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Assessing Visual Attention in Gaze-Based VR Learning Through Eye-Tracking Measures
No full textVirtual and Augmented Reality (VR/AR) are becoming increasingly ubiquitous, with consumer-grade VR head-mounted displays (HMDs) making immersive experiences more accessible for everyday use. VR serves as an effective tool for learning and training by providing immersion, a sense of presence, and the ability to simulate risk-free environments that would otherwise be inaccessible or hazardous in real life. Gaze-based interaction in VR enhances user engagement by detecting and responding to their visual attention within the virtual environment. A key aspect of such interaction is gaze-driven content rendering, which dynamically presents virtual objects or information within the user’s field of view (FOV) based on their gaze direction. In VR learning and training environments, gaze-driven content rendering can improve the learning experience by adapting to the user’s attention, minimizing distractions, and ensuring learners remain engaged with specific visual elements by displaying content precisely where they are looking.
Understanding users\u27 focus and visual scanning behavior can help optimize their engagement in immersive environments. Eye-tracking is a widely used, non-invasive technique for measuring human visual attention, offering valuable insights into how individuals process visual information. In gaze-based VR learning environments, eye-tracking measures can help analyze how learners interact with the virtual environment, focus on content, and engage with learning materials. In this study, we present a framework for assessing visual attention in a gaze-based VR learning environment using eye-tracking measures. Our framework computes basic and advanced gaze metrics, including fixation duration, saccade amplitude, and the ambient/focal attention coefficient K, as indicators of visual attention in VR. To facilitate analysis, the generated gaze data are visualized in an advanced gaze analytics dashboard, allowing us to examine users\u27 gaze behaviors and attention patterns during interactive VR learning tasks.
We conducted a pilot user study to evaluate the utility of the proposed framework. We designed a VR learning application with a gaze-driven content rendering feature to facilitate gaze-based interaction. The VR learning environment was developed using a consumer-grade Meta Quest Pro VR headset, with eye-tracking data captured through its built-in eye tracker. The proposed framework was applied to generate gaze measures for analyzing users\u27 visual attention during the gaze-based VR learning task. This study contributes by introducing a novel approach to integrating advanced eye-tracking technology into VR learning environments, specifically leveraging consumer-grade HMDs
Splitting Hairs: Biomechanics of Gray Whale (Eschrichtius robustus) Baleen
No full textRorqual whales (Mysticetes, Cetacea) use baleen, a filtration structure attached to the upper jaw, to retain prey from water during filter feeding. Baleen is the general term used for the keratin filter of all mysticetes, and refers to the complete structure of the Zwischensubstanz, connective papillae, major baleen plates, minor baleen plates, and baleen fringes. Rorquals lunge filter-feed, engulfing enormous masses of both prey and water. Gray whales (Eschrichtius robustus) use a unique method of suction filter-feeding, in addition to lunge filter-feeding. Gray whales scrape their heads and baleen against the substrate, fluidizing mud and sand to suck in their prey. Gray whale baleen must endure repeated collisions with rough substrate, while withstanding the forces of gallons of prey and water. To better understand the deformation of gray whale baleen, we recorded morphological measurements and performed three-point bend tests to record max load values on baleen plates from 18 gray whales in four demographics categories: male adults, female adults, male subadults, and female subadults. We found significant morphometric differences (p \u3c 0.001) in plate length, plate width, plate fringe diameter, plate lingual thickness, major spacing and minor spacing between the groups. The strongest factor in separating the baleen from one group to another was flexural stiffness (EI), which was consistently higher in male adults than in other demographic groups. Differences in the morphological and material of baleen properties point to variance in behavior and function throughout a gray whale’s lifespan. Future investigation into how the location of a baleen plate in the mouth (anterior/posterior, right/left) relates to its material function may demonstrate behavioral and functional differences in a single individual
Detecting Anomalous SRF Cavity Behavior with Unsupervised Learning
