Outputs (57)

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.

A tool for generating synthetic data (2018)
Presentation / Conference Contribution
Peng, T., & Telle, A. (2018). A tool for generating synthetic data. In DATA '18 Proceedings of the First International Conference on Data Science, E-learning and Information Systems. https://doi.org/10.1145/3279996.3280018

It is popular to use real-world data to evaluate data mining techniques. However, there are some disadvantages to use real-world data for such purposes. Firstly, real-world data in most domains is difficult to obtain for several reasons, such as budg... Read More about A tool for generating synthetic data.

A Dual-spine Approach to Load Error Repair in a HEMS Sensor Network (2018)
Journal Article
Liu, X., Liu, Q., & Sun, M. (2018). A Dual-spine Approach to Load Error Repair in a HEMS Sensor Network. Computers, Materials & Continua, 57(2), 179-194. https://doi.org/10.32604/cmc.2018.04025

In a home energy management system (HEMS), appliances are becoming diversified and intelligent, so that certain simple maintenance work can be completed by appliances themselves. During the measurement, collection and transmission of electricity load... Read More about A Dual-spine Approach to Load Error Repair in a HEMS Sensor Network.

Get Your Project Funded: Using Biometric Data to Understand What Makes People Trust and Support Crowdfunding Campaigns (2018)
Presentation / Conference Contribution
Mcneill, M., Lawson, A., Raeside, R., & Peisl, T. (2018, July). Get Your Project Funded: Using Biometric Data to Understand What Makes People Trust and Support Crowdfunding Campaigns. Presented at 32nd International BCS Human Computer Interaction Conference (HCI 2018), Belfast

Creating a good crowdfunding campaign is difficult. By understanding why people contribute to crowdfunding campaigns we can make campaigns better and raise more money. Crowdfunding websites allow entrepreneurs to make a pitch, which is watched by pot... Read More about Get Your Project Funded: Using Biometric Data to Understand What Makes People Trust and Support Crowdfunding Campaigns.

A Cooperative Learning Approach for the Quadratic Knapsack Problem (2018)
Presentation / Conference Contribution
Lalla-Ruiz, E., Segredo, E., & Voß, S. (2018). A Cooperative Learning Approach for the Quadratic Knapsack Problem. In Learning and Intelligent Optimization Conference (LION12) (31-35). https://doi.org/10.1007/978-3-030-05348-2_3

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.

Feature-preserving detailed 3D face reconstruction from a single image (2018)
Presentation / Conference Contribution
Li, Y., Ma, L., Fan, H., & Mitchell, K. (2018, December). Feature-preserving detailed 3D face reconstruction from a single image. Presented at the 15th ACM SIGGRAPH European Conference, London, United Kingdom

Dense 3D face reconstruction plays a fundamental role in visual media production involving digital actors. We improve upon high fidelity reconstruction from a single 2D photo with a reconstruction framework that is robust to large variations in expre... Read More about Feature-preserving detailed 3D face reconstruction from a single image.

Trusting Intelligent Machines: Deepening Trust Within Socio-Technical Systems (2018)
Journal Article
Andras, P., Esterle, L., Guckert, M., Anh Han, T., Lewis, P. R., Milanovic, K., Payne, T., Perret, C., Pitt, J., Powers, S. T., Urquhart, N., & Wells, S. (2018). Trusting Intelligent Machines: Deepening Trust Within Socio-Technical Systems. IEEE technology & society magazine, 37(4), 76-83. https://doi.org/10.1109/MTS.2018.2876107

Intelligent machines have reached capabilities that go beyond a level that a human being can fully comprehend without sufficiently detailed understanding of the underlying mechanisms. The choice of moves in the game Go (generated by Deep Mind?s Alpha... Read More about Trusting Intelligent Machines: Deepening Trust Within Socio-Technical Systems.

Multi-reality games: an experience across the entire reality-virtuality continuum (2018)
Presentation / Conference Contribution
Casas, L., Ciccone, L., Çimen, G., Wiedemann, P., Fauconneau, M., Sumner, R. W., & Mitchell, K. (2018, December). Multi-reality games: an experience across the entire reality-virtuality continuum. Presented at the 16th ACM SIGGRAPH International Conference, Tokyo, Japan

Interactive play can take very different forms, from playing with physical board games to fully digital video games. In recent years, new video game paradigms were introduced to connect real-world objects to virtual game characters. However, even the... Read More about Multi-reality games: an experience across the entire reality-virtuality continuum.

SMK-means: An Improved Mini Batch K-means Algorithm Based on Mapreduce with Big Data (2018)
Journal Article
Xiao, B., Wang, Z., Liu, Q., & Liu, X. (2018). SMK-means: An Improved Mini Batch K-means Algorithm Based on Mapreduce with Big Data. Computers, Materials & Continua, 56(3), 365-379. https://doi.org/10.3970/cmc.2018.01830

In recent years, the rapid development of big data technology has also been favored by more and more scholars. Massive data storage and calculation problems have also been solved. At the same time, outlier detection problems in mass data have also co... Read More about SMK-means: An Improved Mini Batch K-means Algorithm Based on Mapreduce with Big Data.

BayesPiles: Visualisation Support for Bayesian Network Structure Learning (2018)
Journal Article
Vogogias, A., Kennedy, J., Archambault, D., Bach, B., Smith, V. A., & Currant, H. (2018). BayesPiles: Visualisation Support for Bayesian Network Structure Learning. ACM transactions on intelligent systems and technology, 10(1), Article 5. https://doi.org/10.1145/3230623

We address the problem of exploring, combining and comparing large collections of scored, directed networks for understanding inferred Bayesian networks used in biology. In this feld, heuristic algorithms explore the space of possible network solutio... Read More about BayesPiles: Visualisation Support for Bayesian Network Structure Learning.

