973 resultados para 291702 Optical and Photonic Systems


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We demonstrate that doubly differential decoding can demodulate phase shift keyed data much faster after the switching event of a tunable laser than usual mth power single differential decoding. This technique can significantly improve throughput of optical burst switched networks.

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We derive rigorously the Fokker-Planck equation that governs the statistics of soliton parameters in optical transmission lines in the presence of additive amplifier spontaneous emission. We demonstrate that these statistics are generally non-Gaussian. We present exact marginal probability-density functions for soliton parameters for some cases. A WKB approach is applied to describe the tails of the probability-density functions. © 2005 Optical Society of America.

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The frequency dependent radio frequency power degradation in direct modulated microwave photonic systems employing uniform period fiber Bragg gratings (FBG) as reflective elements in investigated. Results show implications in terms of the available radio frequency bandwidth and the stability requirements for the FBG.

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With the aim of analyzing the complex physical and biogeochemical interactions at high temporal and spatial resolution in the complex estuarine waters of Alfacs Bay, a beam attenuation-based approach was used as optical proxy of different biogeochemical variables. Thus, the dataset contains the attenuation proxies as well as laboratory results from the analysis of water samples, which were used to validate our approach. In addition, the major physical forcing in the Bay was also measured.

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The amount and quality of available biomass is a key factor for the sustainable livestock industry and agricultural management related decision making. Globally 31.5% of land cover is grassland while 80% of Ireland’s agricultural land is grassland. In Ireland, grasslands are intensively managed and provide the cheapest feed source for animals. This dissertation presents a detailed state of the art review of satellite remote sensing of grasslands, and the potential application of optical (Moderate–resolution Imaging Spectroradiometer (MODIS)) and radar (TerraSAR-X) time series imagery to estimate the grassland biomass at two study sites (Moorepark and Grange) in the Republic of Ireland using both statistical and state of the art machine learning algorithms. High quality weather data available from the on-site weather station was also used to calculate the Growing Degree Days (GDD) for Grange to determine the impact of ancillary data on biomass estimation. In situ and satellite data covering 12 years for the Moorepark and 6 years for the Grange study sites were used to predict grassland biomass using multiple linear regression, Neuro Fuzzy Inference Systems (ANFIS) models. The results demonstrate that a dense (8-day composite) MODIS image time series, along with high quality in situ data, can be used to retrieve grassland biomass with high performance (R2 = 0:86; p < 0:05, RMSE = 11.07 for Moorepark). The model for Grange was modified to evaluate the synergistic use of vegetation indices derived from remote sensing time series and accumulated GDD information. As GDD is strongly linked to the plant development, or phonological stage, an improvement in biomass estimation would be expected. It was observed that using the ANFIS model the biomass estimation accuracy increased from R2 = 0:76 (p < 0:05) to R2 = 0:81 (p < 0:05) and the root mean square error was reduced by 2.72%. The work on the application of optical remote sensing was further developed using a TerraSAR-X Staring Spotlight mode time series over the Moorepark study site to explore the extent to which very high resolution Synthetic Aperture Radar (SAR) data of interferometrically coherent paddocks can be exploited to retrieve grassland biophysical parameters. After filtering out the non-coherent plots it is demonstrated that interferometric coherence can be used to retrieve grassland biophysical parameters (i. e., height, biomass), and that it is possible to detect changes due to the grass growth, and grazing and mowing events, when the temporal baseline is short (11 days). However, it not possible to automatically uniquely identify the cause of these changes based only on the SAR backscatter and coherence, due to the ambiguity caused by tall grass laid down due to the wind. Overall, the work presented in this dissertation has demonstrated the potential of dense remote sensing and weather data time series to predict grassland biomass using machine-learning algorithms, where high quality ground data were used for training. At present a major limitation for national scale biomass retrieval is the lack of spatial and temporal ground samples, which can be partially resolved by minor modifications in the existing PastureBaseIreland database by adding the location and extent ofeach grassland paddock in the database. As far as remote sensing data requirements are concerned, MODIS is useful for large scale evaluation but due to its coarse resolution it is not possible to detect the variations within the fields and between the fields at the farm scale. However, this issue will be resolved in terms of spatial resolution by the Sentinel-2 mission, and when both satellites (Sentinel-2A and Sentinel-2B) are operational the revisit time will reduce to 5 days, which together with Landsat-8, should enable sufficient cloud-free data for operational biomass estimation at a national scale. The Synthetic Aperture Radar Interferometry (InSAR) approach is feasible if there are enough coherent interferometric pairs available, however this is difficult to achieve due to the temporal decorrelation of the signal. For repeat-pass InSAR over a vegetated area even an 11 days temporal baseline is too large. In order to achieve better coherence a very high resolution is required at the cost of spatial coverage, which limits its scope for use in an operational context at a national scale. Future InSAR missions with pair acquisition in Tandem mode will minimize the temporal decorrelation over vegetation areas for more focused studies. The proposed approach complements the current paradigm of Big Data in Earth Observation, and illustrates the feasibility of integrating data from multiple sources. In future, this framework can be used to build an operational decision support system for retrieval of grassland biophysical parameters based on data from long term planned optical missions (e. g., Landsat, Sentinel) that will ensure the continuity of data acquisition. Similarly, Spanish X-band PAZ and TerraSAR-X2 missions will ensure the continuity of TerraSAR-X and COSMO-SkyMed.

