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\n \n 2023\n \n \n (54)\n \n \n

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\n \n\n \n \n \n \n \n Evolving the MCTS Upper Confidence Bounds for Trees Using a Semantic-Inspired Evolutionary Algorithm in the Game of Carcassonne.\n \n \n \n\n\n \n Galván, E.; Simpson, G.; and Ameneyro, F. V.\n\n\n \n\n\n\n IEEE Transactions on Games, 15(3): 420-429. 2023.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n\n\n\n

@ARTICLE{9872022,\n  author={Galván, Edgar and Simpson, Gavin and Ameneyro, Fred Valdez},\n  journal={IEEE Transactions on Games}, \n  title={Evolving the MCTS Upper Confidence Bounds for Trees Using a Semantic-Inspired Evolutionary Algorithm in the Game of Carcassonne}, \n  year={2023},\n  volume={15},\n  number={3},\n  pages={420-429},\n  keywords={Semantics;Games;Evolutionary computation;Statistics;Sociology;Tuning;Genetic programming;  $Carcassonne$  ;genetic programming (GP);Monte Carlo tree search (MCTS);semantics},\n  doi={10.1109/TG.2022.3203232}}\n

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\n \n\n \n \n \n \n \n Toward Context-Aware Information Dissemination in Autonomous Networks of Vehicles.\n \n \n \n\n\n \n Chaudhry, S. R.; Malazi, H. T.; Dhara, S.; Kazmi, A. H.; and Clarke, S.\n\n\n \n\n\n\n IEEE Communications Standards Magazine, 7(2): 8-15. 2023.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n\n\n\n

@ARTICLE{10148974,\n  author={Chaudhry, Saqib Rasool and Malazi, Hadi Tabatabaee and Dhara, Sangita and Kazmi, Aqeel Haider and Clarke, Siobhán},\n  journal={IEEE Communications Standards Magazine}, \n  title={Toward Context-Aware Information Dissemination in Autonomous Networks of Vehicles}, \n  year={2023},\n  volume={7},\n  number={2},\n  abstract={Recent advances in vehicular technologies illuminate the significance of vehicular networking, where information dissemination between constituent network elements plays a crucial role. Information sharing in vehicular networks is challenging because mobility introduces a dynamic environment with overwhelming data traffic. Information-Centric Networking (ICN) reduces overheads by in-network caching and name-oriented communication to mitigate these challenges. However, network resources can be used more efficiently if both RSUs and vehicles are managed autonomously. This article proposes autonomous networking to improve information dissemination in vehicular ICN by using available in-network contextual information. First, a Segment-aware ICN (SA-ICN) scheme is proposed by developing a new dynamic namespace convention. Then, we extend SA-ICN by proposing a Segment and Provider-aware Gossiping enabled ICN (SPG-ICN) that leverages a gossip protocol to self-configure and self-optimize the network using content providers. The simulation results demonstrate performance improvements compared to existing content dissemination schemes regarding packet overheads, data delivery delay, and network load.},\n  pages={8-15},\n  keywords={Vehicular and wireless technologies;Protocols;Context awareness;Simulation;Information-centric networking;Vehicular ad hoc networks;Information sharing},\n  doi={10.1109/MCOMSTD.0002.2200008}}\n\n

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\n \n\n \n \n \n \n \n Rich and Expressive Specification of Continuous-Learning Cyber-Physical Systems.\n \n \n \n\n\n \n Flinkow, T.; Pearlmutter, B. A.; and Monahan, R.\n\n\n \n\n\n\n In 2023 53rd Annual IEEE/IFIP International Conference on Dependable Systems and Networks - Supplemental Volume (DSN-S), pages 197-199, 2023. \n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n\n\n\n

@INPROCEEDINGS{10206677,\n  author={Flinkow, Thomas and Pearlmutter, Barak A. and Monahan, Rosemary},\n  booktitle={2023 53rd Annual IEEE/IFIP International Conference on Dependable Systems and Networks - Supplemental Volume (DSN-S)}, \n  title={Rich and Expressive Specification of Continuous-Learning Cyber-Physical Systems}, \n  year={2023},\n  volume={},\n  number={},\n  pages={197-199},\n  keywords={Uncertainty;Neural networks;Cyber-physical systems;Probabilistic logic;Robustness;Aircraft;Autonomous vehicles;Machine learning;neural networks;cyber-physical systems;formal specifications;formal verification},\n  doi={10.1109/DSN-S58398.2023.00054}}\n

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\n \n\n \n \n \n \n \n \n A System for Dense Monocular Mapping with a Fisheye Camera.\n \n \n \n \n\n\n \n Gallagher, L.; Sistu, G.; Horgan, J.; and McDonald, J. B.\n\n\n \n\n\n\n In 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), pages 6479-6487, 2023. \n \n\n\n\n
\n\n\n\n \n \n $\"A$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n\n\n\n

@INPROCEEDINGS{10208776,\n  author={Gallagher, Louis and Sistu, Ganesh and Horgan, Jonathan and McDonald, John B.},\n  booktitle={2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)}, \n  title={A System for Dense Monocular Mapping with a Fisheye Camera}, \n  year={2023},\n  volume={},\n  number={},\n  url={https://openaccess.thecvf.com/content/CVPR2023W/OmniCV/papers/Gallagher_A_System_for_Dense_Monocular_Mapping_With_a_Fisheye_Camera_CVPRW_2023_paper.pdf},\n  pages={6479-6487},\n  keywords={Measurement;Deformable models;Surface reconstruction;Simultaneous localization and mapping;Deformation;Cameras;Trajectory},\n  doi={10.1109/CVPRW59228.2023.00689}}\n\n

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\n \n\n \n \n \n \n \n Digital Twins: A Vehicle Platooning Simulation System for VR.\n \n \n \n\n\n \n Yuan, X.; Du, J.; Yao, Y.; Xu, J.; Wu, G.; Culligan, N.; Bierig, R.; and Bi, T.\n\n\n \n\n\n\n In 2023 IEEE Smart World Congress (SWC), pages 1-6, Aug 2023. \n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n\n\n\n

@INPROCEEDINGS{10448717,\n  author={Yuan, Xiaxin and Du, Jiacheng and Yao, Yilin and Xu, Jiasen and Wu, Gaoyuan and Culligan, Natalie and Bierig, Ralf and Bi, Ting},\n  booktitle={2023 IEEE Smart World Congress (SWC)}, \n  title={Digital Twins: A Vehicle Platooning Simulation System for VR}, \n  year={2023},\n  volume={},\n  number={},\n  pages={1-6},\n  abstract={This system mainly studies the development and application of autonomous driving simulation platform based on virtual reality (VR) technology. A digital twin vehicle platooning simulation system (DTVPSS) is proposed. Digital twin and vehicle platooning (VP) are both concepts that have been proposed. However, developing a complete virtual platform for vehicle queues, with interactive control between the virtual and physical worlds, has rarely been explored. In order to solve this problem, This paper digital twin technology is innovative applied to vehicle queue simulation platform. Digital twin and VR technology build highly simulated and reliable systems. The innovation point of the system is to realize the following of vehicles and form the autonomous driving of car formation by considering the collaborative planning technical scheme between vehicles. The system makes the VP no longer only controlled by hardware, increases the software operability of the VP, and provides a more real, convenient and economical virtual simulation platform with low delay.},\n  keywords={Technological innovation;Virtual reality;Software;Digital twins;Software reliability;Planning;Autonomous vehicles;digital twin;vehicle platooning;driving;virtual reality technology},\n  doi={10.1109/SWC57546.2023.10448717},\n  ISSN={},\n  month={Aug},}\n

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\n \n\n \n \n \n \n \n Banging Interaction in Ubiquitous Music.\n \n \n \n\n\n \n Keller, D.; Yaseen, A.; Messina, M.; Chakraborty, S.; Aliel, L.; Lazzarini, V.; Simurra, I.; and Timoney, J.\n\n\n \n\n\n\n In Brooks, A. L., editor(s), ArtsIT, Interactivity and Game Creation, pages 489–503, Cham, 2023. Springer Nature Switzerland\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@InProceedings{10.1007/978-3-031-28993-4_34,\nauthor="Keller, Dami{\\'a}n\nand Yaseen, Azeema\nand Messina, Marcello\nand Chakraborty, Sutirtha\nand Aliel, Luzilei\nand Lazzarini, Victor\nand Simurra, Ivan\nand Timoney, Joseph",\neditor="Brooks, Anthony L.",\ntitle="Banging Interaction in Ubiquitous Music",\nbooktitle="ArtsIT, Interactivity and Game Creation",\nyear="2023",\ndoi={10.1007/978-3-031-28993-4_34},\npublisher="Springer Nature Switzerland",\naddress="Cham",\npages="489--503",\nabstract="We explore a new conceptual framework for interaction design in the context of ubiquitous musical activities, banging interaction. Our proposal entails a shift of focus from instruments, tools or device-oriented approaches to a timbre-led design practice that targets the potential relationships between sonic and multimodal qualities and the local available technological resources. One thread of this perspective envisages more flexible usage through the application of adaptive techniques. Another thread engages with recent advances in mid-air interaction, hinting at multimodal sensing. Yet another thread involves the incorporation of an aesthetically pliable approach to sonic materials, materialised through timbre as a target, rather than `notes', `instruments' or `orchestras'. We present two examples of deployments: The prototype mixDroid, one of the first systems to employ mobile devices in everyday settings for creative purposes, and the prototype Dynamic Drum Collective, an adaptive implementation for percussive sources based on visual tokens and whole-body interaction.",\nisbn="978-3-031-28993-4"\n}\n\n

\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n Verifying Event-B Hybrid Models Using Cyclone.\n \n \n \n\n\n \n Wu, H.; and Cheng, Z.\n\n\n \n\n\n\n In Glässer, U.; Creissac Campos, J.; Méry, D.; and Palanque, P., editor(s), Rigorous State-Based Methods, pages 179–184, Cham, 2023. Springer Nature Switzerland\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@InProceedings{10.1007/978-3-031-33163-3_13,\nauthor="Wu, Hao\nand Cheng, Zheng",\neditor="Gl{\\"a}sser, Uwe\nand Creissac Campos, Jose\nand M{\\'e}ry, Dominique\nand Palanque, Philippe",\ntitle="Verifying Event-B Hybrid Models Using Cyclone",\nbooktitle="Rigorous State-Based Methods",\nyear="2023",\npublisher="Springer Nature Switzerland",\naddress="Cham",\ndoi={10.1007/978-3-031-33163-3_13},\npages="179--184",\nabstract="Modelling hybrid systems using Event-B is challenging and users typically are unsure about whether their Event-B models are over/under-specified. In this short paper, we present a work-in-progress specification language called Cyclone to tackle this challenge. We demonstrate how one can use Cyclone to check an Event-B hybrid model using a car controller example. Our demonstration shows that Cyclone has a great potential to be used to verify Event-B hybrid models.",\nisbn="978-3-031-33163-3"\n}\n\n

\n\n\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n Building Specifications in the Event-B Institution: A Summary.\n \n \n \n\n\n \n Farrell, M.; Monahan, R.; and Power, J. F.\n\n\n \n\n\n\n In Glässer, U.; Creissac Campos, J.; Méry, D.; and Palanque, P., editor(s), Rigorous State-Based Methods, pages 245–253, Cham, 2023. Springer Nature Switzerland\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@InProceedings{10.1007/978-3-031-33163-3_19,\nauthor="Farrell, Marie\nand Monahan, Rosemary\nand Power, James F.",\neditor="Gl{\\"a}sser, Uwe\nand Creissac Campos, Jose\nand M{\\'e}ry, Dominique\nand Palanque, Philippe",\ntitle="Building Specifications in the Event-B Institution: A Summary",\nbooktitle="Rigorous State-Based Methods",\nyear="2023",\npublisher="Springer Nature Switzerland",\naddress="Cham",\ndoi={10.1007/978-3-031-33163-3_19},\npages="245--253",\nabstract="This ``journal-first'' paper summarises a publication by the same authors in the journal Logical Methods in Computer Science which describes a formal semantics for the Event-B specification language using the theory of institutions. It defines an institution for Event-B and shows how the constructs of the Event-B specification language can be mapped into our institution. This algebraic semantics distinguishes three constituent sub-languages of Event-B: the superstructure, infrastructure and mathematical languages. An important impact of this work is that our semantics provides access to the generic modularisation constructs available in institutions, including specification-building operators for parameterisation and refinement. We demonstrate how these features subsume and enhance the corresponding features already present in Event-B through a detailed study of their use in a worked example. Further benefits of the institutional approach are its provision for mathematically definable interoperability to facilitate heterogeneous specification.",\nisbn="978-3-031-33163-3"\n}\n\n

