All Outputs (41)

Flexible Ontology-Driven Educational Apps and Social Media for Learners with a Disability (2022)
Conference Proceeding
Nganji, J. T., Brayshaw, M., & Gordon, N. (2022). Flexible Ontology-Driven Educational Apps and Social Media for Learners with a Disability. In P. Zaphiris, & A. Ioannou (Eds.), Learning and Collaboration Technologies. Designing the Learner and Teacher Experience. HCII 2022 (361-375). https://doi.org/10.1007/978-3-031-05657-4_26

This paper explores how to build ontology-driven learning systems from a flexible disability-aware mentality and augment them into a learning blend that embraces social media. The approach emphasizes the use of user centered flexible software in a bl... Read More about Flexible Ontology-Driven Educational Apps and Social Media for Learners with a Disability.

Facilitating a smoother transition to renewable energy with AI (2022)
Journal Article
Chatterjee, J., & Dethlefs, N. (2022). Facilitating a smoother transition to renewable energy with AI. Patterns, 3(6), Article 100528. https://doi.org/10.1016/j.patter.2022.100528

Artificial intelligence (AI) can help facilitate wider adoption of renewable energy globally. We organized a social event for the AI and renewables community to discuss these aspects at the International Conference on Learning Representations (ICLR),... Read More about Facilitating a smoother transition to renewable energy with AI.

Learning Analytics and Deep Learning in Large Virtual Learning Environments (VLEs) (2022)
Journal Article
Wechie, N., Brayshaw, M., & Gordon, N. (2022). Learning Analytics and Deep Learning in Large Virtual Learning Environments (VLEs). International Journal on Engineering Technologies and Informatics, 3(1), 1-3. https://doi.org/10.51626/ijeti.2022.03.00029

In this paper we look at the use of Deep Learning as a technique for Education Data Mining and Learnng Analytics. We discuss existing approaches and how Deep Learning can be used in a complimentary manner in order to provide new and insightful perspe... Read More about Learning Analytics and Deep Learning in Large Virtual Learning Environments (VLEs).

Extended grey wolf optimization–based adaptive fast nonsingular terminal sliding mode control of a robotic manipulator (2022)
Journal Article
Rezoug, A., Iqbal, J., & Tadjine, M. (2022). Extended grey wolf optimization–based adaptive fast nonsingular terminal sliding mode control of a robotic manipulator. Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering, https://doi.org/10.1177/09596518221099768

This article proposes a novel hybrid metaheuristic technique based on nonsingular terminal sliding mode controller, time delay estimation method, an extended grey wolf optimization algorithm and adaptive super twisting control law. The fast convergen... Read More about Extended grey wolf optimization–based adaptive fast nonsingular terminal sliding mode control of a robotic manipulator.

Locally fitting hyperplanes to high-dimensional data (2022)
Journal Article
Hou, M., & Kambhampati, C. (2022). Locally fitting hyperplanes to high-dimensional data. Neural Computing and Applications, 34(11), 8885-8896. https://doi.org/10.1007/s00521-022-06909-y

Problems such as data compression, pattern recognition and artificial intelligence often deal with a large data sample as observations of an unknown object. An effective method is proposed to fit hyperplanes to data points in each hypercubic subregio... Read More about Locally fitting hyperplanes to high-dimensional data.

Consensus Adversarial Defense Method Based on Augmented Examples (2022)
Journal Article
Ding, X., Cheng, Y., Luo, Y., Li, Q., & Gope, P. (2022). Consensus Adversarial Defense Method Based on Augmented Examples. IEEE Transactions on Industrial Informatics, https://doi.org/10.1109/TII.2022.3169973

Deep learning has been used in many computer-vision-based industrial Internet of Things applications. However, deep neural networks are vulnerable to adversarial examples that have been crafted specifically to fool a system while being imperceptible... Read More about Consensus Adversarial Defense Method Based on Augmented Examples.

Performance comparison of structured H∞ based looptune and LQR for a 4-DOF robotic manipulator (2022)
Journal Article
Asghar, A., Iqbal, M., Khaliq, A., Rehman, S. U., & Iqbal, J. (2022). Performance comparison of structured H∞ based looptune and LQR for a 4-DOF robotic manipulator. PLoS ONE, 17(4), Article e0266728. https://doi.org/10.1371/journal.pone.0266728

We explore looptune, a MATLAB-based structured H1 synthesis technique in the context of robotics. Position control of a 4 Degree of Freedom (DOF) serial robotic manipulator developed using Simulink is the problem under consideration. Three full state... Read More about Performance comparison of structured H∞ based looptune and LQR for a 4-DOF robotic manipulator.