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.

SICSA Demofest 2018 - Supporting user choice in optimisation. (2018)
Exhibition / Performance
Urquhart, N., Hutcheson, W., & Hoehl, S. SICSA Demofest 2018 - Supporting user choice in optimisation. Exhibited at Our Dynamic Earth, Edinburgh. 6 November 2018 - 6 November 2018. (Unpublished)

Many complex optimisation problems can have multiple solutions, techniques such as MAP –Elites will produce a large number of solutions from which the user should make the final choice. That final choice may be based on a number of soft criteria for... Read More about SICSA Demofest 2018 - Supporting user choice in optimisation..

An Approach to Evolving Legacy Enterprise System to Microservice-Based Architecture through Feature-Driven Evolution Rules (2018)
Journal Article
Habibullah, S., Liu, X., & Tan, Z. (2018). An Approach to Evolving Legacy Enterprise System to Microservice-Based Architecture through Feature-Driven Evolution Rules. International Journal of Computer Theory and Engineering, 10(5), 164-169. https://doi.org/10.7763/ijcte.2018.v10.1219

Evolving legacy enterprise systems into a lean system architecture has been on the agendas of many enterprises. Recent advance in legacy system evaluation is in favour of microservice technologies, which not only significantly reduce the complexity i... Read More about An Approach to Evolving Legacy Enterprise System to Microservice-Based Architecture through Feature-Driven Evolution Rules.

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.

Appliance Recognition Based on Continuous Quadratic Programming (2018)
Presentation / Conference Contribution
Liu, X., & Liu, Q. (2018). Appliance Recognition Based on Continuous Quadratic Programming. In Proceedings of 4th International Conference on Cloud Computing and Security (ICCCS 2018) (63-72). https://doi.org/10.1007/978-3-030-00018-9_6

The detailed information of residents' electricity consumption is of great significance to the planning of the use of electrical appliances and the reduction of electrical energy consumption. On the basis of analyzing the characteristics of residents... Read More about Appliance Recognition Based on Continuous Quadratic Programming.

Cross-modality interactive attention network for multispectral pedestrian detection (2018)
Journal Article
Zhang, L., Liu, Z., Zhang, S., Yang, X., Qiao, H., Huang, K., & Hussain, A. (2019). Cross-modality interactive attention network for multispectral pedestrian detection. Information Fusion, 50, 20-29. https://doi.org/10.1016/j.inffus.2018.09.015

Multispectral pedestrian detection is an emerging solution with great promise in many around-the-clock applications, such as automotive driving and security surveillance. To exploit the complementary nature and remedy contradictory appearance between... Read More about Cross-modality interactive attention network for multispectral pedestrian detection.

A framework for exploring intelligent artificial personhood. (2018)
Book Chapter
Kane, T. (2018). A framework for exploring intelligent artificial personhood. In V. C. Müller (Ed.), Philosophy and theory of artificial intelligence 2017 (255-258). Springer

The paper presents a framework for examining the human use of, and the activities of, artificial persons. This paper applies Hobbesian methodology to ascribe artificial personhood to business organisations, professional persons and algorithmic artifi... Read More about A framework for exploring intelligent artificial personhood..

2-Dimensional Outline Shape Representation for Generative Design with Evolutionary Algorithms (2018)
Presentation / Conference Contribution
Lapok, P., Lawson, A., & Paechter, B. (2018, September). 2-Dimensional Outline Shape Representation for Generative Design with Evolutionary Algorithms. Presented at EngOpt 2018 International Conference on Engineering Optimization, Lisboa, Portugal

In this paper, we investigate the ability of genetic representation methods to describe two-dimensional outline shapes, in order to use them in a generative design system. A specific area of mechanical design focuses on planar mechanisms. These are a... Read More about 2-Dimensional Outline Shape Representation for Generative Design with Evolutionary Algorithms.

CAMA-UAN: A Context-Aware MAC Scheme to the Underwater Acoustic Sensor Networks for the Improved CACA-UAN (2018)
Presentation / Conference Contribution
Liu, X., & Liu, Q. (2018, April). CAMA-UAN: A Context-Aware MAC Scheme to the Underwater Acoustic Sensor Networks for the Improved CACA-UAN. Presented at 2018 3rd International Conference on Computer and Communication Systems (ICCCS), Nagoya, Japan

Acoustic Communication is one of the most common and popular techniques used for Underwater Sensor Networks. The design of its communication protocol becomes a challenge due to its features of high delay and low bandwidth. Relevant research work has... Read More about CAMA-UAN: A Context-Aware MAC Scheme to the Underwater Acoustic Sensor Networks for the Improved CACA-UAN.

Image Based Proximate Shadow Retargeting (2018)
Presentation / Conference Contribution
Casas, L., Fauconneau, M., Kosek, M., Mclister, K., & Mitchell, K. (2018, September). Image Based Proximate Shadow Retargeting. Presented at Computer Graphics & Visual Computing (CGVC) 2018, Swansea University, United Kingdom

We introduce Shadow Retargeting which maps real shadow appearance to virtual shadows given a corresponding deformation of scene geometry, such that appearance is seamlessly maintained. By performing virtual shadow reconstruction from un-occluded real... Read More about Image Based Proximate Shadow Retargeting.