How does the mind process linguistic and non-linguistic sounds? The current study assessed the different ways that spoken words (e.g., "dog") and characteristic sounds (e.g.,
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http://dx.doi.org/10.1177/1747021820923944 | DOI Listing |
Neural Netw
January 2025
State Key Laboratory of Public Big Data, Guizhou University, 550025, China; Engineering Research Center of Text Computing & Cognitive Intelligence, Ministry of Education, Guizhou University, 550025, China; College of Computer Science and Technology, Guizhou University, 550025, China. Electronic address:
Relation extraction independently verifies all entity pairs in a sentence to identify predefined relationships between named entities. Because these entity pairs share the same contextual features of a sentence, they lead to a complicated semantic structure. To distinguish semantic expressions between relation instances, manually designed rules or elaborate deep architectures are usually applied to learn task-relevant representations.
View Article and Find Full Text PDFSensors (Basel)
January 2025
Faculty of Applied Sciences, Macao Polytechnic University, Macao SAR 999078, China.
Visible-infrared person re-identification (VI-ReID) is a challenging cross-modality retrieval task to match a person across different spectral camera views. Most existing works focus on learning shared feature representations from the final embedding space of advanced networks to alleviate modality differences between visible and infrared images. However, exclusively relying on high-level semantic information from the network's final layers can restrict shared feature representations and overlook the benefits of low-level details.
View Article and Find Full Text PDFHealthcare (Basel)
December 2024
Centre for Digital Transformation, School of Computing and Information Technology, University of Wollongong, Wollongong, NSW 2522, Australia.
Background: Traditional methods for analysing surgical processes often fall short in capturing the intricate interconnectedness between clinical procedures, their execution sequences, and associated resources such as hospital infrastructure, staff, and protocols.
Aim: This study addresses this gap by developing an ontology for appendicectomy, a computational model that comprehensively represents appendicectomy processes and their resource dependencies to support informed decision making and optimise appendicectomy healthcare delivery.
Methods: The ontology was developed using the NeON methodology, drawing knowledge from existing ontologies, scholarly literature, and de-identified patient data from local hospitals.
Sci Data
January 2025
Jozef Stefan Institute, Ljubljana, 1000, Slovenia.
Due to growing population and technological advances, global electricity consumption is increasing. Although CO emissions are projected to plateau or slightly decrease by 2025 due to the adoption of clean energy sources, they are still not decreasing enough to mitigate climate change. The residential sector makes up 25% of global electricity consumption and has potential to improve efficiency and reduce CO footprint without sacrificing comfort.
View Article and Find Full Text PDFComput Med Imaging Graph
January 2025
The Department of Computer and Data Science, Case Western Reserve University, Cleveland, OH, USA; The Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA.
A generic and versatile CT Image Reconstruction (CTIR) scheme can efficiently mitigate imaging noise resulting from inherent physical limitations, substantially bolstering the dependability of CT imaging diagnostics across a wider spectrum of patient cases. Current CTIR techniques often concentrate on distinct areas such as Low-Dose CT denoising (LDCTD), Sparse-View CT reconstruction (SVCTR), and Metal Artifact Reduction (MAR). Nevertheless, due to the intricate nature of multi-scenario CTIR, these techniques frequently narrow their focus to specific tasks, resulting in limited generalization capabilities for diverse scenarios.
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