Open Access. Powered by Scholars. Published by Universities.®
![Digital Commons Network](http://assets.bepress.com/20200205/img/dcn/DCsunburst.png)
Physical Sciences and Mathematics Commons™
Open Access. Powered by Scholars. Published by Universities.®
- Institution
-
- Wright State University (158)
- Old Dominion University (54)
- GALILEO, University System of Georgia (31)
- Technological University Dublin (29)
- University of Alabama in Huntsville (23)
-
- University of South Carolina (16)
- University of Richmond (14)
- Portland State University (13)
- Chapman University (10)
- University of the Pacific (9)
- Rowan University (6)
- San Jose State University (6)
- Minnesota State University Moorhead (5)
- Franklin University (4)
- Gettysburg College (4)
- University of Central Florida (4)
- University of Nebraska at Omaha (4)
- University of Nevada, Las Vegas (4)
- Virginia Commonwealth University (4)
- Winona State University (4)
- University of Minnesota Morris Digital Well (3)
- Michigan Technological University (2)
- Minnesota State University, Mankato (2)
- Touro College and University System (2)
- University of Nebraska - Lincoln (2)
- University of South Alabama (2)
- Ateneo de Manila University (1)
- Augsburg University (1)
- Biola University (1)
- College of the Holy Cross (1)
- Keyword
-
- Computer Science (162)
- Engineering (161)
- College of Engineering and Computer Science (157)
- Newsletters (157)
- Science news (157)
-
- Technical writing (157)
- Data representation (15)
- Robert Hooke (15)
- Scientific imaging (15)
- Technology (11)
- Web archives (11)
- Computer science (10)
- Digital preservation (9)
- Cybersecurity (8)
- Grants collection (7)
- Information technology (7)
- Machine learning (6)
- System theory (6)
- Computers (5)
- Disinformation (5)
- Faculty (5)
- Newsletter (5)
- Alumni (4)
- Bioengineering (4)
- Civil engineering (4)
- Computer engineering (4)
- Electrical engineering (4)
- Engineering management (4)
- Engineering physics (4)
- Management (4)
- Publication Year
- Publication
-
- BITs and PCs Newsletter (157)
- Computer Science and Information Technology Grants Collections (30)
- Academic Posters Collection (29)
- College of Sciences Posters (21)
- Computer Science Presentations (17)
-
- Bookshelf (14)
- Systems Science Friday Noon Seminar Series (13)
- Summer Community of Scholars Posters (RCEU and HCR Combined Programs) (12)
- Mathematics, Physics, and Computer Science Faculty Books and Book Chapters (10)
- Open Educational Resources (10)
- Computer & Information Science: Research Experiences for Undergraduates in Disinformation Detection and Analytics (8)
- Section 5: Imaging at the Nano Scale (8)
- The Rock (7)
- Von Braun Symposium Student Posters (7)
- Handouts (6)
- Graduate Bulletins (Catalogs) (5)
- Libraries' Newsletters (4)
- Research Horizons Day Posters (4)
- Undergraduate Research Celebration 2018 (4)
- Faculty Books and Monographs (3)
- The Graduate School Posters (3)
- UNLV Best Teaching Practices Expo (3)
- Cybersecurity: Deep Learning Driven Cybersecurity Research in a Multidisciplinary Environment (2)
- Learning Showcase 2014 (2)
- Pacific Open Texts (2)
- Poster Presentations (2)
- Summer REU Program (2)
- TechTalks (2)
- Textbook Alternatives Project Posters 2014 (2)
- Undergraduate Research Posters (2)
Articles 31 - 60 of 438
Full-Text Articles in Physical Sciences and Mathematics
Detecting Road Intersections From Satellite Images Using Convolutinal Neural Networks, Fatmaelzahraa Eltaher, Luis Miralles-Pechuán, Jane Courtney, Susan Mckeever
Detecting Road Intersections From Satellite Images Using Convolutinal Neural Networks, Fatmaelzahraa Eltaher, Luis Miralles-Pechuán, Jane Courtney, Susan Mckeever
Academic Posters Collection
The location of intersections is an important consideration for vulnerable road users such as People with Blindness or Visually Impairment (PBVI) or children. Route planning applications, however, do not give information about the location of intersections as this information is not available at scale. In this paper, we propose a deep learning framework to automatically detect the location of intersections from satellite images using convolutional neural networks. For this purpose, we labelled 7,342 Google maps images from Washington, DC, USA to create a dataset. This dataset covers a region of 58.98 km$^{2}$ and has 7,548 intersections. We then applied a …
Application Of The Two-Variable Model To Simulate A Multisensory Reaction-Time Task, Rebecca Brady, John Butler
