All Outputs (839)

Leveraging Deep Reinforcement Learning and Healthcare Devices for Active Travelling in Smart Cities (2024)
Journal Article
Kazmi, S. M. A., Khan, Z., Khan, A., Mazzara, M., & Khattak, A. M. (online). Leveraging Deep Reinforcement Learning and Healthcare Devices for Active Travelling in Smart Cities. IEEE Transactions on Consumer Electronics, https://doi.org/10.1109/tce.2024.3470978

Smart cities are increasingly challenged by population growth and the environmental emissions of urban transportation systems, necessitating sustainable urban planning to improve public health, environmental quality, and overall urban livability. A n... Read More about Leveraging Deep Reinforcement Learning and Healthcare Devices for Active Travelling in Smart Cities.

Differentiator- and Observer-Based Feedback Linearized Advanced Nonlinear Control Strategies for an Unmanned Aerial Vehicle System (2024)
Journal Article
Irfan, S., Zhao, L., Ullah, S., Javaid, U., & Iqbal, J. (2024). Differentiator- and Observer-Based Feedback Linearized Advanced Nonlinear Control Strategies for an Unmanned Aerial Vehicle System. Drones, 8(10), Article 527. https://doi.org/10.3390/drones8100527

This paper presents novel chattering-free robust control strategies for addressing disturbances and uncertainties in a two-degree-of-freedom (2-DOF) unmanned aerial vehicle (UAV) dynamic model, with a focus on the highly nonlinear and strongly couple... Read More about Differentiator- and Observer-Based Feedback Linearized Advanced Nonlinear Control Strategies for an Unmanned Aerial Vehicle System.

mm-CUR: A Novel Ubiquitous, Contact-free, and Location-aware Counterfeit Currency Detection in Bundles Using Millimeter-Wave Sensor (2024)
Journal Article
Niaz, F., Zhang, J., Zheng, Y., Khalid, M., & Niaz, A. (online). mm-CUR: A Novel Ubiquitous, Contact-free, and Location-aware Counterfeit Currency Detection in Bundles Using Millimeter-Wave Sensor. ACM Transactions on Sensor Networks, https://doi.org/10.1145/3694970

Target material sensing in non-invasive and ubiquitous contexts plays an important role in various applications. Recently, a few wireless sensing systems have been proposed for material identification. In this paper, we introduce mm-CUR, A Novel Ubiq... Read More about mm-CUR: A Novel Ubiquitous, Contact-free, and Location-aware Counterfeit Currency Detection in Bundles Using Millimeter-Wave Sensor.

Digital Health and Indoor Air Quality: An IoT- Driven Human-Centred Visualisation Platform for Behavioural Change and Technology Acceptance (2024)
Presentation / Conference Contribution
Kureshi, R. R., Mazumdar, S., Mishra, B. K., Li, X., & Thakker, D. (2023, December). Digital Health and Indoor Air Quality: An IoT- Driven Human-Centred Visualisation Platform for Behavioural Change and Technology Acceptance. Presented at 4th International Conference on Distributed Sensing and Intelligent Systems (ICDSIS 2023), Dubai, UAE

The detrimental effects of air pollutants on human health have prompted increasing concerns regarding indoor air quality (IAQ). The emergence of digital health interventions and citizen science initiatives has provided new avenues for raising awarene... Read More about Digital Health and Indoor Air Quality: An IoT- Driven Human-Centred Visualisation Platform for Behavioural Change and Technology Acceptance.

Measuring AI Fairness in a Continuum Maintaining Nuances: A Robustness Case Study (2024)
Journal Article
Paxton, K., Aslansefat, K., Thakker, D., & Papadopoulos, Y. (2024). Measuring AI Fairness in a Continuum Maintaining Nuances: A Robustness Case Study. IEEE Internet Computing, 28(5), 11-19. https://doi.org/10.1109/MIC.2024.3450815

As machine learning is increasingly making decisions about hiring or healthcare, we want AI to treat ethnic and socioeconomic groups fairly. Fairness is currently measured by comparing the average accuracy of reasoning across groups. We argue that im... Read More about Measuring AI Fairness in a Continuum Maintaining Nuances: A Robustness Case Study.

Devising a Responsible Framework for Air Quality Sensor Placement (2024)
Presentation / Conference Contribution
Westcarr, J., Gunturi, V. M. V., Cabaneros, S. M., Raja, R., Thakker, D., & Porter, A. (2024, July). Devising a Responsible Framework for Air Quality Sensor Placement. Presented at 2024 IEEE International Conference on Omni-layer Intelligent Systems (COINS), London, United Kingdom

A major challenge faced when developing smart, sustainable urban environments is the reduction of air pollutants that adversely impact citizens' health. The UK has implemented strategies such as clean air zones (CAZs) coupled with the use of sensor t... Read More about Devising a Responsible Framework for Air Quality Sensor Placement.

