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\n  \n 2026\n \n \n (4)\n \n \n
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\n \n\n \n \n \n \n \n Neural Network Verification for Gliding Drone Control: A Case Study.\n \n \n \n\n\n \n Kessler, C.; Komendantskaya, E.; Casadio, M.; Viola, I. M.; Flinkow, T.; Othman, A. A.; Malhotra, A.; and McPherson, R.\n\n\n \n\n\n\n In Giacobbe, M.; and Lukina, A., editor(s), AI Verification, pages 180–199, Cham, 2026. 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
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@inproceedings{kesslerNeuralNetworkVerification2026,\n  title = {Neural {{Network Verification}} for~{{Gliding Drone Control}}: {{A Case Study}}},\n  shorttitle = {Neural {{Network Verification}} for~{{Gliding Drone Control}}},\n  booktitle = {{{AI Verification}}},\n  author = {Kessler, Colin and Komendantskaya, Ekaterina and Casadio, Marco and Viola, Ignazio Maria and Flinkow, Thomas and Othman, Albaraa Ammar and Malhotra, Alistair and McPherson, Robbie},\n  editor = {Giacobbe, Mirco and Lukina, Anna},\n  year = 2026,\n  pages = {180--199},\n  publisher = {Springer Nature Switzerland},\n  address = {Cham},\n  doi = {10.1007/978-3-031-99991-8_9},\n  abstract = {As machine learning is increasingly deployed in autonomous systems, verification of neural network controllers is becoming an active research domain. Existing tools and annual verification competitions suggest that soon this technology will become effective for real-world applications. Our application comes from the emerging field of microflyers that are passively transported by the wind, which may have various uses in weather or pollution monitoring. Specifically, we investigate centimetre-scale bio-inspired gliding drones that resemble Alsomitra macrocarpa diaspores. In this paper, we propose a new case study on verifying Alsomitra-inspired drones with neural network controllers, with the aim of adhering closely to a target trajectory. We show that our system differs substantially from existing VNN and ARCH competition benchmarks, and show that a combination of tools holds promise for verifying such systems in the future, if certain shortcomings can be overcome. We propose a novel method for robust training of regression networks, and investigate formalisations of this case study in Vehicle and CORA. Our verification results suggest that the investigated training methods do improve performance and robustness of neural network controllers in this application, but are limited in scope and usefulness. This is due to systematic limitations of both Vehicle and CORA, and the complexity of our system reducing the scale of reachability, which we investigate in detail. If these limitations can be overcome, it will enable engineers to develop safe and robust technologies that improve people's lives and reduce our impact on the environment.},\n  isbn = {978-3-031-99991-8},\n  langid = {english}\n}\n\n\n\n \n\n
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\n As machine learning is increasingly deployed in autonomous systems, verification of neural network controllers is becoming an active research domain. Existing tools and annual verification competitions suggest that soon this technology will become effective for real-world applications. Our application comes from the emerging field of microflyers that are passively transported by the wind, which may have various uses in weather or pollution monitoring. Specifically, we investigate centimetre-scale bio-inspired gliding drones that resemble Alsomitra macrocarpa diaspores. In this paper, we propose a new case study on verifying Alsomitra-inspired drones with neural network controllers, with the aim of adhering closely to a target trajectory. We show that our system differs substantially from existing VNN and ARCH competition benchmarks, and show that a combination of tools holds promise for verifying such systems in the future, if certain shortcomings can be overcome. We propose a novel method for robust training of regression networks, and investigate formalisations of this case study in Vehicle and CORA. Our verification results suggest that the investigated training methods do improve performance and robustness of neural network controllers in this application, but are limited in scope and usefulness. This is due to systematic limitations of both Vehicle and CORA, and the complexity of our system reducing the scale of reachability, which we investigate in detail. If these limitations can be overcome, it will enable engineers to develop safe and robust technologies that improve people's lives and reduce our impact on the environment.\n
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\n \n\n \n \n \n \n \n Synthesising Cross-Speaker Data for Low-Resource Pathological Speech Recognition with PEFT.\n \n \n \n\n\n \n Mokgosi, K.; Dadgar, M.; Ennis, C.; and Ross, R.\n\n\n \n\n\n\n In Ekštein, K.; Konopík, Miloslav; Pražák, O.; and Pártl, F., editor(s), Text, Speech, and Dialogue, pages 182–193, Cham, 2026. Springer Nature Switzerland\n \n\n\n\n
\n\n\n\n \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
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@InProceedings{10.1007/978-3-032-02548-7_16,\nauthor="Mokgosi, Kesego\nand Dadgar, Milad\nand Ennis, Cathy\nand Ross, Robert",\neditor="Ek{\\v{s}}tein, Kamil\nand Konop{\\'i}k, Miloslav\nand Pra{\\v{z}}{\\'a}k, Ond{\\v{r}}ej\nand P{\\'a}rtl, Franti{\\v{s}}ek",\ntitle="Synthesising Cross-Speaker Data for Low-Resource Pathological Speech Recognition with PEFT",\nbooktitle="Text, Speech, and Dialogue",\nyear="2026",\npublisher="Springer Nature Switzerland",\naddress="Cham",\npages="182--193",\nabstract="Dysarthric speech recognition is essential for enhancing communication and accessibility for individuals with speech impairments, yet its development is hindered by a scarcity of robust, speaker-specific datasets. This study explores low-resource dysarthric speech recognition through cross-speaker transfer using synthetic data and parameter-efficient fine-tuning (PEFT). We integrate SpeechT5 text-to-speech (TTS) synthesis with x-vector speaker embeddings to generate speaker-specific dysarthric speech, enabling model adaptation while preserving pathological speech characteristics such as prosodic irregularities. Experiments on the TORGO dataset show that mixed cross-synthetic data with LoRA fine-tuning achieves a WER of 0.17, representing a 71.7{\\%} improvement over the standard model (0.60 WER) without fine-tuning the TTS model. However, cross-dataset generalisation remains challenging, yielding higher WERs on MINDS-14 (4.69) and AMI (0.96--3.83) datasets. Whilst synthetic data enhances in-domain recognition, further research is needed to improve cross-dataset generalisation and speaker adaptation, particularly for low-resource pathological speech settings.",\nisbn="978-3-032-02548-7"\n}\n\n\n\n
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\n Dysarthric speech recognition is essential for enhancing communication and accessibility for individuals with speech impairments, yet its development is hindered by a scarcity of robust, speaker-specific datasets. This study explores low-resource dysarthric speech recognition through cross-speaker transfer using synthetic data and parameter-efficient fine-tuning (PEFT). We integrate SpeechT5 text-to-speech (TTS) synthesis with x-vector speaker embeddings to generate speaker-specific dysarthric speech, enabling model adaptation while preserving pathological speech characteristics such as prosodic irregularities. Experiments on the TORGO dataset show that mixed cross-synthetic data with LoRA fine-tuning achieves a WER of 0.17, representing a 71.7% improvement over the standard model (0.60 WER) without fine-tuning the TTS model. However, cross-dataset generalisation remains challenging, yielding higher WERs on MINDS-14 (4.69) and AMI (0.96–3.83) datasets. Whilst synthetic data enhances in-domain recognition, further research is needed to improve cross-dataset generalisation and speaker adaptation, particularly for low-resource pathological speech settings.\n
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\n \n\n \n \n \n \n \n Teaching Computational Thinking Through Active Games: Insights from Teacher Training.\n \n \n \n\n\n \n Lehtimäki, T.; Costello, E.; Casey, K.; Mooney, A.; Monahan, R.; and Naughton, T.\n\n\n \n\n\n\n In Staub, J.; and Singla, A., editor(s), Informatics in Schools. Fostering Problem-Solving, Creativity, and Critical Thinking Through Computer Science Education, pages 80–93, Cham, 2026. Springer Nature Switzerland\n \n\n\n\n
\n\n\n\n \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 
@InProceedings{10.1007/978-3-032-01222-7_7,\nauthor="Lehtim{\\"a}ki, Taina\nand Costello, Eddie\nand Casey, Kevin\nand Mooney, Aidan\nand Monahan, Rosemary\nand Naughton, Thomas J.",\neditor="Staub, Jacqueline\nand Singla, Adish",\ntitle="Teaching Computational Thinking Through Active Games: Insights from Teacher Training",\nbooktitle="Informatics in Schools. Fostering Problem-Solving, Creativity, and Critical Thinking Through Computer Science Education",\nyear="2026",\npublisher="Springer Nature Switzerland",\naddress="Cham",\npages="80--93",\nabstract="Various forms of unplugged computer science activities have been proposed and employed at the student level in the past. However, there have been few studies of its effectiveness at the teacher level. Active Computational Thinking (CT) Games are unplugged CT activities that encourage physical movement. In school systems where computer science is not part of the curriculum, questions arise regarding how well teachers can learn the fundamentals of CT from Active CT Games, and how effective an Active CT Games approach could be in the classroom.",\nisbn="978-3-032-01222-7"\n}\n\n\n
\n
\n\n\n
\n Various forms of unplugged computer science activities have been proposed and employed at the student level in the past. However, there have been few studies of its effectiveness at the teacher level. Active Computational Thinking (CT) Games are unplugged CT activities that encourage physical movement. In school systems where computer science is not part of the curriculum, questions arise regarding how well teachers can learn the fundamentals of CT from Active CT Games, and how effective an Active CT Games approach could be in the classroom.\n
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\n \n\n \n \n \n \n \n \n Selected papers from the Rigorous State-Based Methods, 7th International Conference, ABZ 2023, Nancy, France, May 30–June 2, 2023.\n \n \n \n \n\n\n \n Méry, D.; and Monahan, R.\n\n\n \n\n\n\n Science of Computer Programming, 247: 103321. January 2026.\n \n\n\n\n
\n\n\n\n \n \n \"SelectedPaper\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 
@article{M_ry_2026, title={Selected papers from the Rigorous State-Based Methods, 7th International Conference, ABZ 2023, Nancy, France, May 30–June 2, 2023}, volume={247}, ISSN={0167-6423}, url={http://dx.doi.org/10.1016/j.scico.2025.103321}, DOI={10.1016/j.scico.2025.103321}, journal={Science of Computer Programming}, publisher={Elsevier BV}, author={Méry, Dominique and Monahan, Rosemary}, year={2026}, month=jan, pages={103321} }\n\n
