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All Outputs (1379)

Towards Automatic Tutoring of Custom Student-Stated Math Word Problems (2023)
Presentation / Conference Contribution
Arnau-González, P., Serrano-Mamolar, A., Katsigiannis, S., & Arevalillo-Herráez, M. (2023, July). Towards Automatic Tutoring of Custom Student-Stated Math Word Problems. Presented at International Conference on Artificial Intelligence in Education (AIED), Tokyo, Japan

Math Word Problem (MWP) solving for teaching math with Intelligent Tutoring Systems (ITSs) faces a major limitation: ITSs only supervise pre-registered problems, requiring substantial manual effort to add new ones. ITSs cannot assist with student-gen... Read More about Towards Automatic Tutoring of Custom Student-Stated Math Word Problems.

Exact-NeRF: An Exploration of a Precise Volumetric Parameterization for Neural Radiance Fields (2023)
Presentation / Conference Contribution
Isaac-Medina, B., Willcocks, C., & Breckon, T. (2023, June). Exact-NeRF: An Exploration of a Precise Volumetric Parameterization for Neural Radiance Fields. Presented at IEEE/CVF Conference on Computer Vision and Pattern Recognition 2023, Vancouver, BC

Neural Radiance Fields (NeRF) have attracted significant attention due to their ability to synthesize novel scene views with great accuracy. However, inherent to their underlying formulation, the sampling of points along a ray with zero width may res... Read More about Exact-NeRF: An Exploration of a Precise Volumetric Parameterization for Neural Radiance Fields.

Natural Language Explanations for Machine Learning Classification Decisions (2023)
Presentation / Conference Contribution
Burton, J., Al Moubayed, N., & Enshaei, A. (2023, June). Natural Language Explanations for Machine Learning Classification Decisions. Presented at 2023 International Joint Conference on Neural Networks (IJCNN), Gold Coast, Australia

This paper addresses the challenge of providing understandable explanations for machine learning classification decisions. To do this, we introduce a dataset of expert-written textual explanations paired with numerical explanations, forming a data-to... Read More about Natural Language Explanations for Machine Learning Classification Decisions.

Uniting General-Graph and Geometric-Based Radio Networks via Independence Number Parametrization (2023)
Presentation / Conference Contribution
Davies, P. (2023, June). Uniting General-Graph and Geometric-Based Radio Networks via Independence Number Parametrization. Presented at PODC 2023: ACM Symposium on Principles of Distributed Computing, Orlando, Florida

In the study of radio networks, the tasks of broadcasting (propagating a message throughout the network) and leader election (having the network agree on a node to designate ‘leader’) are two of the most fundamental global problems, and have a long h... Read More about Uniting General-Graph and Geometric-Based Radio Networks via Independence Number Parametrization.

Optimal Message-Passing with Noisy Beeps (2023)
Presentation / Conference Contribution
Davies, P. (2023, June). Optimal Message-Passing with Noisy Beeps. Presented at PODC 2023: ACM Symposium on Principles of Distributed Computing, Orlando, Florida

Beeping models are models for networks of weak devices, such as sensor networks or biological networks. In these networks, nodes are allowed to communicate only via emitting beeps: unary pulses of energy. Listening nodes only the capability of carrie... Read More about Optimal Message-Passing with Noisy Beeps.

Distributed MIS in O(log log n) Awake Complexity (2023)
Presentation / Conference Contribution
Dufoulon, F., Moses Jr., W. K., & Pandurangan, G. (2023, June). Distributed MIS in O(log log n) Awake Complexity. Presented at PODC '23: 2023 ACM Symposium on Principles of Distributed Computing, Orlando, Florida

Maximal Independent Set (MIS) is one of the fundamental and most well-studied problems in distributed graph algorithms. Even after four decades of intensive research, the best known (randomized) MIS algorithms have O(log n) round complexity on genera... Read More about Distributed MIS in O(log log n) Awake Complexity.

PICA-PICA: Exploring a Customisable Smart STEAM Educational Approach via a Smooth Combination of Programming, Engineering and Art (2023)
Presentation / Conference Contribution
Nagai, T., Klem, S., Kayama, M., Asuke, T., Meccawy, M., Wang, J., Cristea, A. I., Stewart, C. D., & Shi, L. (2023, May). PICA-PICA: Exploring a Customisable Smart STEAM Educational Approach via a Smooth Combination of Programming, Engineering and Art. Presented at 2023 IEEE Global Engineering Education Conference (EDUCON), Kuwait

The STEAM approach in education has been gaining increasing popularity over the last decade. This is due to its potential in enhancing students' learning, when teaching arts and scientific disciplines together. This paper introduces the PICA-PICA con... Read More about PICA-PICA: Exploring a Customisable Smart STEAM Educational Approach via a Smooth Combination of Programming, Engineering and Art.