Disease progression in chronic heart failure is linear: Insights from multistate modelling (2024)
Journal Article
Kazmi, S., Kambhampati, C., Rigby, A. S., Cleland, J. G. F., Kazmi, K. S., Cuthbert, J., Pellicori, P., & Clark, A. L. (online). Disease progression in chronic heart failure is linear: Insights from multistate modelling. European journal of heart failure, https://doi.org/10.1002/ejhf.3400

Aims: Understanding the pattern of disease progression in chronic heart failure (HF) may inform patient care and healthcare system design. We used a four-state Markov model to describe the disease trajectory of patients with HF. Methods and results:... Read More about Disease progression in chronic heart failure is linear: Insights from multistate modelling.

A new class of zero-truncated counting models and its application (2024)
Journal Article
Tang, X. P., Tian, Y. Z., Wu, C. H., Wang, Y., & Mian, Z. B. (2024). A new class of zero-truncated counting models and its application. Communications in Statistics - Simulation and Computation, https://doi.org/10.1080/03610918.2024.2384561

Count data is a type of data derived from the number of times an event occurs per unit of time, and zero-truncated count data refers to count data without zero, which often appears in various fields. In this paper, a new zero-truncated Bell (ZTBell)... Read More about A new class of zero-truncated counting models and its application.

Enquiry-based learning pedagogy – Design, development and delivery of a reproducible robotics framework (2024)
Presentation / Conference Contribution
Walker, A., Diaz, K. R. V., McKie, D., & Iqbal, J. (2024, February). Enquiry-based learning pedagogy – Design, development and delivery of a reproducible robotics framework. Presented at Ninth International Congress on Information and Communication Technology (ICICT 2024), London

Hardware-inspired enquiry-based learning (EBL) is an emerging pedagogy to develop transferable engineering skills in students. This paper is aimed at unleashing the potential of this pedagogy via the multidisciplinary domain of robotics to learn the... Read More about Enquiry-based learning pedagogy – Design, development and delivery of a reproducible robotics framework.

A hybrid contextual framework to predict severity of infectious disease: COVID-19 case study (2024)
Journal Article
Azam, M. M. B., Anwaar, F., Khan, A. M., Anwar, M., Ghani, H. B. A., Eisa, T. A. E., & Abdelmaboud, A. (2024). A hybrid contextual framework to predict severity of infectious disease: COVID-19 case study. Egyptian Informatics Journal, 27, Article 100508. https://doi.org/10.1016/j.eij.2024.100508

Infectious disease is a particular type of disorder triggered by organisms and transmitted directly or indirectly from an infected one like COVID-19. The global economy and public health are immensely affected by COVID-19, a recently emerging infecti... Read More about A hybrid contextual framework to predict severity of infectious disease: COVID-19 case study.

Global Knowledge, Local Impact: Domain Adaptation and Classification for Obesity in the UAE (2024)
Presentation / Conference Contribution
Raza, M., Khattak, A., Abbas, W., & Khan, A. (2024, June). Global Knowledge, Local Impact: Domain Adaptation and Classification for Obesity in the UAE. Presented at 37th IEEE International Symposium on Computer-Based Medical Systems (CBMS), Guadalajara, Mexico

Obesity, a global public health concern, is escalating rapidly, especially in the Middle East, with the United Arab Emirates (UAE) witnessing one of the highest prevalence rates among adults and children. This multifactorial health issue is influence... Read More about Global Knowledge, Local Impact: Domain Adaptation and Classification for Obesity in the UAE.

LLM-guided Instance-level Image Manipulation with Diffusion U-Net Cross-Attention Maps (2024)
Presentation / Conference Contribution
Palaev, A., Khan, A., & Kazmi, A. (2024, November). LLM-guided Instance-level Image Manipulation with Diffusion U-Net Cross-Attention Maps. Paper presented at The 35th British Machine Vision Conference, Glasgow

The advancement of text-to-image synthesis has introduced powerful generative models capable of creating realistic images from textual prompts. However, precise control over image attributes remains challenging, especially at the instance level. Whil... Read More about LLM-guided Instance-level Image Manipulation with Diffusion U-Net Cross-Attention Maps.

Spatial Spectral Transformer with Conditional Position Encoding for Hyperspectral Image Classification (2024)
Journal Article
Ahmad, M., Usama, M., Khan, A. M., Distefano, S., Altuwaijri, H. A., & Mazzara, M. (2024). Spatial Spectral Transformer with Conditional Position Encoding for Hyperspectral Image Classification. IEEE Geoscience and Remote Sensing Letters, 1-1. https://doi.org/10.1109/lgrs.2024.3431188

In Transformer-based Hyperspectral Image Classification (HSIC), predefined positional encodings (PEs) are crucial for capturing the order of each input token. However, their typical representation as fixed-dimension learnable vectors makes it challen... Read More about Spatial Spectral Transformer with Conditional Position Encoding for Hyperspectral Image Classification.

