Poluição sonora urbana: a influência de modificações em escapamentos de motocicletas na emissão de ruído

A poluição sonora urbana, em especial a gerada por motocicletas com escapamentos modificados, afeta indistintamente a saúde de toda população de diversas maneiras e tende a aumentar, ao contrário da emissão de gases, que vem se reduzindo ao longo dos anos. Com o objetivo de conter o ruído gerado pelo tráfego urbano, vários países desenvolvem procedimentos, leis e ações mitigatórias como barreiras acústicas e asfaltos fonoabsorventes, porém há grande quantidade de motocicletas, veículo tipicamente de alto potencial de incômodo e ruidoso, que circulam com sistemas de escapamento adulterados e emitem ainda mais excesso de ruído. A inspeção veicular é ferramenta importante no controle de emissões de gases poluentes de veículos em uso, mas falha em restringir aqueles que ultrapassam os limites legais de ruído e, somado a isto, há o agravante de o condutor submeter-se a poluição sonora que ele mesmo produz. A fiscalização de rua surge como alternativa de controle ambiental, mas algumas vezes é contestada por ser subjetiva ou por faltar uma metodologia simples, confiável e eficaz. Buscou-se então compreender a relação entre o aumento do nível sonoro da motocicleta com escapamento modificado ao circular no trânsito e a emissão sonora medida na condição de inspeção, o chamado ruído parado, para trazer subsídios à formação de métodos mais eficazes de fiscalização e controle. Para isto foram avaliadas motocicletas quanto à emissão de ruído em circulação e ruído parado e os resultados obtidos apontam que os escapamentos modificados possuem nível sonoro muito mais elevado que os originais, com forte correspondência entre os dois métodos de medição. Esta poluição sonora atinge de modo particularmente intenso os profissionais, motoboys, que modificam suas motocicletas, pois eles se submetem a todos os fatores que favorecem a perda auditiva por excesso de ruído. Outras questões surgiram em paralelo ao tema principal e foram brevemente avaliadas para se compor o quadro geral, como o nível sonoro de escapamentos não originais avaliados segundo os procedimentos de homologação, a contribuição que a motocicleta traz ao ruído urbano e que resultados estes trazem quanto ao torque e potência da motocicleta. Estes estudos indicaram que a motocicleta modificada contribui fortemente para a poluição sonora urbana, afetando principalmente o condutor e sem trazer ganhos efetivos em termos de potência e dirigibilidade.

Estimação de imagens acústicas com arranjos de microfones.

Nas últimas décadas, a poluição sonora tornou-se um grande problema para a sociedade. É por esta razão que a indústria tem aumentado seus esforços para reduzir a emissão de ruído. Para fazer isso, é importante localizar quais partes das fontes sonoras são as que emitem maior energia acústica. Conhecer os pontos de emissão é necessário para ter o controle das mesmas e assim poder reduzir o impacto acústico-ambiental. Técnicas como \"beamforming\" e \"Near-Field Acoustic Holography\" (NAH) permitem a obtenção de imagens acústicas. Essas imagens são obtidas usando um arranjo de microfones localizado a uma distância relativa de uma fonte emissora de ruído. Uma vez adquiridos os dados experimentais pode-se obter a localização e magnitude dos principais pontos de emissão de ruído. Do mesmo modo, ajudam a localizar fontes aeroacústicas e vibro acústicas porque são ferramentas de propósito geral. Usualmente, estes tipos de fontes trabalham em diferentes faixas de frequência de emissão. Recentemente, foi desenvolvida a transformada de Kronecker para arranjos de microfones, a qual fornece uma redução significativa do custo computacional quando aplicada a diversos métodos de reconstrução de imagens, desde que os microfones estejam distribuídos em um arranjo separável. Este trabalho de mestrado propõe realizar medições com sinais reais, usando diversos algoritmos desenvolvidos anteriormente em uma tese de doutorado, quanto à qualidade do resultado obtido e à complexidade computacional, e o desenvolvimento de alternativas para tratamento de dados quando alguns microfones do arranjo apresentarem defeito. Para reduzir o impacto de falhas em microfones e manter a condição de que o arranjo seja separável, foi desenvolvida uma alternativa para utilizar os algoritmos rápidos, eliminando-se apenas os microfones com defeito, de maneira que os resultados finais serão obtidos levando-se em conta todos os microfones do arranjo.

