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- Eye-tracking (2)
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- Ab initio protein structure predictions (1)
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- TrRosetta (1)
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- VANET (1)
- Vehicular networks (1)
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- Web robot detection (1)
Articles 1 - 11 of 11
Full-Text Articles in Physical Sciences and Mathematics
Unmasking Deception In Vanets: A Decentralized Approach To Verifying Truth In Motion, Susan Zehra, Syed R. Rizvi, Steven Olariu
Unmasking Deception In Vanets: A Decentralized Approach To Verifying Truth In Motion, Susan Zehra, Syed R. Rizvi, Steven Olariu
College of Sciences Posters
VANET, which stands for "Vehicular Ad Hoc Network," is a wireless network that allows vehicles to communicate with each other and with infrastructure, such as Roadside Units (RSUs), with the aim of enhancing road safety and improving the overall driving experience through real-time exchange of information and data. VANET has various applications, including traffic management, road safety alerts, and navigation. However, the security of VANET can be compromised if a malicious user alters the content of messages transmitted, which can harm both individual vehicles and the overall trust in VANET technology. Ensuring the correctness of messages is crucial for the …
Robots Still Outnumber Humans In Web Archives In 2019, But Less Than In 2012, Himarsha R. Jayanetti, Kritika Garg, Sawood Alam, Michael L. Nelson, Michele C. Weigle
Robots Still Outnumber Humans In Web Archives In 2019, But Less Than In 2012, Himarsha R. Jayanetti, Kritika Garg, Sawood Alam, Michael L. Nelson, Michele C. Weigle
College of Sciences Posters
To identify robots and human users in web archives, we conducted a study using the access logs from the Internet Archive’s (IA) Wayback Machine in 2012 (IA2012), 2015 (IA2015), and 2019 (IA2019), and the Portuguese Web Archive (PT) in 2019 (PT2019). We identified user sessions in the access logs and classified them as human or robot based on their browsing behavior. In 2013, AlNoamany et al. [1] studied the user access patterns using IA access logs from 2012. They established four web archive user access patterns: single-page access (Dip), access to the same page at multiple archive times (Dive), access …
Adhd Prediction Through Analysis Of Eye Movements With Graph Convolution Network, Gavindya Jayawardena, Sampath Jayarathna, Yi He
Adhd Prediction Through Analysis Of Eye Movements With Graph Convolution Network, Gavindya Jayawardena, Sampath Jayarathna, Yi He
College of Sciences Posters
Processing speech with background noise requires appropriate parsing of the distorted auditory signal, fundamental language abilities as well as higher signal-to-noise ratio. Adolescents with ADHD have difficulty processing speech with background noise due to reduced inhibitory control and working memory capacity. In this study we utilize Audiovisual Speech-In-Noise performance and eye-tracking measures of young adults with ADHD compared to age-matched controls, and generate graphs for ADHD evaluation using the eye-tracking data. We form graphs utilizing the eight eye-tracking features (fixation count, average, total, and standard deviation of fixation duration, max and min saccade peak velocity, min, average, and standard deviation …
Evaluation Of Scalable Quantum And Classical Machine Learning For Particle Tracking Classification In Nuclear Physics, Polykarpos Thomadakis, Emmanuel Billias, Nikos Chrisochoides
Evaluation Of Scalable Quantum And Classical Machine Learning For Particle Tracking Classification In Nuclear Physics, Polykarpos Thomadakis, Emmanuel Billias, Nikos Chrisochoides
The Graduate School Posters
Future particle accelerators will exceed by far the current data size (1015) per experiment, and high- luminosity program(s) will produce more than 300 times as much data. Classical Machine Learning (ML) likely will benefit from new tools based on quantum computing. Particle track reconstruction is the most computationally intensive process in nuclear physics experiments. A combinatorial approach exhaustively tests track measurements (“hits”), represented as images, to identify those that form an actual particle trajectory, which is then used to reconstruct track parameters necessary for the physics experiment. Quantum Machine Learning (QML) could improve this process in multiple ways, …
Ml-Based Surrogates And Emulators, Tareq Alghamdi, Yaohang Li, Nobuo Sato
Ml-Based Surrogates And Emulators, Tareq Alghamdi, Yaohang Li, Nobuo Sato
College of Sciences Posters
No abstract provided.
