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All Outputs (204)

MicroMaps: Ontology-driven Semantic Geospatial Data Fusion Approach for IoT Integration and Decision Making in Smart Cities (2025)
Presentation / Conference Contribution
Rayis, A., Ortolani, M., David, R.-M., Hirschi, R., & Misirli, G. (2025, August). MicroMaps: Ontology-driven Semantic Geospatial Data Fusion Approach for IoT Integration and Decision Making in Smart Cities. Presented at 2025 the 9th International Conference on Cloud, Big Data and Communication Systems (ICCBDCS 2025), Manchester

Smart cities generate large amounts of Internet of
Things data from diverse sources, often presented in varying
formats and with inconsistent quality, complicating effective data
management and interoperability. Despite recent advancements
relate... Read More about MicroMaps: Ontology-driven Semantic Geospatial Data Fusion Approach for IoT Integration and Decision Making in Smart Cities.

Deep Learning Based Smart Bin for Efficient Sorting of Recyclable, Non-Recyclable, and Compostable Materials (2025)
Presentation / Conference Contribution
Ahmed, M., Ahamed, M. F., Islam, S. M., Dipa, P. R., Debnath, R., & Shariar Sarker, M. N. (2024, December). Deep Learning Based Smart Bin for Efficient Sorting of Recyclable, Non-Recyclable, and Compostable Materials. Presented at 2024 27th International Conference on Computer and Information Technology (ICCIT), Cox's Bazar, Bangladesh

A significant amount of waste is produced every day from urban settings such as homes, offices, residential areas, and basically from our daily activities. Much of such waste remains unutilized due to inefficient sorting practices, which eventually r... Read More about Deep Learning Based Smart Bin for Efficient Sorting of Recyclable, Non-Recyclable, and Compostable Materials.

Towards Designs for Virtual Interconnected Curation Spaces of Heritage Artefacts, Experiences and Histories (2025)
Presentation / Conference Contribution
Rhodes, R., Woolley, S. I., & White, D. (2024, July). Towards Designs for Virtual Interconnected Curation Spaces of Heritage Artefacts, Experiences and Histories. Presented at BCS HCI '24: Proceedings of the 37th International BCS Human-Computer Interaction Conference, University of Central Lancashire (UCLan), UK

Where immersive museum and digital heritage experiences exist, they are often only available for limited project timespans and they do not generally connect to other similar experiences and artefacts, nor connect to physical museums or heritage locat... Read More about Towards Designs for Virtual Interconnected Curation Spaces of Heritage Artefacts, Experiences and Histories.

Interpretative Attention Networks for Structural Component Recognition (2024)
Presentation / Conference Contribution
Uniyal, A., Mandal, B., Puhan, N. B., & Bera, P. Interpretative Attention Networks for Structural Component Recognition. Presented at 27th International Conference on Pattern Recognition, Kolkata, India

Bridges are essential for enabling movement during environmental disasters and serve as crucial links for rescue and aid delivery. Effective bridge inspection and maintenance are more critical than ever due to increasing severity and frequency of env... Read More about Interpretative Attention Networks for Structural Component Recognition.

An Ensemble Modelling of Feature Engineering and Predictions for Enhanced Fake News Detection (2024)
Presentation / Conference Contribution
Asowo, P., Lal, S., & Ani, U. (2024, December). An Ensemble Modelling of Feature Engineering and Predictions for Enhanced Fake News Detection. Presented at AI-2024 Forty-fourth SGAI International Conference on Artificial Intelligence, CAMBRIDGE, ENGLAND

The threat of fake news jeopardizing the credibility of online
news platforms, particularly on social media, underscores the need for innovative solutions. This paper proposes a creative engine for detecting fake news, leveraging advanced machine le... Read More about An Ensemble Modelling of Feature Engineering and Predictions for Enhanced Fake News Detection.

Evaluating the Performance Resilience of Serverless Applications using Chaos Engineering (2024)
Presentation / Conference Contribution
Zayed, A., & Al-Said Ahmad, A. (2024, July). Evaluating the Performance Resilience of Serverless Applications using Chaos Engineering. Presented at 24th International Conference on Software Quality, Reliability, and Security (QRS), Cambridge, United Kingdom

This study explores the use of chaos engineering in evaluating the performance and resilience of serverless applications, which are built as complex distributed systems subject to different types of failures and errors. By intentionally injecting con... Read More about Evaluating the Performance Resilience of Serverless Applications using Chaos Engineering.

