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All Outputs (2001)

L2AE-D: Learning to Aggregate Embeddings for Few-shot Learning with Meta-level Dropout (2021)
Journal Article
Song, H., Torres Torres, M., Özcan, E., & Triguero, I. (2021). L2AE-D: Learning to Aggregate Embeddings for Few-shot Learning with Meta-level Dropout. Neurocomputing, 442, 200-208. https://doi.org/10.1016/j.neucom.2021.02.024

Few-shot learning focuses on learning a new visual concept with very limited labelled examples. A successful approach to tackle this problem is to compare the similarity between examples in a learned metric space based on convolutional neural network... Read More about L2AE-D: Learning to Aggregate Embeddings for Few-shot Learning with Meta-level Dropout.

Demonstrating the potential of indoor positioning for monitoring building occupancy through ecologically valid trials (2021)
Journal Article
Mashuk, M. S., Pinchin, J., Siebers, P. O., & Moore, T. (2021). Demonstrating the potential of indoor positioning for monitoring building occupancy through ecologically valid trials. Journal of Location Based Services, 15(4), 305-327. https://doi.org/10.1080/17489725.2021.1893394

Assessing building performance related to energy consumption in post-design-occupancy stage requires knowledge of building occupancy pattern. These occupancy data can potentially be collected from trials and used to improve the prediction capability... Read More about Demonstrating the potential of indoor positioning for monitoring building occupancy through ecologically valid trials.

Predicting Alcohol Concentration during Beer Fermentation Using Ultrasonic Measurements and Machine Learning (2021)
Journal Article
Bowler, A., Escrig, J., Pound, M., & Watson, N. (2021). Predicting Alcohol Concentration during Beer Fermentation Using Ultrasonic Measurements and Machine Learning. Fermentation, 7(1), Article 34. https://doi.org/10.3390/fermentation7010034

Beer fermentation is typically monitored by periodic sampling and off-line analysis. In-line sensors would remove the need for time-consuming manual operation and provide real-time evaluation of the fermenting media. This work uses a low-cost ultraso... Read More about Predicting Alcohol Concentration during Beer Fermentation Using Ultrasonic Measurements and Machine Learning.

What does it mean for a data subject to make their personal data "manifestly public"? An analysis of GDPR Article 9(2)(e) (2021)
Journal Article
Dove, E. S., & Chen, J. (2021). What does it mean for a data subject to make their personal data "manifestly public"? An analysis of GDPR Article 9(2)(e). International Data Privacy Law, 11(2), 107-124. https://doi.org/10.1093/idpl/ipab005

• This article investigates an under-discussed and potentially significant provision in the EU General Data Protection Regulation (GDPR), namely Article 9(2)(e), which permits processing of special category personal data if the “processing relates to... Read More about What does it mean for a data subject to make their personal data "manifestly public"? An analysis of GDPR Article 9(2)(e).

Organisational responses to the ethical issues of artificial intelligence (2021)
Journal Article
Stahl, B. C., Antoniou, J., Ryan, M., Macnish, K., & Jiya, T. (2022). Organisational responses to the ethical issues of artificial intelligence. AI & Society, 37(1), 23-37. https://doi.org/10.1007/s00146-021-01148-6

The ethics of artificial intelligence (AI) is a widely discussed topic. There are numerous initiatives that aim to develop the principles and guidance to ensure that the development, deployment and use of AI are ethically acceptable. What is generall... Read More about Organisational responses to the ethical issues of artificial intelligence.

Attacking and defence pathways for Intelligent Medical Diagnosis System (IMDS) (2021)
Journal Article
He, Y., Camacho, R. S., Soygazi, H., & Luo, C. (2021). Attacking and defence pathways for Intelligent Medical Diagnosis System (IMDS). International Journal of Medical Informatics, 148, Article 104415. https://doi.org/10.1016/j.ijmedinf.2021.104415

Background

The Intelligent Medical Diagnosis System (IMDS) has been targeted by the cyber attackers, who aim to damage the Healthcare Critical National Infrastructure (CNI). This research is motivated by the recent cyber attacks happened worldwide... Read More about Attacking and defence pathways for Intelligent Medical Diagnosis System (IMDS).

