All Outputs (653)

Prediction of Critical Flashover Voltage of High Voltage Insulators Leveraging Bootstrap Neural Network (2020)
Journal Article
Niazi, M. T. K., Arshad, Ahmad, J., Alqahtani, F., Baotham, F. A., & Abu-Amara, F. (2020). Prediction of Critical Flashover Voltage of High Voltage Insulators Leveraging Bootstrap Neural Network. Electronics, 9(10), Article 1620. https://doi.org/10.3390/electronics9101620

Understanding the flashover performance of the outdoor high voltage insulator has been in the interest of many researchers recently. Various studies have been performed to investigate the critical flashover voltage of outdoor high voltage insulators... Read More about Prediction of Critical Flashover Voltage of High Voltage Insulators Leveraging Bootstrap Neural Network.

EEG-Based Neonatal Sleep-Wake Classification Using Multilayer Perceptron Neural Network (2020)
Journal Article
Abbasi, S. F., Ahmad, J., Tahir, A., Awais, M., Chen, C., Irfan, M., Siddiqa, H. A., Waqas, A. B., Long, X., Yin, B., Akbarzadeh, S., Lu, C., Wang, L., & Chen, W. (2020). EEG-Based Neonatal Sleep-Wake Classification Using Multilayer Perceptron Neural Network. IEEE Access, 8, 183025-183034. https://doi.org/10.1109/access.2020.3028182

Objective: Classification of sleep-wake states using multichannel electroencephalography (EEG) data that reliably work for neonates. Methods: A deep multilayer perceptron (MLP) neural network is developed to classify sleep-wake states using multichan... Read More about EEG-Based Neonatal Sleep-Wake Classification Using Multilayer Perceptron Neural Network.

Mechanism of enhanced energy storage density in AgNbO3-based lead-free antiferroelectrics (2020)
Journal Article
Lu, Z., Bao, W., Wang, G., Sun, S., Li, L., Li, J., …Reaney, I. M. (2021). Mechanism of enhanced energy storage density in AgNbO3-based lead-free antiferroelectrics. Nano Energy, 79, Article 105423. https://doi.org/10.1016/j.nanoen.2020.105423

The mechanisms underpinning high energy storage density in lead-free Ag1–3xNdxTayNb1-yO3 antiferroelectric (AFE) ceramics have been investigated. Rietveld refinements of in-situ synchrotron X-ray data reveal that the structure remains quadrupled and... Read More about Mechanism of enhanced energy storage density in AgNbO3-based lead-free antiferroelectrics.

Development of a BIM-enabled and Cloud-based Sustainability Assessment System for Buildings in Sub-Saharan Africa: The Case of Nigeria (2020)
Thesis
Olawumi, T. O. (2020). Development of a BIM-enabled and Cloud-based Sustainability Assessment System for Buildings in Sub-Saharan Africa: The Case of Nigeria. (Thesis). Hong Kong Polytechnic University. http://researchrepository.napier.ac.uk/Output/2804043

The increasing urbanization of the built environment has bolstered the need of promoting sustainable practices and Building Information Modelling (BIM) initiative in building and construction projects. However, there has not been a unified adoption a... Read More about Development of a BIM-enabled and Cloud-based Sustainability Assessment System for Buildings in Sub-Saharan Africa: The Case of Nigeria.

Identification of a Speaker from Characteristics of a Voice (2020)
Journal Article
Kinkiri, S., Bakarat, B., & Keates, S. (2020). Identification of a Speaker from Characteristics of a Voice. Sensors & transducers, 244(5), 7-12

Speech is unique mode of communication among humans. Speech is a complex method of communication systems when compared with other methods. As humans, we also use non-speech, which is non-verbal communication to convey information. Nonverbal communica... Read More about Identification of a Speaker from Characteristics of a Voice.

A Novel Intelligent Computational Approach to Model Epidemiological Trends and Assess the Impact of Non-Pharmacological Interventions for COVID-19 (2020)
Journal Article
Ren, J., Yan, Y., Zhao, H., Ma, P., Zabalza, J., Hussain, Z., Luo, S., Dai, Q., Zhao, S., Sheikh, A., Hussain, A., & Li, H. (2020). A Novel Intelligent Computational Approach to Model Epidemiological Trends and Assess the Impact of Non-Pharmacological Interventions for COVID-19. IEEE Journal of Biomedical and Health Informatics, 24(12), 3551-3563. https://doi.org/10.1109/JBHI.2020.3027987

The novel coronavirus disease 2019 (COVID-19) pandemic has led to a worldwide crisis in public health. It is crucial we understand the epidemiological trends and impact of non-pharmacological interventions (NPIs), such as lockdowns for effective mana... Read More about A Novel Intelligent Computational Approach to Model Epidemiological Trends and Assess the Impact of Non-Pharmacological Interventions for COVID-19.