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\n \n\n \n \n \n \n \n \n .\n \n \n \n \n\n\n \n Palma, G. R.; Hackett, C. P.; and Markham, C.\n\n\n \n\n\n\n Machine Vision Applied to Entomology, pages 149–184. A. Moral, R.; and Godoy, W. A., editor(s). Springer International Publishing, Cham, 2023.\n \n\n\n\n
\n\n\n\n \n \n $\"Machine$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@Inbook{Palma2023,\nauthor="Palma, Gabriel R.\nand Hackett, Conor P.\nand Markham, Charles",\neditor="A. Moral, Rafael\nand Godoy, Wesley A.C.",\ntitle="Machine Vision Applied to Entomology",\nbookTitle="Modelling Insect Populations in Agricultural Landscapes",\nyear="2023",\npublisher="Springer International Publishing",\naddress="Cham",\npages="149--184",\nabstract="Machine vision has produced many helpful image processing techniques in several fields, such as object detection, classification, and segmentation. Machine vision is an interdisciplinary field that combines methods from computer vision and machine learning, mainly deep learning to solve issues. Common issues, such as classification and localisation, are typical examples that combine these research fields. These techniques have many applications in entomology. In the entomological context, classification methods identify insect species or features of an insect, and localisation methods return their position within a scene. The available techniques for localisation and classification benefit the entomological community by assisting specialists. This chapter introduces the application of machine vision methods to identify and localise insects and the features of their anatomy. The machine vision pipeline, image descriptors, and fundamental methods, such as thresholding, blob, and contour detection, are presented. Deep Learning (DL) methods are applied for insect classification, focusing on Deep Neural Networks and Convolutional Neural Networks (CNNs), including concepts of transfer learning applied to insect classification. A dataset of medically and forensically important flies, Diptera, is used to illustrate these methods. CNN-based methods are described for insect localisation, and semantic segmentation using the U-Net architecture trained on the dataset of flies is presented. The dimensional reduction method PaCMAP is applied to visualise the feature extracted from the fly datasets. The Grad-CAM method is used on the flies datasets to assist insect object localisation. Finally, different platforms of computing are presented and compared under three different metrics of performance, power consumption, and operating temperature.",\nisbn="978-3-031-43098-5",\ndoi="10.1007/978-3-031-43098-5_9",\nurl="https://doi.org/10.1007/978-3-031-43098-5_9"\n}\n\n

\n\n\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n Gesture Mediated Timbre-Led Design based Music Interface for Socio-musical Interaction.\n \n \n \n\n\n \n Yaseen, A.; Chakraborty, S.; and Timoney, J.\n\n\n \n\n\n\n In Kurosu, M.; Hashizume, A.; Marcus, A.; Rosenzweig, E.; Soares, M. M.; Harris, D.; Li, W.; Schmorrow, D. D.; Fidopiastis, C. M.; and Rau, P. P., editor(s), HCI International 2023 – Late Breaking Papers, pages 335–347, Cham, 2023. Springer Nature Switzerland\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@InProceedings{10.1007/978-3-031-48038-6_21,\nauthor="Yaseen, Azeema\nand Chakraborty, Sutirtha\nand Timoney, Joseph",\neditor="Kurosu, Masaaki\nand Hashizume, Ayako\nand Marcus, Aaron\nand Rosenzweig, Elizabeth\nand Soares, Marcelo M.\nand Harris, Don\nand Li, Wen-Chin\nand Schmorrow, Dylan D.\nand Fidopiastis, Cali M.\nand Rau, Pei-Luen Patrick",\ntitle="Gesture Mediated Timbre-Led Design based Music Interface for Socio-musical Interaction",\nbooktitle="HCI International 2023 -- Late Breaking Papers",\nyear="2023",\ndoi={10.1007/978-3-031-48038-6_21},\npublisher="Springer Nature Switzerland",\naddress="Cham",\npages="335--347",\nabstract="Third-wave HCI broadens technology from traditional settings to everyday life. This wave has also influenced the internet of musical things (IoMusT) and ubiquitous music (ubimus), and these fields are inspired by the idea of including everyday things to act as musical things and become part of the push for ubiquitous computing for musical activities. This multiplies the possibilities in which musical interactions can occur and thus allows participants with various levels of musical experience to engage in musical activities. The interface design that not only supports musical activities but also delivers the experience of the musical activity is a challenging task for IoMusT. This paper presents a gesture-based timbre-led musical interface designed for casual musical activities. Earlier studies with this interface have shown the social aspect of interpersonal interactions in a musical activity. As music has a social role when individuals are connected in a musical activity, it is vital to understand the patterns of these interpersonal interactions. Here, we present a qualitative study that explores this social bond and how individuals perceive their own abilities and participation during such activities. The individual and dyadic musical interactions were structured into two steps and the results are explained to discuss the dimensions of this interaction.",\nisbn="978-3-031-48038-6"\n}\n\n

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\n \n\n \n \n \n \n \n \n DEVELOPING A COLLABORATIVE LEARNING APPLICATION TO SUPPORT EFFECTIVE STUDENT COLLABORATION IN HYBRID LEARNING ENVIRONMENTS.\n \n \n \n \n\n\n \n O'Neill, S.; and Mooney, A.\n\n\n \n\n\n\n In EDULEARN23 Proceedings, of 15th International Conference on Education and New Learning Technologies, pages 4931-4936, 3-5 July, 2023 2023. IATED\n \n\n\n\n
\n\n\n\n \n \n $\"DEVELOPING$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@InProceedings{ONEILL2023DEV,\nauthor    = {O'Neill, S. and Mooney, A.},\ntitle     = {DEVELOPING A COLLABORATIVE LEARNING APPLICATION TO SUPPORT EFFECTIVE STUDENT COLLABORATION IN HYBRID LEARNING ENVIRONMENTS},\nseries    = {15th International Conference on Education and New Learning Technologies},\nbooktitle = {EDULEARN23 Proceedings},\nisbn      = {978-84-09-52151-7},\nissn      = {2340-1117},\ndoi       = {10.21125/edulearn.2023.1300},\nurl       = {https://doi.org/10.21125/edulearn.2023.1300},\npublisher = {IATED},\nlocation  = {Palma, Spain},\nmonth     = {3-5 July, 2023},\nyear      = {2023},\npages     = {4931-4936}}

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\n \n\n \n \n \n \n \n Biogeochemical properties of blue carbon sediments influence the distribution and monomer composition of bacterial polyhydroxyalkanoates (PHA).\n \n \n \n\n\n \n Grey, A.; Costeira, R.; Lorenzo, E.; O'Kane, S.; McCaul, M.; McCarthy, T.; Jordan, S.; Allen, C.; and Kelleher, B.\n\n\n \n\n\n\n Biogeochemistry, 162(3): 359-380. 2023.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@article{Grey2023,\nauthor={Grey, A. and Costeira, R. and Lorenzo, E. and O'Kane, S. and McCaul, M.V. and McCarthy, T. and Jordan, S.F. and Allen, C.C.R. and Kelleher, B.P.},\ntitle={Biogeochemical properties of blue carbon sediments influence the distribution and monomer composition of bacterial polyhydroxyalkanoates (PHA)},\njournal={Biogeochemistry},\nyear={2023},\nvolume={162},\nnumber={3},\npages={359-380}, \ndoi={10.1007/s10533-022-01008-5},\nabstract={Coastal wetlands are highly efficient 'blue carbon' sinks which contribute to mitigating climate change through the long-term removal of atmospheric CO2 and capture of carbon (C). Microorganisms are integral to C sequestration in blue carbon sediments and face a myriad of natural and anthropogenic pressures yet their adaptive responses are poorly understood. One such response in bacteria is the alteration of biomass lipids, specifically through the accumulation of polyhydroxyalkanoates (PHAs) and alteration of membrane phospholipid fatty acids (PLFA). PHAs are highly reduced bacterial storage polymers that increase bacterial fitness in changing environments. In this study, we investigated the distribution of microbial PHA, PLFA profiles, community structure and response to changes in sediment geochemistry along an elevation gradient from intertidal to vegetated supratidal sediments. We found highest PHA accumulation, monomer diversity and expression of lipid stress indices in elevated and vegetated sediments where C, nitrogen (N), PAH and heavy metals increased, and pH was significantly lower. This was accompanied by a reduction in bacterial diversity and a shift to higher abundances of microbial community members favouring complex C degradation. Results presented here describe a connection between bacterial PHA accumulation, membrane lipid adaptation, microbial community composition and polluted C rich sediments.},\n}\n\n

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\n \n\n \n \n \n \n \n \n A reproducible approach to generating synthetic spatial data for teaching and learning purposes.\n \n \n \n \n\n\n \n Gorry, P.; and Mooney, P.\n\n\n \n\n\n\n In 31st Annual Geographical Information Science Research UK Conference (GISRUK), Glasgow, Scotland, April 2023. Zenodo\n \n\n\n\n
\n\n\n\n \n \n $\"A$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{gorry_2023_7825100,\n  title        = {A reproducible approach to generating synthetic \n                   spatial data for teaching and learning purposes},\n  author ={ Gorry, Paddy and Mooney, Peter},\n  year         = {2023},\n  publisher    = {Zenodo},\nbooktitle={31st Annual Geographical Information Science Research UK Conference (GISRUK)},\naddress={Glasgow, Scotland},\n  month        = {April},\n  doi          = {10.5281/zenodo.7825100},\n  url          = {https://doi.org/10.5281/zenodo.7825100}\n}\n\n

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\n \n\n \n \n \n \n \n \n Development of a Classification-based Eye Gaze estimation technique using an Integrated Laptop Camera: two models are better than one.\n \n \n \n \n\n\n \n \n\n\n \n\n\n\n In August 2023. Zenodo\n \n\n\n\n
\n\n\n\n \n \n $\"Development$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{cribbin_2023_8217852,\n  title        = {Development of a Classification-based Eye Gaze \n                   estimation technique using an Integrated Laptop\n                   Camera: two models are better than one},\n  year         = {2023},\n  publisher    = {Zenodo},\n  month        = {August},\n  abstract={While there are many purely software-based solutions available for live head pose tracking, the same is not true for gaze\nestimation which is usually done using specialised hardware; typically, eye-trackers that use infrared light sources and\nspecial camera. The challenge when using vision-based Machine Learning methods to estimate gaze from an image of a\nuser is that the features of a user's eyes that vary with gaze position are small and difficult to track. This paper describes\na classification-based Convolutional Neural Network (CNN) system that can, from images of a user's face, estimate where\non a screen they are looking in real time. Labelled images of an individual looking at specified regions of a screen were\ncollected, and these images were used to train a Deep Learning model. The final model trained was found to be accurate\nenough to correctly guess which section of the screen (3x3 grid) the user is looking in over 99% of the time. The current\nsystem requires strict input conditions on head orientation, a limitation on the system. The integration of head pose\nestimation and methods of improving resolution are discussed. The approach uses two classifiers, one for horizontal gaze\n(3 regions) and another for vertical gaze (3 regions) combined to estimate gaze location. This approach was found to be\nmore effective than a single classifier for nine separate regions. Using both eyes, excluding the nose region and other\nfacial features of the input images also improved performance.},\n  doi          = {10.5281/zenodo.8217852},\n  url          = {https://doi.org/10.5281/zenodo.8217852}\n}\n\n

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\n \n\n \n \n \n \n \n \n Initial Steps Towards Tackling High-dimensional Surrogate Modeling for Neuroevolution Using Kriging Partial Least Squares.\n \n \n \n \n\n\n \n Stapleton, F.; and Galvan, E.\n\n\n \n\n\n\n In Proceedings of the Companion Conference on Genetic and Evolutionary Computation, of GECCO '23 Companion, pages 83–84, New York, NY, USA, 2023. Association for Computing Machinery\n \n\n\n\n
\n\n\n\n \n \n $\"Initial$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@inproceedings{10.1145/3583133.3596437,\nauthor = {Stapleton, Fergal and Galvan, Edgar},\ntitle = {Initial Steps Towards Tackling High-dimensional Surrogate Modeling for Neuroevolution Using Kriging Partial Least Squares},\nyear = {2023},\nisbn = {9798400701207},\npublisher = {Association for Computing Machinery},\naddress = {New York, NY, USA},\nurl = {https://doi.org/10.1145/3583133.3596437},\ndoi = {10.1145/3583133.3596437},\nabstract = {Surrogate-assisted evolutionary algorithms (SAEAs) aim to use efficient computational models with the goal of approximating the fitness function in evolutionary computation systems. This area of research has received significant attention from the specialised research community in different areas, for example, single and many objective optimisation or dynamic and stationary optimisation problems. An emergent and exciting area that has received little attention from the SAEAs community is in neuroevolution. This refers to the use of evolutionary algorithms in the automatic configuration of artificial neural network (ANN) architectures, hyper-parameters and/or the training of ANNs. However, ANNs suffer from two major issues: (a) the use of highly-intense computational power for their correct training, and (b) the highly specialised human expertise required to correctly configure ANNs necessary to get a well-performing network. This work aims to fill this important research gap in SAEAs in neuroevolution by addressing these two issues. We demonstrate how one can use a Kriging Partial Least Squares method in place of the well-known Kriging method, which normally cannot be used in neuroevolution due to the high dimensionality of the data.},\nbooktitle = {Proceedings of the Companion Conference on Genetic and Evolutionary Computation},\npages = {83–84},\nnumpages = {2},\nkeywords = {partial least squares, kriging, surrogate-assisted evolutionary algorithms, neural architecture search, neuroevolution},\nlocation = {Lisbon, Portugal},\nseries = {GECCO '23 Companion}\n}\n\n

