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Outputs (492)

From the Virtual to the RealWorld: Referring to Objects in Real-World Spatial Scenes (2015)
Presentation / Conference Contribution
Gkatzia, D., Rieser, V., Bartie, P., & Mackaness, W. (2015, September). From the Virtual to the RealWorld: Referring to Objects in Real-World Spatial Scenes. Presented at 2015 Conference on Empirical Methods in Natural Language Processing, Lisbon

Predicting the success of referring expressions (RE) is vital for real world applications such as navigation systems. Traditionally, research has focused on studying Referring Expression Generation (REG) in virtual, controlled environments. In this p... Read More about From the Virtual to the RealWorld: Referring to Objects in Real-World Spatial Scenes.

A Game-Based Setup for Data Collection and Task-Based Evaluation of Uncertain Information Presentation (2015)
Presentation / Conference Contribution
Gkatzia, D., Cercas Curry, A., Rieser, V., & Lemon, O. (2015, September). A Game-Based Setup for Data Collection and Task-Based Evaluation of Uncertain Information Presentation. Presented at 15th European Workshop on Natural Language Generation (ENLG 2015), University of Brighton, Brighton, UK

Decision-making is often dependent on uncertain data, e.g. data associated with confidence scores, such as probabilities. A concrete example of such data is weather data. We will demo a game-based setup for exploring the effectiveness of different ap... Read More about A Game-Based Setup for Data Collection and Task-Based Evaluation of Uncertain Information Presentation.

A Snapshot of NLG Evaluation Practices 2005 - 2014 (2015)
Presentation / Conference Contribution
Gkatzia, D., & Mahamood, S. (2015). A Snapshot of NLG Evaluation Practices 2005 - 2014. . https://doi.org/10.18653/v1/w15-4708

In this paper we present a snapshot of endto-end NLG system evaluations as presented in conference and journal papers1 over the last ten years in order to better understand the nature and type of evaluations that have been undertaken. We find that re... Read More about A Snapshot of NLG Evaluation Practices 2005 - 2014.

Generating and Evaluating Landmark-Based Navigation Instructions in Virtual Environments (2015)
Presentation / Conference Contribution
Cercas Curry, A., Gkatzia, D., & Rieser, V. (2015, September). Generating and Evaluating Landmark-Based Navigation Instructions in Virtual Environments. Presented at 15th European Workshop on Natural Language Generation (ENLG 2015), University of Brighton, Brighton, UK

Referring to landmarks has been identified to lead to improved navigation instructions. However, a previous corpus study suggests that human “wizards” also choose to refer to street names and generate user-centric instructions. In this paper, we cond... Read More about Generating and Evaluating Landmark-Based Navigation Instructions in Virtual Environments.

Comparing Multi-label Classification with Reinforcement Learning for Summarisation of Time-series Data (2014)
Presentation / Conference Contribution
Gkatzia, D., Hastie, H., & Lemon, O. (2014, June). Comparing Multi-label Classification with Reinforcement Learning for Summarisation of Time-series Data. Presented at The 52nd Annual Meeting of the Association for Computational Linguistics, Baltimore

We present a novel approach for automatic report generation from time-series data, in the context of student feedback generation. Our proposed methodology treats content selection as a multi-label (ML) classification problem, which takes as input ti... Read More about Comparing Multi-label Classification with Reinforcement Learning for Summarisation of Time-series Data.

Finding middle ground? Multi-objective Natural Language Generation from time-series data (2014)
Presentation / Conference Contribution
Gkatzia, D., Hastie, H., & Lemon, O. (2014, April). Finding middle ground? Multi-objective Natural Language Generation from time-series data. Presented at Proceedings of the 14th Conference of the European Chapter of the Association for Computational Linguistics, volume 2: Short Papers, Gothenburg, Sweden

A Natural Language Generation (NLG) system is able to generate text from nonlinguistic data, ideally personalising the content to a user’s specific needs. In some cases, however, there are multiple stakeholders with their own individual goals, needs... Read More about Finding middle ground? Multi-objective Natural Language Generation from time-series data.

