How autonomous control can improve the performance of logistics networks - a simulation experiment (2019)
Thesis
Preinl, T. How autonomous control can improve the performance of logistics networks - a simulation experiment. (Thesis). Edinburgh Napier University. http://researchrepository.napier.ac.uk/Output/2089989

In this thesis the application of autonomous control concepts to logistics networks is studied by means of a simulation model. This simulation model is based on an actual outbound bulk product supply network of a commodity company.
Logistics planni... Read More about How autonomous control can improve the performance of logistics networks - a simulation experiment.

A Data-driven Statistical Approach to Customer Behaviour Analysis and Modelling in Online Freemium Games (2019)
Thesis
Singh Roy, A. A Data-driven Statistical Approach to Customer Behaviour Analysis and Modelling in Online Freemium Games. (Thesis). Edinburgh Napier University. http://researchrepository.napier.ac.uk/Output/2090355

The video games industry is one of the most attractive and lucrative segments in the entertainment and digital media, with big business of more than $150 billion worldwide. A popular approach in this industry is the online freemium model, wherein the... Read More about A Data-driven Statistical Approach to Customer Behaviour Analysis and Modelling in Online Freemium Games.

Efficient Routing Primitives for Low-power and Lossy Networks in Internet of Things (2019)
Thesis
Ghaleb, B. Efficient Routing Primitives for Low-power and Lossy Networks in Internet of Things. (Thesis). Edinburgh Napier University. http://researchrepository.napier.ac.uk/Output/2070542

At the heart of the Internet of Things (IoTs) are the Low-power and Lossy networks (LLNs), a collection of interconnected battery-operated and resource-constrained tiny devices that enable the realization of a wide range of applications in multiple d... Read More about Efficient Routing Primitives for Low-power and Lossy Networks in Internet of Things.

Finding Fair Negotiation Algorithms to Reduce Peak Electricity Consumption in Micro Grids (2019)
Presentation / Conference Contribution
Powers, S. T., Meanwell, O., & Cai, Z. (2019, June). Finding Fair Negotiation Algorithms to Reduce Peak Electricity Consumption in Micro Grids. Presented at 17th International Conference on Practical Applications of Agents and Multi-Agent Systems, Avila, Spain

Reducing peak electricity consumption is important to maximise use of renewable energy sources, and reduce the total amount of capacity required on a grid. Most approaches use a centralised optimisation algorithm run by a utility company. Here we dev... Read More about Finding Fair Negotiation Algorithms to Reduce Peak Electricity Consumption in Micro Grids.

Non-intrusive load monitoring and its challenges in a NILM system framework (2019)
Journal Article
Liu, Q., Lu, M., Liu, X., & Linge, N. (2019). Non-intrusive load monitoring and its challenges in a NILM system framework. International Journal of High Performance Computing and Networking, 14(1), 102-111. https://doi.org/10.1504/IJHPCN.2019.099748

With the increasing of energy demand and electricity price, researchers gain more and more interest among the residential load monitoring. In order to feed back the individual appliance’s energy consumption instead of the whole-house energy consumpti... Read More about Non-intrusive load monitoring and its challenges in a NILM system framework.

Quantifying the effects of increasing user choice in MAP-Elites applied to a Workforce Scheduling and Routing Problem. (2019)
Presentation / Conference Contribution
Urquhart, N., Hart, E., & Hutcheson, W. (2019, April). Quantifying the effects of increasing user choice in MAP-Elites applied to a Workforce Scheduling and Routing Problem. Presented at EvoStar2019: International Conference on the Applications of Evolutionary Computation, Leipzig

Quality-diversity algorithms such as MAP-Elites provide a means of supporting the users when finding and choosing solutions to a problem by returning a set of solutions which are diverse according to set of user-defined features. The number of soluti... Read More about Quantifying the effects of increasing user choice in MAP-Elites applied to a Workforce Scheduling and Routing Problem..

Wattom: a Consumption and Grid Aware Smart Plug with Mid-air Controls (2019)
Presentation / Conference Contribution
Quintal, F., Esteves, A., Caires, F., Baptiste, V., & Mendes, P. (2019, March). Wattom: a Consumption and Grid Aware Smart Plug with Mid-air Controls. Presented at 13th International Conference on Tangible, Embedded, and Embodied Interaction (ACM TEI), Tempe, Arizona

This paper presents Wattom, a highly interactive ambient eco-feedback smart plug that aims to support a more sustainable use of electricity by being tightly coupled to users' energy-related activities. We describe three use cases of the system: using... Read More about Wattom: a Consumption and Grid Aware Smart Plug with Mid-air Controls.