On the Capacity Region of a Quantum Switch with Entanglement Purification (2023)
Presentation / Conference Contribution
Panigrahy, N. K., Vasantam, T., Towsley, D., & Tassiulas, L. (2023, May). On the Capacity Region of a Quantum Switch with Entanglement Purification. Paper presented at INFOCOM 2023: IEEE International Conference on Computer Communications, New York

Quantum switches are envisioned to be an integral component of future entanglement distribution networks. They can provide high quality entanglement distribution service to end-users by performing quantum operations such as entanglement swapping and... Read More about On the Capacity Region of a Quantum Switch with Entanglement Purification.

Efficient GPU Offloading with OpenMP for a Hyperbolic Finite Volume Solver on Dynamically Adaptive Meshes (2023)
Presentation / Conference Contribution
Wille, M., Weinzierl, T., Brito Gadeschi, G., & Bader, M. (2023, December). Efficient GPU Offloading with OpenMP for a Hyperbolic Finite Volume Solver on Dynamically Adaptive Meshes. Presented at ISC High Performance 2023, Hamburg

We identify and show how to overcome an OpenMP bottleneck in the administration of GPU memory. It arises for a wave equation solver on dynamically adaptive block-structured Cartesian meshes, which keeps all CPU threads busy and allows all of them to... Read More about Efficient GPU Offloading with OpenMP for a Hyperbolic Finite Volume Solver on Dynamically Adaptive Meshes.

A Virtual Reality System for the Assessment of Patients with Lower Limb Rotational Abnormalities (2023)
Presentation / Conference Contribution
Sibrina, D., Bethapudi, S., & Koulieris, G. A. (2023, March). A Virtual Reality System for the Assessment of Patients with Lower Limb Rotational Abnormalities. Presented at 2023 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW), Shanghai, China

Rotational lower limb abnormalities cause patellar mal-tracking which impacts young patients. Repetitive patellar dislocation may require knee arthroplasty. Surgeons employ CT to identify rotational abnormalities and make surgical decisions. Recent s... Read More about A Virtual Reality System for the Assessment of Patients with Lower Limb Rotational Abnormalities.

Improving Health Mention Classification Through Emphasising Literal Meanings: A Study Towards Diversity and Generalisation for Public Health Surveillance (2023)
Presentation / Conference Contribution
Aduragba, T. O., Yu, J., Cristea, A. I., & Long, Y. (2023, April). Improving Health Mention Classification Through Emphasising Literal Meanings: A Study Towards Diversity and Generalisation for Public Health Surveillance. Presented at WWW '23: The ACM Web Conference 2023, Austin, Texas

People often use disease or symptom terms on social media and online forums in ways other than to describe their health. Thus the NLP health mention classification (HMC) task aims to identify posts where users are discussing health conditions literal... Read More about Improving Health Mention Classification Through Emphasising Literal Meanings: A Study Towards Diversity and Generalisation for Public Health Surveillance.

Predicting the Performance of a Computing System with Deep Networks (2023)
Presentation / Conference Contribution
Cengiz, M., Forshaw, M., Atapour-Abarghouei, A., & McGough, A. S. (2023, April). Predicting the Performance of a Computing System with Deep Networks. Presented at 2023 ACM/SPEC International Conference on Performance Engineering (ICPE ’23), Coimbra, Portugal

Predicting the performance and energy consumption of computing hardware is critical for many modern applications. This will inform procurement decisions, deployment decisions, and autonomic scaling. Existing approaches to understanding the performanc... Read More about Predicting the Performance of a Computing System with Deep Networks.

Tutor In-sight: Guiding and Visualizing Students Attention with Mixed Reality Avatar Presentation Tools (2023)
Presentation / Conference Contribution
Thanyadit, S., Heintz, M., & Law, E. L.-C. (2023, April). Tutor In-sight: Guiding and Visualizing Students Attention with Mixed Reality Avatar Presentation Tools. Presented at CHI '23: CHI Conference on Human Factors in Computing Systems, Hamburg, Germany

Remote conferencing systems are increasingly used to supplement or even replace in-person teaching. However, prevailing conferencing systems restrict the teacher’s representation to a webcam live-stream, hamper the teacher’s use of body-language, and... Read More about Tutor In-sight: Guiding and Visualizing Students Attention with Mixed Reality Avatar Presentation Tools.

