Squishy, yet satisfying: Exploring deformable shapes' cross-modal correspondences with colours and emotions (2024)
Conference Proceeding
Steer, C., Sauvé, K., Jain, A., Lawal, O., Proulx, M. J., Jicol, C., & Alexander, J. (2024). Squishy, yet satisfying: Exploring deformable shapes' cross-modal correspondences with colours and emotions. In CHI '24: Proceedings of the CHI Conference on Human Factors in Computing Systems (1-20). https://doi.org/10.1145/3613904.3641952

Surfaces with deformable and shape-changing properties seek to enhance and diversify tangible interactions with computing systems. However, we currently lack fundamental knowledge and user interface design principles that connect the inherent propert... Read More about Squishy, yet satisfying: Exploring deformable shapes' cross-modal correspondences with colours and emotions.

DeformIO: Dynamic stiffness control on a deformable force-sensing display (2024)
Conference Proceeding
Nash, J. D., Steer, C., Dinca, T., Sharma, A., Favaratto Santos, A., Wildgoose, B. T., …Alexander, J. (2024). DeformIO: Dynamic stiffness control on a deformable force-sensing display. In CHI EA '24: Extended Abstracts of the CHI Conference on Human Factors in Computing Systems (1-8). https://doi.org/10.1145/3613905.3650772

Introducing DeformIO, a novel deformable display with co-located force input and variable stiffness output. Unlike prior work, our approach does not require pin arrays or re-configurable panels. Instead, we leveraged pneumatics and resistive sensing... Read More about DeformIO: Dynamic stiffness control on a deformable force-sensing display.

Digital twins in industry 4.0 cyber security (2024)
Conference Proceeding
Lo, C., Win, T. Y., Rezaeifar, Z., Khan, Z., & Legg, P. (2024). Digital twins in industry 4.0 cyber security. In Proceedings of the IEEE Smart World Congress 2023. https://doi.org/10.1109/swc57546.2023.10449147

The increased adoption of sophisticated Cyber Physical Systems (CPS) in critical infrastructure and various aspects of Industry 4.0 has exposed vulnerabilities stemming from legacy CPS and Industrial Internet of Things (IIoT) devices. The interconnec... Read More about Digital twins in industry 4.0 cyber security.

Electrical properties of proteinoids for unconventional computing architectures (2023)
Conference Proceeding
Mougkogiannis, P., & Adamatzky, A. (2023). Electrical properties of proteinoids for unconventional computing architectures. In NANOARCH '23: Proceedings of the 18th ACM International Symposium on Nanoscale Architectures (1-4). https://doi.org/10.1145/3611315.3633264

Proteinoids are peptide-like molecules that arise from the combination of amino acids in pre-biotic environments. Recent studies have revealed distinctive electrical characteristics of proteinoids, such as the presence of voltage-gated ion channels,... Read More about Electrical properties of proteinoids for unconventional computing architectures.

Development and evaluation of a mobile app to support reading education (2023)
Conference Proceeding
Mthethwa, L. C., & Matthews, P. (2023). Development and evaluation of a mobile app to support reading education. In AfriCHI '23: Proceedings of the 4th African Human Computer Interaction Conference (58-63). https://doi.org/10.1145/3628096.3628751

We report on the design, development and evaluation of an app to support teachers in the teaching of reading at primary level. The app was developed with two main features: book levelling, where a book photograph, OCR and a simple machine learning mo... Read More about Development and evaluation of a mobile app to support reading education.

Predicting social trust from implicit feedback (2023)
Conference Proceeding
Oshodin, E. (2023). Predicting social trust from implicit feedback. In Artificial Intelligence XL (228-233). https://doi.org/10.1007/978-3-031-47994-6_20

Element of trust exists in every network structure of diverse fields, but suitable computational methods for evaluating the trust remain a problem since there are different definitions of trust in diverse fields where several entities interact with e... Read More about Predicting social trust from implicit feedback.

Enhancing software fault prediction with deep neural networks: An empirical analysis of error-type metrics (2023)
Conference Proceeding
Phung, K., Ogunshile, E., & Aydin, M. E. (in press). Enhancing software fault prediction with deep neural networks: An empirical analysis of error-type metrics.