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\n \n\n \n \n \n \n \n \n A Computational Thinking Obstacle Course Based on Bebras Tasks for K-12 Schools.\n \n \n \n \n\n\n \n Lehtimäki, T.; Monahan, R.; Mooney, A.; Casey, K.; and Naughton, T. J.\n\n\n \n\n\n\n In Proceedings of the 2023 Conference on Innovation and Technology in Computer Science Education V. 1, of ITiCSE 2023, pages 478–484, New York, NY, USA, 2023. Association for Computing Machinery\n \n\n\n\n
\n\n\n\n \n \n $\"A$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@inproceedings{10.1145/3587102.3588775,\nauthor = {Lehtim\\"{a}ki, Taina and Monahan, Rosemary and Mooney, Aidan and Casey, Kevin and Naughton, Thomas J.},\ntitle = {A Computational Thinking Obstacle Course Based on Bebras Tasks for K-12 Schools},\nyear = {2023},\nisbn = {9798400701382},\npublisher = {Association for Computing Machinery},\naddress = {New York, NY, USA},\nurl = {https://doi.org/10.1145/3587102.3588775},\ndoi = {10.1145/3587102.3588775},\nabstract = {This paper describes an unplugged computational thinking (CT) resource for primary and secondary schools developed from Bebras tasks. In Ireland, CT is not part of the primary school curriculum or mandatory in secondary schools. However, the National Council for Curriculum and Assessment is in the process of revising the primary school curriculum to include aspects of CT. Our aim for creating this CT Obstacle Course is to introduce teachers (and pupils) without formal computer science training to the subject of CT. This is done in a manner that informs and motivates, and gives them the confidence to deliver CT materials in the classroom. We also want to find out from teachers how useful and important this type of resource is for developing problem-solving skills, and if our unplugged activity can support learning at various skill levels. Our CT Obstacle Course includes 14 Bebras tasks for primary schools and an additional 6 Bebras tasks for secondary schools. The activity is suitable for indoors and outdoors and is completed in groups, promoting teamwork and communication. We have delivered it to 146 primary school classes during 38 school visits between May 2021 and June 2022. It has been undertaken by 3,445 pupils and 195 teachers and other school staff. This paper describes our CT resource in detail, and reports teacher feedback from primary schools.},\nbooktitle = {Proceedings of the 2023 Conference on Innovation and Technology in Computer Science Education V. 1},\npages = {478–484},\nnumpages = {7},\nkeywords = {Bebras tasks, K-12, computational thinking, unplugged},\nlocation = {<conf-loc>, <city>Turku</city>, <country>Finland</country>, </conf-loc>},\nseries = {ITiCSE 2023}\n}\n\n

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\n \n\n \n \n \n \n \n \n Computational Thinking Resources Inspired by Bebras.\n \n \n \n \n\n\n \n Lehtimäki, T.; Monahan, R.; Mooney, A.; Casey, K.; and Naughton, T. J.\n\n\n \n\n\n\n In Proceedings of the 2023 Conference on Innovation and Technology in Computer Science Education V. 2, of ITiCSE 2023, pages 663, New York, NY, USA, 2023. Association for Computing Machinery\n \n\n\n\n
\n\n\n\n \n \n $\"Computational$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@inproceedings{10.1145/3587103.3594203,\nauthor = {Lehtim\\"{a}ki, Taina and Monahan, Rosemary and Mooney, Aidan and Casey, Kevin and Naughton, Thomas J.},\ntitle = {Computational Thinking Resources Inspired by Bebras},\nyear = {2023},\nisbn = {9798400701399},\npublisher = {Association for Computing Machinery},\naddress = {New York, NY, USA},\nurl = {https://doi.org/10.1145/3587103.3594203},\ndoi = {10.1145/3587103.3594203},\nabstract = {In this poster, we highlight computational thinking resources for schools from the PACT team at Maynooth University, Ireland. The resources are derived from tasks from the Bebras international computational thinking initiative. The different modalities work together throughout the school year to provide initial exposure to computational thinking, and include an obstacle course, seasonal tasks, and a workbook.},\nbooktitle = {Proceedings of the 2023 Conference on Innovation and Technology in Computer Science Education V. 2},\npages = {663},\nnumpages = {1},\nkeywords = {Bebras tasks, K-12, computational thinking, unplugged},\nlocation = {<conf-loc>, <city>Turku</city>, <country>Finland</country>, </conf-loc>},\nseries = {ITiCSE 2023}\n}\n\n

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\n \n\n \n \n \n \n \n \n Introduction to the Special Collection from iFM 2022.\n \n \n \n \n\n\n \n Monahan, R.; and ter Beek, M. H.\n\n\n \n\n\n\n Form. Asp. Comput., 35(3). sep 2023.\n \n\n\n\n
\n\n\n\n \n \n $\"Introduction$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{10.1145/3622995,\nauthor = {Monahan, Rosemary and ter Beek, Maurice H.},\ntitle = {Introduction to the Special Collection from iFM 2022},\nyear = {2023},\nissue_date = {September 2023},\npublisher = {Association for Computing Machinery},\naddress = {New York, NY, USA},\nvolume = {35},\nnumber = {3},\nissn = {0934-5043},\nurl = {https://doi.org/10.1145/3622995},\ndoi = {10.1145/3622995},\nabstract = {This special collection arose from the 17th International Conference on integrated Formal Methods (iFM) held in beautiful Lugano, Switzerland, hosted by the Software Institute of USI Universit\\`{a} della Svizzera italiana.},\njournal = {Form. Asp. Comput.},\nmonth = {sep},\narticleno = {17},\nnumpages = {2},\nkeywords = {synthesis, static analysis, theorem proving, integrated formal methods}\n}\n\n\n

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\n \n\n \n \n \n \n \n \n Evolving Towards a Trustworthy AIEd Model to Predict at Risk Students in Introductory Programming Courses.\n \n \n \n \n\n\n \n Quille, K.; Vidal-Meliá, L.; Nolan, K.; and Mooney, A.\n\n\n \n\n\n\n In Proceedings of the 2023 Conference on Human Centered Artificial Intelligence: Education and Practice, of HCAIep '23, pages 22–28, New York, NY, USA, 2023. Association for Computing Machinery\n \n\n\n\n
\n\n\n\n \n \n $\"Evolving$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@inproceedings{10.1145/3633083.3633190,\nauthor = {Quille, Keith and Vidal-Meli\\'{a}, Lidia and Nolan, Keith and Mooney, Aidan},\ntitle = {Evolving Towards a Trustworthy AIEd Model to Predict at Risk Students in Introductory Programming Courses},\nyear = {2023},\nisbn = {9798400716461},\npublisher = {Association for Computing Machinery},\naddress = {New York, NY, USA},\nurl = {https://doi.org/10.1145/3633083.3633190},\ndoi = {10.1145/3633083.3633190},\nabstract = {Artificial intelligence in education has the potential to transform the educational landscape and influence the role of the involved stakeholders. With recent European Commission publications on the use of artificial intelligence and data in education and training, in addition to the Ethics Guidelines for Trustworthy AI and the forthcoming AI act, there is now a precedent that using AI, in and for education, needs to be more trustworthy (transparent and explainable) to be considered for adoption. This paper further develops an AIEd model (PreSS - Predicting Student Success) that has been developed, validated and re-validated over almost two decades, focusing on explainability and transparency. PreSS aims to identify students who are at risk of failing or dropping out of introductory programming courses. This paper presents our recent work to describe PreSS in the context of a trustworthy model, that is both explainable and transparent. First, for explainability, we present Explainable AI (XAI) approaches to describe how predictions are made, and what set of inputs leads to such decisions, which has not been presented before for PreSS. Second, to examine transparency, we present confusion metrics, focusing first on predicting the performance of all students and then on performance at sub-group level such as by gender and age. Finally, we present a model card illustrating where the model performs well and where it does not. All of these steps provide an evolution towards trustworthy educational AI.},\nbooktitle = {Proceedings of the 2023 Conference on Human Centered Artificial Intelligence: Education and Practice},\npages = {22–28},\nnumpages = {7},\nkeywords = {CS1., Computer Science Education, Machine Learning, Predicting Success, Programming},\nlocation = {<conf-loc>, <city>Dublin</city>, <country>Ireland</country>, </conf-loc>},\nseries = {HCAIep '23}\n}\n\n

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\n \n\n \n \n \n \n \n \n Immersive Neural Network Exploration: A VR Approach to Human-Centered AI Understanding.\n \n \n \n \n\n\n \n Inkarbekov, M.; Pearlmutter, B. A.; and Monahan, R.\n\n\n \n\n\n\n In Proceedings of the 2023 Conference on Human Centered Artificial Intelligence: Education and Practice, of HCAIep '23, pages 48, New York, NY, USA, 2023. Association for Computing Machinery\n \n\n\n\n
\n\n\n\n \n \n $\"Immersive$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{10.1145/3633083.3633221,\nauthor = {Inkarbekov, Medet and Pearlmutter, Barak A. and Monahan, Rosemary},\ntitle = {Immersive Neural Network Exploration: A VR Approach to Human-Centered AI Understanding},\nyear = {2023},\nisbn = {9798400716461},\npublisher = {Association for Computing Machinery},\naddress = {New York, NY, USA},\nurl = {https://doi.org/10.1145/3633083.3633221},\ndoi = {10.1145/3633083.3633221},\nabstract = {In today’s rapidly evolving artificial intelligence (AI) landscape, the complexity of neural networks, especially in deep learning, presents significant challenges for intuitive human understanding. Compelling visualization methods have become crucial with AI systems integrating into everyday experiences and environments. Virtual Reality (VR), as an immersive and interactive technology, offers a novel approach to visualizing intricate AI processes. This work introduces transformative updates to the DeepVisionVR platform, a pioneering tool for 3D visualization of Convolutional Neural Networks (CNNs) in VR. A cornerstone of our enhancements is the Sensitivity Analysis module, which offers real-time interactivity, allowing users to adjust pixels within the VR space, shedding light on the intricacies of model outcomes. In addition, advanced model interpretation methodologies have been integrated, including Integrated Gradients, GradientShap, and Occlusion, enriching the depth of insight into model rationale. Our Adversarial Analysis, utilizing the Fast Gradient Sign Method (FGSM), unveils potential weak points in models, emphasizing their vulnerability to minor input alterations. The new features aim to provide a deeper understanding of how neural networks interpret and react to various inputs, thereby bridging the gap between complex machine learning models and human interpretability.},\nbooktitle = {Proceedings of the 2023 Conference on Human Centered Artificial Intelligence: Education and Practice},\npages = {48},\nnumpages = {1},\nlocation = {<conf-loc>, <city>Dublin</city>, <country>Ireland</country>, </conf-loc>},\nseries = {HCAIep '23}\n}\n\n

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\n \n\n \n \n \n \n \n \n An investigation of the effects of lockdowns and COVID-19 vaccinations in Ireland.\n \n \n \n \n\n\n \n Pourshir Sefidi, N.; Shoari Nejad, A.; and Mooney, P.\n\n\n \n\n\n\n AGILE: GIScience Series, 4: 37. 2023.\n \n\n\n\n
\n\n\n\n \n \n $\"An$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@Article{agile-giss-4-37-2023,\nAUTHOR = {Pourshir Sefidi, N. and Shoari Nejad, A. and Mooney, P.},\nTITLE = {An investigation of the effects of lockdowns and COVID-19 vaccinations in Ireland},\nJOURNAL = {AGILE: GIScience Series},\nVOLUME = {4},\nYEAR = {2023},\nPAGES = {37},\nURL = {https://agile-giss.copernicus.org/articles/4/37/2023/},\nDOI = {10.5194/agile-giss-4-37-2023}\n}

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\n \n\n \n \n \n \n \n Predicting the Success of Transfer Learning for Genetic Programming Using DeepInsight Feature Space Alignment.\n \n \n \n\n\n \n Trujillo, L.; Nation, J.; Muñoz, L.; and Galván, E.\n\n\n \n\n\n\n AI Communications, 36(3): 159 – 173. 2023.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@article{aic-230104,\nauthor={Trujillo, Leonardo  and Nation, Joel and  Muñoz, Luis and Galván, Edgar},\ntitle={Predicting the Success of Transfer Learning for Genetic Programming Using DeepInsight Feature Space Alignment},\ndoi={10.3233/aic-230104},\npages={159 – 173},\nvolume={36},\njournal={AI Communications},\nnumber={3},\nyear={2023},\n}\n\n

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\n \n\n \n \n \n \n \n \n Harvesting Brownian Motion: Zero Energy Computational Sampling.\n \n \n \n \n\n\n \n Doty, D.; Kornerup, N.; Luchsinger, A.; Orshansky, L.; Soloveichik, D.; and Woods, D.\n\n\n \n\n\n\n Technical Report 2023.\n \n\n\n\n
\n\n\n\n \n \n $\"Harvesting$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@techreport{doty2023harvesting,\n      title={Harvesting Brownian Motion: Zero Energy Computational Sampling}, \n      author={David Doty and Niels Kornerup and Austin Luchsinger and Leo Orshansky and David Soloveichik and Damien Woods},\n      year={2023},\n      school={Maynooth University, Ireland},\n      eprint={2309.06957},\n      doi={10.48550/arXiv.2309.06957},\n      url={https://doi.org/10.48550/arXiv.2309.06957},\n      abstract={The key factor currently limiting the advancement of computational power of electronic computation is no longer the manufacturing density and speed of components, but rather their high energy consumption. While it has been widely argued that reversible computation can escape the fundamental Landauer limit of kBTln(2) Joules per irreversible computational step, there is disagreement around whether indefinitely reusable computation can be achieved without energy dissipation. Here we focus on the relatively simpler context of sampling problems, which take no input, so avoids modeling the energy costs of the observer perturbing the machine to change its input. Given an algorithm A for generating samples from a distribution, we desire a device that can perpetually generate samples from that distribution driven entirely by Brownian motion. We show that such a device can efficiently execute algorithm A in the sense that we must wait only O(time(A)2) between samples. We consider two output models: Las Vegas, which samples from the exact probability distribution every 4 tries in expectation, and Monte Carlo, in which every try succeeds but the distribution is only approximated. We base our model on continuous-time random walks over the state space graph of a general computational machine, with a space-bounded Turing machine as one instantiation. The problem of sampling a computationally complex probability distribution with no energy dissipation informs our understanding of the energy requirements of computation, and may lead to more energy efficient randomized algorithms.},\n      archivePrefix={arXiv},\n      primaryClass={cs.DS}\n}\n\n

