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A Roller Coaster For The Mind: Virtual Reality Sickness Modes, Metrics, And Mitigation, Dalton C. Sparks 2022 University of Louisville

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 …


Analysis Of Graph Layout Algorithms For Use In Command And Control Network Graphs, Matthew R. Stone 2022 Air Force Institute of Technology

Analysis Of Graph Layout Algorithms For Use In Command And Control Network Graphs, Matthew R. Stone

Theses and Dissertations

This research is intended to determine which styles of layout algorithm are well suited to Command and Control (C2) network graphs to replace current manual layout methods. Manual methods are time intensive and an automated layout algorithm should decrease the time spent creating network graphs. Simulations on realistic synthetically generated graphs provide information to help infer which algorithms perform better than others on this problem. Data is generated using statistics drawn from multiple real world C2 network graphs. The three algorithms tested against this data are the Spectral algorithm, the Dot algorithm, and the Fruchterman-Reingold algorithm. The results include a …


Largeea: Aligning Entities For Large-Scale Knowledge Graphs, Congcong GE, Xiaoze LIU, Lu CHEN, Yunjun GAO, Baihua ZHENG 2022 Singapore Management University

Largeea: Aligning Entities For Large-Scale Knowledge Graphs, Congcong Ge, Xiaoze Liu, Lu Chen, Yunjun Gao, Baihua Zheng

Research Collection School Of Computing and Information Systems

Entity alignment (EA) aims to find equivalent entities in different knowledge graphs (KGs). Current EA approaches suffer from scalability issues, limiting their usage in real-world EA scenarios. To tackle this challenge, we propose LargeEA to align entities between large-scale KGs. LargeEA consists of two channels, i.e., structure channel and name channel. For the structure channel, we present METIS-CPS, a memory-saving mini-batch generation strategy, to partition large KGs into smaller mini-batches. LargeEA, designed as a general tool, can adopt any existing EA approach to learn entities’ structural features within each mini-batch independently. For the name channel, we first introduce NFF, a …


Distance Based Image Classification: A Solution To Generative Classification’S Conundrum?, Wen-yan LIN, Siying LIU, Bing Tian DAI, Hongdong LI 2022 Singapore Management University

Distance Based Image Classification: A Solution To Generative Classification’S Conundrum?, Wen-Yan Lin, Siying Liu, Bing Tian Dai, Hongdong Li

Research Collection School Of Computing and Information Systems

Most classifiers rely on discriminative boundaries that separate instances of each class from everything else. We argue that discriminative boundaries are counter-intuitive as they define semantics by what-they-are-not; and should be replaced by generative classifiers which define semantics by what-they-are. Unfortunately, generative classifiers are significantly less accurate. This may be caused by the tendency of generative models to focus on easy to model semantic generative factors and ignore non-semantic factors that are important but difficult to model. We propose a new generative model in which semantic factors are accommodated by shell theory’s [25] hierarchical generative process and non-semantic factors by …


Factors That Influence The Implementation Of Information And Communication Technology Inclusive Design Practices In Organisations, Faizel Ebrahim, Salah Kabanda, Guidance Mthwazi 2022 University of Cape Town

Factors That Influence The Implementation Of Information And Communication Technology Inclusive Design Practices In Organisations, Faizel Ebrahim, Salah Kabanda, Guidance Mthwazi

African Conference on Information Systems and Technology

Inclusive design in information and communication technology (ICT) is the development of information and communication technology artifacts that are accessible and easy to use for as many people as possible. Human diversities must be considered when producing these inclusive design artifacts. It is not only important for abled people but also extends to people with disabilities, the elderly and anybody challenged with using these artifacts. Yet, few designers and developers adopt inclusive design methodologies in their practice. This study seeks to identify and understand the factors that influence the implementation of inclusive design practices in organisations. The methodology was based …


Evaluating Privacy Adaptation Presentation Methods To Support Social Media Users In Their Privacy-Related Decision-Making Process, Moses Namara 2022 Clemson University

Evaluating Privacy Adaptation Presentation Methods To Support Social Media Users In Their Privacy-Related Decision-Making Process, Moses Namara

