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Articles 45571 - 45600 of 294392

Full-Text Articles in Physical Sciences and Mathematics

The Coming Of Age Of Nucleic Acid Vaccines During Covid-19, Halie M. Rando, Ronan Lordan, Likhitha Kolla, Elizabeth Sell, Alexandra J. Lee, Nils Wellhausen, Amruta Naik, Jeremy P. Kamil, Anthony Gitter, Casey S. Greene Mar 2023

The Coming Of Age Of Nucleic Acid Vaccines During Covid-19, Halie M. Rando, Ronan Lordan, Likhitha Kolla, Elizabeth Sell, Alexandra J. Lee, Nils Wellhausen, Amruta Naik, Jeremy P. Kamil, Anthony Gitter, Casey S. Greene

Computer Science: Faculty Publications

In the 21st century, several emergent viruses have posed a global threat. Each pathogen has emphasized the value of rapid and scalable vaccine development programs. The ongoing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has made the importance of such efforts especially clear. New biotechnological advances in vaccinology allow for recent advances that provide only the nucleic acid building blocks of an antigen, eliminating many safety concerns. During the COVID-19 pandemic, these DNA and RNA vaccines have facilitated the development and deployment of vaccines at an unprecedented pace. This success was attributable at least in part to broader shifts …

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Responses To Sad Emotion In Autistic And Normal Developing Children: Is There A Difference?, Mohamed Basel Almourad, Emad Bataineh, Zelal Wattar Mar 2023

Responses To Sad Emotion In Autistic And Normal Developing Children: Is There A Difference?, Mohamed Basel Almourad, Emad Bataineh, Zelal Wattar

All Works

This paper describes how the gazing pattern differ between the responses of Normal Developing (ND) and Autistic (AP) children to sad emotion. We employed an eye tracking technology to collect and track the participants’ eye movements by showing a dynamic stimulus (video) that showed a gradual transition from pale emotions to melancholy facial expressions in both female and male faces. The location of the child's gaze in the stimulus was the focus of our data analysis. We deduced that there was a distinction between the two groups based on this. ND children predominantly concentrated on the eyes and mouth region …

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Blockscope: Detecting And Investigating Propagated Vulnerabilities In Forked Blockchain Projects, Xiao Yi, Yuzhou Fang, Daoyuan Wu, Lingxiao Jiang Mar 2023

Blockscope: Detecting And Investigating Propagated Vulnerabilities In Forked Blockchain Projects, Xiao Yi, Yuzhou Fang, Daoyuan Wu, Lingxiao Jiang

Research Collection School Of Computing and Information Systems

Due to the open-source nature of the blockchain ecosystem, it is common for new blockchains to fork or partially reuse the code of classic blockchains. For example, the popular Dogecoin, Litecoin, Binance BSC, and Polygon are all variants of Bitcoin/Ethereum. These “forked” blockchains thus could encounter similar vulnerabilities that are propagated from Bitcoin/Ethereum during forking or subsequently commit fetching. In this paper, we conduct a systematic study of detecting and investigating the propagated vulnerabilities in forked blockchain projects. To facilitate this study, we propose BlockScope, a novel tool that can effectively and efficiently detect multiple types of cloned vulnerabilities given …

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Wearables For In-Situ Monitoring Of Cognitive States: Challenges And Opportunities, Meera Radhakrishnan, Thivya Kandappu, Manoj Gulati, Archan Misra Mar 2023

Wearables For In-Situ Monitoring Of Cognitive States: Challenges And Opportunities, Meera Radhakrishnan, Thivya Kandappu, Manoj Gulati, Archan Misra

Research Collection School Of Computing and Information Systems

We propose using wrist and ear-based sensing, via multiple novel and complementary modalities, to unobtrusively infer activity-aware, complex cognitive and affective states (such as confusion, boredom, and recall failure) of individuals. While state-of-the-art wearable devices are predominantly used (a) independently, with limited coordination among multiple devices, and (b) to capture macro-level physical activity and physiological state, we seek to expand the ambit of unobtrusive wearable sensing to capture the cognitive states while performing commonplace physical activities. Such states typically manifest via fine-grained, almost unobservable, microscopic head, face, and eye movements. We identify some of these fine-grained physical markers that serve …

