Correlations between thermal environment and egg quality of two layer commercial strains

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Denoising swallowing sound to improve the evaluator's qualitative analysis

Swallowing dynamics involves the coordination and interaction of several muscles and nerves which allow correct food transport from mouth to stomach without laryngotracheal penetration or aspiration. Clinical swallowing assessment depends on the evaluator's knowledge of anatomic structures and of neurophysiological processes involved in swallowing. Any alteration in those steps is denominated oropharyngeal dysphagia, which may have many causes, such as neurological or mechanical disorders. Videofluoroscopy of swallowing is presently considered to be the best exam to objectively assess the dynamics of swallowing, but the exam needs to be conducted under certain restrictions, due to patient's exposure to radiation, which limits periodical repetition for monitoring swallowing therapy. Another method, called cervical auscultation, is a promising new diagnostic tool for the assessment of swallowing disorders. The potential to diagnose dysphagia in a noninvasive manner by assessing the sounds of swallowing is a highly attractive option for the dysphagia clinician. Even so, the captured sound has an amount of noise, which can hamper the evaluator's decision. In that way, the present paper proposes the use of a filter to improve the quality of audible sound and facilitate the perception of examination. The wavelet denoising approach is used to decompose the noisy signal. The signal to noise ratio was evaluated to demonstrate the quantitative results of the proposed methodology. (C) 2007 Elsevier Ltd. All rights reserved.

Remote Sensing Detection of atmospheric pollutants using Lidar, Sodar and correlation with air quality data in an industrial area

Optical remote sensing techniques have obvious advantages for monitoring gas and aerosol emissions, since they enable the operation over large distances, far from hostile environments, and fast processing of the measured signal. In this study two remote sensing devices, namely a Lidar (Light Detection and Ranging) for monitoring the vertical profile of backscattered light intensity, and a Sodar (Acoustic Radar, Sound Detection and Ranging) for monitoring the vertical profile of the wind vector were operated during specific periods. The acquired data were processed and compared with data of air quality obtained from ground level monitoring stations, in order to verify the possibility of using the remote sensing techniques to monitor industrial emissions. The campaigns were carried out in the area of the Environmental Research Center (Cepema) of the University of São Paulo, in the city of Cubatão, Brazil, a large industrial site, where numerous different industries are located, including an oil refinery, a steel plant, as well as fertilizer, cement and chemical/petrochemical plants. The local environmental problems caused by the industrial activities are aggravated by the climate and topography of the site, unfavorable to pollutant dispersion. Results of a campaign are presented for a 24- hour period, showing data of a Lidar, an air quality monitoring station and a Sodar. © 2011 SPIE.

A sound education: Becoming aware of the sound around us

In this article it is intended to discuss the issue of noise pollution from an unusual point of view: noise pollution is not only the result of sound increase worldwide, but, particularly, the poor quality of our listening habits in modern life as well. In contemporary society we are subject to a considerable amount of stimulus to all our senses: vision, scent, taste and hearing which are becoming more and more insensible due to over exposure in our environment. These increased stimuli make us look for alternatives to reduce our ability to perceive them and be protected from injuries. However, our sensitivity will also decrease. In the specific case of environment noise, over exposure has made us forget the enchantment of certain sounds that used to give us pleasure or evoke good feelings by many ways, making us recall certain good things, bringing particular moments of our lives to our memory or even filling us with strong emotion. The Canadian composer and music educator, R. Murray Schafer, believes that noise pollution is the result of a society who became deaf. Closing our ears to noise protect us from noise pollution but also prevent us from grasping subtleties of listening. Contemporary world does not help us to be aware of sound in the space around us; acquiring this hearing ability is a matter of focus, interest and practice. Sound education exercises are aimed at children, teenagers and adults who want to improve their listening ability to environmental sounds, perceive its proprieties and learn how sound affects us and touches our feelings. The results are easy to accomplish and contribute to our awareness of the sound environment around us and to the conception of the environmental sound as a composition made by everybody and everything through positive actions, strong will and high sensitivity. Copyright © (2011) by the International Institute of Acoustics & Vibration.

The assessment of the quality of sugar using electronic tongue and machine learning algorithms

The correct classification of sugar according to its physico-chemical characteristics directly influences the value of the product and its acceptance by the market. This study shows that using an electronic tongue system along with established techniques of supervised learning leads to the correct classification of sugar samples according to their qualities. In this paper, we offer two new real, public and non-encoded sugar datasets whose attributes were automatically collected using an electronic tongue, with and without pH controlling. Moreover, we compare the performance achieved by several established machine learning methods. Our experiments were diligently designed to ensure statistically sound results and they indicate that k-nearest neighbors method outperforms other evaluated classifiers and, hence, it can be used as a good baseline for further comparison. © 2012 IEEE.