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\n  \n 2025\n \n \n (48)\n \n \n
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\n \n\n \n \n \n \n \n \n Neutral host within the business model framework.\n \n \n \n \n\n\n \n Otlyvanska, G.; Dooley, J.; Connolly, N.; Walsh, G.; and Derzhuk, O.\n\n\n \n\n\n\n In P. Ahokangas, I. A.; and M. Iivari, & T. K., editor(s), Transformative power of technology in shaping sustainable business models: Proceedings of the Business Model Conference 2025, University of Oulu, 2025. \n \n\n\n\n
\n\n\n\n \n \n \"NeutralPaper\n  \n \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 
@inproceedings{Derzhuk2025,\nauthor={Otlyvanska, G. and Dooley, J. and Connolly, N. and Walsh, G. and Derzhuk, O.},\nyear={2025},\ntitle={Neutral host within the business model framework},\neditor={P. Ahokangas, I. Atkova, M. Iivari, & T. Koivumäki}, \nbooktitle={Transformative power of technology in shaping sustainable business models: Proceedings of the Business Model Conference 2025},\npage={85-90},\naddress={University of Oulu},\nurl={https://urn.fi/URN:NBN:fi:oulu-202512107220},\n}\n\n\n
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\n \n\n \n \n \n \n \n \n Refactoring in Requirements Engineering: Exploring a methodology for formal verification of safety-critical systems.\n \n \n \n \n\n\n \n Sheridan, O.\n\n\n \n\n\n\n In Hess, A.; Susi, A.; Groen, E. C.; Ruiz, M.; Khan, M. A.; Aydemir, F. B.; Daneva, M.; Guizzardi, R.; Gulden, J.; Herrmann, A.; Horkoff, J.; Kopczyńska, S.; Mennig, P.; Oriol, M.; Paja, E.; Perini, A.; Rachmann, A.; Schneider, K.; Semini, L.; Spoletini, P.; and Vogelsang, A., editor(s), Joint Proceedings of REFSQ 2025 Workshops, Doctoral Symposium, Posters & Tools Track, and Education and Training Track, volume 3959, of CEUR Workshop Proceedings, Barcelona, Spain, April 2025. CEUR\n ISSN: 1613-0073\n\n\n\n
\n\n\n\n \n \n \"RefactoringPaper\n  \n \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 
@inproceedings{sheridan_refactoring_2025,\naddress = {Barcelona, Spain},\nseries = {{CEUR} {Workshop} {Proceedings}},\ntitle = {Refactoring in {Requirements} {Engineering}: {Exploring} a methodology for formal verification of safety-critical systems},\nvolume = {3959},\nshorttitle = {Refactoring in {Requirements} {Engineering}},\nurl = {https://ceur-ws.org/Vol-3959/#DS-paper2},\nlanguage = {en},\nurldate = {2025-11-28},\nbooktitle = {Joint {Proceedings} of {REFSQ} 2025 {Workshops}, {Doctoral} {Symposium}, {Posters} \\& {Tools} {Track}, and {Education} and {Training} {Track}},\npublisher = {CEUR},\nauthor = {Sheridan, Oisín},\neditor = {Hess, Anne and Susi, Angelo and Groen, Eduard C. and Ruiz, Marcela and Khan, Muhammad Abbas and Aydemir, Fatma Başak and Daneva, Maya and Guizzardi, Renata and Gulden, Jens and Herrmann, Andrea and Horkoff, Jennifer and Kopczyńska, Sylwia and Mennig, Patrick and Oriol, Marc and Paja, Elda and Perini, Anna and Rachmann, Alexander and Schneider, Kurt and Semini, Laura and Spoletini, Paola and Vogelsang, Andreas},\nmonth = apr,\nyear = {2025},\nnote = {ISSN: 1613-0073},\nfile = {Full Text PDF:C\\:\\\\Users\\\\user\\\\Zotero\\\\storage\\\\3H9CA93E\\\\Sheridan - 2025 - Refactoring in Requirements Engineering Exploring a methodology for formal verification of safety-c.pdf:application/pdf},\n}\n\n\n\n\n
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\n \n\n \n \n \n \n \n \n An Efficient Algorithm to Compute the Minimum Free Energy of Interacting Nucleic Acid Strands.\n \n \n \n \n\n\n \n Shalaby, A.; and Woods, D.\n\n\n \n\n\n\n In Censor-Hillel, K.; Grandoni, F.; Ouaknine, J.; and Puppis, G., editor(s), 52nd International Colloquium on Automata, Languages, and Programming (ICALP 2025), volume 334, of Leibniz International Proceedings in Informatics (LIPIcs), pages 130:1–130:20, Dagstuhl, Germany, 2025. Schloss Dagstuhl – Leibniz-Zentrum für Informatik\n \n\n\n\n
\n\n\n\n \n \n \"AnPaper\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 
@InProceedings{shalaby_et_al:LIPIcs.ICALP.2025.130,\n  author =\t{Shalaby, Ahmed and Woods, Damien},\n  title =\t{{An Efficient Algorithm to Compute the Minimum Free Energy of Interacting Nucleic Acid Strands}},\n  booktitle =\t{52nd International Colloquium on Automata, Languages, and Programming (ICALP 2025)},\n  pages =\t{130:1--130:20},\n  series =\t{Leibniz International Proceedings in Informatics (LIPIcs)},\n  ISBN =\t{978-3-95977-372-0},\n  ISSN =\t{1868-8969},\n  year =\t{2025},\n  volume =\t{334},\n  editor =\t{Censor-Hillel, Keren and Grandoni, Fabrizio and Ouaknine, Jo\\"{e}l and Puppis, Gabriele},\n  publisher =\t{Schloss Dagstuhl -- Leibniz-Zentrum f{\\"u}r Informatik},\n  address =\t{Dagstuhl, Germany},\n  URL =\t\t{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ICALP.2025.130},\n  URN =\t\t{urn:nbn:de:0030-drops-235071},\n  doi =\t\t{10.4230/LIPIcs.ICALP.2025.130},\n  annote =\t{Keywords: Minimum free energy, MFE, partition function, nucleic acid, DNA, RNA, secondary structure, computational complexity, algorithm analysis and design, dynamic programming}\n}\n\n\n
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\n \n\n \n \n \n \n \n \n MIND over Body: Adaptive Thinking using Dynamic Computation.\n \n \n \n \n\n\n \n Mathur, M.; Pearlmutter, B. A.; and Plis, S. M.\n\n\n \n\n\n\n In The Thirteenth International Conference on Learning Representations, 2025. \n \n\n\n\n
\n\n\n\n \n \n \"MINDPaper\n  \n \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
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@inproceedings{mathur2025mind,\ntitle={{MIND} over Body: Adaptive Thinking using Dynamic Computation},\nauthor={Mrinal Mathur and Barak A. Pearlmutter and Sergey M. Plis},\nbooktitle={The Thirteenth International Conference on Learning Representations},\nyear={2025},\nurl={https://openreview.net/forum?id=EjJGND0m1x}\n}\n\n\n
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\n \n\n \n \n \n \n \n \n Leveraging LLMs for Formal Software Requirements: Challenges and Prospects.\n \n \n \n \n\n\n \n Beg, A.; O'Donoghue, D.; and Monahan, R.\n\n\n \n\n\n\n In Proceedings of OVERLAY 2025: Artificial Intelligence and Formal Verification, Logic, Automata, and Synthesis, volume 4142, of CEUR Workshop Proceedings, pages 95–105, 2025. CEUR-WS.org\n \n\n\n\n
\n\n\n\n \n \n \"LeveragingPaper\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
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@inproceedings{Beg2025LLMFormalRequirements,\n  author    = {Beg, Arshad and O'Donoghue, Diarmuid and Monahan, Rosemary},\n  title     = {Leveraging {LLM}s for Formal Software Requirements: Challenges and Prospects},\n  booktitle = {Proceedings of OVERLAY 2025: Artificial Intelligence and Formal Verification, Logic, Automata, and Synthesis},\n  series    = {CEUR Workshop Proceedings},\n  volume    = {4142},\n  pages     = {95--105},\n  year      = {2025},\n  publisher = {CEUR-WS.org},\n  issn      = {1613-0073},\n  url       = {https://ceur-ws.org/Vol-4142/paper11.pdf}\n}\n\n\n
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\n \n\n \n \n \n \n \n \n Artificial intelligence (AI)-driven technologies for managing pediatric speech and language therapy: A scoping review.\n \n \n \n \n\n\n \n Dadgar, M.; Ennis, C.; Mokgosi, K.; and Ross, R.\n\n\n \n\n\n\n DIGITAL HEALTH, 11. May 2025.\n \n\n\n\n
\n\n\n\n \n \n \"ArtificialPaper\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 
@article{Dadgar2025,\n  title = {Artificial intelligence (AI)-driven technologies for managing pediatric speech and language therapy: A scoping review},\n  volume = {11},\n  ISSN = {2055-2076},\n  url = {http://dx.doi.org/10.1177/20552076251376533},\n  DOI = {10.1177/20552076251376533},\n  journal = {DIGITAL HEALTH},\n  publisher = {SAGE Publications},\n  author = {Dadgar,  Milad and Ennis,  Cathy and Mokgosi,  Kesego and Ross,  Robert},\n  year = {2025},\n  month = may \n}\n\n
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\n \n\n \n \n \n \n \n \n Enhancing Synthetic Image Realism with Controlled Diffusion Models.\n \n \n \n \n\n\n \n Nosheen, I.; Farooq, M. A.; Corcoran, P.; Ennis, C.; and Madden, M. G.\n\n\n \n\n\n\n In 2025 International Joint Conference on Neural Networks (IJCNN), pages 1–8, June 2025. IEEE\n \n\n\n\n
\n\n\n\n \n \n \"EnhancingPaper\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 
@inproceedings{Nosheen2025,\n  title = {Enhancing Synthetic Image Realism with Controlled Diffusion Models},\n  url = {http://dx.doi.org/10.1109/IJCNN64981.2025.11228158},\n  DOI = {10.1109/ijcnn64981.2025.11228158},\n  booktitle = {2025 International Joint Conference on Neural Networks (IJCNN)},\n  publisher = {IEEE},\n  author = {Nosheen,  Iqra and Farooq,  Muhammad Ali and Corcoran,  Peter and Ennis,  Cathy and Madden,  Michael G.},\n  year = {2025},\n  month = jun,\n  pages = {1–8},\n}\n\n
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\n \n\n \n \n \n \n \n \n Face Off: Evaluating Virtual Human Expressions and Non-Tracking Control Methods in VR.\n \n \n \n \n\n\n \n Sangeeth Chandran, J K; Salvador, M. L.; and Ennis, C.\n\n\n \n\n\n\n In 2025 11th International Conference on Virtual Reality (ICVR), pages 126–134, July 2025. IEEE\n \n\n\n\n
\n\n\n\n \n \n \"FacePaper\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 
@inproceedings{SangeethChandran2025,\n  title = {Face Off: Evaluating Virtual Human Expressions and Non-Tracking Control Methods in VR},\n  url = {http://dx.doi.org/10.1109/ICVR66534.2025.11172599},\n  DOI = {10.1109/icvr66534.2025.11172599},\n  booktitle = {2025 11th International Conference on Virtual Reality (ICVR)},\n  publisher = {IEEE},\n  author = {Sangeeth Chandran,  J K and Salvador,  Marisa Llorens and Ennis,  Cathy},\n  year = {2025},\n  month = jul,\n  pages = {126–134},\n}\n\n
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\n \n\n \n \n \n \n \n Verifying OCL Pre/Post Condition using Cyclone.\n \n \n \n\n\n \n Yuelou, D.; and Hao, W.\n\n\n \n\n\n\n In 23rd International Workshop on OCL and Textual Modeling, Koblenz, Germany, June 2025. CEUR-WS\n \n\n\n\n
\n\n\n\n \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
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@inproceedings{yuelou_verifying_nodate,\n\taddress = {Koblenz, Germany},\n\ttitle = {Verifying {OCL} {Pre}/{Post} {Condition} using {Cyclone}},\n\tbooktitle = {23rd {International} {Workshop} on {OCL} and {Textual} {Modeling}},\n\tpublisher = {CEUR-WS},\n\tauthor = {Yuelou, Ding and Hao, Wu},\n\tmonth = {June},\n  year={2025},\n}\n\n
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\n \n\n \n \n \n \n \n A New Set of Metrics for Measuring Complexity of OCL Expressions.\n \n \n \n\n\n \n Jha, A.\n\n\n \n\n\n\n In 23rd International Workshop on OCL and Textual Modeling, Koblenz, Germany, June 2025. CEUR-WS\n \n\n\n\n
\n\n\n\n \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
