Outputs (1084)

Using the learning by developing action model: case study in project-based computer science studies in higher education institutions. (2023)
Thesis
LINTILÄ, T. 2023. Using the learning by developing action model: case study in project-based computer science studies in higher education institutions. Robert Gordon University, PhD thesis. Hosted on OpenAIR [online]. Available from: https://doi.org/10.48526/rgu-wt-2271442

Teaching methods change continuously. In the last 30 years, there has been a shift from traditional teacher-centred teaching to student-centred learning, which focuses on developing students' competence and skills, and enables lifelong learning and t... Read More about Using the learning by developing action model: case study in project-based computer science studies in higher education institutions..

Seismic events extraction method based on the B-COSFIRE filter combined with the differential evolution algorithm. (2023)
Journal Article
ZHAO, J., LI, Y., LEI, H., REN, J., ZHANG, F. and SHEN, H. 2023. Seismic events extraction method based on the B-COSFIRE filter combined with the differential evolution algorithm. ACTA geophysica [online], Early Access. Available from: https://doi.org/10.1007/s11600-023-01222-1

Based on an analysis of the information processing mechanism in the primary visual cortex of biological vision, this study proposes an integration method of bar-combination of shifted filter responses (B-COSFIRE) filter with the differential evolutio... Read More about Seismic events extraction method based on the B-COSFIRE filter combined with the differential evolution algorithm..

Immersive innovations for the communication of heritage, handcraft and sustainability. (2023)
Journal Article
CROSS, K., MESJAR, L., STEED, J. and JIANG, Y. [2023]. Immersive innovations for the communication of heritage, handcraft and sustainability. International journal of fashion design, technology and education [online], Latest Articles. Available from: https://doi.org/10.1080/17543266.2023.2277264

Textile and fashion brands convey core values through marketing, and in slow-fashion heritage brands this often includes skilled craftsmanship, authenticity, sustainability and provenance. As industry digitalisation continues, brands are employing im... Read More about Immersive innovations for the communication of heritage, handcraft and sustainability..

Automatic geolocation and measuring of offshore energy infrastructure with multimodal satellite data. (2023)
Journal Article
MA, P., MACDONALD, M., ROUSE, S. and REN, J. 2023. Automatic geolocation and measuring of offshore energy infrastructure with multimodal satellite data. IEEE journal of oceanic engineering [online], Early Access. Available from: https://doi.org/10.1109/joe.2023.3319741

With the increasing trend of energy transition to low-carbon economies, the rate of offshore structure installation and removal will rapidly accelerate through offshore renewable energy development and oil and gas decommissioning. Knowledge of the lo... Read More about Automatic geolocation and measuring of offshore energy infrastructure with multimodal satellite data..

PWDformer: deformable transformer for long-term series forecasting. (2023)
Journal Article
WANG, Z., RAN, H., REN, J. and SUN, M. 2024. PWDformer: deformable transformer for long-term series forecasting. Pattern recognition [online], 147, article number 110118. Available from: https://doi.org/10.1016/j.patcog.2023.110118

Long-term forecasting is of paramount importance in numerous scenarios, including predicting future energy, water, and food consumption. For instance, extreme weather events and natural disasters can profoundly impact infrastructure operations and po... Read More about PWDformer: deformable transformer for long-term series forecasting..

Comparison of simulated annealing and evolution strategies for optimising cyclical rosters with uneven demand and flexible trainee placement. (2023)
Conference Proceeding
COLLINS, J., ZĂVOIANU, A.-C. and MCCALL, J.A.W. 2023. Comparison of simulated annealing and evolution strategies for optimising cyclical rosters with uneven demand and flexible trainee placement. In Bramer, M. and Stahl, F. (eds.) Artificial intelligence XL: proceedings of the 43rd SGAI (Specialist Group on Artificial Intelligence) Artificial intelligence international conference 2023 (AI-2023), 12-14 December 2023, Cambridge, UK. Lecture notes in computer science, 14381. Cham: Springer [online], pages 451-464. Available from: https://doi.org/10.1007/978-3-031-47994-6_39

Rosters are often used for real-world staff scheduling requirements. Multiple design factors such as demand variability, shift type placement, annual leave requirements, staff well-being and the placement of trainees need to be considered when constr... Read More about Comparison of simulated annealing and evolution strategies for optimising cyclical rosters with uneven demand and flexible trainee placement..

