All Outputs (501)

Robust Finite-Time Trajectory Tracking Control of Quadrotor Aircraft via Terminal Sliding Mode-Based Active Antidisturbance Approach: A PIL Experiment (2021)
Journal Article
Mechali, O., Iqbal, J., Xie, X., Xu, L., & Senouci, A. (2021). Robust Finite-Time Trajectory Tracking Control of Quadrotor Aircraft via Terminal Sliding Mode-Based Active Antidisturbance Approach: A PIL Experiment. International Journal of Aerospace Engineering, 2021, Article 5522379. https://doi.org/10.1155/2021/5522379

This paper presents an accurate solution of finite-time Cartesian trajectory tracking control problem of a quadrotor system by designing and implementing a novel robust flight-control algorithm. The quadrotor is subject to nonlinearities, unmodeled d... Read More about Robust Finite-Time Trajectory Tracking Control of Quadrotor Aircraft via Terminal Sliding Mode-Based Active Antidisturbance Approach: A PIL Experiment.

The United Nations Sustainable Development Goals: a setting for Professional and Research skills (2021)
Journal Article
Dixon, J., & Gordon, N. A. (2021). The United Nations Sustainable Development Goals: a setting for Professional and Research skills. New Directions in the Teaching of Physical Sciences, 16(1), https://doi.org/10.29311/ndtps.v0i16.3660

This paper considers the use of the United Nations global goals to provide a framework for the teaching of professional and related skills. The main example and case study considered in this paper is from computing; however, much of the approach and... Read More about The United Nations Sustainable Development Goals: a setting for Professional and Research skills.

Using citizen science to complement IoT data collection: a survey of motivational and engagement factors in technology-centric citizen science projects (2021)
Journal Article
Ali, M. U., Mishra, B. K., Thakker, D., Mazumdar, S., & Simpson, S. (2021). Using citizen science to complement IoT data collection: a survey of motivational and engagement factors in technology-centric citizen science projects. IoT, 2(2), 275--309. https://doi.org/10.3390/iot2020015

A key aspect of the development of Smart Cities involves the efficient and effective management of resources to improve liveability. Achieving this requires large volumes of sensors strategically deployed across urban areas. In many cases, however, i... Read More about Using citizen science to complement IoT data collection: a survey of motivational and engagement factors in technology-centric citizen science projects.

Effect of treatment planning system parameters on beam modulation complexity for treatment plans with single-layer multi-leaf collimator and dual-layer stacked multi-leaf collimator (2021)
Journal Article
Quintero, P., Cheng, Y., Benoit, D., Moore, C., & Beavis, A. (2021). Effect of treatment planning system parameters on beam modulation complexity for treatment plans with single-layer multi-leaf collimator and dual-layer stacked multi-leaf collimator. British Journal of Radiology, 94(1122), Article 20201011. https://doi.org/10.1259/bjr.20201011

OBJECTIVE: High levels of beam modulation complexity (MC) and monitor units (MU) can compromise the plan deliverability of intensity-modulated radiotherapy treatments. Our study evaluates the effect of three treatment planning system (TPS) parameters... Read More about Effect of treatment planning system parameters on beam modulation complexity for treatment plans with single-layer multi-leaf collimator and dual-layer stacked multi-leaf collimator.

System architecture of a proactive intelligent system to monitor health of older adults living alone (2021)
Journal Article
Al-Mejibli, I., Al-Majeed, S., Karam, J., Iqbal, J., Adolfo, C. M., & Yalung, C. (2021). System architecture of a proactive intelligent system to monitor health of older adults living alone. International Journal of Computing and Digital Systems, 10(1), 509-517. https://doi.org/10.12785/IJCDS/100149

Worldwide improvements in the quality of life highlight immense need to have a remote health monitoring system that can provide critical biomedical data. This paper presents a low-cost health monitoring system, forming part of the Internet of Things... Read More about System architecture of a proactive intelligent system to monitor health of older adults living alone.

SRAGL-AWCL: A two-step multi-view clustering via sparse representation and adaptive weighted cooperative learning (2021)
Journal Article
Tan, J., Yang, Z., Cheng, Y., Ye, J., Wang, B., & Dai, Q. (2021). SRAGL-AWCL: A two-step multi-view clustering via sparse representation and adaptive weighted cooperative learning. Pattern Recognition, 117, Article 107987. https://doi.org/10.1016/j.patcog.2021.107987

Sparse representation and cooperative learning are two representative technologies in the field of multi-view spectral clustering. The former can effectively extract features of multiple views by the removal of redundant information contained in each... Read More about SRAGL-AWCL: A two-step multi-view clustering via sparse representation and adaptive weighted cooperative learning.

