Characterization and humidity sensing properties of Bi0.5Na0.5TiO3-Bi0.5K0.5TiO3 powder synthesized by metal-organic decomposition

Bi_0.5Na_0.5TiO₃-Bi_0.5K_0.5TiO₃ (BNT-BKT) powder is synthesized by a metal-organic decomposition method and characterized by field-emission scanning electron microscopy (FE-SEM), transmission electron microscopy (TEM), and X-ray diffraction (XRD). A humidity sensor, which is consisted of five pairs of Ag-Pd interdigitated electrodes and an Al₂O₃ ceramic substrate, is fabricated by spin-coating the BNT-BKT powder on the substrate. Good humidity sensing properties such as high response value, short response and recovery times, and small hysteresis are observed in the sensing measurement. The impedance changes more than four orders of magnitude within the whole humidity range from 11% to 95% relative humidity (RH) at 100 Hz. The response time and recovery time are about 20 and 60 s, respectively. The maximum hysteresis is around 4% RH. The results indicate that BNT-BKT powder is of potential applications for fabricating high performance humidity sensors.     

Irreversible sensing of oxygen ingress

Absorption-based opto-chemical sensors for oxygen are presented that consist of leuco dyes (leuco indigo and leuco thioindigo) incorporated into two kinds of polymer matrices. An irreversible and visible color change (to red or blue) is caused by a chromogenic chemistry involving the oxidation of the (virtually colorless) leuco dyes by molecular oxygen. The moderately gas permeable copolymer poly(styrene-co-acrylonitrile) and a highly oxygen-permeable polyurethane hydrogel, respectively, are used in order to increase the effective dynamic range for visualizing and detecting oxygen. We describe the preparation and properties of four different types of such oxygen sensors that are obtained by dip-coating a gas impermeable foil made from poly(ethylene terephthalate) with a sensor layer composed of leuco dye and polymer.     

Effect of micro-electrode geometry on NO2 gas-sensing characteristics of one-dimensional tin dioxide nanostructure microsensors

Electrodes with micro-gaps are fabricated by using dc-sputtering and FIB techniques. SnO₂ nanowires are deposited on the micro-gap (1-30 μm) by suspension dropping method to fabricate a micro-gas sensor. The sensing ability of various SnO₂ micro-gap sensors is measured. A comparison between sensors reveals that the short-gap electrode has numerous advantages in terms of reliability, high sensitivity and detection of low concentrations of NO₂, while the large-gap electrode is relatively sensitive for high concentrations. Conductance measurements are carried out at different surface temperatures and NO₂ concentrations in order to investigate the effects that the gap size has on the overall sensor conductance. The results suggest that the interface between the electrode and sensitive layer has a very important role for the sensing mechanism of tin dioxide gas sensors.     

Temperature dependent H2S and Cl2 sensing selectivity of Cr2O3 thin films

The conductometric gas sensing characteristics of Cr₂O₃ thin films - prepared by electron-beam deposition of Cr films on quartz substrate followed by oxygen annealing - have been investigated for a host of gases (CH₄, CO, NO₂, Cl₂, NH₃ and H₂S) as a function of operating temperature (between 30 and 300 °C) and gas concentration (1-30 ppm). We demonstrate that these films are highly selective to H₂S at an operating temperature of 100 °C, while at 220 °C the films become selective to Cl₂. This result has been explained on the basis of depletion of chemisorbed oxygen from the surface of films due to temperature and/or interaction with Cl₂/H₂S, which is supported experimentally by carrying out the work function measurements using Kelvin probe method. The temperature dependent selectivity of Cr₂O₃ thin films provides a flexibility to use same film for the sensing of Cl₂ as well as H₂S.     

High-sensitivity NO2 gas sensors based on flower-like and tube-like ZnO nanomaterials

Hierarchical flower-like and 1D tube-like ZnO architectures were synthesized by a microemulsion-based solvothermal method. Technologies of XRD, SEM and TEM were used to characterize the morphological and structural properties of the products. The influence of the flower-like and tube-like morphologies on their NO₂ sensing properties was investigated. The experimental results showed that high-sensitivity NO₂ gas sensors were fabricated. The sensitivity of the tube-like ZnO gas sensor was much higher than that of the flower-like ZnO gas sensor and the tube-like ZnO gas sensor exhibited shorter response time. The in situ diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) technique was employed to investigate the NO₂ sensing mechanisms. Free nitrate ions, nitrate and nitrite were the main adsorbed species during the adsorption, and NO also existed in the initial period of surface reoxidation. Furthermore, N₂O was formed via NO⁻ and N₂O₂⁻ stemmed from NO and increased upon rising temperature. Moreover, the PL spectra and the XPS spectra further proved that the intensity of donors (oxygen vacancy (V_O) and zinc interstitial (Zn_i)) and surface oxygen species (O₂⁻ and O₂) involved in the gas sensing mechanism leaded to the different sensitivities.     

改进的证据理论在合作频谱感知中的应用

为了能够在认知无线电网络中有效、准确地检测出授权用户,提出了基于改进的证据理论的合作频谱感知方案设计方法.根据各个次用户对授权用户进行多次本地检测得出的时域DS融合结果,设计并改进融合顺序和融合结构,将多个时域DS融合结果送到融合中心进行空域DS融合,得到最终判决.在此基础上,给出了融合顺序、融合结构的改变对算法性能的...     

