Outputs (4095)

The role of networking and social media tools during job search: an information behaviour perspective (2017)
Presentation / Conference Contribution
Mowbray, J., Hall, H., Raeside, R., & Robertson, P. (2016, June). The role of networking and social media tools during job search: an information behaviour perspective. Presented at Ninth International Conference on Conceptions of Library and Information Science, Uppsala, Sweden

Introduction. The paper presents a critical analysis of the extant literature pertaining to the networking behaviour of young jobseekers in both offline and online environments. A framework derived from information behaviour theory is proposed as a b... Read More about The role of networking and social media tools during job search: an information behaviour perspective.

5G innovations for new business opportunities (2017)
Report
Sébastien Bedo, J., Eddine El Ayoubi, S., Filippou, M., Gavras, A., Giustiniano, D., Iovanna, P., Manzalini, A., Queseth, O., Rokkas, T., Surridge, M., & Tjelta, T. (2017). 5G innovations for new business opportunities. Brussels: European Commission / 5G PPP

5G is the next generation mobile network that enables
innovation and supports progressive change across all
vertical industries and across our society1. Through its
Radio Access Network (RAN) design and its orchestrated
end-to-end architecture, i... Read More about 5G innovations for new business opportunities.

An Enhanced Route from FE to HE Graduation? (2017)
Journal Article
Meharg, D., Taylor-Smith, E., Varey, A., Mooney, C., & Dallas, S. (2017). An Enhanced Route from FE to HE Graduation?. Journal of Perspectives in Applied Academic Practice, 5(2), 85-92. https://doi.org/10.14297/jpaap.v5i2.269

This study explores student transitions from further (FE) to higher (HE) education through the Associate Student Project (ASP) and examines the effectiveness of this enhanced transition programme for direct entry students. Universities are expected t... Read More about An Enhanced Route from FE to HE Graduation?.

Application of Navigating System based on Bluetooth Smart (2017)
Journal Article
Lee, Y., Jan, S. U., & Koo, I. (2017). Application of Navigating System based on Bluetooth Smart. Journal of the Institute of Internet, Broadcasting and Communication, 17(1), 69-76. https://doi.org/10.7236/jiibc.2017.17.1.69

Bluetooth Low Energy (BLE), also known as Bluetooth Smart, has ultra-low power consumption; in fact, BLE-enabled devices can run on a single coin cell battery for several years. In addition, BLE can estimate the approximate distance between two devi... Read More about Application of Navigating System based on Bluetooth Smart.

An Adaptively Speculative Execution Strategy Based on Real-Time Resource Awareness in a Multi-Job Heterogeneous Environment (2017)
Journal Article
Liu, Q., Cai, W., Liu, Q., Shen, J., Fu, Z., Liu, X., & Linge, N. (2017). An Adaptively Speculative Execution Strategy Based on Real-Time Resource Awareness in a Multi-Job Heterogeneous Environment. KSII transactions on internet and information systems, 11(2), https://doi.org/10.3837/tiis.2017.02.004

MapReduce (MRV1), a popular programming model, proposed by Google, has been well used to process large datasets in Hadoop, an open source cloud platform. Its new version MapReduce 2.0 (MRV2) developed along with the emerging of Yarn has achieved obvi... Read More about An Adaptively Speculative Execution Strategy Based on Real-Time Resource Awareness in a Multi-Job Heterogeneous Environment.

Lung cancer detection using Local Energy-based Shape Histogram (LESH) feature extraction and cognitive machine learning techniques (2017)
Presentation / Conference Contribution
Wajid, S., Hussain, A., Huang, K., & Boulila, W. (2016, August). Lung cancer detection using Local Energy-based Shape Histogram (LESH) feature extraction and cognitive machine learning techniques. Presented at 2016 IEEE 15th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC), Palo Alto, CA, USA

The novel application of Local Energy-based Shape Histogram (LESH) feature extraction technique was recently proposed for breast cancer diagnosis using mammogram images [22]. This paper extends our original work to apply the LESH technique to detect... Read More about Lung cancer detection using Local Energy-based Shape Histogram (LESH) feature extraction and cognitive machine learning techniques.

The Greater The Power, The More Dangerous The Abuse: Facing Malicious Insiders in The Cloud (2017)
Presentation / Conference Contribution
Pitropakis, N., Lyvas, C., & Lambrinoudakis, C. (2017, February). The Greater The Power, The More Dangerous The Abuse: Facing Malicious Insiders in The Cloud. Presented at The Eighth International Conference on Cloud Computing, GRIDs, and Virtualization, Athens, Greece

The financial crisis made companies around the world search for cheaper and more efficient solutions to cover their needs in terms of computational power and storage. Their quest came to end with the birth of Cloud Computing infrastructures. However,... Read More about The Greater The Power, The More Dangerous The Abuse: Facing Malicious Insiders in The Cloud.

Genetic optimization of fuzzy membership functions for cloud resource provisioning (2017)
Presentation / Conference Contribution
Ullah, A., Li, J., Hussain, A., & Shen, Y. (2016, December). Genetic optimization of fuzzy membership functions for cloud resource provisioning. Presented at 2016 IEEE Symposium Series on Computational Intelligence (SSCI), Athens, Greece

The successful usage of fuzzy systems can be seen in many application domains owing to their capabilities to model complex systems by exploiting knowledge of domain experts. Their accuracy and performance are, however, primarily dependent on the desi... Read More about Genetic optimization of fuzzy membership functions for cloud resource provisioning.

STF-RNN: Space Time Features-based Recurrent Neural Network for predicting people next location (2017)
Presentation / Conference Contribution
Al-Molegi, A., Jabreel, M., & Ghaleb, B. (2016, December). STF-RNN: Space Time Features-based Recurrent Neural Network for predicting people next location. Presented at 2016 IEEE Symposium Series on Computational Intelligence (SSCI), Athens, Greece

This paper proposes a novel model called Space Time Features-based Recurrent Neural Network (STF-RNN) for predicting people next movement based on mobility patterns obtained from GPS devices logs. Two main features are involved in model operations, n... Read More about STF-RNN: Space Time Features-based Recurrent Neural Network for predicting people next location.

Group sparse regularization for deep neural networks (2017)
Journal Article
Scardapane, S., Comminiello, D., Hussain, A., & Uncini, A. (2017). Group sparse regularization for deep neural networks. Neurocomputing, 241, 81-89. https://doi.org/10.1016/j.neucom.2017.02.029

In this paper, we address the challenging task of simultaneously optimizing (i) the weights of a neural network, (ii) the number of neurons for each hidden layer, and (iii) the subset of active input features (i.e., feature selection). While these pr... Read More about Group sparse regularization for deep neural networks.