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Investigating Guardian Awareness Techniques To Promote Safety In Virtual Reality, Sixuan Wu, Jiannan Li, Maurício Sousa, Tovi Grossman Mar 2023

Investigating Guardian Awareness Techniques To Promote Safety In Virtual Reality, Sixuan Wu, Jiannan Li, Maurício Sousa, Tovi Grossman

Research Collection School Of Computing and Information Systems

Virtual Reality (VR) can completely immerse users in a virtual world and provide little awareness of bystanders in the surrounding physical environment. Current technologies use predefined guardian area visualizations to set safety boundaries for VR interactions. However, bystanders cannot perceive these boundaries and may collide with VR users if they accidentally enter guardian areas. In this paper, we investigate four awareness techniques on mobile phones and smartwatches to help bystanders avoid invading guardian areas. These techniques include augmented reality boundary overlays and visual, auditory, and haptic alerts indicating bystanders' distance from guardians. Our findings suggest that the proposed techniques effectively …

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An Exploratory Study On Museum Visitor Ship Trends In Singapore, Aldy Gunawan, Chentao Liu, Heranshan S/O Subramaniam, Melissa Tan, Ranice Tan, Clarence Tay, Tasaporn. Visawameteekul Mar 2023

An Exploratory Study On Museum Visitor Ship Trends In Singapore, Aldy Gunawan, Chentao Liu, Heranshan S/O Subramaniam, Melissa Tan, Ranice Tan, Clarence Tay, Tasaporn. Visawameteekul

Research Collection School Of Computing and Information Systems

The COVID-19 outbreak has unpredictably disrupted the operations of numerous museums. Museum visitor experience has a physical, personal, and social context, which are not achievable during the pandemic. Despite the depreciation during the Circuit Breaker period, the disruption also presents an opportunity for local museums to develop new strategies of audience engagement to accommodate the altered audience behavior. This exploratory study analyses data from six Singapore-based museums to understand the visitorship patterns across different ages and genders. The impact of COVID-19 is also analysed. Using R-studio and relevant packages, we conducted statistical tests such as hypothesis testing, Chi-square testing and …

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Dminer: Dashboard Design Mining And Recommendation, Yanna Lin, Haotian Li, Aoyu Wu, Yong Wang, Huamin Qu Mar 2023

Dminer: Dashboard Design Mining And Recommendation, Yanna Lin, Haotian Li, Aoyu Wu, Yong Wang, Huamin Qu

Research Collection School Of Computing and Information Systems

Dashboards, which comprise multiple views on a single display, help analyze and communicate multiple perspectives of data simultaneously. However, creating effective and elegant dashboards is challenging since it requires careful and logical arrangement and coordination of multiple visualizations. To solve the problem, we propose a data-driven approach for mining design rules from dashboards and automating dashboard organization. Specifically, we focus on two prominent aspects of the organization: arrangement , which describes the position, size, and layout of each view in the display space; and coordination , which indicates the interaction between pairwise views. We build a new dataset containing 854 …

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Effective Graph Kernels For Evolving Functional Brain Networks, Xinlei Wang, Jinyi Chen, Bing Tian Dai, Junchang Xin, Yu Gu, Ge Yu Mar 2023

Effective Graph Kernels For Evolving Functional Brain Networks, Xinlei Wang, Jinyi Chen, Bing Tian Dai, Junchang Xin, Yu Gu, Ge Yu

Research Collection School Of Computing and Information Systems

The graph kernel of the functional brain network is an effective method in the field of neuropsychiatric disease diagnosis like Alzheimer's Disease (AD). The traditional static brain networks cannot reflect dynamic changes of brain activities, but evolving brain networks, which are a series of brain networks over time, are able to seize such dynamic changes. As far as we know, the graph kernel method is effective for calculating the differences among networks. Therefore, it has a great potential to understand the dynamic changes of evolving brain networks, which are a series of chronological differences. However, if the conventional graph kernel …

