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All Outputs (126)

A Layered Spiking Neural System for Classification Problems (2022)
Journal Article
Zhang, G., Zhang, X., Rong, H., Paul, P., Zhu, M., Neri, F., & Ong, Y.-S. (2022). A Layered Spiking Neural System for Classification Problems. International Journal of Neural Systems, 32(8), Article 2250023. https://doi.org/10.1142/S012906572250023X

Biological brains have a natural capacity for resolving certain classification tasks. Studies on biologically plausible spiking neurons, architectures and mechanisms of artificial neural systems that closely match biological observations while giving... Read More about A Layered Spiking Neural System for Classification Problems.

Software tools for green and sustainable chemistry (2022)
Journal Article
Derbenev, I. N., Twycross, J., Dowden, J., & Hirst, J. D. (2022). Software tools for green and sustainable chemistry. Current Opinion in Green and Sustainable Chemistry, 35, Article 100623. https://doi.org/10.1016/j.cogsc.2022.100623

In this review, we consider green chemistry metrics, related software tools, and the opportunities and challenges for their use in research laboratories. We provide an overview of state-of-the-art software designed both to aid researchers in planning... Read More about Software tools for green and sustainable chemistry.

Evaluation of Contextual and Game-Based Training for Phishing Detection (2022)
Journal Article
Kävrestad, J., Hagberg, A., Nohlberg, M., Rambusch, J., Roos, R., & Furnell, S. (2022). Evaluation of Contextual and Game-Based Training for Phishing Detection. Future Internet, 14(4), Article 104. https://doi.org/10.3390/fi14040104

Cybersecurity is a pressing matter, and a lot of the responsibility for cybersecurity is put on the individual user. The individual user is expected to engage in secure behavior by selecting good passwords, identifying malicious emails, and more. Typ... Read More about Evaluation of Contextual and Game-Based Training for Phishing Detection.

Cluster analyses of the TCGA and a TMA dataset using the coexpression of HSP27 and CRYAB improves alignment with clinical-pathological parameters of breast cancer and suggests different epichaperome influences for each sHSP (2022)
Journal Article
Quinlan, P. R., Figeuredo, G., Mongan, N., Jordan, L. B., Bray, S. E., Sreseli, R., Ashfield, A., Mitsch, J., van den Ijssel, P., Thompson, A. M., & Quinlan, R. A. (2022). Cluster analyses of the TCGA and a TMA dataset using the coexpression of HSP27 and CRYAB improves alignment with clinical-pathological parameters of breast cancer and suggests different epichaperome influences for each sHSP. Cell Stress and Chaperones, 27(2), 177-188. https://doi.org/10.1007/s12192-022-01258-0

Our cluster analysis of the Cancer Genome Atlas for co-expression of HSP27 and CRYAB in breast cancer patients identified three patient groups based on their expression level combination (high HSP27 + low CRYAB; low HSP27 + high CRYAB; similar HSP27 ... Read More about Cluster analyses of the TCGA and a TMA dataset using the coexpression of HSP27 and CRYAB improves alignment with clinical-pathological parameters of breast cancer and suggests different epichaperome influences for each sHSP.

Workplace 4.0: Exploring the Implications of Technology Adoption in Digital Manufacturing on a Sustainable Workforce (2022)
Journal Article
Leesakul, N., Oostveen, A.-M., Eimontaite, I., Wilson, M. L., & Hyde, R. (2022). Workplace 4.0: Exploring the Implications of Technology Adoption in Digital Manufacturing on a Sustainable Workforce. Sustainability, 14(6), Article 3311. https://doi.org/10.3390/su14063311

As part of the Industry 4.0 movement, the introduction of digital manufacturing technologies (DMTs) poses various concerns, particularly the impact of technology adoption on the workforce. In consideration of adoption challenges and implications, var... Read More about Workplace 4.0: Exploring the Implications of Technology Adoption in Digital Manufacturing on a Sustainable Workforce.

X-ray CT reveals 4D root system development and lateral root responses to nitrate in soil (2022)
Journal Article
Griffiths, M., Mellor, N., Sturrock, C. J., Atkinson, B. S., Johnson, J., Mairhofer, S., York, L. M., Atkinson, J. A., Soltaninejad, M., Foulkes, J. F., Pound, M. P., Mooney, S. J., Pridmore, T. P., Bennett, M. J., & Wells, D. M. (2022). X-ray CT reveals 4D root system development and lateral root responses to nitrate in soil. Plant Phenome Journal, 5(1), Article e20036. https://doi.org/10.1002/ppj2.20036

The spatial arrangement of the root system, termed root system architecture, is important for resource acquisition as it directly affects the soil zone explored. Methods for phenotyping roots are mostly destructive, which prevents analysis of roots o... Read More about X-ray CT reveals 4D root system development and lateral root responses to nitrate in soil.