Theory and practice for autonomous formation flight of quadrotors via distributed robust sliding mode control protocol with fixed-time stability guarantee (2022)
Journal Article
Mechali, O., Xu, L., Xie, X., & Iqbal, J. (2022). Theory and practice for autonomous formation flight of quadrotors via distributed robust sliding mode control protocol with fixed-time stability guarantee. Control engineering practice, 123, Article 105150. https://doi.org/10.1016/j.conengprac.2022.105150

A detailed theoretical design and technological implementation aspects are presented in this paper to address the aerial formation control problem of networked quadrotors with a fixed-time stability property. The control algorithm is embedded in a di... Read More about Theory and practice for autonomous formation flight of quadrotors via distributed robust sliding mode control protocol with fixed-time stability guarantee.

An AI-Driven Secure and Intelligent Robotic Delivery System (2022)
Journal Article
Wang, W., Gope, P., & Cheng, Y. (in press). An AI-Driven Secure and Intelligent Robotic Delivery System. IEEE Transactions on Engineering Management, https://doi.org/10.1109/TEM.2022.3142282

Last-mile delivery has gained much popularity in recent years, it accounts for about half of the whole logistics cost. Unlike container transportation, companies must hire significant number of employees to deliver packages to the customers. Therefor... Read More about An AI-Driven Secure and Intelligent Robotic Delivery System.

Maximum Power Extraction from a Standalone Photo Voltaic System via Neuro-Adaptive Arbitrary Order Sliding Mode Control Strategy with High Gain Differentiation (2022)
Journal Article
Anjum, M. B., Khan, Q., Ullah, S., Hafeez, G., Fida, A., Iqbal, J., & R. Albogamy, F. (2022). Maximum Power Extraction from a Standalone Photo Voltaic System via Neuro-Adaptive Arbitrary Order Sliding Mode Control Strategy with High Gain Differentiation. Applied Sciences, 12(6), Article 2773. https://doi.org/10.3390/app12062773

In this work, a photovoltaic (PV) system integrated with a non-inverting DC-DC buck-boost converter to extract maximum power under varying environmental conditions such as irradiance and temperature is considered. In order to extract maximum power (v... Read More about Maximum Power Extraction from a Standalone Photo Voltaic System via Neuro-Adaptive Arbitrary Order Sliding Mode Control Strategy with High Gain Differentiation.

Addressing Optimisation Challenges for Datasets with Many Variables, Using Genetic Algorithms to Implement Feature Selection (2022)
Journal Article
Gordon, N., Kambhampati, C., & Alabad, A. (2022). Addressing Optimisation Challenges for Datasets with Many Variables, Using Genetic Algorithms to Implement Feature Selection. AI, Computer Science and Robotics Technology, 1, 1-21. https://doi.org/10.5772/acrt.01

This article provides an optimisation method using a Genetic Algorithm approach to apply feature selection techniques for large data sets to improve accuracy. This is achieved through improved classification, a reduced number of features, and further... Read More about Addressing Optimisation Challenges for Datasets with Many Variables, Using Genetic Algorithms to Implement Feature Selection.

Performance improvement in polymer electrolytic membrane fuel cell based on nonlinear control strategies—A comprehensive study (2022)
Journal Article
Javaid, U., Iqbal, J., Mehmood, A., & Uppal, A. A. (2022). Performance improvement in polymer electrolytic membrane fuel cell based on nonlinear control strategies—A comprehensive study. PLoS ONE, 17(2 February), Article e0264205. https://doi.org/10.1371/journal.pone.0264205

A Polymer Electrolytic Membrane Fuel Cell (PEMFC) is an efficient power device for automobiles, but its efficiency and life span depend upon its air delivery system. To ensure improved performance of PEMFC, the air delivery system must ensure proper... Read More about Performance improvement in polymer electrolytic membrane fuel cell based on nonlinear control strategies—A comprehensive study.

Fixed-time nonlinear homogeneous sliding mode approach for robust tracking control of multirotor aircraft: Experimental validation (2022)
Journal Article
Mechali, O., Xu, L., Xie, X., & Iqbal, J. (2022). Fixed-time nonlinear homogeneous sliding mode approach for robust tracking control of multirotor aircraft: Experimental validation. Journal of The Franklin Institute, 359(5), 1971-2029. https://doi.org/10.1016/j.jfranklin.2022.01.010

This paper presents a robust scheme for fixed-time tracking control of a multirotor system. The aircraft is subjected to matched lumped disturbances, i.e., unmodeled dynamics, parameters uncertainties, and external perturbations besides measurement n... Read More about Fixed-time nonlinear homogeneous sliding mode approach for robust tracking control of multirotor aircraft: Experimental validation.

