Detecting and analyzing the body reflection characteristics of objects

The image color recorded in a computer vision system depends on three factors: the physical content of the scene, the illumination on the scene, and the characteristics of the camera. The goal of computational color correction is to reset the intensities of the color channels in digital images, and express the scene colors canonically. In the color correction method based on spectral reflectance reproduction, the finite-dimensional linear-model is an effective way to condense spectral reflectance. Since there are only three channels for each pixel in digital images, color correction based on spectral reflectance reproduction using the finite-dimensional model with three dimensions is needed. In the definite gamut, the spectral reflectance curves are analyzed using the finite-dimensional model. It is shown that reflectance generated by three basis functions which is capturing 99.13% of the overall variance, provides good approximations to the measured spectral reflectance. Together with the measured spectral power distribution of the illumination and the estimated spectral responses of the camera, the quantum catches are calculated. Errors caused by approximation of the finite-dimensional model are relatively small, which shows that color correction based on the finite-dimensional linear-model has feasibility to some extent.

H2 approximation of multiple input/output delay systems

Mixed systems aim at merging the physical and digital worlds. In this context, the Mixed Interaction Model allows us to define a mixed object and the interaction with such an object. In this paper we further define a mixed object by identifying new characteristics and by reusing results from the literature. Such characteristics of an object are useful for comparing existing mixed systems at a fine-grain level. Our characterization space is made of two complementary facets: we first define intrinsic characteristics of an object as well as extrinsic characteristics of a mixed object by considering its role in the interaction. These characteristics are discussed and illustrated in the context of different mixed systems from the literature or developed in our research team.

We represent local spatial structure in a color image using feature matrices that are computed from an image region. Feature matrices contain significantly more information about local image structure than previous representations. Although feature matrices are useful for surface recognition, this representation depends on the spectral properties of the scene illumination. Using a finite dimensional linear model for surface spectral reflectance with the same number of parameters as the number of color bands, we show that illumination changes correspond to linear transformations of the feature matrices and that surface rotations correspond to circular shifts of the matrices. From these relationships we derive an algorithm for illumination and geometry invariant recognition of local surface structure. We demonstrate the algorithm with a series of experiments on images of real objects.

Architectural color is an important visual element for people to feel the perception of the urban environment.In this paper, it takes the basic concept and combination of color research as the breakthrough point, with the help of the interpretation of the basic theory of architectural color, on the basis of analyzing the influence factors of the architectural color, so as to have a systematic analysis on the architectural color.In the process of the rapid development of the urbanization in China, with the emergence of a large number of construction projects, although there are many excellent architectural color designing cases, there still may be existing some bad architectural color designing works due to the following reasons such as : the increase of design, design personnel itself is uneven, especially for the general architecture, some of them were designed by the new designers, therefore, there my be existing bad color designing effect because of lacking experience.At the same time, the architectural design can be acted as a part of the city, the architectural color should reflect the characteristics of the city.The architectural color design itself should cover many subjects, which undoubtedly will increase the difficulty of the architectural color design.

Paintings convey the composition and characteristics of artists; therefore, it is possible to feel the intended style of painting and emotion of each artist through their paintings. In general, basic elements that constitute traditional paintings are color, texture, and composition (formative elements constituting the paintings are color and shape); however, color is the most crucial element expressing the emotion of a painting. In particular, traditional colors manifest the color containing historicity of the era, so the color shown in painting images is considered a representative color of the culture to which the painting belongs. This study constructed a color emotional system by analyzing colors and rearranged color emotion adjectives based on color combination techniques and clustering algorithm proposed by Kobayashi as well as I.R.I HUE & TONE 120 System. Based on the embodied color emotion system, this study confirmed classified emotions of images by extracting and classifying emotions from traditional Korean painted images, focusing on traditional painted images of the late Joseon Dynasty. Moreover, it was possible to verify the cultural traits of the era through the classified emotion images.

