Current Issue : October - December Volume : 2020 Issue Number : 4 Articles : 5 Articles
The absorbent resin for Cu2+ removal was prepared under microwave irradiation through grafting acrylamide (AM) and acrylic\nacid (AA) to cellulose. The initiator is a kind of redox system composed of potassium persulfate/sodium thiosulfate. The\ncrosslinking agent is...................
This work focuses on brain stroke imaging via microwave technology. In particular,\nthe open issue of monitoring patients after stroke onset is addressed here in order to provide clinicians\nwith a tool to control the effectiveness of administered therapies during the follow-up period. In this\npaper, a novel prototype is presented and characterized. The device is based on a low-complexity\narchitecture which makes use of a minimum number of properly positioned and designed antennas\nplaced on a helmet. It exploits a differential imaging approach and provides 3D images of the\nstroke. Preliminary experiments involving a 3D phantom filled with brain tissue-mimicking\nliquid confirm the potential of the technology in imaging a spherical target mimicking a stroke\nof a radius equal to 1.25 cm....
convenient and fast microwave synthesis of gold-doped titanium dioxide materials was\ndeveloped with the aid of commercially available and common cyclodextrin derivatives, acting both\nas reducing and stabilizing agents. Anatase titanium oxide was synthesized from titanium chloride\nby microwave heating without calcination. Then, the resulting titanium oxide was decorated by\ngold nanoparticles thanks to a microwave-assisted reduction of HAuCl4 by cyclodextrin in alkaline\nconditions. The materials were fully characterized by UV-Vis spectroscopy, X-Ray Diffraction (XRD),\nTransmission Electron Microscopy (TEM), and N2 adsorption-desorption measurements, while the\nmetal content was determined by Inductively Coupled Plasma Optical Emission Spectroscopy............
For the optimal design of electromagnetic devices, it is the most time consuming to obtain the training samples from full wave\nelectromagnetic simulation software, including HFSS, CST, and IE3D. Traditional machine learning methods usually use only\nlabeled samples or unlabeled samples, but in practical problems, labeled samples and unlabeled samples coexist, and the acquisition\ncost of labeled samples is relatively high. This paper proposes a semisupervised learning Gaussian Process (GP), which\ncombines unlabeled samples to improve the accuracy of the GP model and reduce the number of labeled training samples\nrequired. The proposed GP model consists two parts: initial training and self-training. In the process of initial training, a small\nnumber of labeled samples obtained by full wave electromagnetic simulation are used for training the initial GP model. Afterwards,\nthe trained GP model is copied to another GP model in the process of self-training, and then the two GP models will\nupdate after crosstraining with different unlabeled samples. Using the same test samples for testing and updating, a model with a\nsmaller error will replace another. Repeat the self-training process until a predefined stopping criterion is met. Four different\nbenchmark functions and resonant frequency modeling problems of three different microstrip antennas are used to evaluate the\neffectiveness of the GP model. The results show that the proposed GP model has a good fitting effectiveness on benchmark\nfunctions. For microstrip antennas resonant frequency modeling problems, in the case of using the same labeled samples, its\npredictive ability is better than that of the traditional supervised GP model....
A novel approach, using low Earth orbit (LEO) satellite microwave communication links\nfor cloud liquid water measurements, is proposed in this paper. The feasibility of this approach\nis studied through simulations of the retrieval system including a LEO satellite communicating\nwith a group of ground receivers equipped with signal-to-noise ratio (SNR) estimators, a synthetic\ncloud attenuation field and a tomographic retrieval algorithm. Rectangular and Gaussian basis\nfunctions are considered to define the targeted field. Simulation results suggest that the proposed\nleast-squares based retrieval algorithm produces satisfactory outcomes for both types of basis\nfunctions. The root-mean-square error of the retrieved field is around 0.2 dB/km, with the range of\nthe reference field as 0 to 2.35 dB/km. It is also confirmed that the partial retrieval of the cloud field is\nachievable when a limited number of receivers with restricted locations are available. The retrieval\noutcomes exhibit properties of high resolution and low error, indicating that the proposed approach\nhas great potential for cloud observations....
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