A general non-local denoising model using multi-kernel-induced measures

Noises are inevitably introduced in digital image acquisition processes, and thus image denoising is still a hot research problem. Different from local methods operating on local regions of images, the non-local methods utilize non-local information (even the whole image) to accomplish image denoising. Due to their superior performance, the non-local methods have recently drawn more and more attention in the image denoising community. However, these methods generally do not work well in handling complicated noises with different levels and types. Inspired by the fact in machine learning field that multi-kernel methods are more robust and effective in tackling complex problems than single-kernel ones, we establish a general non-local denoising model based on multi-kernel-induced measures (GNLMKIM for short), which provides us a platform to analyze some existing and design new filters. With the help of GNLMKIM, we reinterpret two well-known non-local filters in the united view and extend them to their novel multi-kernel counterparts. The comprehensive experiments indicate that these novel filters achieve encouraging denoising results in both visual effect and PSNR index.     

Preliminary evaluation of the anticorrosive properties of aircraft coatings by electrochemical methods

Strict regulations concerning the content of volatile organic compounds (VOCs) and heavy metals (Cr⁶⁺) in aircraft coating systems have increased the economic burden of the United States Air Force (USAF) in the area of coating maintenance. To this end, it is critical to have methods to characterize new coating systems in such a manner that the data can be used to predict accurately and reliably the expected lifetime of the coatings in service. Electrochemical noise method (ENM) and electrochemical impedance spectroscopy (EIS) are two techniques used to monitor extent and rate of corrosion. The USAF is currently employing these methods in order to supplement data acquired from traditional salt-spray methods. ENM and EIS are used to evaluate each component of the coating system and its contribution to corrosion prevention. Preliminary evaluations of an aircraft coating system on aluminum substrate (Al 2024-T3) produces resistance noise values of 10⁶ to 10⁷ Ω/cm². It is hoped that these results will form the basis of coatings that give increased USAF fleet service life and reduction in maintenance manpower and materials costs.     

低浓度含铀废水处理技术的研究进展

各种人为因素使得环境中的铀及其化合物越来越多,对水体造成了放射性污染。在分析环境中低浓度铀来源的基础上,介绍了对低浓度铀污染水体进行处理的最新技术,并着重探讨了应用植物修复技术处理铀污染的研究现状与发展趋势。     

汽车工业生产用热熔胶膜的研制

介绍了汽车工业生产内装饰复合材料用热熔胶膜的性能及其研制状况。这种热熔胶膜具有使用便捷,高效,生产、使用过程中没有污染的具有热熔胶膜的特长。     

New results on PWARX model identification based on clustering approach

This paper deals with the problem of piecewise auto regressive systems with exogenous input(PWARX) model identification based on clustering solution. This problem involves both the estimation of the parameters of the affine sub-models and the hyper planes defining the partitions of the state-input regression. The existing identification methods present three main drawbacks which limit its effectiveness. First, most of them may converge to local minima in the case of poor initializations because they are based on the optimization using nonlinear criteria. Second, they use simple and ineffective techniques to remove outliers. Third, most of them assume that the number of sub-models is known a priori. To overcome these drawbacks, we suggest the use of the density-based spatial clustering of applications with noise(DBSCAN) algorithm. The results presented in this paper illustrate the performance of our methods in comparison with the existing approach. An application of the developed approach to an olive oil esterification reactor is also proposed in order to validate the simulation results.     

A minimum variance distortionless response filter based on the bifrequency spectrum for single-channel noise reduction

This paper deals with the problem of single-channel noise reduction in the short-time Fourier transform (STFT) domain. Many algorithms have been developed to solve this important problem, most of which generally assume that the STFT coefficients in different frequency bands are uncorrelated, so the noise reduction is achieved by applying a gain function to the STFT of the noisy speech in each frequency band. However, this assumption is not accurate and the STFT coefficients of speech signals between neighboring frequency bands are correlated in practice due to the use of small lengths of the fast Fourier transform (FFT) and overlap add/save techniques in implementation. This paper formulates the noise reduction problem by taking into account the interband correlation using the so-called bifrequency spectrum. Based on this formulation, a single-channel minimum variance distortionless response (MVDR) filter is derived, which is shown to be able to significantly improve the signal-to-noise ratio (SNR) and meanwhile maintain the desired speech not much distorted. Simulations are presented to justify the claimed merits of the developed MVDR filter.     

机床噪声及降低噪声的途径

分析了机床噪声的起因，并提出了相应的降噪措施。     

汽车车内行驶噪声测试的阶次跟踪法

应用PULSE测试分析系统中阶次跟踪法,测试分析某型乘用车车内四个位置的噪声水平随发动机转速变化的关系.揭示了该型汽车在测试工况下,不同的转速对车内噪声的贡献规律.为降低车内行驶噪声和振动响应提供了重要的分析依据和参考.     

The use of electrochemical noise methods (ENM) to study thick, high impedance coatings

Thick, high impedance organic coatings are those class of coatings used to provide corrosion protection to naval vessels, pipelines, gasoline storage tanks, and other large structures such as bridges and plant structures. These coatings, especially the newest generations now being used in practice, can provide exceptional protection and lifetime of performance such that properly and accurately assessing and differentiating among competing coatings is a very difficult task. The standard protocol of salt fog testing (ASTM B117), immersion testing, and outdoor exposure in a corrosive environment with subjective evaluation of a coating's performance durings and after testing, does not adequatcly rank and predict coating lifetimes for new coating systems, especially for the environmentally compliant coating systems such as powder coatings (especially the thick, fusion bonded epoxy (FBE) coatings used for pipelines), two component epoxy and urethane coatings and waterborne coatings. New, objective test methods are desperately needed by users and manufacturers of coatings. A relatively new electrochemical test procedure, electrochemical noise methods (ENM), as developed by Skerry and Eden, has been shown in our laboratory to be very successful in the ranking and prediction of relative coating performance. We have used the method successfully on naval ship coatings, several pipeline coatings and other related systems, and Skerry has used them successfully on industrial maintenance coatings. We have used these methods in conjunction with electrochemical impedance spectroscopy, d.c. resistance measurements and cyclic salt fog testing of the Prohesion^TM type. In our studies of pipeline coatings, we needed to investigate thermal effects because of their extended range of use temperature. In these studies, we have discovered that electrochemical methods can be used for an in situ measurement of the T_g of coatings in electrolyte immersion. Further, the ‘plasticizing’ effect of aqueous electrolyte absorption as well as its relative irreversibility has been shown. For all coatings studied, ENM provided useful, objective, numerical data which rapidly ranks coatings and provides useful information on the relative lifetime prediction of coatings which may provide up to 30 years of service.     

Robust sparse principal component analysis

The model for improving the robustness of sparse principal component analysis（PCA） is proposed in this paper. Instead of the l2-norm variance utilized in the conventional sparse PCA model,the proposed model maximizes the l1-norm variance,which is less sensitive to noise and outlier. To ensure sparsity,lp-norm（0 p 1） constraint,which is more general and effective than l1-norm,is considered. A simple yet efficient algorithm is developed against the proposed model. The complexity of the algorithm approximately linearly increases with both of the size and the dimensionality of the given data,which is comparable to or better than the current sparse PCA methods. The proposed algorithm is also proved to converge to a reasonable local optimum of the model. The efficiency and robustness of the algorithm is verified by a series of experiments on both synthetic and digit number image data.