Drizzle: Adaptive and fair route maintenance algorithm for Low-power and Lossy Networks in IoT (2017)
Presentation / Conference Contribution
Ghaleb, B., Al-Dubai, A., Romdhani, I., Nasser, Y., & Boukerche, A. (2017, May). Drizzle: Adaptive and fair route maintenance algorithm for Low-power and Lossy Networks in IoT. Presented at 2017 IEEE International Conference on Communications (ICC)

Low-power and Lossy Networks (LLNs) have been a key component in the Internet of Things (IoT) paradigm. Recently, a standardized algorithm, namely Trickle algorithm, is adopted for routing information maintenance in such networks. This algorithm is o... Read More about Drizzle: Adaptive and fair route maintenance algorithm for Low-power and Lossy Networks in IoT.

Tailoring methodological bricolage to investigate non-discretionary use of digital technology (2017)
Presentation / Conference Contribution
Sobolewska, E. (2017, July). Tailoring methodological bricolage to investigate non-discretionary use of digital technology. Presented at BHCI 2017: Digital Make Believe, Sunderland, UK

Digital technology appears to be an integral part of everyday life: at homes, workplaces, during leisure time; mediating interactions, demanding attention and engagement. In the age of cloud computing, social media, and ubiquitous mobile devices, it... Read More about Tailoring methodological bricolage to investigate non-discretionary use of digital technology.

Trust-Based Defence Model Against MAC Unfairness Attacks for IoT (2017)
Presentation / Conference Contribution
Djedjig, N., Tandjaoui, D., Romdhani, I., & Medjek, F. (2017, July). Trust-Based Defence Model Against MAC Unfairness Attacks for IoT. Presented at The Thirteenth International Conference on Wireless and Mobile Communications

The vulnerability of IoT networks makes channel access security a serious problem. The IEEE 802.15.4 MAC (Media Access Control) layer faces the risk of attacks from malicious nodes which attempts to get a dominating position and hold unfair advantage... Read More about Trust-Based Defence Model Against MAC Unfairness Attacks for IoT.

Complex Pleasures: Designing Optional interactions for Public Spaces (2017)
Thesis
Helgason, I. Complex Pleasures: Designing Optional interactions for Public Spaces. (Thesis). Edinburgh Napier University. http://researchrepository.napier.ac.uk/Output/1022893

This research aims to contribute to knowledge about the design of interactive systems sited in public spaces. In particular, the study concerns "optional interactions" where systems invite interaction from passers-by. These systems are action-orienta... Read More about Complex Pleasures: Designing Optional interactions for Public Spaces.

Data-to-Text Generation Improves Decision-Making Under Uncertainty (2017)
Journal Article
Gkatzia, D., Lemon, O., & Rieser, V. (2017). Data-to-Text Generation Improves Decision-Making Under Uncertainty. IEEE Computational Intelligence Magazine, 12(3), 10-17. https://doi.org/10.1109/MCI.2017.2708998

Decision-making is often dependent on uncertain data, e.g. data associated with confidence scores or probabilities. This article presents a comparison of different information presentations for uncertain data and, for the first time, measures their e... Read More about Data-to-Text Generation Improves Decision-Making Under Uncertainty.

The importance of the individual encoding in memetic algorithms with diversity control applied to large Sudoku puzzles (2017)
Presentation / Conference Contribution
Segura, C., Segredo, E., & Miranda, G. (2017, June). The importance of the individual encoding in memetic algorithms with diversity control applied to large Sudoku puzzles. Presented at 2017 IEEE Congress on Evolutionary Computation (CEC)

In recent years, several memetic algorithms with explicit mechanisms to delay convergence have shown great promise when solving 9x9 Sudoku puzzles. This paper analyzes and extends state-of-the-art schemes for dealing with Sudoku puzzles of larger dim... Read More about The importance of the individual encoding in memetic algorithms with diversity control applied to large Sudoku puzzles.

The Effectiveness of Two Audiovisual Mappings to Control a Concatenative Synthesiser (2017)
Presentation / Conference Contribution
Tsiros, A., & Leplâtre, G. (2017, July). The Effectiveness of Two Audiovisual Mappings to Control a Concatenative Synthesiser. Presented at Sound and Music Computing 2017

This paper presents the results of an investigation into audio visual (AV) correspondences conducted as part of the development of Morpheme, a painting interface to control a corpus-based concatenative sound synthesiser. Our goal was to measure the e... Read More about The Effectiveness of Two Audiovisual Mappings to Control a Concatenative Synthesiser.

A new enhanced RPL based routing for Internet of Things (2017)
Presentation / Conference Contribution
Ghaleb, B., Al-Dubai, A., Ekonomou, E., & Wadhaj, I. (2017, June). A new enhanced RPL based routing for Internet of Things. Presented at 2017 IEEE International Conference on Communications Workshops (ICC Workshops)

The IPv6 Routing Protocol for Low-power and Lossy Networks (RPL) has been recently standardized for routing in the constrained Internet of Things networks. Unfortunately, the RPL storing mode has been found restricted by storage limitations in the ro... Read More about A new enhanced RPL based routing for Internet of Things.

A hybrid method for feature construction and selection to improve wind-damage prediction in the forestry sector (2017)
Presentation / Conference Contribution
Hart, E., Sim, K., Gardiner, B., & Kamimura, K. (2017, July). A hybrid method for feature construction and selection to improve wind-damage prediction in the forestry sector. Presented at Proceedings of the Genetic and Evolutionary Computation Conference on - GECCO '17

Catastrophic damage to forests resulting from major storms has resulted in serious timber and financial losses within the sector across Europe in the recent past. Developing risk assessment methods is thus one of the keys to finding forest management... Read More about A hybrid method for feature construction and selection to improve wind-damage prediction in the forestry sector.

