964 resultados para Continuous emission monitoring


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We report on the single photon emission from single InAs/GaAs self-assembled Stranski-Krastanow quantum dots up to 80K under pulsed and continuous wave excitations. At temperature 80 K, the second-order correlation function at zero time delay, g((2))(0), is measured to be 0.422 for pulsed excitation. At the same temperature under continuous wave excitation, the photon antibunching effect is observed. Thus, our experimental results demonstrate a promising potential application of self-assembled InAs/GaAs quantum dots in single photon emission at liquid nitrogen temperature.

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High-power and broadband quantum-dot (QD) superluminescent light-emitting diodes are realized by using a combination of self-assembled QDs with a high density, large inhomogeneous broadening, a tapered angled pump region, and etched V groove structure. This broad-area device exhibits greater than 70-nm 3-dB bandwidth and drive current insensitive emission spectra with 100-mW output power under continuous-wave operation. For pulsed operation, greater than 200-mW output power is obtained.

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Room-temperature operation of cw GaN based multi-quantum-well laser diodes (LDs) is demonstrated. The LD structure is grown on a sapphire (0001) substrate by metalorganic chemical vapour deposition. A 2.5 mu m x 800 mu m ridge waveguide structure is fabricated. The electrical and optical characteristics of the laser diode under direct current injection at room temperature are investigated. The threshold current and voltage of the LD under cw operation are 110mA and 10.5V, respectively. Thermal induced series resistance decrease and emission wavelength red-shift are observed as the injection current is increased. The full width at half maximum for the parallel and perpendicular far field pattern (FFP) are 12 degrees and 32 degrees, respectively.

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Starting from the growth of high-quality 1.3 mu m GaInNAs/GaAs quantum well (QW), the QW emission wavelength has been extended up to 1.55 mu m by a combination of lowering growth rate, using GaNAs barriers and incorporating some amount of Sb. The photoluminescence properties of 1.5 mu m range GaInNAsSb/GaNAs QWs are quite comparable to the 1.3 mu m QWs, revealing positive effect of Sb on improving the optical quality of the QWs. A 1.59 mu m lasing of a GaInNAsSb/GaNAs single-QW laser diode is obtained under continuous current injection at room temperature. The threshold current density is 2.6 kA/cm(2) with as-cleaved facet mirrors. (c) 2005 American Institute of Physics.

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A self-assembled quantum-wire laser structure was grown by solid-source molecular beam epitaxy in an InAlGaAs-InAlAs matrix oil InP(001) substrate. Ridge-waveguide lasers were fabricated and demonstrated to operate at a heatsink temperature tip to 330 K in continuous-wave (CW) mode. The emission wavelength of the lasers with 5 mm-long cavity was 1.713 mu m at room temperature in CW mode. The temperature stability of the devices was analysed and the characteristic temperature was found to be 47 K in the mnge of 220-320 K.

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Measurement of iron and manganese is very important in evaluating the quality of natural waters. We have constructed an automated Fe(II), total dissolved iron(TDI), Mn(II), and total dissolved manganese(TDM) analysis system for the quality control of underground drinking water by reverse flow injection analysis and chemiluminescence detection(rFIA-CL), The method is based on the measurement of the metal-catalyzed light emission from luminol oxidation by potassium periodate. The typical signal is a narrow peak, in which the height is proportional to light emitted and hence to the concentration of metal ions. The detection limits were 3 x 10(-6) mu g ml(-1) for Fe(II) and the linear range extents up to 1.0 x 10(-4) and 5 x 10(-6) mu g ml(-1) for Mn(II) cover a linear range to 1.0 x 10(-4) mu g ml(-1). This method was used for automated in-situ monitoring of total dissolved iron and total dissolved in underground water during water treatment. (C) 1997 Elsevier Science B.V.

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This paper deals with the evaluation of the reliability of the analytical results obtained by Kalman filtering. Two criteria for evaluation were compared: one is based on the autocorrelation analysis of the innovation sequence, the so-called NAC criterion; the other is the innovations number, which actually is the autocorrelation coefficient of the innovation sequence at the initial wavelength. Both criteria allow compensation for the wavelength positioning errors in spectral scans, but there exists a difference in the way they work. The NAC criterion can provide information about the reliability of an individual result, which is very useful for the indication of unmodelled emissions, while the innovations number should be incorporated with the normalization of the innovations or seek the help of the sequence itself for the same purpose. The major limitation of the NAC criterion is that it does not allow the theoretical modelling of continuous backgrounds, which, however, is convenient in practical analysis and can be taken with the innovations number criterion.

