Algorithm selection using deep learning without feature extraction (2019)
Presentation / Conference Contribution
Alissa, M., Sim, K., & Hart, E. (2019, July). Algorithm selection using deep learning without feature extraction. Presented at Genetic and Evolutionary Computing Conference (GECCO) 2019, Prague, Czech Republic

We propose a novel technique for algorithm-selection which adopts a deep-learning approach, specifically a Recurrent-Neural Network with Long-Short-Term-Memory (RNN-LSTM). In contrast to the majority of work in algorithm-selection, the approach does... Read More about Algorithm selection using deep learning without feature extraction.

Increasing Trust in Meta-Heuristics by Using MAP-Elites (2019)
Presentation / Conference Contribution
Urquhart, N., Guckert, M., & Powers, S. (2019, July). Increasing Trust in Meta-Heuristics by Using MAP-Elites. Presented at Genetic and Evolutionary Computation COnference, Prague, Czech Republic

Intelligent AI systems using approaches containing emergent elements often encounter acceptance problems. Results do not get sufficiently explained and the procedure itself can not be fully retraced because the flow of control is dependent on stochas... Read More about Increasing Trust in Meta-Heuristics by Using MAP-Elites.

Evolving robust policies for community energy system management (2019)
Presentation / Conference Contribution
Cardoso, R., Hart, E., & Pitt, J. (2019, July). Evolving robust policies for community energy system management. Presented at GECCO '19, Prague, Czech Republic

Community energy systems (CESs) are shared energy systems in which multiple communities generate and consume energy from renewable resources. At regular time intervals, each participating community decides whether to self-supply, store, trade, or sel... Read More about Evolving robust policies for community energy system management.

An Illumination Algorithm Approach to Solving the Micro-Depot Routing Problem (2019)
Presentation / Conference Contribution
Urquhart, N., Hoehl, S., & Hart, E. (2019, July). An Illumination Algorithm Approach to Solving the Micro-Depot Routing Problem. Presented at Genetic and Evolutionary Computation Conference (GECCO '19), Prague, Czech Republic

An increasing emphasis on reducing pollution and congestion in city centres combined with an increase in online shopping is changing the ways in which logistics companies address vehicle routing problems (VRP). We introduce the {\em micro-depot}-VRP,... Read More about An Illumination Algorithm Approach to Solving the Micro-Depot Routing Problem.

Reviving legacy enterprise systems with microservice-based architecture within cloud environments (2019)
Presentation / Conference Contribution
Habibullah, S., Liu, X., Tan, Z., Zhang, Y., & Liu, Q. (2019, June). Reviving legacy enterprise systems with microservice-based architecture within cloud environments. Presented at 5th International Conference on Software Engineering (SOFT 2019), Copenhagen, Denmark

Evolution has always been a challenge for enterprise computing systems. The microservice based architecture is a new design model which is rapidly becoming one of the most effective means to re-architect legacy enterprise systems and to reengineer th... Read More about Reviving legacy enterprise systems with microservice-based architecture within cloud environments.

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 Cognitive IoE (Internet of Everything) Approach to Ambient-Intelligent Smart Space (2019)
Thesis
Singh Jamnal, G. A Cognitive IoE (Internet of Everything) Approach to Ambient-Intelligent Smart Space. (Thesis). Edinburgh Napier University. http://researchrepository.napier.ac.uk/Output/2090321

At present, the United Nations figures claim that the current world population would rise from 7.6 billion to 8.5 billion in 2030 and 9.7 billion in 2050. Therefore by the 2050, 65 percent of world’s population would be living in urban mega-cities an... Read More about A Cognitive IoE (Internet of Everything) Approach to Ambient-Intelligent Smart Space.

Embedded document security using sticky policies and identity based encryption (2019)
Thesis
Spyra, G. K. Embedded document security using sticky policies and identity based encryption. (Thesis). Edinburgh Napier University. http://researchrepository.napier.ac.uk/Output/2090564

Data sharing domains have expanded over several, both trusted and insecure environments. At the same time, the data security boundaries have shrunk from internal network perimeters down to a single identity and a piece of information. Since new EU GD... Read More about Embedded document security using sticky policies and identity based encryption.

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.

Constructing and Evaluating Visualisation Task Classifications: Process and Considerations (2019)
Presentation / Conference Contribution
Kerracher, N., & Kennedy, J. (2017, June). Constructing and Evaluating Visualisation Task Classifications: Process and Considerations. Presented at EuroVis 2017 Eurographics / IEEE VGTC Conference on Visualization 2017, Barcelona, Spain

Categorising tasks is a common pursuit in the visualisation research community, with a wide variety of taxonomies, typologies, design spaces, and frameworks having been developed over the last three decades. While these classifications are universall... Read More about Constructing and Evaluating Visualisation Task Classifications: Process and Considerations.