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Detecting C++ Compiler Front-End Bugs Via Grammar Mutation And Differential Testing, Haoxin Tu, He Jiang, Zhide Zhou, Yixuan Tang, Zhilei Ren, Lei Qiao, Lingxiao Jiang Mar 2023

Detecting C++ Compiler Front-End Bugs Via Grammar Mutation And Differential Testing, Haoxin Tu, He Jiang, Zhide Zhou, Yixuan Tang, Zhilei Ren, Lei Qiao, Lingxiao Jiang

Research Collection School Of Computing and Information Systems

C++ is a widely used programming language and the C++ front-end is a critical part of a C++ compiler. Although many techniques have been proposed to test compilers, few studies are devoted to detecting bugs in C++ compiler. In this study, we take the first step to detect bugs in C++ compiler front-ends. To do so, two main challenges need to be addressed, namely, the acquisition of test programs that are more likely to trigger bugs in compiler front-ends and the bug identification from complicated compiler outputs. In this article, we propose a novel framework named Ccoft to detect bugs …

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Demystifying Performance Regressions In String Solvers, Yao Zhang, Xiaofei Xie, Yi Li, Yi Lin, Sen Chen, Yang Liu, Xiaohong Li Mar 2023

Demystifying Performance Regressions In String Solvers, Yao Zhang, Xiaofei Xie, Yi Li, Yi Lin, Sen Chen, Yang Liu, Xiaohong Li

Research Collection School Of Computing and Information Systems

Over the past few years, SMT string solvers have found their applications in an increasing number of domains, such as program analyses in mobile and Web applications, which require the ability to reason about string values. A series of research has been carried out to find quality issues of string solvers in terms of its correctness and performance. Yet, none of them has considered the performance regressions happening across multiple versions of a string solver. To fill this gap, in this paper, we focus on solver performance regressions (SPRs), i.e., unintended slowdowns introduced during the evolution of string solvers. To …

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Multi-Modal Api Recommendation, Ivana Clairine Irsan, Ting Zhang, Ferdian Thung, Kisub Kim, David Lo Mar 2023

Multi-Modal Api Recommendation, Ivana Clairine Irsan, Ting Zhang, Ferdian Thung, Kisub Kim, David Lo

Research Collection School Of Computing and Information Systems

Too many options can be a problem, which is the case for Application Programming Interfaces (APIs). As there are many such APIs, with many more being introduced periodically, it raises the problem of choosing which API to be recommended. Furthermore, numerous APIs are commonly used together with other complementary third-party APIs. It can be challenging for developers to understand how to use each API and to remember all the complementary APIs for the API they want to use. Therefore, an accurate API recommendation approach can improve developers' efficiency in implementing certain functionality. Several approaches have been developed to automatically recommend …

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User Acceptance And Adoption Of Smart Homes: A Decade Long Systematic Literature Review, Ibrahim Mashal, Ahmed Shuhaiber, Ayman Wael Al-Khatib Mar 2023

User Acceptance And Adoption Of Smart Homes: A Decade Long Systematic Literature Review, Ibrahim Mashal, Ahmed Shuhaiber, Ayman Wael Al-Khatib

All Works

This survey aims to provide a coherent and bibliometric overview of the theories and constructs employed in smart homes acceptance and adoption literature. To achieve the study aims, we con-ducted a systematic search for every article related to the SH concept, services and applications, user acceptance and adoption, and integrated IoT home appliances and devices, in 10 major library databases, namely, IEEE Digital Library, ACM Digital Library, Association for Information Systems (AIS), Elsevier, Emerald, Taylor and Francis, Wiley InterScience, Springer, Inderscience, and Hindawi. These databases contain literature focusing on smart home adoption using IoT tech-nology. 40 research articles of journal …

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Hearing Healthcare Professionals’ Views About Over-The-Counter (Otc) Hearing Aids: Analysis Of Retrospective Survey Data, Vinaya Manchaiah, Anu Sharma, Hansapani Rodrigo, Abram Bailey, Karina C. De Sousa, De Wet Swanepoel Mar 2023

