Outputs (293)

Social media as facilitators of tacit knowledge sharing practices amongst public sector employees (2020)
Thesis
Buunk, I. Social media as facilitators of tacit knowledge sharing practices amongst public sector employees. (Thesis). Edinburgh Napier University. Retrieved from http://researchrepository.napier.ac.uk/Output/2709057

This work is concerned with the exploration of social technologies relevant to the sharing of tacit knowledge within the public sector. The findings derive from analysis of empirical data collected via survey research and twenty qualitative interview... Read More about Social media as facilitators of tacit knowledge sharing practices amongst public sector employees.

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/e

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., …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.

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., …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

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.

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

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:

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.

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). Federated learning with hierarchical clustering of local updates to improve training on non-IID data. In 2020 International Joint Conference on Neural Networks (IJCNN). https://doi.org/10.1109/IJCNN48605.2020.920

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 o

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.