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All Outputs (143)

An Ensemble Modelling of Feature Engineering and Predictions for Enhanced Fake News Detection (2025)
Conference Proceeding
Asowo, P., Lal, S., & Ani, U. (2025). An Ensemble Modelling of Feature Engineering and Predictions for Enhanced Fake News Detection. . https://doi.org/10.1007/978-3-031-77918-3_16

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)
Conference Proceeding
Zayed, A., & Al-Said Ahmad, A. (2024). Evaluating the Performance Resilience of Serverless Applications using Chaos Engineering. . https://doi.org/10.1109/qrs-c63300.2024.00172

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.

Towards Designs for Virtual Interconnected Curation Spaces of Heritage Artefacts, Experiences and Histories (2024)
Conference Proceeding
Rhodes, R., Woolley, S. I., & White, D. (in press). Towards Designs for Virtual Interconnected Curation Spaces of Heritage Artefacts, Experiences and Histories.

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.

Android Malware Detection System using Machine Learning (2024)
Conference Proceeding
Kaur, A., Lal, S., Goel, S., Pandey, M., & Agarwal, A. (2024). Android Malware Detection System using Machine Learning. . https://doi.org/10.1145/3675888.3676049

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.

Wearables, Healthcare-Computer Interaction and the Internet of Obscure Medical Things (2024)
Conference Proceeding
Khattak, K. A., Woolley, S. I., & Collins, T. (2024). Wearables, Healthcare-Computer Interaction and the Internet of Obscure Medical Things.

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.

Unified Deep Ensemble Architecture for Multiple Classification Tasks (2024)
Conference Proceeding
Mistry, K. A. J., & Mandal, B. (2024). Unified Deep Ensemble Architecture for Multiple Classification Tasks. In Intelligent Systems and Applications (544-557). https://doi.org/10.1007/978-3-031-66329-1_35

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.

“Should I Throw Away My Old iPad?” - Reconsidering Usefulness in Obsolete Devices (2024)
Conference Proceeding
Goodwin, C., & Woolley, S. (2024). “Should I Throw Away My Old iPad?” - Reconsidering Usefulness in Obsolete Devices. In Design for Equality and Justice (332-339). https://doi.org/10.1007/978-3-031-61688-4_32

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.

Grid LSTM based Attention Modelling for Traffic Flow Prediction (2024)
Conference Proceeding
Biju, R., Goparaju, S. U., Gangadharan, D., & Mandal, B. (2024). Grid LSTM based Attention Modelling for Traffic Flow Prediction. . https://doi.org/10.1109/vtc2024-spring62846.2024.10683344

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.

Elastic waves in periodically anisotropic heterogeneous media: bridge the gap between rigorous and phenomenological approaches (2024)
Conference Proceeding
Andrianov, I., Danishevskyy, V., Kaplunov, J., & Kirichek, Y. (2024). Elastic waves in periodically anisotropic heterogeneous media: bridge the gap between rigorous and phenomenological approaches. . https://doi.org/10.1088/1742-6596/2647/25/252034

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.

VidSearch: Privacy-by-Design Video Search and Retrieval System for Large-Scale CCTV Data (2023)
Conference Proceeding
Tahir, M., Qiao, Y., Kanwal, N., Lee, B., & Asghar, M. N. (2023). VidSearch: Privacy-by-Design Video Search and Retrieval System for Large-Scale CCTV Data. . https://doi.org/10.1109/icmla58977.2023.00329

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.

The Content Quality of Crowdsourced Knowledge on Stack Overflow- A Systematic Mapping Study (2023)
Conference Proceeding
Shahrour, G., Quincey, E. D., & Lal, S. (2023). The Content Quality of Crowdsourced Knowledge on Stack Overflow- A Systematic Mapping Study. . https://doi.org/10.1145/3625007.3627729

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.

Deep Neural Networks Based Multiclass Animal Detection and Classification in Drone Imagery (2023)
Conference Proceeding
Chen, C., Edirisinghe, E., Leonce, A., Simkins, G., Khafaga, T., Sher Shah, M., & Yahya, U. (2023). Deep Neural Networks Based Multiclass Animal Detection and Classification in Drone Imagery. In 2023 International Symposium on Networks, Computers and Communications (ISNCC). https://doi.org/10.1109/isncc58260.2023.10323685

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)
Conference Proceeding
Wang, G., Leonce, A., Hacid, H., & Edirisinghe, E. (2023). Deep Neural Network Based Automatic Litter Detection in Desert Areas Using Unmanned Aerial Vehicle Imagery. In 2023 International Symposium on Networks, Computers and Communications (ISNCC). https://doi.org/10.1109/isncc58260.2023.10323960

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)
Conference Proceeding
Rhodes, R., & Woolley, S. (2023). Virtual and Augmented Reality Interfaces for 3D Mesopotamian Environments and Artefacts – A Survey. . https://doi.org/10.14236/ewic/BCSHCI2023.8

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.

Quantifying Device Usefulness - How Useful is an Obsolete Device? (2023)
Conference Proceeding
Goodwin, C., Woolley, S., de Quincey, E., & Collins, T. (2023). Quantifying Device Usefulness - How Useful is an Obsolete Device?. In Human-Computer Interaction – INTERACT 2023 (90-99). https://doi.org/10.1007/978-3-031-42293-5_8

Obsolete devices add to the rising levels of electronic waste, a major environmental concern, and a contributing factor to climate change. In recent years, device manufacturers have established environmental commitments and launched initiatives such... Read More about Quantifying Device Usefulness - How Useful is an Obsolete Device?.

Visual Attention Assisted Games (2023)
Conference Proceeding
Mandal, B., Puhan, N. B., & Homi Anil, V. (2023). Visual Attention Assisted Games. In 2023 IEEE Conference on Games (CoG). https://doi.org/10.1109/cog57401.2023.10333186

In this work, we propose a committee of attention models developed for improving the deep reinforcement learning frequently used for games. The game environment is manifested with spatial and temporal attention mechanisms so as to focus on important... Read More about Visual Attention Assisted Games.

Optimization and Performance Evaluation of Hybrid Deep Learning Models for Traffic Flow Prediction (2023)
Conference Proceeding
Goparaju, S. U., Biju, R., M, P., MC, B., Gangadharan, D., Mandal, B., & C, P. (2023). Optimization and Performance Evaluation of Hybrid Deep Learning Models for Traffic Flow Prediction. . https://doi.org/10.1109/vtc2023-spring57618.2023.10200600

Traffic flow prediction has been regarded as a critical problem in intelligent transportation systems. An accurate prediction can help mitigate congestion and other societal problems while facilitating safer, cost and time-efficient travel. However,... Read More about Optimization and Performance Evaluation of Hybrid Deep Learning Models for Traffic Flow Prediction.

A Restricted Parametrized Model for Interval-Valued Regression (2023)
Conference Proceeding
Ying, J., Kabir, S., & Wagner, C. (2023). A Restricted Parametrized Model for Interval-Valued Regression. . https://doi.org/10.1109/fuzz52849.2023.10309686

This paper explores the parameter generation of the existing ‘Parametrized Model’ (PM) as the state-of-the-art linear interval-valued regression model, highlighting that its strong performance may arise from unexpected behavior. Focusing on the appro... Read More about A Restricted Parametrized Model for Interval-Valued Regression.