Predicting environmental features by learning spatiotemporal embeddings from social media (2019)
Journal Article
Jeawak, S. S., Jones, C. B., & Schockaert, S. (2020). Predicting environmental features by learning spatiotemporal embeddings from social media. Ecological Informatics, 55, https://doi.org/10.1016/j.ecoinf.2019.101031

Spatiotemporal modelling is an important task for ecology. Social media tags have been found to have great potential to assist in predicting aspects of the natural environment, particularly through the use of machine learning methods. Here we propose... Read More about Predicting environmental features by learning spatiotemporal embeddings from social media.

Tamil Talk: What you speak is what you get! (2019)
Presentation / Conference
Ogunshile, E., & Ramachandran, R. (2019, October). Tamil Talk: What you speak is what you get!. Paper presented at CONISOFT 2019 : IEEE 7th International Conference on Software Engineering Research and Innovation, Mexico City

Tamil is one of the longest surviving classical languages in the world. Speech to text in Tamil would benefit to a lot of native Tamil speakers throughout the world. There are many speech recognition and speech to text applications available for a... Read More about Tamil Talk: What you speak is what you get!.

A honeybees-inspired heuristic algorithm for numerical optimisation (2019)
Journal Article
Dugenci, M., & Aydin, M. E. (2020). A honeybees-inspired heuristic algorithm for numerical optimisation. Neural Computing and Applications, 32, 12311–12325. https://doi.org/10.1007/s00521-019-04533-x

© 2019, The Author(s). Swarm intelligence is all about developing collective behaviours to solve complex, ill-structured and large-scale problems. Efficiency in collective behaviours depends on how to harmonise the individual contributors so that a c... Read More about A honeybees-inspired heuristic algorithm for numerical optimisation.

Printing the Muses: Reimaging digital musical instruments through 2.5D printing (2019)
Conference Proceeding
Parraman, C., & Gaster, B. (2019). Printing the Muses: Reimaging digital musical instruments through 2.5D printing

The objective is to explore cross-disciplinary methods of converting musical terms for tactile interfaces, thus enabling people unfamiliar in creating music to be explorative through the development of novel musical interfaces. The project involves w... Read More about Printing the Muses: Reimaging digital musical instruments through 2.5D printing.

Digital Expression and Representation of Rhythm (2019)
Presentation / Conference
Renney, N., & Gaster, B. R. (2019, September). Digital Expression and Representation of Rhythm. Paper presented at Audio Mostly, Nottingham

Music provides a means to explore time by sequencing musical events in a seemingly endless and expressive way. This potential often far exceeds the ability of digital systems to enable composers and performers to explore musical time, perhaps due to... Read More about Digital Expression and Representation of Rhythm.

Towards trusted security context exchange protocol for SDN based low latency networks (2019)
Presentation / Conference
Ghafoor, A., Abbasi, A. Q., & Khan, Z. (2019, September). Towards trusted security context exchange protocol for SDN based low latency networks. Paper presented at 38th International Conference on Computer Safety, Reliability and Security, Tuku, Finland

To overcome the latency issue in real-time communication, a number of research based solutions and architectures are being proposed. In all these, security is not considered an important factor since it causes extra delay in the communication and int... Read More about Towards trusted security context exchange protocol for SDN based low latency networks.

Further lower bounds for structure-preserving signatures in asymmetric bilinear groups (2019)
Conference Proceeding
Ghadafi, E. (2019). Further lower bounds for structure-preserving signatures in asymmetric bilinear groups. In J. Buchmann, N. Abderrahmane, & R. Tajjeeddine (Eds.), 11th International Conference on Cryptology, AFRICACRYPT 2019. https://doi.org/10.1007/978-3-030-23696-0

Structure-Preserving Signatures (SPSs) are a useful tool for the design of modular cryptographic protocols. Recent series of works have shown that by limiting the message space of those schemes to the set of Diffie-Hellman (DH) pairs, it is possible... Read More about Further lower bounds for structure-preserving signatures in asymmetric bilinear groups.