In the context of software quality assurance, Software Fault Prediction (SFP) serves as a critical technique to optimise costs and efforts by classifying software modules as faulty or not, using pertinent project characteristics. Despite considerable... Read More about Enhancing software fault prediction with deep neural networks: An empirical analysis of error-type metrics.

Augmented reality as a thirdspace: Simultaneous experience of the physical and virtual (2023)
Conference Proceeding
Eagle, R. (2023). Augmented reality as a thirdspace: Simultaneous experience of the physical and virtual. In D. Villa, & F. Zuccoli (Eds.), Proceedings of the 3rd International and Interdisciplinary Conference on Images and Imagination (355-363). https://doi.org/10.1007/978-3-031-25906-7_39

With the proliferation of devices that display augmented reality (AR), now is the time for scholars and practitioners to evaluate and engage critically with emerging applications of the medium. AR mediates the way users see their bodies, hear their e... Read More about Augmented reality as a thirdspace: Simultaneous experience of the physical and virtual.

Fast and accurate evaluation of collaborative filtering recommendation algorithms (2022)
Conference Proceeding
Polatidis, N., Kapetanakis, S., Pimenidis, E., & Manolopoulos, Y. (2022). Fast and accurate evaluation of collaborative filtering recommendation algorithms. In N. Thanh Nguyen, T. Khoa Tran, U. Tukayev, T. Hong, B. Trawiński, & E. Szczerbicki (Eds.), ACIIDS 2022: Intelligent Information and Database Systems (623-634). https://doi.org/10.1007/978-3-031-21743-2_50

Collaborative filtering are recommender systems algorithms that provide personalized recommendations to users in various online environments such as movies, music, books, jokes and others. There are many such recommendation algorithms and, regarding... Read More about Fast and accurate evaluation of collaborative filtering recommendation algorithms.

Supporting patient nutrition in critical care units (2022)
Conference Proceeding
Soomro, K., Pimenidis, E., & McWilliams, C. (2022). Supporting patient nutrition in critical care units. In Engineering Applications of Neural Networks: EANN 2022: Engineering Applications of Neural Networks (128-136). https://doi.org/10.1007/978-3-031-08223-8_11

Critical Care Unit (CCU) patients often benefit from being referred to dietitians for various reasons. This can help improve recovery time, resulting in more effective utilisation of valuable resources within the NHS (National Health Service) in the... Read More about Supporting patient nutrition in critical care units.

Studying how digital luthiers choose their tools (2022)
Conference Proceeding
Renney, N., Renney, H., Mitchell, T. J., & Gaster, B. R. (2022). Studying how digital luthiers choose their tools. . https://doi.org/10.1145/3491102.3517656

Digital lutherie is a sub-domain of digital craft focused on creating digital musical instruments: high-performance devices for musical expression. It represents a nuanced and challenging area of human-computer interaction that is well established an... Read More about Studying how digital luthiers choose their tools.

HyperModels - A framework for GPU accelerated physical modelling sound synthesis (2022)
Conference Proceeding
Renney, H., Willemsen, S., Gaster, B. R., & Mitchell, T. J. (2022). HyperModels - A framework for GPU accelerated physical modelling sound synthesis. . https://doi.org/10.21428/92fbeb44.98a4210a

Physical modelling sound synthesis methods generate vast and intricate sound spaces that are navigated using meaningful parameters. Numerical based physical modelling nsynthesis methods provide authentic representations of the physics they model. Unf... Read More about HyperModels - A framework for GPU accelerated physical modelling sound synthesis.

Automatic report-based labelling of clinical EEGs for classifier training (2022)
Conference Proceeding
Western, D., Weber, T., Kandasamy, R., May, F., Taylor, S., Zhu, Y., & Canham, L. (2022). Automatic report-based labelling of clinical EEGs for classifier training. In 2021 IEEE Signal Processing in Medicine and Biology Symposium (SPMB). https://doi.org/10.1109/SPMB52430.2021.9672295

Machine learning classifiers for detection of abnormal clinical electroencephalography (EEG) signals have advanced signficantly in recent years, largely supported by the carefully curated Temple University Hospital Abnormal EEG Corpus (TUAB). Further... Read More about Automatic report-based labelling of clinical EEGs for classifier training.