Hearing Healthcare Professionals’ Views About Over-The-Counter (Otc) Hearing Aids: Analysis Of Retrospective Survey Data, Vinaya Manchaiah, Anu Sharma, Hansapani Rodrigo, Abram Bailey, Karina C. De Sousa, De Wet Swanepoel

School of Mathematical & Statistical Sciences Faculty Publications

Over-the-counter hearing aids have been available to consumers in the US since 17 October 2022 following a ruling by the Food and Drug Administration. However, their reception by hearing healthcare professionals (HHP) has been mixed, and concerns have been expressed by many HHPs. The aim of this study was to examine the concerns that HHPs have towards over-the-counter (OTC) hearing aids. The study used a retrospective survey design. The survey data of HHPs (n = 730) was obtained from Hearing Tracker. A 22-item structured questionnaire was administered using a Question Scout platform. Descriptive analyses examined reported areas of concern and …

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The Use Of Artificial Intelligence To Detect Students Sentiments And Emotions In Gross Anatomy Reflections, Krzysztof J. Rechowicz, Carrie A. Elzie Mar 2023

The Use Of Artificial Intelligence To Detect Students Sentiments And Emotions In Gross Anatomy Reflections, Krzysztof J. Rechowicz, Carrie A. Elzie

VMASC Publications

Students' reflective writings in gross anatomy provide a rich source of complex emotions experienced by learners. However, qualitative approaches to evaluating student writings are resource heavy and timely. To overcome this, natural language processing, a nascent field of artificial intelligence that uses computational techniques for the analysis and synthesis of text, was used to compare health professional students' reflections on the importance of various regions of the body to their own lives and those of the anatomical donor dissected. A total of 1365 anonymous writings (677 about a donor, 688 about self) were collected from 132 students. Binary and trinary …

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Machine Learning Techniques For Stock Price Prediction And Graphic Signal Recognition, Junde Chen, Yuxin Wen, Y. A. Nanehkaran, M. D. Suzauddola, Weirong Chen, Defu Zhang Mar 2023

Machine Learning Techniques For Stock Price Prediction And Graphic Signal Recognition, Junde Chen, Yuxin Wen, Y. A. Nanehkaran, M. D. Suzauddola, Weirong Chen, Defu Zhang

Engineering Faculty Articles and Research

Stock market analysis is extremely important for investors because knowing the future trend and grasping the changing characteristics of stock prices will decrease the risk of investing capital for profit. Thereupon, the prediction of stock prices and identifying the graphic signals of candlestick charts, which are two crucial tasks in stock price analysis, attract much attention from investors owing to the returns and risks that coexist in financial markets. To introduce a reliable approach for addressing these challenges, this paper proposes the modeling strategies based on machine learning (ML) techniques. A vector autoregression (VAR)-based rolling prediction model is proposed for …

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Mathematical Models For Thalassemia, Hamda Mohammed Al Dhaheri Mar 2023

Mathematical Models For Thalassemia, Hamda Mohammed Al Dhaheri

Theses

Thalassemia is a genetic blood disorder caused by gene mutation or deletion in a blood protein called hemoglobin. Treatment of thalassemia requires a life-long blood transfusion and removal of excessive iron in the blood stream, which usually causes a big pressure on health care systems. Various forms of thalassemia control measures have been used to reduce the prevalence of thalassemia major. This has resulted in a substantial reduction in the prevalence of thalassemia. However, the thalassemia carrier population remains high, which could lead to an increase in the thalassemia major population through carrier-to-carrier marriages. Thus, we developed two mathematical models …

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Design And Assessment Of A Leo Gnss Miniconstellation For Positioning, Navigation, And Timing (Pnt), Mariya Abdulkhaleq Mohamad Mar 2023

Design And Assessment Of A Leo Gnss Miniconstellation For Positioning, Navigation, And Timing (Pnt), Mariya Abdulkhaleq Mohamad

