All Outputs (313)

A simple nod of the head: The effect of minimal robot movements on children's perception of a low-anthropomorphic robot (2017)
Presentation / Conference Contribution
Zaga, C., De Vries, R. A., Li, J., Truong, K. P., & Evers, V. (2017, May). A simple nod of the head: The effect of minimal robot movements on children's perception of a low-anthropomorphic robot. Presented at CHI conference on human factors in computing systems, Denver, Colorado, USA

In this note, we present minimal robot movements for robotic technology for children. Two types of minimal gaze movements were designed: social-gaze movements to communicate social engagement and deictic-gaze movements to communicate task-related ref... Read More about A simple nod of the head: The effect of minimal robot movements on children's perception of a low-anthropomorphic robot.

Towards Next-Generation Lip-Reading Driven Hearing-Aids: A preliminary Prototype Demo (2017)
Presentation / Conference Contribution
Adeel, A., Gogate, M., & Hussain, A. (2017, August). Towards Next-Generation Lip-Reading Driven Hearing-Aids: A preliminary Prototype Demo. Presented at 1st International Workshop on Challenges in Hearing Assistive Technology (CHAT 2017), Stockholm, Sweden

Speech enhancement aims to enhance the perceived speech quality and intelligibility in the presence of noise. Classical speech enhancement methods are mainly based on audio only processing which often perform poorly in adverse conditions, where overw... Read More about Towards Next-Generation Lip-Reading Driven Hearing-Aids: A preliminary Prototype Demo.

The BURCHAK corpus: A challenge data set for interactive learning of visually grounded word meanings (2017)
Presentation / Conference Contribution
Yu, Y., Eshghi, A., Mills, G., & Lemon, O. J. (2017, April). The BURCHAK corpus: A challenge data set for interactive learning of visually grounded word meanings. Presented at The Sixth Workshop on Vision and Language, Valencia, Spain

We motivate and describe a new freely available human-human dialogue data set for interactive learning of visually grounded word meanings through ostensive definition by a tutor to a learner. The data has been collected using a novel, character-by-ch... Read More about The BURCHAK corpus: A challenge data set for interactive learning of visually grounded word meanings.

Alana: Social dialogue using an ensemble model and a ranker trained on user feedback (2017)
Presentation / Conference Contribution
Papaioannou, I., Curry, A. C., Part, J. L., Shalyminov, I., Xu, X., Yu, Y., Dušek, O., Rieser, V., & Lemon, O. (2017, December). Alana: Social dialogue using an ensemble model and a ranker trained on user feedback. Presented at Alexa Prize SocialBot Grand Challenge 1

We describe our Alexa prize system (called ‘Alana’) which consists of an ensemble of bots, combining rule-based and machine learning systems, and using a contextual ranking mechanism to choose system responses. This paper reports on the version of th... Read More about Alana: Social dialogue using an ensemble model and a ranker trained on user feedback.

VOILA: An optimised dialogue system for interactively learning visually-grounded word meanings (demonstration system) (2017)
Presentation / Conference Contribution
Yu, Y., Eshghi, A., & Lemon, O. (2017, August). VOILA: An optimised dialogue system for interactively learning visually-grounded word meanings (demonstration system). Presented at 18th Annual SIGdial Meeting on Discourse and Dialogue, Saarbrücken, Germany

We present VOILA: an optimised, multi-modal dialogue agent for interactive learning of visually grounded word meanings from a human user. VOILA is: (1) able to learn new visual categories interactively from users from scratch; (2) trained on real hum... Read More about VOILA: An optimised dialogue system for interactively learning visually-grounded word meanings (demonstration system).

Decentralizing the Semantic Web: Who Will Pay to Realize It? (2017)
Presentation / Conference Contribution
Grubenmann, T., Dell'Aglio, D., Bernstein, A., Moor, D., & Seuken, S. (2017, October). Decentralizing the Semantic Web: Who Will Pay to Realize It?. Presented at DeSemWeb 2017: Decentralizing the Semantic Web, Vienna

Fueled by enthusiasm of volunteers, government subsidies, and open data legislation, the Web of Data (WoD) has enjoyed a phenomenal growth. Commercial data, however, has been stuck in proprietary silos, as the monetization strategy for sharing data i... Read More about Decentralizing the Semantic Web: Who Will Pay to Realize It?.