Arranjos de sensores orientados à missão para a geração automática de mapas temáticos em VANTs

O uso de veículos aéreos não tripulados (VANTs) tem se tornado cada vez mais comum, principalmente em aplicações de uso civil. No cenário militar, o uso de VANTs tem focado o cumprimento de missões específicas que podem ser divididas em duas grandes categorias: sensoriamento remoto e transporte de material de emprego militar. Este trabalho se concentra na categoria do sensoriamento remoto. O trabalho foca a definição de um modelo e uma arquitetura de referência para o desenvolvimento de sensores inteligentes orientados a missões específicas. O principal objetivo destas missões é a geração de mapas temáticos. Neste trabalho são investigados processos e mecanismos que possibilitem a geração desta categoria de mapas. Neste sentido, o conceito de MOSA (Mission Oriented Sensor Array) é proposto e modelado. Como estudos de caso dos conceitos apresentados são propostos dois sistemas de mapeamento automático de fontes sonoras, um para o caso civil e outro para o caso militar. Essas fontes podem ter origem no ruído gerado por grandes animais (inclusive humanos), por motores de combustão interna de veículos ou por atividade de artilharia (incluindo caçadores). Os MOSAs modelados para esta aplicação são baseados na integração de dados provenientes de um sensor de imageamento termal e uma rede de sensores acústicos em solo. A integração das informações de posicionamento providas pelos sensores utilizados, em uma base cartográfica única, é um dos aspectos importantes tratados neste trabalho. As principais contribuições do trabalho são a proposta de sistemas MOSA, incluindo conceitos, modelos, arquitetura e a implementação de referência representada pelo sistema de mapeamento automático de fontes sonoras.

Fracking/Takings

As the use of fracking has spread during the recent oil and gas boom, inevitable conflicts have arisen between industry and its neighbors, particularly as fracking has moved into densely populated urban and suburban areas. Concerned over the impacts of fracking – such as risks to health and safely, diminished property values, air and water pollution, as well as noise, traffic, and other annoyances – many people have demanded a government response. Government regulation of fracking has struggled to catch up, although in recent years many state and local governments have taken steps to reduce the impacts of fracking in their communities. This article focuses on government restrictions in New York and Colorado, two of the key battlegrounds in the fight over fracking. New York recently prohibited fracking across the entire state, after several towns had enacted their own bans. In Colorado, the people have used the ballot initiative process to enact restrictions on fracking directly. The industry has responded not only with public relations spending to improve the fracking’s damaged reputation, but also legal challenges to these efforts to rein in oil and gas development. In addition to suing local governments, often arguing they do not have authority to regulate fracking, industry threatens to bring costly takings claims for compensation due to alleged economic harms. This Article examines the numerous legal and factual issues that should make it difficult for industry to succeed on fracking/takings claims. First, regulation of fracking, even including outright bans, can almost always be defended as necessary to prevent a nuisance or other background principle of law that justifies government regulation. Even if a nuisance defense could be overcome, industry would have difficulty proving that regulation has destroyed all economic value in their property, unless courts take a narrow view of property that would highlight the arbitrary nature of the “denominator problem.” When fracking/takings claims are considered under the default balancing of the Penn Central case, takings are unlikely to be found except in rare outlier cases. Finally, because requiring governments to pay compensation in fracking/takings cases would likely create a windfall for industry, particularly if the oil and gas eventually is extracted in the future, courts should resist the temptation to rule against government restrictions to protect public health, safety, and the environment.

A study of a soft computing based method for 3D scenario reconstruction

Several recent works deal with 3D data in mobile robotic problems, e.g., mapping. Data comes from any kind of sensor (time of flight, Kinect or 3D lasers) that provide a huge amount of unorganized 3D data. In this paper we detail an efficient approach to build complete 3D models using a soft computing method, the Growing Neural Gas (GNG). As neural models deal easily with noise, imprecision, uncertainty or partial data, GNG provides better results than other approaches. The GNG obtained is then applied to a sequence. We present a comprehensive study on GNG parameters to ensure the best result at the lowest time cost. From this GNG structure, we propose to calculate planar patches and thus obtaining a fast method to compute the movement performed by a mobile robot by means of a 3D models registration algorithm. Final results of 3D mapping are also shown.

μ-MAR: Multiplane 3D Marker based Registration for depth-sensing cameras

Many applications including object reconstruction, robot guidance, and. scene mapping require the registration of multiple views from a scene to generate a complete geometric and appearance model of it. In real situations, transformations between views are unknown and it is necessary to apply expert inference to estimate them. In the last few years, the emergence of low-cost depth-sensing cameras has strengthened the research on this topic, motivating a plethora of new applications. Although they have enough resolution and accuracy for many applications, some situations may not be solved with general state-of-the-art registration methods due to the signal-to-noise ratio (SNR) and the resolution of the data provided. The problem of working with low SNR data, in general terms, may appear in any 3D system, then it is necessary to propose novel solutions in this aspect. In this paper, we propose a method, μ-MAR, able to both coarse and fine register sets of 3D points provided by low-cost depth-sensing cameras, despite it is not restricted to these sensors, into a common coordinate system. The method is able to overcome the noisy data problem by means of using a model-based solution of multiplane registration. Specifically, it iteratively registers 3D markers composed by multiple planes extracted from points of multiple views of the scene. As the markers and the object of interest are static in the scenario, the transformations obtained for the markers are applied to the object in order to reconstruct it. Experiments have been performed using synthetic and real data. The synthetic data allows a qualitative and quantitative evaluation by means of visual inspection and Hausdorff distance respectively. The real data experiments show the performance of the proposal using data acquired by a Primesense Carmine RGB-D sensor. The method has been compared to several state-of-the-art methods. The results show the good performance of the μ-MAR to register objects with high accuracy in presence of noisy data outperforming the existing methods.

