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DMG-GCN: A Dynamic Microstate-Guided Graph Convolutional Network for EEG Cognitive Workload Decoding in Air Traffic Control. [PDF]
Biosensors (Basel)Zhang Y, Shao Q, Yang H, Ren X, Peng X.
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Pretrained Financial Language Model-Guided Multimodal Sensing with Hardware Provenance and Cross-Frequency Temporal Alignment for Event Prediction. [PDF]
Sensors (Basel)Chen S +6 more
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Traffic noise monitoring and modelling — an overview
Environmental Science and Pollution Research, 2022Noise has emerged as a leading environmental problem and is an underestimated threat. The most significant source of noise pollution is road traffic. Road traffic noise problem has reached alarming levels. This proves the severity and necessity of mitigating the traffic noise from every delicate corner possible.
Suman Mann, Gyanendra Singh
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Traffic noise models and noise guidelines: A review
Noise & Vibration Worldwide, 2021Traffic noise is a major cause of noise pollution, and impacts of noise pollution on humans have been studied extensively. Previous studies have helped in the development of traffic noise prediction analysis using robust analytical and computational models, parameters connected with traffic, road characteristics, and environment. This study reviewed 11
Fidelma Ibili +5 more
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A NOISE MODEL FOR URBAN WATER TRAFFIC IN VENICE
IOA 40th Anniversary Conference 2014, 2023Noise is considered among the first causes of urban degradation and the impact on human health and environment quality is huge. Many studies have demonstrated that urban noise exposure may produce a number of direct and indirect effects other than hearing damage. These include interference on communication and sleep disturbance effects.
REMIGI, FRANCESCA, DI BELLA, ANTONINO
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Efficient numerical modeling of traffic noise
The Journal of the Acoustical Society of America, 2010An optimized method is presented for the numerical evaluation of the sound field generated by an incoherent line source, which is commonly used to model road and rail traffic noise. Two different solutions for the numerical integration over the line source are distinguished, a point source solution and a line source solution.
Salomons, E.M., Zhou, H., Lohman, W.J.A.
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Fractals, 1993
One-dimensional traffic flow is simulated by a cellular-automaton-type discrete model. As we increase the car density, the model shows a phase transition between a jam phase and a non-jam phase. By adding random perturbations we found a 1/f power spectrum in the jam phase, whereas a white noise is observed in the non-jam phase.
Misako Takayasu, Hideki Takayasu
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One-dimensional traffic flow is simulated by a cellular-automaton-type discrete model. As we increase the car density, the model shows a phase transition between a jam phase and a non-jam phase. By adding random perturbations we found a 1/f power spectrum in the jam phase, whereas a white noise is observed in the non-jam phase.
Misako Takayasu, Hideki Takayasu
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Modelling traffic noise mathematically
Applied Acoustics, 1975Abstract In this paper we describe a mathematical model for the prediction of traffic noise levels in an urban or suburban situation. The model is ultimately intended to provide an alternative to existing methods of prediction. At the present time, only noise levels produced by stationary sound sources have been considered.
A.D. Clayden, R.W.D. Culley, P.S. Marsh
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