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@inproceedings{jha_new_nodate,\n\taddress = {Koblenz, Germany},\n\ttitle = {A {New} {Set} of {Metrics} for {Measuring} {Complexity} of {OCL} {Expressions}},\n\tbooktitle = {23rd {International} {Workshop} on {OCL} and {Textual} {Modeling}},\n\tpublisher = {CEUR-WS},\n\tauthor = {Jha, Ankit},\n\tmonth =  {June},\n    year={2025},\n}\n\n
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\n \n\n \n \n \n \n \n \n A parallel genetic algorithm for multi-criteria path routing on complex real-world road networks.\n \n \n \n \n\n\n \n Sharma, H.; Galván, E.; and Mooney, P.\n\n\n \n\n\n\n Applied Soft Computing, 170: 112559. February 2025.\n \n\n\n\n
\n\n\n\n \n \n \"APaper\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 
@article{Sharma_2025, title={A parallel genetic algorithm for multi-criteria path routing on complex real-world road networks}, volume={170}, ISSN={1568-4946}, url={http://dx.doi.org/10.1016/j.asoc.2024.112559}, DOI={10.1016/j.asoc.2024.112559}, journal={Applied Soft Computing}, publisher={Elsevier BV}, author={Sharma, Harish and Galván, Edgar and Mooney, Peter}, year={2025}, month=feb, pages={112559} }\n\n
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\n \n\n \n \n \n \n \n \n A self-reference approach for optical diffraction tomography.\n \n \n \n \n\n\n \n Tang, Z.; Winnik, J.; and Hennelly, B. M.\n\n\n \n\n\n\n In Ferraro, P.; Grilli, S.; Psaltis, D.; and Vasdekis, A. E., editor(s), Optical Methods for Inspection, Characterization, and Imaging of Biomaterials VII, pages 17, August 2025. SPIE\n \n\n\n\n
\n\n\n\n \n \n \"APaper\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 
@inproceedings{Tang_2025, title={A self-reference approach for optical diffraction tomography}, url={http://dx.doi.org/10.1117/12.3066513}, DOI={10.1117/12.3066513}, booktitle={Optical Methods for Inspection, Characterization, and Imaging of Biomaterials VII}, publisher={SPIE}, author={Tang, Zhengyuan and Winnik, Julianna and Hennelly, Bryan M.}, editor={Ferraro, Pietro and Grilli, Simonetta and Psaltis, Demetri and Vasdekis, Andreas E.}, year={2025}, month=aug, pages={17} }\n \n
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\n \n\n \n \n \n \n \n \n A Thermodynamically Favoured Molecular Computer: Robust, Fast, Renewable, Scalable.\n \n \n \n \n\n\n \n Stérin, T.; Eshra, A.; Adio, J.; Evans, C. G.; and Woods, D.\n\n\n \n\n\n\n . July 2025.\n \n\n\n\n
\n\n\n\n \n \n \"APaper\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
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@article{St_rin_2025, title={A Thermodynamically Favoured Molecular Computer: Robust, Fast, Renewable, Scalable}, url={http://dx.doi.org/10.1101/2025.07.16.664196}, DOI={10.1101/2025.07.16.664196}, publisher={Cold Spring Harbor Laboratory}, author={Stérin, Tristan and Eshra, Abeer and Adio, Janet and Evans, Constantine Glen and Woods, Damien}, year={2025}, month=jul }\n\n
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\n \n\n \n \n \n \n \n \n An analysis on the effects of evolving the Monte Carlo tree search upper confidence for trees selection policy on unimodal, multimodal and deceptive landscapes.\n \n \n \n \n\n\n \n Galván, E.; and Valdez Ameneyro, F.\n\n\n \n\n\n\n Information Sciences, 715: 122226. October 2025.\n \n\n\n\n
\n\n\n\n \n \n \"AnPaper\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 
@article{Galv_n_2025, title={An analysis on the effects of evolving the Monte Carlo tree search upper confidence for trees selection policy on unimodal, multimodal and deceptive landscapes}, volume={715}, ISSN={0020-0255}, url={http://dx.doi.org/10.1016/j.ins.2025.122226}, DOI={10.1016/j.ins.2025.122226}, journal={Information Sciences}, publisher={Elsevier BV}, author={Galván, Edgar and Valdez Ameneyro, Fred}, year={2025}, month=oct, pages={122226} }\n\n
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\n \n\n \n \n \n \n \n \n Benchmarking EfficientTAM on FMO datasets.\n \n \n \n \n\n\n \n Aktas, S.; Markham, C.; McDonald, J.; and Dahyot, R.\n\n\n \n\n\n\n In Irish Machine Vision and Image Processing (IMVIP 2025), pages 59-66, Ulster University, Derry-Londonderry, Northern Ireland, 2025. \n \n\n\n\n
\n\n\n\n \n \n \"BenchmarkingPaper\n  \n \n \n \"BenchmarkingCode\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
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@inproceedings{Aktas2025,\nauthor  =  {Senem Aktas and Charles Markham and John McDonald and Rozenn Dahyot}, \ntitle  =  {Benchmarking EfficientTAM on FMO datasets},\nbooktitle  =  {Irish Machine Vision and Image Processing (IMVIP 2025)},\naddress =  {Ulster University, Derry-Londonderry, Northern Ireland},\nyear  =  {2025},\npages=  {59-66},\nabstract  =  {Fast and tiny object tracking remains a challenge in computer vision and in this paper we first introduce\na JSON metadata file associated with four open source datasets of Fast Moving Objects (FMOs) image\nsequences. In addition, we extend the description of the FMOs datasets with additional ground truth information\nin JSON format (called FMOX) with object size information. Finally we use our FMOX file to test\na recently proposed foundational model for tracking (called EfficientTAM) showing that its performance\ncompares well with the pipelines originally taylored for these FMO datasets. Our comparison of these stateof-\nthe-art techniques on FMOX is provided with Trajectory Intersection of Union (TIoU) scores. The code\nand JSON is shared open source allowing FMOX to be accessible and usable for other machine learning\npipelines aiming to process FMO datasets.},\nurl  =  {Paper=https://arxiv.org/pdf/2509.06536.pdf\nCode=https://cvmlmu.github.io/FMOX/},\ndoi  =  {10.21251/8043511f-bf93-4b36-9348-0726af0987f6},\nkeywords = {Tracking, fast moving objects},\nnote  =  {},\n}\n\n
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\n Fast and tiny object tracking remains a challenge in computer vision and in this paper we first introduce a JSON metadata file associated with four open source datasets of Fast Moving Objects (FMOs) image sequences. In addition, we extend the description of the FMOs datasets with additional ground truth information in JSON format (called FMOX) with object size information. Finally we use our FMOX file to test a recently proposed foundational model for tracking (called EfficientTAM) showing that its performance compares well with the pipelines originally taylored for these FMO datasets. Our comparison of these stateof- the-art techniques on FMOX is provided with Trajectory Intersection of Union (TIoU) scores. The code and JSON is shared open source allowing FMOX to be accessible and usable for other machine learning pipelines aiming to process FMO datasets.\n
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\n \n\n \n \n \n \n \n \n Evaluation of 3D Gaussian Splatting in Plant Reconstruction.\n \n \n \n \n\n\n \n McAfee, A.; Pluck, T.; Dahyot, R.; and Lacey, G.\n\n\n \n\n\n\n In Irish Machine Vision and Image Processing (IMVIP 2025), pages 26-29, Ulster University, Derry-Londonderry, Northern Ireland, 2025. \n \n\n\n\n
\n\n\n\n \n \n \"EvaluationPaper\n  \n \n \n \"EvaluationCode\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 1 download\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
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@inproceedings{McAfee2025,\ntitle  =  {Evaluation of 3D Gaussian Splatting in Plant Reconstruction},\nauthor = {Aaron McAfee and Thomas Pluck and Rozenn Dahyot and Gerry Lacey},\nbooktitle  =  {Irish Machine Vision and Image Processing (IMVIP 2025)},\naddress =  {Ulster University, Derry-Londonderry, Northern Ireland},\nvolume  =  {},\nyear  =  {2025},\npages={26-29},\nabstract  =  {Accurate 3D reconstruction of plants is essential for applications in precision agriculture, phenotyping,\nand plant health monitoring. Traditional methods such as LiDAR or Structure-from-Motion often struggle\nwith complex plant topologies or require complex sensing hardware. Recent advances in neural rendering,\nparticularly 3D Gaussian Splatting (3DGS), have shown promise in efficiently capturing fine-grained plant\ndetails. In this paper, we evaluate the performance of 3DGS on a new dataset of seven plants, each comprising\napproximately 500 multi-view images. Results demonstrate that 3DGS effectively reconstructs complex\nplant structures and is a suitable visual aid for plant phenotyping experts.},\nurl  =  {Paper=https://pure.ulster.ac.uk/ws/portalfiles/portal/227817636/FinalProceedings_v1.1.pdf \nCode=https://github.com/aaronmcafee123/SynthPlant3D},\ndoi={10.21251/8043511f-bf93-4b36-9348-0726af0987f6},\nkeywords={3D Gaussian Splatting, Precision Agriculture, Plant Phenotyping, 3D Reconstruction},\nnote  =  {},\n}\n\n\n
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\n Accurate 3D reconstruction of plants is essential for applications in precision agriculture, phenotyping, and plant health monitoring. Traditional methods such as LiDAR or Structure-from-Motion often struggle with complex plant topologies or require complex sensing hardware. Recent advances in neural rendering, particularly 3D Gaussian Splatting (3DGS), have shown promise in efficiently capturing fine-grained plant details. In this paper, we evaluate the performance of 3DGS on a new dataset of seven plants, each comprising approximately 500 multi-view images. Results demonstrate that 3DGS effectively reconstructs complex plant structures and is a suitable visual aid for plant phenotyping experts.\n
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\n \n\n \n \n \n \n \n \n Blockchain enabled policy-based access control mechanism to restrict unauthorized access to electronic health records.\n \n \n \n \n\n\n \n Yaqub, N.; Zhang, J.; Khalid, M. I.; Wang, W.; Helfert, M.; Ahmed, M.; and Kim, J.\n\n\n \n\n\n\n PeerJ Computer Science, 11: e2647. January 2025.\n \n\n\n\n
\n\n\n\n \n \n \"BlockchainPaper\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
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@article{Yaqub_2025, title={Blockchain enabled policy-based access control mechanism to restrict unauthorized access to electronic health records}, volume={11}, ISSN={2376-5992}, url={http://dx.doi.org/10.7717/peerj-cs.2647}, DOI={10.7717/peerj-cs.2647}, journal={PeerJ Computer Science}, publisher={PeerJ}, author={Yaqub, Nadeem and Zhang, Jianbiao and Khalid, Muhammad Irfan and Wang, Weiru and Helfert, Markus and Ahmed, Mansoor and Kim, Jungsuk}, year={2025}, month=jan, pages={e2647} }\n\n
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\n \n\n \n \n \n \n \n \n Broadband CARS Hyperspectral Classification of Single Immune Cells.\n \n \n \n \n\n\n \n Muddiman, R.; Harkin, S.; Butler, M.; and Hennelly, B.\n\n\n \n\n\n\n Journal of Biophotonics, 18(3). January 2025.\n \n\n\n\n
\n\n\n\n \n \n \"BroadbandPaper\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 
@article{Muddiman_2025, title={Broadband <scp>CARS</scp> Hyperspectral Classification of Single Immune Cells}, volume={18}, ISSN={1864-0648}, url={http://dx.doi.org/10.1002/jbio.202400382}, DOI={10.1002/jbio.202400382}, number={3}, journal={Journal of Biophotonics}, publisher={Wiley}, author={Muddiman, Ryan and Harkin, Sarah and Butler, Marion and Hennelly, Bryan}, year={2025}, month=jan }\n\n
