Outputs (173)

Machine Learning and the Optimal Choice of Asset Pricing Model (2023)
Book Chapter
Bielinski, A., & Broby, D. (2023). Machine Learning and the Optimal Choice of Asset Pricing Model. In S. Hasan Jafar, H. K, H. El-Chaarani, S. Moturi, & N. Gupta (Eds.), Artificial Intelligence for Capital Markets (91-127). Boca Raton, Florida: Taylor & Francis. https://doi.org/10.1201/9781003327745-7

This chapter evaluates the traditional methods for price prediction and examines what we believe are the most promising machine learning techniques for that task. Asset price forecasting is one of the fundamental problems in the financial field. Trad... Read More about Machine Learning and the Optimal Choice of Asset Pricing Model.

Participatory polyvocal performative and playful interpreting Resnik's 4 for creative placemaking with digital tools (2023)
Book Chapter
Grandison, T., Flint, T., & Jamieson, K. (2023). Participatory polyvocal performative and playful interpreting Resnik's 4 for creative placemaking with digital tools. In D. Giglitto, L. Ciolfi, E. Lockley, & E. Kaldeli (Eds.), Digital Approaches to Inclusion and Participation in Cultural Heritage: Insights from Research and Practice in Europe (114-140). Routledge. https://doi.org/10.4324/9781003277606-7

This chapter discusses inclusive playful encounters made possible through a Digi-Mapping project that ran in partnership with local arts organisation WHALE Arts and participants aged between 8 and 11 from three local primary schools. As part of a bot... Read More about Participatory polyvocal performative and playful interpreting Resnik's 4 for creative placemaking with digital tools.

IoT for Sustainability (2022)
Book Chapter
Davison, B. (2022). IoT for Sustainability. In R. Buyya, L. Garg, G. Fortino, & S. Misra (Eds.), New Frontiers in Cloud Computing and Internet of Things (253-286). Cham: Springer. https://doi.org/10.1007/978-3-031-05528-7_10

The Internet of Things (IoT) comprises a set of complementary technologies which offer unprecedented opportunities for interacting with the physical environment. Faced with multiple pressures on our physical wellbeing such as climate change, habitat... Read More about IoT for Sustainability.

Sign in Human-Sound Interaction (2022)
Book Chapter
Di Donato, B. (2022). Sign in Human-Sound Interaction. In J. L. Drever, & A. Hugill (Eds.), Aural Diversity (187-192). New York: Routledge. https://doi.org/10.4324/9781003183624-21

This chapter explores the concept of Human–Sound Interaction (HSI) in music performance in the context of Aural Diversity. HSI focuses on human factors in experiencing sound and how this affects interaction with instruments. HSI looks at people’s div... Read More about Sign in Human-Sound Interaction.

A Testing Methodology for the Internet of Things Affordable IP Cameras (2022)
Book Chapter
Dzwigala, G., Ghaleb, B., Aldhaheri, T. A., Wadhaj, I., Thomson, C., & Al-Zidi, N. M. (2022). A Testing Methodology for the Internet of Things Affordable IP Cameras. In H. Sharma, V. Shrivastava, K. Kumari Bharti, & L. Wang (Eds.), . Springer. https://doi.org/10.1007/978-981-19-2130-8_37

IP cameras are becoming a cheaper and more convenient option for a lot of households, whether it being for outdoor, indoor security, or as baby or pet monitors. Their security, however, is often lacking, and there is currently no testbed that focuses... Read More about A Testing Methodology for the Internet of Things Affordable IP Cameras.

A Commonsense-Enhanced Document-Grounded Conversational Agent: A Case Study on Task-Based Dialogue (2022)
Book Chapter
Strathearn, C., & Gkatzia, D. (2023). A Commonsense-Enhanced Document-Grounded Conversational Agent: A Case Study on Task-Based Dialogue. In M. Abbas (Ed.), Analysis and Application of Natural Language and Speech Processing (123-144). Cham: Springer. https://doi.org/10.1007/978-3-031-11035-1_6

This paper argues that future dialogue systems must retrieve relevant information from multiple structured and unstructured data sources in order to generate natural and informative responses as well as exhibit commonsense capabilities and flexibilit... Read More about A Commonsense-Enhanced Document-Grounded Conversational Agent: A Case Study on Task-Based Dialogue.

A Fast Inference Framework for Medical Image Semantic Segmentation Tasks Using Deep Learning Framework (2022)
Book Chapter
Yang, S., & Li, Y. (2022). A Fast Inference Framework for Medical Image Semantic Segmentation Tasks Using Deep Learning Framework. In C. H. Chen (Ed.), Computational Intelligence and Image Processing in Medical Applications (157-174). World Scientific Publishing. https://doi.org/10.1142/9789811257452_0010

Deep neural network powered semantic segmentation implementation has great advantages of providing accurate object detection using pixel-based classification; however, when this technique is applied within resource-constrained platforms, such as mobi... Read More about A Fast Inference Framework for Medical Image Semantic Segmentation Tasks Using Deep Learning Framework.

Cyber Threats in the Healthcare Sector and Countermeasures (2022)
Book Chapter
Ahmed, M. M., Maglaras, L., & Ferrag, M. A. (2022). Cyber Threats in the Healthcare Sector and Countermeasures. In M. Khosrow-Pour (Ed.), Research Anthology on Securing Medical Systems and Records. IGI Global. https://doi.org/10.4018/978-1-6684-6311-6.ch001

Healthcare is one of the most targeted industries by cybercriminals. The healthcare sector is far behind in cybersecurity as compared to other organizations. The vulnerabilities in the system open the door for cybercriminals to exploit it and get una... Read More about Cyber Threats in the Healthcare Sector and Countermeasures.

Artificial Intelligence: Practical and Ethical Challenges (2022)
Book Chapter
Rice, S., & Maglaras, L. (2022). Artificial Intelligence: Practical and Ethical Challenges. In M. Ahmed, S. Rabiul Islam, A. Anwar, N. Moustafa, & A. Khan Pathan (Eds.), Explainable Artificial Intelligence for Cyber Security (59-71). Springer. https://doi.org/10.1007/978-3-030-96630-0_3

Artificial Intelligence (AI) & Machine Learning (ML) is used everywhere in daily life from speech recognition on our phones, targeted marketing strategies & face recognition without the majority of society even realising it. The power of technology a... Read More about Artificial Intelligence: Practical and Ethical Challenges.

Lifelong Learning Machines: Towards Developing Optimisation Systems That Continually Learn (2022)
Book Chapter
Hart, E. (2022). Lifelong Learning Machines: Towards Developing Optimisation Systems That Continually Learn. In A. E. Smith (Ed.), Women in Computational Intelligence: Key Advances and Perspectives on Emerging Topics (187-203). Cham: Springer. https://doi.org/10.1007/978-3-030-79092-9_9

Standard approaches to developing optimisation algorithms tend to involve selecting an algorithm and tuning it to work well on a large set of problem instances from the domain of interest. Once deployed, the algorithm remains static, failing to impro... Read More about Lifelong Learning Machines: Towards Developing Optimisation Systems That Continually Learn.