Outputs (61)

A Fuzzy-Immune-Regulated Single-Neuron Proportional–Integral–Derivative Control System for Robust Trajectory Tracking in a Lawn-Mowing Robot (2024)
Journal Article
Saleem, O., Hamza, A., & Iqbal, J. (2024). A Fuzzy-Immune-Regulated Single-Neuron Proportional–Integral–Derivative Control System for Robust Trajectory Tracking in a Lawn-Mowing Robot. Computers, 13(11), Article 301. https://doi.org/10.3390/computers13110301

This paper presents the constitution of a computationally intelligent self-adaptive steering controller for a lawn-mowing robot to yield robust trajectory tracking and disturbance rejection behavior. The conventional fixed-gain proportional–integral–... Read More about A Fuzzy-Immune-Regulated Single-Neuron Proportional–Integral–Derivative Control System for Robust Trajectory Tracking in a Lawn-Mowing Robot.

A Secure User Anonymity-Preserving Biometrics and PUFs-Based Multi-Server Authentication Scheme With Key Agreement in 5G Networks (2024)
Journal Article
Xu, D., Bian, W., Li, Q., Xie, D., Zhao, J., & Hu, Y. (online). A Secure User Anonymity-Preserving Biometrics and PUFs-Based Multi-Server Authentication Scheme With Key Agreement in 5G Networks. IEEE internet of things journal, https://doi.org/10.1109/JIOT.2024.3486005

The 5G networks can provide high data rates, ultra-low latency and huge network capacity. In 5G networks environment, the popularity of the Internet of Things (IoT) has led to a rapid increase in the amount of data. Multi-server distributed cloud com... Read More about A Secure User Anonymity-Preserving Biometrics and PUFs-Based Multi-Server Authentication Scheme With Key Agreement in 5G Networks.

LLM Based Cross Modality Retrieval to Improve Recommendation Performance (2024)
Presentation / Conference Contribution
Anwaar, F., Khan, A. M., & Khalid, M. (2024, August). LLM Based Cross Modality Retrieval to Improve Recommendation Performance. Presented at 2024 29th International Conference on Automation and Computing (ICAC), Sunderland, UK

The metadata of items and users play an important role in improving the decision-making process in the Recom-mender System. In recent times, web scraping-based techniques have been widely utilized to extract explicit user and item meta-data from diff... Read More about LLM Based Cross Modality Retrieval to Improve Recommendation Performance.

Genetic algorithm inspired optimal integrated nonlinear control technique for an electric power steering system (2024)
Journal Article
Nguyen, T. A., & Iqbal, J. (2024). Genetic algorithm inspired optimal integrated nonlinear control technique for an electric power steering system. Journal of the Brazilian Society of Mechanical Sciences and Engineering, 46(11), Article 661. https://doi.org/10.1007/s40430-024-05255-5

This paper introduces an optimal integrated control method for automotive steering systems called Backstepping Proportional Integral Derivative-Genetic Algorithm (BSPID-GA). The proposed algorithm combines Back Stepping Control (BSC) and Proportional... Read More about Genetic algorithm inspired optimal integrated nonlinear control technique for an electric power steering system.

Improving Generalization for Hyperspectral Image Classification: The Impact of Disjoint Sampling on Deep Models (2024)
Journal Article
Ahmad, M., Mazzara, M., Distefano, S., Khan, A. M., & Altuwaijri, H. A. (2024). Improving Generalization for Hyperspectral Image Classification: The Impact of Disjoint Sampling on Deep Models. Computers, Materials & Continua, 81(1), 503-532. https://doi.org/10.32604/cmc.2024.056318

Disjoint sampling is critical for rigorous and unbiased evaluation of state-of-the-art (SOTA) models e.g., Attention Graph and Vision Transformer. When training, validation, and test sets overlap or share data, it introduces a bias that inflates perf... Read More about Improving Generalization for Hyperspectral Image Classification: The Impact of Disjoint Sampling on Deep Models.

Andromeda: A model-connected framework for safety assessment and assurance (2024)
Journal Article
Retouniotis, A., Papadopoulos, Y., & Sorokos, I. (2025). Andromeda: A model-connected framework for safety assessment and assurance. Journal of Systems and Software, 220, Article 112256. https://doi.org/10.1016/j.jss.2024.112256

Safety is a key factor in the development of critical systems, encompassing both conventional types, such as aircraft, and modern technologies, such as autonomous vehicles. Failures during their operation can be potentially far-reaching and impact pe... Read More about Andromeda: A model-connected framework for safety assessment and assurance.

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. (2024). 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.