Fun with Interfaces (SVG Interfaces for Musical Expression) (2019)
Presentation / Conference
Gaster, B., Nathan, R., & Carinna, P. (2019, August). Fun with Interfaces (SVG Interfaces for Musical Expression). Paper presented at 7th ACM SIGPLAN International Workshop on Functional Art, Music, Modeling, and Design, Berlin

In this paper we address the design and implementation of custom controller interfaces, bridging the issue of user mapping between action and sound in interactive music systems. A simple framework utilizing functional specifications for musical inter... Read More about Fun with Interfaces (SVG Interfaces for Musical Expression).

A probabilistic logic for resource-bounded multi-agent systems (2019)
Presentation / Conference
Nguyen, H. N., & Rakib, A. (2019, August). A probabilistic logic for resource-bounded multi-agent systems. Paper presented at 28th International Joint Conference on Artificial Intelligence, Macao, China

Resource-bounded alternating-time temporal logic (RB-ATL), an extension of Coalition Logic (CL) and Alternating-time Temporal Logic (ATL), allows reasoning about resource requirements of coalitions in concurrent systems. However, many real-world syst... Read More about A probabilistic logic for resource-bounded multi-agent systems.

Symmetry degree measurement and its applications to anomaly detection (2019)
Journal Article
Qin, T., Liu, Z., Wang, P., Li, S., Guan, X., & Gao, L. (2019). Symmetry degree measurement and its applications to anomaly detection. IEEE Transactions on Information Forensics and Security, 15, 1040-1055. https://doi.org/10.1109/TIFS.2019.2933731

IEEE Anomaly detection is an important technique used to identify patterns of unusual network behavior and keep the network under control. Today, network attacks are increasing in terms of both their number and sophistication. To avoid causing signif... Read More about Symmetry degree measurement and its applications to anomaly detection.

Blockchain based digital forensics investigation framework in the internet of things and social systems (2019)
Journal Article
Li, S., Qin, T., & Min, G. (2019). Blockchain based digital forensics investigation framework in the internet of things and social systems. IEEE Transactions on Computational Social Systems, 6(6), 1433-1441. https://doi.org/10.1109/TCSS.2019.2927431

The decentralised nature of blockchain technologies can well match the needs of integrity and provenances of evidences collecting in digital forensics across jurisdictional borders. In this work, a novel blockchain based digital forensics investigati... Read More about Blockchain based digital forensics investigation framework in the internet of things and social systems.

A switching multi-level method for the long tail recommendation problem (2019)
Journal Article
Alshammari, G., Jorro-Aragoneses, J. L., Polatidis, N., Kapetanakis, S., Pimenidis, E., & Petridis, M. (2019). A switching multi-level method for the long tail recommendation problem. Journal of Intelligent and Fuzzy Systems, 37(6), 7189-7198. https://doi.org/10.3233/JIFS-179331

© 2019 - IOS Press and the authors. All rights reserved. Recommender systems are decision support systems that play an important part in generating a list of product or service recommendations for users based on the past experiences and interactions.... Read More about A switching multi-level method for the long tail recommendation problem.

Neuroscience patient identification using big data and fuzzy logic–An Alzheimer’s disease case study (2019)
Journal Article
Munir, K., de Ramón-Fernández, A., Iqbal, S., & Javaid, N. (2019). Neuroscience patient identification using big data and fuzzy logic–An Alzheimer’s disease case study. Expert Systems with Applications, 136, 410-425. https://doi.org/10.1016/j.eswa.2019.06.049

Modern neuroscience imaging technologies considerably affect diagnostic and prognostic accuracy and facilitate progress towards the cure of brain diseases. The benefits largely depend on the practicalities by which the large-scale imaging and clinica... Read More about Neuroscience patient identification using big data and fuzzy logic–An Alzheimer’s disease case study.

Smart city big data analytics: An advanced review (2019)
Journal Article
Soomro, K., Bhutta, M. N. M., Khan, Z., & Tahir, M. A. (2019). Smart city big data analytics: An advanced review. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 9(5), Article e1319. https://doi.org/10.1002/widm.1319

© 2019 Wiley Periodicals, Inc. With the increasing role of ICT in enabling and supporting smart cities, the demand for big data analytics solutions is increasing. Various artificial intelligence, data mining, machine learning and statistical analysis... Read More about Smart city big data analytics: An advanced review.