The gamification of cybersecurity training (2017)
Presentation / Conference Contribution
Coull, N., Donald, I., Ferguson, I., Keane, E., Mitchell, T., Smith, O. V., Stevenson, E., & Tomkins, P. (2017, June). The gamification of cybersecurity training. Presented at 11th International Conference on E-Learning and Games, Edutainment 2017

Due to the rapidly and continued evolving nature of technology, there is a constant need to update police officers{\textquoteright} training in cyber security to ensure that the UK continues to be a secure place to live and do business. Rather than d... Read More about The gamification of cybersecurity training.

Tea leaves moisture prediction using one-port monopole sensor (2017)
Presentation / Conference Contribution
Ling, J., Then, Y., You, K., Ahmed, J., & Zaidel, D. (2017, November). Tea leaves moisture prediction using one-port monopole sensor. Presented at 2017 IEEE Asia Pacific Microwave Conference (APMC), Kuala Lumpur, Malaysia

This paper presents the application of using a coaxial monopole sensor for determining and formulating the relationship between the reflection coefficient and the moisture content of tea leaves. A coaxial monopole sensor with operating frequency rang... Read More about Tea leaves moisture prediction using one-port monopole sensor.

A unified global investigation on the spectral effects of soiling losses of PV glass substrates: preliminary results (2017)
Presentation / Conference Contribution
Micheli, L., Fernández, E. F., Smestad, G. P., Alrashidi, H., Sarmah, N., Sellami, N., Hassan, I. A., Kasry, A., Nofuentes, G., Sood, N., & et al. (2017, June). A unified global investigation on the spectral effects of soiling losses of PV glass substrates: preliminary results. Presented at 2017 IEEE 44th Photovoltaic Specialist Conference (PVSC), Washington, DC, USA

The present work reports on the initial results of an international collaboration aiming to investigate the spectral effects of soiling losses. Identical glass coupons have been exposed outdoors for eight weeks in different locations worldwide, and w... Read More about A unified global investigation on the spectral effects of soiling losses of PV glass substrates: preliminary results.

Reproducibility in machine Learning-Based studies: An example of text mining (2017)
Presentation / Conference Contribution
Olorisade, B. K., Brereton, P., & Andras, P. (2017, August). Reproducibility in machine Learning-Based studies: An example of text mining. Presented at ICML 2017 RML Workshop: Reproducibility in Machine Learning, Sydney, Autralia

Reproducibility is an essential requirement for computational studies including those based on machine learning techniques. However, many machine learning studies are either not reproducible or are difficult to reproduce.
In this paper, we consider... Read More about Reproducibility in machine Learning-Based studies: An example of text mining.

Translating Design Details to Construction Details- with Both Eyes Open (2017)
Presentation / Conference Contribution
Sajjadianm, S. (2017, December). Translating Design Details to Construction Details- with Both Eyes Open. Presented at International Conference for Sustainable Design of the Built Environment, London

Sustainable designs will come to nothing if they are lost in construction process. Therefore, the accuracy of design details and the transformation to the construction details is vital to achieve initial design thinking targets. This is driven most i... Read More about Translating Design Details to Construction Details- with Both Eyes Open.

Quantifying the Behavior of Modern and Traditional Construction Systems on the Basis of Thermal Comfort (2017)
Presentation / Conference Contribution
Sajjadian, S., & Sharples, S. (2017, July). Quantifying the Behavior of Modern and Traditional Construction Systems on the Basis of Thermal Comfort. Presented at PLEA 2017, Edinburgh

Thermal comfort is crucial to ascertain the energy consumption in buildings and is a key factor for decision-making in the design of sustainable building envelopes. This paper presents a methodology to assess the performance of construction systems q... Read More about Quantifying the Behavior of Modern and Traditional Construction Systems on the Basis of Thermal Comfort.

Inflection Generation for Spanish Verbs using Supervised Learning (2017)
Presentation / Conference Contribution
Barros, C., Gkatzia, D., & Lloret, E. (2017, September). Inflection Generation for Spanish Verbs using Supervised Learning. Presented at First Workshop on Subword and Character Level Models in NLP, Copenhagen, Denmark

We present a novel supervised approach to inflection generation for verbs in Spanish. Our system takes as input the verb’s lemma form and the desired features such as person, number, tense, and is able to predict the appropriate grammatical conjugati... Read More about Inflection Generation for Spanish Verbs using Supervised Learning.