Healthcare Security Incident Response Strategy - A Proactive Incident Response (IR) Procedure (2022)
Journal Article
He, Y., Maglaras, L., Aliyu, A., & Luo, C. (2022). Healthcare Security Incident Response Strategy - A Proactive Incident Response (IR) Procedure. Security and Communication Networks, 2022, Article 2775249. https://doi.org/10.1155/2022/2775249

The healthcare information system (HIS) has become a victim of cyberattacks. Traditional ways to handle cyber incidents in healthcare organizations follow a predefined incident response (IR) procedure. However, this procedure is usually reactive, mis... Read More about Healthcare Security Incident Response Strategy - A Proactive Incident Response (IR) Procedure.

A Deep Learning Method for Fully Automatic Stomatal Morphometry and Maximal Conductance Estimation (2021)
Journal Article
Gibbs, J. A., Mcausland, L., Robles-Zazueta, C. A., Murchie, E. H., & Burgess, A. J. (2021). A Deep Learning Method for Fully Automatic Stomatal Morphometry and Maximal Conductance Estimation. Frontiers in Plant Science, 12, Article 780180. https://doi.org/10.3389/fpls.2021.780180

Stomata are integral to plant performance, enabling the exchange of gases between the atmosphere and the plant. The anatomy of stomata influences conductance properties with the maximal conductance rate, gsmax, calculated from density and size. Howev... Read More about A Deep Learning Method for Fully Automatic Stomatal Morphometry and Maximal Conductance Estimation.

Temporal refinement of 3D CNN semantic segmentations on 4D time-series of undersampled tomograms using hidden Markov models (2021)
Journal Article
Bellos, D., Basham, M., Pridmore, T., & French, A. P. (2021). Temporal refinement of 3D CNN semantic segmentations on 4D time-series of undersampled tomograms using hidden Markov models. Scientific Reports, 11(1), Article 23279. https://doi.org/10.1038/s41598-021-02466-x

Recently, several convolutional neural networks have been proposed not only for 2D images, but also for 3D and 4D volume segmentation. Nevertheless, due to the large data size of the latter, acquiring a sufficient amount of training annotations is mu... Read More about Temporal refinement of 3D CNN semantic segmentations on 4D time-series of undersampled tomograms using hidden Markov models.

Adaptive Fuzzy Learning Superpixel Representation for PolSAR Image Classification (2021)
Journal Article
Guo, Y., Jiao, L., Qu, R., Sun, Z., Wang, S., Wang, S., & Liu, F. (2022). Adaptive Fuzzy Learning Superpixel Representation for PolSAR Image Classification. IEEE Transactions on Geoscience and Remote Sensing, 60, Article 5217818. https://doi.org/10.1109/TGRS.2021.3128908

The increasing applications of polarimetric synthetic aperture radar (PolSAR) image classification demand for effective superpixels’ algorithms. Fuzzy superpixels’ algorithms reduce the misclassification rate by dividing pixels into superpixels, whic... Read More about Adaptive Fuzzy Learning Superpixel Representation for PolSAR Image Classification.

Domain adaptation and federated learning for ultrasonic monitoring of beer fermentation (2021)
Journal Article
Bowler, A. L., Pound, M. P., & Watson, N. J. (2021). Domain adaptation and federated learning for ultrasonic monitoring of beer fermentation. Fermentation, 7(4), Article 253. https://doi.org/10.3390/fermentation7040253

Beer fermentation processes are traditionally monitored through sampling and off-line wort density measurements. In-line and on-line sensors would provide real-time data on the fermentation progress whilst minimising human involvement, enabling ident... Read More about Domain adaptation and federated learning for ultrasonic monitoring of beer fermentation.

Self-Adaptive Particle Swarm Optimization-Based Echo State Network for Time Series Prediction (2021)
Journal Article
Xue, Y., Zhang, Q., & Neri, F. (2021). Self-Adaptive Particle Swarm Optimization-Based Echo State Network for Time Series Prediction. International Journal of Neural Systems, 31(12), Article 2150057. https://doi.org/10.1142/s012906572150057x

Echo state networks (ESNs), belonging to the family of recurrent neural networks (RNNs), are suitable for addressing complex nonlinear tasks due to their rich dynamic characteristics and easy implementation. The reservoir of the ESN is composed of a... Read More about Self-Adaptive Particle Swarm Optimization-Based Echo State Network for Time Series Prediction.

