Search results for " electronic engineering"
showing 10 items of 8284 documents
Wooden panel paintings investigation: An air-coupled ultrasonic imaging approach
2007
In this paper, a method for the study of wooden panel paintings using air-coupled acoustical imaging is presented. In order to evaluate the advantages of the technique, several samples were made to mimic panel paintings along with their typical defects. These specimens were tested by means of both single-sided and through-transmission techniques using planar transducers. Image data were processed by means of a two-dimensional (2-D)-fast Fourier transform-based algorithm to increase the S/N ratio and 2-D representations (C-scans) were generated. The simulated defects were imaged using both configurations. Investigations were undertaken on four antique paintings from a private collection. The…
Semantic structures of timbre emerging from social and acoustic descriptions of music
2011
The perceptual attributes of timbre have inspired a considerable amount of multidisciplinary research, but because of the complexity of the phenomena, the approach has traditionally been confined to laboratory conditions, much to the detriment of its ecological validity. In this study, we present a purely bottom-up approach for mapping the concepts that emerge from sound qualities. A social media ( http://www.last.fm ) is used to obtain a wide sample of verbal descriptions of music (in the form of tags) that go beyond the commonly studied concept of genre, and from this the underlying semantic structure of this sample is extracted. The structure that is thereby obtained is then evaluated th…
Combining gestures and vocalizations to imitate sounds
2015
International audience; Communicating about sounds is a difficult task without a technical language, and naïve speakers often rely on different kinds of non-linguistic vocalizations and body gestures (Lemaitre et al. 2014). Previous work has independently studied how effectively people describe sounds with gestures or vocalizations (Caramiaux, 2014, Lemaitre and Rocchesso, 2014). However, speech communication studies suggest a more intimate link between the two processes (Kendon, 2004). Our study thus focused on the combination of manual gestures and non-speech vocalizations in the communication of sounds. We first collected a large database of vocal and gestural imitations of a variety of …
Archetypal analysis: an alternative to clustering for unsupervised texture segmentation
2019
Texture segmentation is one of the main tasks in image applications, specifically in remote sensing, where the objective is to segment high-resolution images of natural landscapes into different cover types. Often the focus is on the selection of discriminant textural features, and although these are really fundamental, there is another part of the process that is also influential, partitioning different homogeneous textures into groups. A methodology based on archetype analysis (AA) of the local textural measurements is proposed. AA seeks the purest textures in the image and it can find the borders between pure textures, as those regions composed of mixtures of several archetypes. The prop…
Mini-COVIDNet: Efficient Lightweight Deep Neural Network for Ultrasound Based Point-of-Care Detection of COVID-19
2021
Lung ultrasound (US) imaging has the potential to be an effective point-of-care test for detection of COVID-19, due to its ease of operation with minimal personal protection equipment along with easy disinfection. The current state-of-the-art deep learning models for detection of COVID-19 are heavy models that may not be easy to deploy in commonly utilized mobile platforms in point-of-care testing. In this work, we develop a lightweight mobile friendly efficient deep learning model for detection of COVID-19 using lung US images. Three different classes including COVID-19, pneumonia, and healthy were included in this task. The developed network, named as Mini-COVIDNet, was bench-marked with …
Model Predictive Control for Shunt Active Filters With Fixed Switching Frequency
2016
This paper presents a modification to the classical Model Predictive Control algorithm, named Modulated Model Predictive Control, and its application to active power filters. The proposed control is able to retain all the advantages of a Finite Control Set Model Predictive Control whilst improving the generated waveforms harmonic spectrum. In fact a modulation algorithm, based on the cost function ratio for different output vectors, is inherently included in the MPC. The cost function-based modulator is introduced and its effectiveness on reducing the current ripple is demonstrated. The presented solution provides an effective and straightforward single loop controller, maintaining an excel…
Low repetition rate gain-switched double-clad thulium-doped fiber laser operating in the 2 µm wavelength region
2021
Abstract The experimental demonstration of a gain-switched pulsed fiber laser with low repetition rate emission in the 2 µm wavelength region is presented. The laser cavity is based on the figure-9 shape, where the gain-switched operation of the laser is obtained by using a double-clad Tm-doped fiber (DCTDF) as gain medium and a commercial pulsed laser diode at 793-nm with configurable parameters as pump source. The pulse parameters of the pump source are optimized for efficient suppressing of unstable gain-switched laser oscillations. As a result, laser pulses with low repetition rate in a range from 10 to 20 kHz with laser emission at the wavelength of 1951 nm are obtained. The generated …
Remote sensing image segmentation by active queries
2012
Active learning deals with developing methods that select examples that may express data characteristics in a compact way. For remote sensing image segmentation, the selected samples are the most informative pixels in the image so that classifiers trained with reduced active datasets become faster and more robust. Strategies for intelligent sampling have been proposed with model-based heuristics aiming at the search of the most informative pixels to optimize model's performance. Unlike standard methods that concentrate on model optimization, here we propose a method inspired in the cluster assumption that holds in most of the remote sensing data. Starting from a complete hierarchical descri…
Recognition of Falls and Daily Living Activities Using Machine Learning
2018
A robust fall detection system is essential to support the independent living of elderlies. In this context, we develop a machine learning framework for fall detection and daily living activity recognition. Using acceleration data from public databases, we test the performance of two algorithms to classify seven different activities including falls and activities of daily living. We extract new features from the acceleration signal and demonstrate their effect on improving the accuracy and the precision of the classifier. Our analysis reveals that the quadratic support vector machine classifier achieves an overall accuracy of 93.2% and outperforms the artificial neural network algorithm. Re…
Novel solutions for closed-loop Reverse Electrodialysis: thermodynamic characterisation and perspective analysis
2019
Abstract Closed-loop Reverse Electrodialysis is a novel technology to directly convert low-grade heat into electricity. It consists of a reverse electrodialysis (RED) unit where electricity is produced exploiting the salinity gradient between two salt-water solutions, coupled with a regeneration unit where waste-heat is used to treat the solutions exiting from the RED unit and restore their initial composition. One of the most important advantages of closed-loop systems compared to the open systems is the possibility to select ad-hoc salt solutions to achieve high efficiencies. Therefore, the properties of the salt solutions are essential to assess the performance of the energy generation a…