Designing Motion Matching for Real-World Applications: Lessons from Realistic Deployments (2019)
Presentation / Conference Contribution
Verweij, D., Esteves, A., Bakker, S., & Khan, V.-J. (2019, March). Designing Motion Matching for Real-World Applications: Lessons from Realistic Deployments. Presented at 13th International Conference on Tangible, Embedded, and Embodied Interaction (ACM TEI), Tempe, Arizona

Amongst the variety of (multi-modal) interaction techniques that are being developed and explored, the Motion Matching paradigm provides a novel approach to selection and control. In motion matching, users interact by rhythmically moving their bodies... Read More about Designing Motion Matching for Real-World Applications: Lessons from Realistic Deployments.

Lightweight Reinforcement Learning for Energy Efficient Communications in Wireless Sensor Networks (2019)
Journal Article
Savaglio, C., Pace, P., Aloi, G., Liotta, A., & Fortino, G. (2019). Lightweight Reinforcement Learning for Energy Efficient Communications in Wireless Sensor Networks. IEEE Access, 7, 29355-29364. https://doi.org/10.1109/access.2019.2902371

High-density communications in wireless sensor networks (WSNs) demand for new approaches to meet stringent energy and spectrum requirements. We turn to reinforcement learning, a prominent method in artificial intelligence, to design an energy-preserv... Read More about Lightweight Reinforcement Learning for Energy Efficient Communications in Wireless Sensor Networks.

A new security approach for the spectrum access in vehicular networks (2019)
Presentation / Conference Contribution
Alsarhan, A., Al-Dubai, A., Kilani, Y., & Alkhalidy, M. (2019, February). A new security approach for the spectrum access in vehicular networks. Presented at ICDS 2019 : The Thirteenth International Conference on Digital Society and eGovernments, Athens, Greece

Vehicular ad hoc networks (VANETs) have been instrumental in intelligent transportation systems that enhances road safety and road management significantly. This technology enables communication among vehicles where drivers can share road information... Read More about A new security approach for the spectrum access in vehicular networks.

Analyzing Objective and Subjective Data in Social Sciences: Implications for Smart Cities (2019)
Journal Article
Erhan, L., Ndubuaku, M., Ferrara, E., Richardson, M., Sheffield, D., Ferguson, F. J., Brindley, P., & Liotta, A. (2019). Analyzing Objective and Subjective Data in Social Sciences: Implications for Smart Cities. IEEE Access, 7, 19890-19906. https://doi.org/10.1109/access.2019.2897217

The ease of deployment of digital technologies and the Internet of Things gives us the opportunity to carry out large-scale social studies and to collect vast amounts of data from our cities. In this paper, we investigate a novel way of analyzing dat... Read More about Analyzing Objective and Subjective Data in Social Sciences: Implications for Smart Cities.

A Cooperative Learning Approach for the Quadratic Knapsack Problem (2018)
Presentation / Conference Contribution
Lalla-Ruiz, E., Segredo, E., & Voß, S. (2018, June). A Cooperative Learning Approach for the Quadratic Knapsack Problem. Presented at Learning and Intelligent Optimization Conference (LION12), Kalamata, Greece

The Quadratic Knapsack Problem (QKP) is a well-known optimization problem aimed to maximize a quadratic objective function subject to linear capacity constraints. It has several applications in different fields such as telecommunications, graph theor... Read More about A Cooperative Learning Approach for the Quadratic Knapsack Problem.

A supervised energy monitoring-based machine learning approach for anomaly detection in a clean water supply system (2018)
Presentation / Conference Contribution
Robles-Durazno, A., Moradpoor, N., McWhinnie, J., & Russell, G. (2018, June). A supervised energy monitoring-based machine learning approach for anomaly detection in a clean water supply system. Presented at Cyber Security 2018: 2018 International Conference on Cyber Security and Protection of Digital Services, Glasgow, United Kingdom

Industrial Control Systems are part of our daily life in industries such as transportation, water, gas, oil, smart cities, and telecommunications. Technological development over time have improved their components including operating system platforms... Read More about A supervised energy monitoring-based machine learning approach for anomaly detection in a clean water supply system.

Short-long term anomaly detection in wireless sensor networks based on machine learning and multi-parameterized edit distance (2018)
Journal Article
Cauteruccio, F., Fortino, G., Guerrieri, A., Liotta, A., Mocanu, D. C., Perra, C., Terracina, G., & Torres Vega, M. (2019). Short-long term anomaly detection in wireless sensor networks based on machine learning and multi-parameterized edit distance. Information Fusion, 52, 13-30. https://doi.org/10.1016/j.inffus.2018.11.010

Heterogeneous wireless sensor networks are a source of large amount of different information representing environmental aspects such as light, temperature, and humidity. A very important research problem related to the analysis of the sensor data is... Read More about Short-long term anomaly detection in wireless sensor networks based on machine learning and multi-parameterized edit distance.