Grid LSTM based Attention Modelling for Traffic Flow Prediction (2024)
Presentation / Conference Contribution
Biju, R., Goparaju, S. U., Gangadharan, D., & Mandal, B. (2024, June). Grid LSTM based Attention Modelling for Traffic Flow Prediction. Presented at 2024 IEEE 99th Vehicular Technology Conference (VTC2024-Spring), Singapore

Traffic flow prediction is an important task that can directly impact the control of traffic flow positively and improve the overall traffic throughput. Although a large number of studies have been performed to improve traffic flow prediction, there... Read More about Grid LSTM based Attention Modelling for Traffic Flow Prediction.

Android Malware Detection System using Machine Learning (2024)
Presentation / Conference Contribution
Kaur, A., Lal, S., Goel, S., Pandey, M., & Agarwal, A. (2024, August). Android Malware Detection System using Machine Learning. Presented at The International Conference on Contemporary Computing (IC3), India

Detecting Android malware is imperative for safeguarding user privacy, securing data, and preserving device performance. Consequently,
numerous studies have underscored the complexities associated with Android malware detection, prompting a multidim... Read More about Android Malware Detection System using Machine Learning.

Unified Deep Ensemble Architecture for Multiple Classification Tasks (2024)
Presentation / Conference Contribution
Mistry, K. A. J., & Mandal, B. (2024, August). Unified Deep Ensemble Architecture for Multiple Classification Tasks. Presented at 2024 Intelligent Systems Conference (IntelliSys), Amsterdam, The Netherlands

Banks face regular challenges in making decisions for ever increasing need for bank loans. Most banks use applicant’s financial situations, their past history, affordability checks, credit score and risk assessment, which are time consuming, challeng... Read More about Unified Deep Ensemble Architecture for Multiple Classification Tasks.

Wearables, Healthcare-Computer Interaction and the Internet of Obscure Medical Things (2024)
Presentation / Conference Contribution
Khattak, K. A., Woolley, S. I., & Collins, T. (2024, July). Wearables, Healthcare-Computer Interaction and the Internet of Obscure Medical Things. Presented at 37th International BCS Human-Computer Interaction Conference, Preston, UK

In recent years, wearable computers, in the form of wrist-worn trackers and smartwatches, have transitioned apace from the well-being market into the set of 'Internet of Medical Things' (IoMTs) used in clinical research and healthcare. Despite concer... Read More about Wearables, Healthcare-Computer Interaction and the Internet of Obscure Medical Things.

“Should I Throw Away My Old iPad?” - Reconsidering Usefulness in Obsolete Devices (2024)
Presentation / Conference Contribution
Goodwin, C., & Woolley, S. (2023, August). “Should I Throw Away My Old iPad?” - Reconsidering Usefulness in Obsolete Devices. Presented at INTERACT 2023 IFIP TC 13 Workshops, York, England, UK

Device obsolescence contributes to the rising levels of annual e-waste. The research presented in this extended workshop paper summarises the findings of two studies conducted in 2021 and 2022 that highlighted the difficulties faced by consumers in d... Read More about “Should I Throw Away My Old iPad?” - Reconsidering Usefulness in Obsolete Devices.

Elastic waves in periodically anisotropic heterogeneous media: bridge the gap between rigorous and phenomenological approaches (2024)
Presentation / Conference Contribution
Andrianov, I., Danishevskyy, V., Kaplunov, J., & Kirichek, Y. (2023, July). Elastic waves in periodically anisotropic heterogeneous media: bridge the gap between rigorous and phenomenological approaches. Presented at XII INTERNATIONAL CONFERENCE ON STRUCTURAL DYNAMICS (EURODYN 2023), Delft, Netherlands

Despite the growing capacity of computer codes, analytical solutions are still of great interest. As a rule, they are based on certain asymptotic approximations. In our work, we use a two-scale asymptotic procedure. Anti-plane shear waves in a layere... Read More about Elastic waves in periodically anisotropic heterogeneous media: bridge the gap between rigorous and phenomenological approaches.