Application Of The Two-Variable Model To Simulate A Multisensory Reaction-Time Task, Rebecca Brady, John Butler
Academic Posters Collection
To navigate the world in an efficient manner, the brain seamlessly integrates signals received across multiple sensory modalities. Behavioral studies have suggested that multisensory processing is a winner-take-all sensory response mechanism to some optimal combination of sensory signals. In addition, multiple sensory cues are not always beneficial with some studies showing maladaptive multisensory processing as an identifier of older adults prone to falls from age matched healthy controls.
A stalwart of modelling sensory decision-making is the work by (Wong &Wang, 2006) but to date almost all of this research has been focused on unisensory tasks. We extend the reduced two-variable …
Enhancing Health Data Representation For Older Adults: Unlocking Opportunities, Peterson Jean
Enhancing Health Data Representation For Older Adults: Unlocking Opportunities, Peterson Jean
Academic Posters Collection
The prevalence of off-the-shelf wearable devices increases the monitoring and measurement of critical physiological parameters like activity, sleep, heart rate, and blood pressure. However, the accessibility of health data representations poses challenges for older adults, who often struggle to understand the criticality of their own health data without assistance. This poster highlights the challenges older adults face in accessing their health data from wearable technologies, specifically focusing on data representations.
To address these challenges, it proposes a methodology that involves a heuristic evaluation of existing data representations with experts and accessibility studies with older adults using a mixed methods approach …
Improve Engagement With Full Labs And Motivated Students: Interactive Labs Via Low Stakes Assessment, Susan Mckeever, Patricia O'Byrne, Amanda O'Farrell
Improve Engagement With Full Labs And Motivated Students: Interactive Labs Via Low Stakes Assessment, Susan Mckeever, Patricia O'Byrne, Amanda O'Farrell
Academic Posters Collection
Poor engagement and attendance is an endemic problem at third level, particularly post covid. Our approach shows how the use of regular in-lab assessment and challenges can dramatically increase student participation and learning. Using three case studies, we demonstrate how we have successfully used this low-stakes assessment approach to improve student outcomes, across a range of modules.
Attention-Based Gender-Stereotype Detection, Manuela Nayantara, Sarah Jane Delany
Attention-Based Gender-Stereotype Detection, Manuela Nayantara, Sarah Jane Delany
Academic Posters Collection
Gender stereotypes are perceptions about the typical physical, emotional, and social characteristics of individuals. Unlike gender bias which can result in the systematic and unfair treatment of individuals based on their gender, gender stereotypes do not always perpetuate a negative impact. Hence, there is no solid definition that frames what is considered a gender-stereotype in text. In addition, there is also a lack of labelled gender-stereotype datasets. This has led to most of the work in literature being about gender bias and not gender stereotypes. Therefore, in our research, we frame a clear definition of what constitutes a gender-stereotype in …
Detecting Patches On Road Pavement Images Acquired With 3d Laser Sensors Using Object Detection And Deep Learning, Ibrahim Hassan Syed, Dympna O'Sullivan, Susan Mckeever, David Power, Ray Mcgowan, Kieran Feighan
Detecting Patches On Road Pavement Images Acquired With 3d Laser Sensors Using Object Detection And Deep Learning, Ibrahim Hassan Syed, Dympna O'Sullivan, Susan Mckeever, David Power, Ray Mcgowan, Kieran Feighan
Academic Posters Collection
Regular pavement inspections are key to good road maintenance and road defect corrections. Advanced pavement inspection systems such as LCMS (Laser Crack Measurement System) can automatically detect the presence of different defects using 3D lasers. However, such systems still require manual involvement to complete the detection of pavement defects. This work proposes an automatic patch detection system using an object detection technique. Results show that the object detection model can successfully detect patches inside LCMS images and suggest that the proposed approach could be integrated into the existing pavement inspection systems.