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At a time when technological advances are providing new sensor capabilities, novel network capabilities, long-range communications technologies and data interpreting and delivery formats via the World Wide Web, we never before had such opportunities to sense and analyse the environment around us. However, the challenges exist. While measurement and detection of environmental pollutants can be successful under laboratory-controlled conditions, continuous in-situ monitoring remains one of the most challenging aspects of environmental sensing. This paper describes the development and test of a multi-sensor heterogeneous real-time water monitoring system. A multi-sensor system was deployed in the River Lee, County Cork, Ireland to monitor water quality parameters such as pH, temperature, conductivity, turbidity and dissolved oxygen. The R. Lee comprises of a tidal water system that provides an interesting test site to monitor. The multi-sensor system set-up is described and results of the sensor deployment and the various challenges are discussed.

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Structural Health Monitoring (SHM) is an integral part of infrastructure maintenance and management systems due to socio-economic, safety and security reasons. The behaviour of a structure under vibration depends on structure characteristics. The change of structure characteristics may suggest the change in system behaviour due to the presence of damage(s) within. Therefore the consistent, output signal guided, and system dependable markers would be convenient tool for the online monitoring, the maintenance, rehabilitation strategies, and optimized decision making policies as required by the engineers, owners, managers, and the users from both safety and serviceability aspects. SHM has a very significant advantage over traditional investigations where tangible and intangible costs of a very high degree are often incurred due to the disruption of service. Additionally, SHM through bridge-vehicle interaction opens up opportunities for continuous tracking of the condition of the structure. Research in this area is still in initial stage and is extremely promising. This PhD focuses on using bridge-vehicle interaction response for SHM of damaged or deteriorating bridges to monitor or assess them under operating conditions. In the present study, a number of damage detection markers have been investigated and proposed in order to identify the existence, location, and the extent of an open crack in the structure. The theoretical and experimental investigation has been conducted on Single Degree of Freedom linear system, simply supported beams. The novel Delay Vector Variance (DVV) methodology has been employed for characterization of structural behaviour by time-domain response analysis. Also, the analysis of responses of actual bridges using DVV method has been for the first time employed for this kind of investigation.

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It is estimated that the quantity of digital data being transferred, processed or stored at any one time currently stands at 4.4 zettabytes (4.4 × 2 70 bytes) and this figure is expected to have grown by a factor of 10 to 44 zettabytes by 2020. Exploiting this data is, and will remain, a significant challenge. At present there is the capacity to store 33% of digital data in existence at any one time; by 2020 this capacity is expected to fall to 15%. These statistics suggest that, in the era of Big Data, the identification of important, exploitable data will need to be done in a timely manner. Systems for the monitoring and analysis of data, e.g. stock markets, smart grids and sensor networks, can be made up of massive numbers of individual components. These components can be geographically distributed yet may interact with one another via continuous data streams, which in turn may affect the state of the sender or receiver. This introduces a dynamic causality, which further complicates the overall system by introducing a temporal constraint that is difficult to accommodate. Practical approaches to realising the system described above have led to a multiplicity of analysis techniques, each of which concentrates on specific characteristics of the system being analysed and treats these characteristics as the dominant component affecting the results being sought. The multiplicity of analysis techniques introduces another layer of heterogeneity, that is heterogeneity of approach, partitioning the field to the extent that results from one domain are difficult to exploit in another. The question is asked can a generic solution for the monitoring and analysis of data that: accommodates temporal constraints; bridges the gap between expert knowledge and raw data; and enables data to be effectively interpreted and exploited in a transparent manner, be identified? The approach proposed in this dissertation acquires, analyses and processes data in a manner that is free of the constraints of any particular analysis technique, while at the same time facilitating these techniques where appropriate. Constraints are applied by defining a workflow based on the production, interpretation and consumption of data. This supports the application of different analysis techniques on the same raw data without the danger of incorporating hidden bias that may exist. To illustrate and to realise this approach a software platform has been created that allows for the transparent analysis of data, combining analysis techniques with a maintainable record of provenance so that independent third party analysis can be applied to verify any derived conclusions. In order to demonstrate these concepts, a complex real world example involving the near real-time capturing and analysis of neurophysiological data from a neonatal intensive care unit (NICU) was chosen. A system was engineered to gather raw data, analyse that data using different analysis techniques, uncover information, incorporate that information into the system and curate the evolution of the discovered knowledge. The application domain was chosen for three reasons: firstly because it is complex and no comprehensive solution exists; secondly, it requires tight interaction with domain experts, thus requiring the handling of subjective knowledge and inference; and thirdly, given the dearth of neurophysiologists, there is a real world need to provide a solution for this domain

