Mapeamento acústico como ferramenta para predição de ruído urbano na área de influência do estádio Arena das Dunas, Natal/ RN

The Noise Pollution causes degradation in the quality of the environment and presents itself as one of the most common environmental problems in the big cities. An Urban environment present scenario and their complex acoustic study need to consider the contribution of various noise sources. Accordingly to computational models through mapping and prediction of acoustic scene become important, because they enable the realization of calculations, analyzes and reports, allowing the interpretation of satisfactory results. The study neighborhood is the neighborhood of Lagoa Nova, a central area of the city of Natal, which will undergo major changes in urban space due to urban mobility projects planned for the area around the stadium and the consequent changes of urban form and traffic. Thus, this study aims to evaluate the noise impact caused by road and morphological changes around the stadium Arena das Dunas in the neighborhood of Lagoa Nova, through on-site measurements and mapping using the computational model SoundPLAN year 2012 and the scenario evolution acoustic for the year 2017. For this analysis was the construction of the first acoustic mapping based on current diagnostic acoustic neighborhood, physical mapping, classified vehicle count and measurement of sound pressure level, and to build the prediction of noise were observed for the area study the modifications provided for traffic, urban form and mobility work. In this study, it is concluded that the sound pressure levels of the year in 2012 and 2017 extrapolate current legislation. For the prediction of noise were numerous changes in the acoustic scene, in which the works of urban mobility provided will improve traffic flow, thus reduce the sound pressure level where interventions are expected

Supressão do ruído de rolamento superficial utilizando a transformada Curvelet

Among the many types of noise observed in seismic land acquisition there is one produced by surface waves called Ground Roll that is a particular type of Rayleigh wave which characteristics are high amplitude, low frequency and low velocity (generating a cone with high dip). Ground roll contaminates the relevant signals and can mask the relevant information, carried by waves scattered in deeper regions of the geological layers. In this thesis, we will present a method that attenuates the ground roll. The technique consists in to decompose the seismogram in a basis of curvelet functions that are localized in time, in frequency, and also, incorporate an angular orientation. These characteristics allow to construct a curvelet filter that takes in consideration the localization of denoise in scales, times and angles in the seismogram. The method was tested with real data and the results were very good

Filtro kl/dvs para atenuação do ruído "ground roll"

In geophysics there are several steps in the study of the Earth, one of them is the processing of seismic records. These records are obtained through observations made on the earth surface and are useful for information about the structure and composition of the inaccessible parts in great depths. Most of the tools and techniques developed for such studies has been applied in academic projects. The big problem is that the seismic processing power unwanted, recorded by receivers that do not bring any kind of information related to the reflectors can mask the information and/or generate erroneous information from the subsurface. This energy is known as unwanted seismic noise. To reduce the noise and improve a signal indicating a reflection, without losing desirable signals is sometimes a problem of difficult solution. The project aims to get rid of the ground roll noise, which shows a pattern characterized by low frequency, low rate of decay, low velocity and high amplituds. The Karhunen-Loève Transform is a great tool for identification of patterns based on the eigenvalues and eigenvectors. Together with the Karhunen-Loève Transform we will be using the Singular Value Decomposition, since it is a great mathematical technique for manipulating data

Podem os programas sociais e de transferência de renda influenciar a oferta de trabalho em atividades não agrícolas? uma análise para as famílias em condição de pobreza no meio rural do nordeste

This study aims to analyze the main effect of social programs and cash transfers on the labor supply of non-farm family members in poverty in rural areas of the Northeast. Among the specific objectives, we sought to investigate the effects of these programs and individual characteristics on the decision of participation and allocation of working hours of parents and children in non-agricultural activities. It was assumed, as a theoretical basis, the model of neoclassical labor supply as well as the principle that the decision of allocation of working hours, non-agricultural, is subject to the initial choice of the worker devote or not the non-agricultural employment . The hypothesis assumes that access to social programs and income transfer contributes to the dismay of rural workers, in poverty, in its decision to participate and offer hours of work in non-agricultural activities. To achieve this objective, we applied the models of Heckman (1979) and Double Hurdle, of Cragg (1971), consisting of associating the decision to participate in the labor market with the decision on the amount of hours allocated. The database used was the National Survey by Household Sampling (PNAD) of 2006. The results of the heads of households showed that transfers of income, although they may have some effect on labor supply rural nonfarm, the magnitude has to say that there may be some dependence on benefits. The estimates for the joint children of 10 to 15 years showed that the programs have negatively influenced participation in suggesting an increase in school participation, although for the allocation of working hours the results were not significant on the incidence of child labor

Implementação e avaliação de máquinas de comitê em um ambiente com múltiplos processadores embarcados em um único chip