Futures Thinking: The case of ECOR (2020)
Journal Article
Logtens, E., & Weigend Rodríguez, R. (2021). Futures Thinking: The case of ECOR. Journal of Futures Studies, 25(4), 97-110. https://doi.org/10.6531/JFS.202106_25%284%29.0009

This interview is part of a research project which aims to formulate an interdisciplinary systematic approach based on Circular Economy (CE) principles and Futures Studies (FS) methods for anticipatory decision making in SMEs. The interest in intervi... Read More about Futures Thinking: The case of ECOR.

Offsite Ready Booklets (2020)
Report
Duncheva, M., Calcagno, C., Henquel, V., Leitch, K., Stinson, J., Plant O'Toole, E., Bros-Williamson, J., Livingstone, A., De Saint-Sernin, A., Hairstans, R., Hillier, J., Bentley, A., Barran, R., Avins, L., Setiati, D., Richards, L., & Ferriz-Papi, J. A. (2020). Offsite Ready Booklets. Edinburgh: Construction Industry Training Board

Visual Encodings for Networks with Multiple Edge Types (2020)
Presentation / Conference Contribution
Vogogias, T., Archambault, D. W., Bach, B., & Kennedy, J. (2020, October). Visual Encodings for Networks with Multiple Edge Types. Presented at International Conference on Advanced Visual Interfaces, Napkes, Italy

This paper reports on a formal user study on visual encodings of networks with multiple edge types in adjacency matrices. Our tasks and conditions were inspired by real problems in computational biology. We focus on encodings in adjacency matrices, s... Read More about Visual Encodings for Networks with Multiple Edge Types.

Technology acceptance and perceptions of robotic assistive devices by older adults – implications for exoskeleton design (2020)
Journal Article
Shore, L., de Eyto, A., & O’Sullivan, L. (2022). Technology acceptance and perceptions of robotic assistive devices by older adults – implications for exoskeleton design. Disability and Rehabilitation: Assistive Technology, 17(7), 782-790. https://doi.org/10.1080/17483107.2020.1817988

Aim This study explored and interpreted insights expressed by a cohort of older adults related to their life experience, their experiences using or assisting someone with assistive devices, and their perceptions of robots and robotic assistive devic... Read More about Technology acceptance and perceptions of robotic assistive devices by older adults – implications for exoskeleton design.

A Sensory Similarities Approach to Load Disaggregation of Charging Stations in Internet of Electric Vehicles (2020)
Journal Article
Liu, Q., Kamoto, K. M., Liu, X., Zhang, Y., Yang, Z., Khosravi, M. R., Xu, Y., & Qi, L. (2021). A Sensory Similarities Approach to Load Disaggregation of Charging Stations in Internet of Electric Vehicles. IEEE Sensors Journal, 21(14), 15895-15903. https://doi.org/10.1109/jsen.2020.3027684

Intelligent transportation systems (ITSs) have become popular in recent years as an essential requirement for safer and more efficient transportation systems. Internet of Electric vehicles (IoEV) as well as their hybrid forms provide an ideal means o... Read More about A Sensory Similarities Approach to Load Disaggregation of Charging Stations in Internet of Electric Vehicles.

A robust and computationally efficient finite element framework for coupled electromechanics (2020)
Journal Article
Kadapa, C., & Hossain, M. (2020). A robust and computationally efficient finite element framework for coupled electromechanics. Computer Methods in Applied Mechanics and Engineering, 372, Article 113443. https://doi.org/10.1016/j.cma.2020.113443

Electro-active polymers (EAPs) are increasingly becoming popular materials for actuators, sensors, and energy harvesters. To simulate the complex behaviour of actuators under coupled loads, particularly in the realm of soft robotics, biomedical engin... Read More about A robust and computationally efficient finite element framework for coupled electromechanics.

Federated learning with hierarchical clustering of local updates to improve training on non-IID data (2020)
Presentation / Conference Contribution
Briggs, C., Fan, Z., & Andras, P. (2020, July). Federated learning with hierarchical clustering of local updates to improve training on non-IID data. Presented at 2020 International Joint Conference on Neural Networks (IJCNN), Glasgow

Federated learning (FL) is a well established method for performing machine learning tasks over massively distributed data. However in settings where data is distributed in a non-iid (not independent and identically distributed) fashion - as is typic... Read More about Federated learning with hierarchical clustering of local updates to improve training on non-IID data.

Deep Neural Network Driven Binaural Audio Visual Speech Separation (2020)
Presentation / Conference Contribution
Gogate, M., Dashtipour, K., Bell, P., & Hussain, A. (2020, July). Deep Neural Network Driven Binaural Audio Visual Speech Separation. Presented at 2020 International Joint Conference on Neural Networks (IJCNN), Glasgow

The central auditory pathway exploits the auditory signals and visual information sent by both ears and eyes to segregate speech from multiple competing noise sources and help disambiguate phonological ambiguity. In this study, inspired from this uni... Read More about Deep Neural Network Driven Binaural Audio Visual Speech Separation.

