All Outputs (1379)

Detrimental task execution patterns in mainstream OpenMP runtimes (2024)
Presentation / Conference Contribution
Weinzierl, T., Tuft, A., & Klemm, M. (2024, September). Detrimental task execution patterns in mainstream OpenMP runtimes. Presented at IWOMP 2024, Perth, Australia

The OpenMP API offers both task-based and data-parallel concepts to scientific computing. While it provides descriptive and prescriptive annotations, it is in many places deliberately unspecific how to implement its annotations. As the predomina... Read More about Detrimental task execution patterns in mainstream OpenMP runtimes.

Superpixel-based Anomaly Detection for Irregular Textures with a Focus on Pixel-level Accuracy (2024)
Presentation / Conference Contribution
Rafiei, M., Breckon, T. P., & Iosifidis, A. (2024, June). Superpixel-based Anomaly Detection for Irregular Textures with a Focus on Pixel-level Accuracy. Presented at 2024 International Joint Conference on Neural Networks (IJCNN), Yokohama, Japan

Recent anomaly detection methods achieve high performance on commonly used image and pixel-level metrics. However, due to the imbalance in the number of normal and abnormal pixels commonly encountered in anomaly detection problems, commonly adopted p... Read More about Superpixel-based Anomaly Detection for Irregular Textures with a Focus on Pixel-level Accuracy.

Extracting Quantitative Streamline Information from Surface Flow Visualization Images in a Linear Cascade using Convolutional Neural Networks (2024)
Presentation / Conference Contribution
Liu, X., Ingram, G., Sims-Williams, D., & Breckon, T. P. (2024, September). Extracting Quantitative Streamline Information from Surface Flow Visualization Images in a Linear Cascade using Convolutional Neural Networks. Presented at GPPS Chania24, Chania

Surface flow visualization (SFV), specifically surface oil flow visualization, is an experimental technique that involves coating the surface with a mixture of oils and dyes before applying the flow to the subject. While investigating the surface flo... Read More about Extracting Quantitative Streamline Information from Surface Flow Visualization Images in a Linear Cascade using Convolutional Neural Networks.

Centersam: Fully Automatic Prompt for Dense Nucleus Segmentation (2024)
Presentation / Conference Contribution
Li, Y., Ren, H., Deng, J., Ma, X., & Xie, X. (2024, May). Centersam: Fully Automatic Prompt for Dense Nucleus Segmentation. Presented at 2024 IEEE International Symposium on Biomedical Imaging (ISBI), Athens, Greece

Nucleus segmentation is a vitally important task in biomedical image analysis which leads to multiple applications such as cellular behavior study, tumor detection and cancer diagnosis. However, challenges, such as ambiguous boundary for touching or... Read More about Centersam: Fully Automatic Prompt for Dense Nucleus Segmentation.

Code Gradients: Towards Automated Traceability of LLM-Generated Code (2024)
Presentation / Conference Contribution
North, M., Atapour-Abarghouei, A., & Bencomo, N. (2024, June). Code Gradients: Towards Automated Traceability of LLM-Generated Code. Presented at 2024 IEEE 32nd International Requirements Engineering Conference (RE), Reykjavik, Iceland

Large language models (LLMs) have recently seen huge growth in capability and usage. Within software engineering, LLMs are increasingly being used by developers to generate code. Code generated by an LLM can be seen essentially a continuous mapping f... Read More about Code Gradients: Towards Automated Traceability of LLM-Generated Code.

Responsible AI in Personalised Movie Recommender Systems for the Hearing Impaired Community (2024)
Presentation / Conference Contribution
Vachhani, R., & Hadzidedic, S. (2024, September). Responsible AI in Personalised Movie Recommender Systems for the Hearing Impaired Community. Presented at 2024 Intelligent Systems Conference (IntelliSys), Amsterdam, The Netherlands

The aim of this paper is to develop a personalised recommender system (RS) in the movie domain - MRSystem - with a focus on Responsible AI for the hearing impaired community. There is currently no movie RS that looks at protected characteristics when... Read More about Responsible AI in Personalised Movie Recommender Systems for the Hearing Impaired Community.

