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Evaluating floating photovoltaics (FPVs) potential in providing clean energy and supporting agricultural growth in Vietnam (2022)
Journal Article
Pouran, H., Padilha Campos Lopes, M., Ziar, H., Alves Castelo Branco, D., & Sheng, Y. (2022). Evaluating floating photovoltaics (FPVs) potential in providing clean energy and supporting agricultural growth in Vietnam. Renewable & sustainable energy reviews, 169, Article 112925. https://doi.org/10.1016/j.rser.2022.112925

Vietnam's promising economic growth has led to energy shortage, growing coal imports, and increasing carbon emissions. The country's electricity demand annual growth rate has been 12% in recent years and is projected to be 8–9% by 2030. In Vietnam 40... Read More about Evaluating floating photovoltaics (FPVs) potential in providing clean energy and supporting agricultural growth in Vietnam.

The role of ‘living laboratories’ in accelerating the energy system decarbonization (2022)
Journal Article
Fan, Z., Cao, J., Jamal, T., Fogwill, C., Samende, C., Robinson, Z., …Healey, D. (2022). The role of ‘living laboratories’ in accelerating the energy system decarbonization. Energy Reports, 8, 11858-11864. https://doi.org/10.1016/j.egyr.2022.09.046

To decarbonize the energy system by the year 2050, it is crucial that innovations are trialled in a ‘real world’ setting for the purpose of increasing public adoption and support, and for providing insights to decision-makers to ensure their decision... Read More about The role of ‘living laboratories’ in accelerating the energy system decarbonization.

A Reinforcement Learning-based Assignment Scheme for EVs to Charging Stations (2022)
Conference Proceeding
Aljaidi, M., Aslam, N., Chen, X., Kaiwartya, O., Al-Gumaei, A., & Khalid, M. (2022). A Reinforcement Learning-based Assignment Scheme for EVs to Charging Stations. In IEEE 95th Vehicular Technology Conference: VTC2022-Spring. https://doi.org/10.1109/VTC2022-Spring54318.2022.9860535

Due to recent developments in electric mobility, public charging infrastructure will be essential for modern transportation systems. As the number of electric vehicles (EVs) increases, the public charging infrastructure needs to adopt efficient charg... Read More about A Reinforcement Learning-based Assignment Scheme for EVs to Charging Stations.

Automated Question-Answering for Interactive Decision Support in Operations & Maintenance of Wind Turbines (2022)
Journal Article
Chatterjee, J., & Dethlefs, N. (2022). Automated Question-Answering for Interactive Decision Support in Operations & Maintenance of Wind Turbines. IEEE Access, 10, 84710-84737. https://doi.org/10.1109/ACCESS.2022.3197167

Intelligent question-answering (QA) systems have witnessed increased interest in recent years, particularly in their ability to facilitate information access, data interpretation or decision support. The wind energy sector is one of the most promisin... Read More about Automated Question-Answering for Interactive Decision Support in Operations & Maintenance of Wind Turbines.

Increasing Engagement Through Explicit and Implicit Gamification in Higher Education (2022)
Book Chapter
Gordon, N., & Grey, S. (2022). Increasing Engagement Through Explicit and Implicit Gamification in Higher Education. In O. Bernardes, V. Amorim, & A. Carrizo Moreira (Eds.), Handbook of Research on the Influence and Effectiveness of Gamification in Education (662-681). Hershey, Pa.: IGI Global. https://doi.org/10.4018/978-1-6684-4287-6

Engagement is essential in higher education but can be problematic to achieve. Successful games are, at their core, designed to be engaging experiences. In attempts to increase engagement in learning, there has been an increase in playful learning, g... Read More about Increasing Engagement Through Explicit and Implicit Gamification in Higher Education.

Synchronous Multi-User Cross-Platform Virtual Reality for School Teachers (2022)
Conference Proceeding
Kambili-Mzembe, F., & Gordon, N. A. (2022). Synchronous Multi-User Cross-Platform Virtual Reality for School Teachers. In Proceedings of the 8th International Conference of the Immersive Learning Research Network (iLRN). https://doi.org/10.23919/iLRN55037.2022.9815966

Motivated by a desire to apply Computer Science and Virtual Reality (VR) technology due to the need for improving secondary school education in Malawi, this paper presents a prototype of a synchronous multi-user cross-platform real-time 3D VR applica... Read More about Synchronous Multi-User Cross-Platform Virtual Reality for School Teachers.

Characterization and calibration of multiple 2D laser scanners (2022)
Journal Article
Riaz un Nabi Jafri, S., Shamim, S., Faraz, S. M., Ahmed, A., Yasir, S. M., & Iqbal, J. (2022). Characterization and calibration of multiple 2D laser scanners. PLoS ONE, 17(7), Article e0272063. https://doi.org/10.1371/journal.pone.0272063

This paper presents the comparative evaluation of multiple compact and lightweight 2D laser scanners for their possible backpack based scanning and mapping applications. These scanners include Hokuyo URG-04LX, Slamtec RPLidar A1-M8 and Hokuyo UTM- 30... Read More about Characterization and calibration of multiple 2D laser scanners.

The HDIN dataset: A Real-world Indoor UAV Dataset with Multi-task Labels for Visual-based Navigation (2022)
Dataset
Chang, Y., Cheng, Y., Murray, J., Huang, S., & Shi, G. (2022). The HDIN dataset: A Real-world Indoor UAV Dataset with Multi-task Labels for Visual-based Navigation. [Dataset]

The dataset contains image samples and Multi-task labels (i.e., regression and classification labels) collected from onboard UAV sensors in real-world indoor environments. By transforming the original labels following the instructions at: https://git... Read More about The HDIN dataset: A Real-world Indoor UAV Dataset with Multi-task Labels for Visual-based Navigation.

Dynamic risk stratification using Markov chain modelling in patients with chronic heart failure (2022)
Journal Article
Kazmi, S., Kambhampati, C., Cleland, J., Cuthbert, J., Kazmi, K. S., Pellicori, P., …Clark, A. L. (2022). Dynamic risk stratification using Markov chain modelling in patients with chronic heart failure. ESC Heart Failure, https://doi.org/10.1002/ehf2.14028

Aims: Risk changes with the progression of disease and the impact of treatment. We developed a dynamic risk stratification Markov chain model using artificial intelligence in patients with chronic heart failure (CHF). Methods and results: We describe... Read More about Dynamic risk stratification using Markov chain modelling in patients with chronic heart failure.

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.