Hydrodynamic characterization of soil compaction using integrated electrical resistivity and X-ray computed tomography (2021)
Journal Article
Cimpoiasu, M. O., Kuras, O., Wilkinson, P., Pridmore, T., & Mooney, S. J. (2021). Hydrodynamic characterization of soil compaction using integrated electrical resistivity and X-ray computed tomography. Vadose Zone Journal, 20(4), Article e20109. https://doi.org/10.1002/vzj2.20109

© 2020 The Authors. Vadose Zone Journal published by Wiley Periodicals LLC on behalf of Soil Science Society of America Modern agricultural practices can cause significant stress on soil, which ultimately has degrading effects, such as compaction. Th... Read More about Hydrodynamic characterization of soil compaction using integrated electrical resistivity and X-ray computed tomography.

Dealing with Scarce Labelled Data: Semi-supervised Deep Learning with Mix Match for Covid-19 Detection Using Chest X-ray Images (2021)
Presentation / Conference Contribution
Calderon-Ramirez, S., Giri, R., Moemeni, A., Umaña, M., Elizondo, D., Torrents-Barrena, J., & Molina-Cabello, M. A. (2021). Dealing with Scarce Labelled Data: Semi-supervised Deep Learning with Mix Match for Covid-19 Detection Using Chest X-ray Images. In Proceedings of ICPR 2020 : 25th International Conference on Pattern Recognition. https://doi.org/10.1109/ICPR48806.2021.9412946

Coronavirus (Covid-19) is spreading fast, infecting people through contact in various forms including droplets from sneezing and coughing. Therefore, the detection of infected subjects in an early, quick and cheap manner is urgent. Currently availabl... Read More about Dealing with Scarce Labelled Data: Semi-supervised Deep Learning with Mix Match for Covid-19 Detection Using Chest X-ray Images.

Understanding cybersecurity behavioral habits: Insights from situational support (2021)
Journal Article
Hong, Y., & Furnell, S. (2021). Understanding cybersecurity behavioral habits: Insights from situational support. Journal of Information Security and Applications, 57, Article 102710. https://doi.org/10.1016/j.jisa.2020.102710

© 2020 While the Internet has become an indispensable aspect of personal and professional lives, it has also served to render many individuals vulnerable to cybersecurity threats. Thus, the promotion of cybersecurity behaviors can effectively protect... Read More about Understanding cybersecurity behavioral habits: Insights from situational support.

"I can't get round": Recruiting Assistance in Mobile Robotic Telepresence (2021)
Journal Article
Boudouraki, A., Fischer, J. E., Reeves, S., & Rintel, S. (2021). "I can't get round": Recruiting Assistance in Mobile Robotic Telepresence. Proceedings of the ACM on Human-Computer Interaction, 4(CSCW3), Article 248. https://doi.org/10.1145/3432947

Via audiovisual communications and a controllable physical embodiment, Mobile Robotic telePresence (MRP) systems aim to support enhanced collaboration between remote and local members of a given setting. But MRP systems also put the remote user in po... Read More about "I can't get round": Recruiting Assistance in Mobile Robotic Telepresence.

Neural Network based Weighting Factor Selection of MPC for Optimal Battery and Load Management in MEA (2020)
Presentation / Conference Contribution
Wang, X., Gao, Y., Atkin, J., & Bozhko, S. (2020). Neural Network based Weighting Factor Selection of MPC for Optimal Battery and Load Management in MEA. . https://doi.org/10.23919/icems50442.2020.9290968

This paper presents a Neural Network (NN)-based weighting factor (WF) selection method for the multi-objective cost function in Model Predictive Control (MPC). MPC is adopted for scheduling the loads and charging/discharging the battery intelligently... Read More about Neural Network based Weighting Factor Selection of MPC for Optimal Battery and Load Management in MEA.

