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Potential of geoelectrical methods to monitor root zone processes and structure: A review (2020)
Journal Article
Cimpoiasu, M. O., Kuras, O., Pridmore, T., & Mooney, S. J. (2020). Potential of geoelectrical methods to monitor root zone processes and structure: A review. Geoderma, 365, https://doi.org/10.1016/j.geoderma.2020.114232

© 2020 Understanding the processes that control mass and energy exchanges between soil, plants and the atmosphere plays a critical role for understanding the root zone system, but it is also beneficial for practical applications such as sustainable a... Read More about Potential of geoelectrical methods to monitor root zone processes and structure: A review.

Haptic-Guided Teleoperation of a 7-DoF Collaborative Robot Arm with an Identical Twin Master (2020)
Journal Article
Singh, J., Srinivasan, A., Neumann, G., & Kucukyilmaz, A. (2020). Haptic-Guided Teleoperation of a 7-DoF Collaborative Robot Arm with an Identical Twin Master. IEEE Transactions on Haptics, https://doi.org/10.1109/TOH.2020.2971485

In this study, we describe two techniques to enable haptic-guided teleoperation using 7-DoF cobot arms as master and slave devices. A shortcoming of using cobots as master-slave systems is the lack of force feedback at the master side. However, recen... Read More about Haptic-Guided Teleoperation of a 7-DoF Collaborative Robot Arm with an Identical Twin Master.

An Innovative Approach to Multi-Method Integrated Assessment Modelling of Global Climate Change (2020)
Journal Article
Siebers, P., Lim, Z. E., Figueredo, G. P., & Hey, J. (2020). An Innovative Approach to Multi-Method Integrated Assessment Modelling of Global Climate Change. Journal of Artificial Societies and Social Simulation, 23(1), https://doi.org/10.18564/jasss.4209

Modelling and simulation play an increasingly significant role in exploratory studies for informing policy makers on climate change mitigation strategies. There is considerable research being done in creating Integrated Assessment Models (IAMs), whic... Read More about An Innovative Approach to Multi-Method Integrated Assessment Modelling of Global Climate Change.

A Membrane Parallel Rapidly-Exploring Random Tree Algorithm for Robotic Motion Planning (2020)
Journal Article
Pérez-Hurtado, I., Martínez-Del-Amor, M. A., Zhang, G., Neri, F., & Pérez-Jiménez, M. J. (2020). A Membrane Parallel Rapidly-Exploring Random Tree Algorithm for Robotic Motion Planning. Integrated Computer-Aided Engineering, https://doi.org/10.3233/ICA-190616

In recent years, incremental sampling-based motion planning algorithms have been widely used to solve robot motion planning problems in high-dimensional configuration spaces. In particular, the Rapidly-exploring Random Tree (RRT) algorithm and its as... Read More about A Membrane Parallel Rapidly-Exploring Random Tree Algorithm for Robotic Motion Planning.

A Local Search for Numerical Optimisation based on Covariance Matrix Diagonalisation (2020)
Conference Proceeding
Neri, F., & Rostami, S. (in press). A Local Search for Numerical Optimisation based on Covariance Matrix Diagonalisation

Pattern Search is a family of optimisation algorithms that improve upon an initial solution by performing moves along the directions of a basis of vectors. In its original definition Pattern Search moves along the directions of each variable. Amongst... Read More about A Local Search for Numerical Optimisation based on Covariance Matrix Diagonalisation.

A Local Search with a Surrogate Assisted Option for Instance Reduction (2020)
Conference Proceeding
Neri, F., & Triguero, I. (in press). A Local Search with a Surrogate Assisted Option for Instance Reduction

In data mining, instance reduction is a key data pre-processing step that simplifies and cleans raw data, by either selecting or creating new samples, before applying a learning algorithm. This usually yields to a complex large scale and computationa... Read More about A Local Search with a Surrogate Assisted Option for Instance Reduction.

