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Development and Evaluation of Adaptive Learning Support System Based on Ontology of Multiple Programming Languages (2025)
Journal Article
Na Nongkhai, L., Wang, J., & Mendori, T. (2025). Development and Evaluation of Adaptive Learning Support System Based on Ontology of Multiple Programming Languages. Education Sciences, 15(6), Article 724

This paper introduces an ontology-based approach within an adaptive learning support system for computer programming. This system is designed to deliver personalized programming exercises that are tailored to individual learners’ skill levels. This p... Read More about Development and Evaluation of Adaptive Learning Support System Based on Ontology of Multiple Programming Languages.

Geometric Visual Fusion Graph Neural Networks for Multi-Person Human-Object Interaction Recognition in Videos (2025)
Journal Article
Qiao, T., Li, R., Li, F. W. B., Kubotani, Y., Morishima, S., & Shum, H. P. H. (2025). Geometric Visual Fusion Graph Neural Networks for Multi-Person Human-Object Interaction Recognition in Videos. Expert Systems with Applications, 290, Article 128344. https://doi.org/10.1016/j.eswa.2025.128344

Human-Object Interaction (HOI) recognition in videos requires understanding both visual patterns and geometric relationships as they evolve over time. Visual and geometric features offer complementary strengths. Visual features capture appearance con... Read More about Geometric Visual Fusion Graph Neural Networks for Multi-Person Human-Object Interaction Recognition in Videos.

Talking Face Generation with Lip and Identity Priors (2025)
Journal Article
Wu, J., Li, F. W. B., Tam, G. K. L., Yang, B., Nan, F., & Pan, J. (2025). Talking Face Generation with Lip and Identity Priors. Computer Animation and Virtual Worlds, 36(3), Article e70026. https://doi.org/10.1002/cav.70026

Speech-driven talking face video generation has attracted growing interest in recent research. While person-specific approaches yield high-fidelity results, they require extensive training data from each individual speaker. In contrast, general-purpo... Read More about Talking Face Generation with Lip and Identity Priors.

CLN: A multi-task deep neural network for chest X-ray image localisation and classification (2025)
Journal Article
Okolo, G. I., Katsigiannis, S., & Ramzan, N. (2025). CLN: A multi-task deep neural network for chest X-ray image localisation and classification. Expert Systems with Applications, 288, Article 128162. https://doi.org/10.1016/j.eswa.2025.128162

Chest X-ray (CXR) imaging is a widely used and cost-effective medical imaging technique for detecting various pathologies. However, accurate interpretation of CXR images is a challenging and time-consuming task that requires expert radiologists. Alth... Read More about CLN: A multi-task deep neural network for chest X-ray image localisation and classification.

SPECTRA: A Markovian Framework for Managing NFR Tradeoffs in Systems with Mixed Observability (2025)
Journal Article
Ignatius, H. T. N., Bahsoon, R., Bencomo, N., & Samin, H. (online). SPECTRA: A Markovian Framework for Managing NFR Tradeoffs in Systems with Mixed Observability. ACM Transactions on Autonomous and Adaptive Systems, https://doi.org/10.1145/3735643

Non-Functional Requirements (NFRs) play a critical role in driving self-adaptation in software systems. In Self-Adaptive Systems (SAS), satisfying multiple NFRs simultaneously introduces significant complexity, as these requirements often conflict-im... Read More about SPECTRA: A Markovian Framework for Managing NFR Tradeoffs in Systems with Mixed Observability.

Acyclic, star and injective colouring: A complexity picture for H-free graphs (2025)
Journal Article
Bok, J., Jedličková, N., Martin, B., Ochem, P., Paulusma, D., & Smith, S. (2025). Acyclic, star and injective colouring: A complexity picture for H-free graphs. Journal of Computer and System Sciences, 154, Article 103662. https://doi.org/10.1016/j.jcss.2025.103662

A (proper) colouring is acyclic, star, or injective if any two colour classes induce a forest, star forest or disjoint union of vertices and edges, respectively. The corresponding decision problems are Acyclic Colouring, Star Colouring and Injective... Read More about Acyclic, star and injective colouring: A complexity picture for H-free graphs.

Comparing width parameters on graph classes (2025)
Journal Article
Brettell, N., Munaro, A., Paulusma, D., & Yang, S. (2025). Comparing width parameters on graph classes. European Journal of Combinatorics, 127, Article 104163. https://doi.org/10.1016/j.ejc.2025.104163

We study how the relationship between non-equivalent width parameters changes once we restrict to some special graph class. As width parameters we consider treewidth, clique-width, twin-width, mim-width, sim-width and tree-independence number, wherea... Read More about Comparing width parameters on graph classes.

A study on the impact of different components of a traditional webcam-based 2D gaze tracking algorithm (2025)
Journal Article
Blakey, W., Katsigiannis, S., & Ramzan, N. (online). A study on the impact of different components of a traditional webcam-based 2D gaze tracking algorithm. IEEE Sensors Journal, https://doi.org/10.1109/JSEN.2025.3564397

Webcam-based 2D gaze tracking algorithms are lightweight and are becoming increasingly used in the fields of medicine, market research and many others. As they become increasingly used, it becomes vital to break down their components to understand th... Read More about A study on the impact of different components of a traditional webcam-based 2D gaze tracking algorithm.

T-STAR: Time-Optimal Swarm Trajectory Planning for Quadrotor Unmanned Aerial Vehicles (2025)
Journal Article
Pan, H., Zahmatkesh, M., Rekabi-Bana, F., Arvin, F., & Hu, J. (online). T-STAR: Time-Optimal Swarm Trajectory Planning for Quadrotor Unmanned Aerial Vehicles. IEEE Transactions on Intelligent Transportation Systems, https://doi.org/10.1109/TITS.2025.3557783

This paper introduces a time-optimal swarm tra-jectory planner for cooperative unmanned aerial vehicle (UAV) systems, designed to generate collision-free trajectories for flocking control in cluttered environments. To achieve this goal, model predict... Read More about T-STAR: Time-Optimal Swarm Trajectory Planning for Quadrotor Unmanned Aerial Vehicles.