The Content Quality of Crowdsourced Knowledge on Stack Overflow- A Systematic Mapping Study (2024)
Presentation / Conference Contribution
Shahrour, G., De Quincey, E., & Lal, S. (2023, November). The Content Quality of Crowdsourced Knowledge on Stack Overflow- A Systematic Mapping Study. Presented at ASONAM '23: Proceedings of the 2023 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, Kusadasi, Turkiye

Community Question Answering (CQA) forums such as Stack Overflow (SO) are a form of crowdsourced knowledge for software engineers who seek solutions to development and programming challenges. While such a forum provides valuable support to engineers,... Read More about The Content Quality of Crowdsourced Knowledge on Stack Overflow- A Systematic Mapping Study.

Taxonomy of Emerging Security Risks in Digital Railway (2024)
Presentation / Conference Contribution
Al-Mhiqani, M., Ani, U., Watson, J., & He, H. (2023, July). Taxonomy of Emerging Security Risks in Digital Railway. Presented at CYBER SCIENCE 2023, University of Aalborg, Copenhagen, Denmark

The railway industry has embraced digitisation and interconnectivity by introducing Information and Communication Technologies into traditional operational technology infrastructure. This convergence has brought numerous advantages, including improve... Read More about Taxonomy of Emerging Security Risks in Digital Railway.

VidSearch: Privacy-by-Design Video Search and Retrieval System for Large-Scale CCTV Data (2023)
Presentation / Conference Contribution
Tahir, M., Qiao, Y., Kanwal, N., Lee, B., & Asghar, M. N. (2023, December). VidSearch: Privacy-by-Design Video Search and Retrieval System for Large-Scale CCTV Data. Presented at 2023 International Conference on Machine Learning and Applications (ICMLA), Jacksonville, FL, USA

The surge in surveillance camera deployment in the era of Big Data and the Internet of Things (IoT) has emphasized the paramount importance of safeguarding the privacy of individuals, objects, and locations they record. Therefore, this paper proposes... Read More about VidSearch: Privacy-by-Design Video Search and Retrieval System for Large-Scale CCTV Data.

Preface (2023)
Presentation / Conference Contribution
Bell, P. C., Potapov, I., Schmitz, S., & Totzke, P. Preface

Deep Neural Networks Based Multiclass Animal Detection and Classification in Drone Imagery (2023)
Presentation / Conference Contribution
Chen, C., Edirisinghe, E., Leonce, A., Simkins, G., Khafaga, T., Sher Shah, M., & Yahya, U. (2023, October). Deep Neural Networks Based Multiclass Animal Detection and Classification in Drone Imagery. Presented at 2023 International Symposium on Networks, Computers and Communications (ISNCC), Doha, Qatar

There is a growing interest among the research community in the search for possible technology-driven strategies for the conservation of the much-needed, historically rich and culturally important, desert life. In this work, we investigate the use of... Read More about Deep Neural Networks Based Multiclass Animal Detection and Classification in Drone Imagery.

Deep Neural Network Based Automatic Litter Detection in Desert Areas Using Unmanned Aerial Vehicle Imagery (2023)
Presentation / Conference Contribution
Wang, G., Leonce, A., Hacid, H., & Edirisinghe, E. (2023, October). Deep Neural Network Based Automatic Litter Detection in Desert Areas Using Unmanned Aerial Vehicle Imagery. Presented at 2023 International Symposium on Networks, Computers and Communications (ISNCC), Doha, Qatar

The United Arab Emirates (UAE) values its relationship with the desert, considering it a crucial part of its heritage and culture. However, the desert faces environmental challenges due to the improper disposal of garbage by visitors and the dumping... Read More about Deep Neural Network Based Automatic Litter Detection in Desert Areas Using Unmanned Aerial Vehicle Imagery.

Virtual and Augmented Reality Interfaces for 3D Mesopotamian Environments and Artefacts – A Survey (2023)
Presentation / Conference Contribution
Rhodes, R., & Woolley, S. (2023, August). Virtual and Augmented Reality Interfaces for 3D Mesopotamian Environments and Artefacts – A Survey. Presented at 36th International BCS Human-Computer Interaction Conference, University of York, UK

This paper surveys twenty years of published works and implementations of virtual reality (VR), augmented
reality (AR) and 3D repositories relevant to ancient Mesopotamia. Results are sorted according to type,
relevance to cuneiform, evaluation, an... Read More about Virtual and Augmented Reality Interfaces for 3D Mesopotamian Environments and Artefacts – A Survey.