All Outputs (830)

PD-Type Iterative Learning Consensus Control Approach for an Electromechanical Actuator-Based Multiagent System (2025)
Journal Article
Li, B., Riaz, S., Saleem, O., Zhao, Y., & Iqbal, J. (2025). PD-Type Iterative Learning Consensus Control Approach for an Electromechanical Actuator-Based Multiagent System. Applied Intelligence, 55, Article 684. https://doi.org/10.1007/s10489-025-06559-2

Achieving consensus tracking control of a multiagent system (MAS) is challenging. This article proposes an innovative consensus control scheme of a MAS that is composed of electromechanical actuators. The open-loop derivative-type iterative learning... Read More about PD-Type Iterative Learning Consensus Control Approach for an Electromechanical Actuator-Based Multiagent System.

DiffFormer: a Differential Spatial-Spectral Transformer for Hyperspectral Image Classification (2025)
Journal Article
Ahmad, M., Mazzara, M., Distefano, S., Khan, A. M., & Ullo, S. L. (in press). DiffFormer: a Differential Spatial-Spectral Transformer for Hyperspectral Image Classification. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 18, 10419-10428. https://doi.org/10.1109/JSTARS.2025.3558889

Hyperspectral image classification (HSIC) presents significant challenges due to spectral redundancy and spatial discontinuity, both of which can negatively impact classification performance. To mitigate these issues, this work proposes the Different... Read More about DiffFormer: a Differential Spatial-Spectral Transformer for Hyperspectral Image Classification.

LiqState: Liquid Identification and State Monitoring Using mmWave IoT Sensing (2025)
Journal Article
Niaz, F., Zhang, J., Khalid, M., Younas, M., & Majid, A. (online). LiqState: Liquid Identification and State Monitoring Using mmWave IoT Sensing. IEEE internet of things journal, https://doi.org/10.1109/JIOT.2025.3549374

Traditional RF-based liquid identification methods generally rely on a single characteristic such as refractive index or permittivity and often assume prior container knowledge, limiting their versatility. These approaches also face challenges in sce... Read More about LiqState: Liquid Identification and State Monitoring Using mmWave IoT Sensing.

Scaling up and automating formative assessment in computer science (2025)
Book Chapter
Gordon, N. (2025). Scaling up and automating formative assessment in computer science. In S. Elkington, & A. Irons (Eds.), Formative Assessment and Feedback in Post-Digital Learning Environments: Disciplinary Case Studies in Higher Education (172-178). Routledge. https://doi.org/10.4324/9781003360254-22

The rise in student numbers in computer science creates a challenge for delivery. Computer science has some of the worst attainment and retention profiles across subjects. Given its technology focus, it is a subject where digital technologies have lo... Read More about Scaling up and automating formative assessment in computer science.

Adaptive reconfigurable learning algorithm for robust optimal longitudinal motion control of UAVs (2025)
Journal Article
Saleem, O., Tanveer, A., & Iqbal, J. (2025). Adaptive reconfigurable learning algorithm for robust optimal longitudinal motion control of UAVs. Algorithms, 18(4), Article 180. https://doi.org/10.3390/a18040180

This study presents the formulation and verification of a novel online adaptive reconfigu-rable learning control algorithm (RLCA) for improved longitudinal motion control and disturbance compensation in unmanned aerial vehicles (UAVs). The proposed a... Read More about Adaptive reconfigurable learning algorithm for robust optimal longitudinal motion control of UAVs.

Spatial-spectral morphological mamba for hyperspectral image classification (2025)
Journal Article
Ahmad, M., Butt, M. H. F., Khan, A. M., Mazzara, M., Distefano, S., Usama, M., Roy, S. K., Chanussot, J., & Hong, D. (online). Spatial-spectral morphological mamba for hyperspectral image classification. Neurocomputing, Article 129995. https://doi.org/10.1016/j.neucom.2025.129995

Recent advancements in transformers, specifically self-attention mechanisms, have significantly improved hyperspectral image (HSI) classification. However, these models often have inefficiencies, as their computational complexity scales quadratically... Read More about Spatial-spectral morphological mamba for hyperspectral image classification.