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\n \n\n \n \n \n \n \n \n Comparing Differentiable Logics for Learning Systems: A Research Preview.\n \n \n \n \n\n\n \n Flinkow, T.; Pearlmutter, B. A.; and Monahan, R.\n\n\n \n\n\n\n Electronic Proceedings in Theoretical Computer Science, 395: 17–29. November 2023.\n \n\n\n\n
\n\n\n\n \n \n $\"Comparing$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@article{Flinkow_2023,\n   title={Comparing Differentiable Logics for Learning Systems: A Research Preview},\n   volume={395},\n   ISSN={2075-2180},\n   url={http://dx.doi.org/10.4204/EPTCS.395.3},\n   DOI={10.4204/eptcs.395.3},\n   journal={Electronic Proceedings in Theoretical Computer Science},\n   publisher={Open Publishing Association},\n   abstract={Extensive research on formal verification of machine learning (ML) systems indicates that learning from data alone often fails to capture underlying background knowledge. A variety of verifiers have been developed to ensure that a machine-learnt model satisfies correctness and safety properties, however, these verifiers typically assume a trained network with fixed weights. ML-enabled autonomous systems are required to not only detect incorrect predictions, but should also possess the ability to self-correct, continuously improving and adapting. A promising approach for creating ML models that inherently satisfy constraints is to encode background knowledge as logical constraints that guide the learning process via so-called differentiable logics. In this research preview, we compare and evaluate various logics from the literature in weakly-supervised contexts, presenting our findings and highlighting open problems for future work. Our experimental results are broadly consistent with results reported previously in literature; however, learning with differentiable logics introduces a new hyperparameter that is difficult to tune and has significant influence on the effectiveness of the logics.},\n   author={Flinkow, Thomas and Pearlmutter, Barak A. and Monahan, Rosemary},\n   year={2023},\n   month=nov, \n   pages={17–29} }\n   \n

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\n \n\n \n \n \n \n \n Introducing a collaborative learning strategy in a hybrid and traditional laboratory for undergraduate computer science students.\n \n \n \n\n\n \n O'Neill, S. I.; and Mooney, A.\n\n\n \n\n\n\n In Ninth International Conference on Higher Education Advances Ninth International Conference on Higher Education Advances, 2023. \n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{oneill2023introducing,\ntitle={Introducing a collaborative learning strategy in a hybrid and traditional laboratory for undergraduate computer science students},\nauthor={O'Neill, Sam Ivan and Mooney, Aidan},\nbooktitle={ Ninth International Conference on Higher Education Advances Ninth International Conference on Higher Education Advances},\nyear={2023},\nabstract={Collaborative learning is an advantageous pedagogical strategy to include in e-learning. In this study we aim to demonstrate a methodology created to implement this strategy in an undergraduate student population. We will present our findings from running this experiment in two scenarios, namely an in-person environment and a simulated remote environment. We analyse the impact this methodology has on students understanding of the topic along with how their assessment compares to their peers in a previous year. We also analyse the different perception of personal and collaborative work in both scenarios. We conclude that this methodology is effective in increasing a student's understanding of the work being assessed and contributes to an increase in students' assessment grades.},\ndoi={10.4995/head23.2023.16339},\n}

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\n \n\n \n \n \n \n \n \n INVESTIGATING THE IMPACT OF COLLABORATIVE LEARNING ON UNDERGRADUATE COMPUTER SCIENCE STUDENTS.\n \n \n \n \n\n\n \n O'Neill, S.; and Mooney, A.\n\n\n \n\n\n\n In EDULEARN23 Proceedings, of 15th International Conference on Education and New Learning Technologies, pages 4986-4992, 3-5 July, 2023 2023. IATED\n \n\n\n\n
\n\n\n\n \n \n $\"INVESTIGATING$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@InProceedings{ONEILL2023INV,\nauthor    = {O'Neill, S. and Mooney, A.},\ntitle     = {INVESTIGATING THE IMPACT OF COLLABORATIVE LEARNING ON UNDERGRADUATE COMPUTER SCIENCE STUDENTS},\nseries    = {15th International Conference on Education and New Learning Technologies},\nbooktitle = {EDULEARN23 Proceedings},\nisbn      = {978-84-09-52151-7},\nissn      = {2340-1117},\ndoi       = {10.21125/edulearn.2023.1309},\nurl       = {https://doi.org/10.21125/edulearn.2023.1309},\npublisher = {IATED},\nlocation  = {Palma, Spain},\nmonth     = {3-5 July, 2023},\nyear      = {2023},\npages     = {4986-4992}}\n\n

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\n \n\n \n \n \n \n \n Pattern-based prediction of population outbreaks.\n \n \n \n\n\n \n Palma, G. R.; Godoy, W. A.; Engel, E.; Lau, D.; Galvan, E.; Mason, O.; Markham, C.; and Moral, R. A.\n\n\n \n\n\n\n Ecological Informatics, 77: 102220. November 2023.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@ARTICLE{2023EcInf..7702220P,\n       author = {{Palma}, Gabriel R. and {Godoy}, Wesley A.~C. and {Engel}, Eduardo and {Lau}, Douglas and {Galvan}, Edgar and {Mason}, Oliver and {Markham}, Charles and {Moral}, Rafael A.},\n        title = "{Pattern-based prediction of population outbreaks}",\n      journal = {Ecological Informatics},\n     keywords = {Alert zone procedure, Deep learning, Machine learning, Population dynamics, Time series, Quantitative Biology - Quantitative Methods},\n         year = 2023,\n        month = nov,\n       volume = {77},\n          eid = {102220},\n        pages = {102220},\n          doi = {10.1016/j.ecoinf.2023.102220},\narchivePrefix = {arXiv},\n       eprint = {2209.02346},\n primaryClass = {q-bio.QM},\n       adsurl = {https://ui.adsabs.harvard.edu/abs/2023EcInf..7702220P},\n      adsnote = {Provided by the SAO/NASA Astrophysics Data System}\n}\n\n\n

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\n \n\n \n \n \n \n \n \n Banging Interaction: A Ubimus-Design Strategy for the Musical Internet.\n \n \n \n \n\n\n \n Keller, D.; Yaseen, A.; Timoney, J.; Chakraborty, S.; and Lazzarini, V.\n\n\n \n\n\n\n Future Internet, 15(4). 2023.\n \n\n\n\n
\n\n\n\n \n \n $\"Banging$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@Article{fi15040125,\nAUTHOR = {Keller, Damián and Yaseen, Azeema and Timoney, Joseph and Chakraborty, Sutirtha and Lazzarini, Victor},\nTITLE = {Banging Interaction: A Ubimus-Design Strategy for the Musical Internet},\nJOURNAL = {Future Internet},\nVOLUME = {15},\nYEAR = {2023},\nNUMBER = {4},\nARTICLE-NUMBER = {125},\nURL = {https://www.mdpi.com/1999-5903/15/4/125},\nISSN = {1999-5903},\nABSTRACT = {We introduce a new perspective for musical interaction tailored to a specific class of sonic resources: impact sounds. Our work is informed by the field of ubiquitous music (ubimus) and engages with the demands of artistic practices. Through a series of deployments of a low-cost and highly flexible network-based prototype, the Dynamic Drum Collective, we exemplify the limitations and specific contributions of banging interaction. Three components of this new design strategy—adaptive interaction, mid-air techniques and timbre-led design—target the development of creative-action metaphors that make use of resources available in everyday settings. The techniques involving the use of sonic gridworks yielded positive outcomes. The subjects tended to choose sonic materials that—when combined with their actions on the prototype—approached a full rendition of the proposed soundtrack. The results of the study highlighted the subjects’ reliance on visual feedback as a non-exclusive strategy to handle both temporal organization and collaboration. The results show a methodological shift from device-centric and instrumental-centric methods to designs that target the dynamic relational properties of ubimus ecosystems.},\nDOI = {10.3390/fi15040125}\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Fine Grained Spoken Document Summarization Through Text Segmentation.\n \n \n \n \n\n\n \n Kotey, S.; Dahyot, R.; and Harte, N.\n\n\n \n\n\n\n In 2022 IEEE Spoken Language Technology Workshop (SLT), pages 647-654, Jan 2023. \n \n\n\n\n
\n\n\n\n \n \n $\"Fine$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n \n \n 6 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@INPROCEEDINGS{KoteySLT2023,\nauthor = {Kotey, Samantha and Dahyot, Rozenn and Harte, Naomi},\nbooktitle = {2022 IEEE Spoken Language Technology Workshop (SLT)}, \ntitle = {Fine Grained Spoken Document Summarization Through Text Segmentation}, \nyear = {2023},\nvolume = {},\nnumber = {},\npages = {647-654},\nabstract = {Podcast transcripts are long spoken documents of conversational dialogue. \nChallenging to summarize, podcasts cover a diverse range of topics, vary in length, and \nhave uniquely different linguistic styles. Previous studies in podcast summarization have generated short,\nconcise dialogue summaries. In contrast, we propose a method to generate long fine-grained summaries, which describe details of \nsub-topic narratives. Leveraging a readability formula, we curate a data subset to train a long sequence transformer for abstractive summarization.\nThrough text segmentation, we filter the evaluation data and exclude specific segments of text. \nWe apply the model to segmented data, producing different types of fine grained summaries. We show that appropriate filtering \ncreates comparable results on ROUGE and serves as an alternative method to truncation. Experiments show our model outperforms \nprevious studies on the Spotify podcast dataset when tasked with generating longer sequences of text.},\nkeywords = {},\ndoi = {10.1109/SLT54892.2023.10022829},\nurl = {https://roznn.github.io/PDF/STL2022Kotey.pdf},\nISSN = {},\nmonth = {Jan},}\n

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\n \n\n \n \n \n \n \n \n Visualization of AI Systems in Virtual Reality: A Comprehensive Review.\n \n \n \n \n\n\n \n Inkarbekov, M.; Monahan, R.; and Pearlmutter, B. A.\n\n\n \n\n\n\n International Journal of Advanced Computer Science and Applications, 14(8). 2023.\n \n\n\n\n
\n\n\n\n \n \n $\"Visualization$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@article{Inkarbekov2023,\ntitle = {Visualization of AI Systems in Virtual Reality: A Comprehensive Review},\njournal = {International Journal of Advanced Computer Science and Applications},\ndoi = {10.14569/IJACSA.2023.0140805},\nurl = {http://dx.doi.org/10.14569/IJACSA.2023.0140805},\nyear = {2023},\npublisher = {The Science and Information Organization},\nvolume = {14},\nnumber = {8},\nauthor = {Medet Inkarbekov and Rosemary Monahan and Barak A. Pearlmutter}\n}\n\n

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\n \n\n \n \n \n \n \n \n Improving GMM registration with class encoding.\n \n \n \n \n\n\n \n Panahi, S.; Chopin, J.; Ulicny, M.; and Dahyot, R.\n\n\n \n\n\n\n In Irish Machine Vision and Image Processing (IMVIP 2023), Galway, Ireland, 2023. \n https://github.com/solmak97/GMMReg_Extension\n\n\n\n
\n\n\n\n \n \n $\"Improving$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n \n \n 4 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n\n\n\n

@inproceedings{Panahi2023,\nauthor  =  {Solmaz Panahi and Jeremy Chopin and Matej Ulicny and Rozenn Dahyot}, \ntitle  =  {Improving  GMM  registration with class encoding},\nbooktitle  =  {Irish Machine Vision and Image Processing (IMVIP 2023)},\naddress =  {Galway, Ireland},\nvolume  =  {},\nyear  =  {2023},\nabstract  =  {Point set registration is critical in many applications such as  computer vision, pattern recognition, or in fields like robotics and medical imaging.\nThis paper focuses on reformulating point set registration using Gaussian Mixture Models while considering attributes associated with each point. Our approach introduces class score vectors as additional features \nto the spatial data information. By incorporating these attributes, we enhance the optimization process by penalizing incorrect matching terms. Experimental results show that our approach \nwith class scores outperforms the original algorithm  in both accuracy and speed.},\nurl  =  {https://zenodo.org/records/8205096/files/Improving_GMM_registration_with_class_encodings.pdf},\ndoi  =  {10.5281/zenodo.8205096},\nkeywords = {registration, GMM, class encoding},\nnote  =  {https://github.com/solmak97/GMMReg_Extension}\n}\n