Optimising IT Security Research via a Low Cost, Instantly Available, Cloud Based Cyber Range (2024)
Presentation / Conference Contribution
Wake, P., Black, S., & Young, J. (2024, July). Optimising IT Security Research via a Low Cost, Instantly Available, Cloud Based Cyber Range. Presented at 2024 International Conference on Electrical, Computer and Energy Technologies (ICECET), Sydney, Australia

Testing the effectiveness of IT security measures for enterprises, companies, and institutions can often incur substantial costs in terms of time and resources. These costs encompass not only the investment in infrastructure for creating a cyber rang... Read More about Optimising IT Security Research via a Low Cost, Instantly Available, Cloud Based Cyber Range.

Fitting Room: Lung Transplantation Donor-Recipient Size-matching in Virtual Reality (2024)
Presentation / Conference Contribution
Sibrina, D., Novysedlak, R., Kolarik, J., Lischke, R., & Koulieris, G. A. (2024, July). Fitting Room: Lung Transplantation Donor-Recipient Size-matching in Virtual Reality. Poster presented at SIGGRAPH '24: Special Interest Group on Computer Graphics and Interactive Techniques Conference, Denver CO USA

SID-NERF: Few-Shot Nerf Based on Scene Information Distribution (2024)
Presentation / Conference Contribution
Li, Y., Wan, F., & Long, Y. (2024, July). SID-NERF: Few-Shot Nerf Based on Scene Information Distribution. Presented at 2024 IEEE International Conference on Multimedia and Expo (ICME), Niagara Falls, ON, Canada

The novel view synthesis from a limited set of images is a significant research focus. Traditional NeRF methods, relying mainly on color supervision, struggle with accurate scene geometry reconstruction when faced with sparse input images, leading to... Read More about SID-NERF: Few-Shot Nerf Based on Scene Information Distribution.

1-in-3 vs. Not-All-Equal: Dichotomy of a broken promise (2024)
Presentation / Conference Contribution
Ciardo, L., Kozik, M., Krokhin, A., Nakajima, T.-V., & Živný, S. (2024, July). 1-in-3 vs. Not-All-Equal: Dichotomy of a broken promise. Presented at LLICS '24: 39th Annual ACM/IEEE Symposium on Logic in Computer Science, Tallinn, Estonia

The 1-in-3 and Not-All-Equal satisfiability problems for Boolean CNF formulas are two well-known NP-hard problems. In contrast, the promise 1-in-3 vs. Not-All-Equal problem can be solved in polynomial time. In the present work, we investigate this co... Read More about 1-in-3 vs. Not-All-Equal: Dichotomy of a broken promise.

Parallel Derandomization for Coloring (2024)
Presentation / Conference Contribution
Coy, S., Czumaj, A., Davies-Peck, P., & Mishra, G. (2024, May). Parallel Derandomization for Coloring. Presented at 38th IEEE International Parallel & Distributed Processing Symposium (IPDPS 2024), San Francisco

Graph coloring problems are among the most fundamental problems in parallel and distributed computing, and have been studied extensively in both settings. In this context, designing efficient deterministic algorithms for these problems has been found... Read More about Parallel Derandomization for Coloring.

Designing a Pedagogical Framework for Developing Abstraction Skills (2024)
Presentation / Conference Contribution
Begum, M., Crossley, J., Strömbäck, F., Akrida, E., Alpizar-Chacon, I., Evans, A., Gross, J. B., Haglund, P., Lonati, V., Satyavolu, C., & Thorgeirsson, S. (2024, July). Designing a Pedagogical Framework for Developing Abstraction Skills. Presented at ITiCSE 2024: Innovation and Technology in Computer Science Education, Milan Italy

Simplifying Multimedia Programming for Novice Programmers: MediaLib and Its Learning Materials (2024)
Presentation / Conference Contribution
Wynn, A., Wang, J., & Valente, A. (2024, July). Simplifying Multimedia Programming for Novice Programmers: MediaLib and Its Learning Materials. Presented at ITiCSE 2024: Innovation and Technology in Computer Science Education, Milan, Italy

Beginner programmers can develop an intuitive understanding of programming by leveraging the motivating field of multimedia to visually inspect outputs and experiment with different ways to solve problems. This paper presents MediaLib, a Python libra... Read More about Simplifying Multimedia Programming for Novice Programmers: MediaLib and Its Learning Materials.