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\n \n\n \n \n \n \n \n \n Characterizing spectral peaks with deep-learning auto encoders.\n \n \n \n \n\n\n \n McNamara, T.; and Hennelly, B. M.\n\n\n \n\n\n\n In Ferraro, P.; Grilli, S.; Psaltis, D.; and Vasdekis, A. E., editor(s), Optical Methods for Inspection, Characterization, and Imaging of Biomaterials VII, pages 25, August 2025. SPIE\n \n\n\n\n
\n\n\n\n \n \n \"CharacterizingPaper\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
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@inproceedings{McNamara_2025, title={Characterizing spectral peaks with deep-learning auto encoders}, url={http://dx.doi.org/10.1117/12.3066295}, DOI={10.1117/12.3066295}, booktitle={Optical Methods for Inspection, Characterization, and Imaging of Biomaterials VII}, publisher={SPIE}, author={McNamara, Timothy and Hennelly, Bryan M.}, editor={Ferraro, Pietro and Grilli, Simonetta and Psaltis, Demetri and Vasdekis, Andreas E.}, year={2025}, month=aug, pages={25} }\n\n
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\n \n\n \n \n \n \n \n \n Exploring User Turning Perception and Comfort of the Segment Addition Redirected Walking Technique.\n \n \n \n \n\n\n \n Krueger, L.; Markham, C.; and Bierig, R.\n\n\n \n\n\n\n In Proceedings of the 3rd International Conference of the ACM Greek SIGCHI Chapter, of CHIGreece 2025, pages 147–152, September 2025. ACM\n \n\n\n\n
\n\n\n\n \n \n \"ExploringPaper\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
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@inproceedings{Krueger_2025, series={CHIGreece 2025}, title={Exploring User Turning Perception and Comfort of the Segment Addition Redirected Walking Technique}, url={http://dx.doi.org/10.1145/3749012.3749065}, DOI={10.1145/3749012.3749065}, booktitle={Proceedings of the 3rd International Conference of the ACM Greek SIGCHI Chapter}, publisher={ACM}, author={Krueger, Linda and Markham, Charles and Bierig, Ralf}, year={2025}, month=sep, pages={147–152}, collection={CHIGreece 2025} }\n\n
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\n \n\n \n \n \n \n \n \n Hyperspectral imaging system with switchable spontaneous Raman spectroscopy and broadband CARS.\n \n \n \n \n\n\n \n McNamara, T.; and Hennelly, B. M.\n\n\n \n\n\n\n In Falldorf, C.; Soldovieri, F.; Bianco, V.; and Picart, P., editor(s), Multimodal Sensing and Artificial Intelligence for Sustainable Future, pages 77, August 2025. SPIE\n \n\n\n\n
\n\n\n\n \n \n \"HyperspectralPaper\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
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@inproceedings{McNamara_2025, title={Hyperspectral imaging system with switchable spontaneous Raman spectroscopy and broadband CARS}, url={http://dx.doi.org/10.1117/12.3066294}, DOI={10.1117/12.3066294}, booktitle={Multimodal Sensing and Artificial Intelligence for Sustainable Future}, publisher={SPIE}, author={McNamara, Timothy and Hennelly, Bryan M.}, editor={Falldorf, Claas and Soldovieri, Francesco and Bianco, Vittorio and Picart, Pascal}, year={2025}, month=aug, pages={77} }\n\n \n
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\n \n\n \n \n \n \n \n \n LOMATCE: LOcal Model-Agnostic Time Series Classification Explanations.\n \n \n \n \n\n\n \n Mekonnen, E. T.; Longo, L.; and Dondio, P.\n\n\n \n\n\n\n IEEE Access, 13: 185218–185232. 2025.\n \n\n\n\n
\n\n\n\n \n \n \"LOMATCE: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
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@article{Mekonnen_2025, title={LOMATCE: LOcal Model-Agnostic Time Series Classification Explanations}, volume={13}, ISSN={2169-3536}, url={http://dx.doi.org/10.1109/access.2025.3625442}, DOI={10.1109/access.2025.3625442}, journal={IEEE Access}, publisher={Institute of Electrical and Electronics Engineers (IEEE)}, author={Mekonnen, Ephrem Tibebe and Longo, Luca and Dondio, Pierpaolo}, year={2025}, pages={185218–185232} }\n\n\n
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\n \n\n \n \n \n \n \n \n Manganese occurrence in groundwater and health risk assessment: a case study in various Upazillas of Chattogram district of Bangladesh.\n \n \n \n \n\n\n \n Rahman, M. A.; Zuthi, M. F. R.; Purkayestha, P. D.; Ahmed, M.; Hasan, S. M. F.; and Islam, S.\n\n\n \n\n\n\n Water Practice & Technology, 20(8): 1704–1715. August 2025.\n \n\n\n\n
\n\n\n\n \n \n \"ManganesePaper\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
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@article{Rahman_2025, title={Manganese occurrence in groundwater and health risk assessment: a case study in various Upazillas of Chattogram district of Bangladesh}, volume={20}, ISSN={1751-231X}, url={http://dx.doi.org/10.2166/wpt.2025.107}, DOI={10.2166/wpt.2025.107}, number={8}, journal={Water Practice &amp; Technology}, publisher={IWA Publishing}, author={Rahman, Md. Ajijur and Zuthi, Mst. Farzana Rahman and Purkayestha, Pias Datta and Ahmed, Mushfiq and Hasan, S. M. Farzin and Islam, Saima}, year={2025}, month=aug, pages={1704–1715} }\n\n
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\n \n\n \n \n \n \n \n \n MultiPath Island-Based Genetic Algorithm for the K-Most Diverse Near-Shortest Paths.\n \n \n \n \n\n\n \n Sharma, H.; Galván, E.; and Mooney, P.\n\n\n \n\n\n\n Information Sciences, 719: 122495. November 2025.\n \n\n\n\n
\n\n\n\n \n \n \"MultiPathPaper\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
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@article{Sharma_2025, title={MultiPath Island-Based Genetic Algorithm for the K-Most Diverse Near-Shortest Paths}, volume={719}, ISSN={0020-0255}, url={http://dx.doi.org/10.1016/j.ins.2025.122495}, DOI={10.1016/j.ins.2025.122495}, journal={Information Sciences}, publisher={Elsevier BV}, author={Sharma, Harish and Galván, Edgar and Mooney, Peter}, year={2025}, month=nov, pages={122495} }\n\n
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\n \n\n \n \n \n \n \n \n Neuroevolution-based multiobjective algorithm for feature selection and binary classification of DNA microarrays.\n \n \n \n \n\n\n \n García-Núñez, D.; Rodrígez-Vázquez, K.; Hernández, C.; and Galván, E.\n\n\n \n\n\n\n Applied Soft Computing, 184: 113520. December 2025.\n \n\n\n\n
\n\n\n\n \n \n \"Neuroevolution-basedPaper\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
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@article{Garc_a_N_ez_2025, title={Neuroevolution-based multiobjective algorithm for feature selection and binary classification of DNA microarrays}, volume={184}, ISSN={1568-4946}, url={http://dx.doi.org/10.1016/j.asoc.2025.113520}, DOI={10.1016/j.asoc.2025.113520}, journal={Applied Soft Computing}, publisher={Elsevier BV}, author={García-Núñez, Daniel and Rodrígez-Vázquez, Katya and Hernández, Carlos and Galván, Edgar}, year={2025}, month=dec, pages={113520} }\n\n
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\n \n\n \n \n \n \n \n NeuroLGP-SM: A Surrogate-Assisted Neuroevolution Approach Using Linear Genetic Programming.\n \n \n \n\n\n \n Stapleton, F.; Cody-Kenny, B.; and Galván, E.\n\n\n \n\n\n\n In Dorronsoro, B.; Zagar, M.; and Talbi, E., editor(s), Optimization and Learning, pages 67–81, Cham, 2025. Springer Nature Switzerland\n \n\n\n\n
\n\n\n\n \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
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@InProceedings{10.1007/978-3-031-77941-1_6,\nauthor="Stapleton, Fergal\nand Cody-Kenny, Brendan\nand Galv{\\'a}n, Edgar",\neditor="Dorronsoro, Bernab{\\'e}\nand Zagar, Martin\nand Talbi, El-Ghazali",\ntitle="NeuroLGP-SM: A Surrogate-Assisted Neuroevolution Approach Using Linear Genetic Programming",\nbooktitle="Optimization and Learning",\nyear="2025",\npublisher="Springer Nature Switzerland",\naddress="Cham",\npages="67--81",\nabstract="Evolutionary algorithms are increasingly recognised as a viable computational approach for the automated optimisation of deep neural networks (DNNs) within artificial intelligence. This method extends to the training of DNNs, an approach known as neuroevolution. However, neuroevolution is an inherently resource-intensive process, with certain studies reporting the consumption of thousands of GPU days for refining and training a single DNN network. To address the computational challenges associated with neuroevolution while still attaining good DNN accuracy, surrogate models emerge as a pragmatic solution. Despite their potential, the integration of surrogate models into neuroevolution is still in its early stages, hindered by factors such as the effective use of high-dimensional data and the representation employed in neuroevolution. In this context, we address these challenges by employing a suitable representation based on Linear Genetic Programming, denoted as NeuroLGP, and leveraging Kriging Partial Least Squares. The amalgamation of these two techniques culminates in our proposed methodology known as the NeuroLGP-Surrogate Model (NeuroLGP-SM). For comparison purposes, we also code and use a baseline approach incorporating a repair mechanism, a common practice in neuroevolution. Notably, the baseline approach surpasses the renowned VGG-16 model in accuracy. Given the computational intensity inherent in DNN operations, a singular run is typically the norm. To evaluate the efficacy of our proposed approach, we conducted 96 independent runs spanning a duration of 4 weeks. Significantly, our methodologies consistently outperform the baseline, with the SM model demonstrating superior accuracy or comparable results to the NeuroLGP approach. Noteworthy is the additional advantage that the SM approach exhibits a 25{\\$}{\\$}{\\backslash}{\\%}{\\$}{\\$}{\\%}reduction in computational requirements, further emphasising its efficiency for neuroevolution.",\nisbn="978-3-031-77941-1"\n}\n\n\n \n
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\n Evolutionary algorithms are increasingly recognised as a viable computational approach for the automated optimisation of deep neural networks (DNNs) within artificial intelligence. This method extends to the training of DNNs, an approach known as neuroevolution. However, neuroevolution is an inherently resource-intensive process, with certain studies reporting the consumption of thousands of GPU days for refining and training a single DNN network. To address the computational challenges associated with neuroevolution while still attaining good DNN accuracy, surrogate models emerge as a pragmatic solution. Despite their potential, the integration of surrogate models into neuroevolution is still in its early stages, hindered by factors such as the effective use of high-dimensional data and the representation employed in neuroevolution. In this context, we address these challenges by employing a suitable representation based on Linear Genetic Programming, denoted as NeuroLGP, and leveraging Kriging Partial Least Squares. The amalgamation of these two techniques culminates in our proposed methodology known as the NeuroLGP-Surrogate Model (NeuroLGP-SM). For comparison purposes, we also code and use a baseline approach incorporating a repair mechanism, a common practice in neuroevolution. Notably, the baseline approach surpasses the renowned VGG-16 model in accuracy. Given the computational intensity inherent in DNN operations, a singular run is typically the norm. To evaluate the efficacy of our proposed approach, we conducted 96 independent runs spanning a duration of 4 weeks. Significantly, our methodologies consistently outperform the baseline, with the SM model demonstrating superior accuracy or comparable results to the NeuroLGP approach. Noteworthy is the additional advantage that the SM approach exhibits a 25$}{$\\%$}{$%reduction in computational requirements, further emphasising its efficiency for neuroevolution.\n
