The possibility of reducing structural response under external excitations such as earthquakes and wind storms via control systems is attracting the interest of a large number of researchers. In the field of civil str...
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ISBN:
(纸本)9781479949885
The possibility of reducing structural response under external excitations such as earthquakes and wind storms via control systems is attracting the interest of a large number of researchers. In the field of civil structures, control systems based on semi-active (SA) devices seem to be close to feasible implementation. Semi-active devices are typically passive elements capable of self-adjusting their own mechanical properties according to the instantaneous response of the hosting structure and, therefore, they can be considered as smart devices. Dampers based on magnetorheological fluids are considered very effective in practical implementations. This paper aims to show the potential of such devices to reduce the seismic response of structures exploiting some information provide by a seismic early warning system (SEWS). Current research on SEWS include the anticipate estimate of the peak ground acceleration (PGA) of the incoming earthquake. The paper focuses on the control algorithm needed to select the optimal voltage to set the variable devices according to the PGA estimate. The authors found that the different characteristics of earthquakes, that occur on different sites, such as frequency content, duration and magnitude, play a significant role in the definition of the best control algorithm. For this reason, a regional control algorithm has been built for each of three selected worldwide regions (Japan, California and Italy).
Standard ocean color data products from the Medium Resolution Imaging Spectrometer (MERIS) are compared with equivalent regional products in European seas exhibiting different bio-optical properties: the northern Adri...
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Standard ocean color data products from the Medium Resolution Imaging Spectrometer (MERIS) are compared with equivalent regional products in European seas exhibiting different bio-optical properties: the northern Adriatic Sea, the Baltic Sea and the Western Black Sea (ADRS, BLTS and BLKS, respectively). Investigated quantities are: 1) the algal-2 pigment index, alg2;2) the composite-absorption coefficient of yellow substance and non-pigmented particles at 442 nm, a(dg);and 3) the concentration of the total suspended matter, TSM. regional data products are created using ocean color inversion schemes based on MultiLayer Perceptron (MLP) neural nets trained with field measurements from the Coastal Atmosphere and Sea Time Series (CoASTS) and Bio-Optical mapping of Marine Properties (BiOMaP) programs. MLP input is the remote sensing reflectance Res at MERIS center-wavelengths specifically selected for different water types in view of minimizing the perturbing effects of inaccurate atmospheric correction on the retrieval of regional data products. A new method is also proposed to define the applicability of regional MLPs to input Res. Results indicate that MERIS alg2 values tend to overestimate the equivalent quantity computed with MLP regional algorithms. The agreement between MERIS and regional TSM data products is significantly better than that reported for alg2 and ad, especially for BLKS. Findings highlight the relevance of using regional inversion schemes to evaluate standard products over extended oceanographic regions as a complement to the analysis of match-ups between marine products measured in situ and derived from space-born data. (C) 2013 Elsevier Inc. All rights reserved.
Multilayer perceptron (MLP) neural networks for regional satellite ocean color applications have been developed and assessed using in situ data from various European seas. Considered MLP products are chlorophyll a con...
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Multilayer perceptron (MLP) neural networks for regional satellite ocean color applications have been developed and assessed using in situ data from various European seas. Considered MLP products are chlorophyll a concentration (Chl-a), absorption by yellow substance at 412 nm (a(ys)(412)) and concentration of total suspended matter (TSM), all determined from spectral remote sensing reflectance R-RS. Investigated oceanographic regions comprise the Eastern Mediterranean Sea, the northern Adriatic Sea, the Westem Black Sea and the Baltic Sea. The in situ measurements applied in the study were produced within the framework of the Coastal Atmosphere and Sea Time Series (COASTS) and Rio-Optical Mapping of Marine Properties (BiOMaP) programs contributing to a unique dataset that represents different water types including chlorophyll a, yellow substance and sediment dominated waters. Performance analysis of the proposed regional MLPs indicates that Chl-a can be quantified with the highest accuracy in the Eastern Mediterranean Sea (with absolute percent difference of 14% with respect to in situ measurements). In the case of a(ys)(412), the most accurate determination is observed for the Baltic Sea waters (13%). Instead, TSM retrieval is the most accurate in the Black Sea (14%). The study demonstrated the limited generalization capability of regional algorithms. Within this context, saturation of MLP output occurring with input data not statistically represented in the training set has been investigated through cross-basin product analysis in view of proposing a practical solution to the problem. (C) 2012 Elsevier Inc. All rights reserved.