Theses

Recently, there has been a resurgent demand in the United Arab Emirates for more accurate positioning, navigation, and timing signals, especially for some targeted applications such as autonomous vehicles and flying taxis. The existing Global Navigation Satellite Systems (GNSS) provide real-time positioning accuracy for up to several meters, while the targeted applications require fast convergence of centimeterlevel positioning accuracy. Recent studies have shown that transmitting GNSS signals from a Low Earth Orbit (LEO) instead of a Medium Earth Orbit (MEO) would enhance positioning accuracy. The main objective of this thesis is to design and simulate an optimum scenario of a …

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Feasibility Study On The Characterization Of Mars Atmospheric And Surface Features In Spacecraft Images By Machine Learning And Similar Automated Methods, Hind Hassan Alriyami Mar 2023

Feasibility Study On The Characterization Of Mars Atmospheric And Surface Features In Spacecraft Images By Machine Learning And Similar Automated Methods, Hind Hassan Alriyami

Theses

This thesis is focused on automated detection of Mars atmospheric and surface features in spacecraft images based on machine learning and similar automated methods using crater detection algorithm (CDA) software, named DeepMars2 algorithm. The purpose of this study is to perform machine learning to detect coarse and high-resolution topography craters on mars. The algorithm is applied to two digital elevation models (DEMs) of the Mars surface with high and coarse resolution in order to identify craters using machine and deep learning methods. The DEMs are based on the satellite instruments MOLA/MGS (Mars Orbiter Laser Altimeter/Mars Global Surveyor) and HRSC/MEX (High …

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The Three-Dimensional Visualization Of Mars Dust Storms Based On Deriving Digital Elevation Maps From Satellite Imagery, Meirah Ali Alzeyoudi Mar 2023

The Three-Dimensional Visualization Of Mars Dust Storms Based On Deriving Digital Elevation Maps From Satellite Imagery, Meirah Ali Alzeyoudi

Theses

This work focuses on generating a Three-Dimensional Visualization of Mars's local dust storms utilizing satellite images from publicly available archives. The work aimed to create a Three-Dimensional Visualization of two Local Dust storms, the first local dust storm occurred on May 20, 2020, in the Chryse Planitia Region of Mars, while the second one occurred on 8 June 2021, on the northern side of the Utopia Planitia Region of Mars. The visualization will assist in providing a better understanding of the dynamics of Dust Storms on Mars by indicating and analyzing the main features of dust storms on Mars. Also, …

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Correlation Between The Preparation Methods And The Physiochemical Characteristics Of Mgal₂O₄ As A Support For Ni Catalysts In Partial Oxidation Of Methane, Fatima El Alem Mar 2023

Correlation Between The Preparation Methods And The Physiochemical Characteristics Of Mgal₂O₄ As A Support For Ni Catalysts In Partial Oxidation Of Methane, Fatima El Alem

Theses

Due to different technical challenges associated with direct use of methane, the main component of natural gas, its conversion to higher hydrocarbons has been a subject of great industrial importance. All of the known routes for methane conversion are catalytic processes, where the performance is largely dependent on the physicochemical properties of the catalyst. The catalysts that have shown promising performance in methane reforming are based on expensive metals such as Pt, Pd, and Ru. Ni, on the other hand, is a cost-effective metal and has shown promising catalytic activity. These catalysts are usually in the form of metal nanoparticles …

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Generating Synthetic Satellite Images Of Mars Dust Storms Based On Radiative Transfer Models, As A Follow-On Application Of Marswrf Dust Cycle Simulations, Fatima Ali Alkaabi Mar 2023

Generating Synthetic Satellite Images Of Mars Dust Storms Based On Radiative Transfer Models, As A Follow-On Application Of Marswrf Dust Cycle Simulations, Fatima Ali Alkaabi

Theses

Dust is a fundamental component of the Martian atmosphere; it plays a vital role in the planet's climate system and atmospheric variability. For these reasons, it is considered one of the essential keys to understanding the Martian atmosphere's behavior. The dust events on Mars range from local/regional dust storms that occur every Martian year to global dust storms that have only been observed, on average, once every 3-4 Martian years. The large regional and global dust storms have strong thermal and dynamic effects on the atmosphere. MarsWRF is a Mars version of the terrestrial numerical weather and climate model WRF …