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In recent years, nanoscience and nanotechnology has emerged as one of the most important and exciting frontier areas of research interest in almost all fields of science and technology. This technology provides the path of many breakthrough changes in the near future in many areas of advanced technological applications. Nanotechnology is an interdisciplinary area of research and development. The advent of nanotechnology in the modern times and the beginning of its systematic study can be thought of to have begun with a lecture by the famous physicist Richard Feynman. In 1960 he presented a visionary and prophetic lecture at the meeting of the American Physical Society entitled “there is plenty of room at the bottom” where he speculated on the possibility and potential of nanosized materials. Synthesis of nanomaterials and nanostructures are the essential aspects of nanotechnology. Studies on new physical properties and applications of nanomaterials are possible only when materials are made available with desired size, morphology, crystal structure and chemical composition. Cerium oxide (ceria) is one of the important functional materials with high mechanical strength, thermal stability, excellent optical properties, appreciable oxygen ion conductivity and oxygen storage capacity. Ceria finds a variety of applications in mechanical polishing of microelectronic devices, as catalysts for three-way automatic exhaust systems and as additives in ceramics and phosphors. The doped ceria usually has enhanced catalytic and electrical properties, which depend on a series of factors such as the particle size, the structural characteristics, morphology etc. Ceria based solid solutions have been widely identified as promising electrolytes for intermediate temperature solid oxide fuel cells (SOFC). The success of many promising device technologies depends on the suitable powder synthesis techniques. The challenge for introducing new nanopowder synthesis techniques is to preserve high material quality while attaining the desired composition. The method adopted should give reproducible powder properties, high yield and must be time and energy effective. The use of a variety of new materials in many technological applications has been realized through the use of thin films of these materials. Thus the development of any new material will have good application potential if it can be deposited in thin film form with the same properties. The advantageous properties of thin films include the possibility of tailoring the properties according to film thickness, small mass of the materials involved and high surface to volume ratio. The synthesis of polymer nanocomposites is an integral aspect of polymer nanotechnology. By inserting the nanometric inorganic compounds, the properties of polymers can be improved and this has a lot of applications depending upon the inorganic filler material present in the polymer.

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The aim of this paper is to show how principles of ecological psychology and dynamical systems theory can underpin a philosophy of coaching practice in a nonlinear pedagogy. Nonlinear pedagogy is based on a view of the human movement system as a nonlinear dynamical system. We demonstrate how this perspective of the human movement system can aid understanding of skill acquisition processes and underpin practice for sports coaches. We provide a description of nonlinear pedagogy followed by a consideration of some of the fundamental principles of ecological psychology and dynamical systems theory that underpin it as a coaching philosophy. We illustrate how each principle impacts on nonlinear pedagogical coaching practice, demonstrating how each principle can substantiate a framework for the coaching process.

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