Performing the Digital Self: Understanding Location-Based Social Networking, Territory, Space, and Identity in the City (2020)
Journal Article
Papangelis, K., Chamberlain, A., Khan, V., Lykourentzou, I., Saker, M., Liang, H., …Cao, T. (2020). Performing the Digital Self: Understanding Location-Based Social Networking, Territory, Space, and Identity in the City. ACM Transactions on Computer-Human Interaction, 27(1), 1-26. https://doi.org/10.1145/3364997

Expressions of territoriality have been positioned as one of the main reasons users alter their behaviors and perceptions of spatiality and sociality while engaging with location-based social networks (LBSN). Despite the potential for this interplay... Read More about Performing the Digital Self: Understanding Location-Based Social Networking, Territory, Space, and Identity in the City.

Sensory Alignment in Immersive Entertainment (2019)
Conference Proceeding
Marshall, J., Benford, S., Byrne, R., & Tennent, P. (2019). Sensory Alignment in Immersive Entertainment. In CHI '19 Proceedings of the 2019 CHI Conference on Human Factors in Computing Systemshttps://doi.org/10.1145/3290605.3300930

When we use digital systems to stimulate the senses, we typically stimulate only a subset of users' senses, leaving other senses stimulated by the physical world. This creates potential for misalignment between senses, where digital and physical stim... Read More about Sensory Alignment in Immersive Entertainment.

MeMa: Designing the Memory Machine (2019)
Conference Proceeding
Price, D., Jacobs, R., Darzentas, D., Perez Vallejos, E., Chadborn, N., Martindale, S., & Urquhart, L. (2019). MeMa: Designing the Memory Machine. In Companion Publication of the 2019 on Designing Interactive Systems Conference 2019 Companion, 271--276. doi:10.1145/3301019.3323882

The Memory Machine is an ambitious project that aims to develop a device to capture people's memories to create a blend of personal and factual data that builds identities, and contextualizes personal recollections. The Memory Machine has been guided... Read More about MeMa: Designing the Memory Machine.

Object landmark discovery through unsupervised adaptation (2019)
Journal Article
Sanchez, E., & Tzimiropoulos, G. (2019). Object landmark discovery through unsupervised adaptation. Advances in Neural Information Processing Systems,

This paper proposes a method to ease the unsupervised learning of object landmark detectors. Similarly to previous methods, our approach is fully unsupervised in a sense that it does not require or make any use of annotated landmarks for the target o... Read More about Object landmark discovery through unsupervised adaptation.

The Effect of Light Intensity, Sensor Height, and Spectral Pre-Processing Methods When Using NIR Spectroscopy to Identify Different Allergen-Containing Powdered Foods (2019)
Journal Article
Rady, A., Fischer, J., Reeves, S., Logan, B., & James Watson, N. (2020). The Effect of Light Intensity, Sensor Height, and Spectral Pre-Processing Methods When Using NIR Spectroscopy to Identify Different Allergen-Containing Powdered Foods. Sensors, 20(1), https://doi.org/10.3390/s20010230

Food allergens present a significant health risk to the human population, so their presence must be monitored and controlled within food production environments. This is especially important for powdered food, which can contain nearly all known food... Read More about The Effect of Light Intensity, Sensor Height, and Spectral Pre-Processing Methods When Using NIR Spectroscopy to Identify Different Allergen-Containing Powdered Foods.

Crowdsourcing in China: Exploring the Work Experiences of Solo Crowdworkers and Crowdfarm Workers (2019)
Conference Proceeding
Wang, Y., Papangelis, K., Khan, V., Lykourentzou, I., Chamberlain, A., & Saker, M. (in press). Crowdsourcing in China: Exploring the Work Experiences of Solo Crowdworkers and Crowdfarm Workers

Recent research highlights the potential of crowdsourcing in China. Yet very few studies explore the workplace context and experiences of Chinese crowdworkers. Those that do, focus mainly on the work experiences of solo crowdworkers but do not deal w... Read More about Crowdsourcing in China: Exploring the Work Experiences of Solo Crowdworkers and Crowdfarm Workers.