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\n \n\n \n \n \n \n \n \n Query Based Acoustic Summarization for Podcasts.\n \n \n \n \n\n\n \n Kotey, S.; Dahyot, R.; and Harte, N.\n\n\n \n\n\n\n In Proceedings INTERSPEECH 2023, pages 1483–1487, Dublin, Ireland, August 2023. \n \n\n\n\n
\n\n\n\n \n \n $\"Query$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n \n \n 3 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@inproceedings{KoteyInterSpeech2023,\nauthor  =  {Samantha Kotey and Rozenn Dahyot and Naomi Harte},\ntitle  =  {Query Based Acoustic Summarization for Podcasts}, \nbooktitle = {Proceedings INTERSPEECH 2023},\nyear  =  {2023},\nvolume  =  {},\nnumber  =  {},\npages  =  {1483--1487},\nabstract  =  {Podcasts are a rich storytelling medium of long diverse conversations. \nTypically, listeners preview an episode through an audio clip, before deciding to consume the content. \nAn automatic system that produces promotional clips, by supporting acoustic queries would greatly benefit podcasters. \nPrevious text based methods do not use the acoustic signal directly or incorporate acoustic defined queries.\nTherefore, we propose a query based summarization approach, to produce audio clip summaries from podcast data. \nLeveraging unsupervised clustering methods, we apply our framework to the Spotify podcasts dataset.\nAudio signals are transformed into acoustic word embeddings, along with a pre-selected candidate query.\nWe initiate the cluster centroids with the query vector and obtain the final snippets by computing a global and local similarity score. \nAdditionally, we apply our framework to the AMI meeting dataset and demonstrate how audio can successfully be utilized to perform summarization.},\nkeywords  =  {query-based summarization, unsupervised speech summarization, clustering, acoustic word embeddings},\ndoi  =  {10.21437/Interspeech.2023-864},\nurl  =  {https://www.isca-archive.org/interspeech_2023/kotey23_interspeech.pdf},\nISSN  =  {},\naddress  =  {Dublin, Ireland},\nmonth  =  {August}\n}\n\n

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\n \n\n \n \n \n \n \n \n DEVELOPING A THEORETICAL ASSESSMENT METHOD FOR AN ASSISTED DIRECT GEOREFERENCING APPROACH TO IMPROVE ACCURACY WHEN MAPPING OVER WATER: THE CONCEPT, POTENTIAL AND LIMITATIONS.\n \n \n \n \n\n\n \n Essel, B.; Bolger, M.; McDonald, J.; and Cahalane, C.\n\n\n \n\n\n\n The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLVIII-1/W1-2023: 139–144. 2023.\n \n\n\n\n
\n\n\n\n \n \n $\"DEVELOPING$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@Article{isprs-archives-XLVIII-1-W1-2023-139-2023,\nAUTHOR = {Essel, B. and Bolger, M. and McDonald, J. and Cahalane, C.},\nTITLE = {DEVELOPING A THEORETICAL ASSESSMENT METHOD FOR AN ASSISTED DIRECT GEOREFERENCING APPROACH TO IMPROVE ACCURACY WHEN MAPPING OVER WATER: THE CONCEPT, POTENTIAL AND LIMITATIONS},\nJOURNAL = {The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences},\nVOLUME = {XLVIII-1/W1-2023},\nYEAR = {2023},\nPAGES = {139--144},\nurl={https://isprs-archives.copernicus.org/articles/XLVIII-1-W1-2023/139/2023/isprs-archives-XLVIII-1-W1-2023-139-2023.pdf},\nDOI = {10.5194/isprs-archives-XLVIII-1-W1-2023-139-2023}\n}\n\n

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\n \n\n \n \n \n \n \n \n Repositioning Tiered HotSpot Execution Performance Relative to the Interpreter.\n \n \n \n \n\n\n \n Lambert, J.; Casey, K.; and Monahan, R.\n\n\n \n\n\n\n Technical Report 2023.\n \n\n\n\n
\n\n\n\n \n \n $\"Repositioning$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@techreport{lambert2023repositioning,\n      title={Repositioning Tiered HotSpot Execution Performance Relative to the Interpreter}, \n      author={Jonathan Lambert and Kevin Casey and Rosemary Monahan},\n      year={2023},\n      eprint={2304.06460},\n      doi={10.48550/arXiv.2304.06460},\n      url={https://arxiv.org/pdf/2304.06460.pdf},\n      abstract={Although the advantages of just-in-time compilation over traditional \n      interpretive execution are widely recognised, there needs to be more current research \n      investigating and repositioning the performance differences between these two execution models \n      relative to contemporary workloads. Specifically, there is a need to examine the performance\n       differences between Java Runtime Environment (JRE) Java Virtual Machine (JVM) tiered execution \n       and JRE JVM interpretive execution relative to modern multicore architectures and modern concurrent \n       and parallel benchmark workloads. This article aims to fill this research gap by presenting \n       the results of a study that compares the performance of these two execution models under load \n       from the Renaissance Benchmark Suite. This research is relevant to anyone interested in understanding\n        the performance differences between just-in-time compiled code and interpretive execution. It provides a contemporary assessment of the interpretive JVM core, the entry and starting point for bytecode execution, relative to just-in-time tiered execution. The study considers factors such as the JRE version, the GNU GCC version used in the JRE build toolchain, and the garbage collector algorithm specified at runtime, and their impact on the performance difference envelope between interpretive and tiered execution. Our findings indicate that tiered execution is considerably more efficient than interpretive execution, and the performance gap has increased, ranging from 4 to 37 times more efficient. On average, tiered execution is approximately 15 times more efficient than interpretive execution. Additionally, the performance differences between interpretive and tiered execution are influenced by workload category, with narrower performance differences observed for web-based workloads and more significant differences for Functional and Scala-type workloads.},\n}\n

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\n \n\n \n \n \n \n \n \n CONTEXT AWARE OBJECT GEOTAGGING.\n \n \n \n \n\n\n \n Liu, C.; Ulicny, M.; and Dahyot, R.\n\n\n \n\n\n\n June 2023.\n \n\n\n\n
\n\n\n\n \n \n $\"CONTEXT$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 3 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@patent{Patent2023,\n  author = "Chao-jung Liu and Matej Ulicny and Rozenn Dahyot",\n  title = "CONTEXT AWARE OBJECT GEOTAGGING",\n  nationality = "United States",\n  number = "18087227",\n  day = "29",\n  month = "June",\n  year = "2023",\n  url = "https://patents.google.com/patent/US20230206402A1/en"\n}\n\n

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\n \n\n \n \n \n \n \n \n An assessment of Sentinel-1 synthetic aperture radar, geophysical and topographical covariates for estimating topsoil particle-size fractions.\n \n \n \n \n\n\n \n Deodoro, S. C.; Moral, R. A.; Fealy, R.; McCarthy, T.; and Fealy, R.\n\n\n \n\n\n\n European Journal of Soil Science, 74(5): e13414. 2023.\n \n\n\n\n
\n\n\n\n \n \n $\"An$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{https://doi.org/10.1111/ejss.13414,\nauthor = {Deodoro, Sandra Cristina and Moral, Rafael Andrade and Fealy, Reamonn and McCarthy, Tim and Fealy, Rowan},\ntitle = {An assessment of Sentinel-1 synthetic aperture radar, geophysical and topographical covariates for estimating topsoil particle-size fractions},\njournal = {European Journal of Soil Science},\nvolume = {74},\nnumber = {5},\npages = {e13414},\nkeywords = {clay, compositional, linear regression, log-ratio transformations, random forest, sand, Sentinel 1, silt},\ndoi = {https://doi.org/10.1111/ejss.13414},\nurl = {https://bsssjournals.onlinelibrary.wiley.com/doi/abs/10.1111/ejss.13414},\neprint = {https://bsssjournals.onlinelibrary.wiley.com/doi/pdf/10.1111/ejss.13414},\nabstract = {Abstract Data derived from synthetic aperture radar (SAR) are widely employed to predict soil properties, particularly soil moisture and soil carbon content. However, few studies address the use of microwave sensors for soil texture retrieval and those that do are typically constrained to bare soil conditions. Here, we test two statistical modelling approaches—linear (with and without interaction terms) and tree-based models, namely compositional linear regression model (LRM) and random forest (RF)—and both nongeophysical (e.g., surface soil moisture, topographic, etc) and geophysical-based (electromagnetic, magnetic and radiometric) covariates to estimate soil texture (sand \\%, silt \\% and clay \\%), using microwave remote sensing data (ESA Sentinel-1). The statistical models evaluated explicitly consider the compositional nature of soil texture and were evaluated with leave-one-out cross-validation (LOOCV). Our findings indicate that both modelling approaches yielded better estimates when fitted without the geophysical covariates. Based on the Nash–Sutcliffe efficiency coefficient (NSE), LRM slightly outperformed RF, with NSE values for sand, silt and clay of 0.94, 0.62 and 0.46, respectively; for RF, the NSE values were 0.93, 0.59 and 0.44. When interaction terms were included, RF was found to outperform LRM. The inclusion of interactions in the LRM resulted in a decrease in NSE value and an increase in the size of the residuals. Findings also indicate that the use of radar-derived variables (e.g., VV, VH, RVI) alone was not able to predict soil particle size without the aid of other covariates. Our findings highlight the importance of explicitly considering the compositional nature of soil texture information in statistical analysis and regression modelling. As part of the continued assessment of microwave remote sensing data (e.g., ESA Sentinel-1) for predicting topsoil particle size, we intend to test surface scattering information derived from the dual-polarimetric decomposition technique and integrate that predictor into the models in order to deal with the effects of vegetation cover on topsoil backscattering.},\nyear = {2023}\n}\n\n

\n\n\n

\n Abstract Data derived from synthetic aperture radar (SAR) are widely employed to predict soil properties, particularly soil moisture and soil carbon content. However, few studies address the use of microwave sensors for soil texture retrieval and those that do are typically constrained to bare soil conditions. Here, we test two statistical modelling approaches—linear (with and without interaction terms) and tree-based models, namely compositional linear regression model (LRM) and random forest (RF)—and both nongeophysical (e.g., surface soil moisture, topographic, etc) and geophysical-based (electromagnetic, magnetic and radiometric) covariates to estimate soil texture (sand %, silt % and clay %), using microwave remote sensing data (ESA Sentinel-1). The statistical models evaluated explicitly consider the compositional nature of soil texture and were evaluated with leave-one-out cross-validation (LOOCV). Our findings indicate that both modelling approaches yielded better estimates when fitted without the geophysical covariates. Based on the Nash–Sutcliffe efficiency coefficient (NSE), LRM slightly outperformed RF, with NSE values for sand, silt and clay of 0.94, 0.62 and 0.46, respectively; for RF, the NSE values were 0.93, 0.59 and 0.44. When interaction terms were included, RF was found to outperform LRM. The inclusion of interactions in the LRM resulted in a decrease in NSE value and an increase in the size of the residuals. Findings also indicate that the use of radar-derived variables (e.g., VV, VH, RVI) alone was not able to predict soil particle size without the aid of other covariates. Our findings highlight the importance of explicitly considering the compositional nature of soil texture information in statistical analysis and regression modelling. As part of the continued assessment of microwave remote sensing data (e.g., ESA Sentinel-1) for predicting topsoil particle size, we intend to test surface scattering information derived from the dual-polarimetric decomposition technique and integrate that predictor into the models in order to deal with the effects of vegetation cover on topsoil backscattering.\n

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\n \n\n \n \n \n \n \n Contributions of artificial intelligence for circular economy transition leading toward sustainability: an explorative study in agriculture and food industries of Pakistan.\n \n \n \n\n\n \n Ali, Z. A.; Zain, M.; Pathan, M. S.; and Mooney, P.\n\n\n \n\n\n\n Environment, Development and Sustainability. 2023.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@article{Zain2023,\nauthor={Zain Anwar Ali and Mahreen Zain and M. Salman Pathan and Peter Mooney}, \ntitle={Contributions of artificial intelligence for circular economy transition leading toward sustainability: \nan explorative study in agriculture and food industries of Pakistan},\njournal={Environment, Development and Sustainability},\nyear={2023}, \ndoi={10.1007/s10668-023-03458-9},\nabstract={Circular economy (CE) regenerates nature by introducing circularity in economic systems. It tackles various global challenges of sustainability, specifically in the agriculture and food sectors. Digital technologies support its implementations; especially, artificial intelligence (AI) is acquiring momentum. In this regard through algorithms, remote sensors, drones etc must be incorporated to achieve the desired target. The current studies provide bounded investigations of AI-driven CE exclusively in Pakistan. The main purpose of this paper is to elaborate on AI support in the implementation of CE practices and to explore the current waste situation in Pakistan and the implementations of CE and AI-driven CE practices in it. Inductive research is conducted in two stages. On the one hand, the theory is developed to evaluate the CE concept and AI techniques to strengthen its practices. On the other hand, a framework is proposed for multi-purpose case studies in the agriculture and food industries of Pakistan to integrate capabilities of CE and CE driven by AI. The outcomes of this research reveal that the true value of AI lies in the transition of CE and recommends that Pakistan must take some crucial measures to boost these practices to achieve sustainable development goals. Some limitations and future research proposals are also provided. The study helps researchers, companies and institues to participate positively towards the Circular Economy goal achievement by imlementing the AI.},\npublisher={Springer},\n}\n

