Tran, Xiaodong Yang, Diego Manzanas Lopez, Patrick Musau, Luan Viet Nguyen, Weiming Xiang, Stanley Bak, Taylor T. Johnson

Computer Science Faculty Publications

This paper presents the Neural Network Verification (NNV) software tool, a set-based verification framework for deep neural networks (DNNs) and learning-enabled cyber-physical systems (CPS). The crux of NNV is a collection of reachability algorithms that make use of a variety of set representations, such as polyhedra, star sets, zonotopes, and abstract-domain representations. NNV supports both exact (sound and complete) and over-approximate (sound) reachability algorithms for verifying safety and robustness properties of feed-forward neural networks (FFNNs) with various activation functions. For learning-enabled CPS, such as closed-loop control systems incorporating neural networks, NNV provides exact and over-approximate reachability analysis schemes for linear …

A Saliency-Driven Video Magnifier For People With Low Vision, Ali Selman Aydin, Shirin Feiz, Iv Ramakrishnan, Vikas Ashok

Computer Science Faculty Publications

Consuming video content poses significant challenges for many screen magnifier users, which is the “go to” assistive technology for people with low vision. While screen magnifier software could be used to achieve a zoom factor that would make the content of the video visible to low-vision users, it is oftentimes a major challenge for these users to navigate through videos. Towards making videos more accessible for low-vision users, we have developed the SViM video magnifier system [6]. Specifically, SViM consists of three different magnifier interfaces with easy-to-use means of interactions. All three interfaces are driven by visual saliency as a …