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\n \n\n \n \n \n \n \n \n Overview of photon-counted three-dimensional imaging and related applications.\n \n \n \n \n\n\n \n Dodda, V. C.; Kuruguntla, L.; Ravichandran, N. K.; Lee, K.; Sollapur, R.; Damodaran, M.; Kumar, R.; Anilkumar, N.; Itapu, S.; Kumar, M.; Matoba, O.; Hennelly, B. M.; Stern, A.; and Muniraj, I.\n\n\n \n\n\n\n Optics Express, 33(15): 31211. July 2025.\n \n\n\n\n
\n\n\n\n \n \n \"OverviewPaper\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 
@article{Dodda_2025, title={Overview of photon-counted three-dimensional imaging and related applications}, volume={33}, ISSN={1094-4087}, url={http://dx.doi.org/10.1364/oe.546629}, DOI={10.1364/oe.546629}, number={15}, journal={Optics Express}, publisher={Optica Publishing Group}, author={Dodda, Vineela Chandra and Kuruguntla, Lakshmi and Ravichandran, Naresh Kumar and Lee, Kye-Sung and Sollapur, Rudrakant and Damodaran, Mathivanan and Kumar, Ravi and Anilkumar, Neelapala and Itapu, Srikanth and Kumar, Manoj and Matoba, Osamu and Hennelly, Bryan M. and Stern, Adrian and Muniraj, Inbarasan}, year={2025}, month=jul, pages={31211} }\n\n
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\n \n\n \n \n \n \n \n \n Real-time synthetic-aperture digital holographic microscopy.\n \n \n \n \n\n\n \n Tang, Z.; and Hennelly, B. M.\n\n\n \n\n\n\n Optics & Laser Technology, 188: 112848. October 2025.\n \n\n\n\n
\n\n\n\n \n \n \"Real-timePaper\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 
@article{Tang_2025, title={Real-time synthetic-aperture digital holographic microscopy}, volume={188}, ISSN={0030-3992}, url={http://dx.doi.org/10.1016/j.optlastec.2025.112848}, DOI={10.1016/j.optlastec.2025.112848}, journal={Optics &amp; Laser Technology}, publisher={Elsevier BV}, author={Tang, Zhengyuan and Hennelly, Bryan M.}, year={2025}, month=oct, pages={112848} }\n\n
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\n \n\n \n \n \n \n \n \n Surrogate-Assisted Evolution for Efficient Multi-branch Connection Design in Deep Neural Networks.\n \n \n \n \n\n\n \n Stapleton, F.; García Núñez, D.; Sun, Y.; and Galván, E.\n\n\n \n\n\n\n In Proceedings of the Genetic and Evolutionary Computation Conference Companion, of GECCO ’25 Companion, pages 747–750, July 2025. ACM\n \n\n\n\n
\n\n\n\n \n \n \"Surrogate-AssistedPaper\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 
@inproceedings{Stapleton_2025, series={GECCO ’25 Companion}, title={Surrogate-Assisted Evolution for Efficient Multi-branch Connection Design in Deep Neural Networks}, url={http://dx.doi.org/10.1145/3712255.3726649}, DOI={10.1145/3712255.3726649}, booktitle={Proceedings of the Genetic and Evolutionary Computation Conference Companion}, publisher={ACM}, author={Stapleton, Fergal and García Núñez, Daniel and Sun, Yanan and Galván, Edgar}, year={2025}, month=jul, pages={747–750}, collection={GECCO ’25 Companion} }\n\n
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\n \n\n \n \n \n \n \n \n Surrogate-Assisted Evolution for Efficient Multi-branch Connection Design in Deep Neural Networks.\n \n \n \n \n\n\n \n Stapleton, F.; Núñez, D. G.; Sun, Y.; and Galván, E.\n\n\n \n\n\n\n 2025.\n \n\n\n\n
\n\n\n\n \n \n \"Surrogate-AssistedPaper\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
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@misc{https://doi.org/10.48550/arxiv.2506.20469,\n  doi = {10.48550/ARXIV.2506.20469},\n  url = {https://arxiv.org/abs/2506.20469},\n  author = {Stapleton, Fergal and Núñez, Daniel García and Sun, Yanan and Galván, Edgar},\n  keywords = {Neural and Evolutionary Computing (cs.NE), FOS: Computer and information sciences, FOS: Computer and information sciences},\n  title = {Surrogate-Assisted Evolution for Efficient Multi-branch Connection Design in Deep Neural Networks},\n  publisher = {arXiv},\n  year = {2025},\n  copyright = {Creative Commons Attribution 4.0 International}\n}\n\n
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\n \n\n \n \n \n \n \n \n Synthetically Expressive: Evaluating gesture and voice for emotion and empathy in VR and 2D scenarios.\n \n \n \n \n\n\n \n Du, H.; Chhatre, K.; Peters, C.; Keegan, B.; McDonnell, R.; and Ennis, C.\n\n\n \n\n\n\n In Proceedings of the 25th ACM International Conference on Intelligent Virtual Agents, of IVA ’25, pages 1–10, September 2025. ACM\n Won best paper at IVA\n\n\n\n
\n\n\n\n \n \n \"SyntheticallyPaper\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 
@inproceedings{Du_2025, series={IVA ’25}, title={Synthetically Expressive: Evaluating gesture and voice for emotion and empathy in VR and 2D scenarios},\n  url={http://dx.doi.org/10.1145/3717511.3747074}, \n  DOI={10.1145/3717511.3747074}, \n  booktitle={Proceedings of the 25th ACM International Conference on Intelligent Virtual Agents}, \n  publisher={ACM},\n   author={Du, Haoyang and Chhatre, Kiran and Peters, Christopher and Keegan, Brian and McDonnell, Rachel and Ennis, Cathy}, \n   year={2025},\n    month=sep, pages={1–10}, collection={IVA ’25},\n    note={Won best paper at IVA},\n     }\n\n
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\n \n\n \n \n \n \n \n \n Time-Modulated Hebbian Learning for Classic Control Tasks.\n \n \n \n \n\n\n \n García Núñez, D.; Stapleton, F.; and Galván, E.\n\n\n \n\n\n\n In Proceedings of the Genetic and Evolutionary Computation Conference Companion, of GECCO ’25 Companion, pages 2119–2126, July 2025. ACM\n \n\n\n\n
\n\n\n\n \n \n \"Time-ModulatedPaper\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 
@inproceedings{Garc_a_N_ez_2025, series={GECCO ’25 Companion}, title={Time-Modulated Hebbian Learning for Classic Control Tasks}, url={http://dx.doi.org/10.1145/3712255.3734322}, DOI={10.1145/3712255.3734322}, booktitle={Proceedings of the Genetic and Evolutionary Computation Conference Companion}, publisher={ACM}, author={García Núñez, Daniel and Stapleton, Fergal and Galván, Edgar}, year={2025}, month=jul, pages={2119–2126}, collection={GECCO ’25 Companion} }\n\n\n\n
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\n \n\n \n \n \n \n \n \n A General Framework for Property-Driven Machine Learning.\n \n \n \n \n\n\n \n Flinkow, T.; Casadio, M.; Kessler, C.; Monahan, R.; and Komendantskaya, E.\n\n\n \n\n\n\n 2025.\n \n\n\n\n
\n\n\n\n \n \n \"APaper\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
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@misc{https://doi.org/10.48550/arxiv.2505.00466,\n  doi = {10.48550/ARXIV.2505.00466},\n  url = {https://arxiv.org/abs/2505.00466},\n  author = {Flinkow, Thomas and Casadio, Marco and Kessler, Colin and Monahan, Rosemary and Komendantskaya, Ekaterina},\n  keywords = {Machine Learning (cs.LG), Logic in Computer Science (cs.LO), FOS: Computer and information sciences, FOS: Computer and information sciences},\n  title = {A General Framework for Property-Driven Machine Learning},\n  publisher = {arXiv},\n  year = {2025},\n  copyright = {Creative Commons Attribution 4.0 International}\n}\n\n
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\n \n\n \n \n \n \n \n \n A self-reference approach to synthetic aperture digital holographic microscopy.\n \n \n \n \n\n\n \n Tang, Z.; and Hennelly, B. M.\n\n\n \n\n\n\n In Falldorf, C.; Soldovieri, F.; Bianco, V.; and Picart, P., editor(s), Multimodal Sensing and Artificial Intelligence for Sustainable Future, pages 29, August 2025. SPIE\n \n\n\n\n
\n\n\n\n \n \n \"APaper\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 
@inproceedings{Tang_2025, title={A self-reference approach to synthetic aperture digital holographic microscopy}, url={http://dx.doi.org/10.1117/12.3066515}, DOI={10.1117/12.3066515}, booktitle={Multimodal Sensing and Artificial Intelligence for Sustainable Future}, publisher={SPIE}, author={Tang, Zhengyuan and Hennelly, Bryan M.}, editor={Falldorf, Claas and Soldovieri, Francesco and Bianco, Vittorio and Picart, Pascal}, year={2025}, month=aug, pages={29} }\n\n
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\n \n\n \n \n \n \n \n \n A Short Survey on Formalising Software Requirements using Large Language Models.\n \n \n \n \n\n\n \n Beg, A.; O'Donoghue, D.; and Monahan, R.\n\n\n \n\n\n\n 2025.\n \n\n\n\n
\n\n\n\n \n \n \"APaper\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 1 download\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
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@misc{https://doi.org/10.48550/arxiv.2506.11874,\n  doi = {10.48550/ARXIV.2506.11874},\n  url = {https://arxiv.org/abs/2506.11874},\n  author = {Beg, Arshad and O'Donoghue, Diarmuid and Monahan, Rosemary},\n  keywords = {Software Engineering (cs.SE), FOS: Computer and information sciences, FOS: Computer and information sciences, D.2.1; D.2.4; D.2.10; F.4.1; F.4.3},\n  title = {A Short Survey on Formalising Software Requirements using Large Language Models},\n  publisher = {arXiv},\n  year = {2025},\n  copyright = {Creative Commons Attribution 4.0 International}\n}\n\n
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\n \n\n \n \n \n \n \n Adventures in FRET and Specification.\n \n \n \n\n\n \n Farrell, M.; Luckcuck, M.; Monahan, R.; Reynolds, C.; and Sheridan, O.\n\n\n \n\n\n\n In Margaria, T.; and Steffen, B., editor(s), Leveraging Applications of Formal Methods, Verification and Validation. Specification and Verification, pages 106–123, Cham, 2025. Springer Nature Switzerland\n \n\n\n\n
\n\n\n\n \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
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@InProceedings{10.1007/978-3-031-75380-0_7,\nauthor="Farrell, Marie\nand Luckcuck, Matt\nand Monahan, Rosemary\nand Reynolds, Conor\nand Sheridan, Ois{\\'i}n",\neditor="Margaria, Tiziana\nand Steffen, Bernhard",\ntitle="Adventures in FRET and Specification",\nbooktitle="Leveraging Applications of Formal Methods, Verification and Validation. Specification and Verification",\nyear="2025",\npublisher="Springer Nature Switzerland",\naddress="Cham",\npages="106--123",\nabstract="This paper gives an overview of previous work in which the authors used NASA's Formal Requirement Elicitation Tool (FRET) to formalise requirements. We discuss four case studies where we used FRET to capture the system's requirements. These formalised requirements subsequently guided the case study specifications in a combination of formal paradigms. For each case study we summarise insights gained during this process, exploring the expressiveness and the potential interoperability of these approaches.  Our experience confirms FRET's suitability as a framework for the elicitation and understanding of requirements and for providing traceability from requirements to specification.",\nisbn="978-3-031-75380-0"\n}\n\n\n\n\n