A Survey of Error Analysis and Calibration Methods for MEMS Triaxial Accelerometers (2020)
Journal Article
Xiao, B., Jiang, Y., Liu, Q., Liu, X., & Sun, M. (2020). A Survey of Error Analysis and Calibration Methods for MEMS Triaxial Accelerometers. Computers, Materials & Continua, 64(1), 389-399. https://doi.org/10.32604/cmc.2020.06092

MEMS accelerometers are widely used in various fields due to their small size and low cost, and have good application prospects. However, the low accuracy limits its range of applications. To ensure data accuracy and safety we need to calibrate MEMS... Read More about A Survey of Error Analysis and Calibration Methods for MEMS Triaxial Accelerometers.

Automatic Generation of Adversarial Metamorphic Malware Using MAP-Elites (2020)
Presentation / Conference Contribution
Babaagba, K. O., Tan, Z., & Hart, E. (2020, April). Automatic Generation of Adversarial Metamorphic Malware Using MAP-Elites. Presented at EvoStar 2020, Seville, Spain

In the field of metamorphic malware detection, training a detection model with malware samples that reflect potential mutants of the malware is crucial in developing a model resistant to future attacks. In this paper, we use a Multi-dimensional Archi... Read More about Automatic Generation of Adversarial Metamorphic Malware Using MAP-Elites.

Large-scale Argument Visualization (LSAV) (2016)
Presentation / Conference Contribution
Khartabil, D., Wells, S., & Kennedy, J. (2016). Large-scale Argument Visualization (LSAV). In Eurographics Conference on Visualization (EuroVis), Posters Track (2016)

Arguments are structures of premises and conclusions that underpin rational reasoning processes. Within complex knowledge domains, especially if they are contentious, argument structures can become large and complex. Visualization tools have been dev... Read More about Large-scale Argument Visualization (LSAV).

An Optimized Resource Scheduling Strategy for Hadoop Speculative Execution Based on Non-cooperative Game Schemes (2020)
Journal Article
Jiang, Y., Liu, Q., Dannah, W., Jin, D., Liu, X., & Sun, M. (2020). An Optimized Resource Scheduling Strategy for Hadoop Speculative Execution Based on Non-cooperative Game Schemes. Computers, Materials & Continua, 62(2), 713-729. https://doi.org/10.32604/cmc.2020.04604

Hadoop is a well-known parallel computing system for distributed computing and large-scale data processes. “Straggling” tasks, however, have a serious impact on task allocation and scheduling in a Hadoop system. Speculative Execution (SE) is an effic... Read More about An Optimized Resource Scheduling Strategy for Hadoop Speculative Execution Based on Non-cooperative Game Schemes.

Using MAP-Elites to support policy making around Workforce Scheduling and Routing (2020)
Journal Article
Urquhart, N., Hart, E., & Hutcheson, W. (2020). Using MAP-Elites to support policy making around Workforce Scheduling and Routing. Automatisierungstechnik, 68(2), https://doi.org/10.1515/auto-2019-0107

English abstract: Algorithms such as MAP-Elites provide a means of allowing users to explore a solution space by returning an archive of high-performing solutions. Such an archive, can allow the user an overview of the solution space which may be use... Read More about Using MAP-Elites to support policy making around Workforce Scheduling and Routing.

An Adaptive Kalman Filtering Approach to Sensing and Predicting Air Quality Index Values (2020)
Journal Article
Chen, J., Chen, K., Ding, C., Wang, G., Liu, Q., & Liu, X. (2020). An Adaptive Kalman Filtering Approach to Sensing and Predicting Air Quality Index Values. IEEE Access, 8, 4265-4272. https://doi.org/10.1109/access.2019.2963416

In recent years, Air Quality Index (AQI) have been widely used to describe the severity of haze and other air pollutions yet suffers from inefficiency and compatibility on real-time perception and prediction. In this paper, an Auto-Regressive (AR) pr... Read More about An Adaptive Kalman Filtering Approach to Sensing and Predicting Air Quality Index Values.

A Review on Deep Learning Approaches to Image Classification and Object Segmentation (2019)
Journal Article
Wu, H., Liu, Q., & Liu, X. (2019). A Review on Deep Learning Approaches to Image Classification and Object Segmentation. Computers, Materials & Continua, 60(2), 575-597. https://doi.org/10.32604/cmc.2019.03595

Deep learning technology has brought great impetus to artificial intelligence, especially in the fields of image processing, pattern and object recognition in recent years. Present proposed artificial neural networks and optimization skills have effe... Read More about A Review on Deep Learning Approaches to Image Classification and Object Segmentation.

