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.

The Social Impact of Digital Youth Work: What Are We Looking For? (2019)
Journal Article
Pawluczuk, A., Webster, G., Smith, C., & Hall, H. (2019). The Social Impact of Digital Youth Work: What Are We Looking For?. Media and Communication, 7(2), 59-68. https://doi.org/10.17645/mac.v7i2.1907

Digital youth work is an emerging field of research and practice which seeks to investigate and support youth-centred digital literacy initiatives. Whilst digital youth work projects have become prominent in Europe in recent years, it has also become... Read More about The Social Impact of Digital Youth Work: What Are We Looking For?.

Is the Zero-Wait Policy Always Optimum for Information Freshness (Peak Age) or Throughput? (2019)
Journal Article
Barakat, B., Keates, S., Wassell, I., & Arshad, K. (2019). Is the Zero-Wait Policy Always Optimum for Information Freshness (Peak Age) or Throughput?. IEEE Communications Letters, 23(6), 987-990. https://doi.org/10.1109/LCOMM.2019.2907935

The Zero-Wait (ZW) policy is widely held to achieve maximum information 'freshness', i.e., to achieve minimum Peak Age (PA) and maximum throughput, for real-time Internet-of-Things applications. In this paper, it was shown through a series of experim... Read More about Is the Zero-Wait Policy Always Optimum for Information Freshness (Peak Age) or Throughput?.

Deep Precomputed Radiance Transfer for Deformable Objects (2019)
Presentation / Conference Contribution
Li, Y., Wiedemann, P., & Mitchell, K. (2019, May). Deep Precomputed Radiance Transfer for Deformable Objects. Presented at ACM Symposium on Interactive 3D Graphics and Games, Montreal, Quebec, Canada

We propose, DeepPRT, a deep convolutional neural network to compactly encapsulate the radiance transfer of a freely deformable object for rasterization in real-time.
With pre-computation of radiance transfer (PRT) we can store complex light interac... Read More about Deep Precomputed Radiance Transfer for Deformable Objects.

An optimized Speculative Execution Strategy Based on Local Data Prediction in Heterogeneous Hadoop Environment (2018)
Journal Article
Jin, D.-D., Liu, Q., Liu, X., & Linge, N. (2019). An optimized Speculative Execution Strategy Based on Local Data Prediction in Heterogeneous Hadoop Environment. Journal of Computers, 30(3), 130-142. https://doi.org/10.3966/199115992019063003010

Hadoop is a famous parallel computing framework that is applied to process large-scale data, but there exists such a task in hadoop framework, which is called “Straggling task” and has a serious impact on Hadoop. Speculative execution (SE) is an effe... Read More about An optimized Speculative Execution Strategy Based on Local Data Prediction in Heterogeneous Hadoop Environment.

System and method for management of confidential data (2018)
Patent
Buchanan, B., Lo, O., Macfarlane, R., Penrose, P., & Ramsay, B. (2018). System and method for management of confidential data. GB2561176A

This application is for a method of data management to identify confidential digital content on a database by first receiving a management request 302 from a system 304 to carry out data management operations. These include the identification of data... Read More about System and method for management of confidential data.

Design of Multi-View Based Email Classification for IoT Systems via Semi-Supervised Learning (2018)
Journal Article
Li, W., Meng, W., Tan, Z., & Xiang, Y. (2019). Design of Multi-View Based Email Classification for IoT Systems via Semi-Supervised Learning. Journal of Network and Computer Applications, 128, 56-63. https://doi.org/10.1016/j.jnca.2018.12.002

Suspicious emails are one big threat for Internet of Things (IoT) security, which aim to induce users to click and then redirect them to a phishing webpage. To protect IoT systems, email classification is an essential mechanism to classify spam and l... Read More about Design of Multi-View Based Email Classification for IoT Systems via Semi-Supervised Learning.

Psychogeography With Technology (2018)
Presentation / Conference Contribution
Flint, T., Grandison, T., & Barrett, H. (2018, November). Psychogeography With Technology. Poster presented at Engage 2018, Edinburgh, Scotland

No abstract available.

Copy-move forgery detection using combined features and transitive matching (2018)
Journal Article
Lin, C., Lu, W., Huang, X., Liu, K., Sun, W., Lin, H., & Tan, Z. (2019). Copy-move forgery detection using combined features and transitive matching. Multimedia Tools and Applications, 78(21), 30081-30096. https://doi.org/10.1007/s11042-018-6922-4

Recently, the research of Internet of Things (IoT) and Multimedia Big Data (MBD) has been growing tremendously. Both IoT and MBD have a lot of multimedia data, which can be tampered easily. Therefore, the research of multimedia forensics is necessary... Read More about Copy-move forgery detection using combined features and transitive matching.

A caching and spatial K-anonymity driven privacy enhancement scheme in continuous location-based services (2018)
Journal Article
Zhang, S., Li, X., Tan, Z., Peng, T., & Wang, G. (2019). A caching and spatial K-anonymity driven privacy enhancement scheme in continuous location-based services. Future Generation Computer Systems, 94, 40-50. https://doi.org/10.1016/j.future.2018.10.053

With the rapid pervasion of location-based services (LBSs), protection of location privacy has become a significant concern. In most continuous LBSs' privacy-preserving solutions, users need to transmit the location query data to an untrusted locatio... Read More about A caching and spatial K-anonymity driven privacy enhancement scheme in continuous location-based services.