Cslinc: A Nationwide Cs Mooc For Second-Level Students, Karen Nolan, Keith Quille, Brett A. Becker
Cslinc: A Nationwide Cs Mooc For Second-Level Students, Karen Nolan, Keith Quille, Brett A. Becker
Academic Posters Collection
This poster introduces CSLINC, a free scaffolded MOOC framework tailored to second-level students in Ireland that consists of: an online platform built for accessibility; a suite of modules developed upon international best practices with varying co-creators; and automated assessment and certificates of completion. Its aim is to provide content to promote national CS curricula to all second-level students in Ireland. In September 2021, CSLINC launched to 10,000 students across 100 schools. Future work will include collecting and collating research to validate CSLINC’s goals, scaffolding that will build foundations for national curriculum learning outcomes, and measure its impact on students, their …
Investigating The Use Of Conversational Agents As Accountable Buddies To Support Health And Lifestyle Change, Ekaterina Uetova, Dympna O'Sullivan, Lucy Hederman, Robert J. Ross
Investigating The Use Of Conversational Agents As Accountable Buddies To Support Health And Lifestyle Change, Ekaterina Uetova, Dympna O'Sullivan, Lucy Hederman, Robert J. Ross
Academic Posters Collection
The poster focuses on the role of conversational agents in promoting health and well-being. Results of the literature review indicate that negative emotions can hinder individuals from taking necessary actions related to their health. The study concludes that understanding and addressing emotional barriers is essential to facilitating early access to health services and improving well-being. The poster outlines plans to investigate motivation strategies, develop a prototype conversational agent based on user study insights and chat log data, and incorporate emotion regulation to effectively manage users' emotional experiences.
Spoken Language To Irish Sign Language Machine Translation: A Linguistically Informed Approach, Jesus Aguilar Lopez, Irene Murtagh, Sheila Castilho
Spoken Language To Irish Sign Language Machine Translation: A Linguistically Informed Approach, Jesus Aguilar Lopez, Irene Murtagh, Sheila Castilho
Academic Posters Collection
Many deaf and hard-of-hearing individuals rely on sign language (SL) on a daily basis as a preferred language. Although nowadays there are significant advances on spoken language research, current approaches are often neither linguistically motivated nor tailored to the unique features of SLs. Further research and development are necessary to enhance Sign Language Machine Translation (SLMT) and bring it to a similar level as spoken language MT. This research will endeavour to improve the accuracy and efficiency of SLMT systems, making them more accessible to the Deaf community and empowering deaf and hard of hearing individuals to communicate more effectively …
Framework For Trustworthy Ai In The Health Sector, Mykhailo Danilevskyi
Framework For Trustworthy Ai In The Health Sector, Mykhailo Danilevskyi
Academic Posters Collection
The European Commission defines that Trustworthy AI should be lawful, ethical and robust. The ethical component and its technical methods are the main focus of the research. According to this, the initial research goal is to create a methodology for evaluating datasets for ML modeling using ethical principles in the healthcare domain. Ethical risk assessment will help to ensure compliance with principles such as privacy, fairness, safety and transparency which are especially important for the Health Care sector. At the same time, risks must be evaluated with respect to AI model performance and possible scenarios of risk mitigation. Ethical risk …
From Overlay To Interplay - Subverting The Message And Creating The Surreal With Augmented Reality, Nina Lyons
From Overlay To Interplay - Subverting The Message And Creating The Surreal With Augmented Reality, Nina Lyons
Academic Posters Collection
This proof of concept utilises content creation tools that create diegetic presentation which is not commonly utilised in AR systems. In this study, the virtual overlay that becomes visible through AR displays diegetic content that disrupts the meaning of the poster highlighting the potential for AR as a visual communication medium and the opportunities that AR has, as a medium, for creating narrative.