Enhancing user fairness in OFDMA radio access networks through machine learning (2019)
Conference Proceeding
Comsa, I., Zhang, S., Aydin, M., Kuonen, P., Trestian, R., & Ghinea, G. (2019). Enhancing user fairness in OFDMA radio access networks through machine learning. In 2019 Wireless Days (WD). , (1-8). https://doi.org/10.1109/WD.2019.8734262

The problem of radio resource scheduling subject to fairness satisfaction is very challenging even in future radio access networks. Standard fairness criteria aim to find the best trade-off between overall throughput maximization and user fairness sa... Read More about Enhancing user fairness in OFDMA radio access networks through machine learning.

Monitoring the performance of petrochemical organizations in Saudi Arabia using data envelopment analysis (2019)
Journal Article
Alidrisi, H., Aydin, M. E., Bafail, A. O., Abdulal, R., & Karuvatt, S. A. (2019). Monitoring the performance of petrochemical organizations in Saudi Arabia using data envelopment analysis. Mathematics, 7(6), 519. https://doi.org/10.3390/math7060519

The petrochemical industry plays a crucial role in the economy of the Kingdom of Saudi Arabia. Therefore, the effectiveness and efficiency of this industry is of high importance. Data envelopment analysis (DEA) is found to be more acceptable in measu... Read More about Monitoring the performance of petrochemical organizations in Saudi Arabia using data envelopment analysis.

Reliable data analysis through blockchain based crowdsourcing in mobile ad-hoc cloud (2019)
Journal Article
Rasool, S., Iqbal, M., Dagiuklas, T., Ql-Qayyum, Z., & Li, S. (2020). Reliable data analysis through blockchain based crowdsourcing in mobile ad-hoc cloud. Mobile Networks and Applications, 25, 153-163. https://doi.org/10.1007/s11036-019-01221-x

Mobile Ad-hoc Cloud (MAC) is the constellation of nearby mobile devices to serve the heavy computational needs of the resource constrained edge devices. One of the major challenges of MAC is to convince the mobile devices to offer their limited resou... Read More about Reliable data analysis through blockchain based crowdsourcing in mobile ad-hoc cloud.

Tools and techniques for improving cyber situational awareness of targeted phishing attacks (2019)
Conference Proceeding
Legg, P., & Blackman, T. (2019). Tools and techniques for improving cyber situational awareness of targeted phishing attacks. . https://doi.org/10.1109/CyberSA.2019.8899406

© 2019 IEEE. Phishing attacks continue to be one of the most common attack vectors used online today to deceive users, such that attackers can obtain unauthorised access or steal sensitive information. Phishing campaigns often vary in their level of... Read More about Tools and techniques for improving cyber situational awareness of targeted phishing attacks.

Efficient and interpretable real-time malware detection using random-forest (2019)
Conference Proceeding
Mills, A., Spyridopoulos, T., & Legg, P. (2019). Efficient and interpretable real-time malware detection using random-forest. . https://doi.org/10.1109/CyberSA.2019.8899533

© 2019 IEEE. Malicious software, often described as malware, is one of the greatest threats to modern computer systems, and attackers continue to develop more sophisticated methods to access and compromise data and resources. Machine learning methods... Read More about Efficient and interpretable real-time malware detection using random-forest.

What makes for effective visualisation in cyber situational awareness for non-expert users? (2019)
Conference Proceeding
Carroll, F., Chakof, A., & Legg, P. (2019). What makes for effective visualisation in cyber situational awareness for non-expert users?. . https://doi.org/10.1109/CyberSA.2019.8899440

© 2019 IEEE. As cyber threats continue to become more prevalent, there is a need to consider how best we can understand the cyber landscape when acting online, especially so for non-expert users. Satellite navigation systems provide the de facto stan... Read More about What makes for effective visualisation in cyber situational awareness for non-expert users?.