Hand Gesture Discrimination with Passive Infrared Sensor Arrays (2017)
Thesis
Wojtczuk, P. Hand Gesture Discrimination with Passive Infrared Sensor Arrays. (Thesis). Edinburgh Napier University. http://researchrepository.napier.ac.uk/Output/979764

Gesture recognition is a natural way of non-verbal communication for humans. However it is technically challenging to capture the relatively undefined movement of body parts in free space and also extract the intended gestures. Many existing technolo... Read More about Hand Gesture Discrimination with Passive Infrared Sensor Arrays.

Sustainable HCI: Blending permaculture and user-experience (2017)
Presentation / Conference Contribution
Benyon, D., & Egan, C. (2017, June). Sustainable HCI: Blending permaculture and user-experience. Presented at DIS: Designing Interactive Systems, Edinburgh

For approximately 10 years the SIGCHI Sustainable HCI (sHCI) and Sustainable Interaction Design (SID) communities have debated the contribution that HCI can make to sustainability. However, there has been little real progress in the field with few, i... Read More about Sustainable HCI: Blending permaculture and user-experience.

Big data analytics in healthcare: A cloud based framework for generating insights (2017)
Book Chapter
Anjum, A., Aizad, S., Arshad, B., Subhani, M. M., Davies-Tagg, D., Abdullah, T., & Antonopoulos, N. (2017). Big data analytics in healthcare: A cloud based framework for generating insights. In N. Antonopoulos, & L. Gillam (Eds.), Cloud Computing (153-170). Springer. https://doi.org/10.1007/978-3-319-54645-2_6

With exabytes of data being generated from genome sequencing, a whole new science behind genomics big data has emerged. As technology improves, the cost of sequencing a human genome has gone down considerably increasing the number of genomes being se... Read More about Big data analytics in healthcare: A cloud based framework for generating insights.

AGADE-TRAFFIC: Multi-Agent Simulations in Geographical Networks (2017)
Presentation / Conference Contribution
Rotärmel, S., Farrenkopf, T., Guckert, M., & Urquhart, N. (2017, June). AGADE-TRAFFIC: Multi-Agent Simulations in Geographical Networks. Presented at Practical Applications of Agents and Multi-Agent Systems, Porto, Portugal

AGADE-TRAFFIC is a tool for simulating traffic flow in networks. Traffic participants are modelled as NetLogo agents and are visualised in a graphical user interface. Geographic information is stored in a graph database and AGADE-TRAFFIC communicates... Read More about AGADE-TRAFFIC: Multi-Agent Simulations in Geographical Networks.

InOt-RePCoN: Forecasting user behavioural trend in large-scale cloud environments (2017)
Journal Article
Panneerselvam, J., Liu, L., & Antonopoulos, N. (2018). InOt-RePCoN: Forecasting user behavioural trend in large-scale cloud environments. Future Generation Computer Systems, 80, 322-341. https://doi.org/10.1016/j.future.2017.05.022

Cloud Computing has emerged as a low cost anywhere anytime computing paradigm. Given the energy consumption characteristics of the Cloud resources, service providers are under immense pressure to reduce the energy implications of the datacentres. For... Read More about InOt-RePCoN: Forecasting user behavioural trend in large-scale cloud environments.

Efficient service discovery in decentralized online social networks (2017)
Journal Article
Yuan, B., Liu, L., & Antonopoulos, N. (2018). Efficient service discovery in decentralized online social networks. Future Generation Computer Systems, 86, 775-791. https://doi.org/10.1016/j.future.2017.04.022

Online social networks (OSN) have attracted millions of users worldwide over the last decade. There are a series of urgent issues faced by existing OSN such as information overload, single-point of failure and privacy concerns. The booming Internet o... Read More about Efficient service discovery in decentralized online social networks.

Robotic assistants for universal access (2017)
Presentation / Conference Contribution
Keates, S., & Kyberd, P. J. (2017, July). Robotic assistants for universal access. Presented at HCI International 2017, Vancouver Convention Centre, Vancouver, Canada

Much research is now focusing on how technology is moving away from the traditional computer to a range of smart devices in smart environments, the so-called Internet of Things. With this increase in computing power and decrease in form factor, we ar... Read More about Robotic assistants for universal access.

New trust metric for the RPL routing protocol (2017)
Presentation / Conference Contribution
Romdhani, I., Djedjig, N., Medjek, F., & Tandjaoui, D. (2017, April). New trust metric for the RPL routing protocol. Presented at 2017 8th International Conference on Information and Communication Systems (ICICS)

Establishing trust relationships between routing nodes represents a vital security requirement to establish reliable routing processes that exclude infected or selfish nodes. In this paper, we propose a new security scheme for the Internet of things... Read More about New trust metric for the RPL routing protocol.

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.

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.

Mango: A model-driven approach to engineering green Mobile Cloud Applications (2017)
Thesis
Chinenyeze, S. J. Mango: A model-driven approach to engineering green Mobile Cloud Applications. (Thesis). Edinburgh Napier University. http://researchrepository.napier.ac.uk/Output/976572

With the resource constrained nature of mobile devices and the resource abundant offerings of the cloud, several promising optimisation techniques have been proposed by the green computing research community. Prominent techniques and unique methods h... Read More about Mango: A model-driven approach to engineering green Mobile Cloud Applications.