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Specification-Based Autonomous Driving System Testing, Yuan Zhou, Yang Sun, Yun Tang, Yuqi Chen, Jun Sun, Christopher M. Poskitt, Yang Liu, Zijiang Yang Mar 2023

Specification-Based Autonomous Driving System Testing, Yuan Zhou, Yang Sun, Yun Tang, Yuqi Chen, Jun Sun, Christopher M. Poskitt, Yang Liu, Zijiang Yang

Research Collection School Of Computing and Information Systems

Autonomous vehicle (AV) systems must be comprehensively tested and evaluated before they can be deployed. High-fidelity simulators such as CARLA or LGSVL allow this to be done safely in very realistic and highly customizable environments. Existing testing approaches, however, fail to test simulated AVs systematically, as they focus on specific scenarios and oracles (e.g., lane following scenario with the "no collision" requirement) and lack any coverage criteria measures. In this paper, we propose AVUnit, a framework for systematically testing AV systems against customizable correctness specifications. Designed modularly to support different simulators, AVUnit consists of two new languages for specifying dynamic …

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Concept-Oriented Transformers For Visual Sentiment Analysis, Quoc Tuan Truong, Hady Wirawan Lauw Mar 2023

Concept-Oriented Transformers For Visual Sentiment Analysis, Quoc Tuan Truong, Hady Wirawan Lauw

Research Collection School Of Computing and Information Systems

In the richly multimedia Web, detecting sentiment signals expressed in images would support multiple applications, e.g., measuring customer satisfaction from online reviews, analyzing trends and opinions from social media. Given an image, visual sentiment analysis aims at recognizing positive or negative sentiment, and occasionally neutral sentiment as well. A nascent yet promising direction is Transformer-based models applied to image data, whereby Vision Transformer (ViT) establishes remarkable performance on largescale vision benchmarks. In addition to investigating the fitness of ViT for visual sentiment analysis, we further incorporate concept orientation into the self-attention mechanism, which is the core component of Transformer. The …

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Generalizing Graph Neural Network Across Graphs And Time, Zhihao Wen Mar 2023

Generalizing Graph Neural Network Across Graphs And Time, Zhihao Wen

Research Collection School Of Computing and Information Systems

Graph-structured data widely exist in diverse real-world scenarios, analysis of these graphs can uncover valuable insights about their respective application domains. However, most previous works focused on learning node representation from a single fixed graph, while many real-world scenarios require representations to be quickly generated for unseen nodes, new edges, or entirely new graphs. This inductive ability is essential for high-throughtput machine learning systems. However, this inductive graph representation problem is quite difficult, compared to the transductive setting, for that generalizing to unseen nodes requires new subgraphs containing the new nodes to be aligned to the neural network trained already. …

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Proactive Conversational Agents, Lizi Liao, Grace Hui Yang, Chirag Shah Mar 2023

Proactive Conversational Agents, Lizi Liao, Grace Hui Yang, Chirag Shah

Research Collection School Of Computing and Information Systems

Conversational agents, or commonly known as dialogue systems, have gained escalating popularity in recent years. Their widespread applications support conversational interactions with users and accomplishing various tasks as personal assistants. However, one key weakness in existing conversational agents is that they only learn to passively answer user queries via training on pre-collected and manually-labeled data. Such passiveness makes the interaction modeling and system-building process relatively easier, but it largely hinders the possibility of being human-like hence lowering the user engagement level. In this tutorial, we introduce and discuss methods to equip conversational agents with the ability to interact with end …

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Green Data Analytics Of Supercomputing From Massive Sensor Networks: Does Workload Distribution Matter?, Zhiling Guo, Jin Li, Ram Ramesh Mar 2023

Green Data Analytics Of Supercomputing From Massive Sensor Networks: Does Workload Distribution Matter?, Zhiling Guo, Jin Li, Ram Ramesh