Scientometric review of artificial intelligence for operations & maintenance of wind turbines: The past, present and future (2021)
Journal Article
Chatterjee, J., & Dethlefs, N. (2021). Scientometric review of artificial intelligence for operations & maintenance of wind turbines: The past, present and future. Renewable & sustainable energy reviews, 144, Article 111051. https://doi.org/10.1016/j.rser.2021.111051

Wind energy has emerged as a highly promising source of renewable energy in recent times. However, wind turbines regularly suffer from operational inconsistencies, leading to significant costs and challenges in operations and maintenance (O&M). Condi... Read More about Scientometric review of artificial intelligence for operations & maintenance of wind turbines: The past, present and future.

A new perspective on teaching the natural exponential to engineering students (2021)
Journal Article
Ullah, M., Aman, M. N., Wolkenhauer, O., & Iqbal, J. (2021). A new perspective on teaching the natural exponential to engineering students. International Journal of Mathematical Education in Science and Technology, https://doi.org/10.1080/0020739X.2021.1896812

The natural exponential and logarithm are typically introduced to undergraduate engineering students in a calculus course using the notion of limits. We here present an approach to introduce the natural exponential/logarithm through a novel interpret... Read More about A new perspective on teaching the natural exponential to engineering students.

XAI4Wind: A Multimodal Knowledge Graph Database for Explainable Decision Support in Operations & Maintenance of Wind Turbines (2021)
Journal Article
Chatterjee, J., & Dethlefs, N. XAI4Wind: A Multimodal Knowledge Graph Database for Explainable Decision Support in Operations & Maintenance of Wind Turbines. https://doi.org/10.48550/arXiv.2012.10489. Manuscript submitted for publication

Condition-based monitoring (CBM) has been widely utilised in the wind industry for monitoring operational inconsistencies and failures in turbines, with techniques ranging from signal processing and vibration analysis to artificial intelligence (AI)... Read More about XAI4Wind: A Multimodal Knowledge Graph Database for Explainable Decision Support in Operations & Maintenance of Wind Turbines.

Hierarchical Multiscale Recurrent Neural Networks for Detecting Suicide Notes (2021)
Journal Article
Schoene, A. M., Turner, A. P., De Mel, G., & Dethlefs, N. (in press). Hierarchical Multiscale Recurrent Neural Networks for Detecting Suicide Notes. IEEE Transactions on Affective Computing, https://doi.org/10.1109/TAFFC.2021.3057105

Recent statistics in suicide prevention show that people are increasingly posting their last words online and with the unprecedented availability of textual data from social media platforms researchers have the opportunity to analyse such data. Furth... Read More about Hierarchical Multiscale Recurrent Neural Networks for Detecting Suicide Notes.

Towards design and implementation of Industry 4.0 for food manufacturing (2021)
Journal Article
Konur, S., Lan, Y., Thakker, D., Morkyani, G., Polovina, N., & Sharp, J. (2023). Towards design and implementation of Industry 4.0 for food manufacturing. Neural Computing and Applications, 35(33), 23753–23765. https://doi.org/10.1007/s00521-021-05726-z

Today’s factories are considered as smart ecosystems with humans, machines and devices interacting with each other for efficient manufacturing of products. Industry 4.0 is a suite of enabler technologies for such smart ecosystems that allow transform... Read More about Towards design and implementation of Industry 4.0 for food manufacturing.

A Semantic Knowledge-Based Framework for Information Extraction and Exploration (2021)
Journal Article
Aljamel, A., Osman, T., & Thakker, D. (2021). A Semantic Knowledge-Based Framework for Information Extraction and Exploration. International Journal of Decision Support System Technology, 13(2), 85--109. https://doi.org/10.4018/IJDSST.2021040105

The availability of online documents that describe domain-specific information provides an opportunity in employing a knowledge-based approach in extracting information from web data. This research proposes a novel comprehensive semantic knowledge-ba... Read More about A Semantic Knowledge-Based Framework for Information Extraction and Exploration.

Nonlinear adaptive backstepping control of permanent magnet synchronous motor (2021)
Journal Article
Ali, N., Alam, W., Pervaiz, M., & Iqbal, J. (2021). Nonlinear adaptive backstepping control of permanent magnet synchronous motor. Revue Roumaine des Sciences Techniques : Série Électrotechnique et Énergétique, 66(1), 9-14

This paper addresses the speed tracking problem of a permanent magnet synchronous motor (PMSM) under the influence of parametric uncertainties and external load torque disturbances. The nonlinear dynamics associated with both PMSM and load is conside... Read More about Nonlinear adaptive backstepping control of permanent magnet synchronous motor.

