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Outputs (4095)

Energy demand prediction through novel random neural network predictor for large non-domestic buildings (2017)
Presentation / Conference Contribution
Ahmad, J., Larijani, H., Emmanuel, R., Mannion, M., Javed, A., & Phillipson, M. (2017, April). Energy demand prediction through novel random neural network predictor for large non-domestic buildings. Presented at 2017 Annual IEEE International Systems Conference (SysCon), Montreal, QC, Canada

Buildings are among the largest consumers of energy in the world. In developed countries, buildings currently consumes 40% of the total energy and 51% of total electricity consumption. Energy prediction is a key factor in reducing energy wastage. Thi... Read More about Energy demand prediction through novel random neural network predictor for large non-domestic buildings.

SCIPS: Using Experiential Learning to Raise Cyber Situational Awareness in Industrial Control System (2017)
Journal Article
Cook, A., Smith, R. G., Maglaras, L., & Janicke, H. (2017). SCIPS: Using Experiential Learning to Raise Cyber Situational Awareness in Industrial Control System. International Journal of Cyber Warfare and Terrorism, 7(2), Article 1. https://doi.org/10.4018/ijcwt.2017040101

The cyber threat to industrial control systems is an acknowledged security issue, but a qualified dataset to quantify the risk remains largely unavailable. Senior executives of facilities that operate these systems face competing requirements for inv... Read More about SCIPS: Using Experiential Learning to Raise Cyber Situational Awareness in Industrial Control System.

Communicating Connected Components: Extending Plug-and-Play to Support Skeletons (2017)
Presentation / Conference Contribution
Chalmers, K., Kerridge, J., & Pedersen, J. B. (2016, August). Communicating Connected Components: Extending Plug-and-Play to Support Skeletons. Presented at Communicating Process Architectures 2016, Copenhagen, Denmark

For a number of years, the Communicating Process Architecture (CPA) community have developed languages and runtimes supporting message passing concurrency. For these we always provide a set of reusable processes called plug and play. These components... Read More about Communicating Connected Components: Extending Plug-and-Play to Support Skeletons.

Secure speech communication algorithm via DCT and TD-ERCS chaotic map (2017)
Presentation / Conference Contribution
Habib, Z., Khan, J. S., Ahmad, J., Khan, M. A., & Khan, F. A. (2017, April). Secure speech communication algorithm via DCT and TD-ERCS chaotic map. Presented at 2017 4th International Conference on Electrical and Electronic Engineering (ICEEE), Ankara, Turkey

Secure communication has always been a demanding area in civil, commercial and particularly in military set up. Robust and time-tested efficient algorithms are needed to have an essential privacy for speech transmission in the telephone networks, rad... Read More about Secure speech communication algorithm via DCT and TD-ERCS chaotic map.

Estimating 3D trajectories from 2D projections via disjunctive factored four-way conditional restricted Boltzmann machines (2017)
Journal Article
Mocanu, D. C., Bou Ammar, H., Puig, L., Eaton, E., & Liotta, A. (2017). Estimating 3D trajectories from 2D projections via disjunctive factored four-way conditional restricted Boltzmann machines. Pattern Recognition, 69, 325-335. https://doi.org/10.1016/j.patcog.2017.04.017

Estimation, recognition, and near-future prediction of 3D trajectories based on their two dimensional projections available from one camera source is an exceptionally difficult problem due to uncertainty in the trajectories and environment, high dime... Read More about Estimating 3D trajectories from 2D projections via disjunctive factored four-way conditional restricted Boltzmann machines.

Dual-branch deep convolution neural network for polarimetric SAR image classification (2017)
Journal Article
Gao, F., Huang, T., Wang, J., Sun, J., Hussain, A., & Yang, E. (2017). Dual-branch deep convolution neural network for polarimetric SAR image classification. Applied Sciences, 7(5), https://doi.org/10.3390/app7050447

The deep convolution neural network (CNN), which has prominent advantages in feature learning, can learn and extract features from data automatically. Existing polarimetric synthetic aperture radar (PolSAR) image classification methods based on the C... Read More about Dual-branch deep convolution neural network for polarimetric SAR image classification.

A novel image encryption scheme based on orthogonal matrix, skew tent map, and XOR operation (2017)
Journal Article
Ahmad, J., Khan, M. A., Ahmed, F., & Khan, J. S. (2018). A novel image encryption scheme based on orthogonal matrix, skew tent map, and XOR operation. Neural Computing and Applications, 30(12), 3847-3857. https://doi.org/10.1007/s00521-017-2970-3

Content protection is considered as an important issue in today’s world. Therefore, encryption of such contents is a challenging task for researchers. They are focusing on protection of valuable data such as image, video, and audio against different... Read More about A novel image encryption scheme based on orthogonal matrix, skew tent map, and XOR operation.

E-Government and the Digital Divide: A Study of English-as-a-Second-Language Users’ Information Behaviour (2017)
Presentation / Conference Contribution
Brazier, D., & Harvey, M. (2017, April). E-Government and the Digital Divide: A Study of English-as-a-Second-Language Users’ Information Behaviour. Presented at 39th European Conference on IR Research, ECIR 2017, Aberdeen, UK

Internet-based technologies are increasingly used by organisations and governments to offer services to consumers and the public in a quick and efficient manner, removing the need for face-to-face conversations and human advisors. Despite their obvio... Read More about E-Government and the Digital Divide: A Study of English-as-a-Second-Language Users’ Information Behaviour.

Rapid one-shot acquisition of dynamic VR avatars (2017)
Presentation / Conference Contribution
Malleson, C., Kosek, M., Klaudiny, M., Huerta, I., Bazin, J.-C., Sorkine-Hornung, A., Mine, M., & Mitchell, K. (2017, March). Rapid one-shot acquisition of dynamic VR avatars. Presented at 2017 IEEE Virtual Reality (VR), Los Angeles, US

We present a system for rapid acquisition of bespoke, animatable, full-body avatars including face texture and shape. A blendshape rig with a skeleton is used as a template for customization. Identity blendshapes are used to customize the body and fa... Read More about Rapid one-shot acquisition of dynamic VR avatars.