9 resultados para detection probability

em Repositório Institucional UNESP - Universidade Estadual Paulista "Julio de Mesquita Filho"


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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Balancing power production and environmental conservation can be problematic. The objective of this study was to investigate the abundance of marsh deer in the Paraná River Basin, above the Sergio Motta (Porto Primavera) Dam, before and after the impact of the dam closure. A fixed-wing, flat window aircraft was used to survey study transects. Observations were recorded based on the distance sampling line transect method, assuming that the detection probability decreases with increased distance. The abundance of marsh deer in the survey region prior to flooding was estimated to be 974 individuals (CV = 0.23). The overall abundance dropped from 974 to 444 (CV = 0.26) individuals after flooding, an overall reduction of 54%. This reduction can be attributed to the direct impact of the flooding process, but it was likely exacerbated by indirect effects, such as increased disease, hunting, and reduction in food availability. Prior to flooding, the marsh deer was distributed widely throughout the dam's catchment area; however, the marsh deer habitat was almost completely destroyed by the flooding process. This situation highlights the need to implement management strategies that ensure the survival of the remaining fragmented population.

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

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Structural Health Monitoring (SHM) denotes a system with the ability to detect and interpret adverse changes in structures in order to improve reliability and reduce life-cycle costs. The greatest challenge for designing a SHM system is knowing what changes to look for and how to classify them. Different approaches for SHM have been proposed for damage identification, each one with advantages and drawbacks. This paper presents a methodology for improvement in vibration signal analysis using statistics information involving the probability density. Generally, the presence of noises in input and output signals results in false alarms, then, it is important that the methodology can minimize this problem. In this paper, the proposed approach is experimentally tested in a flexible plate using a piezoelectric (PZT) actuator to provide the disturbance.

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Multisensor data fusion is a technique that combines the readings of multiple sensors to detect some phenomenon. Data fusion applications are numerous and they can be used in smart buildings, environment monitoring, industry and defense applications. The main goal of multisensor data fusion is to minimize false alarms and maximize the probability of detection based on the detection of multiple sensors. In this paper a local data fusion algorithm based on luminosity, temperature and flame for fire detection is presented. The data fusion approach was embedded in a low cost mobile robot. The prototype test validation has indicated that our approach can detect fire occurrence. Moreover, the low cost project allow the development of robots that could be discarded in their fire detection missions. © 2013 IEEE.

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

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

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