928 resultados para Passive sampling


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The relationship between microbial colonization of two kinds of passive metals and ennobling of their corrosion potentials (E-corr) were studied. Two types of passive metal coupons were exposed to natural seawater for about ten days. Under laboratory conditions, all corrosion potentials of the samples ennobled for about 200 mV. Epifluorescence microscopy showed that bacteria adsorption was the main process during about the first day immersion and bacteria reproduced in the following days. The bacteria number increased on the metal surface according to an exponential law and the kinetics of bacteria adsorption at the metal surface during this period was proposed. The ennoblement of E-corr was similar to the increasing bacteria number: E-corr increased quickly during the bacteria adsorption process and increased slowly after biofilms had formed.

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Recent work in sensor databases has focused extensively on distributed query problems, notably distributed computation of aggregates. Existing methods for computing aggregates broadcast queries to all sensors and use in-network aggregation of responses to minimize messaging costs. In this work, we focus on uniform random sampling across nodes, which can serve both as an alternative building block for aggregation and as an integral component of many other useful randomized algorithms. Prior to our work, the best existing proposals for uniform random sampling of sensors involve contacting all nodes in the network. We propose a practical method which is only approximately uniform, but contacts a number of sensors proportional to the diameter of the network instead of its size. The approximation achieved is tunably close to exact uniform sampling, and only relies on well-known existing primitives, namely geographic routing, distributed computation of Voronoi regions and von Neumann's rejection method. Ultimately, our sampling algorithm has the same worst-case asymptotic cost as routing a point-to-point message, and thus it is asymptotically optimal among request/reply-based sampling methods. We provide experimental results demonstrating the effectiveness of our algorithm on both synthetic and real sensor topologies.

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A novel technique to detect and localize periodic movements in video is presented. The distinctive feature of the technique is that it requires neither feature tracking nor object segmentation. Intensity patterns along linear sample paths in space-time are used in estimation of period of object motion in a given sequence of frames. Sample paths are obtained by connecting (in space-time) sample points from regions of high motion magnitude in the first and last frames. Oscillations in intensity values are induced at time instants when an object intersects the sample path. The locations of peaks in intensity are determined by parameters of both cyclic object motion and orientation of the sample path with respect to object motion. The information about peaks is used in a least squares framework to obtain an initial estimate of these parameters. The estimate is further refined using the full intensity profile. The best estimate for the period of cyclic object motion is obtained by looking for consensus among estimates from many sample paths. The proposed technique is evaluated with synthetic videos where ground-truth is known, and with American Sign Language videos where the goal is to detect periodic hand motions.

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Considerable attention has been focused on the properties of graphs derived from Internet measurements. Router-level topologies collected via traceroute studies have led some authors to conclude that the router graph of the Internet is a scale-free graph, or more generally a power-law random graph. In such a graph, the degree distribution of nodes follows a distribution with a power-law tail. In this paper we argue that the evidence to date for this conclusion is at best insufficient. We show that graphs appearing to have power-law degree distributions can arise surprisingly easily, when sampling graphs whose true degree distribution is not at all like a power-law. For example, given a classical Erdös-Rényi sparse, random graph, the subgraph formed by a collection of shortest paths from a small set of random sources to a larger set of random destinations can easily appear to show a degree distribution remarkably like a power-law. We explore the reasons for how this effect arises, and show that in such a setting, edges are sampled in a highly biased manner. This insight allows us to distinguish measurements taken from the Erdös-Rényi graphs from those taken from power-law random graphs. When we apply this distinction to a number of well-known datasets, we find that the evidence for sampling bias in these datasets is strong.

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Les Houches workshop, September 28-October 2, 1998.

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In this paper, we propose generalized sampling approaches for measuring a multi-dimensional object using a compact compound-eye imaging system called thin observation module by bound optics (TOMBO). This paper shows the proposed system model, physical examples, and simulations to verify TOMBO imaging using generalized sampling. In the system, an object is modulated and multiplied by a weight distribution with physical coding, and the coded optical signal is integrated on to a detector array. A numerical estimation algorithm employing a sparsity constraint is used for object reconstruction.

