Enhanced electromagnetic microwave absorption of Fe/C/SiCN composite ceramics targeting in integrated structure and function

The Fe/C/SiCN composite ceramics were synthesized by polymer-derived method to obtain the integration of structure and functions. The electromagnetic waves (EMW) absorption properties at X and Ku bands were investigated. The addition of nano-sized Fe particles improved the magnetic loss and impedance matching, and the carbon nanotubes generated by the iron in-situ catalysis increased the internal relaxation polarization and interfacial polarization, which together improved the EMW absorption properties significantly. In particular, the Fe/C/SiCN-9 showed the optimum reflection loss (RL) of ?31.06 dB at 10.03 GHz with an effective absorption bandwidth (EAB, RL < ?10 dB) of 3.03 GHz at 2.51 mm, indicating the excellent EMW absorption properties of Fe/C/SiCN composite ceramics.     

Unsupervised Segmentation of Stereoscopic Video Objects: Constrained Segmentation Fusion Versus Greedy Active Contours

In this paper, we present a novel memory access reduction scheme (MARS) for two-dimension fast cosine transform (2-D FCT). It targets programmable DSPs with high memory-access latency. It reduces the number of memory accesses by: 1) reducing the number of weighting factors and 2) combining butterflies in vector-radix 2-D FCT pruning diagram from two stages to one stage with an efficient structure. Hardware platform based on general purpose processor is used to verify the effectiveness of the proposed method for vector-radix 2-D FCT pruning implementation. Experimental results validate the benefits of the proposed method with reduced memory access, less clock cycle and fewer memory space compared with the conventional implementation.     

Generating Questions Based on Semi-Automated and End-to-End Neural Network

With the emergence of large-scale knowledge base, how to use triple information to generate natural questions is a key technology in question answering systems. The traditional way of generating questions require a lot of manual intervention and produce lots of noise. To solve these problems, we propose a joint model based on semi-automated model and End-to-End neural network to automatically generate questions. The semi-automated model can generate question templates and real questions combining the knowledge base and center graph. The End-to-End neural network directly sends the knowledge base and real questions to BiLSTM network. Meanwhile, the attention mechanism is utilized in the decoding layer, which makes the triples and generated questions more relevant. Finally, the experimental results on SimpleQuestions demonstrate the effectiveness of the proposed approach.     

How to Valorize Peanut Shells by a Simple Thermal-Catalytic Method

Topics in Catalysis - In this work, a simple thermal-catalytic system was used to valorize peanut shells (Arachis hypogaea), the residual biomass from the peanut industry. To accomplish this...     

Development of a new ion-imprinted polymer (IIP) with Cd2+ ions based on divinylbenzene copolymers containing amidoxime groups

Polymer Bulletin - In this study, we synthesized a new ion-imprinted polymer (IIP) based on introduction of amidoxime groups in acrylonitrile, complexation with Cd2+ ions and polymerization with...     

Heuristic Solution to the Diffraction Problem on a Superconducting Half-Plane

Journal of Communications Technology and Electronics - Abstract—The article presents a rigorous numerical solution, using the Wiener–Hopf method, to the problem of plane wave...