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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

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

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

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

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 R. Tajjeeddine, N. Abderrahmane, & J. Buchmann (Eds.), 11th International Conference on Cryptology, AFRICACRYPT 2019https://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

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

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

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

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

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

Anomaly detection is an important technique to identify network unusual behaviour patterns and keep the network under control. The network attacks are increasing in both number and sophistication. To avoid causing significant traffic patterns and bei... Read More

A guideline-based approach for assisting with the reproducibility of experiments in recommender systems evaluation (2019)
Journal Article
Polatidis, N., Pimenidis, E., Fish, A., & Kapetanakis, S. (in press). A guideline-based approach for assisting with the reproducibility of experiments in recommender systems evaluation. International Journal on Artificial Intelligence Tools,

Recommender systems’ evaluation is usually based on predictive accuracy and information retrieval metrics, with better scores meaning recommendations are of higher quality. However, new algorithms are constantly developed and the comparison of result... Read More

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. (in press). A switching multi-level method for the long tail recommendation problem. https://doi.org/10.3233/JIFS-179331

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. The most popular recommendation method is Collaborative... Read More

Blockchain based digital forensics investigation framework in the internet of things and social systems (2019)
Journal Article
Li, S., Qin, T., & Min, G. (in press). Blockchain based digital forensics investigation framework in the internet of things and social systems. IEEE Transactions on Computational Social Systems, 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

Neuroscience patient identification using big data and fuzzy logic–An Alzheimer’s disease case study (2019)
Journal Article
Munir, K., Ramón-Fernández, A. D., 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

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

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 based solutions have been succ... Read More

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

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

What makes for effective visualisation in cyber situational awareness for non-expert users? (2019)
Presentation / Conference
Carroll, F., Chakof, A., & Legg, P. (2019, June). What makes for effective visualisation in cyber situational awareness for non-expert users?. Paper presented at IEEE Int. Conf. on Cyber Situational Awareness, Data Analytics and Assessment (CyberSA)

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 standard for many... Read More

Efficient and interpretable real-time malware detection using random-forest (2019)
Presentation / Conference
Mills, A., Spyridopoulos, T., & Legg, P. (2019, June). Efficient and interpretable real-time malware detection using random-forest. Paper presented at Int. Conf. on Cyber Situational Awareness, Data Analytics and Assessment (CyberSA)

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 have potenti... Read More

Tools and techniques for improving cyber situational awareness of targeted phishing attacks (2019)
Presentation / Conference
Legg, P., & Blackman, T. (2019, June). Tools and techniques for improving cyber situational awareness of targeted phishing attacks. Paper presented at IEEE Int. Conf. on Cyber Situational Awareness, Data Analytics and Assessment (CyberSA)

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 sophisticatio... Read More

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. (in press). Reliable data analysis through blockchain based crowdsourcing in mobile ad-hoc cloud. Mobile Networks and Applications, 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

An explanation-based approach for experiment reproducibility in recommender systems (2019)
Journal Article
Polatidis, N., Papaleonidas, A., Pimenidis, E., & Iliadis, L. (in press). An explanation-based approach for experiment reproducibility in recommender systems. Neural Computing and Applications, https://doi.org/10.1007/s00521-019-04274-x

The offline evaluation of recommender systems is typically based on accuracy metrics such as the Mean Absolute Error and the Root Mean Squared Error for error rating prediction and Precision and Recall for measuring the quality of the top-N recommend... Read More

Towards an evolvable cancer treatment simulator (2019)
Journal Article
Preen, R., Bull, L., & Adamatzky, A. (2019). Towards an evolvable cancer treatment simulator. BioSystems, 182, 1-7. https://doi.org/10.1016/j.biosystems.2019.05.005

The use of high-fidelity computational simulations promises to enable high-throughput hypothesis testing and optimisation of cancer therapies. However, increasing realism comes at the cost of increasing computational requirements. This article explor... Read More

Venue2Vec: An efficient embedding model for fine-grained user location prediction in geo-social networks (2019)
Journal Article
Xu, S., Cao, J., Li, S., Legg, P., & Liu, B. (2019). Venue2Vec: An efficient embedding model for fine-grained user location prediction in geo-social networks. IEEE Systems Journal, https://doi.org/10.1109/JSYST.2019.2913080

Abstract—Geo-Social networks (GSN) significantly improve location-aware capability of services by offering geo-located content based on the huge volumes of data generated in the GSN. The problem of user location prediction based on user generated da... Read More