Degradation of acephate using combined ultrasonic and ozonation method

The degradation of acephate in aqueous solutions was investigated with the ultrasonic and ozonation methods, as well as a combination of both. An experimental facility was designed and operation parameters such as the ultrasonic power, temperature, and gas flow rate were strictly controlled at constant levels. The frequency of the ultrasonic wave was 160 kHz. The ultraviolet-visible （UV-Vis） spectroscopic and Raman spectroscopic techniques were used in the experiment. The UV-Vis spectroscopic results show that ultrasonication and ozonation have a syn- ergistic effect in the combined system. The degradation efficiency of acephate increases from 60.6% to 87.6% after the solution is irradiated by a 160 kHz ultrasonic wave for 60 min in the ozonation process, and it is higher with the combined method than the sum of the separated ultrasonic and ozonation methods. Raman spectra studies show that degradation via the combined ultrasonic/ozonation method is more thorough than photocatalysis. The oxidability of nitrogen atoms is promoted under ultrasonic waves. Changes of the inorganic ions and degradation pathway during the degradation process were investigated in this study. Most final products are innocuous to the environment.

Time difference based measurement of ultrasonic cavitations in wastewater treatment

Intensity of cavitation is significant in ultrasonic wastewater treatment,but is complicated to measure.A time difference based method of ultrasonic cavitation measurement is proposed.The time differences at different powers of 495 kHz ultrasonic are measured in experiment in comparison with conductimetric method.Simulation results show that time difference and electrical conductivity are both approximately positive proportional to the ultrasonic power.The degradation of PNP solution verifies the availability in wastewater treatment by using ultrasonic.

Image Denoising with Adaptive Weighted Graph Filtering

Graph filtering,which is founded on the theory of graph signal processing,is proved as a useful tool for image denoising.Most graph filtering methods focus on learning an ideal lowpass filter to remove noise,where clean images are restored from noisy ones by retaining the image components in low graph frequency bands.However,this lowpass filter has limited ability to separate the low-frequency noise from clean images such that it makes the denoising procedure less effective.To address this issue,we propose an adaptive weighted graph filtering(AWGF)method to replace the design of traditional ideal lowpass filter.In detail,we reassess the existing low-rank denoising method with adaptive regularizer learning(ARLLR)from the view of graph filtering.A shrinkage approach subsequently is presented on the graph frequency domain,where the components of noisy image are adaptively decreased in each band by calculating their component significances.As a result,it makes the proposed graph filtering more explainable and suitable for denoising.Meanwhile,we demonstrate a graph filter under the constraint of subspace representation is employed in the ARLLR method.Therefore,ARLLR can be treated as a special form of graph filtering.It not only enriches the theory of graph filtering,but also builds a bridge from the low-rank methods to the graph filtering methods.In the experiments,we perform the AWGF method with a graph filter generated by the classical graph Laplacian matrix.The results show our method can achieve a comparable denoising performance with several state-of-the-art denoising methods.

Leaky Interface Wave Measurement at a Solid-Solid Interface with Laser Ultrasonics

The experimental investigation on transparent solid/solid(aluminum and plexiglas)interface leaky waves generated by a pulse laser and detected with a photoelastic effect technique is reported.Three waves,i.e.,longitudinal head wave,leaky Rayleigh wave and leaky interface wave,are detected successfully.The leaky waves propagating along the'weak bonding'interface are also measured.It is found that with the continuing epoxy solidification,the wave amplitude gradually decreases and the two leaky waves are more difficult to distinguish.The velocities of the detected interface wave are in good agreement with the theoretical calculation and the attenuation characteristics of the two leaky waves are also in accordance with the theoretical prediction.

Adaptive image enhancement using nonsubsampled contourlet transform domain histogram matching

In this letter, we propose a novel adaptive image enhancement algorithm based on nonsubsampled contourlet transform （NSCT） coefficient histogram matching. Firstly, the original image is decomposed in the NSCT domain. Secondly, the NSCT coefficient histograms of the original image in corresponding subbands are adaptively mapped to those of the reference image via histogram matching after threshold denoising. Finally, the enhanced image is reconstructed fl＇om the modified coefficients via inverse NSCT. Experimental results demonstrate that the proposed adaptive algorithm effectively improves subtle features while suppressing noise compared with existing algorithms.