Improving the Naturalness and Expressivity of Language Generation for Spanish (2017)
Presentation / Conference Contribution
Barros, C., Gkatzia, D., & Lloret, E. (2017, September). Improving the Naturalness and Expressivity of Language Generation for Spanish. Presented at 10th International Conference on Natural Language Generation, Santiago de Compostela, Spain

We present a flexible Natural Language Generation approach for Spanish, focused on the surface realisation stage, which integrates an inflection module in order to improve the naturalness and expressivity of the generated language. This inflection mo... Read More about Improving the Naturalness and Expressivity of Language Generation for Spanish.

Method for Efficient CPU-GPU Streaming for Walkthrough of Full Motion Lightfield Video (2017)
Presentation / Conference Contribution
Chitalu, F. M., Koniaris, B., & Mitchell, K. (2017, December). Method for Efficient CPU-GPU Streaming for Walkthrough of Full Motion Lightfield Video. Presented at 14th European Conference on Visual Media Production (CVMP 2017), London, United Kingdom

Lightfield video, as a high-dimensional function, is very demanding in terms of storage. As such, lightfield video data, even in a compressed form, do not typically fit in GPU or main memory unless the capture area, resolution or duration is sufficie... Read More about Method for Efficient CPU-GPU Streaming for Walkthrough of Full Motion Lightfield Video.

Building an Adaptive E-Learning System (2017)
Presentation / Conference Contribution
Chrysoulas, C., & Fasli, M. (2017, April). Building an Adaptive E-Learning System. Presented at 9th International Conference on Computer Supported Education, Porto, Portugal

Research in adaptive learning is mainly focused on improving learners’ learning achievements based mainly on personalization information, such as learning style, cognitive style or learning achievement. In this paper, an innovative adaptive learning... Read More about Building an Adaptive E-Learning System.

Exploring Musical Creativity through Interactive Cymatics (2017)
Presentation / Conference Contribution
McGowan, J., Leplatre, G., & McGregor, I. (2017, July). Exploring Musical Creativity through Interactive Cymatics. Presented at HCI 2017 - Digital make-believe, Sunderland, UK

What does music look like? Representation of sound has taken many forms over time, from sinusoidal wave patterns, through to random algorithm-based visualisations based on the amplitude of an audio signal. One aspect of music visualisation that has n... Read More about Exploring Musical Creativity through Interactive Cymatics.

Predicting obesity using longitudinal near infra-red spectroscopy (NIRS) data (2017)
Presentation / Conference Contribution
Abdullah, A., Hussain, A., & Khan, I. (2017, May). Predicting obesity using longitudinal near infra-red spectroscopy (NIRS) data. Presented at ICCDA '17: International Conference on Compute and Data Analysis, Lakeland, FL, USA

Globally there has been a dramatic increase in obesity. Thus understanding, predicting and managing obesity has the potential to save lives and billions. Behavioral studies suggest that binging by obese persons is prompted by inflated brain reward ce... Read More about Predicting obesity using longitudinal near infra-red spectroscopy (NIRS) data.

Simulation of PMSM in maxwell 3D/simplorer to optimize direct flux control (2017)
Presentation / Conference Contribution
Mueller, T., See, C., Ghani, A., & Thiemann, P. (2017, June). Simulation of PMSM in maxwell 3D/simplorer to optimize direct flux control. Presented at IEEE International Symposium on Industrial Electronics (ISIE 2017), Edinburgh, Scotland

This paper discusses the problem of a sensorless control method for permanent magnet synchronous machines named Direct Flux Control (DFC). Direct Flux Control provides its users with the angle of the total flux in the machine at all working points, i... Read More about Simulation of PMSM in maxwell 3D/simplorer to optimize direct flux control.

Reviewing the current state of machine learning for artificial intelligence with regards to the use of contextual information (2017)
Presentation / Conference Contribution
Kinch, M. W., Melis, W. J., & Keates, S. (2017, June). Reviewing the current state of machine learning for artificial intelligence with regards to the use of contextual information. Presented at The Second Medway Engineering Conference on Systems: Efficiency, Sustainability and Modelling, Chatham Maritime, Kent

This paper will consider the current state of Machine Learning for Artificial Intelligence, more specifically for applications, such as: Speech Recognition, Game Playing and Image Processing. The artificial world tends to make limited use of context... Read More about Reviewing the current state of machine learning for artificial intelligence with regards to the use of contextual information.