Identity and belonging for graduate apprenticeships in computing: the experience of first cohort degree apprentices in Scotland (2019)
Presentation / Conference Contribution
Taylor-Smith, E., Smith, S., & Smith, C. (2019, July). Identity and belonging for graduate apprenticeships in computing: the experience of first cohort degree apprentices in Scotland. Presented at Innovation and Technology in Computer Science Education (ITiCSE), Aberdeen

In September 2017, our university’s first graduate apprentices began degrees in Software Development, Cybersecurity, and Information Technology Management for Business. This study explores how apprentices experience their association with the univers... Read More about Identity and belonging for graduate apprenticeships in computing: the experience of first cohort degree apprentices in Scotland.

Simulating Dynamic Vehicle Routing Problems with Athos (2019)
Presentation / Conference Contribution
Hoffman, B., Guckert, M., Chalmers, K., & Urquhart, N. (2019, June). Simulating Dynamic Vehicle Routing Problems with Athos. Presented at ECMS2019: 33rd INTERNATIONAL ECMS CONFERENCE ON MODELLING AND SIMULATION, Napoli, Italy

Complex routing problems, such as vehicle routing problems with additional constraints, are both hard to solve and hard to express in a form that is accessible to the human expert and at the same time processible by a computer system that is supposed... Read More about Simulating Dynamic Vehicle Routing Problems with Athos.

An Agent Based Technique for Improving Multi-Stakeholder Optimisation Problems (2019)
Presentation / Conference Contribution
Urquhart, N., & Powers, S. T. (2019, June). An Agent Based Technique for Improving Multi-Stakeholder Optimisation Problems. Presented at PAAMS 2019: International Conference on Practical Applications of Agents and Multi-Agent Systems, Avila, Spain

We present an agent based framework for improving multi-stakeholder optimisation problems, which we define as optimisation problems where the solution is utilised by a number of stakeholders who have their own local preferences. We explore our ideas... Read More about An Agent Based Technique for Improving Multi-Stakeholder Optimisation Problems.

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.

A Self-Organizing Memory Neural Network for Aerosol Concentration Prediction (2019)
Journal Article
Liu, Q., Zou, Y., & Liu, X. (2019). A Self-Organizing Memory Neural Network for Aerosol Concentration Prediction. Computer Modeling in Engineering and Sciences, 119(3), 617-637. https://doi.org/10.32604/cmes.2019.06272

Haze-fog, which is an atmospheric aerosol caused by natural or man-made factors, seriously affects the physical and mental health of human beings. PM2.5 (a particulate matter whose diameter is smaller than or equal to 2.5 microns) is the chief culpri... Read More about A Self-Organizing Memory Neural Network for Aerosol Concentration Prediction.

PLC Memory Attack Detection and Response in a Clean Water Supply System (2019)
Journal Article
Robles-Durazno, A., Moradpoor, N., McWhinnie, J., Russell, G., & Maneru-Marin, I. (2019). PLC Memory Attack Detection and Response in a Clean Water Supply System. International Journal of Critical Infrastructure Protection, 26, https://doi.org/10.1016/j.ijcip.2019.05.003

Industrial Control Systems (ICS) are frequently used in manufacturing and critical infrastructures like water treatment, chemical plants, and transportation schemes. Citizens tend to take modern-day conveniences such as trains, planes or tap water fo... Read More about PLC Memory Attack Detection and Response in a Clean Water Supply System.

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.

Getting in, getting on: fragility in student and graduate identity (2019)
Journal Article
Smith, S., Sobolewska, E., & Hunter, D. (2019). Getting in, getting on: fragility in student and graduate identity. Higher Education Research and Development, 38(5), 1046-1060. https://doi.org/10.1080/07294360.2019.1612857

Over a period of three years this longitudinal study explored new approaches to consider student identity during the transition from university to employment. Students were followed through a new portfolio-based final year course and beyond universit... Read More about Getting in, getting on: fragility in student and graduate identity.

A Comprehensive Survey of Security Threats and their Mitigation Techniques for next-generation SDN Controllers (2019)
Journal Article
Han, T., Jan, S., Tan, T., Usman, M., Jan, M., Khan, R., & Xu, Y. (2020). A Comprehensive Survey of Security Threats and their Mitigation Techniques for next-generation SDN Controllers. Concurrency and Computation: Practice and Experience, 32(16), Article e5300. https://doi.org/10.1002/cpe.5300

Software Dened Network (SDN) and Network Virtualization (NV) are emerged paradigms that simplied the control and management of the next generation networks, most importantly, Internet of Things (IoT), Cloud Computing, and Cyber-Physical Systems. Th... Read More about A Comprehensive Survey of Security Threats and their Mitigation Techniques for next-generation SDN Controllers.

Future Quantum-to-the-Home (QTTH) All-Optical Networks (Invited Talk) (2019)
Presentation / Conference Contribution
Asif, R. (2018, August). Future Quantum-to-the-Home (QTTH) All-Optical Networks (Invited Talk). Presented at 10th International Conference on Advanced Infocomm Technology, Stockholm, Sweden

For imparting data security to the end-users in a archetypal fiber-to-the-home (FTTH) network, quantum cryptography (QC) is getting much attention now-a-days. QC or more specifically quantum key distribution (QKD) promises unconditionally secure prot... Read More about Future Quantum-to-the-Home (QTTH) All-Optical Networks (Invited Talk).