A color constancy mechanism is proposed to perceive the image color from the strengths of three RGB responses of a color camera or the like, independent of the color of the light illuminating the object. The first step of the method is to use a finite-dimensional linear model to estimate the color signals. It is shown that any color signal can be characterized as a linear combination of four principal component basis functions. Once the color signals have been estimated the unknown illuminant can be determined by S. Tominaga and B.A. Wandell's (1989) estimation method, which is based on a dichromatic model. In color constancy, the knowledge of surface reflectance helps in determining the canonical color descriptors despite the variations in the spectral power distribution of the ambient light. It is shown that the estimate of surface reflectance is derived from both the estimated color signal and illuminant straightforwardly. The model of a combination of the estimations of the surface spectral reflectance and the color signals can be employed in designing a color constancy electronic video camera which indeed improves the shortcomings of the traditional video camcorders.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Being a natural material of complex and orthotropic nature, the fracture displayed by bamboo remains widely unsolved to date. The fracture of natural bamboo is contingent on several external factors ranging from environmental to physical ones such as maturity and humidity. To elucidate the intricate fracture mechanisms in bamboo, there is a need to suppress numerous variables observed in natural materials, namely natural defects, geometry, and other physical and mechanical characteristics. One proven technique, which has shown numerous benefits to probing further into the fracture mechanisms of natural composite materials like bamboo, is the finite element method (FEM). This chapter focuses on the state-of-the-art research involving FEM simulation which has been considered to elucidate the fracture mechanisms in whole culm bamboo. The contents of this chapter will also comprise research findings from recent studies conducted by the author in this field. The research findings, in the first instance, will cover the effects of contributing factors such as material inhomogeneity, thermal modification, and direction of loading on the fracture mechanisms of bamboo. Under-researched areas involving the associated effects of physical and geometrical factors on the fracture of bamboo requiring further application of FEM techniques are also covered. Despite its wide usage over the last decades, the advent of high-end FEM simulation capabilities could exert a key role in elucidating the complex fracture mechanisms in bamboo products and bamboo-inspired structures. Besides, FEM can as well be considered to optimize the material structure of similar bio-inspired and advanced composites in further research.KeywordsBambooInhomogeneityOrthotropic natureExternal loadingThermal modificationFinite element method (FEM)Fracture mechanismsCrack propagation

A key factor in the prognosis of colorectal cancer, and its response to chemoradiotherapy, is the ratio of cancer cells to surrounding tissue (the so called tumour:stroma ratio). Currently tumour:stroma ratio is calculated manually, by examining H&E stained slides and counting the proportion of area of each. Virtual slides facilitate this analysis by allowing pathologists to annotate areas of tumour on a given digital slide image, and in-house developed stereometry tools mark random, systematic points on the slide, known as spots. These spots are examined and classified by the pathologist. Typical analyses require a pathologist to score at least 300 spots per tumour. This is a time consuming (10- 60 minutes per case) and laborious task for the pathologist and automating this process is highly desirable. Using an existing dataset of expert-classified spots from one colorectal cancer clinical trial, an automated tumour:stroma detection algorithm has been trained and validated. Each spot is extracted as an image patch, and then processed for feature extraction, identifying colour, texture, stain intensity and object characteristics. These features are used as training data for a random forest classification algorithm, and validated against unseen image patches. This process was repeated for multiple patch sizes. Over 82,000 such patches have been used, and results show an accuracy of 79%, depending on image patch size. A second study examining contextual requirements for pathologist scoring was conducted and indicates that further analysis of structures within each image patch is required in order to improve algorithm accuracy.

If specially oriented relativistic jets are a defining characteristic of BL Lac objects as a class, then several consequences follow unavoidably. First, the observed emission is relativistically boosted and may in fact represent only a small fraction of the emitted luminosity of the source. This tends to hide the identity of the “parent population” (those objects with misdirected jets) since intrinsic characteristics may be swamped by the boosted radiation. Second, the parent population must be relatively numerous since only a small fraction of randomly oriented jets would point toward us. In many cases, this has been used in a naive way to comment on possible parent populations for BL Lac objects (and to argue, erroneously, against the beaming hypothesis). Third — the point stressed in this paper — the observed luminosity distribution of BL Lac objects depends on both the luminosity function (LF) of the parent population and the properties of the jet (its speed and orientation). For simple power-law parent LFs, the shape of the LF for the beamed objects is a distinctive broken power-law which is very flat at low luminosities. For more complicated parent LFs, the beamed LF will still be at least as flat at the low luminosity end.

This paper focuses on the identification problem for a class of bilinear-in-parameter systems with an additive noise modeled by an autoregressive moving average process. By using the over-parameterization model, the special form of the bilinear term can be obtained by the model equivalent transformation. Then, we use a decomposition of the model into two synthetic models in order to separate the effect of the two sets of parameters, i.e., the coefficients of the nonlinear basis functions from the parameters of the colored noise. Moreover, two decomposition based iterative algorithms are proposed to identify the unknown parameters. A numerical example is presented to confirm the effectiveness of the proposed methods.