Data-Driven Techniques for Low-Cost Sensor Selection and Calibration for the Use Case of Air Quality Monitoring (2022)
Journal Article
Kureshi, R., Mishra, B., Thakker, D., John, R., Walker, A., Simpson, S., …Wante, A. (2022). Data-Driven Techniques for Low-Cost Sensor Selection and Calibration for the Use Case of Air Quality Monitoring. Sensors, 22(3), Article 1093. https://doi.org/10.3390/s22031093

With the emergence of Low-Cost Sensor (LCS) devices, measuring real-time data on a large scale has become a feasible alternative approach to more costly devices. Over the years, sensor technologies have evolved which has provided the opportunity to h... Read More about Data-Driven Techniques for Low-Cost Sensor Selection and Calibration for the Use Case of Air Quality Monitoring.

Highly Accurate and Reliable Wireless Network Slicing in 5 th Generation Networks: A Hybrid Deep Learning Approach (2022)
Journal Article
Khan, S., Khan, S., Ali, Y., Khalid, M., Ullah, Z., & Mumtaz, S. (2022). Highly Accurate and Reliable Wireless Network Slicing in 5 th Generation Networks: A Hybrid Deep Learning Approach. Journal of Network and Systems Management, 30, Article 29. https://doi.org/10.1007/s10922-021-09636-2

In current era, the next generation networks like 5 th generation (5G) and 6 th generation (6G) networks requires high security, low latency with a high reliable standards and capacity. In these networks, reconfigurable wireless network slicing is co... Read More about Highly Accurate and Reliable Wireless Network Slicing in 5 th Generation Networks: A Hybrid Deep Learning Approach.

Neural network-based adaptive global sliding mode MPPT controller design for stand-alone photovoltaic systems (2022)
Journal Article
Haq, I. U., Khan, Q., Ullah, S., Ahmed Khan, S., Akmeliawati, R., Khan, M. A., & Iqbal, J. (2022). Neural network-based adaptive global sliding mode MPPT controller design for stand-alone photovoltaic systems. PLoS ONE, 17(1), Article e0260480. https://doi.org/10.1371/journal.pone.0260480

The increasing energy demand and the target to reduce environmental pollution make it essential to use efficient and environment-friendly renewable energy systems. One of these systems is the Photovoltaic (PV) system which generates energy subject to... Read More about Neural network-based adaptive global sliding mode MPPT controller design for stand-alone photovoltaic systems.

Collaborative position control of pantograph robot using particle swarm optimization (2022)
Journal Article
Ali, N., Ayaz, Y., & Iqbal, J. (2022). Collaborative position control of pantograph robot using particle swarm optimization. International journal of control, automation, and systems, 20(1), 198-207. https://doi.org/10.1007/s12555-019-0931-6

This article presents the design and real-time implementation of an optimal collaborative approach to obtain the desired trajectory tracking of two Degree of Freedom (DOF) pantograph end effector position. The proposed controller constructively syner... Read More about Collaborative position control of pantograph robot using particle swarm optimization.

Improving Graduate Futures and Employability Through Embedded Industrial Experience (2022)
Journal Article
Dixon, J., & Gordon, N. (2022). Improving Graduate Futures and Employability Through Embedded Industrial Experience. New Directions in the Teaching of Physical Sciences, https://doi.org/10.29311/ndtps.v0i17.3596

The financial cost to individuals of higher education is now regularly exceeding £50k before maintenance in the UK; consequently, students are more concerned than ever that their degree should offer value for money when they enter the jobs marketplac... Read More about Improving Graduate Futures and Employability Through Embedded Industrial Experience.

Adaptive FIT-SMC Approach for an Anthropomorphic Manipulator With Robust Exact Differentiator and Neural Network-Based Friction Compensation (2022)
Journal Article
Ali, K., Ullah, S., Mehmood, A., Mostafa, H., Marey, M., & Iqbal, J. (2022). Adaptive FIT-SMC Approach for an Anthropomorphic Manipulator With Robust Exact Differentiator and Neural Network-Based Friction Compensation. IEEE Access, 10, 3378-3389. https://doi.org/10.1109/ACCESS.2021.3139041

In robotic manipulators, feedback control of nonlinear systems with fast finite-time convergence is desirable. However, because of the parametric and model uncertainties, the robust control and tuning of the robotic manipulators pose many challenges... Read More about Adaptive FIT-SMC Approach for an Anthropomorphic Manipulator With Robust Exact Differentiator and Neural Network-Based Friction Compensation.

IoP System Dependability Evaluation Method Based on AADL (2022)
Journal Article
Shi, X., Mian, Z., & Gao, Y. (2022). IoP System Dependability Evaluation Method Based on AADL. Jisuanji Gongcheng/Computer Engineering, 48(1), 204-213. https://doi.org/10.19678/j.issn.1000-3428.0059738

The Internet of People(IoP)is characterized by the complex architecture and massive changing data, which adds to the difficulty of the analysis on IoP-based system dependability.Currently, there is still no robust dependability modelling and analysis... Read More about IoP System Dependability Evaluation Method Based on AADL.