高分辨率遥感卫星数据传输中信道编码技术分析与研究

根据RS编译码原理,结合高分辨率遥感卫星在轨影像实际数据压缩情况,提出将RS(255,243)和RS(34,26)两种编码算法进行联合使用的方案,以解决数据传输中误码问题,仿真试验证明该方法在解决有干扰条件下的星地数据传输时,可有效防止和减少误码扩散。     

A genetic algorithm with gene rearrangement for K-means clustering

In this paper, a new clustering algorithm based on genetic algorithm (GA) with gene rearrangement (GAGR) is proposed, which in application may effectively remove the degeneracy for the purpose of a more efficient search. A new crossover operator that exploits a measure of similarity between chromosomes in a population is also presented. Adaptive probabilities of crossover and mutation are employed to prevent the convergence of the GAGR to a local optimum. Using the real-world data sets, we compare the performance of our GAGR clustering algorithm with K-means algorithm and other GA methods. An application of the GAGR clustering algorithm in unsupervised classification of multispectral remote sensing images is also provided. Experiment results demonstrate that the GAGR clustering algorithm has high performance, effectiveness and flexibility.     

The CM-SAF operational scheme for the satellite based retrieval of solar surface irradiance — A LUT based eigenvector hybrid approach

The radiation budget at the earth surface is an essential climate variable for climate monitoring and analysis as well as for verification of climate model output and reanalysis data. Accurate solar surface irradiance data is a prerequisite for an accurate estimation of the radiation budget and for an efficient planning and operation of solar energy systems.This paper describes a new approach for the retrieval of the solar surface irradiance from satellite data. The method is based on radiative transfer modelling and enables the use of extended information about the atmospheric state. Accurate analysis of the interaction between the atmosphere, surface albedo, transmission and the top of atmosphere albedo has been the basis for the new method, characterised by a combination of parameterisations and “eigenvector” look-up tables. The method is characterised by a high computing performance combined with a high accuracy. The performed validation shows that the mean absolute deviation is of the same magnitude as the confidence level of the BSRN (Baseline Surface Radiation Measurement) ground based measurements and significant lower as the CM-SAF (Climate Monitoring Satellite Application Facility) target accuracy of 10 W/m². The mean absolute difference between monthly means of ground measurements and satellite based solar surface irradiance is 5 W/m² with a mean bias deviation of − 1 W/m² and a RMSD (Root Mean Square Deviation) of 5.4 W/m² for the investigated European sites. The results for the investigated African sites obtained by comparing instantaneous values are also encouraging. The mean absolute difference is with 2.8% even lower as for the European sites being 3.9%, but the mean bias deviation is with − 1.1% slightly higher as for the European sites, being 0.8%. Validation results over the ocean in the Mediterranean Sea using shipboard data complete the validation. The mean bias is − 3.6 W/m² and 2.3% respectively. The slightly higher mean bias deviation over ocean is at least partly resulting from inherent differences due to the movement of the ship (shadowing, allocation of satellite pixel). The validation results demonstrate that the high accuracy of the surface solar irradiance is given in different climate regions. The discussed method has also the potential to improve the treatment of radiation processes in climate and Numerical Weather Prediction (NWP) models, because of the high accuracy combined with a high computing speed.     

An assessment of photosynthetic light use efficiency from space: Modeling the atmospheric and directional impacts on PRI reflectance

Estimation of photosynthetic light use efficiency (ε) from satellite observations is an important component of climate change research. The photochemical reflectance index, a narrow waveband index based on the reflectance at 531 and 570 nm, allows sampling of the photosynthetic activity of leaves; upscaling of these measurements to landscape and global scales, however, remains challenging. Only a few studies have used spaceborne observations of PRI so far, and research has largely focused on the MODIS sensor. Its daily global coverage and the capacity to detect a narrow reflectance band at 531 nm make it the best available choice for sensing ε from space. Previous results however, have identified a number of key issues with MODIS-based observations of PRI. First, the differences between the footprint of eddy covariance (EC) measurements and the MODIS footprint, which is determined by the sensor's observation geometry make a direct comparison between both data sources challenging and second, the PRI reflectance bands are affected by atmospheric scattering effects confounding the existing physiological signal. In this study we introduce a new approach for upscaling EC based ε measurements to MODIS. First, EC-measured ε values were “translated” into a tower-level optical PRI signal using AMSPEC, an automated multi-angular, tower-based spectroradiometer instrument. AMSPEC enabled us to adjust tower-measured PRI values to the individual viewing geometry of each MODIS overpass. Second, MODIS data were atmospherically corrected using a Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm, which uses a time series approach and an image-based rather than pixel-based processing for simultaneous retrievals of atmospheric aerosol and surface bidirectional reflectance (BRDF). Using this approach, we found a strong relationship between tower-based and spaceborne reflectance measurements (r² = 0.74, p < 0.01) throughout the vegetation period of 2006. Swath (non-gridded) observations yielded stronger correlations than gridded data (r² = 0.58, p < 0.01) both of which included forward and backscatter observations. Spaceborne PRI values were strongly related to canopy shadow fractions and varied with different levels of ε. We conclude that MAIAC-corrected MODIS observations were able to track the site-level physiological changes from space throughout the observation period.