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Pianists of the twenty-first century have a wealth of repertoire at their fingertips. They busily study music from the different periods -- Baroque, Classical, Romantic, and some of the twentieth century -- trying to understand the culture and performance practice of the time and the stylistic traits of each composer so they can communicate their music effectively. Unfortunately, this leaves little time to notice the composers who are writing music today. Whether this neglect proceeds from lack of time or lack of curiosity, I feel we should be connected to music that was written in our own lifetime, when we already understand the culture and have knowledge of the different styles that preceded us. Therefore, in an attempt to promote today’s composers, I have selected piano music written during my lifetime, to show that contemporary music is effective and worthwhile and deserves as much attention as the music that preceded it. This dissertation showcases piano music composed from 1978 to 2005. A point of departure in selecting the pieces for this recording project is to represent the major genres in the piano repertoire in order to show a variety of styles, moods, lengths, and difficulties. Therefore, from these recordings, there is enough variety to successfully program a complete contemporary recital from the selected works, and there is enough variety to meet the demands of pianists with different skill levels and recital programming needs. Since we live in an increasingly global society, music from all parts of the world is included to offer a fair representation of music being composed everywhere. Half of the music in this project comes from the United States. The other half comes from Australia, Japan, Russia, and Argentina. The composers represented in these recordings are: Lowell Liebermann, Richard Danielpour, Frederic Rzewski, Judith Lang Zaimont, Samuel Adler, Carl Vine, Nikolai Kapustin, Akira Miyoshi and Osvaldo Golijov. With the exception of one piano concerto, all the works are for solo piano. This recording project dissertation consists of two 60 minute CDs of selected repertoire, accompanied by a substantial document of in-depth program notes. The recordings are documented on compact discs that are housed within the University of Maryland Library System.

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Ocean Sampling Day was initiated by the EU-funded Micro B3 (Marine Microbial Biodiversity, Bioinformatics, Biotechnology) project to obtain a snapshot of the marine microbial biodiversity and function of the world's oceans. It is a simultaneous global mega-sequencing campaign aiming to generate the largest standardized microbial data set in a single day. This will be achievable only through the coordinated efforts of an Ocean Sampling Day Consortium, supportive partnerships and networks between sites. This commentary outlines the establishment, function and aims of the Consortium and describes our vision for a sustainable study of marine microbial communities and their embedded functional traits.

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Thanks to a passive cavity configuration, modulational instability in fibers is successfully observed, for the first time to our knowledge, in the continuous-wave regime. Our technique provides a new means of generating all-optically ultrahigh-repetition-rate pulse trains and opens up new possibilities for the fundamental study of modulational instability and related phenomena. © 2001 Optical Society of America.

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High pollution levels have been often observed in urban street canyons due to the increased traffic emissions and reduced natural ventilation. Microscale dispersion models with different levels of complexity may be used to assess urban air qualityand support decision-making for pollution control strategies and traffic planning. Mathematical models calculate pollutant concentrations by solving either analytically a simplified set of parametric equations or numerically a set of differential equations that describe in detail wind flow and pollutant dispersion. Street canyon models, which might also include simplified photochemistry and particle deposition–resuspension algorithms, are often nested within larger-scale urban dispersion codes. Reduced-scale physical models in wind tunnels may also be used for investigating atmospheric processes within urban canyons and validating mathematical models. A range of monitoring techniques is used to measure pollutant concentrations in urban streets. Point measurement methods (continuous monitoring, passive and active pre-concentration sampling, grab sampling) are available for gaseous pollutants. A number of sampling techniques (mainlybased on filtration and impaction) can be used to obtain mass concentration, size distribution and chemical composition of particles. A combination of different sampling/monitoring techniques is often adopted in experimental studies. Relativelysimple mathematical models have usually been used in association with field measurements to obtain and interpret time series of pollutant concentrations at a limited number of receptor locations in street canyons. On the other hand, advanced numerical codes have often been applied in combination with wind tunnel and/or field data to simulate small-scale dispersion within the urban canopy.

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