Exploring Machine Learning Approaches for Classifying Mental Workload using fNIRS Data from HCI Tasks (2019)
Conference Proceeding
Benerradi, J., Maior, H. A., Marinescu, A., Clos, J., Wilson, M. L., Benerradi, J., …Clos, J. (2019). Exploring Machine Learning Approaches for Classifying Mental Workload using fNIRS Data from HCI Tasks. In Proceedings of the Halfway to the Future Symposium 2019https://doi.org/10.1145/3363384.3363392

Functional Near-Infrared Spectroscopy (fNIRS) has shown promise for being potentially more suitable (than e.g. EEG) for brain-based Human Computer Interaction (HCI). While some machine learning approaches have been used in prior HCI work, this paper... Read More about Exploring Machine Learning Approaches for Classifying Mental Workload using fNIRS Data from HCI Tasks.

A hybrid combinatorial approach to a two-stage stochastic portfolio optimization model with uncertain asset prices (2019)
Journal Article
Cui, T., Bai, R., Ding, S., Parkes, A. J., Qu, R., He, F., & Li, J. (2019). A hybrid combinatorial approach to a two-stage stochastic portfolio optimization model with uncertain asset prices. Soft Computing, https://doi.org/10.1007/s00500-019-04517-y

© 2019, Springer-Verlag GmbH Germany, part of Springer Nature. Portfolio optimization is one of the most important problems in the finance field. The traditional Markowitz mean-variance model is often unrealistic since it relies on the perfect market... Read More about A hybrid combinatorial approach to a two-stage stochastic portfolio optimization model with uncertain asset prices.

Information Retrieval for Evidence-Based Policy Making applied to Lifelong Learning (2019)
Conference Proceeding
Clos, J., Qu, R., & Atkin, J. (2019). Information Retrieval for Evidence-Based Policy Making applied to Lifelong Learning. https://doi.org/10.1007/978-3-030-34885-4_41

Policy making involves an extensive research phase during which existing policies which are similar to the one under development need to be retrieved and analysed. This phase is time-consuming for the following reasons: (i) there is no unified format... Read More about Information Retrieval for Evidence-Based Policy Making applied to Lifelong Learning.

End-of-life vehicle management: a comprehensive review (2019)
Journal Article
Karagoz, S., Aydin, N., & Simic, V. (2019). End-of-life vehicle management: a comprehensive review. Journal of Material Cycles and Waste Management, https://doi.org/10.1007/s10163-019-00945-y

Waste management is gaining very high importance in recent years. As automotive is one of the most critical sectors worldwide, which is rapidly increasing, the management of end-of-life vehicles (ELVs) gains importance day by day. Due to legislation... Read More about End-of-life vehicle management: a comprehensive review.

RootNav 2.0: Deep learning for automatic navigation of complex plant root architectures (2019)
Journal Article
Yasrab, R., Atkinson, J. A., Wells, D. M., French, A. P., Pridmore, T. P., & Pound, M. P. (2019). RootNav 2.0: Deep learning for automatic navigation of complex plant root architectures. GigaScience, 8(11), https://doi.org/10.1093/gigascience/giz123

© The Author(s) 2019. Published by Oxford University Press. BACKGROUND: In recent years quantitative analysis of root growth has become increasingly important as a way to explore the influence of abiotic stress such as high temperature and drought on... Read More about RootNav 2.0: Deep learning for automatic navigation of complex plant root architectures.

RootNav 2.0: Deep Learning for Automatic Navigation of Complex Plant Root Architectures (2019)
Journal Article
Yasrab, R., Atkinson, J. A., Wells, D. M., French, A. P., Pridmore, T. P., & Pound, M. P. (2019). RootNav 2.0: Deep Learning for Automatic Navigation of Complex Plant Root Architectures. GigaScience, 8(11), https://doi.org/10.1101/709147

We present a new image analysis approach that provides fully-automatic extraction of complex root system architectures from a range of plant species in varied imaging setups. Driven by modern deep-learning approaches, RootNav 2.0 replaces previously... Read More about RootNav 2.0: Deep Learning for Automatic Navigation of Complex Plant Root Architectures.