Effectiveness of audible warning devices on emergency vehicles. Final report.

Transportation Department, Office of Noise Abatement, Washington, D.C.

Aquifers of Illinois : underground sources of drinking water and non-drinking water /

"September, 1981."

Ground water level changes and demographic analysis of ground water in Illinois /

"October, 1981."

Groundwater withdrawals from aquifers in Illinois with emphasis on PWS wells /

Bibliography: p. 25-26.

Public opinion of a proposed wind farm situated close to a populated area in New Zealand: Results from a cross-sectional study

In accordance with New Zealand’s Resource Management Act 1991, in 2003, electricity generating company Genesis Energy made public its intention to apply for consent to build the Awhitu wind farm. Several community groups claiming to represent the majority opposed this application and in September 2004 consent was declined. The aim was to investigate the attitudes of local community members to the proposed wind farm. A survey was mailed to 500 Franklin residents, systematically selected from the local 2004/2005 telephone directory. Forty questionnaires were returned undelivered. Of the remaining 460, completed questionnaires were returned from 46% (211). Most, 70% (145), residents supported a wind farm being built in their area, with 17% (35) neutral, and only 13% (28) against the farm. There was no statistical difference in respondents’ attitudes between sex, age, or residential proximity to the farm. Respondents listed renewable resource (83%), suitability (78%), and environmental friendliness (76%) as main advantages. Visual unsightliness (24%) and noise pollution (21%) were listed as main perceived disadvantages. Contrary to the assertions of several lobby groups, the majority of local residents support the construction of the Awhitu wind farm. Scientifically robust methods are essential to measure appropriately community attitudes, particularly on contentious issues.

A modified particle filter for simultaneous robot localization and landmark tracking in an indoor environment

This paper presents the implementation of a modified particle filter for vision-based simultaneous localization and mapping of an autonomous robot in a structured indoor environment. Through this method, artificial landmarks such as multi-coloured cylinders can be tracked with a camera mounted on the robot, and the position of the robot can be estimated at the same time. Experimental results in simulation and in real environments show that this approach has advantages over the extended Kalman filter with ambiguous data association and various levels of odometric noise.

A generative probabilistic oriented wavelet model for texture segmentation

This Letter addresses image segmentation via a generative model approach. A Bayesian network (BNT) in the space of dyadic wavelet transform coefficients is introduced to model texture images. The model is similar to a Hidden Markov model (HMM), but with non-stationary transitive conditional probability distributions. It is composed of discrete hidden variables and observable Gaussian outputs for wavelet coefficients. In particular, the Gabor wavelet transform is considered. The introduced model is compared with the simplest joint Gaussian probabilistic model for Gabor wavelet coefficients for several textures from the Brodatz album [1]. The comparison is based on cross-validation and includes probabilistic model ensembles instead of single models. In addition, the robustness of the models to cope with additive Gaussian noise is investigated. We further study the feasibility of the introduced generative model for image segmentation in the novelty detection framework [2]. Two examples are considered: (i) sea surface pollution detection from intensity images and (ii) image segmentation of the still images with varying illumination across the scene.

Semi-supervised learning of hierarchical latent trait models for data visualisation

An interactive hierarchical Generative Topographic Mapping (HGTM) ¸iteH_GTM has been developed to visualise complex data sets. In this paper, we build a more general visualisation system by extending the HGTM visualisation system in 3 directions: bf (1) We generalize HGTM to noise models from the exponential family of distributions. The basic building block is the Latent Trait Model (LTM) developed in ¸iteKaban_pami. bf (2) We give the user a choice of initializing the child plots of the current plot in either em interactive, or em automatic mode. In the interactive mode the user interactively selects ``regions of interest'' as in ¸iteH_GTM, whereas in the automatic mode an unsupervised minimum message length (MML)-driven construction of a mixture of LTMs is employed. bf (3) We derive general formulas for magnification factors in latent trait models. Magnification factors are a useful tool to improve our understanding of the visualisation plots, since they can highlight the boundaries between data clusters. The unsupervised construction is particularly useful when high-level plots are covered with dense clusters of highly overlapping data projections, making it difficult to use the interactive mode. Such a situation often arises when visualizing large data sets. We illustrate our approach on a toy example and apply our system to three more complex real data sets.

EM algorithm for GTM-FS

We propose a generative topographic mapping (GTM) based data visualization with simultaneous feature selection (GTM-FS) approach which not only provides a better visualization by modeling irrelevant features ("noise") using a separate shared distribution but also gives a saliency value for each feature which helps the user to assess their significance. This technical report presents a varient of the Expectation-Maximization (EM) algorithm for GTM-FS.