FMDConv: Fast multi-attention dynamic convolution via speed-accuracy trade-off (2025)
Journal Article
Zhang, T., Wan, F., Duan, H., Tong, K. W., Deng, J., & Long, Y. (2025). FMDConv: Fast multi-attention dynamic convolution via speed-accuracy trade-off. Knowledge-Based Systems, 317, Article 113393. https://doi.org/10.1016/j.knosys.2025.113393

Spatial convolution is fundamental in constructing deep Convolutional Neural Networks (CNNs) for visual recognition. While dynamic convolution enhances model accuracy by adaptively combining static kernels, it incurs significant computational overhe... Read More about FMDConv: Fast multi-attention dynamic convolution via speed-accuracy trade-off.

Towards empathic medical conversation in Narrative Medicine: A visualization approach based on intelligence augmentation (2025)
Journal Article
Ma, H., Law, E. L.-C., Sun, X., Yang, W., He, X., Lawson, G., Zheng, H., Wang, Q., Li, Q., & Yuan, X. (2025). Towards empathic medical conversation in Narrative Medicine: A visualization approach based on intelligence augmentation. International Journal of Human-Computer Studies, 199, Article 103506. https://doi.org/10.1016/j.ijhcs.2025.103506

Empathic medical conversation is central to patient-centered care within Narrative Medicine. However, difficulties, such as physicians’ limited empathic capabilities and lack of time, impede the practice. Research on real-time, on-site empathic medic... Read More about Towards empathic medical conversation in Narrative Medicine: A visualization approach based on intelligence augmentation.

Model‐Driven Engineering for Digital Twins: Opportunities and Challenges (2025)
Journal Article
Michael, J., Cleophas, L., Zschaler, S., Clark, T., Combemale, B., Godfrey, T., Khelladi, D. E., Kulkarni, V., Lehner, D., Rumpe, B., Wimmer, M., Wortmann, A., Ali, S., Barn, B., Barosan, I., Bencomo, N., Bordeleau, F., Grossmann, G., Karsai, G., Kopp, O., …Vangheluwe, H. (online). Model‐Driven Engineering for Digital Twins: Opportunities and Challenges. Systems Engineering, https://doi.org/10.1002/sys.21815

Digital twins are increasingly used across a wide range of industries. Modeling is a key to digital twin development—both when considering the models which a digital twin maintains of its real‐world complement (“models in digital twin”) and when cons... Read More about Model‐Driven Engineering for Digital Twins: Opportunities and Challenges.

BP-SGCN: Behavioral Pseudo-Label Informed Sparse Graph Convolution Network for Pedestrian and Heterogeneous Trajectory Prediction (2025)
Journal Article
Li, R., Katsigiannis, S., Kim, T.-K., & Shum, H. P. H. (online). BP-SGCN: Behavioral Pseudo-Label Informed Sparse Graph Convolution Network for Pedestrian and Heterogeneous Trajectory Prediction. IEEE Transactions on Neural Networks and Learning Systems, https://doi.org/10.1109/TNNLS.2025.3545268

Trajectory prediction allows better decision-making in applications of autonomous vehicles (AVs) or surveillance by predicting the short-term future movement of traffic agents. It is classified into pedestrian or heterogeneous trajectory prediction.... Read More about BP-SGCN: Behavioral Pseudo-Label Informed Sparse Graph Convolution Network for Pedestrian and Heterogeneous Trajectory Prediction.

Reconfigurable routing in data center networks (2025)
Journal Article
Stewart, I., & Kutner, D. (2025). Reconfigurable routing in data center networks. Theoretical Computer Science, 1038, Article 115154. https://doi.org/10.1016/j.tcs.2025.115154

A hybrid network is a static (electronic) network that is augmented with optical switches. The Reconfigurable Routing Problem (RRP) in hybrid networks is the problem of finding settings for the optical switches augmenting a static network so as to ac... Read More about Reconfigurable routing in data center networks.

Fg-T2M++: LLMs-Augmented Fine-Grained Text Driven Human Motion Generation (2025)
Journal Article
Wang, Y., Li, M., Liu, J., Leng, Z., Li, F. W. B., Zhang, Z., & Liang, X. (online). Fg-T2M++: LLMs-Augmented Fine-Grained Text Driven Human Motion Generation. International Journal of Computer Vision, https://doi.org/10.1007/s11263-025-02392-9

We address the challenging problem of fine-grained text-driven human motion generation. Existing works generate imprecise motions that fail to accurately capture relationships specified in text due to: (1) lack of effective text parsing for detailed... Read More about Fg-T2M++: LLMs-Augmented Fine-Grained Text Driven Human Motion Generation.

HotReRAM: A Performance-Power-Thermal Simulation Framework for ReRAM based Caches (2025)
Journal Article
Chakraborty, S., Bunnam, T., Arunruerk, J., Agarwal, S., Yu, S., Shafik, R., & Sjalander, M. (online). HotReRAM: A Performance-Power-Thermal Simulation Framework for ReRAM based Caches. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, https://doi.org/10.1109/TCAD.2025.3546855

This paper proposes a comprehensive thermal modeling and simulation framework, HotReRAM, for resistive RAM (ReRAM)-based caches that is verified against a memristor circuit-level model. The simulation is driven by power traces based on cache accesses... Read More about HotReRAM: A Performance-Power-Thermal Simulation Framework for ReRAM based Caches.