电路过渡过程的计算机辅助分析

电路过渡过程所列方程是微分方程，本文中采用的是方框图模型分析法，即将微分方程的复杂示解分解成最基本的加（减）、乘（除）、积分（微分）、增益等运算，采用VB设计用户界面产进行计算，并给出了一算例。     

Patterns and Symmetries in the Visual Cortex and in Natural Images

As borders between different entities, lines are an important element of natural images. Indeed, the neurons of the mammalian visual cortex are tuned to respond best to lines of a given orientation. This preferred orientation varies continuously across most of the cortex, but also has vortex-like singularities known as pinwheels. In attempting to describe such patterns of orientation preference, we are led to consider underlying rotation symmetries: Oriented segments in natural images tend to be collinear; neurons are more likely to be connected if their preferred orientations are aligned to their topographic separation. These are indications of a reduced symmetry requiring joint rotations of both orientation preference and the underlying topography. This is verified by direct statistical tests in both natural images and in cortical maps. Using the statistics of natural scenes we construct filters that are best suited to extracting information from such images, and find qualitative similarities to mammalian vision. PACS84.35+i 89.70.+c 87.57.Nk     

Basic Properties of the (t, n)-Threshold Visual Secret Sharing Scheme with Perfect Reconstruction of Black Pixels

In this paper we consider the (t, n)-threshold visual secret sharing scheme (VSSS) in which black pixels in a secret black-white images is reproduced perfectly as black pixels when we stack arbitrary t shares. This paper provides a new characterization of the (t, n)-threshold visual secret sharing scheme with such a property (hereafter, we call such a VSSS the (t, n)-PBVSSS for short). We use an algebraic method to characterize basis matrices of the (t, n)-PBVSSS in a certain class of matrices. We show that the set of all homogeneous polynomials each element of which yields basis matrices of the (t, n)-PBVSSS becomes a set of lattice points in an (n−t+1)-dimensional linear space. In addition, we prove that the optimal basis matrices in the sense of maximizing the relative difference among all the basis matrices in the class coincides with the basis matrices given by Blundo, Bonis and De Santis [3] for all n≥ t ≥ 2.     

Visual recognition of melamine in milk via selective metallo-hydrogel formation

A novel protocol allowing convenient and highly selective visual recognition of melamine in raw milk via selective metallo-hydrogel formation at a concentration as low as 10 ppm without any tedious pretreatment has been developed.     

Phytochrome,the Visual Pigment of Plants

Plants require light for photosynthesis. In order to adapt to the light conditions in their particular habitat, they have developed various photoreceptor systems. Of these, phytochrome allows even two-color vision in the red/far-red region. The photoreceptor phytochrome is of interest not only to botanists, but also to natural product chemists, photochemists, biochemists, photobiologists, and recently molecular biologists. Despite numerous studies, there are still considerable gaps in our knowledge of this photoreceptor. This article first describes the basic structural studies of the tetrapyrrole chromophore and its photochemical cis–trans isomerization, which is the source of the chromoprotein's photochromism. In the section on the protein moiety, beside other topics, the domain structure of phytochrome and the conformational changes during phototransformation are discussed. Finally, the known phytochrome genes are used to derive phylogenetic relationships, and possible structure–function relationships are discussed.     

Simple laser vision sensor calibration for surface profiling applications

Due to the relatively large structures in the Oil and Gas industry, original equipment manufacturers (OEMs) have been implementing custom-designed laser vision sensor (LVS) surface profiling systems as part of quality control in their manufacturing processes. The rough manufacturing environment and the continuous movement and misalignment of these custom-designed tools adversely affect the accuracy of laser-based vision surface profiling applications. Accordingly, Oil and Gas businesses have been raising the demand from the OEMs to implement practical and robust LVS calibration techniques prior to running any visual inspections. This effort introduces an LVS calibration technique representing a simplified version of two known calibration techniques, which are commonly implemented to obtain a calibrated LVS system for surface profiling applications. Both calibration techniques are implemented virtually and experimentally to scan simulated and three-dimensional (3D) printed features of known profiles, respectively. Scanned data is transformed from the camera frame to points in the world coordinate system and compared with the input profiles to validate the introduced calibration technique capability against the more complex approach and preliminarily assess the measurement technique for weld profiling applications. Moreover, the sensitivity to stand-off distances is analyzed to illustrate the practicality of the presented technique.     