Introducing Code Quality in the CS1 Classroom (2024)
Presentation / Conference Contribution
Izu, C., Mirolo, C., Börstler, J., Connamacher, H., Crosby, R., Glassey, R., Haldeman, G., Kiljunen, O., Kumar, A. N., Liu, D., Luxton-Reilly, A., Matsumoto, S., Carneiro de Oliveira, E., Russell, S., & Shah, A. (2024, July). Introducing Code Quality in the CS1 Classroom. Presented at ITiCSE 2024: Innovation and Technology in Computer Science Education, Milan Italy

Characterising code quality is a challenge that was addressed by Börstler et al. 's working group in 2017. As emerged from their study, educators, developers and students have different perceptions of the manifold aspects involved, and a major conclu... Read More about Introducing Code Quality in the CS1 Classroom.

Natural Language Processing for a Personalised Educational Experience in Virtual Reality (2024)
Presentation / Conference Contribution
Alghamdi, N., & Cristea, A. I. (2024, July). Natural Language Processing for a Personalised Educational Experience in Virtual Reality. Presented at Artificial Intelligence in Education (AIED 2024), Recife, Brazil

Virtual Reality (VR) is a technology that creates a simulated immersive environment, allowing users to be more engaged and interactive. The user can interact with a VR environment using head-mounted displays, hand controllers, and, in some cases, spe... Read More about Natural Language Processing for a Personalised Educational Experience in Virtual Reality.

Reducing University Students’ Exam Anxiety via Mindfulness-Based Cognitive Therapy in VR with Real-Time EEG Neurofeedback (2024)
Presentation / Conference Contribution
Pan, Z., Cristea, A. I., & Li, F. W. B. (2024, July). Reducing University Students’ Exam Anxiety via Mindfulness-Based Cognitive Therapy in VR with Real-Time EEG Neurofeedback. Presented at AIED 2024: Artificial Intelligence in Education, Recife, Brazil

This research aims to develop and evaluate a novel approach to reduce university students’ exam anxiety and teach them how to better manage it using a personalised, emotion-informed Mindfulness-Based Cognitive Therapy (MBCT) method, delivered within... Read More about Reducing University Students’ Exam Anxiety via Mindfulness-Based Cognitive Therapy in VR with Real-Time EEG Neurofeedback.

Exploiting Automorphisms of Temporal Graphs for Fast Exploration and Rendezvous (2024)
Presentation / Conference Contribution
Dogeas, K., Erlebach, T., Kammer, F., Meintrup, J., & Moses Jr, W. K. (2024, July). Exploiting Automorphisms of Temporal Graphs for Fast Exploration and Rendezvous. Presented at 51st EATCS International Colloquium on Automata, Languages and Programming, Tallinn, Estonia

Virtual Reality (VR) in Safety Education: A Case Study of Mining Engineering (2024)
Presentation / Conference Contribution
Chang, H., Pan, Z., & Cristea, A. I. (2024, July). Virtual Reality (VR) in Safety Education: A Case Study of Mining Engineering. Presented at AIED 2024: Artificial Intelligence in Education, Recife, Brazil

Safety education and training are vital in the mining industry. However, traditional training relies on passive modalities, such as lectures, videos and brochures. These suffer from sever limitations - poor reproducibility, inefficient resource utili... Read More about Virtual Reality (VR) in Safety Education: A Case Study of Mining Engineering.

Disentangling Racial Phenotypes: Fine-Grained Control of Race-related Facial Phenotype Characteristics (2024)
Presentation / Conference Contribution
Yucer, S., Abarghouei, A. A., Al Moubayed, N., & Breckon, T. P. (2024, June). Disentangling Racial Phenotypes: Fine-Grained Control of Race-related Facial Phenotype Characteristics. Presented at 2024 International Joint Conference on Neural Networks (IJCNN), Yokohama, Japan

Achieving an effective fine-grained appearance variation over 2D facial images, whilst preserving facial identity, is a challenging task due to the high complexity and entanglement of common 2D facial feature encoding spaces. Despite these challenges... Read More about Disentangling Racial Phenotypes: Fine-Grained Control of Race-related Facial Phenotype Characteristics.

Inner Metric Analysis as a Measure of Rhythmic Syncopation (2024)
Presentation / Conference Contribution
Bemman, B., & Christensen, J. (2024, November). Inner Metric Analysis as a Measure of Rhythmic Syncopation. Presented at ISMIR 2024: 25th International Society for Music Information Retrieval Conference, San Francisco