Get PDFWe present an unsupervised learning framework for detecting anomalous superconducting radio-frequency (SRF) cavity behavior at the Continuous Electron Beam Accelerator Facility (CEBAF), emphasizing its initial performance and effectiveness. Key to the system’s success was the development of data acquisition systems (DAQs) that capture fast-sampled, information-rich signals, essential for detecting transient effects. The approach involves creating daily cavity-specific models using principal component analysis to handle variations in rf signal behavior and mitigate performance degradation from data drift. This unsupervised method eliminates the need for expensive labeling by continuously updating models with recent data. Deployed and operational for 3 months before a scheduled shutdown, the system successfully identified several issues with DAQ signals, confirming its effectiveness. Despite access to only a fraction of CEBAF’s SRF cavity signals, the framework efficiently detected several instances requiring intervention, demonstrating a significant improvement over traditional, labor-intensive methods of manual plot inspection
Analysing Nontraditional Students\u27 ChatGPT Interaction, Engagement, Self-Efficacy and Performance: A Mixed-Methods Approach
Get PDFGenerative artificial intelligence brings opportunities and unique challenges to nontraditional higher education students, stemming, in part, from the experience of the digital divide. Providing access and practice is critical to bridge this divide and equip students with needed digital competencies. This mixed-methods study investigated how nontraditional higher education students interact with ChatGPT in multiple courses and examined relationships between ChatGPT interactions, engagement, self-efficacy and performance. Data were collected from 73 undergraduate and graduate students through chat logs, course reflections and artefacts, surveys and interviews. ChatGPT interactions were analysed using four metrics: prompt number, depth of knowledge (DoK), prompt relevance and originality. Results showed that ChatGPT prompt numbers (β = 0.256, p \u3c 0.03) and engagement (β = 0.267, p \u3c 0.05) significantly predicted performance, while self-efficacy did not. Students\u27 DoK (r = 0.40, p \u3c 0.01) and prompt relevance (r = 0.42, p \u3c 0.01) were positively correlated with performance. Text mining analysis identified distinct interaction patterns, with ‘strategic inquirers’ demonstrating significantly higher performance than ‘exploratory inquirers’ through more sophisticated follow-up questioning. Qualitative findings revealed that while most students were first-time ChatGPT users who initially showed resistance, they developed growing acceptance. Still, students tended to use ChatGPT sparingly and, even then, as only a starting point for assignments. The study highlights the need for targeted guidance in prompt engineering and AI literacy training to help nontraditional higher education students leverage ChatGPT more effectively for higher-order thinking tasks
The Effect of Inelastic Compression Wraps on the Quality of Life of People with Chronic Venous Insufficiency: A Single-Center, Single-Arm Prospective Study
Get PDFBackground/Objectives: First line therapy for all manifestations of chronic venous insufficiency (CVI) is compression. However, patients frequently report dissatisfaction with compression stockings. Therefore, there is a need to find alternative therapeutic options that can promote compliance. Here, we investigate the impact of the novel, inelastic compression wrap device on quality of life (QoL) in patients with CVI who have failed therapy with compression stockings in the past. Methods: We conducted a six-week, open-label, single-center, non-blinded, prospective cohort study. The primary endpoint was the change in QoL over 6 weeks as measured by the Chronic Venous Disease Quality of Life Questionnaire (CIVIQ-20). Results: Thirty patients completed the study. Twenty-five (83.3%) reported wearing the compression device most of the time. At the six-week follow-up, CIVIQ-20 scores improved on average 12.123 ± 21.06 points on a 100-point scale (p = 0.0019). Calf circumference decreased on average 1.3 cm ± 2.21 cm (p = 0.0009). Measured on a ten-point scale, average itch decreased 1.9 ± 2.63 points (p = 0.0008) and reported levels of the worst itch decreased on average 2.73 ± 3.63 points (p = 0.0001). The Venous Clinical Severity Scoring scores decreased on average by 1.276 ± 2.297 points (p = 0.0029). Conclusions: Compression stockings remain the mainstay of treatment for advanced cutaneous manifestations of CVI. However, we demonstrated that the novel inelastic compression device offers an alternative and may improve QoL, compliance, and clinical venous symptoms in a safe manner in people who could not tolerate compression stockings
FIDS: Accelerating Network Intrusion Detection Through Strategic Feature Selection