The tandem cascade of compressor can perform larger flow turning angle and less losses than a single-row cascade. The Proper Orthogonal Decomposition (POD) was used in this paper to extract the dominant mode of the tandem flow field especially the gap injection between two blades. Radial Basis Function Network (RBFN) was used to respond to the coefficients of POD basis function for one Reduced-order-model (ROM) construction, so as to predict the flow field. It is concluded that the combined method can be utilized to accurately predict the aerodynamics parameters and flow field of tandem cascade. The adaptive sampling method was developed to further advance the sampling efficiency for ROM prediction. The result shows that the adaptive sampling method has obvious advantages compared with static sampling in terms of efficiency and accuracy.

There are several methods available for representing boundaries in two dimensions. The more widely known ones involve boundary modeling with run-length codes, chain codes and polygons, AR model coefficients, Fourier descriptors (FD's) and B-spline control points (CP's). In this paper, we present results showing the usefulness of CP's in boundary representation. CP's can yield large compression of the boundary data and they exercise local control over boundary shape. Because they can be normalized with respect to scale, translation and rotation, they are valuable in boundary matching applications. Finally, being the series coefficients of spline basis functions, CP's are useful features for boundaries detected in noisy environments.

The paper presents a hierarchical polynomial chaos expansion-based probabilistic approach to analyze the single diode solar cell model under Gaussian parametric uncertainty. It is important to analyze single diode solar cell model response under random events or factors due to uncertainty propagation. The optimal values of five electrical parameters associated with the single diode model are estimated using six deterministic optimization techniques through the root-mean-square minimization approach. Values corresponding to the best objective function response are further utilized to describe the probabilistic design space of each random electrical parameter under uncertainty. Adequate samples of each parameter corresponding Gaussian uncertain distribution are generated using Latin hypercube sampling. Furthermore, a multistage probabilistic approach is adopted to evaluate the model response using low-cost polynomial chaos series expansion and perform global sensitivity analysis under specified Gaussian distribution. Coefficients of polynomial basis functions are calculated using least square and least angle regression techniques. Unlike the highly non-linear and complex single diode representation of solar cells, the polynomial chaos expansion model provides a low computational burden and reduced complexity. To ensure reproducibility, probabilistic output response computed using proposed polynomial chaos expansion model is compared with the true model response. Finally, a multidimensional sensitivity analysis is performed through Sobol decomposition of polynomial chaos series representation to quantify the contribution of each parameter to the variance of the probabilistic response. The validation and assessment result shows that the output probabilistic response of the solar cell under Gaussian parametric uncertainty correlates to a Rayleigh probability distribution function. Output response is characterized by a mean value of 0.0060 and 0.0760 for RTC France and Solarex MSX83 solar cells, respectively. The standard deviation of pm 0.0034 and pm 0.0052 was observed in the probabilistic response for RTC France and Solarex MSX83 solar cells, respectively.

The unimolecular isomerisation of the prompt propargyl + propargyl "head-to-head" adduct, 1,5-hexadiyne, to fulvene and benzene by the 3,4-dimethylenecyclobut-1-ene (DMCB) intermediate (all C6H6) was studied in the high-pressure limit by threshold photoelectron (TPE) spectroscopy. TPE spectra (TPES) were recorded with photoelectron photoion coincidence spectroscopy using synchrotron vacuum ultraviolet radiation. Reference TPES, obtained using pure compounds or judiciously extracted from the pyrolysis data, served as basis functions for pyrolysis quantification. From these spectra, we measured a revised fulvene ionisation energy of 8.401 ± 0.005 eV. Temperature-dependent pyrolysis spectra were decomposed using these basis functions. The basis function coefficients were converted to product yields relying on assumed integral threshold photoionisation cross sections obtained by three, partially mutually exclusive sets of assumptions. Thus, the product yields of DMCB, fulvene, and benzene have been established, as well as their uncertainty. The derived mole fractions are consistent with modeling based on the C6H6 potential and RRKM master equation model of Miller and Klippenstein [J. Phys. Chem. A, 2003, 107, 7783]. Although our results are fully consistent with the parallel isomerisation pathways to benzene and fulvene found by Miller and Klippenstein, we observe the onset of fulvene at a lower temperature than that of the onset of benzene, in agreement with the master equation model but in contrast to the previous experiments of Stein et al. [Proc. Combust. Inst., 1990, 23, 85]. This work promotes the use of photoion mass-selected threshold photoelectron spectroscopy as a rapid, sensitive, isomer-selective, and quantitative detection tool among the panoply of established analytical techniques.