Explaining Deep Learning Time Series Classification Models Using A Decision Tree, Ephrem T. Mekonnen, Pierpaolo Dondio, Luca Longo
Explaining Deep Learning Time Series Classification Models Using A Decision Tree, Ephrem T. Mekonnen, Pierpaolo Dondio, Luca Longo
Academic Posters Collection
This preliminary study proposes a new post hoc method to explain deep learning-based time series classification models using a decision tree. Our approach generates a decision tree graph or rulesets as an explanation, improving interpretability compared to saliency map-based methods. The method involves two phases: training and evaluating the deep learning-based time series classification model and extracting prototypical events from the evaluation set to train the decision tree classifier. We conducted experiments on artificial and real datasets, evaluating the explanations based on accuracy, fidelity, number of nodes, and depth. Our preliminary findings suggest that our post-hoc method improves the interpretability …
The European Commission And Ai: Guidelines, Acts And Plans Impacting The Teaching Of Ai And Teaching With Ai, Keith Quille, Brett A. Becker, Lidia Vidal-Meliá
The European Commission And Ai: Guidelines, Acts And Plans Impacting The Teaching Of Ai And Teaching With Ai, Keith Quille, Brett A. Becker, Lidia Vidal-Meliá
Academic Posters Collection
Recent developments, guidelines, and acts by the European Commission have started to frame policy for AI and related areas such as ML and data, not only for the broader community, but in the context of education specifically. This poster presents a succinct overview of these developments. Specifically, we look to bring together all publications that might impact the teaching of AI (for example, teacher expectations in the coming years around AI competencies) and publications that affect the use of AI in the classroom. We mean using tools and systems that incorporate both ‘Good Old Fashioned’ AI and those that can …
A Framework For Confusion Mitigation In Task-Oriented Interactions, Na Li, Robert J. Ross
A Framework For Confusion Mitigation In Task-Oriented Interactions, Na Li, Robert J. Ross
Academic Posters Collection
Confusion is a mental state that can be triggered in task-oriented interactions and which can if left unattended lead to boredom, frustration, or disengagement from the task at hand. Previous work has demonstrated that confusion can be detected in situated human-robot interactions from visual and auditory cues. Therefore, in the next step, we propose appropriate interaction structures in this study, which should be used to mitigate confusion. We motivate and describe this dialogue mechanism through an information state-style dialogue framework and policies, and also outline the approach we are taking to integrate such a meta-conversational goal alongside core task-oriented considerations …
Techmate: A Research-Driven Toolkit To Enhance Gender Balance In Computing Education, Alina Berry, Sarah Jane Delany
Techmate: A Research-Driven Toolkit To Enhance Gender Balance In Computing Education, Alina Berry, Sarah Jane Delany
Academic Posters Collection
This poster presents a toolkit of practical initiatives and guidance on how to enhance gender balance in computing higher education. The suggested initiatives are designed in the way that could be adapted for a use in a local context, especially in universities in the UK or in Ireland. The initiatives are categorised under four main areas: Policy, Pedagogy, Influence & Support and Promotion & Engagement. Additionally, guidance is given on mechanisms to evaluate the impact of these initiatives. This work will be of interest to champions looking to enhance gender balance in their computing courses.
Ideating Explainable Ai, Helen Sheridan, Emma Murphy, Dympna O'Sullivan
Ideating Explainable Ai, Helen Sheridan, Emma Murphy, Dympna O'Sullivan
Academic Posters Collection
Exploring user's mental models of an AI-driven recruitment system using design-thinking methods as an approach to ideating XAI.