User Engagement Triggers in Social Media Discourse on Biodiversity Conservation (2024)
Journal Article
Dethlefs, N., & Cuayáhuitl, H. (online). User Engagement Triggers in Social Media Discourse on Biodiversity Conservation. ACM Transactions on Social Computing, https://doi.org/10.1145/3662685

Studies in digital conservation have increasingly used social media in recent years as a source of data to understand the interactions between humans and nature, model and monitor biodiversity, and analyse online discourse about the conservation of s... Read More about User Engagement Triggers in Social Media Discourse on Biodiversity Conservation.

An empirical analysis of agricultural and rural carbon emissions under the background of rural revitalization strategy–based on machine learning algorithm (2024)
Journal Article
Niu, X. Y., Tian, Y. Z., Tang, M. L., & Mian, Z. B. (2024). An empirical analysis of agricultural and rural carbon emissions under the background of rural revitalization strategy–based on machine learning algorithm. Air Quality, Atmosphere and Health, https://doi.org/10.1007/s11869-024-01606-2

Agricultural and rural carbon (ARC) emissions are a major source of greenhouse gas emissions in China and have profound implications for implementing the rural revitalization strategy. This study takes Shandong Province, a leading agricultural provin... Read More about An empirical analysis of agricultural and rural carbon emissions under the background of rural revitalization strategy–based on machine learning algorithm.

Artificial Intelligence in Education: An automatic Rule-Based Chatbot to generate guidance from lecture recordings (2024)
Journal Article
Hing, W., Gordon, N., & Al Jaber, T. (2024). Artificial Intelligence in Education: An automatic Rule-Based Chatbot to generate guidance from lecture recordings. Acta Scientific Computer Sciences, 6(7), 64-74

In a new era of educational and research-based chatbots, implementing personalised interactive learning resources is critical in enhancing students' academic experiences. Whilst general purpose chatbots are now available with a range of platforms, th... Read More about Artificial Intelligence in Education: An automatic Rule-Based Chatbot to generate guidance from lecture recordings.

Challenges Faced by International Students in Understanding British Accents and Their Mitigation Strategies—A Mixed Methods Study (2024)
Journal Article
Vasquez Diaz, K. R., & Iqbal, J. (2024). Challenges Faced by International Students in Understanding British Accents and Their Mitigation Strategies—A Mixed Methods Study. Education Sciences, 14(7), Article 784. https://doi.org/10.3390/educsci14070784

The massive relocation of international students calls for a thorough investigation of diverse difficulties faced by them, among which language-related barriers are reported to have serious consequences. The main goal of this research is to investiga... Read More about Challenges Faced by International Students in Understanding British Accents and Their Mitigation Strategies—A Mixed Methods Study.

AI enabled: a novel IoT-based fake currency detection using millimeter wave (mmWave) sensor (2024)
Journal Article
Niaz, F., Zhang, J., Khalid, M., Qureshi, K. N., Zheng, Y., Younas, M., & Imran, N. (in press). AI enabled: a novel IoT-based fake currency detection using millimeter wave (mmWave) sensor. Computing, https://doi.org/10.1007/s00607-024-01300-2

In recent years, the significance of millimeter wave sensors has achieved a paramount role, especially in the non-invasive and ubiquitous analysis of various materials and objects. This paper introduces a novel IoT-based fake currency detection using... Read More about AI enabled: a novel IoT-based fake currency detection using millimeter wave (mmWave) sensor.

Fuzzy-Augmented Model Reference Adaptive PID Control Law Design for Robust Voltage Regulation in DC–DC Buck Converters (2024)
Journal Article
Saleem, O., Rasheed Ahmad, K., & Iqbal, J. (2024). Fuzzy-Augmented Model Reference Adaptive PID Control Law Design for Robust Voltage Regulation in DC–DC Buck Converters. Mathematics, 12(12), Article 1893. https://doi.org/10.3390/math12121893

This paper presents a novel fuzzy-augmented model reference adaptive voltage regulation strategy for the DC–DC buck converters to enhance their resilience against random input variations and load-step transients. The ubiquitous proportional-integral-... Read More about Fuzzy-Augmented Model Reference Adaptive PID Control Law Design for Robust Voltage Regulation in DC–DC Buck Converters.

Meta-Heuristic Optimization of Sliding Mode Control—Application to Quadrotor-Based Inspection of Solar Panels (2024)
Presentation / Conference Contribution
Rezoug, A., Bouderbala, F.-Z., Baizid, K., & Iqbal, J. (2022, December). Meta-Heuristic Optimization of Sliding Mode Control—Application to Quadrotor-Based Inspection of Solar Panels. Presented at 1st International Conference on Advanced Renewable Energy Systems (ICARES 2022), Tipaza, Algeria

In this paper, inspection of solar energy system is addressed using a quadrotor unmanned aerial vehicle (UAV) system. The accurate positioning of the system on the solar panel requires a robust controller to precisely address the fault while ensuring... Read More about Meta-Heuristic Optimization of Sliding Mode Control—Application to Quadrotor-Based Inspection of Solar Panels.