Spectral radiance reconstruction from trichromatic camera responses based on orthogonal test and regularized algorithm

Reconstruction of spectral information based on multi‐channel image system is a significant problem in color reproduction, detection, and recognition. A spectral radiance reconstruction from trichromatic digital camera responses is researched in this article. The mapping relationship between the trichromatic imaging system response and the incident spectral radiance is analyzed. Then, in order to remove the ill‐posedness of the problem, a regularized constraint solution model of spectral radiance reconstruction matrix is established. And the spectral radiance can be reconstructed by spectral radiance reconstruction matrices and trichromatic imaging system response. Finally, the spectral radiance reconstruction matrix is estimated by the system radiometric calibration experiment. The input radiance is offered by a LCD display. A 3‐factor and 9‐level orthogonal test is designed for the calibration experiment, and a test set of 24 colors is used for precision analysis. The results show that the average relative mean error of our method is 8.69%, it is lower than that of Wiener filtering method by 2.84%. The method can reconstruct spectral radiance information effectively.     

虚实结合的可穿戴产品适合性检验研究

目的 为了更科学地研究和检验可穿戴产品的适合性,提出一种适合性检验方法,能够精确保留现实环境中的产品佩戴关系,并能将现实与虚拟的适合性检验研究相结合,得到合理的适合性检验结果.方法 以虚拟现实眼镜的适合性检验为例,通过高精度的三维测量技术将现实环境中的人、产品以及人—产品佩戴关系转化为三维虚拟信息,并以人—产品佩戴三维模型为参考基准对齐人和产品的虚拟模型,得到保留现实佩戴关系的人—产品佩戴模型组,再应用偏差分析法得出人—机佩戴区域的可视化适合性结果和统计数据,结合主观评价方法进一步分析产品的适合性.结论 虚实结合的产品适合性检验方法可在虚拟环境中高精度地保留现实环境中的人—产品佩戴关系,并能得到可视化的适合性检验结果,为检验和指导产品的适合性提供依据.     

Convolutional Neural Network Auto Encoder Channel Estimation Algorithm in MIMO-OFDM System

Higher transmission rate is one of the technological features of prominently used wireless communication namely Multiple Input Multiple Output-Orthogonal Frequency Division Multiplexing (MIMO–OFDM). One among an effective solution for channel estimation in wireless communication system, specifically in different environments is Deep Learning (DL) method. This research greatly utilizes channel estimator on the basis of Convolutional Neural Network Auto Encoder (CNNAE) classifier for MIMO-OFDM systems. A CNNAE classifier is one among Deep Learning (DL) algorithm, in which video signal is fed as input by allotting significant learnable weights and biases in various aspects/objects for video signal and capable of differentiating from one another. Improved performances are achieved by using CNNAE based channel estimation, in which extension is done for channel selection as well as achieve enhanced performances numerically, when compared with conventional estimators in quite a lot of scenarios. Considering reduction in number of parameters involved and re-usability of weights, CNNAE based channel estimation is quite suitable and properly fits to the video signal. CNNAE classifier weights updation are done with minimized Signal to Noise Ratio (SNR), Bit Error Rate (BER) and Mean Square Error (MSE).     

Influence of accelerated curing on the compressive strength of polymer-modified concrete

In recent building practice, rapid construction is one of the principal requisites. Furthermore, in designing concrete structures, compressive strength is the most significant of all parameters. While 3-d and 7-d compressive strength reflects the strengths at early phases, the ultimate strength is paramount. An effort has been made in this study to develop mathematical models for predicting compressive strength of concrete incorporating ethylene vinyl acetate (EVA) at the later phases. Kolmogorov-Smirnov (KS) goodness-of-fit test was used to examine distribution of the data. The compressive strength of EVA-modified concrete was studied by incorporating various concentrations of EVA as an admixture and by testing at ages of 28, 56, 90, 120, 210, and 365 d. An accelerated compressive strength at 3.5 hours was considered as a reference strength on the basis of which all the specified strengths were predicted by means of linear regression fit. Based on the results of KS goodness-of-fit test, it was concluded that KS test statistics value (D) in each case was lower than the critical value 0.521 for a significance level of 0.05, which demonstrated that the data was normally distributed. Based on the results of compressive strength test, it was concluded that the strength of EVA-modified specimens increased at all ages and the optimum dosage of EVA was achieved at 16% concentration. Furthermore, it was concluded that predicted compressive strength values lies within a 6% difference from the actual strength values for all the mixes, which indicates the practicability of the regression equations. This research work may help in understanding the role of EVA as a viable material in polymer-based cement composites.     