SPMS-ALS: A Single-Point Memetic structure with accelerated local search for instance reduction (2021)
Journal Article
Le, H. L., Neri, F., & Triguero, I. (2022). SPMS-ALS: A Single-Point Memetic structure with accelerated local search for instance reduction. Swarm and Evolutionary Computation, 69, Article 100991. https://doi.org/10.1016/j.swevo.2021.100991

Real-world optimisation problems pose domain specific challenges that often require an ad-hoc algorithmic design to be efficiently addressed. The present paper investigates the optimisation of a key stage in data mining, known as instance reduction,... Read More about SPMS-ALS: A Single-Point Memetic structure with accelerated local search for instance reduction.

Locating Identities in Time: An Examination of the Formation and Impact of Temporality on Presentations of the Self Through Location-based Social Networks (2021)
Journal Article
Papangelis, K., Lykourentzou, I., Khan, V.-J., Chamberlain, A., Cao, T., Saker, M., & Lalone, N. (2021). Locating Identities in Time: An Examination of the Formation and Impact of Temporality on Presentations of the Self Through Location-based Social Networks. ACM Transactions on Social Computing, 4(3), 1-23. https://doi.org/10.1145/3473043

Studies of identity and location-based social networks (LBSN) have tended to focus on the performative aspects associated with marking one’s location. Yet, these studies often present this practice as being an a priori aspect of locative media. What... Read More about Locating Identities in Time: An Examination of the Formation and Impact of Temporality on Presentations of the Self Through Location-based Social Networks.

The Meaning in "the Mix": Using Ethnography to Inform the Design of Intelligent Tools in the Context of Music Production (2021)
Presentation / Conference Contribution
McGarry, G., Chamberlain, A., Crabtree, A., & Greenhalgh, C. (2021, September). The Meaning in "the Mix": Using Ethnography to Inform the Design of Intelligent Tools in the Context of Music Production. Presented at Audio Mostly 2021, Trento University, Italy

In this paper we report on two ethnographic studies of professional music producers at work in their respective studio settings, to underpin the design of intelligent tools and platforms in this domain. The studies are part of a body of work that exp... Read More about The Meaning in "the Mix": Using Ethnography to Inform the Design of Intelligent Tools in the Context of Music Production.

Convolutional feature extraction for process monitoring using ultrasonic sensors (2021)
Journal Article
Bowler, A., Pound, M., & Watson, N. (2021). Convolutional feature extraction for process monitoring using ultrasonic sensors. Computers and Chemical Engineering, 155, Article 107508. https://doi.org/10.1016/j.compchemeng.2021.107508

Ultrasonic sensors are a low-cost and in-line technique and can be combined with machine learning for industrial process monitoring. However, training accurate machine learning models for process monitoring using sensor data is dependant on the featu... Read More about Convolutional feature extraction for process monitoring using ultrasonic sensors.

Connecting Constructive Notions of Ordinals in Homotopy Type Theory (2021)
Presentation / Conference Contribution
Kraus, N., Nordvall Forsberg, F., & Xu, C. (2021, August). Connecting Constructive Notions of Ordinals in Homotopy Type Theory. Presented at 46th International Symposium on Mathematical Foundations of Computer Science (MFCS 2021), Tallinn, Estonia

In classical set theory, there are many equivalent ways to introduce ordinals. In a constructive setting, however, the different notions split apart, with different advantages and disadvantages for each. We consider three different notions of ordinal... Read More about Connecting Constructive Notions of Ordinals in Homotopy Type Theory.

Beyond global and local multi-target learning (2021)
Journal Article
Basgalupp, M., Cerri, R., Schietgat, L., Triguero, I., & Vens, C. (2021). Beyond global and local multi-target learning. Information Sciences, 579, 508-524. https://doi.org/10.1016/j.ins.2021.08.022

In multi-target prediction, an instance has to be classified along multiple target variables at the same time, where each target represents a category or numerical value. There are several strategies to tackle multi-target prediction problems: the lo... Read More about Beyond global and local multi-target learning.

The Extent of User Involvement in the Design of Self-Tracking Technology for Bipolar Disorder: Literature Review (2021)
Preprint / Working Paper
Majid, S., Reeves, S., Figueredo, G., Brown, S., Lang, A., Moore, M., & Morriss, R. The Extent of User Involvement in the Design of Self-Tracking Technology for Bipolar Disorder: Literature Review

Background:
Self-monitoring applications for bipolar disorder are increasing in numbers. The application of user-centred design (UCD) is becoming standardised to optimise the reach, adoption and sustained use of this type of technology.

Objectiv... Read More about The Extent of User Involvement in the Design of Self-Tracking Technology for Bipolar Disorder: Literature Review.