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\n \n\n \n \n \n \n \n \n Broadband CARS high-throughput single-cell imaging.\n \n \n \n \n\n\n \n Muddiman, R.; and Hennelly, B.\n\n\n \n\n\n\n EPJ Web Conf., 287: 03018. 2023.\n \n\n\n\n
\n\n\n\n \n \n $\"Broadband$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@article{refId0,\n\tauthor = {Muddiman, Ryan and Hennelly, Bryan},\n\ttitle = {Broadband CARS high-throughput single-cell imaging},\n\tDOI= "10.1051/epjconf/202328703018",\n\turl= "https://doi.org/10.1051/epjconf/202328703018",\n\tjournal = {EPJ Web Conf.},\n\tyear = 2023,\n\tvolume = 287,\n\tpages = "03018",\n}\n

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\n \n\n \n \n \n \n \n \n Following the Flux in diffracted fields – An efficient numerical method for tracing the Eikonal function.\n \n \n \n \n\n\n \n Yu, Q.; Muddiman, R.; and Hennelly, B.\n\n\n \n\n\n\n EPJ Web Conf., 287: 02011. 2023.\n \n\n\n\n
\n\n\n\n \n \n $\"Following$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@article{refId0q,\n\tauthor = {Yu, Qin and Muddiman, Ryan and Hennelly, Bryan},\n\ttitle = {Following the Flux in diffracted fields – An efficient numerical method for tracing the Eikonal function},\n\tDOI= "10.1051/epjconf/202328702011",\n\turl= "https://doi.org/10.1051/epjconf/202328702011",\n\tjournal = {EPJ Web Conf.},\n\tyear = 2023,\n\tvolume = 287,\n\tpages = "02011",\n}\n

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\n \n\n \n \n \n \n \n \n Using an inexpensive module for Quantitative Phase Imaging.\n \n \n \n \n\n\n \n Xin, F.; Muddiman, R.; and Hennelly, B.\n\n\n \n\n\n\n EPJ Web Conf., 287: 09044. 2023.\n \n\n\n\n
\n\n\n\n \n \n $\"Using$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@article{refId0a,\n\tauthor = {Xin, Fan and Muddiman, Ryan and Hennelly, Bryan},\n\ttitle = {Using an inexpensive module for Quantitative Phase Imaging},\n\tDOI= "10.1051/epjconf/202328709044",\n\turl= "https://doi.org/10.1051/epjconf/202328709044",\n\tjournal = {EPJ Web Conf.},\n\tyear = 2023,\n\tvolume = 287,\n\tpages = "09044",\n}\n

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\n \n\n \n \n \n \n \n \n Raman signal extraction from BCARS intensity measurements using deep learning with a prior excitation profile.\n \n \n \n \n\n\n \n Muddiman, R.; O’Dwyer, K.; Camp, C. H.; and Hennelly, B.\n\n\n \n\n\n\n EPJ Web Conf., 287: 13019. 2023.\n \n\n\n\n
\n\n\n\n \n \n $\"Raman$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@article{refId0,\n\tauthor = {Muddiman, Ryan and O’Dwyer, Kevin and Camp, Charles H. and Hennelly, Bryan},\n\ttitle = {Raman signal extraction from BCARS intensity measurements using deep learning with a prior excitation profile},\n\tDOI= "10.1051/epjconf/202328713019",\n\turl= "https://doi.org/10.1051/epjconf/202328713019",\n\tjournal = {EPJ Web Conf.},\n\tyear = 2023,\n\tvolume = 287,\n\tpages = "13019",\n}\n\n

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\n \n\n \n \n \n \n \n \n CSP2Turtle: Verified Turtle Robot Plans.\n \n \n \n \n\n\n \n MacConville, D.; Farrell, M.; Luckcuck, M.; and Monahan, R.\n\n\n \n\n\n\n Robotics, 12(2). 2023.\n \n\n\n\n
\n\n\n\n \n \n $\"CSP2Turtle:$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@Article{robotics12020062,\nAUTHOR = {MacConville, Dara and Farrell, Marie and Luckcuck, Matt and Monahan, Rosemary},\nTITLE = {CSP2Turtle: Verified Turtle Robot Plans},\nJOURNAL = {Robotics},\nVOLUME = {12},\nYEAR = {2023},\nNUMBER = {2},\nARTICLE-NUMBER = {62},\nURL = {https://www.mdpi.com/2218-6581/12/2/62},\nISSN = {2218-6581},\nABSTRACT = {Software verification is an important approach to establishing the reliability of critical systems. One important area of application is in the field of robotics, as robots take on more tasks in both day-to-day areas and highly specialised domains. Our particular interest is in checking the plans that robots are expected to follow to detect errors that would lead to unreliable behaviour. Python is a popular programming language in the robotics domain through the use of the Robot Operating System (ROS) and various other libraries. Python’s Turtle package provides a mobile agent, which we formally model here using Communicating Sequential Processes (CSP). Our interactive toolchain CSP2Turtle with CSP models and Python components enables plans for the turtle agent to be verified using the FDR model-checker before being executed in Python. This means that certain classes of errors can be avoided, providing a starting point for more detailed verification of Turtle programs and more complex robotic systems. We illustrate our approach with examples of robot navigation and obstacle avoidance in a 2D grid-world. We evaluate our approach and discuss future work, including how our approach could be scaled to larger systems.},\nDOI = {10.3390/robotics12020062}\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Removing non-resonant background from broadband CARS using a physics-informed neural network.\n \n \n \n \n\n\n \n Muddiman, R.; O' Dwyer, K.; Camp, C. H.; and Hennelly, B.\n\n\n \n\n\n\n Anal. Methods, 15: 4032-4043. 2023.\n \n\n\n\n
\n\n\n\n \n \n $\"Removing$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@Article{D3AY01131C,\nauthor ="Muddiman, Ryan and O{'} Dwyer, Kevin and Camp, Charles. H. and Hennelly, Bryan",\ntitle  ="Removing non-resonant background from broadband CARS using a physics-informed neural network",\njournal  ="Anal. Methods",\nyear  ="2023",\nvolume  ="15",\nissue  ="32",\npages  ="4032-4043",\npublisher  ="The Royal Society of Chemistry",\ndoi  ="10.1039/D3AY01131C",\nurl  ="http://dx.doi.org/10.1039/D3AY01131C",\nabstract  ="Broadband coherent anti-Stokes Raman scattering (BCARS) is capable of producing high-quality Raman spectra spanning broad bandwidths{,} 400–4000 cm−1{,} with millisecond acquisition times. Raw BCARS spectra{,} however{,} are a coherent combination of vibrationally resonant (Raman) and non-resonant (electronic) components that may challenge or degrade chemical analyses. Recently{,} we demonstrated a deep convolutional autoencoder network{,} trained on pairs of simulated BCARS-Raman datasets{,} which could retrieve the Raman signal with high quality under ideal conditions. In this work{,} we present a new computational system that incorporates experimental measurements of the laser system spectral and temporal properties{,} combined with simulated susceptibilities. Thus{,} the neural network learns the mapping between the susceptibility and the measured response for a specific BCARS system. The network is tested on simulated and measured experimental results taken with our BCARS system."}\n\n

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\n \n\n \n \n \n \n \n \n The effect of benevolent leadership on safety behavior: A moderated mediation model.\n \n \n \n \n\n\n \n Wang, D.; Sun, Z.; Zong, Z.; Mao, W.; Wang, L.; Sun, Y.; Zhang, J.; Maguire, P.; and Hu, Y.\n\n\n \n\n\n\n Journal of Safety Research, 85: 31-41. 2023.\n \n\n\n\n
\n\n\n\n \n \n $\"The$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{WANG202331,\ntitle = {The effect of benevolent leadership on safety behavior: A moderated mediation model},\njournal = {Journal of Safety Research},\nvolume = {85},\npages = {31-41},\nyear = {2023},\nissn = {0022-4375},\ndoi = {10.1016/j.jsr.2023.01.004},\nurl = {https://doi.org/10.1016/j.jsr.2023.01.004},\nauthor = {Dawei Wang and Zhenzhen Sun and Zhaobiao Zong and Wenxu Mao and Li Wang and Yuchen Sun and Jun Zhang and Phil Maguire and Yixin Hu},\nkeywords = {Employee behavior, Subordinates' moqi, Safety climate, Implicit followership theory, Implicit leadership theory},\nabstract = {Introduction: While high quality leadership is of great importance for enhancing safety behavior in the workplace, there has been a lack of research on how benevolent leadership influences such behavior. Subordinates’ moqi (i.e., their unspoken understanding of the work expectations, intentions, and requirements of their superiors) and safety climate were introduced to examine this relationship. Method: Based on implicit followership theory, this study explores the relationship between benevolent (well meaning, kindly) leadership and employees' safety behavior, as well as the mediating role of subordinates' moqi and the moderating role of safety climate. 608 employees of a petroleum company in China were randomly selected as participants, and the data were collected in two stages. Results: The results showed that: (1) Benevolent leadership is positively correlated with employees' safety behavior. (2) Subordinates' moqi mediates between benevolent leadership and employees' safety behavior. (3) Safety climate moderates the mediating role of subordinates' moqi between benevolent leadership and employees' safety behavior. (4) The positive effect of subordinates' moqi on employees' safety behavior is enhanced under a positive safety climate. Conclusions: Benevolent leadership is an effective leadership style that enhances employees’ safety behaviors by promoting a moqi state between supervisors and subordinates. The invisible environmental climate, in particular, the safety climate, should be a key focus in the promotion of safety behaviors. Practical Applications: This study further broadens the research perspective of employee safety behavior from the perspective of implicit followership theory. It also provides practical guidance for improving employee safety behavior, namely selecting and cultivating benevolent leaders, enhancing subordinates' moqi, and actively fostering a positive organizational safety climate.}\n}\n\n

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\n \n\n \n \n \n \n \n \n A new spin on Ashkin's laser trapping forces in the ray optics regime.\n \n \n \n \n\n\n \n Yu, Q.; and Hennelly, B. M.\n\n\n \n\n\n\n Optics and Lasers in Engineering, 170: 107764. 2023.\n \n\n\n\n
\n\n\n\n \n \n $\"A$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{YU2023107764,\ntitle = {A new spin on Ashkin's laser trapping forces in the ray optics regime},\njournal = {Optics and Lasers in Engineering},\nvolume = {170},\npages = {107764},\nyear = {2023},\nissn = {0143-8166},\ndoi = {https://doi.org/10.1016/j.optlaseng.2023.107764},\nurl = {https://www.sciencedirect.com/science/article/pii/S0143816623002932},\nauthor = {Qin Yu and Bryan M. Hennelly},\nkeywords = {Optical trap, Laser tweezers, Ray forces, Rotational force, Dielectric sphere, Absorption},\nabstract = {We repeat the derivation of the forces of a single-beam gradient laser trap on a dielectric sphere in the ray optics regime as first reported by Ashkin; in this case, however, we investigate the impact of partial absorption of light by the sphere on these trapping forces. Our model indicates that the effect of absorption is to reduce the axial and transverse trapping forces as a function of absorption, as well as changing the axial trap position. The trap stiffness is predicted to remain relatively unchanged even for high levels of absorption. The model also predicts that a rotational force is imparted on the sphere as a consequence of absorption. The torque associated with a single ray is first derived, which is shown to increase as a function of both absorption, radius, and the angle of incidence. This enables a derivation of the torque acting on a trapped sphere as it is laterally displaced from the trapping position, which is found to increase linearly with respect to the transverse displacement of the sphere. The torque is derived to be zero for the case of no absorption, and also for the case of axial displacement of the sphere, regardless of absorption. The model reduces exactly to Ashkin's model for the case of zero absorption.}\n}\n\n

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\n \n\n \n \n \n \n \n \n QMaxUSE: A new tool for verifying UML class diagrams and OCL invariants.\n \n \n \n \n\n\n \n Wu, H.\n\n\n \n\n\n\n Science of Computer Programming, 228: 102955. 2023.\n \n\n\n\n
\n\n\n\n \n \n $\"QMaxUSE:$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{WU2023102955,\ntitle = {QMaxUSE: A new tool for verifying UML class diagrams and OCL invariants},\njournal = {Science of Computer Programming},\nvolume = {228},\npages = {102955},\nyear = {2023},\nissn = {0167-6423},\ndoi = {https://doi.org/10.1016/j.scico.2023.102955},\nurl = {https://www.sciencedirect.com/science/article/pii/S0167642323000370},\nauthor = {Hao Wu},\nkeywords = {Verification, UML&OCL, Query SMT, Unsatisfiable core},\nabstract = {Formal verification of a UML class diagram annotated with OCL constraints has been a long-standing challenge in Model-driven Engineering. In the past decades, many tools and techniques have been proposed to tackle this challenge. However, they do not scale well and are often unable to locate the conflicts when then number of OCL constraints significantly increases. In this paper, we present a new tool called QMaxUSE. This tool is designed for verifying UML class diagrams annotated with large number of OCL invariants. QMaxUSE is easy to install and deploy. It offers two distinct features. (1) A simple query language that allows users to choose parts of a UML class diagram to be verified. (2) A new procedure that is capable of performing concurrent verification.}\n}\n\n