The number of applications based on embedded systems grows significantly every year, even with the fact that embedded systems have restrictions, and simple processing units, the performance of these has improved every day. However the complexity of applications also increase, a better performance will always be necessary. So even such advances, there are cases, which an embedded system with a single unit of processing is not sufficient to achieve the information processing in real time. To improve the performance of these systems, an implementation with parallel processing can be used in more complex applications that require high performance. The idea is to move beyond applications that already use embedded systems, exploring the use of a set of units processing working together to implement an intelligent algorithm. The number of existing works in the areas of parallel processing, systems intelligent and embedded systems is wide. However works that link these three areas to solve any problem are reduced. In this context, this work aimed to use tools available for FPGA architectures, to develop a platform with multiple processors to use in pattern classification with artificial neural networks

Sistema inteligente para diagnóstico de patologias na laringe utilizando máquinas de vetor de suporte

The human voice is an important communication tool and any disorder of the voice can have profound implications for social and professional life of an individual. Techniques of digital signal processing have been used by acoustic analysis of vocal disorders caused by pathologies in the larynx, due to its simplicity and noninvasive nature. This work deals with the acoustic analysis of voice signals affected by pathologies in the larynx, specifically, edema, and nodules on the vocal folds. The purpose of this work is to develop a classification system of voices to help pre-diagnosis of pathologies in the larynx, as well as monitoring pharmacological treatments and after surgery. Linear Prediction Coefficients (LPC), Mel Frequency cepstral coefficients (MFCC) and the coefficients obtained through the Wavelet Packet Transform (WPT) are applied to extract relevant characteristics of the voice signal. For the classification task is used the Support Vector Machine (SVM), which aims to build optimal hyperplanes that maximize the margin of separation between the classes involved. The hyperplane generated is determined by the support vectors, which are subsets of points in these classes. According to the database used in this work, the results showed a good performance, with a hit rate of 98.46% for classification of normal and pathological voices in general, and 98.75% in the classification of diseases together: edema and nodules

Desenvolvimento de um Sistema de Automação e Supervisão de Máquinas Dispensadoras Através da Internet

This paper aims to design and develop a control and monitoring system of vending machines, based on a Central Processing Unit with peripheral Internet communication. Coupled with the condom vending machines, a data acquisition module will be connected to the original circuits in order to collect and send, via internet, the information to the healthy government agencies, in the form of charts and reports. In the face of this, such agencies may analyze these data and compare them with the rates of reduction, in medium or long term, of the STD/AIDS in their respective regions, after the implementation of these vending machines, together with the conventional preventing programs. Reading the methodology, this paper is about an explaining and bibliography research, with the aspect of a qualitative-quantitative methodology, presenting a deductive method of approach and an indirect documentation technique research. About the results of the tests and simulations, we concluded that the implementation of this system will have the same success in any other type of dispenser machine

Classificação de padrões através de um comitê de máquinas aprimorado por aprendizagem por reforço

Reinforcement learning is a machine learning technique that, although finding a large number of applications, maybe is yet to reach its full potential. One of the inadequately tested possibilities is the use of reinforcement learning in combination with other methods for the solution of pattern classification problems. It is well documented in the literature the problems that support vector machine ensembles face in terms of generalization capacity. Algorithms such as Adaboost do not deal appropriately with the imbalances that arise in those situations. Several alternatives have been proposed, with varying degrees of success. This dissertation presents a new approach to building committees of support vector machines. The presented algorithm combines Adaboost algorithm with a layer of reinforcement learning to adjust committee parameters in order to avoid that imbalances on the committee components affect the generalization performance of the final hypothesis. Comparisons were made with ensembles using and not using the reinforcement learning layer, testing benchmark data sets widely known in area of pattern classification

Viabilidade da Utilização de Máquinas de Indução Convencionais como Motores sem Mancais Mecânicos

Electrical Motors transform electrical energy into mechanic energy in a relatively easy way. In some specific applications, there is a need for electrical motors to function with noncontaminated fluids, in high speed systems, under inhospitable conditions, or yet, in local of difficult access and considerable depth. In these cases, the motors with mechanical bearings are not adequate as their wear give rise to maintenance. A possible solution for these problems stems from two different alternatives: motors with magnetic bearings, that increase the length of the machine (not convenient), and the bearingless motors that aggregate compactness. Induction motors have been used more and more in research, as they confer more robustness to bearingless motors compared to other types of machines building with others motors. The research that has already been carried out with bearingless induction motors utilized prototypes that had their structures of stator/rotor modified, that differ most of the times from the conventional induction motors. The goal of this work is to study the viability of the use of conventional induction Motors for the beringless motors applications, pointing out the types of Motors of this category that can be more useful. The study uses the Finite Elements Method (FEM). As a means of validation, a conventional induction motor with squirrel-cage rotor was successfully used for the beringless motor application of the divided winding type, confirming the proposed thesis. The controlling system was implemented in a Digital Signal Processor (DSP)

Estabilizador de sistema de potência para máquinas síncronas de polos salientes utilizando a transformada Wavelet