Musical Genre Recognition Based on Deep Descriptors of Harmony, Instrumentation, and Segments (2023)
Presentation / Conference Contribution
Vatolkin, I., Gotham, M., Lόpez, N. N., & Ostermann, F. (2023, April). Musical Genre Recognition Based on Deep Descriptors of Harmony, Instrumentation, and Segments. Presented at EvoMUSART 2023: Artificial Intelligence in Music, Sound, Art and Design, Brno, Czech Republic

Deep learning has recently established itself as a cluster of methods of choice for almost all classification tasks in music information retrieval. However, despite very good classification performance, it sometimes brings disadvantages including lon... Read More about Musical Genre Recognition Based on Deep Descriptors of Harmony, Instrumentation, and Segments.

Realism versus Performance for Adversarial Examples Against DL-based NIDS (2023)
Presentation / Conference Contribution
Alatwi, H. A., & Morisset, C. (2023, March). Realism versus Performance for Adversarial Examples Against DL-based NIDS. Presented at SAC '23: 38th ACM/SIGAPP Symposium on Applied Computing, Tallinn Estonia

The application of deep learning-based (DL) network intrusion detection systems (NIDS) enables effective automated detection of cyberattacks. Such models can extract valuable features from high-dimensional and heterogeneous network traffic with minim... Read More about Realism versus Performance for Adversarial Examples Against DL-based NIDS.

Atmospheric optical turbulence analysis in London’s financial district (2023)
Presentation / Conference Contribution
Westerby-Griffin, L., Osborn, J., Farley, O. J. D., Griffiths, R., & Love, G. D. (2023, January). Atmospheric optical turbulence analysis in London’s financial district. Presented at Free-Space Laser Communications XXXV, San Francisco, United States

Atmospheric optical turbulence causes signal loses in laser propagation. Here we present vertical measurements of optical turbulence taken in London’s financial district. Additionally, we demonstrate a method of modelling atmospheric states in simula... Read More about Atmospheric optical turbulence analysis in London’s financial district.

1st Workshop on Maritime Computer Vision (MaCVi) 2023: Challenge Results (2023)
Presentation / Conference Contribution
Kiefer, B., Kristan, M., Pers, J., Zust, L., Poiesi, F., De Alcantara Andrade, F. A., Bernardino, A., Dawkins, M., Raitoharju, J., Quan, Y., Atmaca, A., Hofer, T., Zhang, Q., Xu, Y., Zhang, J., Tao, D., Sommer, L., Spraul, R., Zhao, H., Zhang, H., …Yang, M. T. (2023, January). 1st Workshop on Maritime Computer Vision (MaCVi) 2023: Challenge Results. Presented at Proceedings - 2023 IEEE/CVF Winter Conference on Applications of Computer Vision Workshops, WACVW 2023, Waikoloa, HI, USA

The 1st Workshop on Maritime Computer Vision (MaCVi) 2023 focused on maritime computer vision for Unmanned Aerial Vehicles (UAV) and Unmanned Surface Vehicle (USV), and organized several subchallenges in this domain: (i) UAV-based Maritime Object Det... Read More about 1st Workshop on Maritime Computer Vision (MaCVi) 2023: Challenge Results.

Atmospheric optical turbulence measurements at varying elevation angles (2023)
Presentation / Conference Contribution
Westerby-Griffin, L., Osborn, J., Farley, O. J. D., Griffiths, R., & Love, G. D. (2023, January). Atmospheric optical turbulence measurements at varying elevation angles. Paper presented at Free-Space Laser Communications XXXV, San Francisco, United States

FFM-SVD: A Novel Approach for Personality-aware Recommender Systems (2023)
Presentation / Conference Contribution
Widdeson, K., & Hadžidedić, S. (2022, December). FFM-SVD: A Novel Approach for Personality-aware Recommender Systems. Presented at 2022 IEEE/ACS 19th International Conference on Computer Systems and Applications (AICCSA), Abu Dhabi, UAE

This paper addresses and evaluates approaches to incorporating personality data into a recommender system. Automatic personality recognition is enabled by the LIWC dictionary. Personality-aware pre-filtering techniques are developed and discussed, wi... Read More about FFM-SVD: A Novel Approach for Personality-aware Recommender Systems.