Memory-constrained context-aware reasoning (2022)
Conference Proceeding
Uddin, I., Rakib, A., Ali, M., & Vinh, P. C. (2022). Memory-constrained context-aware reasoning. In P. Cong Vinh, & A. Rakib (Eds.), Context-Aware Systems and Applications (133-146). https://doi.org/10.1007/978-3-030-93179-7_11

The context-aware computing paradigm introduces environments, known as smart spaces, which can unobtrusively and proactively assist their users. These systems are currently mostly implemented on mobile platforms considering various techniques, includ... Read More about Memory-constrained context-aware reasoning.

Bespoke anywhere (2021)
Conference Proceeding
Gaster, B., & Challinor, R. (2021). Bespoke anywhere.

This paper reports on a project aimed to break away from the portability concerns of native DSP code between different platforms, thus freeing the instrument designer from the burden of porting new Digital Musical Instruments (DMIs) to different arch... Read More about Bespoke anywhere.

Automatic for the people: Crowd-driven generative scores using Manhattan and machine vision (2021)
Conference Proceeding
Nash, C. (2021). Automatic for the people: Crowd-driven generative scores using Manhattan and machine vision.

This paper details a workshop and optional public installation based on the development of situational scores that combine music notation, AI, and code to create dynamic interactive art driven by the realtime movements of objects and people in a live... Read More about Automatic for the people: Crowd-driven generative scores using Manhattan and machine vision.

Modeling diseases with Stream X Machine (2021)
Conference Proceeding
Jayatilake, S., Ogunshile, E., Aydin, M., & Phung, K. (2021). Modeling diseases with Stream X Machine. In 2021 9th International Conference in Software Engineering Research and Innovation (CONISOFT) (61-68). https://doi.org/10.1109/CONISOFT52520.2021.00020

At present the world is moving towards alternative medicine and behavioural alteration for treating, managing, and preventing chronical diseases. With the individuality of the human beings has added more complexity in a domain where very high accurac... Read More about Modeling diseases with Stream X Machine.

A novel software fault prediction approach to predict error-type proneness in the Java programs using Stream X-Machine and machine learning (2021)
Conference Proceeding
Phung, K., Ogunshile, E., & Aydin, M. (2021). A novel software fault prediction approach to predict error-type proneness in the Java programs using Stream X-Machine and machine learning. In 2021 9th International Conference in Software Engineering Research and Innovation (CONISOFT) (168-179). https://doi.org/10.1109/CONISOFT52520.2021.00032

Software fault prediction makes software quality assurance process more efficient and economic. Most of the works related to software fault prediction have mainly focused on classifying software modules as faulty or not, which does not produce suffic... Read More about A novel software fault prediction approach to predict error-type proneness in the Java programs using Stream X-Machine and machine learning.

WhiskEye: A biomimetic model of multisensory spatial memory based on sensory reconstruction (2021)
Conference Proceeding
Knowles, T. C., Stentiford, R., & Pearson, M. J. (2021). WhiskEye: A biomimetic model of multisensory spatial memory based on sensory reconstruction. In TAROS 2021: Towards Autonomous Robotic Systems (408-418). https://doi.org/10.1007/978-3-030-89177-0_43

We present WhiskEye, a visual tactile robot supporting a neurorobotic investigation of spatial memory as a multisensory reconstructive process. This article outlines the motivation for building WhiskEye; the technical details of the physical robot, a... Read More about WhiskEye: A biomimetic model of multisensory spatial memory based on sensory reconstruction.

Establishing the informational requirements for modelling open domain dialogue and prototyping a retrieval open domain dialogue system (2021)
Conference Proceeding
Meier, T., & Pimenidis, E. (2021). Establishing the informational requirements for modelling open domain dialogue and prototyping a retrieval open domain dialogue system. In N. Nguyen, L. Iliadis, I. Maglogiannis, & B. Trawiński (Eds.), Computational Collective Intelligence (655-667). https://doi.org/10.1007/978-3-030-88081-1_49

Open domain dialogue systems aim to coherently respond to users over long conversations through multiple conversational turns. Modelling open domain dialogue is challenging as both the syntactic and semantic features of language play a role in respon... Read More about Establishing the informational requirements for modelling open domain dialogue and prototyping a retrieval open domain dialogue system.