A Novel Parking Management In Smart City Vehicular Datacenters, Syed Rizvi, Susan Zehra, Steven Olariu
A Novel Parking Management In Smart City Vehicular Datacenters, Syed Rizvi, Susan Zehra, Steven Olariu
College of Sciences Posters
Researchers have shown that most vehicles spend the majority of their time parked in parking garages, lots, or driveways. During this time, their computing resources are unused and untapped. This has led to substantial interest in Vehicular Cloud, an area of research in which each vehicle acts as a computation node. The main difference between traditional cloud computing and vehicular cloud computing is the availability of nodes. In traditional clouds, nodes are available 24/7, while in vehicular clouds, nodes (vehicles) are only available while parked in parking lots. This creates a dynamic environment as vehicles enter and exit parking garages …
Analysis Of Ab Initio Protein Structure Prediction Methods, Maytha Alshammari, Jing He
Analysis Of Ab Initio Protein Structure Prediction Methods, Maytha Alshammari, Jing He
College of Sciences Posters
Protein structure prediction produces atomic models of three-dimensional structure of a protein from its amino acid sequence. Understanding the function mechanism of proteins requires knowledge of three-dimensional structures. When developing new enzymes and drugs, it's essential to understand the structure of the target protein. In this study, we analyze models predicted using two ab initio protein structure prediction methods, trRosetta and Quark. A set of thirty protein chains was used to evaluate the effectiveness of the methods. The thirty chains were collected from Protein Data Bank (June – November, 2020). The length and the relative position of the predicted secondary …
Scalable Quantum Edge Detection Method For D-Nisq Imaging Simulations: Use Cases From Nuclear Physics And Medical Image Computing, Emmanuel Billias, Nikos Chrisochoides
Scalable Quantum Edge Detection Method For D-Nisq Imaging Simulations: Use Cases From Nuclear Physics And Medical Image Computing, Emmanuel Billias, Nikos Chrisochoides
The Graduate School Posters
Edge Detection is one of the computationally intensive modules in image analysis. It is used to find important landmarks by identifying a significant change (or “edge”) between pixels and voxels. We present a hybrid Quantum Edge Detection method by improving three aspects of an existing widely referenced implementation, which for our use cases generates incomprehensible results for the type and size of images we are required to process. Our contributions are in the pre- and post-processing (i.e., classical phase) and a quantum edge detection circuit: (1) we use space- filling curves to eliminate image artifacts introduced by the image decomposition, …
Exploring Human Perception While Reading Fake And Real News Articles, Yasasi Abeysinghe, Gavindya Jayawardana, Autumn Woodson, Efe Bozkir, Enkelejda Kasneci, Andrew Duchowski, Sampath Jayarathna
Exploring Human Perception While Reading Fake And Real News Articles, Yasasi Abeysinghe, Gavindya Jayawardana, Autumn Woodson, Efe Bozkir, Enkelejda Kasneci, Andrew Duchowski, Sampath Jayarathna
College of Sciences Posters
With the increased spread of misinformation on online platforms and the popularity of AI-generated text, there is a critical need to detect human perception regarding the truthfulness of news. Users’ believability in a news item influences the reading and sharing of that news. Hence, in order to reduce the spread of fake news online, it is important to understand how users' engagement with fake and real news and users' perceived believability impact their behavioral and physiological factors. In this work, we study human eye movements based on the truthfulness of news and their perceived believability. Using the publicly available FakeNewsPerception …
Metaenhance: Metadata Quality Improvement For Electronic Theses And Dissertations, Muntabir H. Choudhury, Lamia Salsabil, Himarsha R. Jayanetti, Jian Wu
Metaenhance: Metadata Quality Improvement For Electronic Theses And Dissertations, Muntabir H. Choudhury, Lamia Salsabil, Himarsha R. Jayanetti, Jian Wu
College of Sciences Posters
Metadata quality is crucial for digital objects to be discovered through digital library interfaces. Although DL systems have adopted Dublin Core to standardize metadata formats (e.g., ETD-MS v1.11), the metadata of digital objects may contain incomplete, inconsistent, and incorrect values [1]. Most existing frameworks to improve metadata quality rely on crowdsourced correction approaches, e.g., [2]. Such methods are usually slow and biased toward documents that are more discoverable by users. Artificial intelligence (AI) based methods can be adopted to overcome this limit by automatically detecting, correcting, and canonicalizing the metadata, featuring quick and unbiased responses to document metadata. …
X-Disetrac: Distributed Eye-Tracking With Extended Realities, Bhanuka Mahanama, Sampath Jayarathna
X-Disetrac: Distributed Eye-Tracking With Extended Realities, Bhanuka Mahanama, Sampath Jayarathna
College of Sciences Posters
Humans use heterogeneous collaboration mediums such as in-person, online, and extended realities for day-to-day activities. Identifying patterns in viewpoints and pupillary responses (a.k.a eye-tracking data) provide informative cues on individual and collective behavior during collaborative tasks. Despite the increasing ubiquity of these different mediums, the aggregation and analysis of eye-tracking data in heterogeneous collaborative environments remain unexplored. Our study proposes X-DisETrac: Extended Distributed Eye Tracking, a versatile framework for eye tracking in heterogeneous environments. Our approach tackles the complexity by establishing a platform-agnostic communication protocol encompassing three data streams to simplify data aggregation and …