All Outputs (839)

Second order sliding mode control with proportional integral observer for wing rock (2025)
Journal Article
Mahmood, A., & Iqbal, J. (2025). Second order sliding mode control with proportional integral observer for wing rock. Systems Science and Control Engineering, 13(1), Article 245224779. https://doi.org/10.1080/21642583.2025.2460427

In this study, a reduced-order fast proportional integral (PI) observer with a fast convergence function based on the equivalent control notion is developed to estimate the side slip angle β. An unknown state can be discovered by forcing the PI term... Read More about Second order sliding mode control with proportional integral observer for wing rock.

Multi-head spatial-spectral mamba for hyperspectral image classification (2025)
Journal Article
Ahmad, A., Butt, M. H. F., Usama, M., Altuwaijri, H. A., Mazzara, M., Distefano, S., & Khan, A. M. (2025). Multi-head spatial-spectral mamba for hyperspectral image classification. Remote Sensing Letters, 16(4), 15-29. https://doi.org/10.1080/2150704X.2025.2461330

Spatial-Spectral Mamba (SSM) improves computational efficiency and captures long-range dependencies, addressing the limitations of transformers. However, traditional Mamba models often overlook the rich spectral information in hyperspectral images (H... Read More about Multi-head spatial-spectral mamba for hyperspectral image classification.

Air quality forecasting and rating based on machine learning algorithm and cumulative logit model: an empirical study for Lanzhou city of China (2025)
Journal Article
Xu, T., Tian, Y., Cai, X., Wu, C., & Mian, Z. (2025). Air quality forecasting and rating based on machine learning algorithm and cumulative logit model: an empirical study for Lanzhou city of China. Environment, Development and Sustainability, https://doi.org/10.1007/s10668-024-05792-y

With the quick development of society and industry, air quality has become a grim and global environmental concern. Predicting and rating air quality for many cities remains a significant challenge. Consequently, machine learning algorithms have garn... Read More about Air quality forecasting and rating based on machine learning algorithm and cumulative logit model: an empirical study for Lanzhou city of China.

Dual FOPID-neural network controller based on fast grey wolf optimizer: application to two-inputs two-outputs helicopter (2025)
Journal Article
Rezoug, A., Iqbal, J., & Nemra, A. (2025). Dual FOPID-neural network controller based on fast grey wolf optimizer: application to two-inputs two-outputs helicopter. Systems Science and Control Engineering, 13(1), Article 2449156. https://doi.org/10.1080/21642583.2024.2449156

This research introduces a novel dual Fast Grey Wolf Optimizer (FGWO) combined with Radial Basis Function Neural Networks (RBFNN) for a Fractional-Order PID (FOPID) controller applied to a helicopter simulator. The proposed FGWO improves the standard... Read More about Dual FOPID-neural network controller based on fast grey wolf optimizer: application to two-inputs two-outputs helicopter.

mmFruit: A Contactless and Non-Destructive Approach for Fine-Grained Fruit Moisture Sensing Using Millimeter-Wave Technology (2024)
Journal Article
Niaz, F., Zhang, J., Khalid, M., Younas, M., & Niaz, A. (online). mmFruit: A Contactless and Non-Destructive Approach for Fine-Grained Fruit Moisture Sensing Using Millimeter-Wave Technology. IEEE Transactions on Mobile Computing (TMC), https://doi.org/10.1109/TMC.2024.3520914

Wireless sensing offers a promising approach for non-destructive and contactless identification of the moisture content in fruits. Traditional methods assess fruit quality based on external features such as color, shape, size, and texture. However, f... Read More about mmFruit: A Contactless and Non-Destructive Approach for Fine-Grained Fruit Moisture Sensing Using Millimeter-Wave Technology.

Teaching and Assessing at Scale: The Use of Objective Rubrics and Structured Feedback Teaching and Assessing at Scale: The Use of Objective Rubrics and Structured Feedback (2024)
Journal Article
Grey, S., & Gordon, N. (2024). Teaching and Assessing at Scale: The Use of Objective Rubrics and Structured Feedback Teaching and Assessing at Scale: The Use of Objective Rubrics and Structured Feedback. New Directions in the Teaching of Physical Sciences, 19(1), 1-9. https://doi.org/10.29311/ndtns.vi19.4103

It is widely recognised that feedback is an important part of learning: effective feedback should result in a meaningful change in student behaviour (Morris et al., 2021). However, individual feedback takes time to produce, and for large cohorts-typi... Read More about Teaching and Assessing at Scale: The Use of Objective Rubrics and Structured Feedback Teaching and Assessing at Scale: The Use of Objective Rubrics and Structured Feedback.

HFL-GAN: scalable hierarchical federated learning GAN for high quantity heterogeneous clients (2024)
Journal Article
Petch, L., Moustafa, A., Ma, X., & Yasser, M. (2025). HFL-GAN: scalable hierarchical federated learning GAN for high quantity heterogeneous clients. Applied Intelligence, 55(2), Article 170. https://doi.org/10.1007/s10489-024-05924-x

This paper introduces a novel approach for training generative adversarial networks using federated machine learning. Generative adversarial networks have gained plenty of attention in the research community especially with their abilities to produce... Read More about HFL-GAN: scalable hierarchical federated learning GAN for high quantity heterogeneous clients.