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\n This paper gives an overview of previous work in which the authors used NASA's Formal Requirement Elicitation Tool (FRET) to formalise requirements. We discuss four case studies where we used FRET to capture the system's requirements. These formalised requirements subsequently guided the case study specifications in a combination of formal paradigms. For each case study we summarise insights gained during this process, exploring the expressiveness and the potential interoperability of these approaches.  Our experience confirms FRET's suitability as a framework for the elicitation and understanding of requirements and for providing traceability from requirements to specification.\n
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\n \n\n \n \n \n \n \n \n An efficient method to simulate wildfire propagation using irregular grids.\n \n \n \n \n\n\n \n Hackett, C.; de Andrade Moral, R.; Misra, G.; McCarthy, T.; and Markham, C.\n\n\n \n\n\n\n Natural Hazards and Earth System Sciences, 25(8): 2909–2928. August 2025.\n \n\n\n\n
\n\n\n\n \n \n \"AnPaper\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 
@article{Hackett_2025, title={An efficient method to simulate wildfire propagation using irregular grids}, volume={25}, ISSN={1684-9981}, url={http://dx.doi.org/10.5194/nhess-25-2909-2025}, DOI={10.5194/nhess-25-2909-2025}, number={8}, journal={Natural Hazards and Earth System Sciences}, publisher={Copernicus GmbH}, author={Hackett, Conor and de Andrade Moral, Rafael and Misra, Gourav and McCarthy, Tim and Markham, Charles}, year={2025}, month=aug, pages={2909–2928} }\n\n
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\n \n\n \n \n \n \n \n \n Asset price movement prediction using empirical mode decomposition and Gaussian mixture models.\n \n \n \n \n\n\n \n Palma, G. R.; Skoczeń, M.; and Maguire, P.\n\n\n \n\n\n\n 2025.\n \n\n\n\n
\n\n\n\n \n \n \"AssetPaper\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
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@misc{https://doi.org/10.48550/arxiv.2503.20678,\n  doi = {10.48550/ARXIV.2503.20678},\n  url = {https://arxiv.org/abs/2503.20678},\n  author = {Palma, Gabriel R. and Skoczeń, Mariusz and Maguire, Phil},\n  keywords = {Methodology (stat.ME), Machine Learning (cs.LG), FOS: Computer and information sciences, FOS: Computer and information sciences},\n  title = {Asset price movement prediction using empirical mode decomposition and Gaussian mixture models},\n  publisher = {arXiv},\n  year = {2025},\n  copyright = {Creative Commons Attribution 4.0 International}\n}\n\n
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\n \n\n \n \n \n \n \n \n Comparing differentiable logics for learning with logical constraints.\n \n \n \n \n\n\n \n Flinkow, T.; Pearlmutter, B. A.; and Monahan, R.\n\n\n \n\n\n\n Science of Computer Programming, 244: 103280. September 2025.\n \n\n\n\n
\n\n\n\n \n \n \"ComparingPaper\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 
@article{Flinkow_2025, title={Comparing differentiable logics for learning with logical constraints}, volume={244}, ISSN={0167-6423}, url={http://dx.doi.org/10.1016/j.scico.2025.103280}, DOI={10.1016/j.scico.2025.103280}, journal={Science of Computer Programming}, publisher={Elsevier BV}, author={Flinkow, Thomas and Pearlmutter, Barak A. and Monahan, Rosemary}, year={2025}, month=sep, pages={103280} }\n\n
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\n \n\n \n \n \n \n \n \n Forecasting insect abundance using time series embedding and machine learning.\n \n \n \n \n\n\n \n Palma, G. R.; Mello, R. F.; Godoy, W. A.; Engel, E.; Lau, D.; Markham, C.; and Moral, R. A.\n\n\n \n\n\n\n Ecological Informatics, 85: 102934. March 2025.\n \n\n\n\n
\n\n\n\n \n \n \"ForecastingPaper\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 
@article{Palma_2025, title={Forecasting insect abundance using time series embedding and machine learning}, volume={85}, ISSN={1574-9541}, url={http://dx.doi.org/10.1016/j.ecoinf.2024.102934}, DOI={10.1016/j.ecoinf.2024.102934}, journal={Ecological Informatics}, publisher={Elsevier BV}, author={Palma, Gabriel R. and Mello, Rodrigo F. and Godoy, Wesley A.C. and Engel, Eduardo and Lau, Douglas and Markham, Charles and Moral, Rafael A.}, year={2025}, month=mar, pages={102934} }\n\n
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\n \n\n \n \n \n \n \n \n Implementation of global soil databases in the Noah-MP model and the effects on simulated mean and extreme soil hydrothermal changes.\n \n \n \n \n\n\n \n Ishola, K. A.; Mills, G.; Sati, A. P.; Obe, B.; Demuzere, M.; Upreti, D.; Misra, G.; Lewis, P.; Walsh, D.; McCarthy, T.; and Fealy, R.\n\n\n \n\n\n\n Hydrology and Earth System Sciences, 29(12): 2551–2582. June 2025.\n \n\n\n\n
\n\n\n\n \n \n \"ImplementationPaper\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 
@article{Ishola_2025, title={Implementation of global soil databases in the Noah-MP model and the effects on simulated mean and extreme soil hydrothermal changes}, volume={29}, ISSN={1607-7938}, url={http://dx.doi.org/10.5194/hess-29-2551-2025}, DOI={10.5194/hess-29-2551-2025}, number={12}, journal={Hydrology and Earth System Sciences}, publisher={Copernicus GmbH}, author={Ishola, Kazeem Abiodun and Mills, Gerald and Sati, Ankur Prabhat and Obe, Benjamin and Demuzere, Matthias and Upreti, Deepak and Misra, Gourav and Lewis, Paul and Walsh, Daire and McCarthy, Tim and Fealy, Rowan}, year={2025}, month=jun, pages={2551–2582} }\n\n
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\n \n\n \n \n \n \n \n \n Informing implementation of Nature-based Solutions in marine and coastal environments: the MaCoBioS Blue NBS Toolbox.\n \n \n \n \n\n\n \n Casal, G.; Fonseca, C.; Allegri, E.; Bianconi, A.; Boyd, E.; Cornet, C. C.; de Juan, S.; Espinoza Córdova, F.; Furlan, E.; Gil, A.; Krause, T.; Maréchal, J.; McCarthy, T.; Özkiper, O.; Pérez, G.; Pham, H. V.; Roberts, C.; Simide, R.; Simeoni, C.; Taylor, D.; Tiengo, R.; Trégarot, E.; Uchôa, J.; and O’Leary, B.\n\n\n \n\n\n\n One Ecosystem, 10. April 2025.\n \n\n\n\n
\n\n\n\n \n \n \"InformingPaper\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
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@article{Casal_2025, title={Informing implementation of Nature-based Solutions in marine and coastal environments: the MaCoBioS Blue NBS Toolbox}, volume={10}, ISSN={2367-8194}, url={http://dx.doi.org/10.3897/oneeco.10.e149010}, DOI={10.3897/oneeco.10.e149010}, journal={One Ecosystem}, publisher={Pensoft Publishers}, author={Casal, Gema and Fonseca, Catarina and Allegri, Elena and Bianconi, Angelica and Boyd, Emily and Cornet, Cindy C. and de Juan, Silvia and Espinoza Córdova, Fabiola and Furlan, Elisa and Gil, Artur and Krause, Torsten and Maréchal, Jean-Philippe and McCarthy, Tim and Özkiper, Ozan and Pérez, Géraldine and Pham, Hung Voung and Roberts, Callum and Simide, Rémy and Simeoni, Christian and Taylor, Daisy and Tiengo, Rafaela and Trégarot, Ewan and Uchôa, Jéssica and O’Leary, Bethan}, year={2025}, month=apr }\n\n
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\n \n\n \n \n \n \n \n \n Machine Learning and Device’s Neighborhood-Enabled Fusion Algorithm for the Internet of Things.\n \n \n \n \n\n\n \n Al-Rasheed, A.; Alsaedi, T.; Khan, R.; Rathore, B.; Dhiman, G.; Kundi, M.; and Ahmad, A.\n\n\n \n\n\n\n IEEE Transactions on Consumer Electronics, 71(1): 467–475. February 2025.\n \n\n\n\n
\n\n\n\n \n \n \"MachinePaper\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 
@article{Al_Rasheed_2025, title={Machine Learning and Device’s Neighborhood-Enabled Fusion Algorithm for the Internet of Things}, volume={71}, ISSN={1558-4127}, url={http://dx.doi.org/10.1109/tce.2024.3500024}, DOI={10.1109/tce.2024.3500024}, number={1}, journal={IEEE Transactions on Consumer Electronics}, publisher={Institute of Electrical and Electronics Engineers (IEEE)}, author={Al-Rasheed, Amal and Alsaedi, Tahani and Khan, Rahim and Rathore, Bharati and Dhiman, Gaurav and Kundi, Mahwish and Ahmad, Aftab}, year={2025}, month=feb, pages={467–475} }\n\n
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\n \n\n \n \n \n \n \n \n Modelling Implicit Bias in Gender–Career Associations: A systematic comparison of language models.\n \n \n \n \n\n\n \n Porshnev, A.; Lynott, D.; Wingfield, C.; Kiy, K. D.; O’Donoghue, D.; and Singh, M.\n\n\n \n\n\n\n . May 2025.\n \n\n\n\n
\n\n\n\n \n \n \"ModellingPaper\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 
@article{Porshnev_2025, title={Modelling Implicit Bias in Gender–Career Associations: A systematic comparison of language models}, url={http://dx.doi.org/10.31234/osf.io/p7hvw_v1}, DOI={10.31234/osf.io/p7hvw_v1}, publisher={Center for Open Science}, author={Porshnev, Alexander and Lynott, Dermot and Wingfield, Cai and Kiy, Kevin D. and O’Donoghue, Diarmuid and Singh, Manokamna}, year={2025}, month=may }\n\n
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\n \n\n \n \n \n \n \n \n Modelling Implicit Bias in Gender–Career Associations: A systematic comparison of language models.\n \n \n \n \n\n\n \n Porshnev, A.; Lynott, D.; Wingfield, C.; Kiy, K. D.; O’Donoghue, D.; and Singh, M.\n\n\n \n\n\n\n . May 2025.\n \n\n\n\n
\n\n\n\n \n \n \"ModellingPaper\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 
@article{Porshnev_2025, title={Modelling Implicit Bias in Gender–Career Associations: A systematic comparison of language models}, url={http://dx.doi.org/10.31234/osf.io/p7hvw_v2}, DOI={10.31234/osf.io/p7hvw_v2}, publisher={Center for Open Science}, author={Porshnev, Alexander and Lynott, Dermot and Wingfield, Cai and Kiy, Kevin D. and O’Donoghue, Diarmuid and Singh, Manokamna}, year={2025}, month=may }\n\n
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\n \n\n \n \n \n \n \n \n Refining Environmental Requirements for Autonomous Driving Systems: Leveraging the FRAV Framework.\n \n \n \n \n\n\n \n Kundi, M.; Ahmad, F.; and Monahan, R.\n\n\n \n\n\n\n In 2025 55th Annual IEEE/IFIP International Conference on Dependable Systems and Networks Workshops (DSN-W), pages 15–22, June 2025. IEEE\n \n\n\n\n
\n\n\n\n \n \n \"RefiningPaper\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 
@inproceedings{Kundi_2025, title={Refining Environmental Requirements for Autonomous Driving Systems: Leveraging the FRAV Framework}, url={http://dx.doi.org/10.1109/dsn-w65791.2025.00033}, DOI={10.1109/dsn-w65791.2025.00033}, booktitle={2025 55th Annual IEEE/IFIP International Conference on Dependable Systems and Networks Workshops (DSN-W)}, publisher={IEEE}, author={Kundi, Mahwish and Ahmad, Faraz and Monahan, Rosemary}, year={2025}, month=jun, pages={15–22} }\n\n