Research Collection School Of Computing and Information Systems

Energy costs represent a significant share of the total cost of ownership in high performance computing (HPC) systems. Using a unique data set collected by massive sensor networks in a peta scale national supercomputing center, we first present an explanatory model to identify key factors that affect energy consumption in supercomputing. Our analytic results show that, not only does computing node utilization significantly affect energy consumption, workload distribution among the nodes also has significant effects and could effectively be leveraged to improve energy efficiency. Next, we establish the high model performance using in-sample and out-of-sample analyses. We then develop prescriptive …

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Volere: Leakage Resilient User Authentication Based On Personal Voice Challenges, Rui Zhang, Zheng Yan, Xuerui Wang, Robert H. Deng Mar 2023

Volere: Leakage Resilient User Authentication Based On Personal Voice Challenges, Rui Zhang, Zheng Yan, Xuerui Wang, Robert H. Deng

Research Collection School Of Computing and Information Systems

Voiceprint Authentication as a Service (VAaS) offers great convenience due to ubiquity, generality, and usability. Despite its attractiveness, it suffers from user voiceprint leakage over the air or at the cloud, which intrudes user voice privacy and retards its wide adoption. The literature still lacks an effective solution on this issue. Traditional methods based on cryptography are too complex to be practically deployed while other approaches distort user voiceprints, which hinders accurate user identification. In this article, we propose a leakage resilient user authentication cloud service with privacy preservation based on random personal voice challenges, named VOLERE (VOice LEakage REsilient). …

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Investment And Risk Management With Online News And Heterogeneous Networks, Meng Kiat Gary Ang, Ee-Peng Lim Mar 2023

Investment And Risk Management With Online News And Heterogeneous Networks, Meng Kiat Gary Ang, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

Stock price movements in financial markets are influenced by large volumes of news from diverse sources on the web, e.g., online news outlets, blogs, social media. Extracting useful information from online news for financial tasks, e.g., forecasting stock returns or risks, is, however, challenging due to the low signal-to-noise ratios of such online information. Assessing the relevance of each news article to the price movements of individual stocks is also difficult, even for human experts. In this article, we propose the Guided Global-Local Attention-based Multimodal Heterogeneous Network (GLAM) model, which comprises novel attention-based mechanisms for multimodal sequential and graph encoding, …

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Investigating Noticeable Hand Redirection In Virtual Reality Using Physiological And Interaction Data, Martin Feick, Kora Regitz, Anthony Tang, Jungbluth Mar 2023

Investigating Noticeable Hand Redirection In Virtual Reality Using Physiological And Interaction Data, Martin Feick, Kora Regitz, Anthony Tang, Jungbluth

Research Collection School Of Computing and Information Systems

Hand redirection is effective so long as the introduced offsets are not noticeably disruptive to users. In this work we investigate the use of physiological and interaction data to detect movement discrepancies between a user's real and virtual hand, pushing towards a novel approach to identify discrepancies which are too large and therefore can be noticed. We ran a study with 22 participants, collecting EEG, ECG, EDA, RSP, and interaction data. Our results suggest that EEG and interaction data can be reliably used to detect visuo-motor discrepancies, whereas ECG and RSP seem to suffer from inconsistencies. Our findings also show …

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Towards A Design Space For Storytelling On The Fashion Technology Runway, Sydney Pratte, Anthony Tang, Shannon Hoover, Maria Elena Hoover, Matt Laprarie, Catherine Larose, Lora Oehlberg Mar 2023

Towards A Design Space For Storytelling On The Fashion Technology Runway, Sydney Pratte, Anthony Tang, Shannon Hoover, Maria Elena Hoover, Matt Laprarie, Catherine Larose, Lora Oehlberg

Research Collection School Of Computing and Information Systems

Fashion is driven by a narrative, i.e. a story or idea that the designer wants to convey to the audience. Fashion-tech now adds another dimension to this narrative through dynamically changing aspects of the garments. Many factors of presentation in a runway show affect how fashion-tech garments communicate a story to the audience. In this pictorial, we review a set of twenty-eight storytelling fashion-tech garments. We identify, catalogue, and categorize the factors designers used to convey stories to the audience from the runway. The design space consists of three levels: (1) the artifact-level, (2) the viewer-level, and (3) the context-level. …

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