All Dissertations

Several privacy scholars have advocated for user-tailored privacy (UTP). A privacy-enhancing adaptive privacy approach to help reconcile users' lack of awareness, privacy management skills and motivation to use available platform privacy features with their need for personalized privacy support in alignment with their privacy preferences. The idea behind UTP is to measure users' privacy characteristics and behaviors, use these measurements to create a personalized model of the user's privacy preferences, and then provide adaptive support to the user in navigating and engaging with the available privacy settings---or even implement certain settings automatically on the user's behalf. To this end, most …


A Detailed Review Work On The Existing Animal Detection System, Dechen Doma Bhutia Miss, Swarup Das Dr., Rakesh Kumar Mandal Dr. 2022 North Bengal University,West Bengal,India

A Detailed Review Work On The Existing Animal Detection System, Dechen Doma Bhutia Miss, Swarup Das Dr., Rakesh Kumar Mandal Dr.

International Journal of Computer and Communication Technology

Technology plays a very important part in today’s world, the simplest of tasks demands technology and we as humans crave every day for better technology to make our lives easier, with the help of technology that saves us valuable time and energy which can be utilized to do more productive work, amongst technological advances, expert system plays a very important role in every field and the major field where expert systems can be employed in, is animal detection, for the welfare of animals and the people who need to interact and at times avoid interaction with these animals. The review …


The Message Design Of Raiders Of The Lost Ark On The Atari 2600 & A Fan’S Map, Quick Start, And Strategy Guide, Miguel Ramlatchan, William I. Ramlatchan 2022 Old Dominion University

The Message Design Of Raiders Of The Lost Ark On The Atari 2600 & A Fan’S Map, Quick Start, And Strategy Guide, Miguel Ramlatchan, William I. Ramlatchan

Distance Learning Faculty & Staff Books

The message design and human performance technology in video games, especially early video games have always been fascinating to me. From an instructional design perspective, the capabilities of the technology of the classic game consoles required a careful balance of achievable objectives, cognitive task analysis, guided problem solving, and message design. Raiders on the Atari is an excellent example of this balance. It is an epic adventure game, spanning 13+ distinct areas, with an inventory of items, where those hard to find items had to be used by the player to solve problems during their quest (and who would have …


Open-Set Domain Adaptation By Deconfounding Domain Gaps, Xin ZHAO, Shengsheng WANG, Qianru SUN 2022 Singapore Management University

Open-Set Domain Adaptation By Deconfounding Domain Gaps, Xin Zhao, Shengsheng Wang, Qianru Sun

Research Collection School Of Computing and Information Systems

Open-Set Domain Adaptation (OSDA) aims to adapt the model trained on a source domain to the recognition tasks in a target domain while shielding any distractions caused by open-set classes, i.e., the classes “unknown” to the source model. Compared to standard DA, the key of OSDA lies in the separation between known and unknown classes. Existing OSDA methods often fail the separation because of overlooking the confounders (i.e., the domain gaps), which means their recognition of “unknown classes” is not because of class semantics but domain difference (e.g., styles and contexts). We address this issue by explicitly deconfounding domain gaps …


Snerf: Stylized Neural Implicit Representations For 3d Scenes, Thu Nguyen-Phuoc, Feng Liu, Lei Xiao 2022 Meta

Snerf: Stylized Neural Implicit Representations For 3d Scenes, Thu Nguyen-Phuoc, Feng Liu, Lei Xiao

Computer Science Faculty Publications and Presentations

This paper presents a stylized novel view synthesis method. Applying state-of-the-art stylization methods to novel views frame by frame often causes jittering artifacts due to the lack of cross-view consistency. Therefore, this paper investigates 3D scene stylization that provides a strong inductive bias for consistent novel view synthesis. Specifically, we adopt the emerging neural radiance fields (NeRF) as our choice of 3D scene representation for their capability to render high-quality novel views for a variety of scenes. However, as rendering a novel view from a NeRF requires a large number of samples, training a stylized NeRF requires a large amount …


Proceedings Of The 13th International Workshop On Graph Computation Models (Gcm 2022), Reiko HECKEL, Christopher M. POSKITT 2022 Singapore Management University

Proceedings Of The 13th International Workshop On Graph Computation Models (Gcm 2022), Reiko Heckel, Christopher M. Poskitt