Get PDFNetwork intrusion detection systems (IDS) typically analyze complete network flows to identify malicious traffic, requiring flows to conclude before classification. This approach creates detection delays for attacks like Slowloris that intentionally keep connections open for extended periods of time. This paper introduces a novel approach that classifies network traffic using only features available from the first few packets of a flow, enabling faster detection while maintaining high accuracy. We evaluate three random forest models on the CICIDS2017 dataset using expanding sets of features: the first-packet model trained on on features available from the first backward packet, the few-packet model which includes features estimable from the first few packets of a flow, and a full-flow model using all features in the dataset for reference. Our few-packet model achieves 99.64% accuracy, 99.80% precision, and 99.64% recall-comparable to state-of-the-art approaches using full-flow information-while enabling significantly faster detection. This approach is particularly effective against slow-rate DoS attacks, achieving over 99% F1 scores for both Slowloris and Slowhttptest traffic. At a low false positive rate of 0.01%, our model maintains a 99.17% true positive rate. These results demonstrate that carefully selected early-flow features can provide effective intrusion detection without sacrificing accuracy
The Evolution of Russian and Chinese Disinformation Tactics and the Threat They Pose to the U.S. Cybersecurity
Get PDFThis paper aims to discuss how disinformation has become the most powerful tool used against the United State by foreign operatives. Of these foreign operatives, Russia and China have shown the ability to use advanced tactics to truly affect the United States security. Often these tools came in the form of state-sponsored media, influence campaigns and fake online identities. This literature review explores the evolution of Russian and Chinese disinformation tactics, examining how these approaches have changed over time and become more sophisticated. This paper will highlight major campaigns which use tools such as bot networks, and social media manipulation. The findings display the complex threat these sorts of tactics pose to the United States cyber and national security. By tracing their evolution we were able to stress the importance of stronger cybersecurity measures to defend against ongoing operations
Keynote Presentation: Quo Vadis Cardiovascular Research
No full textKeynote presentation by Dr. Raymond Benza
Panels
No full textPanel Sessions: Women\u27s Cardiovascular Health: Challenges and Breakthroughs (12:50-1:30pm) Disparities in Cardiovascular Research: Identifying Gaps and Solutions (1:35-2:15pm) Emerging Technologies in Heart Health: From Bench to Bedside (2:20-3pm
Evidence for Distal Bolide Impact and Tsunami Deposits in the Upper Atlantic Coastal Plain of Moore County (North Carolina, USA) generated by the Eocene Chesapeake Bay Bolide Impact
Get PDFBeds interpreted as Eocene bolide-generated impact and tsunami deposits occur at Paint Hill in the Upper Atlantic Coastal Plain of Moore County, North Carolina, USA. These strata, herein named the Mount Helicon Formation, consist of four distinct beds comprising about one meter of total section. Bed 1 (the basal bed) is approximately 43 cm thick and consists of sandy carbonaceous clay with carbon glass and rock fragments and contains 14-18 parts per billion (ppb) iridium (interpreted as bolide impact ejecta). Bed 2 is approximately 9 cm thick and consists of non-cohesive silt-size particles and loosely bound sand-size accretionary lapilli-like masses composed of quartz and carbon glass particles imbedded in a gray-green, flakey clay matrix and contains 2-6 ppb iridium (interpreted as atmospheric fallout deposits). Bed 3, is a sandy-matrix breccia approximately 6 cm thick (although thickness is greater in some places because of large clasts). This bed has terrestrially-derived clasts such as paleosol rip-ups (gravel to boulder-size) and petrified wood logs, along with marine-derived clasts, such as fossiliferous chert fragments and (up to) meter-size clasts of rolled strata contains 1-2 ppb iridium (interpreted as tsunami-surge deposits). Bed 4 is approximately 15 cm thick and consists of medium to coarse quartz sand with occasional pea size quartz gravel (interpreted as a possible later tsunami deposit). The beds of the Mount Helicon Formation fill a channel cut into the upper part of newly described upper middle Eocene (Bartonian) siliciclastic strata, herein named the Paint Hill Formation. The Paint Hill Formation consists of approximately 11 m of clay, sandstone (some glauconitic), and conglomerate (interpreted as nearshore marine strata) that are divided into five intervals of fining-upward or coarsening-upward sediments comprising 2.5 high-resolution transgressive regressive cycles. The age of the Paint Hill Formation as determined from fossil shark teeth, specifically Pseudabdounia claibornensis, is Bartonian, 41.2-37.7 Ma, late middle Eocene. The uppermost unit in the Paint Hill Member has weathered to plinthic paleosol, indicating that the land area hosting these marine strata became subaerially emergent , probably during the late Eocene. This emergent land provided a source for rip-up paleosol clasts found in Bed 3 of the Mount Helicon Formation. This discovery indicates that a catastrophic event (most likely the ~35 Ma Chesapeake Bay Impact that occurred about 380 km to the northeast of Paint Hill) generated bolide impact and tsunami deposits in a shallow marine and adjacent terrestrial setting in the southwestern part of the North Carolina Coastal Plain