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..

Vulnerability Assessment of Objective Function of RPL Protocol for Internet of Things (2018)
Presentation / Conference Contribution
Semedo, F., Moradpoor, N., & Rafiq, M. (2018, September). Vulnerability Assessment of Objective Function of RPL Protocol for Internet of Things. Presented at 11th International Conference On Security Of Information and Networks, Cardiff, United Kingdom

The Internet of Things (IoT) can be described as the ever-growing global network of objects with built-in sensing and communication interfaces such as sensors, Global Positioning devices (GPS) and Local Area Network (LAN) interfaces. Security is by f... Read More about Vulnerability Assessment of Objective Function of RPL Protocol for Internet of Things.

Intertwining and NCA Maps Based New Image Encryption Scheme (2018)
Presentation / Conference Contribution
Khan, F. A., Ahmed, J., Ahmad, J., Khan, J. S., & Stankovic, V. (2018, August). Intertwining and NCA Maps Based New Image Encryption Scheme. Presented at 2018 International Conference on Computing, Electronics & Communications Engineering (iCCECE), Southend, United Kingdom

In this digital era, the Internet is a main source of communication. Due to exponential advancement in Internet technologies, transmission of multimedia data is very common now. However, transmitting sensitive information over the Internet is always... Read More about Intertwining and NCA Maps Based New Image Encryption Scheme.

Virtualizing the real: a virtual reality contemporary sculpture park for children (2018)
Journal Article
Flint, T., Hall, L., Stewart, F., & Hagan, D. (2018). Virtualizing the real: a virtual reality contemporary sculpture park for children. Digital Creativity, 29(2/3), 191-207. https://doi.org/10.1080/14626268.2018.1511601

This paper discusses a virtual reality experience for a contemporary sculpture park, Jupiter Artland, developed in Minecraft targeting 9-11-year-old children. Issues of fidelity, realism and authenticity are considered, examining the use of Minecraft... Read More about Virtualizing the real: a virtual reality contemporary sculpture park for children.

A Secured Data Management Scheme for Smart Societies in Industrial Internet of Things Environment (2018)
Journal Article
Babar, M., Khan, F., Iqbal, W., Yahya, A., Arif, F., Tan, Z., & Chuma, J. (2018). A Secured Data Management Scheme for Smart Societies in Industrial Internet of Things Environment. IEEE Access, 6, 43088-43099

Smart societies have an increasing demand for quality-oriented services and infrastructure in an Industrial Internet of Things (IIoT) paradigm. Smart urbanization faces numerous challenges. Among them, secured energy Demand Side Management (DSM) is o... Read More about A Secured Data Management Scheme for Smart Societies in Industrial Internet of Things Environment.

Evolution of a Functionally Diverse Swarm via a Novel Decentralised Quality-Diversity Algorithm (2018)
Presentation / Conference Contribution
Hart, E., Steyven, A. S. W., & Paechter, B. (2018, July). Evolution of a Functionally Diverse Swarm via a Novel Decentralised Quality-Diversity Algorithm. Presented at GECCO 2018, Kyoto, Japan

The presence of functionality diversity within a group has been demonstrated to lead to greater robustness, higher performance and increased problem-solving ability in a broad range of studies that includes insect groups, human groups and swarm robot... Read More about Evolution of a Functionally Diverse Swarm via a Novel Decentralised Quality-Diversity Algorithm.

Reliable and Energy-Efficient Two Levels Unequal Clustering Mechanism for Wireless Sensor Networks (2018)
Presentation / Conference Contribution
Ali, A. E., Al-Dubai, A., Romdhani, I., & Eshaftri, M. (2018, June). Reliable and Energy-Efficient Two Levels Unequal Clustering Mechanism for Wireless Sensor Networks. Presented at The 16th IEEE International Conference on Smart City (IEEE SmartCity-2018), Exeter

In Wireless Sensor Networks, clustering sensor nodes into disjoint groups is widely used to achieve load balance and increase network lifetime. In particular, traditional unequal clustering approaches where small clusters located close to the base st... Read More about Reliable and Energy-Efficient Two Levels Unequal Clustering Mechanism for Wireless Sensor Networks.

An approach to the semantic intelligence cloud (2018)
Thesis
Greenwell, R. An approach to the semantic intelligence cloud. (Thesis). Edinburgh Napier University. http://researchrepository.napier.ac.uk/Output/1255157

Cloud computing is a disruptive technology that aims to provide a utility approach to computing, where users can obtain their required computing resources without investment in infrastructure, computing platforms or services. Cloud computing resource... Read More about An approach to the semantic intelligence cloud.

Scalable training of artificial neural networks with adaptive sparse connectivity inspired by network science (2018)
Journal Article
Mocanu, D. C., Mocanu, E., Stone, P., Nguyen, P. H., Gibescu, M., & Liotta, A. (2018). Scalable training of artificial neural networks with adaptive sparse connectivity inspired by network science. Nature Communications, 9(1), Article 2383. https://doi.org/10.1038/s41467-018-04316-3

Through the success of deep learning in various domains, artificial neural networks are currently among the most used artificial intelligence methods. Taking inspiration from the network properties of biological neural networks (e.g. sparsity, scale-... Read More about Scalable training of artificial neural networks with adaptive sparse connectivity inspired by network science.

Deep Learning Hyper-Parameter Optimization for Video Analytics in Clouds (2018)
Journal Article
Yaseen, M. U., Anjum, A., Rana, O., & Antonopoulos, N. (2019). Deep Learning Hyper-Parameter Optimization for Video Analytics in Clouds. IEEE Transactions on Systems, Man and Cybernetics: Systems, 49(1), 253-264. https://doi.org/10.1109/TSMC.2018.2840341

A system to perform video analytics is proposed using a dynamically tuned convolutional network. Videos are fetched from cloud storage, preprocessed, and a model for supporting classification is developed on these video streams using cloud-based infr... Read More about Deep Learning Hyper-Parameter Optimization for Video Analytics in Clouds.

When Universal Access does not go to plan: Lessons to be learned (2018)
Presentation / Conference Contribution
Keates, S. (2018, July). When Universal Access does not go to plan: Lessons to be learned. Presented at International Conference on Universal Access in Human-Computer Interaction UAHCI 2018: Universal Access in Human-Computer Interaction. Methods, Technologies, and Users, Las Vegas, USA

While the theory of designing for Universal Access is increasingly understood, there remain persistent issues over realising products and systems that meet the goal of being accessible and usable by the broadest possible set of users. Clearly product... Read More about When Universal Access does not go to plan: Lessons to be learned.

An Edge-Based Architecture to Support Efficient Applications for Healthcare Industry 4.0 (2018)
Journal Article
Pace, P., Aloi, G., Gravina, R., Caliciuri, G., Fortino, G., & Liotta, A. (2019). An Edge-Based Architecture to Support Efficient Applications for Healthcare Industry 4.0. IEEE Transactions on Industrial Informatics, 15(1), 481-489. https://doi.org/10.1109/tii.2018.2843169

Edge computing paradigm has attracted many interests in the last few years as a valid alternative to the standard cloud-based approaches to reduce the interaction timing and the huge amount of data coming from Internet of Things (IoT) devices toward... Read More about An Edge-Based Architecture to Support Efficient Applications for Healthcare Industry 4.0.