Towards Accommodating Gerunds Within The Sign Language Lexicon, Zaid Mohammed, Irene Murtagh
Towards Accommodating Gerunds Within The Sign Language Lexicon, Zaid Mohammed, Irene Murtagh
Academic Posters Collection
This work is part of ongoing research work that focuses on the linguistic analysis and computational description of five different Sign Languages (SLs) namely Irish Sign Language (ISL), Flemish Sign Language (VGT), Dutch Sign Language (NGT), Spanish Sign Language (LSE), and British Sign Language (BSL) as part of the SignON project. This work will be leveraged to inform the development of SL lexicon entries for a Sign Language Machine Translation (SLMT) system. In particular, this research focuses on ISL. We investigate the existence of constructions similar to or equivalent in functionality to gerunds in spoken language, in particular, English. The …
Using Open-Source To Enhance Teaching And Scholarship, Steven Clontz, Michael Black, Ricky Green, Carlos Montalvo, Rebecca Macdonald, Sean Stalley
Using Open-Source To Enhance Teaching And Scholarship, Steven Clontz, Michael Black, Ricky Green, Carlos Montalvo, Rebecca Macdonald, Sean Stalley
CoTL 2023 Panel
The adoption of open-source resources (software, hardware, educational content, and more) that are freely licensed for use, sharing, repurposing, and remixing has grown dramatically in recent years, within both academia and industry. This panel features several faculty and staff who will share and discuss their experiences using open-source solutions to enhance teaching and scholarship (both SoTL and discipline research) at their institutions.
The Rock 2022, School Of Engineering And Computer Science
The Rock 2022, School Of Engineering And Computer Science
The Rock
No abstract provided.
Algorithm-Based Fault Tolerance At Scale, Hayden Estes
Algorithm-Based Fault Tolerance At Scale, Hayden Estes
Summer Community of Scholars Posters (RCEU and HCR Combined Programs)
No abstract provided.
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
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 …
A Machine Learning Approach To Denoising Particle Detector Observations In Nuclear Physics, Polykarpos Thomadakis, Angelos Angelopoulos, Gagik Gavalian, Nikos Chrisochoides
A Machine Learning Approach To Denoising Particle Detector Observations In Nuclear Physics, Polykarpos Thomadakis, Angelos Angelopoulos, Gagik Gavalian, Nikos Chrisochoides
College of Sciences Posters
With the evolution in detector technologies and electronic components used in the Nuclear Physics field, experimental setups become larger and more complex. Faster electronics enable particle accelerator experiments to run with higher beam intensity, providing more interactions per time and more particles per interaction. However, the increased beam intensities present a challenge to particle detectors because of the higher amount of noise and uncorrelated signals. Higher noise levels lead to a more challenging particle reconstruction process by increasing the number of combinatorics to analyze and background signals to eliminate. On the other hand, increasing the beam intensity can provide physics …
Lattice Optics Optimization For Recirculatory Energy Recovery Linacs With Multi-Objective Optimization, Isurumali Neththikumara, Todd Satogata, Alex Bogacz, Ryan Bodenstein, Arthur Vandenhoeke
Lattice Optics Optimization For Recirculatory Energy Recovery Linacs With Multi-Objective Optimization, Isurumali Neththikumara, Todd Satogata, Alex Bogacz, Ryan Bodenstein, Arthur Vandenhoeke
College of Sciences Posters
Beamline optics design for recirculatory linear accelerators requires special attention to suppress beam instabilities arising due to collective effects. The impact of these collective effects becomes more pronounced with the addition of energy recovery (ER) capability. Jefferson Lab’s multi-pass, multi-GeV ER proposal for the CEBAF accelerator, ER@CEBAF, is a 10- pass ER demonstration with low beam current. Tighter control of the beam parameters at lower energies is necessary to avoid beam break-up (BBU) instabilities, even with a small beam current. Optics optimizations require balancing both beta excursions at high-energy passes and overfocusing at low-energy passes. Here, we discuss an optics …