EUSC: A clustering-based surrogate model to accelerate evolutionary undersampling in imbalanced classification (2020)
Journal Article
Le, H. L., Landa-Silva, D., Galar, M., Garcia, S., & Triguero, I. (2021). EUSC: A clustering-based surrogate model to accelerate evolutionary undersampling in imbalanced classification. Applied Soft Computing, 101, Article 107033. https://doi.org/10.1016/j.asoc.2020.107033

© 2020 Learning from imbalanced datasets is highly demanded in real-world applications and a challenge for standard classifiers that tend to be biased towards the classes with the majority of the examples. Undersampling approaches reduce the size of... Read More about EUSC: A clustering-based surrogate model to accelerate evolutionary undersampling in imbalanced classification.

Measuring Mental Workload Variations in Office Work Tasks using fNIRS (2020)
Journal Article
Midha, S., Maior, H. A., Wilson, M. L., & Sharples, S. (2021). Measuring Mental Workload Variations in Office Work Tasks using fNIRS. International Journal of Human-Computer Studies, 147, Article 102580. https://doi.org/10.1016/j.ijhcs.2020.102580

The motivation behind using physiological measures to estimate cognitive activity is typically to build technology that can help people to understand themselves and their work, or indeed for systems to do so and adapt. While functional Near Infrared... Read More about Measuring Mental Workload Variations in Office Work Tasks using fNIRS.

Framing governance for a contested emerging technology:insights from AI policy (2020)
Journal Article
Ulnicane, I., Knight, W., Leach, T., Stahl, B. C., & Wanjiku, W.-G. (2021). Framing governance for a contested emerging technology:insights from AI policy. Policy and Society, 40(2), 158-177. https://doi.org/10.1080/14494035.2020.1855800

This paper examines how the governance in AI policy documents have been framed as way to resolve public controversies surrounding AI. It draws on the studies of governance of emerging technologies, the concept of policy framing, and analysis of 49 re... Read More about Framing governance for a contested emerging technology:insights from AI policy.

Artificial intelligence for human flourishing – Beyond principles for machine learning (2020)
Journal Article
Stahl, B. C., Andreou, A., Brey, P., Hatzakis, T., Kirichenko, A., Macnish, K., …Wright, D. (2021). Artificial intelligence for human flourishing – Beyond principles for machine learning. Journal of Business Research, 124, 374-388. https://doi.org/10.1016/j.jbusres.2020.11.030

The technical and economic benefits of artificial intelligence (AI) are counterbalanced by legal, social and ethical issues. It is challenging to conceptually capture and empirically measure both benefits and downsides. We therefore provide an accoun... Read More about Artificial intelligence for human flourishing – Beyond principles for machine learning.

Test Record (2020)
Presentation / Conference Contribution
Veasey, B., CREATORS_FN: Price, C. V., CREATORS_FN: Green, C. J., CREATORS_FN: Sperring, C. D., CREATORS_FN: Houghton, C. L., Bloggs, & Person, N. U. (2017, August). Test Record. Presented at CHI 2017: ACM CHI Conference on Human Factors in Computing Systems, Magicland

ABSTRACT: This is a test record for the purposes of analysis of collected meta against particular input fieldname titles and how it is exposed through JSON export from eprints (Everything Version)

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This is an adjusted abstract with two ne... Read More about Test Record.

Hyper-Heuristics based on Reinforcement Learning, Balanced Heuristic Selection and Group Decision Acceptance (2020)
Journal Article
Santiago Júnior, V. A. D., Özcan, E., & Carvalho, V. R. D. (2020). Hyper-Heuristics based on Reinforcement Learning, Balanced Heuristic Selection and Group Decision Acceptance. Applied Soft Computing, 97(Part A), Article 106760. https://doi.org/10.1016/j.asoc.2020.106760

In this paper, we introduce a multi-objective selection hyper-heuristic approach combining Reinforcement Learning, (meta)heuristic selection, and group decision-making as acceptance methods, referred to as Hyper-Heuristic based on Reinforcement Learn... Read More about Hyper-Heuristics based on Reinforcement Learning, Balanced Heuristic Selection and Group Decision Acceptance.