Comprehensive Health Tracking Through Machine Learning and Wearable Technology (2025)
Journal Article
Yusuf, A., Jaber, T. A., & Gordon, N. (online). Comprehensive Health Tracking Through Machine Learning and Wearable Technology. Journal of Data Science and Intelligent Systems, https://doi.org/10.47852/bonviewjdsis52023588

The accurate interpretation of data from wearable devices is paramount in advancing personalized healthcare and disease prevention. This study explores the application of machine learning techniques to improve the interpretation of health metrics fro... Read More about Comprehensive Health Tracking Through Machine Learning and Wearable Technology.

An Adaptive Flooding Detection Framework with Blockchain Mitigation for Satellite Communications † (2025)
Journal Article
Arshad, M., Liu, |., Khalid, |. M., Liu, Y., Wang, P., & Arshad, M. (online). An Adaptive Flooding Detection Framework with Blockchain Mitigation for Satellite Communications †. International Journal of Satellite Communications and Networking, https://doi.org/10.1002/sat.1560

Satellite communication has gained significant attention in the context of sixth-generation (6G) internet technology. Due to their high altitudes, dynamic link switching, and limited resources, satellite nodes are prone to higher bit error rates and... Read More about An Adaptive Flooding Detection Framework with Blockchain Mitigation for Satellite Communications †.

Evaluating and implementing machine learning models for personalised mobile health app recommendations (2025)
Journal Article
Morenigbade, H., Al Jaber, T., Gordon, N., & Eke, G. (2025). Evaluating and implementing machine learning models for personalised mobile health app recommendations. PLoS ONE, 20(3 March), Article e0319828. https://doi.org/10.1371/journal.pone.0319828

This paper focuses on the evaluation and recommendation of healthcare applications in the mHealth field. The increase in the use of health applications, supported by an expanding mHealth market, highlights the importance of this research. In this stu... Read More about Evaluating and implementing machine learning models for personalised mobile health app recommendations.

Correction to: Dual FOPID-neural network controller based on fast grey wolf optimizer: application to two-inputs two-outputs helicopter (Systems Science & Control Engineering, (2025), 13, 1, (2449156), 10.1080/21642583.2024.2449156) (2025)
Journal Article
Rezoug, A., Iqbal, J., & Nemra, A. (2025). Correction to: Dual FOPID-neural network controller based on fast grey wolf optimizer: application to two-inputs two-outputs helicopter (Systems Science & Control Engineering, (2025), 13, 1, (2449156), 10.1080/21642583.2024.2449156). Systems Science and Control Engineering, 13(1), Article 2456881. https://doi.org/10.1080/21642583.2025.2456881

Article title: Dual FOPID-neural network controller based on fast grey wolf optimizer: application to two-inputs two-outputs helicopter Authors: Rezoug, A., Iqbal, J., & Nemra, A. Journal:Systems Science & Control EngineeringBibliometrics: Volume 13,... Read More about Correction to: Dual FOPID-neural network controller based on fast grey wolf optimizer: application to two-inputs two-outputs helicopter (Systems Science & Control Engineering, (2025), 13, 1, (2449156), 10.1080/21642583.2024.2449156).

An Ordinal Collaboration Network Model with Zero Truncated Poisson Latent Variables and Its Application (2025)
Journal Article
Yang, Q., Tian, Y.-Z., Zhang, Y.-J., Wang, Y., & Mian, Z. (2025). An Ordinal Collaboration Network Model with Zero Truncated Poisson Latent Variables and Its Application. Stat, 14(1), Article e70040. https://doi.org/10.1002/sta4.70040

Link prediction has traditionally been regarded as a binary classification problem, aiming to predict whether a link exists between two nodes in a given network. However, this binary framework fails to account for the cooperation intensity or the div... Read More about An Ordinal Collaboration Network Model with Zero Truncated Poisson Latent Variables and Its Application.