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\n \n\n \n \n \n \n \n \n Marine coastal biodiversity and services in Ireland in a three-dimensional context: Scientific, news media, and legislative.\n \n \n \n \n\n\n \n Casal, G.; and McCarthy, T.\n\n\n \n\n\n\n Ocean & Coastal Management, 244: 106796. 2023.\n \n\n\n\n
\n\n\n\n \n \n $\"Marine$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{CASAL2023106796,\ntitle = {Marine coastal biodiversity and services in Ireland in a three-dimensional context: Scientific, news media, and legislative},\njournal = {Ocean & Coastal Management},\nvolume = {244},\npages = {106796},\nyear = {2023},\nissn = {0964-5691},\ndoi = {https://doi.org/10.1016/j.ocecoaman.2023.106796},\nurl = {https://www.sciencedirect.com/science/article/pii/S0964569123003216},\nauthor = {Gema Casal and Tim McCarthy},\nkeywords = {Biodiversity, Ecosystem services, Coastal areas, Climate change, Bibliometrics},\nabstract = {Biodiversity is a key indicator of ecosystem health and plays an important role in providing ecosystem services that are essential for economic development and social well-being. In Ireland, climate change and anthropogenic pressures have led to biodiversity loss and habitat degradation, which in turn affects the provision of ecosystem services. The aim of this study was to determine how marine coastal biodiversity and ecosystem services in the Republic of Ireland are portrayed in the scientific literature, news media, and current legislation in order to identify knowledge gaps and priority areas of intervention for policymakers and other decision-making stakeholders. A review of the scientific literature based on the Scopus database suggests a lack of stakeholder involvement in the scientific-based approach. Up to 2022 research on marine coastal biodiversity focused primarily on species richness and diversity, especially in the context of climate change, while research on ecosystem services focused primarily on ecosystem function. Analysis of the news media found that coverage of biodiversity and ecosystem services has increased over the past decade, but opportunities are being missed to raise public awareness of the multiple benefits, not just economic, of marine coastal ecosystems, their biodiversity, and the services they provide. The terms “biodiversity” and “ecosystem services” have only been introduced into Irish legislation in recent years. The legislative context at the national level is rather fragmented at diverse levels and mainly corresponds to the transposition of European Directives while national specific legislation is less developed. The interconnection between these three domains: scientific, news media and legislative was not evident in this study, especially in the case of the scientific field. Efforts to promote science-based knowledge, communication, collaboration, and transparency between these domains are crucial to support informed decision-making and promote public engagement while conserving biodiversity. Addressing the information gaps identified in this work could help advance the implementation of Nature-based Solutions (NbS), key cost-effective measures to mitigate and adapt to the impacts of climate change while protecting biodiversity and ecosystem services.}\n}\n\n

\n\n\n

\n Biodiversity is a key indicator of ecosystem health and plays an important role in providing ecosystem services that are essential for economic development and social well-being. In Ireland, climate change and anthropogenic pressures have led to biodiversity loss and habitat degradation, which in turn affects the provision of ecosystem services. The aim of this study was to determine how marine coastal biodiversity and ecosystem services in the Republic of Ireland are portrayed in the scientific literature, news media, and current legislation in order to identify knowledge gaps and priority areas of intervention for policymakers and other decision-making stakeholders. A review of the scientific literature based on the Scopus database suggests a lack of stakeholder involvement in the scientific-based approach. Up to 2022 research on marine coastal biodiversity focused primarily on species richness and diversity, especially in the context of climate change, while research on ecosystem services focused primarily on ecosystem function. Analysis of the news media found that coverage of biodiversity and ecosystem services has increased over the past decade, but opportunities are being missed to raise public awareness of the multiple benefits, not just economic, of marine coastal ecosystems, their biodiversity, and the services they provide. The terms “biodiversity” and “ecosystem services” have only been introduced into Irish legislation in recent years. The legislative context at the national level is rather fragmented at diverse levels and mainly corresponds to the transposition of European Directives while national specific legislation is less developed. The interconnection between these three domains: scientific, news media and legislative was not evident in this study, especially in the case of the scientific field. Efforts to promote science-based knowledge, communication, collaboration, and transparency between these domains are crucial to support informed decision-making and promote public engagement while conserving biodiversity. Addressing the information gaps identified in this work could help advance the implementation of Nature-based Solutions (NbS), key cost-effective measures to mitigate and adapt to the impacts of climate change while protecting biodiversity and ecosystem services.\n

\n\n\n

\n \n\n \n \n \n \n \n \n Evolutionary Multi-objective Optimisation in Neurotrajectory Prediction.\n \n \n \n \n\n\n \n Galván, E.; and Stapleton, F.\n\n\n \n\n\n\n Applied Soft Computing, 146: 110693. 2023.\n \n\n\n\n
\n\n\n\n \n \n $\"Evolutionary$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{GALVAN2023110693,\ntitle = {Evolutionary Multi-objective Optimisation in Neurotrajectory Prediction},\njournal = {Applied Soft Computing},\nvolume = {146},\npages = {110693},\nyear = {2023},\nissn = {1568-4946},\ndoi = {https://doi.org/10.1016/j.asoc.2023.110693},\nurl = {https://www.sciencedirect.com/science/article/pii/S1568494623007111},\nauthor = {Edgar Galván and Fergal Stapleton},\nkeywords = {Neuroevolution, Multi-objective Optimisation, Evolutionary algorithms, Deep neural networks, Autonomous vehicles, Scaling},\nabstract = {Machine learning has rapidly evolved during the last decade, achieving expert human performance on notoriously challenging problems such as image classification. This success is partly due to the re-emergence of bio-inspired modern artificial neural networks (ANNs) along with the availability of computation power, vast labelled data and ingenious human-based expert knowledge as well as optimisation approaches that can find the correct configuration (and weights) for these networks. Neuroevolution is a term used for the latter when employing evolutionary algorithms. Most of the works in neuroevolution have focused their attention in a single type of ANNs, named Convolutional Neural Networks (CNNs). Moreover, most of these works have used a single optimisation approach. This work makes a progressive step forward in neuroevolution for vehicle trajectory prediction, referred to as neurotrajectory prediction, where multiple objectives must be considered. To this end, rich ANNs composed of CNNs and Long-short Term Memory Network are adopted. Two well-known and robust Evolutionary Multi-objective Optimisation (EMO) algorithms, named Non-dominated Sorting Genetic Algorithm-II (NSGA-II) and Multi-Objective Evolutionary Algorithm based on Decomposition (MOEA/D) are also adopted. The completely different underlying mechanism of each of these algorithms sheds light on the implications of using one over the other EMO approach in neurotrajectory prediction. In particular, the importance of considering objective scaling is highlighted, finding that MOEA/D can be more adept at focusing on specific objectives whereas, NSGA-II tends to be more invariant to objective scaling. Additionally, certain objectives are shown to be either beneficial or detrimental to finding valid models, for instance, inclusion of a distance feedback objective was considerably detrimental to finding valid models, while a lateral velocity objective was more beneficial.}\n}\n\n

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\n \n\n \n \n \n \n \n \n Geospatial complex event processing in smart city applications.\n \n \n \n \n\n\n \n Khazael, B.; Vahidi Asl, M.; and Tabatabaee Malazi, H.\n\n\n \n\n\n\n Simulation Modelling Practice and Theory, 122: 102675. 2023.\n \n\n\n\n
\n\n\n\n \n \n $\"Geospatial$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{KHAZAEL2023102675,\ntitle = {Geospatial complex event processing in smart city applications},\njournal = {Simulation Modelling Practice and Theory},\nvolume = {122},\npages = {102675},\nyear = {2023},\nissn = {1569-190X},\ndoi = {10.1016/j.simpat.2022.102675},\nurl = {https://www.sciencedirect.com/science/article/pii/S1569190X22001459},\nauthor = {Behnam Khazael and Mojtaba {Vahidi Asl} and Hadi {Tabatabaee Malazi}},\nkeywords = {Complex event processing, Spatio-temporal stream processing, T-Rex engine, TESLA language, Edge computing, Smart city},\nabstract = {The extensive deployment of the Internet of things (IoT) devices in urban areas enables smart city systems (e.g., urban traffic detection and air pollution monitoring) to use these devices to discover the affected regions by various events, particularly complex ones. A complex event is inferred from patterns of different individual primitive events according to their spatio-temporal information. Complex event processing (CEP) systems facilitate applications to define their reasoning rules based on event processing languages (EPL), similar to SQL. However, current languages and CEP engines do not efficiently support spatial data characteristics. Geospatial CEP is challenging since applications have diverse definitions for complex events (e.g., air quality index), IoT devices have heterogeneous specifications/capabilities, and complex events may happen concurrently. This paper proposes the Geo-Tesla language that enables smart city applications to define spatial attributes in complex event definitions and reasoning rules. Then, we devise the GeoT-Rex CEP engine that implements geospatial operations that compiles Geo-Tesla language and processes the spatial data. The integration of Geo-Tesla and GeoT-Rex enables applications to process complex events with spatial characteristics in their reasoning rules and identify boundaries of the detected complex event (event footprint). The evaluation results from the proof of concept implementation show that our proposed solution outperforms in identifying the footprint of complex events up to 44% in the largest network size. They also show that the detection percentage in the concurrent appearance of complex events is 40% more on average than a close state-of-the-art baseline.}\n}\n\n

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\n \n\n \n \n \n \n \n \n A method for creating complex real-world networks using ESRI Shapefiles.\n \n \n \n \n\n\n \n Harish; Mooney, P.; and Galván, E.\n\n\n \n\n\n\n MethodsX, 11: 102426. 2023.\n \n\n\n\n
\n\n\n\n \n \n $\"A$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{HARISH2023102426,\ntitle = {A method for creating complex real-world networks using ESRI Shapefiles.},\njournal = {MethodsX},\nvolume = {11},\npages = {102426},\nyear = {2023},\nissn = {2215-0161},\ndoi = {https://doi.org/10.1016/j.mex.2023.102426},\nurl = {https://www.sciencedirect.com/science/article/pii/S2215016123004223},\nauthor = { Harish and Peter Mooney and Edgar Galván},\nkeywords = {Graphical Networks, ESRI Shapefiles, NetworkX, OSMnx},\nabstract = {A classic optimization problem with many real-world applications is optimal route search in graphs or networks. Graphical networks resembling real world networks are an important requirement for these studies. Python packages NetworkX and OSMnx are probably the most popular approaches in industry for creating and analyzing real world graphical networks using ESRI Shapefiles (Geospatial Vector Data). However, creating such a network is a complex and tedious process as these packages require the input data to be in a specific format. In this study,•We outline a flexible method that can be used to easily create graphical network representations in NetworkX or OSMnx using road network topology data stored in ESRI Shapefiles.•A detailed step-by-step process is outlined to successfully transform the ESRI Shapefile data into the compatible format for graph analysis libraries like OSMnx and NetworkX.•A data cleaning strategy is suggested to reduce resource consumption without distorting the actual structure of the graph.This method will allow researchers to efficiently generate graphical networks and validate their theories by evaluating their efficiencies using real-world network data of different sizes and topologies. This method could benefit, but is not limited to, research areas such as Advanced Transportation Systems (ATS), Graph Neural Networks (GNN), Multi-Objective Genetic Algorithms, to mention a few.}\n}\n\n

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\n \n\n \n \n \n \n \n \n Survey data of public awareness on climate change and the value of marine and coastal ecosystems.\n \n \n \n \n\n\n \n Fonseca, C.; Wood, L. E.; Andriamahefazafy, M.; Casal, G.; Chaigneau, T.; Cornet, C. C.; Degia, A. K.; Failler, P.; Ferraro, G.; Furlan, E.; Hawkins, J.; de Juan , S.; Krause, T.; McCarthy, T.; Pérez, G.; Roberts, C.; Trégarot, E.; and O'Leary, B. C.\n\n\n \n\n\n\n Data in Brief, 47: 108924. 2023.\n \n\n\n\n
\n\n\n\n \n \n $\"Survey$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{FONSECA2023108924,\ntitle = {Survey data of public awareness on climate change and the value of marine and coastal ecosystems},\njournal = {Data in Brief},\nvolume = {47},\npages = {108924},\nyear = {2023},\nissn = {2352-3409},\ndoi = {https://doi.org/10.1016/j.dib.2023.108924},\nurl = {https://www.sciencedirect.com/science/article/pii/S2352340923000422},\nauthor = {Catarina Fonseca and Louisa E. Wood and Mialy Andriamahefazafy and Gema Casal and Tomas Chaigneau and Cindy C. Cornet and A. Karima Degia and Pierre Failler and Gianluca Ferraro and Elisa Furlan and Julie Hawkins and Silvia {de Juan} and Torsten Krause and Tim McCarthy and Géraldine Pérez and Callum Roberts and Ewan Trégarot and Bethan C. O'Leary},\nkeywords = {Ecosystem services, Environmental perceptions, Human threats, Marine conservation, Nature-based solutions, Ocean management, Public opinion, Sustainable development},\nabstract = {The long-term provision of ocean ecosystem services depends on healthy ecosystems and effective sustainable management. Understanding public opinion about marine and coastal ecosystems is important to guide decision-making and inform specific actions. However, available data on public perceptions on the interlinked effects of climate change, human impacts and the value and management of marine and coastal ecosystems are rare. This dataset presents raw data from an online, self-administered, public awareness survey conducted between November 2021 and February 2022 which yielded 709 responses from 42 countries. The survey was released in four languages (English, French, Spanish and Italian) and consisted of four main parts: (1) perceptions about climate change; (2) perceptions about the value of, and threats to, coasts, oceans and their wildlife, (3) perceptions about climate change response; and (4) socio-demographic information. Participation in the survey was voluntary and all respondents provided informed consent after reading a participant information form at the beginning of the survey. Responses were anonymous unless respondents chose to provide contact information. All identifying information has been removed from the dataset. The dataset can be used to conduct quantitative analyses, especially in the area of public perceptions of the interlinkages between climate change, human impacts and options for sustainable management in the context of marine and coastal ecosystems. The dataset is provided with this article, including a copy of the survey and participant information forms in all four languages, data and the corresponding codebook.}\n}\n

