We present two strategies for detecting patterns and clusters in high-dimensional timedependent functional data. The use on wavelet-based similarity measures, since wavelets are well suited for identifying highly discriminant local time and scale features. The multiresolution aspect of the wavelet transform provides a time-scale decomposition of the signals allowing to visualize and to cluster ...

High resolution multidimensional image data yield huge datasets. For compression and analysis, 2D approaches are often used, neglecting the information coherence in higher dimensions, which can be exploited for improved compression. We designed a wavelet compression algorithm suited for data of arbitrary dimensions, and assessed its ability for compression of 4D medical images. Basically, separ...

Electricity is considered a new commodity, mainly since the start of the electricity markets liberalization. However it represents an increasingly important sector of trading and as such a challenging area of research. Here we focus on the role of electricity power exchanges for the creation of a single European electricity market, on a di¤erent empirical perspective. We use daily power exchang...

We examine possible links between solar cycle irradiance variations the large atmospheric circulation systems that affect whole planet’s climate. In particular we examine the putative mechanism of solar forcing mediated by changes in induced stratospheric conditions over the polar regions. We test this hypothesis by examining causal links between time series of solar irradiance based on both am...

This study attempts to empirically estimate the interdependence between COVID-19, tourism market, oil prices, and sustainable climate in United States. In doing so, we employ an advanced Morlet’s wavelet approach, namely, Wavelet coherence transform (WCT), Partial Multiple Coherence found a strong co-movement variables, which is varied across time scales, indicating initial, peak, after peak ef...

A novel speckle reduction technique based on soft thresholding of wavelet coefficients using interval type II fuzzy system was developed for reducing speckle noise in Optical Coherence Tomography images. The proposed algorithm is an extension of a recently published method for filtering additive Gaussian noise by use of type I fuzzy system. Unlike type I, interval type II fuzzy based thresholdi...

Monitoring pilot's mental states is a relevant approach to mitigate human error and enhance human machine interaction. A promising brain imaging technique to perform such a continuous measure of human mental state under ecological settings is Functional Near-InfraRed Spectroscopy (fNIRS). However, to our knowledge no study has yet assessed the potential of fNIRS connectivity metrics as long as ...

Precipitation and temperature are important drivers of soil respiration. The role of moisture and temperature are generally explored at seasonal or inter-annual timescales; however, significant variability also occurs on hourly to daily time-scales. We used small (1.54 m(2)), throughfall exclusion shelters to evaluate the role soil moisture and temperature as temporal controls on soil CO2 efflu...

This paper proposes new enhancement models to the methods of nonlinear anisotropic diffusion to greatly reduce speckle and preserve image features in medical ultrasound images. By incorporating local physical characteristics of the image, in this case scatterer density, in addition to the gradient, into existing tensorbased image diffusion methods, we were able to greatly improve the performanc...