88 research outputs found
Cloaking and imaging at the same time
In this letter, we propose a conceptual device to perform subwavelength
imaging with positive refraction. The key to this proposal is that a drain is
no longer a must for some cases. What's more, this device is an isotropic
omnidirectional cloak with a perfect electric conductor hiding region and shows
versatile illusion optical effects. Numerical simulations are performed to
verify the functionalities.Comment: 15 pages, 4 figure
Remote Sensing of Soil Alkalinity and Salinity in the Wuyu’er-Shuangyang River Basin, Northeast China
The Songnen Plain of the Northeast China is one of the three largest soda saline-alkali regions worldwide. To better understand soil alkalinization and salinization in this important agricultural region, it is vital to explore the distribution and variation of soil alkalinity and salinity in space and time. This study examined soil properties and identified the variables to extract soil alkalinity and salinity via physico-chemical, statistical, spectral, and image analysis. The physico-chemical and statistical results suggested that alkaline soils, coming from the main solute Na2CO3 and NaHCO3 in parent rocks, characterized the study area. The pH and electric conductivity (EC ) were correlated with both narrow band and broad band reflectance. For soil pH, the sensitive bands were in short wavelength (VIS) and the band with the highest correlation was 475 nm (r = 0.84). For soil EC, the sensitive bands were also in VIS and the band with the highest correlation was 354 nm (r = 0.84). With the stepwise regression, it was found that the pH was sensitive to reflectance of OLI band 2 and band 6, while the EC was only sensitive to band 1. The R2Adj (0.73 and 0.72) and root mean square error (RMSE) (0.98 and 1.07 dS/m) indicated that, the two stepwise regression models could estimate soil alkalinity and salinity with a considerable accuracy. Spatial distributions of soil alkalinity and salinity were mapped from the OLI image with the RMSE of 1.01 and 0.64 dS/m, respectively. Soil alkalinity was related to salinity but most soils in the study area were non-saline soils. The area of alkaline soils was 44.46% of the basin. Highly alkaline soils were close to the Zhalong wetland and downstream of rivers, which could become a severe concern for crop productivity in this area
Comparative Profiling of Triple-Negative Breast Carcinomas Tissue Glycoproteome by Sequential Purification of Glycoproteins and Stable Isotope Labeling
Hybrid Nanomaterials Based on Graphene and Gold Nanoclusters for Efficient Electrocatalytic Reduction of Oxygen
The Design and Fabrication of a MEMS Electronic Calibration Chip
During the test of microelectromechanical system (MEMS) devices, calibration of test cables, loads and test instruments is an indispensable step. Calibration kits with high accuracy, great operability and small loss can reduce the systematic errors in the test process to the greatest extent and improve the measurement accuracy. Aiming at the issues of the conventional discrete calibration piece unit, which presents cumbersome calibration steps and large system loss, an integrated electronic calibration chip based on frequency microelectromechanical system (RF MEMS) switches is designed and fabricated. The short-open-load-through (SOLT) calibration states can be completed on a single chip, step by step, by adjusting the on–off state of the RF MEMS switches. The simulation results show that the operating frequency of the electronic calibration piece covers the range of DC~26.5 GHz, the insertion loss in through (thru) state is less than 0.2 dB, the return loss is less than 1.0 dB in short-circuit and open-circuit states, the return loss under load-circuit state is less than 20 dB and its size is only 2.748 mm × 2.2 mm × 0.5 mm. This novel calibration chip design has certain esteem for advancing calibration exactness and effectiveness
SAR and optical images registration using uniform distribution and structure description-based ASIFT
Aiming at the problems of nonlinear gray difference, speckle noise and different imaging viewpoints in SAR and optical image registration, this paper presents a SAR and optical images registration using uniform distribution and structure description-based ASIFT. In the proposed algorithm, firstly, the guided scale space is constructed by guided filter to achieve noise suppression and edge preservation. In the feature extraction stage, the phase congruency is utilized due to the nonlinear gray difference, and combined with scale space gridding to extract from images for the uniform feature points. In the feature description stage, the consistency gradient magnitude and orientation of SAR and optical image are calculated by extended phase congruency method, which improves the accuracy of the main orientation and descriptor. At last, Optimal-RANSAC is used to establish feature descriptor matching to achieve effective registration. The simulation experiment and analysis on four pairs of real images show that the proposed algorithm has more accurate registration accuracy than SAR-SIFT and traditional ASIFT
A Knowledge-Aware Attentional Reasoning Network for Recommendation
Knowledge-graph-aware recommendation systems have increasingly attracted attention in both industry and academic recently. Many existing knowledge-aware recommendation methods have achieved better performance, which usually perform recommendation by reasoning on the paths between users and items in knowledge graphs. However, they ignore the users' personal clicked history sequences that can better reflect users' preferences within a period of time for recommendation. In this paper, we propose a knowledge-aware attentional reasoning network KARN that incorporates the users' clicked history sequences and path connectivity between users and items for recommendation. The proposed KARN not only develops an attention-based RNN to capture the user's history interests from the user's clicked history sequences, but also a hierarchical attentional neural network to reason on paths between users and items for inferring the potential user intents on items. Based on both user's history interest and potential intent, KARN can predict the clicking probability of the user with respective to a candidate item. We conduct experiment on Amazon review dataset, and the experimental results demonstrate the superiority and effectiveness of our proposed KARN model
Design of a Ka-Band Five-Bit MEMS Delay with a Coplanar Waveguide Loaded U-Shaped Slit
This paper designs a five-bit microelectromechanical system (MEMS) time delay consisting of a single-pole six-throw (SP6T) RF switch and a coplanar waveguide (CPW) microstrip line. The focus is on the switch upper electrode design, power divider design, transmission line corner compensation structure design, CPW loading U-shaped slit structure design, and system simulation. The switch adopts a triangular upper electrode structure to reduce the cantilever beam equivalent elastic coefficient and the closed contact area to achieve low drive voltage and high isolation. The SP6T RF MEMS switch uses a disc-type power divider to achieve consistent RF performance across the output ports. When designed by loading U-shaped slit on transmission lines and step-compensated tangents at corners, the system loss is reduced, and the delay amount is improved. In addition, the overall size of the device is 2.1 mm × 2.4 mm × 0.5 mm, simulation results show that the device has a delay amount of 0–60 ps in the frequency range of 26.5–40 GHz, the delay accuracy at the center frequency is better than 0.63 ps, the delay error in the whole frequency band is less than 22.2%, the maximum insertion loss is 3.69 dB, and the input–output return rejection is better than 21.54 dB
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