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\n \n\n \n \n \n \n \n \n The Role of Artificial Intelligence within Circular Economy Activities—A View from Ireland.\n \n \n \n \n\n\n \n Pathan, M. S.; Richardson, E.; Galvan, E.; and Mooney, P.\n\n\n \n\n\n\n Sustainability, 15(12). 2023.\n \n\n\n\n
\n\n\n\n \n \n $\"The$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@Article{su15129451,\nAUTHOR = {Pathan, Muhammad Salman and Richardson, Edana and Galvan, Edgar and Mooney, Peter},\nTITLE = {The Role of Artificial Intelligence within Circular Economy Activities—A View from Ireland},\nJOURNAL = {Sustainability},\nVOLUME = {15},\nYEAR = {2023},\nNUMBER = {12},\nARTICLE-NUMBER = {9451},\nURL = {https://www.mdpi.com/2071-1050/15/12/9451},\nISSN = {2071-1050},\nABSTRACT = {The world’s current linear economic model is unsustainable. This model encourages improper use of limited natural resources and causes abundant waste production resulting in severe harm to the environment. A circular economy (CE) is a sustainable, restorative, and regenerative alternative to the current linear economy and is gaining popularity worldwide. Amongst various digital technologies, Artificial intelligence (AI) is a crucial enabler for CE and can aid significantly with the adoption and implementation of CE in real-world applications. In this paper, we describe the intersection of AI and CE and policies around implementing CE principles using AI. As a means of grounding the discussion, we discuss some initiatives taken by the Irish government to adopt circularity and explore the role AI plays in these. We present a number of practical examples of AI and CE from Ireland. We argue that digitalisation has potential in CE and it has a major role to play in the transition towards CE. We close the paper by reflecting on future steps around practical implementations of AI-based CE processes.},\nDOI = {10.3390/su15129451}\n}\n\n\n\n

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\n \n\n \n \n \n \n \n Geochemical properties of blue carbon sediments through an elevation gradient: study of an anthropogenically impacted coastal lagoon.\n \n \n \n\n\n \n Grey, A.; Costeira, R.; Lorenzo, E.; O'Kane, S.; McCaul, M. V.; McCarthy, T.; Jordan, S. F.; Allen, C. C. R.; and Kelleher, B. P.\n\n\n \n\n\n\n Biogeochemistry, 162: 381–408. 2023.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@article{Gery2023Bio,\nauthor={Anthony Grey and Ricardo Costeira and Emmaline Lorenzo and Sean O'Kane and Margaret V. McCaul and Tim McCarthy and Sean F. Jordan and Christopher C. R. Allen and Brian P. Kelleher},\ntitle={Geochemical properties of blue carbon sediments through an elevation gradient: study of an anthropogenically impacted coastal lagoon}, \njournal={Biogeochemistry}, \nvolume={162}, \npages={381–408},\nyear={2023},\nabstract={Global research is showing that coastal blue carbon ecosystems are vulnerable to climate change driven threats including accelerated sea-level rise and prolonged periods of drought. Furthermore, direct anthropogenic impacts present immediate threats through deterioration of coastal water quality, land reclamation, long-term impact to sediment biogeochemical cycling. These threats will invariably alter the future efficacy of carbon (C) sequestration processes and it is imperative that currently existing blue carbon habitats be protected. Knowledge of underlying biogeochemical, physical and hydrological interactions occurring in functioning blue carbon habitats is essential for developing strategies to mitigate threats, and promote conditions to optimise C sequestration/storage. In this current work, we investigated how sediment geochemistry (0–10 cm depth) responds to elevation, an edaphic factor driven by long-term hydrological regimes consequently exerting control over particle sedimentation rates and vegetation succession. }, \ndoi={10.1007/s10533-022-00974-0},\n}

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\n \n\n \n \n \n \n \n \n Combining geolocation and height estimation of objects from street level imagery.\n \n \n \n \n\n\n \n Ulicny, M.; Krylov, V. A.; Connelly, J.; and Dahyot, R.\n\n\n \n\n\n\n Technical Report 2023.\n \n\n\n\n
\n\n\n\n \n \n $\"Combining$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n \n \n 2 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@techreport{ulicny2023combining,\ndoi = {10.48550/arXiv.2305.08232},\nurl = {https://arxiv.org/pdf/2305.08232.pdf},\nabstract = {We propose a pipeline for combined multi-class object geolocation and \nheight estimation from street level RGB imagery, which is considered as a single available input data modality. \nOur solution is formulated via Markov Random Field optimization with deterministic output. \nThe proposed technique uses image metadata along with coordinates of objects detected in the image plane as \nfound by a custom-trained Convolutional Neural Network. Computing the object height using our methodology, \nin addition to object geolocation, has negligible effect on the overall computational cost. \nAccuracy is demonstrated experimentally for water drains and road signs on which we achieve average elevation estimation error lower than 20cm.},\ntitle = {Combining geolocation and height estimation of objects from street level imagery}, \nauthor  =  {Matej Ulicny and Vladimir A. Krylov and Julie Connelly and Rozenn Dahyot},\nyear = {2023},\neprint = {2305.08232},\narchivePrefix = {arXiv},\nprimaryClass = {cs.CV}\n}\n\n

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\n \n 2022\n \n \n (6)\n \n \n

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\n \n\n \n \n \n \n \n Interoperable Internet of Things for Smart Transportation Systems in Circular Cities.\n \n \n \n\n\n \n Kazmi, A.; Chaudhry, S. R.; Malazi, H. T.; Dhara, S.; and Clarke, S.\n\n\n \n\n\n\n Computer, 55(12): 86-97. 2022.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n\n\n\n

@ARTICLE{9963761,\n  author={Kazmi, Aqeel and Chaudhry, Saqib Rasool and Malazi, Hadi Tabatabaee and Dhara, Sangita and Clarke, Siobhán},\n  journal={Computer}, \n  title={Interoperable Internet of Things for Smart Transportation Systems in Circular Cities}, \n  year={2022},\n  volume={55},\n  number={12},\n  pages={86-97},\n  abstract={This article discusses recent developments in the area of interoperable Internet of Things, using an example of delivering data-driven transportation services. Initial results obtained by exploiting heterogeneous traffic data streams reveal interesting traffic patterns for different vehicle types.},\n  keywords={Urban areas;Traffic control;Smart transportation;Internet of Things},\n  doi={10.1109/MC.2022.3202298}}\n

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\n \n\n \n \n \n \n \n A Cross-platform Metaverse Data Management System.\n \n \n \n\n\n \n Chen, B.; Song, C.; Lin, B.; Xu, X.; Tang, R.; Lin, Y.; Yao, Y.; Timoney, J.; and Bi, T.\n\n\n \n\n\n\n In 2022 IEEE International Conference on Metrology for Extended Reality, Artificial Intelligence and Neural Engineering (MetroXRAINE), pages 145-150, 2022. \n \n\n\n\n
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@INPROCEEDINGS{9967588,\n  author={Chen, Bohan and Song, Chengxin and Lin, Boyu and Xu, Xin and Tang, Ruoyan and Lin, Yunxuan and Yao, Yuan and Timoney, Joseph and Bi, Ting},\n  booktitle={2022 IEEE International Conference on Metrology for Extended Reality, Artificial Intelligence and Neural Engineering (MetroXRAINE)}, \n  title={A Cross-platform Metaverse Data Management System}, \n  year={2022},\n  volume={},\n  number={},\n  pages={145-150},\n  keywords={Industries;Metaverse;Extended reality;Neural engineering;Metrology;X reality;Artificial intelligence;cross-platform;data management;extended Reality;metaverse;Unity},\n  doi={10.1109/MetroXRAINE54828.2022.9967588}}\n

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\n \n\n \n \n \n \n \n A Study of Synchronization Deviation Between Vision and Haptic in multi-sensorial Extended Reality.\n \n \n \n\n\n \n Li, Z.; Yuan, X.; Chen, Y.; Xie, S.; Li, L.; An, Y.; Lin, Y.; Zhao, Z.; Timoney, J.; and Bi, T.\n\n\n \n\n\n\n In 2022 IEEE International Conference on Metrology for Extended Reality, Artificial Intelligence and Neural Engineering (MetroXRAINE), pages 75-80, 2022. \n \n\n\n\n
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@INPROCEEDINGS{9967654,\n  author={Li, Zheng and Yuan, Xiaxin and Chen, Yijing and Xie, Siyan and Li, Liangkai and An, Yi and Lin, Yinheng and Zhao, Zhijun and Timoney, Joseph and Bi, Ting},\n  booktitle={2022 IEEE International Conference on Metrology for Extended Reality, Artificial Intelligence and Neural Engineering (MetroXRAINE)}, \n  title={A Study of Synchronization Deviation Between Vision and Haptic in multi-sensorial Extended Reality}, \n  year={2022},\n  volume={},\n  number={},\n  pages={75-80},\n  keywords={Extended reality;Linear regression;Neural engineering;Metrology;Data models;Haptic interfaces;Quality of experience;XR;Regression Analysis;Multiple-Sensory;Synchronization Deviation},\n  doi={10.1109/MetroXRAINE54828.2022.9967654}}\n

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\n \n\n \n \n \n \n \n Towards Understanding the Effects of Evolving the MCTS UCT Selection Policy.\n \n \n \n\n\n \n Ameneyro, F. V.; and Galván, E.\n\n\n \n\n\n\n In 2022 IEEE Symposium Series on Computational Intelligence (SSCI), pages 1683-1690, 2022. \n \n\n\n\n
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@INPROCEEDINGS{10022266,\n  author={Ameneyro, Fred Valdez and Galván, Edgar},\n  booktitle={2022 IEEE Symposium Series on Computational Intelligence (SSCI)}, \n  title={Towards Understanding the Effects of Evolving the MCTS UCT Selection Policy}, \n  year={2022},\n  volume={},\n  number={},\n  pages={1683-1690},\n  keywords={Monte Carlo methods;Focusing;Search problems;Tuning;Computational intelligence;Monte Carlo Tree Search;UCT},\n  doi={10.1109/SSCI51031.2022.10022266}}\n

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\n \n\n \n \n \n \n \n \n Building Specifications in the Event-B Institution.\n \n \n \n \n\n\n \n Farrell, M.; Monahan, R.; and Power, J. F.\n\n\n \n\n\n\n Logical Methods in Computer Science, Volume 18, Issue 4. November 2022.\n \n\n\n\n
\n\n\n\n \n \n $\"Building$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n\n\n\n

@article{lmcs:10282,\n  TITLE = {Building Specifications in the Event-B Institution},\n  AUTHOR = {Marie Farrell and Rosemary Monahan and James F. Power},\n  URL = {https://lmcs.episciences.org/10282},\n  DOI = {10.46298/lmcs-18(4:4)2022},\n  abstract={This paper describes a formal semantics for the Event-B specification language using the theory of institutions. We define an institution for Event-B, EVT, and prove that it meets the validity requirements for satisfaction preservation and model amalgamation. We also present a series of functions that show how the constructs of the Event-B specification language can be mapped into our institution. Our semantics sheds new light on the structure of the Event-B language, allowing us to clearly delineate three constituent sub-languages: the superstructure, infrastructure and mathematical languages. One of the principal goals of our semantics is to provide access to the generic modularisation constructs available in institutions, including specification-building operators for parameterisation and refinement. We demonstrate how these features subsume and enhance the corresponding features already present in Event-B through a detailed study of their use in a worked example. We have implemented our approach via a parser and translator for Event-B specifications, EBtoEVT, which also provides a gateway to the Hets toolkit for heterogeneous specification.},\n  JOURNAL = {{Logical Methods in Computer Science}},\n  VOLUME = {{Volume 18, Issue 4}},\n  YEAR = {2022},\n  MONTH = Nov,\n  KEYWORDS = {Computer Science - Logic in Computer Science ; Computer Science - Formal Languages and Automata Theory},\n}\n\n

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\n \n\n \n \n \n \n \n \n Eye movement control in reading Chinese: A matter of strength of character?.\n \n \n \n \n\n\n \n Fan, X.; and Reilly, R. G.\n\n\n \n\n\n\n Acta Psychologica, 230: 103711. 2022.\n \n\n\n\n
\n\n\n\n \n \n $\"Eye$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{FAN2022103711,\ntitle = {Eye movement control in reading Chinese: A matter of strength of character?},\njournal = {Acta Psychologica},\nvolume = {230},\npages = {103711},\nyear = {2022},\nissn = {0001-6918},\nurl = {https://doi.org/10.1016/j.actpsy.2022.103711},\ndoi = {10.1016/j.actpsy.2022.103711},\nauthor = {Xi Fan and Ronan G. Reilly},\nkeywords = {Eye movements, Reading, Reading ability, Reading Chinese, Saccade targeting},\nabstract = {This paper explores the processes underlying eye movement control in Chinese reading among a population of young 4th and 5th grade readers. Various proposals to explain the underlying mechanisms involved in eye movement control are examined and the paper concludes that the most likely account is of a two-factor process whereby the character is the main driver for longer saccades and that the word plays a role in shorter ones. A computational model is proposed to provide an integrated account of the dynamic interaction of these two factors.}\n}\n\n

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