All Outputs (833)

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., Thakkar, N., & 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.

Toward Efficient Mobile Electric Vehicle Charging under Heterogeneous Battery Switching Technology (2022)
Journal Article
Ahmad, A., Ullah, Z., Khalid, M., & Ahmad, N. (2022). Toward Efficient Mobile Electric Vehicle Charging under Heterogeneous Battery Switching Technology. Applied Sciences, 12(2), Article 904. https://doi.org/10.3390/app12020904

The fast increase in adoption and development of Electric Vehicles (EVs) has invited a significant challenge to the existing charging management techniques and infrastructure. It is necessary to efficiently manage a large number of mobile EVs. As com... Read More about Toward Efficient Mobile Electric Vehicle Charging under Heterogeneous Battery Switching Technology.

A Deep Learning Framework for Wind Turbine Repair Action Prediction Using Alarm Sequences and Long Short Term Memory Algorithms (2022)
Journal Article
Walker, C., Rothon, C., Aslansefat, K., Papadopoulos, Y., & Dethlefs, N. (2022). A Deep Learning Framework for Wind Turbine Repair Action Prediction Using Alarm Sequences and Long Short Term Memory Algorithms. Lecture notes in computer science, 13525 LNCS, 189-203. https://doi.org/10.1007/978-3-031-15842-1_14

With an increasing emphasis on driving down the costs of Operations and Maintenance (O &M) in the Offshore Wind (OSW) sector, comes the requirement to explore new methodology and applications of Deep Learning (DL) to the domain. Condition-based monit... Read More about A Deep Learning Framework for Wind Turbine Repair Action Prediction Using Alarm Sequences and Long Short Term Memory Algorithms.

Hybrid Dense Network With Attention Mechanism for Hyperspectral Image Classification (2022)
Journal Article
Ahmad, M., Khan, A. M., Mazzara, M., Distefano, S., Roy, S. K., & Wu, X. (2022). Hybrid Dense Network With Attention Mechanism for Hyperspectral Image Classification. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 15, 3948-3957. https://doi.org/10.1109/JSTARS.2022.3171586

The nonlinear relation between the spectral information and the corresponding objects (complex physiognomies) makes pixelwise classification challenging for conventional methods. To deal with nonlinearity issues in hyperspectral image classification... Read More about Hybrid Dense Network With Attention Mechanism for Hyperspectral Image Classification.

The Role of Gamification in a Software Development Lifecycle (2021)
Presentation / Conference Contribution
Gordon, N., Brayshaw, M., Dixon, J., Grey, S., & Parker, D. (2021, June). The Role of Gamification in a Software Development Lifecycle. Presented at INSPIRE XXVI International e-conference, Online

Teaching Software Engineering students raises a number of challenges; in particular that student developers typically demonstrate behaviours that run counter to good software development. These include failing to plan properly, failing to develop the... Read More about The Role of Gamification in a Software Development Lifecycle.

Terminal sliding mode control of an anthropomorphic manipulator with friction based observer (2021)
Presentation / Conference Contribution
Ali, K., Mehmood, A., & Iqbal, J. (2021, October). Terminal sliding mode control of an anthropomorphic manipulator with friction based observer. Presented at 2021 International Conference on Robotics and Automation in Industry (ICRAI), Rawalpindi, Pakistan

The role of modern control techniques has been instrumental in today’s robotic applications because of their increasing requirements for reliability, accuracy, productivity and repeatability. Robotic manipulators are highly non-linear systems with co... Read More about Terminal sliding mode control of an anthropomorphic manipulator with friction based observer.

Using Proximity Graph Cut for Fast and Robust Instance-Based Classification in Large Datasets (2021)
Journal Article
Protasov, S., & Khan, A. M. (2021). Using Proximity Graph Cut for Fast and Robust Instance-Based Classification in Large Datasets. Complexity, 2021, Article 2011738. https://doi.org/10.1155/2021/2011738

K-nearest neighbours (kNN) is a very popular instance-based classifier due to its simplicity and good empirical performance. However, large-scale datasets are a big problem for building fast and compact neighbourhood-based classifiers. This work pres... Read More about Using Proximity Graph Cut for Fast and Robust Instance-Based Classification in Large Datasets.

NEAT Activity Detection using Smartwatch at Low Sampling Frequency (2021)
Presentation / Conference Contribution
Dewan, A., Gunturi, V. M., Naik, V., & Dutta, K. K. (2021, October). NEAT Activity Detection using Smartwatch at Low Sampling Frequency. Presented at 2021 IEEE SmartWorld, Ubiquitous Intelligence and Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Internet of People, and Smart City Innovations, SmartWorld/ScalCom/UIC/ATC/IoP/SCI 2021, Atlanta, GA, USA

Our paper aims to build a classification model to discern the typical NEAT (Non-Exercise Activity Thermogenesis) activities done in a home setting. The concept of NEAT is broadly defined as the energy spent in everything which is not sleeping, eating... Read More about NEAT Activity Detection using Smartwatch at Low Sampling Frequency.

