Multi-fractal analysis of weighted networks

In many real complex networks, the fractal and self-similarity properties have been found. The fractal dimension is a useful method to describe fractal property of complex networks. Fractal analysis is inadequate if only taking one fractal dimension to study complex networks. In this case, multifractal analysis of complex networks are concerned. However, multifractal dimension of weighted networks are less involved. In this paper, multifractal dimension of weighted networks is proposed based on box-covering algorithm for fractal dimension of weighted networks (BCANw). The proposed method is applied to calculate the fractal dimensions of some real networks. Our numerical results indicate that the proposed method is efficient for analysis fractal property of weighted networks

Self-protected nanoscale thermometry based on spin defects in silicon carbide

Quantum sensors with solid state electron spins have attracted considerable interest due to their nanoscale spatial resolution.A critical requirement is to suppress the environment noise of the solid state spin sensor.Here we demonstrate a nanoscale thermometer based on silicon carbide (SiC) electron spins.We experimentally demonstrate that the performance of the spin sensor is robust against dephasing due to a self protected machenism. The SiC thermometry may provide a promising platform for sensing in a noisy environment ,e.g. biological system sensing

Surface-induced brightness temperature variations and their effects on detecting thin cirrus clouds using IR emission channels in the 8-12 micrometer region

A method for detecting cirrus clouds in terms of brightness temperature differences between narrow bands at 8, 11, and 12 mu m has been proposed by Ackerman et al. (1990). In this method, the variation of emissivity with wavelength for different surface targets was not taken into consideration. Based on state-of-the-art laboratory measurements of reflectance spectra of terrestrial materials by Salisbury and D'Aria (1992), we have found that the brightness temperature differences between the 8 and 11 mu m bands for soils, rocks and minerals, and dry vegetation can vary between approximately -8 K and +8 K due solely to surface emissivity variations. We conclude that although the method of Ackerman et al. is useful for detecting cirrus clouds over areas covered by green vegetation, water, and ice, it is less effective for detecting cirrus clouds over areas covered by bare soils, rocks and minerals, and dry vegetation. In addition, we recommend that in future the variation of surface emissivity with wavelength should be taken into account in algorithms for retrieving surface temperatures and low-level atmospheric temperature and water vapor profiles

A linear spectral matching technique for retrieving equivalent water thickness and biochemical constituents of green vegetation

Over the last decade, technological advances in airborne imaging spectrometers, having spectral resolution comparable with laboratory spectrometers, have made it possible to estimate biochemical constituents of vegetation canopies. Wessman estimated lignin concentration from data acquired with NASA's Airborne Imaging Spectrometer (AIS) over Blackhawk Island in Wisconsin. A stepwise linear regression technique was used to determine the single spectral channel or channels in the AIS data that best correlated with measured lignin contents using chemical methods. The regression technique does not take advantage of the spectral shape of the lignin reflectance feature as a diagnostic tool nor the increased discrimination among other leaf components with overlapping spectral features. A nonlinear least squares spectral matching technique was recently reported for deriving both the equivalent water thicknesses of surface vegetation and the amounts of water vapor in the atmosphere from contiguous spectra measured with the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). The same technique was applied to a laboratory reflectance spectrum of fresh, green leaves. The result demonstrates that the fresh leaf spectrum in the 1.0-2.5 microns region consists of spectral components of dry leaves and the spectral component of liquid water. A linear least squares spectral matching technique for retrieving equivalent water thickness and biochemical components of green vegetation is described

Separation of cirrus cloud from clear surface from AVIRIS data using the 1.38 micron water vapor band