MLCut: exploring multi-level cuts in dendrograms for biological data (2016)
Presentation / Conference Contribution
Vogogias, A., Kennedy, J., Archambault, D., Anne Smith, V., & Currant, H. (2016, September). MLCut: exploring multi-level cuts in dendrograms for biological data. Presented at Computer Graphics & Visual Computing (CGVC) 2016

Choosing a single similarity threshold for cutting dendrograms is not sufficient for performing hierarchical clustering analysis of heterogeneous data sets. In addition, alternative automated or semi-automated methods that cut dendrograms in multiple... Read More about MLCut: exploring multi-level cuts in dendrograms for biological data.

The evaluation of data filtering criteria in wind turbine power performance assessment (2019)
Thesis
Davison, B. The evaluation of data filtering criteria in wind turbine power performance assessment. (Thesis). Edinburgh Napier University. http://researchrepository.napier.ac.uk/Output/2376943

The post-installation verification of wind turbine performance is an essential part of a wind energy project. Data collected from meteorological instruments and from the turbine is analysed to produce an estimate of the annual energy production (AEP)... Read More about The evaluation of data filtering criteria in wind turbine power performance assessment.

Statistical Assessment of IP Multimedia Subsystem in a Softwarized Environment: a Queueing Networks Approach (2019)
Journal Article
Di Mauro, M., & Liotta, A. (2019). Statistical Assessment of IP Multimedia Subsystem in a Softwarized Environment: a Queueing Networks Approach. IEEE Transactions on Network and Service Management, 16(4), 1493-1506. https://doi.org/10.1109/tnsm.2019.2943776

The Next Generation 5G Networks can greatly benefit from the synergy between virtualization paradigms, such as the Network Function Virtualization (NFV), and service provisioning platforms such as the IP Multimedia Subsystem (IMS). The NFV concept is... Read More about Statistical Assessment of IP Multimedia Subsystem in a Softwarized Environment: a Queueing Networks Approach.

An AI approach to Collecting and Analyzing Human Interactions with Urban Environments (2019)
Journal Article
Ferrara, E., Fragale, L., Fortino, G., Song, W., Perra, C., di Mauro, M., & Liotta, A. (2019). An AI approach to Collecting and Analyzing Human Interactions with Urban Environments. IEEE Access, 7, 141476-141486. https://doi.org/10.1109/access.2019.2943845

Thanks to advances in Internet of Things and crowd-sensing, it is possible to collect vast amounts of urban data, to better understand how citizens interact with cities and, in turn, improve human well-being in urban environments. This is a scientifi... Read More about An AI approach to Collecting and Analyzing Human Interactions with Urban Environments.

The ARE Robot Fabricator: How to (Re)produce Robots that Can Evolve in the Real World (2019)
Presentation / Conference Contribution
Hale, M. F., Buchanan, E., Winfield, A. F., Timmis, J., Hart, E., Eiben, A. E., Angus, M., Veenstra, F., Li, W., Woolley, R., De Carlo, M., & Tyrrell, A. M. (2019, July). The ARE Robot Fabricator: How to (Re)produce Robots that Can Evolve in the Real World. Presented at Artificial Life, Newcastle, UK

The long term vision of the Autonomous Robot Evolution (ARE) project is to create an ecosystem of both virtual and physical robots with evolving brains and bodies. One of the major challenges for such a vision is the need to construct many unique ind... Read More about The ARE Robot Fabricator: How to (Re)produce Robots that Can Evolve in the Real World.

Being a leader or being the leader: The evolution of institutionalised hierarchy (2019)
Presentation / Conference Contribution
Perret, C., Hart, E., & Powers, S. T. (2019, July). Being a leader or being the leader: The evolution of institutionalised hierarchy. Presented at ALIFE 2019, Newcastle upon Tyne

Human social hierarchy has the unique characteristic of existing in two forms. Firstly, as an informal hierarchy where leaders and followers are implicitly defined by their personal characteristics, and secondly, as an institutional hierarchy where l... Read More about Being a leader or being the leader: The evolution of institutionalised hierarchy.