The power system stabilizers are used to suppress low-frequency electromechanical oscillations and improve the synchronous generator stability limits. This master thesis proposes a wavelet-based power system stabilizer, composed of a new methodology for extraction and compensation of electromechanical oscillations in electrical power systems based on the scaling coefficient energy of the maximal overlap discrete wavelet transform in order to reduce the effects of delay and attenuation of conventional power system stabilizers. Moreover, the wavelet coefficient energy is used for electric oscillation detection and triggering the power system stabilizer only in fault situations. The performance of the proposed power system stabilizer was assessed with experimental results and comparison with the conventional power system stabilizer. Furthermore, the effects of the mother wavelet were also evaluated in this work

A Perda Auditiva Induzida pelo Ruído (PAIR) na formação odontológica: conhecimentos e níveis de exposição

The rationalization of work in the Dentistry has been taking the professional to work for ways and systems based in the ergonomics, turning their work efficient and less tiring. Since their academic formation, the dentists surgeons are concerned with the high productivity in clinic and with the final result of the work, neglecting the way as it is executed, which reduce their work capacity and exhibits them to occupational diseases that could be minimized and/or forewarned. This research had as the main objective to investigate the knowledge of the Dentistry academics of Rio Grande do Norte Federal University concerning the Noise-induced Hearing Loss (NIHL), relating them at the noise levels that they are exposed, as well as to the preventive measures taken during the clinical activities. Was observed that 95% of the individuals know that the dentist surgeon is a professional in risk for NIHL. Among the causes of NIHL, the one that obtained the largest frequency citation was the high-speed handpieces, reminded by 92,4% of the academics. Among the students which enumerated protective measures for NIHL, 92% mentioned the use of the ear plugs, although 97% of the researched have told do not use any kind of preventive measure related to the noise. Was also observed that 96% of the academics notice the noise during the clinical attendance, what inconvenience 28,1% of them. Related the noise levels, the high-speed handpieces of the academics presented a medium value of 80,5 dB varying from 72,3 to 88,3 dB. The average of the ambient noise observed at the Integrated Clinic was about 74,8 dB. In spite of the noise levels in this research were observed below the established limits of tolerance by the legislation, they can provoke damages to the Dentistry professionals' health, or that suggests the need of an intervention and use of immediate preventive measures able to generate a healthy atmosphere of work and less risky

Avaliação de impacto ambiental e gestão dos recursos natuarias no estuário Apodi Mossoró, nordeste do Brasil

The aim of this study is to investigate the eco-environmental vulnerability, its changes, and its causes to develop a management system for application of eco-environmental vulnerability and risk assessment in the Apodi-Mossory estuary, Northeast Brazil. This analysis is focused on the interference of the landscape conditions, and its changes, due to the following factors: the oil and natural gas industry, tropical fruits industry, shrimp farms, marine salt industry, occupation of the sensitive areas; demand for land, vegetation degradation, siltation in rivers, severe flooding, sea level rise (SLR), coastal dynamics, low and flat topography, high ecological value and tourism in the region and the rapid growth of urbanization. Conventional and remote sensing data were analyzed using modeling techniques based on ArcGIS, ER-Mapper, ERDAS Imagine and ENVI software. Digital images were initially processed by Principal Component Analysis and transformation of the maximum fraction of noise, and then all bands were normalized to reduce errors caused by bands of different sizes. They were integrated in a Geographic Information System analysis to detect changes, to generate digital elevation models, geomorphic indices and other variables of the study area. A three band color combination of multispectral bands was used to monitor changes of land and vegetation cover from 1986 to 2009. This task also included the analysis of various secondary data, such as field data, socioeconomic data, environmental data and prospects growth. The main objective of this study was to improve our understanding of eco-environmental vulnerability and risk assessment; it´s causes basically show the intensity, its distribution and human-environment effect on the ecosystem, and identify the high and low sensitive areas and area of inundation due to future SLR, and the loss of land due to coastal erosion in the Apodi-Mossoró estuary in order to establish a strategy for sustainable land use. The developed model includes some basic factors such as geology, geomorphology, soils, land use / land cover, vegetation cover, slope, topography and hydrology. The numerical results indicate that 9.86% of total study area was under very high vulnerability, 29.12% high vulnerability, 52.90% moderate vulnerability and 2.23% were in the category of very low vulnerability. The analysis indicates that 216.1 km² and 362.8 km² area flooded on 1m and 10m in sea levels respectively. The sectors most affected were residential, industrial and recreational areas, agricultural land, and ecosystems of high environmental sensitivity. The results showed that changes in eco-environmental vulnerability have a significant impact on the sustainable development of the RN state, since the indicator is a function of sensitivity, exposure and status in relation to a level of damage. The model were presented as a tool to assist in indexing vulnerability in order to optimize actions and assess the implications of decisions makers and policies regarding the management of coastal and estuarine areas. In this context aspects such as population growth, degradation of vegetation, land use / land cover, amount and type of industrialization, SLR and government policies for environmental protection were considered the main factors that affect the eco-environmental changes over the last three decades in the Apodi-Mossoró estuary.