Analysis Of An Existing Method In Refinement Of Protein Structure Predictions Using Cryo-Em Images, Maytha Alshammari, Jing He, Willy Wriggers, Jiangwen Sun
Analysis Of An Existing Method In Refinement Of Protein Structure Predictions Using Cryo-Em Images, Maytha Alshammari, Jing He, Willy Wriggers, Jiangwen Sun
College of Sciences Posters
Protein structure prediction produces atomic models from its amino acid sequence. Three-dimensional structures are important for understanding the function mechanism of proteins. Knowing the structure of a given protein is crucial in drug development design of novel enzymes. AlphaFold2 is a protein structure prediction tool with good performance in recent CASP competitions. Phenix is a tool for determination of a protein structure from a high-resolution 3D molecular image. Recent development of Phenix shows that it is capable to refine predicted models from AlphaFold2, specifically the poorly predicted regions, by incorporating information from the 3D image of the protein. The goal …
Physics-Informed Neural Networks (Pinns) For Dvcs Cross Sections, Manal Almaeen, Jake Grigsby, Joshua Hoskins, Brandon Kriesten, Yaohang Li, Huey-Wen Lin, Simonetta Liuti, Sorawich Maichum
Physics-Informed Neural Networks (Pinns) For Dvcs Cross Sections, Manal Almaeen, Jake Grigsby, Joshua Hoskins, Brandon Kriesten, Yaohang Li, Huey-Wen Lin, Simonetta Liuti, Sorawich Maichum
College of Sciences Posters
We present a physics informed deep learning technique for Deeply Virtual Compton Scattering (DVCS) cross sections from an unpolarized proton target using both an unpolarized and polarized electron beam. Training a deep learning model typically requires a large size of data that might not always be available or possible to obtain. Alternatively, a deep learning model can be trained using additional knowledge gained by enforcing some physics constraints such as angular symmetries for better accuracy and generalization. By incorporating physics knowledge to our deep learning model, our framework shows precise predictions on the DVCS cross sections and better extrapolation on …
Medical Devices And Cybersecurity, Hilary Finch
Medical Devices And Cybersecurity, Hilary Finch
School of Cybersecurity Posters
I begin by looking at the role of cybersecurity in the medical world. The healthcare industry adopted information technology quite quickly. While the advancement was obviously beneficial and necessary to keep up with an ever-growing demand, the healthcare industry did not place any kind of pointed focus on the security of their IT department, or the sensitive information housed therein.
When rapid advancements of technology outpaced the gradual advancement of hospital cybersecurity, security concerns became a difficult issue to control. There is a serious need for more advancements in hospital security. Each interconnected medical device has its own unique security …
Did They Really Tweet That?, Caleb Bradford, Michael L. Nelson (Mentor)
Did They Really Tweet That?, Caleb Bradford, Michael L. Nelson (Mentor)
Computer & Information Science: Research Experiences for Undergraduates in Disinformation Detection and Analytics
No abstract provided.
Computer-Based Scaffolding In Computer Science Education, Rebecca Trinh, Simone Levy
Computer-Based Scaffolding In Computer Science Education, Rebecca Trinh, Simone Levy
Summer REU Program
No abstract provided.
Nlp@Vcu: Crop Characteristic Extraction Framework, Cora Lewis, Bridget Mcinnes, Getiria Onsongo
Nlp@Vcu: Crop Characteristic Extraction Framework, Cora Lewis, Bridget Mcinnes, Getiria Onsongo
Summer REU Program
We developed a crop characteristic extraction framework. Starting from a custom SpaCy named entity recognition model, we added pre-trained word embeddings and a part-of-speech based entity expansion post-processing step. Then, we implemented an evaluation framework that functioned as a 5-fold cross validation wrapper for SpaCy custom training. Preliminary results showed improvement in the extraction framework after these additions.
Disinformation About Mental Health On Tiktok, Dani Graber, Anne Perrotti (Mentor)
Disinformation About Mental Health On Tiktok, Dani Graber, Anne Perrotti (Mentor)
Computer & Information Science: Research Experiences for Undergraduates in Disinformation Detection and Analytics
No abstract provided.