Social Media Data: Challenges, Mitigation Strategies, and Opportunities for Disaster Management (2024)
Presentation / Conference Contribution
Abid, S., Mishra, B. K., Younis, U., Thakker, D., & Mishra, N. (2024, December). Social Media Data: Challenges, Mitigation Strategies, and Opportunities for Disaster Management. Presented at 2024 International Conference on Frontiers of Information Technology, FIT 2024, Islamabad, Pakistan

For disaster management, the accurate and timely availability of factual information is crucial for effective decision-making and response. Traditional communication channels are either costly or do not provide real-time data. Here comes the role of... Read More about Social Media Data: Challenges, Mitigation Strategies, and Opportunities for Disaster Management.

Tailored Risk Assessment and Forecasting in Intermittent Claudication: A Proof of Concept Decision Support Tool (2024)
Presentation / Conference Contribution
Ravindhran, B., Prosser, J., Lim, A., Mishra, B., Lathan, R., Hitchman, L., Smith, G., Carradice, D., Thakker, D., Pymer, S., & Chetter, I. (2024, June). Tailored Risk Assessment and Forecasting in Intermittent Claudication: A Proof of Concept Decision Support Tool. Presented at The European Society for Vascular Surgery Translational Spring Meeting 2024, Stockholm, Sweden

Machine learning and deep learning prediction models for time-series: a comparative analytical study for the use case of the UK short-term electricity price prediction (2024)
Journal Article
Mishra, B. K., Preniqi, V., Thakker, D., & Feigl, E. (2024). Machine learning and deep learning prediction models for time-series: a comparative analytical study for the use case of the UK short-term electricity price prediction. Discover Internet of Things, 4(1), Article 24. https://doi.org/10.1007/s43926-024-00075-4

Electricity price prediction has an imperative role in the UK energy market among energy trading organisations. The price prediction directly impacts organisational policy for profitable electricity trading, better bidding plans, and the optimisation... Read More about Machine learning and deep learning prediction models for time-series: a comparative analytical study for the use case of the UK short-term electricity price prediction.

Progression of risk in heart failure using dynamic risk modelling (2024)
Thesis
Kazmi, S. (2024). Progression of risk in heart failure using dynamic risk modelling. (Thesis). University of Hull. https://hull-repository.worktribe.com/output/5086141

Heart failure (HF) is a prevalent condition affecting a significant number of individuals in the UK, leading to substantial healthcare utilisation and adverse outcomes. Despite advancements in treatment and management, the prognosis for hospitalised... Read More about Progression of risk in heart failure using dynamic risk modelling.

Understanding Slang with LLMs: Modelling Cross-Cultural Nuances through Paraphrasing (2024)
Presentation / Conference Contribution
Wuraola, I., Dethlefs, N., & Marciniak, D. (2024, November). Understanding Slang with LLMs: Modelling Cross-Cultural Nuances through Paraphrasing. Presented at EMNLP 2024 - 2024 Conference on Empirical Methods in Natural Language Processing, Proceedings of the Conference, Miami, FLorida, USA

In the realm of social media discourse, the integration of slang enriches communication, reflecting the sociocultural identities of users. This study investigates the capability of large language models (LLMs) to paraphrase slang within climate-relat... Read More about Understanding Slang with LLMs: Modelling Cross-Cultural Nuances through Paraphrasing.

Computing for Social Good in Education (2024)
Journal Article
Ellis, H., Hislop, G. W., Goldweber, M., Rebelsky, S., Pearce, J., Ordonez, P., Pias, M., & Gordon, N. (2024). Computing for Social Good in Education. ACM Inroads, 15(4), 47-57. https://doi.org/10.1145/3699719

Computing for Social Good in Education (CSG-Ed) engages students with the positive potential of computing to benefit society. It can introduce students to aspects of professional responsibility, something computing students need more than ever given... Read More about Computing for Social Good in Education.

Blood-glucose regulator design for diabetics based on LQIR-driven Sliding-Mode-Controller with self-adaptive reaching law (2024)
Journal Article
Saleem, O., & Iqbal, J. (2024). Blood-glucose regulator design for diabetics based on LQIR-driven Sliding-Mode-Controller with self-adaptive reaching law. PLoS ONE, 19(11), Article e0314479. https://doi.org/10.1371/journal.pone.0314479

Type I Diabetes is an endocrine disorder that prevents the pancreas from regulating the blood glucose (BG) levels in a patient’s body. The ubiquitous Linear-Quadratic-Integral-Regulator (LQIR) is an optimal glycemic regulation strategy; however, it i... Read More about Blood-glucose regulator design for diabetics based on LQIR-driven Sliding-Mode-Controller with self-adaptive reaching law.

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.

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.

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.