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.     

天然气水合物储层泥质细粉砂挡砂介质堵塞规律与微观挡砂机制

中国南海海域部分天然气水合物储层中地层砂为高泥质含量细粉砂，开采防控砂难度较大。针对高泥质细粉砂挡砂机制问题，使用粒度中值为10.13 μm的泥质细粉砂样品，模拟单向气液携砂流动条件，使用绕丝筛板、金属烧结网、金属纤维、预充填陶粒4类挡砂介质在20~80 μm挡砂精度下进行挡砂模拟实验，采用显微成像系统观察挡砂介质内部及表面砂粒沉积与堵塞动态，分析介质流通性能和挡砂性能变化，总结堵塞规律、微观挡砂机制与形态及其控制因素。研究结果表明，不同类型和精度的挡砂介质对泥质细粉砂的堵塞总体呈现堵塞开始、堵塞加剧和堵塞平衡3个阶段。随着驱替进行，挡砂介质渗透率逐渐降低，幅度会高达90%以上；同时过砂速度减缓，最终过砂率为5%~10%。根据堵塞规律和微观图像分析，提出了粗组分分选桥架、局部砂团适度挡砂、整体砂桥阻挡等挡砂介质对泥质细粉砂的3种微观挡砂机制。以粗组分分选桥架挡砂机制为主的挡砂工况下，挡砂介质堵塞渗透率较高，但过砂率超过15%，挡砂效果较差；以整体砂桥挡砂机制为主时，过砂率在10%以下，挡砂性能较好，但各类挡砂介质的堵塞渗透率不足1 D，流通性能较差。局部砂团适度挡砂机制为主时介质挡砂性能及流通性能介于两者之间。挡砂介质对天然气水合物储层泥质细粉砂的微观挡砂机制和形态受挡砂介质类型、精度、地层砂特征以及流动条件等因素控制，其规律对于水合物泥质细粉砂防控砂优化有指导意义。     

“新国潮”设计要素对受众关注度的影响研究

目的 针对“新国潮”这一新兴的设计现象进行受众关注度研究，旨在剖析“新国潮”设计风格，发现影响“新国潮”受众关注度的设计要素，并展开实验分析，为设计领域的实证研究提供方法层面上的启示，为“新国潮”风格的推广提供设计策略。方法 在从字体、符号和色彩三方面解构“新国潮”设计要素的基础上，通过因素分析方法确定实验数据的信度、效度，运用眼动实验系统和方差分析法从无意注意和有意注意两个阶段实证研究“新国潮”设计要素对受众关注度的影响，并对原因展开分析。结果 在无意注意阶段，书法体、有色彩渐变、高纯度色彩、非象征符号能够获得较高关注度;在有意注意阶段，受众对宋体、有色彩渐变、高纯度色彩、象征符号的关注度更高。结论 研究在提高受众对“新国潮”画面的关注度、发现关注度影响机理和构建设计要素有效表达方面具有重要意义。     

Farmers' preferences for adopting on-farm concentration of raw milk: Results from a discrete choice experiment in Germany

Milk concentrates are used in the manufacturing of dairy products such as yogurt and cheese or are processed into milk powder. Processes for the nonthermal separation of water and valuable milk ingredients are becoming increasingly widespread at farm level. The technical barriers to using farm-manufactured milk concentrate in dairies are minimal, hence the suspicion that the practice of on-farm raw milk concentration is still fairly uncommon for economic reasons. This study, therefore, set out to investigate farmers' potential willingness to adopt a raw milk concentration plant. The empirical analysis was based on discrete choice experiments with 75 German dairy farmers to identify preferences and the possible adoption of on-farm raw milk concentration. The results showed that, in particular, farmers who deemed the current milk price to be insufficient viewed on-farm concentration using membrane technology as an option for diversifying their milk sales. We found no indication that adoption would be impeded by a lack of trustworthy information on milk processing technologies or capital.     

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).     

Kinetic Monte Carlo simulation of hydrogen production from photocatalytic water splitting in the presence of methanol by 1 wt% Au/TiO2

In this research, using the kinetic Monte Carlo simulation (KMC), the hydrogen production from a water-methanol mixture using Au/TiO₂ photocatalyst is investigated. A mechanism is proposed, and the rate constants of the reaction steps are specified. The reaction rate constants of different steps and the concentration of the active sites on the photocatalyst surface were determined. An excellent match between simulated and experimental data confirms the results. The electron-hole pair production, methanol adsorption on the photocatalyst surface, and electron-hole recombination steps are considered the most critical steps. To study the effects of independent variables (initial concentration of methanol, photocatalyst dosage, pH, and time of reaction) on the produced hydrogen, a combination of KMC simulation and design of experiment was employed. The concentration of photocatalysis has the highest and pH has the lowest effect on the hydrogen production. The optimal conditions for photocatalytic hydrogen production are presented.     

Experimental and numerical investigations on the heat production and thermal storage characteristics of rapid preparation amorphous powder activated coke

The heat production and thermal storage characteristics of rapid-preparation amorphous powder activated coke (RAC) were investigated. RAC was prepared by using a drop-tube reactor system. The natural oxidation characteristics of RAC were studied through combined TG–FTIR analysis and temperature-programmed experiment. Experimental results showed that CO and CO₂ were the main oxidation products of RAC in air, and that the oxidation reaction was in accordance with the Arrhenius equation and law of mass action. Thermal storage characteristics were studied through computational fluid dynamics simulation. The maximum excess temperature θ_max increases linearly with the increase of the initial temperature. The concentration fields of the products show that CO₂ is mainly concentrated in the upper part of the coke bin, and the CO generated by CO₂ at high temperature is mainly concentrated in the central part of the coke bin.     

广义正交码索引调制系统的性能分析

摘 要：为了提高码索引调制（code index modulation，CIM）系统的传输效率，提出了一种具有更低复杂度的单输入单输出（single input single output，SISO）的广义正交码索引调制（generalized orthogonal code index modulation，GQCIM）系统。CIM 系统使用扩频码和星座符号传输信息，但只能激活两个扩频码索引和一个调制符号。而 GQCIM 系统以一种新颖的方式克服了只激活一个调制符号的限制，同时充分利用了调制符号的正交性，增加扩频码索引以传输更多的额外信息位，提高了系统的传输效率。此外，分析了GQCIM系统的理论性能，推导了误码率性能的上界。通过蒙特卡罗仿真验证了GQCIM系统的性能，对比发现GQCIM系统的理论和仿真性能一致。而且在相同的传输效率下，结果显示GQCIM系统的性能优于同样具有正交性的调制系统，如广义码索引调制（generalized code index modulation，GCIM）系统、CIM系统、码索引调制-正交空间调制（code index modulation aided quadrature spatial modulation，CIM-QSM）系统、码索引调制-正交空间调制（code index modulation aided spatial modulation，CIM-SM）系统、脉冲索引调制（pulse index modulation，PIM）系统。     

数字电子技术实验“线上-线下混合”教学改革

在“移动互联网+课堂”的大势趋动下,针对现在“数字电子技术实验”教学存在的教学模式落后,教学手段单一,教学内容简单、以及考核不够全面等问题,借助超星泛雅 “一平三端”平台进行“线上-线下混合教学”改革。通过课前发布任务、课中有效组织课堂活动、课后发布作业、统计数据和教学反思进行。实践表明：该方法提高了学生的自主学习能力,并且增强了教师对学生学习情况的动态跟踪和过程性指导,同时也让课堂教学更有效,教学评价方式更有针对性、更精准,最终达到知识、技能和情感态度价值观的培养。