Salient region detection using background priors

In this paper, we introduce a novel salient region detection algorithm by using background priors. Because of the fact that superpixel is perceptually more meaningful than pixel, and which can reduce the complexity of image processing, we use the superpixel algorithm to reprocess original images. In addition, we hold the point that the colors in the image boundary could mainly represent all background colors, hence we compute the color contrast between the intern colors and the boundary colors. Since the nearer the patches are close to center, the more they affect other patches, we propose a new distribution-based model. Finally, experimental results demonstrate that the proposed method outperforms the state-of-the-art approaches.     

Two-scale image fusion of visible and infrared images using saliency detection

Military, navigation and concealed weapon detection need different imaging modalities such as visible and infrared to monitor a targeted scene. These modalities provide complementary information. For better situation awareness, complementary information of these images has to be integrated into a single image. Image fusion is the process of integrating complementary source information into a composite image. In this paper, we propose a new image fusion method based on saliency detection and two-scale image decomposition. This method is beneficial because the visual saliency extraction process introduced in this paper can highlight the saliency information of source images very well. A new weight map construction process based on visual saliency is proposed. This process is able to integrate the visually significant information of source images into the fused image. In contrast to most of the multi-scale image fusion techniques, proposed technique uses only two-scale image decomposition. So it is fast and efficient. Our method is tested on several image pairs and is evaluated qualitatively by visual inspection and quantitatively using objective fusion metrics. Outcomes of the proposed method are compared with the state-of-art multi-scale fusion techniques. Results reveal that the proposed method performance is comparable or superior to the existing methods.     

An infrared small target detection algorithm based on high-speed local contrast method

Small-target detection in infrared imagery with a complex background is always an important task in remote sensing fields. It is important to improve the detection capabilities such as detection rate, false alarm rate, and speed. However, current algorithms usually improve one or two of the detection capabilities while sacrificing the other. In this letter, an Infrared (IR) small target detection algorithm with two layers inspired by Human Visual System (HVS) is proposed to balance those detection capabilities. The first layer uses high speed simplified local contrast method to select significant information. And the second layer uses machine learning classifier to separate targets from background clutters. Experimental results show the proposed algorithm pursue good performance in detection rate, false alarm rate and speed simultaneously.     

A sorbent tube for oral malodour monitoring

Volatile sulphur compounds (VSCs) and particularly hydrogen sulphide are considered as the predominant gases causing oral malodour. In this paper, a simple alarm sensor has been developed for VSCs determination in mouth air. The device consists of a glass tube packed with a solid sensing phase. The VSCs react with the sensing phase to produce a change in the colour of the sensor visible with a naked eye.Different “reagents” were investigated to develop the sensing phase (neocuproine + Cu(II), bathocuproine + Cu(II), resazurin, 2,6-dichlorophenolindophenol and lead acetate), finding the neocuproine + Cu(II) as the best for our purposes. Also, different substrates such as Amberlite XAD-4 and XAD-7 and different trademarks of silica gel were tested as solid supports, being selected the silica gel.A device consisting of a glass tube packed with the sensing phase was optimized and tested with halitosis patients as a rapid illness test and the results compared with those obtained with a commercially available instrument, the Halimeter™, used for the determination of VSCs in mouth air. The results exhibited acceptable agreement between the proposed “qualitative” alarm sensor and a commercially available technique selected as reference, showing the possibility of using this “visual sensor” to control the halitosis and its evolution with an eventual treatment, by the own patient.