Expiratory and inspiratory cries detection using different signals' decomposition techniques

This paper addresses the problem of automatic cry signal segmentation for the purposes of infant cry analysis. The main goal is to automatically detect expiratory and inspiratory phases from recorded cry signals. The approach used in this paper is made up of three stages: signal decomposition, features extraction, and classification. In the first stage, short-time Fourier transform, empirical mode decomposition (EMD), and wavelet packet transform have been considered. In the second stage, various set of features have been extracted, and in the third stage, two supervised learning methods, Gaussian mixture models and hidden Markov models, with four and five states, have been discussed as well. The main goal of this work is to investigate the EMD performance and to compare it with the other standard decomposition techniques. A combination of two and three intrinsic mode functions (IMFs) that resulted from EMD has been used to represent cry signal. The performance of nine different segmentation systems has been evaluated. The experiments for each system have been repeated several times with different training and testing datasets, randomly chosen using a 10-fold cross-validation procedure. The lowest global classification error rates of around 8.9% and 11.06% have been achieved using a Gaussian mixture models classifier and a hidden Markov models classifier, respectively. Among all IMF combinations, the winner combination is IMF3+IMF4+IMF5

Haar wavelet-based adaptive finite volume shallow water solver

This paper presents the formulation of an adaptive finite volume (FV) model for the shallow water equations. A Godunov-type reformulation combining the Haar wavelet is achieved to enable solutiondriven resolution adaptivity (both coarsening and refinement) by depending on the wavelet’s threshold value. The ability to properly model irregular topographies and wetting/drying are transferred from the (baseline) FV uniform mesh model, with no extra notable efforts. Selected hydraulic tests are employed to analyse the performance of the Haar wavelet FV shallow water solver considering adaptivity and practical issues including choice for the threshold value driving the adaptivity, mesh convergence study, shock and wet/dry front capturing abilities. Our findings show that Haar wavelet-based adaptive FV solutions offer great potential to improve the reliability of multiscale shallow water models

BMQ

BMQ: Boston Medical Quarterly was published from 1950-1966 by the Boston University School of Medicine and the Massachusetts Memorial Hospitals

The Nature of Educational Adventure Programming: Linking Education to Adventure in Xwander Nordic

This thesis explores the delivery of education in adventure programming, focused in the context of adventure provider Xwander Nordic, based in Ivalo, Finland. The project is commissioned by Xwander Nordic and aims to aid in the development of educational adventure products and to address the desire to market existing adventure products as adventure education. The main goals of this project are to understand the difference between adventure and adventure education, create a theoretical foundation for delivering adventure education, analyze Xwander Nordic's current and potential ability to provide adventure education, and define what is needed to promote their products as educational experiences. This work reviews a vast collection of education theory across multiple disciplines, exploring behavioral and cognitive psychology, social constructivism, experiential learning, and transfer theory. Five common principles are uncovered: practice, feedback, reflection, goal setting, and planning for transfer. These principles inform the research into Xwander Nordic. The conducted research involves interviews with adventure guides and the head of Xwander Nordic and an analysis of Xwander Nordic's current ativities listed on their website. Findings reveal that Xwander Nordic already provides educational experiences in their available products. The nature of adventure itself fulfills the principle of practice through active voluntary participation. Guides demonstrate enthusiasm for education and teaching, incorporating educational practice in their activities to facilitate skill development in customer groups. Feedback is frequently provided, particularly for beginner level participants. While guides express understanding of reflection, it was discovered that this principle was mainly used as a personal tool. More knowledge and practice is needed to be able to expand adventure products into adventure education. Goal setting and planning for transfer are particularly important to include in future deveopment, as this ensures that learning can be taken forward and applied to every day scenarios outside of adventure settings. Although this thesis is conducted through the lens of Xwander Nordic, the theory and findings offer valuable insight for all education and adventure providers interested in expanding their services into the realm of adventure education

Nonlinear Statistical Analysis of Normal and Pathological Infant Cry Signals in Cepstrum Domain by Multifractal Wavelet Leaders

Multifractal behavior in the cepstrum representation of healthy and unhealthy infant cry signals is examined by means of wavelet leaders and compared using the Student t-test. The empirical results show that both expiration and inspiration signals exhibit clear evidence of multifractal properties under healthy and unhealthy conditions. In addition, expiration and inspiration signals exhibit more complexity under healthy conditions than under unhealthy conditions. Furthermore, distributions of multifractal characteristics are different across healthy and unhealthy conditions. Hence, this study improves the understanding of infant crying by providing a complete description of its intrinsic dynamics to better evaluate its health status