KDP/DKDP倍频晶体主截面定位方法

KDP/DKDP倍频晶体是惯性约束聚变系统中的关键元件,其主截面方向与晶体相位匹配角、晶体吸收系数紧密相关。为了实现KDP/DKDP倍频晶体主截面方向的高精度定位,本文提出一种光强测量间接定位方法。通过激光器结合稳功率仪及半波片输出稳定线偏振光,同时旋转相互正交的起偏器与检偏器可获得晶体的最佳消光位置即为主截面方向。推导了该测量系统光强的琼斯矩阵模型,给出了光强与起偏器、检偏器角度间的关系表达式。采用最小二乘方法拟合经过起偏器、倍频晶体及检偏器的光强变化曲线,从而可精确定位倍频晶体主截面的方向。通过计算机仿真模拟和实验验证了该方法的正确性和可行性。实验表明,该方法定位的重复测量精度优于0.02°,满足惯性约束聚变系统中KDP/DKDP倍频晶体主截面的定位控制精度要求。     

Recursive generalized extended least squares and RML algorithms for identification of bilinear systems with ARMA noise

Bilinear systems are considered as a particular class of nonlinear systems including the state variables which are typically used for online identification. By using a recursive identification method and the maximum likelihood principle, this paper presents two recursive-based algorithms to identify the parameters of bilinear in parameter systems with ARMA noise. In this regard, recursive generalized extended least squares (RGELS) and recursive Maximum Likelihood (RML) algorithms have been proposed for identification of bilinear systems. These algorithms can be used as an alternative choice in system identification with acceptable performance. The proposed algorithms estimate the correlated noise parameters with high accuracy by making full use of the measurement data. Simulation results indicate that the proposed algorithms are effective for online identification of bilinear in parameter systems with high convergence speed.     

Improvement of quantitative analysis of molybdenum element using PLS-based approaches for laser-induced breakdown spectroscopy in various pressure environments

An experimental setup has been designed and realized in order to optimize the characteristics of laser-induced breakdown spectroscopy system working in various pressure environments. An approach combined the normalization methods with the partial least squares(PLS) method are developed for quantitative analysis of molybdenum(Mo) element in the multi-component alloy,which is the first wall material in the Experimental Advanced Superconducting Tokamak. In this study, the different spectral normalization methods(total spectral area normalization,background normalization, and reference line normalization) are investigated for reducing the uncertainty and improving the accuracy of spectral measurement. The results indicates that the approach of PLS based on inter-element interference is significantly better than the conventional PLS methods as well as the univariate linear methods in the various pressure for molybdenum element analysis.     

盘县火腿自然发酵过程中理化和风味特征

分析盘县火腿自然发酵过程中理化特性和风味特征的变化，并结合香气活度值（odor activity value，OAV）和偏最小二乘回归（partial least squares regression，PLSR）分析确定盘县火腿主体香气成分。结果表明：盘县火腿理化特性在发酵过程中发生显著变化（P＜0.05），pH值和NaCl含量显著上升，而水分活度、水分含量和肌内脂肪含量显著下降，亮度值和黄度值呈持续下降趋势，而红度值先降低后升高；随着发酵的进行，盘县火腿中风味物质的种类从25 种增加至40 种，含量从（218.50±22.14） μg/kg上升至（1 044.49±51.47） μg/kg，其中醛类物质的种类和含量最丰富；OAV分析筛选出16 种主体香气物质，PLSR模型显示3-甲基丁醛、十二醛、十六醛、(Z)-9-十八烯醛和十八醛对盘县火腿肉香、清香和油脂香有显著贡献。     

近红外光谱法对松原不同品种大米的确证探究

该文提出一种对松原不同品种大米进行判别的方法,对来自松原的稻花香、小高粱、通系926、吉粳515、农大521,5个品种共368个大米样品,利用波数范围为12000 cm^-1~4000 cm^-1的傅里叶近红外光谱仪获取光谱数据并对数据进行6种方法的预处理。结果表明,一阶导数结合SG9点平滑为最佳预处理方法,并用偏最小二乘判别(partial least squares discrimination analysis,PLS-DA)方法对校正样本建立判别分析模型,用验证集对模型进行验证,模型对验证集中稻花香、小高粱、通系926、吉粳515、农大521共5个品种的识别率均为100%;且优于主成分分析的结果。用来自柳河和梅河的稻花香样本与松原的稻花香样本进行产地判别,结果显示,此模型可以将松原样本与非松原样本进行判别。