Research Collection School Of Computing and Information Systems

This volume contains the proceedings of the Thirteenth International Workshop on Graph Computation Models (GCM 2022) , which was held in Nantes, France on 6th July 2022 as part of the STAF federation of conferences. Graphs are common mathematical structures that are visual and intuitive. They constitute a natural and seamless way for system modelling in science, engineering, and beyond, including computer science, biology, and business process modelling. Graph computation models constitute a class of very high-level models where graphs are first-class citizens. The aim of the International GCM Workshop series is to bring together researchers interested in all aspects …


A Low-Cost Virtual Coach For 2d Video-Based Compensation Assessment Of Upper Extremity Rehabilitation Exercises, Ana Rita Coias, Min Hun LEE, Alexandre Bernardino 2022 Singapore Management University

A Low-Cost Virtual Coach For 2d Video-Based Compensation Assessment Of Upper Extremity Rehabilitation Exercises, Ana Rita Coias, Min Hun Lee, Alexandre Bernardino

Research Collection School Of Computing and Information Systems

Background: The increasing demands concerning stroke rehabilitation and in-home exercise promotion grew the need for affordable and accessible assistive systems to promote patients' compliance in therapy. These assistive systems require quantitative methods to assess patients' quality of movement and provide feedback on their performance. However, state-of-the-art quantitative assessment approaches require expensive motion-capture devices, which might be a barrier to the development of low-cost systems.Methods: In this work, we develop a low-cost virtual coach (VC) that requires only a laptop with a webcam to monitor three upper extremity rehabilitation exercises and provide real-time visual and audio feedback on compensatory motion patterns …


Docee: A Large-Scale And Fine-Grained Benchmark For Document-Level Event Extraction, Meihan TONG, Bin XU, Shuai WANG, Meihuan HAN, Yixin CAO, Jiangqi ZHU, Siyu CHEN, Lei HOU, Juanzi LI 2022 Singapore Management University

Docee: A Large-Scale And Fine-Grained Benchmark For Document-Level Event Extraction, Meihan Tong, Bin Xu, Shuai Wang, Meihuan Han, Yixin Cao, Jiangqi Zhu, Siyu Chen, Lei Hou, Juanzi Li

Research Collection School Of Computing and Information Systems

Event extraction aims to identify an event and then extract the arguments participating in the event. Despite the great success in sentencelevel event extraction, events are more naturally presented in the form of documents, with event arguments scattered in multiple sentences. However, a major barrier to promote documentlevel event extraction has been the lack of large-scale and practical training and evaluation datasets. In this paper, we present DocEE, a new document-level event extraction dataset including 27,000+ events, 180,000+ arguments. We highlight three features: largescale manual annotations, fine-grained argument types and application-oriented settings. Experiments show that there is still a big …


End-To-End Open-Set Semi-Supervised Node Classification With Out-Of-Distribution Detection, Tiancheng HUANG, Donglin WANG, Yuan FANG 2022 Singapore Management University

End-To-End Open-Set Semi-Supervised Node Classification With Out-Of-Distribution Detection, Tiancheng Huang, Donglin Wang, Yuan Fang

Research Collection School Of Computing and Information Systems

Out-Of-Distribution (OOD) samples are prevalent in real-world applications. The OOD issue becomes even more severe on graph data, as the effect of OOD nodes can be potentially amplified by propagation through the graph topology. Recent works have considered the OOD detection problem, which is critical for reducing the uncertainty in learning and improving the robustness. However, no prior work considers simultaneously OOD detection and node classification on graphs in an end-to-end manner. In this paper, we study a novel problem of end-to-end open-set semisupervised node classification (OSSNC) on graphs, which deals with node classification in the presence of OOD nodes. …


Enhancing Security Patch Identification By Capturing Structures In Commits, Bozhi WU, Shangqing LIU, Ruitao FENG, Xiaofei XIE, Jingkai SIOW, Shang-Wei LIN 2022 Singapore Management University

Enhancing Security Patch Identification By Capturing Structures In Commits, Bozhi Wu, Shangqing Liu, Ruitao Feng, Xiaofei Xie, Jingkai Siow, Shang-Wei Lin

Research Collection School Of Computing and Information Systems

With the rapid increasing number of open source software (OSS), the majority of the software vulnerabilities in the open source components are fixed silently, which leads to the deployed software that integrated them being unable to get a timely update. Hence, it is critical to design a security patch identification system to ensure the security of the utilized software. However, most of the existing works for security patch identification just consider the changed code and the commit message of a commit as a flat sequence of tokens with simple neural networks to learn its semantics, while the structure information is …