The Challenges of Investigating Cryptocurrencies and Blockchain Related Crime (2018)
Journal Article
Dyson, S., Buchanan, W., & Bell, L. (2018). The Challenges of Investigating Cryptocurrencies and Blockchain Related Crime. The Journal of the British Blockchain Association, 1(2), 1-6. https://doi.org/10.31585/jbba-1-2-%288%292018

We increasingly live in a world where there is a balance between the rights to privacy and the requirements for consent, and the rights of society to protect itself. Within this world, there is an ever-increasing requirement to protect the identities... Read More about The Challenges of Investigating Cryptocurrencies and Blockchain Related Crime.

Use of machine learning techniques to model wind damage to forests (2018)
Journal Article
Hart, E., Sim, K., Kamimura, K., Meredieu, C., Guyon, D., & Gardiner, B. (2019). Use of machine learning techniques to model wind damage to forests. Agricultural and forest meteorology, 265, 16-29. https://doi.org/10.1016/j.agrformet.2018.10.022

This paper tested the ability of machine learning techniques, namely artificial neural networks and random forests, to predict the individual trees within a forest most at risk of damage in storms. Models based on these techniques were developed i... Read More about Use of machine learning techniques to model wind damage to forests.

Designing Mixed Reality Experiences and Pedagogies on the NYC High Line (2018)
Presentation / Conference Contribution
O’Keefe, B., Flint, T., Friedman, E., & Benyon, D. (2018, October). Designing Mixed Reality Experiences and Pedagogies on the NYC High Line. Poster presented at Celebration of Scholarship, SUNY Farmingdale State College New York

No abstract available.

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.

GDPR and Cyber Security for Business Information Systems (2018)
Book
Gobeo, A., Fowler, C., & Buchanan, B. (2018). GDPR and Cyber Security for Business Information Systems. River Publishers

The General Data Protection Regulation is the latest, and one of the most stringent, regulations regarding Data Protection to be passed into law by the European Union. Fundamentally, it aims to protect the Rights and Freedoms of all the individuals i... Read More about GDPR and Cyber Security for Business Information Systems.

GPU-accelerated depth codec for real-time, high-quality light field reconstruction (2018)
Journal Article
Koniaris, B., Kosek, M., Sinclair, D., & Mitchell, K. (2018). GPU-accelerated depth codec for real-time, high-quality light field reconstruction. Proceedings of the ACM on Computer Graphics and Interactive Techniques, 1(1), 1-15. https://doi.org/10.1145/3203193

Pre-calculated depth information is essential for efficient light field video rendering, due to the prohibitive cost of depth estimation from color when real-time performance is desired. Standard state-of-the-art video codecs fail to satisfy such per... Read More about GPU-accelerated depth codec for real-time, high-quality light field reconstruction.

Empowerment and embodiment for collaborative mixed reality systems: Empowerment and Embodiment (2018)
Journal Article
Pan, Y., Sinclair, D., & Mitchell, K. (2018). Empowerment and embodiment for collaborative mixed reality systems: Empowerment and Embodiment. Computer Animation and Virtual Worlds, 29(3-4), https://doi.org/10.1002/cav.1838

We present several mixed‐reality‐based remote collaboration settings by using consumer head‐mounted displays. We investigated how two people are able to work together in these settings. We found that the person in the AR system will be regarded as th... Read More about Empowerment and embodiment for collaborative mixed reality systems: Empowerment and Embodiment.

Compressed Animated Light Fields with Real-time View-dependent Reconstruction (2018)
Journal Article
Koniaris, C., Kosek, M., Sinclair, D., & Mitchell, K. (2019). Compressed Animated Light Fields with Real-time View-dependent Reconstruction. IEEE Transactions on Visualization and Computer Graphics, 25(4), 1666-1680. https://doi.org/10.1109/tvcg.2018.2818156

We propose an end-to-end solution for presenting movie quality animated graphics to the user while still allowing the sense of presence afforded by free viewpoint head motion. By transforming offline rendered movie content into a novel immersive repr... Read More about Compressed Animated Light Fields with Real-time View-dependent Reconstruction.

Moving Towards Highly Reliable and Effective Sensor Networks. (2018)
Journal Article
Ahmad, M., Tan, Z., He, X., & Ni, W. (2018). Moving Towards Highly Reliable and Effective Sensor Networks. Ad-hoc & sensor wireless networks, 40(3-4), 163-168

Wireless Sensor Networks (WSNs) have been the preferred choice for the design and deployment of next generation monitoring and control systems [1]. In these networks, the sensor nodes forward their sensed data towards a centralized base station. The... Read More about Moving Towards Highly Reliable and Effective Sensor Networks..

Using mobile technologies for mathematics: effects on student attitudes and achievement (2018)
Journal Article
Fabian, K., Topping, K. J., & Barron, I. G. (2018). Using mobile technologies for mathematics: effects on student attitudes and achievement. Educational Technology Research and Development, 66(5), 1119-1139. https://doi.org/10.1007/s11423-018-9580-3

The ubiquity of mobile devices together with its potential to bridge classroom learning to real-world has added a new angle to contextualising mathematics learning. This study investigated the effects of using mobile technologies to students’ attitud... Read More about Using mobile technologies for mathematics: effects on student attitudes and achievement.