Clinical dialogue transcription error correction with self-supervision. (2023)
Conference Proceeding
NANAYAKKARA, G., WIRATUNGA, N., CORSAR, D., MARTIN, K. and WIJEKOON, A. 2023. Clinical dialogue transcription error correction with self-supervision. In Bramer, M. and Stahl, F. (eds.) Artificial intelligence XL: proceedings of the 43rd SGAI international conference on artificial intelligence (AI-2023), 12-14 December 2023, Cambridge, UK. Lecture notes in computer science, 14381. Cham: Springer [online], pages 33-46. Available from: https://doi.org/10.1007/978-3-031-47994-6_3

A clinical dialogue is a conversation between a clinician and a patient to share medical information, which is critical in clinical decision-making. The reliance on manual note-taking is highly inefficient and leads to transcription errors when digit... Read More about Clinical dialogue transcription error correction with self-supervision..

Explaining a staff rostering problem by mining trajectory variance structures. (2023)
Conference Proceeding
FYVIE, M., MCCALL, J.A.W., CHRISTIE, L.A., ZĂVOIANU, A.-C., BROWNLEE, A.E.I. and AINSLIE, R. 2023. Explaining a staff rostering problem by mining trajectory variance structures. In Bramer, M. and Stahl, F. (eds.) Artificial intelligence XL: proceedings of the 43rd SGAI international conference on artificial intelligence (AI-2023), 12-14 December 2023, Cambridge, UK. Lecture notes in computer science, 14381. Cham: Springer [online], pages 275-290. Available from: https://doi.org/10.1007/978-3-031-47994-6_27

The use of Artificial Intelligence-driven solutions in domains involving end-user interaction and cooperation has been continually growing. This has also lead to an increasing need to communicate crucial information to end-users about algorithm behav... Read More about Explaining a staff rostering problem by mining trajectory variance structures..

Object-aware multi-criteria decision-making approach using the heuristic data-driven theory for intelligent transportation systems. (2023)
Conference Proceeding
MEKALA, M.S., EYAD, E. and SRIVASTAVA, G. 2023. Object-aware multi-criteria decision-making approach using the heuristic data-driven theory for intelligent transportation systems. In Proceedings of the 10th IEEE (Institute of Electrical and Electronics Engineers) Data science and advanced analytics international conference 2023 (DSAA 2023), 9-13 October 2023, Thessaloniki, Greece. Piscataway: IEEE [online], 10302554. Available from: https://doi.org/10.1109/DSAA60987.2023.10302554

Sharing up-to-date information about the surrounding measured by On-Board Units (OBUs) and Roadside Units (RSUs) is crucial in accomplishing traffic efficiency and pedestrians safety towards Intelligent Transportation Systems (ITS). Transferring meas... Read More about Object-aware multi-criteria decision-making approach using the heuristic data-driven theory for intelligent transportation systems..

Siamese residual neural network for musical shape evaluation in piano performance assessment. (2023)
Conference Proceeding
LI, X., WEISS, S., YAN, Y., LI, Y., REN, J., SORAGHAN, J. and GONG, M. 2023. Siamese residual neural network for musical shape evaluation in piano performance assessment. In Proceedings of the 31st European signal processing conference 2023 (EUSIPCO 2023), 4-8 September 2023, Helsinki, Finland. Piscataway: IEEE [online], pages 216-220. Available from: https://doi.org/10.23919/EUSIPCO58844.2023.10289901

Understanding and identifying musical shape plays an important role in music education and performance assessment. To simplify the otherwise time- and cost-intensive musical shape evaluation, in this paper we explore how artificial intelligence (AI)... Read More about Siamese residual neural network for musical shape evaluation in piano performance assessment..