Analysis Of Digital Image Segmentation Algorithms, Khalilov Sirojiddin 2022 Nurafshan branch of Tashkent University of Information Technologies named after Muhammad al-Khwarizmi

Analysis Of Digital Image Segmentation Algorithms, Khalilov Sirojiddin

Karakalpak Scientific Journal

Ushbu maqolada zamonaviy axborot-kommunikatsiya texnologiyalaridan foydalanishni kengaytirish maqsadida raqamli tasvirni qayta ishlash usullari va algoritmlari tahlil qilinadi. Maqolada, shuningdek, raqamli tasvirni qayta ishlash, tasvirni segmentatsiyalash usullari, WaterShed, MeanShift, FloodFill, GrabCut algoritmlarining afzalliklari va kamchiliklari o'rganiladi.


Spotlight Report #6: Proffering Machine-Readable Personal Privacy Research Agreements: Pilot Project Findings For Ieee P7012 Wg, Noreen Y. Whysel, Lisa LeVasseur 2022 Internet Safety Labs

Spotlight Report #6: Proffering Machine-Readable Personal Privacy Research Agreements: Pilot Project Findings For Ieee P7012 Wg, Noreen Y. Whysel, Lisa Levasseur

Publications and Research

What if people had the ability to assert their own legally binding permissions for data collection, use, sharing, and retention by the technologies they use? The IEEE P7012 has been working on an interoperability specification for machine-readable personal privacy terms to support this ability since 2018. The premise behind the work of IEEE P7012 is that people need technology that works on their behalf—i.e. software agents that assert the individual’s permissions and preferences in a machine-readable format.

Thanks to a grant from the IEEE Technical Activities Board Committee on Standards (TAB CoS), we were able to explore the attitudes of …


Corrective Feedback Timing In Kanji Writing Instruction Apps, Phoenix Mulgrew 2022 Union College - Schenectady, NY

Corrective Feedback Timing In Kanji Writing Instruction Apps, Phoenix Mulgrew

Honors Theses

The focus of this research paper is to determine the correct time to provide corrective feedback to people who are learning how to write Japanese kanji. To do this, we developed a system that is able to recognize Japanese kanji that is handwritten onto an iPad screen and check for errors such as wrong stroke order. Previous research has achieved success in developing similar systems, but this project is unique because the research question involves the timing of corrective feedback. In particular, we are looking at whether immediate or delayed corrective feedback results in better learning.


Designing Narrative-Based Interfaces For Collective Action: A Case Study Using Amazon, Climate Change, And Consumer Behavior, Catherine Parnell 2022 Dartmouth College

Designing Narrative-Based Interfaces For Collective Action: A Case Study Using Amazon, Climate Change, And Consumer Behavior, Catherine Parnell

Dartmouth College Undergraduate Theses

Climate change is the most pressing issue facing future generations. Amongst expanses of the population there is a lack of collective action on environmental issues, as there is a large gap between awareness and behavior change. This study suggests persuasive design that utilizes a narrative framing as a solution to reduce barriers to engaging in issues of collective action. Through extensive need-finding studies to understand target users, this thesis uses online-shopping via Amazon as a context for arguing that narrative can support actionable change in behavior. The technical artifact resulting from this research is a developed chrome extension and web …


Reinforcement Learning-Based Interactive Video Search, Zhixin MA, Jiaxin WU, Chong-wah NGO, Chong-Wah NGO 2022 Singapore Management University

Reinforcement Learning-Based Interactive Video Search, Zhixin Ma, Jiaxin Wu, Chong-Wah Ngo, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

Despite the rapid progress in text-to-video search due to the advancement of cross-modal representation learning, the existing techniques still fall short in helping users to rapidly identify the search targets. Particularly, in the situation that a system suggests a long list of similar candidates, the user needs to painstakingly inspect every search result. The experience is frustrated with repeated watching of similar clips, and more frustratingly, the search targets may be overlooked due to mental tiredness. This paper explores reinforcement learning-based (RL) searching to relieve the user from the burden of brute force inspection. Specifically, the system maintains a graph …


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