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\n \n\n \n \n \n \n \n Sharper Specs for Smarter Drones: Formalising Requirements with FRET.\n \n \n \n\n\n \n Sheridan, O.; Becker, L. B.; Farrell, M.; Luckcuck, M.; and Monahan, R.\n\n\n \n\n\n\n In Hess, A.; and Susi, A., editor(s), Requirements Engineering: Foundation for Software Quality, pages 350–362, Cham, 2025. Springer Nature Switzerland\n \n\n\n\n
\n\n\n\n \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
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@InProceedings{10.1007/978-3-031-88531-0_25,\nauthor="Sheridan, Ois{\\'i}n\nand Becker, Leandro Buss\nand Farrell, Marie\nand Luckcuck, Matt\nand Monahan, Rosemary",\neditor="Hess, Anne\nand Susi, Angelo",\ntitle="Sharper Specs for Smarter Drones: Formalising Requirements with FRET",\nbooktitle="Requirements Engineering: Foundation for Software Quality",\nyear="2025",\npublisher="Springer Nature Switzerland",\naddress="Cham",\npages="350--362",\nabstract="[Context and motivation] Software requirements are commonly expressed in natural-language, which must be formalised if they are to be used by formal methods such as Runtime Verification (RV), where we verify that an implementation obeys its requirements during execution. [Question/problem] This paper reports on our experience of using the Formal Requirements Elicitation Tool (FRET) to formalise requirements for an autonomous tilt-rotor drone in the ProVANT Emergentia research project. Structured, formalised requirements help to refine the meaning of, and discover ambiguities in, a requirements set, which is beneficial for safety-critical systems. FRET generates a temporal logic semantics for each requirement, providing formulas that can be used for RV. [Principal ideas/results] We describe the process of formalising the natural-language requirements using FRET. We present the progress made in each of the four versions of the requirements set as new information was elicited and incorporated. Our two concrete outputs are the formalised requirement set, which we will use in our ongoing development and verification of ProVANT; and metrics about the requirements. [Contribution] From our experience, we present guidance for requirements elicitation and formalisation with FRET. We highlight situations where it was difficult to formalise these requirements and describe potential improvements to FRET to address these difficulties.",\nisbn="978-3-031-88531-0"\n}\n\n\n
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\n [Context and motivation] Software requirements are commonly expressed in natural-language, which must be formalised if they are to be used by formal methods such as Runtime Verification (RV), where we verify that an implementation obeys its requirements during execution. [Question/problem] This paper reports on our experience of using the Formal Requirements Elicitation Tool (FRET) to formalise requirements for an autonomous tilt-rotor drone in the ProVANT Emergentia research project. Structured, formalised requirements help to refine the meaning of, and discover ambiguities in, a requirements set, which is beneficial for safety-critical systems. FRET generates a temporal logic semantics for each requirement, providing formulas that can be used for RV. [Principal ideas/results] We describe the process of formalising the natural-language requirements using FRET. We present the progress made in each of the four versions of the requirements set as new information was elicited and incorporated. Our two concrete outputs are the formalised requirement set, which we will use in our ongoing development and verification of ProVANT; and metrics about the requirements. [Contribution] From our experience, we present guidance for requirements elicitation and formalisation with FRET. We highlight situations where it was difficult to formalise these requirements and describe potential improvements to FRET to address these difficulties.\n
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\n \n\n \n \n \n \n \n \n Towards species' classification of the Anastrepha pseudoparallela group.\n \n \n \n \n\n\n \n Palma, G. R.; Alaiz, R.; Araújo, A. S.; Savaris, M.; Zucchi, R. A.; Markham, C.; and Moral, R. A.\n\n\n \n\n\n\n 2025.\n \n\n\n\n
\n\n\n\n \n \n \"TowardsPaper\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
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@misc{https://doi.org/10.48550/arxiv.2503.08598,\n  doi = {10.48550/ARXIV.2503.08598},\n  url = {https://arxiv.org/abs/2503.08598},\n  author = {Palma, Gabriel R. and Alaiz, Rocío and Araújo, Alexandre S. and Savaris, Marcoandre and Zucchi, Roberto A. and Markham, Charles and Moral, Rafael A.},\n  keywords = {Quantitative Methods (q-bio.QM), FOS: Biological sciences, FOS: Biological sciences},\n  title = {Towards species' classification of the \\textit{Anastrepha pseudoparallela} group},\n  publisher = {arXiv},\n  year = {2025},\n  copyright = {Creative Commons Attribution 4.0 International}\n}\n\n
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\n  \n 2024\n \n \n (16)\n \n \n
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\n \n\n \n \n \n \n \n \n Reinforcement Learning and Sequential QAP-Based Graph Matching for Semantic Segmentation of Images.\n \n \n \n \n\n\n \n Chopin, J.; Fasquel, J.; Mouchere, H.; Dahyot, R.; and Bloch, I.\n\n\n \n\n\n\n Emerging Topics in Pattern Recognition and Artificial Intelligence, pages 259-294. World Scientific, 2024.\n \n\n\n\n
\n\n\n\n \n \n \"EmergingPaper\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
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@inbook{doi:10.1142/9789811289125_0011,\nauthor = {Jeremy   Chopin  and  Jean-Baptiste   Fasquel  and  Harold   Mouchere  and  Rozenn   Dahyot  and  Isabelle   Bloch },\nchapter = {Reinforcement Learning and Sequential QAP-Based Graph Matching for Semantic Segmentation of Images},\ntitle = {Emerging Topics in Pattern Recognition and Artificial Intelligence},\npublisher = {World Scientific},\npages = {259-294},\nyear ={2024},\ndoi = {10.1142/9789811289125_0011},\nURL = {https://www.worldscientific.com/doi/abs/10.1142/9789811289125_0011},\neprint = {https://www.worldscientific.com/doi/pdf/10.1142/9789811289125_0011},\nabstract = { This chapter addresses the fundamental task of semantic image analysis by exploiting structural information (spatial relationships between image regions). \nWe propose to combine a deep neural network (DNN) with graph matching (formulated as a quadratic assignment problem (QAP)) where graphs encode efficiently structural information\n related to regions segmented by the DNN. Our novel approach solves the QAP sequentially for matching graphs, in the context of image semantic segmentation, \n where the optimal sequence for graph matching is conveniently defined using reinforcement learning (RL) based on the region membership probabilities\n  produced by the DNN and their structural relationships. Our RL-based strategy for solving QAP sequentially allows us to significantly reduce the combinatorial complexity\n   for graph matching. Two experiments are performed on two public datasets dedicated respectively to the semantic segmentation of face images and sub-cortical region of the brain. \n   Results show that the proposed RL-based ordering performs better than using a random ordering, especially when using DNNs that have been trained on a limited number of samples. \n   The open-source code and data are shared with the community. }\n}\n\n\n
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\n This chapter addresses the fundamental task of semantic image analysis by exploiting structural information (spatial relationships between image regions). We propose to combine a deep neural network (DNN) with graph matching (formulated as a quadratic assignment problem (QAP)) where graphs encode efficiently structural information related to regions segmented by the DNN. Our novel approach solves the QAP sequentially for matching graphs, in the context of image semantic segmentation, where the optimal sequence for graph matching is conveniently defined using reinforcement learning (RL) based on the region membership probabilities produced by the DNN and their structural relationships. Our RL-based strategy for solving QAP sequentially allows us to significantly reduce the combinatorial complexity for graph matching. Two experiments are performed on two public datasets dedicated respectively to the semantic segmentation of face images and sub-cortical region of the brain. Results show that the proposed RL-based ordering performs better than using a random ordering, especially when using DNNs that have been trained on a limited number of samples. The open-source code and data are shared with the community. \n
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\n \n\n \n \n \n \n \n Towards Correct-by-Construction Machine-Learnt Models.\n \n \n \n\n\n \n Flinkow, T.; Pearlmutter, B. A.; and Monahan, R.\n\n\n \n\n\n\n In Proceedings of the PhD Symposium at the 19th International Conference on Integrated Formal Methods in Manchester 2024 (iFM 2024), Manchester, United Kingdom, November 12, 2024, volume 3860, of CEUR Workshop Proceedings, pages 23–29, 2024. CEUR-WS.org\n \n\n\n\n
\n\n\n\n \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
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@inproceedings{flinkowCorrectbyConstructionMachineLearntModels2024,\n  title = {Towards {{Correct-by-Construction Machine-Learnt Models}}},\n  booktitle = {Proceedings of the {{PhD Symposium}} at the 19th {{International Conference}} on Integrated {{Formal Methods}} in {{Manchester}} 2024 ({{iFM}} 2024), {{Manchester}}, {{United Kingdom}}, {{November}} 12, 2024},\n  author = {Flinkow, Thomas and Pearlmutter, Barak A. and Monahan, Rosemary},\n  year = 2024,\n  series = {{{CEUR Workshop Proceedings}}},\n  volume = {3860},\n  pages = {23--29},\n  publisher = {CEUR-WS.org},\n  urldate = {2024-12-13}\n}\n\n \n\n
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\n \n\n \n \n \n \n \n \n DNA nanotechnology for cell-free DNA marker for tumor detection: a comprehensive overview.\n \n \n \n \n\n\n \n Soliman, S. S.; Abd El-Samie, F. E.; Abd El-atty, S. M.; Badawy, W.; and Eshra, A.\n\n\n \n\n\n\n Nucleosides, Nucleotides & Nucleic Acids, 44(4): 276–290. October 2024.\n \n\n\n\n
\n\n\n\n \n \n \"DNAPaper\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 
@article{Soliman_2024, title={DNA nanotechnology for cell-free DNA marker for tumor detection: a comprehensive overview}, volume={44}, ISSN={1532-2335}, url={http://dx.doi.org/10.1080/15257770.2024.2337853}, DOI={10.1080/15257770.2024.2337853}, number={4}, journal={Nucleosides, Nucleotides &amp; Nucleic Acids}, publisher={Informa UK Limited}, author={Soliman, Sara Sami and Abd El-Samie, Fathi E. and Abd El-atty, Saied M. and Badawy, Wael and Eshra, Abeer}, year={2024}, month=oct, pages={276–290} }\n\n
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\n \n\n \n \n \n \n \n \n Modelling note’s pitch and duration in trained professional singers.\n \n \n \n \n\n\n \n Faghih, B.; Shoari Nejad, A.; and Timoney, J.\n\n\n \n\n\n\n EURASIP Journal on Audio, Speech, and Music Processing, 2024(1). November 2024.\n \n\n\n\n