Interference graphs to monitor and control schedules in low-power WPAN (2018)
Journal Article
van der Lee, T., Liotta, A., & Exarchakos, G. (2019). Interference graphs to monitor and control schedules in low-power WPAN. Future Generation Computer Systems, 93, 111-120. https://doi.org/10.1016/j.future.2018.10.014

Highlights
• This study presents the complete and slotted interference graph model.
• The service uses the complete interference graph to evaluate the network.
• Slotted interference graphs are used to reschedule problematic connections.
• Rea... Read More about Interference graphs to monitor and control schedules in low-power WPAN.

A Survey of Limitations and Enhancements of the IPv6 Routing Protocol for Low-power and Lossy Networks: A Focus on Core Operations (2018)
Journal Article
Ghaleb, B., Al-Dubai, A. Y., Ekonomou, E., Alsarhan, A., Nasser, Y., Mackenzie, L. M., & Boukerche, A. (2019). A Survey of Limitations and Enhancements of the IPv6 Routing Protocol for Low-power and Lossy Networks: A Focus on Core Operations. Communications Surveys and Tutorials, IEEE Communications Society, 21(2), 1607-1635. https://doi.org/10.1109/COMST.2018.2874356

Driven by the special requirements of the Low-power and Lossy Networks (LLNs), the IPv6 Routing Protocol for LLNs (RPL) was standardized by the IETF some six years ago to tackle the routing issue in such networks. Since its introduction, however, num... Read More about A Survey of Limitations and Enhancements of the IPv6 Routing Protocol for Low-power and Lossy Networks: A Focus on Core Operations.

DNA Sequence Based Medical Image Encryption Scheme (2018)
Presentation / Conference Contribution
Khan, J. S., Ahmad, J., Abbasi, S. F., Ali, A., & Kayhan, S. K. (2018, September). DNA Sequence Based Medical Image Encryption Scheme. Presented at 2018 10th Computer Science and Electronic Engineering (CEEC), Colchester, United Kingdom

Medical consultants and doctors store and update patients confidential information on Internet cloud computing platforms. These days, securing medical images from eavesdroppers is one of the most challenging and significant research areas. Due to var... Read More about DNA Sequence Based Medical Image Encryption Scheme.

Collaborative Computing: Networking, Applications and Worksharing: 13th International Conference, CollaborateCom 2017, Edinburgh, UK, December 11–13, 2017, Proceedings (2018)
Presentation / Conference Contribution
(2017, December). Collaborative Computing: Networking, Applications and Worksharing: 13th International Conference, CollaborateCom 2017, Edinburgh, UK, December 11–13, 2017, Proceedings. Presented at CollaborateCom 2017, Edinburgh, UK

This book constitutes the thoroughly refereed proceedings of the 13th International Conference on Collaborative Computing: Networking, Applications, and Worksharing, CollaborateCom 2017, held in Edinburgh, UK, in December 2017. The 65 papers presente... Read More about Collaborative Computing: Networking, Applications and Worksharing: 13th International Conference, CollaborateCom 2017, Edinburgh, UK, December 11–13, 2017, Proceedings.

Cloud-based video analytics using convolutional neural networks (2018)
Journal Article
Yaseen, M. U., Anjum, A., Farid, M., & Antonopoulos, N. (2019). Cloud-based video analytics using convolutional neural networks. Software: Practice and Experience, 49(4), 565-583. https://doi.org/10.1002/spe.2636

Object classification is a vital part of any video analytics system, which could aid in complex applications such as object monitoring and management. Traditional video analytics systems work on shallow networks and are unable to harness the power of... Read More about Cloud-based video analytics using convolutional neural networks.

Socio-environmental Health. Exploring risk and resource spaces within urban environments. An interdisciplinary enquiry. (2018)
Presentation / Conference Contribution
Carnegie, E., Reid, A., Deakin, M., & Inglis, G. (2018, September). Socio-environmental Health. Exploring risk and resource spaces within urban environments. An interdisciplinary enquiry. Paper presented at Space and Poverty (Salzburg Conference in Interdisciplinary Poverty Research)

Regenerative spaces (good for health, environment and the planet) are essential for human flourishing. Findings from previous research suggest an association between spatial patterning and health outcomes (Hagedoorn et al. 2016; Meijer et al. 2012; P... Read More about Socio-environmental Health. Exploring risk and resource spaces within urban environments. An interdisciplinary enquiry..