Use Case of Building an Indoor Air Quality Monitoring System (2021)
Presentation / Conference Contribution
Kureshi, R. R., Thakker, D., Mishra, B. K., & Ahmed, B. (2021, June). Use Case of Building an Indoor Air Quality Monitoring System. Presented at 7th IEEE World Forum on Internet of Things, WF-IoT 2021, New Orleans, USA

On average, we spend around 90% of the time in indoor environments. Indoor Air Quality (IAQ) has been receiving increased attention from the environmental bodies, local authorities and citizens as it is becoming clearer that poor IAQ has public healt... Read More about Use Case of Building an Indoor Air Quality Monitoring System.

Unscented Kalman filter for airship model uncertainties and wind disturbance estimation (2021)
Journal Article
Wasim, M., Ali, A., Ahmad Choudhry, M., Saleem, F., Shaikh, I. U. H., & Iqbal, J. (2021). Unscented Kalman filter for airship model uncertainties and wind disturbance estimation. PLoS ONE, 16(11 November), Article e0257849. https://doi.org/10.1371/journal.pone.0257849

An airship is lighter than an air vehicle with enormous potential in applications such as communication, aerial inspection, border surveillance, and precision agriculture. An airship model is made up of dynamic, aerodynamic, aerostatic, and propulsiv... Read More about Unscented Kalman filter for airship model uncertainties and wind disturbance estimation.

Robust fuzzy sliding mode controller for a skid-steered vehicle subjected to friction variations (2021)
Journal Article
Mehmood, Y., Aslam, J., Ullah, N., Alsheikhy, A. A., Din, E. U., & Iqbal, J. (2021). Robust fuzzy sliding mode controller for a skid-steered vehicle subjected to friction variations. PLoS ONE, 16(11), Article 0258909. https://doi.org/10.1371/journal.pone.0258909

Skid-steered vehicles (SSV) are gaining huge importance in the market due to their applications like construction, agricultural work, material handling etc. The accuracy of performing such tasks require a robust control algorithm. The design of such... Read More about Robust fuzzy sliding mode controller for a skid-steered vehicle subjected to friction variations.

Control of an anthropomorphic manipulator using LuGre friction model - Design and experimental validation (2021)
Journal Article
Ali, K., Mehmood, A., Muhammad, I., Razzaq, S., & Iqbal, J. (2021). Control of an anthropomorphic manipulator using LuGre friction model - Design and experimental validation. Strojniški vestnik - Journal of Mechanical Engineering, 67(9), 401-410. https://doi.org/10.5545/sv-jme.2021.7258

Automation technology has been extensively recognized as an emerging field in various industrial applications. Recent breakthrough in flexible automation is primarily due to deployment of robotic arms or manipulators. Autonomy in these manipulators i... Read More about Control of an anthropomorphic manipulator using LuGre friction model - Design and experimental validation.

Optimization of fuzzy logic quadrotor attitude controller - particle swarm, Cuckoo search and BAT algorithms (2021)
Journal Article
Siddiq Zatout, M., Rezoug, A., Rezoug, A., Baizid, K., & Iqbal, J. (2021). Optimization of fuzzy logic quadrotor attitude controller - particle swarm, Cuckoo search and BAT algorithms. International Journal of Systems Science, https://doi.org/10.1080/00207721.2021.1978012

Bio-inspired optimisation algorithms have recently attracted much attention in the control community. Most of these algorithms mimic particular behaviours of some animal species in such a way that allows solving optimisation problems. The present pap... Read More about Optimization of fuzzy logic quadrotor attitude controller - particle swarm, Cuckoo search and BAT algorithms.

Predicting personalised optimal arc parameter using knowledge-based planning model for inoperable locally advanced lung cancer patients to reduce organ at risk doses (2021)
Journal Article
Tambe, N. S., Pires, I. M., Moore, C., Wieczorek, A., Upadhyay, S., & Beavis, A. W. (2021). Predicting personalised optimal arc parameter using knowledge-based planning model for inoperable locally advanced lung cancer patients to reduce organ at risk doses. Biomedical Physics and Engineering Express, 7(6), Article 065016. https://doi.org/10.1088/2057-1976/ac2635

Objectives. Volumetric modulated arc therapy (VMAT) allows for reduction of organs at risk (OAR) volumes receiving higher doses, but increases OAR volumes receiving lower radiation doses and can subsequently increasing associated toxicity. Therefore,... Read More about Predicting personalised optimal arc parameter using knowledge-based planning model for inoperable locally advanced lung cancer patients to reduce organ at risk doses.