Outputs (4095)

Exploring coupled images fusion based on joint tensor decomposition (2020)
Journal Article
Lu, L., Ren, X., Yeh, K.-H., Tan, Z., & Chanussot, J. (2020). Exploring coupled images fusion based on joint tensor decomposition. Human-Centric Computing and Information Sciences, 10, Article 10 (2020). https://doi.org/10.1186/s13673-020-00215-z

Data fusion has always been a hot research topic in human-centric computing and extended with the development of artificial intelligence. Generally, the coupled data fusion algorithm usually utilizes the information from one data set to improve the e... Read More about Exploring coupled images fusion based on joint tensor decomposition.

Machine Learning for Detecting Drift Fault of Sensors in Cyber-Physical Systems (2020)
Presentation / Conference Contribution
Jan, S. U., Saeed, U., & Koo, I. (2020, January). Machine Learning for Detecting Drift Fault of Sensors in Cyber-Physical Systems. Presented at 2020 17th International Bhurban Conference on Applied Sciences and Technology (IBCAST), Islamabad, Pakistan

Cyber-Physical System (CPS) emerges as a potential direction to improve the applications relating to object-to-object, human-to-human and human-to-object communications in both the real world and virtual world. The examples of CPSs include Smart Gird... Read More about Machine Learning for Detecting Drift Fault of Sensors in Cyber-Physical Systems.

Workshop report for DISIPRAC: Digital identity security information practices of citizens (March 2020) (2020)
Report
Cruickshank, P., & Ryan, F. (2020). Workshop report for DISIPRAC: Digital identity security information practices of citizens (March 2020). Edinburgh: Edinburgh Napier University

The report reflects the outcome of a workshop with practitioners held on 27 February 2020. It is aimed at practitioners and policy makers, and gives some evidence of a number of issues around management of digital identities (including a few scenario... Read More about Workshop report for DISIPRAC: Digital identity security information practices of citizens (March 2020).

A Formal Technique for Composing Cloud Services (2020)
Journal Article
Barati, M. (2020). A Formal Technique for Composing Cloud Services. Information Technology and Control, 49(1), 5-27. https://doi.org/10.5755/j01.itc.49.1.23403

Recent cloud search engines lack a formal method in their service composition mechanisms to automatically build composite services realizing user requirements. This paper prescribes behavior composition framework as a formal tools for the search engi... Read More about A Formal Technique for Composing Cloud Services.

Degree apprenticeships - a win-win model? A comparison of policy aims with the expectations and experiences of apprentices (2020)
Journal Article
Smith, S., Caddell, M., Taylor-Smith, E., Smith, C., & Varey, A. (2022). Degree apprenticeships - a win-win model? A comparison of policy aims with the expectations and experiences of apprentices. Journal of Vocational Education and Training, 73(4), 505-525. https://doi.org/10.1080/13636820.2020.1744690

This article compares policy aims with experiences following the introduction of a new model for STEM apprenticeships in the UK. Degree apprentices work while studying for a degree, undertaking work-based learning and attending on-campus classes. Spe... Read More about Degree apprenticeships - a win-win model? A comparison of policy aims with the expectations and experiences of apprentices.

P4ID: P4 enhanced intrusion detection (2020)
Presentation / Conference Contribution
Lewis, B., Broadbent, M., & Race, N. (2019, November). P4ID: P4 enhanced intrusion detection. Presented at 2019 IEEE Conference on Network Function Virtualization and Software Defined Networks (NFV-SDN), Dallas, TX, USA

The growth in scale and capacity of networks in recent years leads to challenges of positioning and scalability of Intrusion Detection Systems (IDS). With the flexibility afforded by programmable dataplanes, it is now possible to perform a new level... Read More about P4ID: P4 enhanced intrusion detection.

Improved Particle Swarm Optimization for Sea Surface Temperature Prediction (2020)
Journal Article
He, Q., Zha, C., Song, W., Hao, Z., Du, Y., Liotta, A., & Perra, C. (2020). Improved Particle Swarm Optimization for Sea Surface Temperature Prediction. Energies, 13(6), Article 1369. https://doi.org/10.3390/en13061369

The Sea Surface Temperature (SST) is one of the key factors affecting ocean climate change. Hence, Sea Surface Temperature Prediction (SSTP) is of great significance to the study of navigation and meteorology. However, SST data is well-known to suffe... Read More about Improved Particle Swarm Optimization for Sea Surface Temperature Prediction.

Novel deep neural network based pattern field classification architectures (2020)
Journal Article
Huang, K., Zhang, S., Zhang, R., & Hussain, A. (2020). Novel deep neural network based pattern field classification architectures. Neural Networks, 127, 82-95. https://doi.org/10.1016/j.neunet.2020.03.011

Field classification is a new extension of traditional classification frameworks that attempts to utilize consistent information from a group of samples (termed fields). By forgoing the independent identically distributed (i.i.d.) assumption, field c... Read More about Novel deep neural network based pattern field classification architectures.

Routing Schemes in Software-Defined Vehicular Networks: Design, Open Issues and Challenges (2020)
Journal Article
Zhao, L., Al-Dubai, A., Zomaya, A. Y., Min, G., Hawbani, A., & Li, J. (2021). Routing Schemes in Software-Defined Vehicular Networks: Design, Open Issues and Challenges. IEEE Intelligent Transportation Systems Magazine, 13(4), 217-226. https://doi.org/10.1109/MITS.2019.2953557

Software-defined vehicular networks (SDVN) is a promising technology to overcome the limitations of current vehicular networking. However, existing vehicular routing schemes are not equipped to handle communication in SDVNs. In addition, routing sche... Read More about Routing Schemes in Software-Defined Vehicular Networks: Design, Open Issues and Challenges.

Quantum GestART: identifying and applying correlations between mathematics, art, and perceptual organization (2020)
Journal Article
Mannone, M., Favali, F., Di Donato, B., & Turchet, L. (2021). Quantum GestART: identifying and applying correlations between mathematics, art, and perceptual organization. Journal of Mathematics and Music, 15(1), 62-94. https://doi.org/10.1080/17459737.2020.1726691

Mathematics can help analyze the arts and inspire new artwork. Mathematics can also help make transformations from one artistic medium to another, considering exceptions and choices, as well as artists' individual and unique contributions. We propose... Read More about Quantum GestART: identifying and applying correlations between mathematics, art, and perceptual organization.