Sequence Outlier Detection and Application of Gated Recurrent Unit Autoencoder Gaussian Mixture Model Based on Various Loss Optimization (2025)
Journal Article
Xu, T., Tian, Y., Wu, C., & Mian, Z. (2025). Sequence Outlier Detection and Application of Gated Recurrent Unit Autoencoder Gaussian Mixture Model Based on Various Loss Optimization. Statistical Analysis and Data Mining, 18(1), Article e70001. https://doi.org/10.1002/sam.70001

In the era of big data, detecting outliers in time series data is crucial, particularly in fields such as finance and engineering. This article proposes a novel sequence outlier detection method based on the gated recurrent unit autoencoder with Gaus... Read More about Sequence Outlier Detection and Application of Gated Recurrent Unit Autoencoder Gaussian Mixture Model Based on Various Loss Optimization.

TOA and TDOA Based Asynchronous Self-Localization: Three Stage Framework for Simultaneous Localization of Microphones and Audio Sources (2025)
Thesis
Cao, F. (2025). TOA and TDOA Based Asynchronous Self-Localization: Three Stage Framework for Simultaneous Localization of Microphones and Audio Sources. (Thesis). University of Hull. https://hull-repository.worktribe.com/output/5086296

Self-localization, a pivotal aspect explored in this research, holds significant relevance across various applications, including human-robot interaction and surveillance for aging individuals. Traditional localization methods relying on GPS signals... Read More about TOA and TDOA Based Asynchronous Self-Localization: Three Stage Framework for Simultaneous Localization of Microphones and Audio Sources.

Analysis of the influencing factors of the trade potential between countries along the ‘Belt and Road’ and China: a study based on spatial panel data model (2025)
Journal Article
Zhang, F. L., Tian, Y., Lam, L. K., & Mian, Z. (online). Analysis of the influencing factors of the trade potential between countries along the ‘Belt and Road’ and China: a study based on spatial panel data model. Enterprise Information Systems, https://doi.org/10.1080/17517575.2024.2448315

In 2013, China launched a cooperative initiative to build the “Silk Road Economic Belt” and the “21st Century Maritime Silk Road”. Based on the data of import and export trade between 57 countries along the “Belt and Road” and China from 2010 to 2021... Read More about Analysis of the influencing factors of the trade potential between countries along the ‘Belt and Road’ and China: a study based on spatial panel data model.

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.

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.

Robust Position Control of VTOL UAVs Using a Linear Quadratic Rate-Varying Integral Tracker: Design and Validation (2025)
Journal Article
Saleem, O., Kazim, M., & Iqbal, J. (2025). Robust Position Control of VTOL UAVs Using a Linear Quadratic Rate-Varying Integral Tracker: Design and Validation. Drones, 9(1), Article 73. https://doi.org/10.3390/drones9010073

This article presents an optimal tracking controller retrofitted with a nonlinear adaptive integral compensator, specifically designed to ensure robust and accurate positioning of Vertical Take-Off and Landing (VTOL) Unmanned Aerial Vehicles (UAVs) t... Read More about Robust Position Control of VTOL UAVs Using a Linear Quadratic Rate-Varying Integral Tracker: Design and Validation.

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.

Combined Oriented Data Augmentation Method for Brain MRI Images (2025)
Journal Article
Farhan, A. S., Khalid, M., & Manzoor, U. (2025). Combined Oriented Data Augmentation Method for Brain MRI Images. IEEE Access, 13, 9981-9994. https://doi.org/10.1109/ACCESS.2025.3526684

In recent years, deep learning’s use in medical imaging has grown exponentially. However, one of the biggest problems with training deep learning models is the unavailability of large amounts of data, which leads to overfitting. Collecting large quan... Read More about Combined Oriented Data Augmentation Method for Brain MRI Images.

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.