In synthetic aperture radar (SAR) image segmentation field, regional algorithms have shown great potential for image segmentation. The SAR images have a multiplicity of complex texture, which are difficult to be divid...
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In synthetic aperture radar (SAR) image segmentation field, regional algorithms have shown great potential for image segmentation. The SAR images have a multiplicity of complex texture, which are difficult to be divided as a whole. Existing algorithm may cause mixed super-pixels with different labels due to speckle noise. This study presents the technique based on organization evolution (OEA) algorithm to improve ISODATA in pixels. This approach effectively filters out the useless local information and successfully introduces the effective information. To verify the accuracy of OEA-ISO data algorithm, the segmentation effect of this algorithm is tested on SAR image and compared with other techniques. The results demonstrate that the OEA-ISO data algorithm is 10.16% more accurate than the WIPFCM algorithm, 23% more accurate than the K-means algorithm, and 27.14% more accurate than the fuzzy C-means algorithm in the light-colored farmland category. It can be seen that the OEA-ISO data algorithm introduces the pixel block strategy, which successfully reduces the noise interference in the image, and the effect is more obvious when the image background is complex.
Launched on 15 November 2017, China's FengYun-3D (FY-3D) has taken over prime operational weather service from the aging FengYun-3B (FY-3B). Rather than directly implementing an FY-3B operational snow depth retrie...
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Launched on 15 November 2017, China's FengYun-3D (FY-3D) has taken over prime operational weather service from the aging FengYun-3B (FY-3B). Rather than directly implementing an FY-3B operational snow depth retrieval algorithm on FY-3D, we investigated this and four other well-known snow depth algorithms with respect to regional uncertainties in China. Applicable to various passive microwave sensors, these four snow depth algorithms are the Environmental and Ecological Science Data Centre of Western China (WESTDC) algorithm, the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) algorithm, the Chang algorithm, and the Foster algorithm. Among these algorithms, validation results indicate that FY-3B and WESTDC perform better than the others. However, these two algorithms often result in considerable underestimation for deep snowpack (greater than 20 cm), while the other three persistently overestimate snow depth, probably because of their poor representation of snowpack characteristics in China. To overcome the retrieval errors that occur under deep snowpack conditions without sacrificing performance under relatively thin snowpack conditions, we developed an empirical snow depth retrieval algorithm suite for the FY-3D satellite. Independent evaluation using weather station observations in 2014 and 2015 demonstrates that the FY-3D snow depth algorithm's root mean square error (RMSE) and bias are 6.6 cm and 0.2 cm, respectively, and it has advantages over other similar algorithms.
A relevant indicator for the eutrophication status in the Baltic Sea is the Chlorophyll-a concentration (Chl-a). Alas, ocean color remote sensing applications to estimate Chl-a in this brackish basin, characterized by...
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A relevant indicator for the eutrophication status in the Baltic Sea is the Chlorophyll-a concentration (Chl-a). Alas, ocean color remote sensing applications to estimate Chl-a in this brackish basin, characterized by large gradients in salinity and dissolved organic matter, are hampered by its optical complexity and atmospheric correction limits. This study presents Chl-a retrieval improvements for a fully reprocessed multi-sensor time series of remote-sensing reflectances (R-rs) at similar to 1 km spatial resolution for the Baltic Sea. A new ensemble scheme based on multilayer perceptron neural net (MLP) bio-optical algorithms has been implemented to this end. The study documents that this approach outperforms band-ratio algorithms when compared to in situ datasets, reducing the gross overestimates of Chl-a observed in the literature for this basin. The R-rs and Chl-a time series were then exploited for eutrophication monitoring, providing a quantitative description of spring and summer phytoplankton blooms in the Baltic Sea over 1998-2019. The analysis of the phytoplankton dynamics enabled the identification of the latitudinal variations in the spring bloom phenology across the basin, the early blooming in spring in the last two decades, and the description of the spatiotemporal coverage of summer cyanobacterial blooms in the central and southern Baltic Sea.
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