A novel approach based on stochastic hybrid fault tree to compare alternative flare gas recovery systems (2021)
Journal Article
Khodayee, S. M., Chiacchio, F., & Papadopoulos, Y. (2021). A novel approach based on stochastic hybrid fault tree to compare alternative flare gas recovery systems. IEEE Access, 9, 51029-51049. https://doi.org/10.1109/ACCESS.2021.3069807

Flaring has always been an inseparable part of oil production and exploration. Previously, waste gas collected from different parts of facilities was released for safety or operational reasons and combusted on top of a flare stack since there was not... Read More about A novel approach based on stochastic hybrid fault tree to compare alternative flare gas recovery systems.

Finding the most navigable path in road networks (2021)
Journal Article
Kaur, R., Goyal, V., & Gunturi, V. M. (2021). Finding the most navigable path in road networks. GeoInformatica, 25(1), 207-240. https://doi.org/10.1007/s10707-020-00428-5

Input to the Most Navigable Path (MNP) problem consists of the following: (a) a road network represented as a directed graph, where each edge is associated with numeric attributes of cost and “navigability score” values; (b) a source and a destinatio... Read More about Finding the most navigable path in road networks.

Computational Intelligence for Safety Assurance of Cooperative Systems of Systems (2020)
Journal Article
Kabir, S., & Papadopoulos, Y. (2020). Computational Intelligence for Safety Assurance of Cooperative Systems of Systems. Computer, 53(12), 24-34. https://doi.org/10.1109/MC.2020.3014604

Cooperative systems of systems (CSoSs) form a new technological frontier for their enormous economic and societal potentials in various domains. This article presents a novel framework for dynamic safety assurance of CSoSs that integrates design time... Read More about Computational Intelligence for Safety Assurance of Cooperative Systems of Systems.

Hourly performance forecast of a dew point cooler using explainable Artificial Intelligence and evolutionary optimisations by 2050 (2020)
Journal Article
Golizadeh Akhlaghi, Y., Aslansefat, K., Zhao, X., Sadati, S., Badiei, A., Xiao, X., Shittu, S., Fan, Y., & Ma, X. (2021). Hourly performance forecast of a dew point cooler using explainable Artificial Intelligence and evolutionary optimisations by 2050. Applied energy, 281, Article 116062. https://doi.org/10.1016/j.apenergy.2020.116062

The empirical success of the Artificial Intelligence (AI), has enhanced importance of the transparency in black box Machine Learning (ML) models. This study pioneers in developing an explainable and interpretable Deep Neural Network (DNN) model for a... Read More about Hourly performance forecast of a dew point cooler using explainable Artificial Intelligence and evolutionary optimisations by 2050.

Effect of IDT position parameters on SAW yarn tension sensor sensitivity (2020)
Journal Article
Lei, B., Lu, W., Mian, Z., & Bao, W. (2020). Effect of IDT position parameters on SAW yarn tension sensor sensitivity. Measurement and Control, 53(9-10), 2055-2062. https://doi.org/10.1177/0020294020965620

In this paper, the effect of the interdigital transducer (IDT) position parameters on the surface acoustic wave (SAW) yarn tension sensor sensitivity is investigated. The stress–strain characteristic of substrate was studied by the combination of fin... Read More about Effect of IDT position parameters on SAW yarn tension sensor sensitivity.

GANS-based data augmentation for citrus disease severity detection using deep learning (2020)
Journal Article
Zeng, Q., Ma, X., Cheng, B., Zhou, E., & Pang, W. (2020). GANS-based data augmentation for citrus disease severity detection using deep learning. IEEE Access, 8, 172882-172891. https://doi.org/10.1109/ACCESS.2020.3025196

Recently, many Deep Learning models have been employed to classify different kinds of plant diseases, but very little work has been done for disease severity detection. However, it is more important to master the severities of plant diseases accurate... Read More about GANS-based data augmentation for citrus disease severity detection using deep learning.

Predictive control using active aerodynamic surfaces to improve ride quality of a vehicle (2020)
Journal Article
Ahmad, E., Iqbal, J., Khan, M. A., Liang, W., & Youn, I. (2020). Predictive control using active aerodynamic surfaces to improve ride quality of a vehicle. Electronics, 9(9), Article 1463. https://doi.org/10.3390/electronics9091463

This work presents a predictive control strategy for a four degrees of freedom (DOF) half-car model in the presence of active aerodynamic surfaces. The proposed control strategy consists of two parts: the feedback control deals with the tracking erro... Read More about Predictive control using active aerodynamic surfaces to improve ride quality of a vehicle.