Traffic flow prediction plays an important role in managing urban transportation systems, helping to reduce congestion and improve road safety. Although existing deep learning models improve their predictive accuracy with complex architectures, they ... read more
A rapid proliferation of industrial internet of things (IIoT) systems has increased the vulnerability of interconnected devices for sophisticated cyberattacks, which necessitates intelligent and privacy-preserving solution for security. This paper pr... read more
We present a Wilson-Cowan reservoir computer (WC-RC) that treats a retinotopic excitatory-inhibitory neural field as a structured reservoir. Travelling waves and bounded oscillations provide an interpretable spatiotemporal basis, while a two-stage sa... read more
The case of mental health disorders has been a main topic in the clinical and psychological field. The advancement of computing studies, especially in Natural Language Processing (NLP)-a subset of Machine Learning, created a system of detection that ... read more
Transition-metal nanoclusters exhibit structural and electronic properties that depend on their size, often making them superior to bulk materials for heterogeneous catalysis. However, their performance can be limited by sulfur poisoning. Here, we us... read more
Early-stage infrared forest fire detection is severely hindered by strong background thermal interference and extremely weak fire radiation signals. Existing methods mainly rely on spatial-domain modeling and overlook the frequency-domain characteris... read more
Fault detection in Digital Logic Circuits is an important problem in Very Large Scale Integration (VLSI) testing especially in case of growing circuit complexity and various fault characteristics. Traditional methods tend to have a problem in the abi... read more
Molecular subtyping is essential for guiding systemic therapy in breast cancer but currently requires invasive biopsy. Conventional B-mode ultrasound offers rich anatomical information, yet lacks the functional dynamics needed to capture the comprehe... read more
Explainable artificial intelligence (XAI) is increasingly required for anomaly detection in high-dimensional sensor systems operating in safety-critical and resource-constrained environments. While existing post-hoc explanation methods provide useful... read more
This study represents the systematic examination of full lifecycle management for radiology artificial intelligence medical (AI) devices approved by the US Food and Drug Administration (FDA), with an in-depth analysis of post-market adverse events, r... read more
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