\n\n\n\n \n \n \"ModellingPaper\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 
@article{Faghih_2024, title={Modelling note’s pitch and duration in trained professional singers}, volume={2024}, ISSN={1687-4722}, url={http://dx.doi.org/10.1186/s13636-024-00380-4}, DOI={10.1186/s13636-024-00380-4}, number={1}, journal={EURASIP Journal on Audio, Speech, and Music Processing}, publisher={Springer Science and Business Media LLC}, author={Faghih, Behnam and Shoari Nejad, Amin and Timoney, Joseph}, year={2024}, month=nov }\n\n
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\n \n\n \n \n \n \n \n \n Optical diffraction tomography using a self-reference module.\n \n \n \n \n\n\n \n Tang, Z.; Winnik, J.; and Hennelly, B. M.\n\n\n \n\n\n\n Biomedical Optics Express, 16(1): 57. December 2024.\n \n\n\n\n
\n\n\n\n \n \n \"OpticalPaper\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
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@article{Tang_2024, title={Optical diffraction tomography using a self-reference module}, volume={16}, ISSN={2156-7085}, url={http://dx.doi.org/10.1364/boe.545296}, DOI={10.1364/boe.545296}, number={1}, journal={Biomedical Optics Express}, publisher={Optica Publishing Group}, author={Tang, Zhengyuan and Winnik, Julianna and Hennelly, Bryan M.}, year={2024}, month=dec, pages={57} }\n\n
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\n \n\n \n \n \n \n \n \n Performance of Gaussian Mixture Model Classifiers on Embedded Feature Spaces.\n \n \n \n \n\n\n \n Chopin, J.; and Dahyot, R.\n\n\n \n\n\n\n 2024.\n \n\n\n\n
\n\n\n\n \n \n \"PerformancePaper\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
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@misc{https://doi.org/10.48550/arxiv.2410.13421,\n  doi = {10.48550/ARXIV.2410.13421},\n  url = {https://arxiv.org/abs/2410.13421},\n  author = {Chopin, Jeremy and Dahyot, Rozenn},\n  keywords = {Computer Vision and Pattern Recognition (cs.CV), FOS: Computer and information sciences, FOS: Computer and information sciences},\n  title = {Performance of Gaussian Mixture Model Classifiers on Embedded Feature Spaces},\n  publisher = {arXiv},\n  year = {2024},\n  copyright = {Creative Commons Attribution 4.0 International}\n}\n\n
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\n \n\n \n \n \n \n \n \n A dataset of domestic environment room adjacency scene graphs.\n \n \n \n \n\n\n \n Gallagher, F.; Gallagher, L.; Cognetti, M.; and McDonald, J. B.\n\n\n \n\n\n\n IET Conference Proceedings, 2024(10): 335–338. October 2024.\n \n\n\n\n
\n\n\n\n \n \n \"APaper\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 
@article{Gallagher_2024, title={A dataset of domestic environment room adjacency scene               graphs}, volume={2024}, ISSN={2732-4494}, url={http://dx.doi.org/10.1049/icp.2024.3327}, DOI={10.1049/icp.2024.3327}, number={10}, journal={IET Conference Proceedings}, publisher={Institution of Engineering and Technology (IET)}, author={Gallagher, Frank and Gallagher, Louis and Cognetti, Marco and McDonald, John B.}, year={2024}, month=oct, pages={335–338} }\n\n
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\n \n\n \n \n \n \n \n \n A Method to Identify Wildfire Ignition Points and Propagation Durations Using Genetic Algorithms.\n \n \n \n \n\n\n \n Hackett, C.; Moral, R. d. A.; and Markham, C.\n\n\n \n\n\n\n . October 2024.\n \n\n\n\n
\n\n\n\n \n \n \"APaper\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
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@article{Hackett_2024, title={A Method to Identify Wildfire Ignition Points and Propagation Durations Using Genetic Algorithms}, url={http://dx.doi.org/10.21203/rs.3.rs-5099486/v1}, DOI={10.21203/rs.3.rs-5099486/v1}, publisher={Springer Science and Business Media LLC}, author={Hackett, Conor and Moral, Rafael de Andrade and Markham, Charles}, year={2024}, month=oct }\n\n
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\n \n\n \n \n \n \n \n \n A Validation of OLCI Sentinel-3 Water Products in the Baltic Sea and an Evaluation of the Effect of System Vicarious Calibration (SVC) on the Level-2 Water Products.\n \n \n \n \n\n\n \n O’Kane, S.; McCarthy, T.; Fealy, R.; and Kratzer, S.\n\n\n \n\n\n\n Remote Sensing, 16(21): 3932. October 2024.\n \n\n\n\n
\n\n\n\n \n \n \"APaper\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 
@article{O_Kane_2024, title={A Validation of OLCI Sentinel-3 Water Products in the Baltic Sea and an Evaluation of the Effect of System Vicarious Calibration (SVC) on the Level-2 Water Products}, volume={16}, ISSN={2072-4292}, url={http://dx.doi.org/10.3390/rs16213932}, DOI={10.3390/rs16213932}, number={21}, journal={Remote Sensing}, publisher={MDPI AG}, author={O’Kane, Sean and McCarthy, Tim and Fealy, Rowan and Kratzer, Susanne}, year={2024}, month=oct, pages={3932} }\n\n
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\n \n\n \n \n \n \n \n \n Aerial image based localisation via learned embeddings.\n \n \n \n \n\n\n \n Avila H., E. A.; Magee, A.; McCarthy, T.; and McDonald, J.\n\n\n \n\n\n\n IET Conference Proceedings, 2024(10): 291–298. October 2024.\n \n\n\n\n
\n\n\n\n \n \n \"AerialPaper\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
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@article{Avila_H__2024, title={Aerial image based localisation via learned embeddings}, volume={2024}, ISSN={2732-4494}, url={http://dx.doi.org/10.1049/icp.2024.3317}, DOI={10.1049/icp.2024.3317}, number={10}, journal={IET Conference Proceedings}, publisher={Institution of Engineering and Technology (IET)}, author={Avila H., Eduardo A. and Magee, Aidan and McCarthy, Tim and McDonald, John}, year={2024}, month=oct, pages={291–298} }\n\n
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\n \n\n \n \n \n \n \n \n An exploration of the connection between COVID-19 and cardiovascular disease (CVD) in European countries.\n \n \n \n \n\n\n \n Pourshir Sefidi, N.; and Mooney, P.\n\n\n \n\n\n\n Journal of Public Health. November 2024.\n \n\n\n\n
\n\n\n\n \n \n \"AnPaper\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
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@article{Pourshir_Sefidi_2024, title={An exploration of the connection between COVID-19 and cardiovascular disease (CVD) in European countries}, ISSN={1613-2238}, url={http://dx.doi.org/10.1007/s10389-024-02372-2}, DOI={10.1007/s10389-024-02372-2}, journal={Journal of Public Health}, publisher={Springer Science and Business Media LLC}, author={Pourshir Sefidi, Niloufar and Mooney, Peter}, year={2024}, month=nov }\n\n
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\n \n\n \n \n \n \n \n \n Automatic Differentiation: Inverse Accumulation Mode.\n \n \n \n \n\n\n \n Pearlmutter, B. A.; and Siskind, J. M.\n\n\n \n\n\n\n 2024.\n \n\n\n\n
\n\n\n\n \n \n \"AutomaticPaper\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
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@misc{https://doi.org/10.48550/arxiv.2411.18786,\n  doi = {10.48550/ARXIV.2411.18786},\n  url = {https://arxiv.org/abs/2411.18786},\n  author = {Pearlmutter, Barak A. and Siskind, Jeffrey Mark},\n  keywords = {Numerical Analysis (math.NA), FOS: Mathematics, FOS: Mathematics},\n  title = {Automatic Differentiation: Inverse Accumulation Mode},\n  publisher = {arXiv},\n  year = {2024},\n  copyright = {arXiv.org perpetual, non-exclusive license}\n}\n\n
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\n \n\n \n \n \n \n \n \n Creating a Formally Verified Neural Network for Autonomous Navigation: An Experience Report.\n \n \n \n \n\n\n \n Bukhari, S. A. A.; Flinkow, T.; Inkarbekov, M.; Pearlmutter, B. A.; and Monahan, R.\n\n\n \n\n\n\n Electronic Proceedings in Theoretical Computer Science, 411: 178–190. November 2024.\n \n\n\n\n
\n\n\n\n \n \n \"CreatingPaper\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
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@article{Bukhari_2024, title={Creating a Formally Verified Neural Network for Autonomous Navigation: An Experience Report}, volume={411}, ISSN={2075-2180}, url={http://dx.doi.org/10.4204/eptcs.411.12}, DOI={10.4204/eptcs.411.12}, journal={Electronic Proceedings in Theoretical Computer Science}, publisher={Open Publishing Association}, author={Bukhari, Syed Ali Asadullah and Flinkow, Thomas and Inkarbekov, Medet and Pearlmutter, Barak A. and Monahan, Rosemary}, year={2024}, month=nov, pages={178–190} }\n\n
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\n \n\n \n \n \n \n \n \n Effects of Pandemic Response Measures on Crime Counts in English and Welsh Local Authorities.\n \n \n \n \n\n\n \n Pourshir Sefidi, N.; Shoari Nejad, A.; and Mooney, P.\n\n\n \n\n\n\n Applied Spatial Analysis and Policy, 18(1). November 2024.\n \n\n\n\n
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@article{Pourshir_Sefidi_2024, title={Effects of Pandemic Response Measures on Crime Counts in English and Welsh Local Authorities}, volume={18}, ISSN={1874-4621}, url={http://dx.doi.org/10.1007/s12061-024-09614-6}, DOI={10.1007/s12061-024-09614-6}, number={1}, journal={Applied Spatial Analysis and Policy}, publisher={Springer Science and Business Media LLC}, author={Pourshir Sefidi, Niloufar and Shoari Nejad, Amin and Mooney, Peter}, year={2024}, month=nov }\n\n \n
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\n \n\n \n \n \n \n \n \n THE ENHANCEMENT OF THE COMPUTER SCIENCE CENTRE WITH A FOCUS ON STUDENT SUPPORT AND MOTIVATION.\n \n \n \n \n\n\n \n Boyle, H.; Mooney, A.; and Noone, M.\n\n\n \n\n\n\n In ICERI2024 Proceedings, volume 1, of ICERI2024, pages 1769–1774, November 2024. IATED\n \n\n\n\n
\n\n\n\n \n \n \"THEPaper\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
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@inproceedings{Boyle_2024, series={ICERI2024}, title={THE ENHANCEMENT OF THE COMPUTER SCIENCE CENTRE WITH A FOCUS ON STUDENT SUPPORT AND MOTIVATION}, volume={1}, ISSN={2340-1095}, url={http://dx.doi.org/10.21125/iceri.2024.0515}, DOI={10.21125/iceri.2024.0515}, booktitle={ICERI2024 Proceedings}, publisher={IATED}, author={Boyle, Hope and Mooney, Aidan and Noone, Mark}, year={2024}, month=nov, pages={1769–1774}, collection={ICERI2024} }\n\n
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\n \n\n \n \n \n \n \n \n The experience of stigma and concealment in multiple sclerosis.\n \n \n \n \n\n\n \n Maguire, R.; Ahern, A.; Shrivastava, S.; and Maguire, P.\n\n\n \n\n\n\n Stigma and Health. December 2024.\n \n\n\n\n
\n\n\n\n \n \n \"ThePaper\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
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@article{Maguire_2024, title={The experience of stigma and concealment in multiple sclerosis.}, ISSN={2376-6972}, url={http://dx.doi.org/10.1037/sah0000599}, DOI={10.1037/sah0000599}, journal={Stigma and Health}, publisher={American Psychological Association (APA)}, author={Maguire, Rebecca and Ahern, Aisling and Shrivastava, Sowmya and Maguire, Phil}, year={2024}, month=dec }\n\n
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