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The Continuous Plankton Recorder (CPR) survey was conceived from the outset as a programme of applied research designed to assist the fishing industry. Its survival and continuing vigour after 70 years is a testament to its utility, which has been achieved in spite of great changes in our understanding of the marine environment and in our concerns over how to manage it. The CPR has been superseded in several respects by other technologies, such as acoustics and remote sensing, but it continues to provide unrivalled seasonal and geographic information about a wide range of zooplankton and phytoplankton taxa. The value of this coverage increases with time and provides the basis for placing recent observations into the context of long-term, large-scale variability and thus suggesting what the causes are likely to be. Information from the CPR is used extensively in judging environmental impacts and producing quality status reports (QSR); it has shown the distributions of fish stocks, which had not previously been exploited; it has pointed to the extent of ungrazed phytoplankton production in the North Atlantic, which was a vital element in establishing the importance of carbon sequestration by phytoplankton. The CPR continues to be the principal source of large-scale, long-term information about the plankton ecosystem of the North Atlantic. It has recently provided extensive information about the biodiversity of the plankton and about the distribution of introduced species. It serves as a valuable example for the design of future monitoring of the marine environment and it has been essential to the design and implementation of most North Atlantic plankton research.

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The continuous plankton recorder (CPR) survey is the largest multi-decadal plankton monitoring programme in the world. It was initiated in 1931 and by the end of 2004 had counted 207,619 samples and identified 437 phyto- and zooplankton taxa throughout the North Atlantic. CPR data are used extensively by the research community and in recent years have been used increasingly to underpin marine management. Here, we take a critical look at how best to use CPR data. We first describe the CPR itself, CPR sampling, and plankton counting procedures. We discuss the spatial and temporal biases in the Survey, summarise environmental data that have not previously been available, and describe the new data access policy. We supply information essential to using CPR data, including descriptions of each CPR taxonomic entity, the idiosyncrasies associated with counting many of the taxa, the logic behind taxonomic changes in the Survey, the semi-quantitative nature of CPR sampling, and recommendations on choosing the spatial and temporal scale of study. This forms the basis for a broader discussion on how to use CPR data for deriving ecologically meaningful indices based on size, functional groups and biomass that can be used to support research and management. This contribution should be useful for plankton ecologists, modellers and policy makers that actively use CPR data.

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The Continuous Plankton Recorder (CPR) survey, operated by the Sir Alister Hardy Foundation for Ocean Science (SAHFOS), is the largest plankton monitoring programme in the world and has spanned >70 yr. The dataset contains information from ~200 000 samples, with over 2.3 million records of individual taxa. Here we outline the evolution of the CPR database through changes in technology, and how this has increased data access. Recent high-impact publications and the expanded role of CPR data in marine management demonstrate the usefulness of the dataset. We argue that solely supplying data to the research community is not sufficient in the current research climate; to promote wider use, additional tools need to be developed to provide visual representation and summary statistics. We outline 2 software visualisation tools, SAHFOS WinCPR and the digital CPR Atlas, which provide access to CPR data for both researchers and non-plankton specialists. We also describe future directions of the database, data policy and the development of visualisation tools. We believe that the approach at SAHFOS to increase data accessibility and provide new visualisation tools has enhanced awareness of the data and led to the financial security of the organisation; it also provides a good model of how long-term monitoring programmes can evolve to help secure their future.

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Preserved and archived organic material offers huge potential for the conduct of retrospective and long-term historical ecosystem reconstructions using stable isotope analyses, but because of isotopic exchange with preservatives the obtained values require validation. The Continuous Plankton Recorder (CPR) Survey is the most extensive long-term monitoring program for plankton communities worldwide and has utilised ships of opportunity to collect samples since 1931. To keep the samples intact for subsequent analysis, they are collected and preserved in formalin; however, previous studies have found that this may alter stable carbon and nitrogen isotope ratios in zooplankton. A maximum ~0.9‰ increase of δ15N and a time dependent maximum ~1.0‰ decrease of δ13C were observed when the copepod, Calanus helgolandicus, was experimentally exposed to two formalin preservatives for 12 months. Applying specific correction factors to δ15N and δ13C values for similarly preserved Calanoid species collected by the CPR Survey within 12 months of analysis may be appropriate to enable their use in stable isotope studies. The isotope values of samples stored frozen did not differ significantly from those of controls. Although the impact of formalin preservation was relatively small in this and other studies of marine zooplankton, changes in isotope signatures are not consistent across taxa, especially for δ15N, indicating that species-specific studies may be required. Copyright © 2011 John Wiley & Sons, Ltd.

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We review current knowledge and understanding of the biology and ecology of Centropages typicus in the European shelf-seas (e.g. North Sea, English Channel and Bay of Biscay). Our study is based on observations at seven coastal time-series stations as well as on the Continuous Plankton Recorder dataset. This paper focuses on the influence of the environmental parameters (e.g. temperature and Chla) on the life cycle and distribution of C typicus and provides a comparison with its congeneric species C. hamatus and C. chierchiae in the study area. Data on abundance, seasonality and egg production have been used to define the temperature and chlorophyll optima for occurrence and reproduction of Centropages spp. within this region of the European shelf-seas. (C) 2007 Elsevier Ltd. All rights reserved.