Cirrus clouds play an important role in climate systems because of their large area coverage, persistence, and radiative effects. Thin cirrus clouds are difficult to detect in visible images and infrared images in the 10-12 micron atmospheric window region, particularly over land, because these clouds are partially transparent. Ackerman recently developed a method for detecting cirrus clouds using three narrow channels centered near 8, 11, and 12 microns, respectively, based on the analysis of IR emission spectra measured with a high spectral resolution interferometer. Barton also described a method for estimating cirrus cloud height and amount from measurements with two narrow channel radiometers of the Selective Chopper Radiometer on Nimbus 5. Both channels are located within the strong 2.7 micron water vapor band absorption region. One of the channels includes additional carbon dioxide absorption. A differential absorption technique with sets of empirical coefficients was used in the estimation of cirrus cloud heights and amounts. A technique using narrow channels in the strong 1.38 micron water vapor band absorption region for detecting cirrus clouds from spectral imaging data acquired by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) on 5 Dec. 1991 during the FIRE (The First International Satellite Cloud Climatology Project (ISCCP) Regional Experiment) Phase 2 Field Experiment is described

Remote sensing of smoke, clouds, and radiation using AVIRIS during SCAR experiments

During the past two years, researchers from several institutes joined together to take part in two SCAR experiments. The SCAR-A (Sulfates, Clouds And Radiation - Atlantic) took place in the mid-Atlantic region of the United States in July, 1993. remote sensing data were acquired with the Airborne Visible Infrared Imaging Spectrometer (AVIRIS), the MODIS Airborne Simulator (MAS), and a RC-10 mapping camera from an ER-2 aircraft at 20 km. In situ measurements of aerosol and cloud microphysical properties were made with a variety of instruments equipped on the University of Washington's C-131A research aircraft. Ground based measurements of aerosol optical depths and particle size distributions were made using a network of sunphotometers. The main purpose of SCAR-A experiment was to study the optical, physical and chemical properties of sulfate aerosols and their interaction with clouds and radiation. Sulfate particles are believed to affect the energy balance of the earth by directly reflecting solar radiation back to space and by increasing the cloud albedo. The SCAR-C (Smoke, Clouds And Radiation - California) took place on the west coast areas during September - October of 1994. Sets of aircraft and ground-based instruments, similar to those used during SCAR-A, were used during SCAR-C. Remote sensing of fires and smoke from AVIRIS and MAS imagers on the ER-2 aircraft was combined with a complete in situ characterization of the aerosol and trace gases from the C-131A aircraft of the University of Washington and the Cesna aircraft from the U.S. Forest Service. The comprehensive data base acquired during SCAR-A and SCAR-C will contribute to a better understanding of the role of clouds and aerosols in global change studies. The data will also be used to develop satellite remote sensing algorithms from MODIS on the Earth Observing System

Remote sensing of smoke, clouds, and fire using AVIRIS data

Clouds remain the greatest element of uncertainty in predicting global climate change. During deforestation and biomass burning processes, a variety of atmospheric gases, including CO2 and SO2, and smoke particles are released into the atmosphere. The smoke particles can have important effects on the formation of clouds because of the increased concentration of cloud condensation nuclei. They can also affect cloud albedo through changes in cloud microphysical properties. Recently, great interest has arisen in understanding the interaction between smoke particles and clouds. We describe our studies of smoke, clouds, and fire using the high spatial and spectral resolution data acquired with the NASA/JPL Airborne Visible/Infrared Imaging Spectrometer (AVIRIS)

Software for the derivation of scaled surface reflectances from AVIRIS data

An operational software program is now available for deriving 'scaled surface reflectances' from spectral data collected by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). The program simulates both the atmospheric scattering and absorption effects. Brief descriptions of the algorithm, inputs, outputs, the limitations of the software, and procedures for obtaining the software are given

Research on Dual-Variable Integrated Electro-Hydrostatic Actuator

AbstractThe integrated electro-hydrostatic actuator (EHA) with variable displacement and variable rotation speed is researched. In the system, the output of the actuator is changed by controlling the rotation speed of the brushless DC servomotor and the displacement of the servopump. The mathematical model described in state space model is created. The system characteristics are studied based on the point of multiplicative dual variable. And the basic method of control of the system is presented