Real-time anomaly intrusion detection for a clean water supply system, utilising machine learning with novel energy-based features (2020)
Presentation / Conference Contribution
Robles-Durazno, A., Moradpoor, N., McWhinnie, J., & Russell, G. (2020, July). Real-time anomaly intrusion detection for a clean water supply system, utilising machine learning with novel energy-based features. Presented at International Joint Conference on Neural Networks (IJCNN 2020), Glasgow, UK

Industrial Control Systems have become a priority domain for cybersecurity practitioners due to the number of cyber-attacks against those systems has increased over the past few years. This paper proposes a real-time anomaly intrusion detector for a... Read More about Real-time anomaly intrusion detection for a clean water supply system, utilising machine learning with novel energy-based features.

A Novel Approach to Shadow Boundary Detection Based on an Adaptive Direction-Tracking Filter for Brain-Machine Interface Applications (2020)
Journal Article
Ju, Z., Gun, L., Hussain, A., Mahmud, M., & Ieracitano, C. (2020). A Novel Approach to Shadow Boundary Detection Based on an Adaptive Direction-Tracking Filter for Brain-Machine Interface Applications. Applied Sciences, 10(19), Article 6761. https://doi.org/10.3390/app10196761

In this paper, a Brain-Machine Interface (BMI) system is proposed to automatically control the navigation of wheelchairs by detecting the shadows on their route. In this context, a new algorithm to detect shadows in a single image is proposed. Specif... Read More about A Novel Approach to Shadow Boundary Detection Based on an Adaptive Direction-Tracking Filter for Brain-Machine Interface Applications.

Implementing Deep Learning Techniques in 5G IoT Networks for 3D Indoor Positioning: DELTA (DeEp Learning-Based Co-operaTive Architecture) (2020)
Journal Article
El Boudani, B., Kanaris, L., Kokkinis, A., Kyriacou, M., Chrysoulas, C., Stavrou, S., & Dagiuklas, T. (2020). Implementing Deep Learning Techniques in 5G IoT Networks for 3D Indoor Positioning: DELTA (DeEp Learning-Based Co-operaTive Architecture). Sensors, 20(19), Article 5495. https://doi.org/10.3390/s20195495

In the near future, the fifth-generation wireless technology is expected to be rolled out, offering low latency, high bandwidth and multiple antennas deployed in a single access point. This ecosystem will help further enhance various location-based s... Read More about Implementing Deep Learning Techniques in 5G IoT Networks for 3D Indoor Positioning: DELTA (DeEp Learning-Based Co-operaTive Architecture).

A novel automatic classification system based on hybrid unsupervised and supervised machine learning for electrospun nanofibers (2020)
Journal Article
Ieracitano, C., Paviglianiti, A., Campolo, M., Hussain, A., Pasero, E., & Carlo Morabito, F. (2021). A novel automatic classification system based on hybrid unsupervised and supervised machine learning for electrospun nanofibers. IEEE/CAA Journal of Automatica Sinica, 8(1), 64-76. https://doi.org/10.1109/JAS.2020.1003387

The manufacturing of nanomaterials by the electrospinning process requires accurate and meticulous inspection of related scanning electron microscope ( SEM ) images of the electrospun nanofiber, to ensure that no structural defects are produced. The... Read More about A novel automatic classification system based on hybrid unsupervised and supervised machine learning for electrospun nanofibers.

A Novel Cost Optimization Strategy for SDN-Enabled UAV-Assisted Vehicular Computation Offloading (2020)
Journal Article
Zhao, L., Yang, K., Tan, Z., Li, X., Sharma, S., & Liu, Z. (2021). A Novel Cost Optimization Strategy for SDN-Enabled UAV-Assisted Vehicular Computation Offloading. IEEE Transactions on Intelligent Transportation Systems, 22(6), 3664-3674. https://doi.org/10.1109/TITS.2020.3024186

Vehicular computation offloading is a well-received strategy to execute delay-sensitive and/or compute-intensive tasks of legacy vehicles. The response time of vehicular computation offloading can be shortened by using mobile edge computing that offe... Read More about A Novel Cost Optimization Strategy for SDN-Enabled UAV-Assisted Vehicular Computation Offloading.

Emplacement of screen-printed graphene oxide coating for building thermal comfort discernment (2020)
Journal Article
Roy, A., Ghosh, A., Benson, D., Mallick, T. K., & Sundaram, S. (2020). Emplacement of screen-printed graphene oxide coating for building thermal comfort discernment. Scientific Reports, 10, Article 15578. https://doi.org/10.1038/s41598-020-72670-8

This study demonstrates the development of flexible graphene oxide coatings (GOCs) by the screen-printed technique and further its implementation as a thermal absorber for buildings’ thermal comfort purpose. The basic concept consists the integration... Read More about Emplacement of screen-printed graphene oxide coating for building thermal comfort discernment.