Edge computing plays a crucial role in the advancement of Beyond 5G (B5G) and 6G networks. The substantial growth in network traffic and computational requirements necessitates the implementation of multi-access edge ...
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This paper proposes a novel multi-scale fusion network based on fuzzy region enlargement and shrinking (SVFNet) for camouflaged object detection (COD) tasks. Camouflaged objects are highly similar to their backgrounds...
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Brain-computer interfaces (BCIs) represent an alternative channel of communication between the user and the external environment, circumventing the need for traditional neural pathways. The capability to modulate one&...
ISBN:
(纸本)9798350358513;9798350358520
Brain-computer interfaces (BCIs) represent an alternative channel of communication between the user and the external environment, circumventing the need for traditional neural pathways. The capability to modulate one's own electroencephalogram (electroencephalography (EEG)) signal holds the potential to facilitate specific movements in external devices, thereby restoring or enhancing certain abilities that may have been compromised. In this study, we propose two potential configurations for a four-class, closed loop, real-time Motor Imagery (MI) brain-computer interface (BCI), with the objective of assessing the viability of these endogenous BCIs in accurately directing a cursor on the screen. Twelve healthy participants and one individual with motor disability participated in the experiment, with nine of them successfully transitioning from one-dimensional to two-dimensional cursor control. This outcome suggests that proficient control is achievable with sufficient training time.
Cyberbullying and online harassment present significant challenges to digital safety, demanding robust detection systems capable of identifying abusive content across multiple formats. This work proposes a multi-modal...
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Model-driven methods are increasingly being adopted in many industrial sectors to support the design and development of software intensive systems. Many available model-based system engineering methods support progres...
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ISBN:
(纸本)9783031663383;9783031663390
Model-driven methods are increasingly being adopted in many industrial sectors to support the design and development of software intensive systems. Many available model-based system engineering methods support progressive levels of functional decomposition, enabling to reason at different levels of granularity. In contrast, requirements modelling tends to stay quite monolithic in nature despite the ability to provide different forms of refinement and traceability. This work analyses how to better structure requirements across multiple levels in the scope of goal-oriented requirements engineering to provide better support for decomposition and analysis of inner subcomponents or the outer system of systems. We introduce the explicit notion of system and show how to integrate it in the widely used KAOS and i* frameworks. Our extension is prototyped on available tools and validated on two complementary case studies of a meeting scheduler and a smart city.
At the intersection of personality psychology, computerscience, and linguistics, more and more researchers are paying attention to personality detection based on content analysis of texts on social media. However, ex...
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Aiming at the existing multi-exposure image fusion method based on weight function, the fused image obtained tends to introduce halo artifacts, loss of details, unclear edges and other problems. A multi-exposure image...
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In recent years, the rapid development of Electric Vehicles has been used worldwide to sustain the environment and to reduce dependency on fuel. These cars have batteries which can last up to 10-20 years. With the eno...
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This paper addresses the need for automatic pain recognition in healthcare without relying on expert feature extraction from physiological signals. Instead, it introduces a deep learning approach that combines classif...
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The attention mechanism can extract task-relevant vital information while suppressing less important information, playing an increasingly critical role in deep feature representation for semantic segmentation. This re...
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