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.     

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).     

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。     

Chemical Bonding by the Chemical Orthogonal Space of Reactivity

The fashionable Parr–Pearson (PP) atoms-in-molecule/bonding (AIM/AIB) approach for determining the exchanged charge necessary for acquiring an equalized electronegativity within a chemical bond is refined and generalized here by introducing the concepts of chemical power within the chemical orthogonal space (COS) in terms of electronegativity and chemical hardness. Electronegativity and chemical hardness are conceptually orthogonal, since there are opposite tendencies in bonding, i.e., reactivity vs. stability or the HOMO-LUMO middy level vs. the HOMO-LUMO interval (gap). Thus, atoms-in-molecule/bond electronegativity and chemical hardness are provided for in orthogonal space (COS), along with a generalized analytical expression of the exchanged electrons in bonding. Moreover, the present formalism surpasses the earlier Parr–Pearson limitation to the context of hetero-bonding molecules so as to also include the important case of covalent homo-bonding. The connections of the present COS analysis with PP formalism is analytically revealed, while a numerical illustration regarding the patterning and fragmentation of chemical benchmarking bondings is also presented and fundamental open questions are critically discussed.     

POD-assisted strategies for structural topology optimization

We propose a new numerical tool for structural optimization design. To cut down the computational burden typical of the Solid Isotropic Material with Penalization (SIMP) method, we apply Proper Orthogonal Decomposition on SIMP snapshots computed on a fixed grid to construct a rough structure (predictor) which becomes the input of a SIMP procedure performed on an anisotropic adapted mesh (corrector). The benefit of the proposed design tool is to deliver smooth and sharp layouts which require a contained computational effort before moving to the 3D printing production phase.     

基于PFC~(3D)对无底柱分段崩落法结构参数优化研究

为了减少矿山企业的采矿成本,提高矿山的经济效益,对无底柱分段崩落法的结构参数、多分段放矿等方面进行研究,分析与矿石的回收率和贫化率的关系。探讨以大间距结构参数为理论基础,结合矿山的实际放矿参数,确定正交试验因素,采用室内多分段放矿模型,分别对低贫化放矿和矿山现行截止品位放矿进行了试验,分别分析放矿结构参数与矿石回收率和贫化率的关系。采用计算机PFC~(3D)软件模拟低贫化放矿,将模拟所得数据采用回贫差因素分析方法进行分析,利用ORIGIN软件采用响应面法拟合函数分析回贫差和结构参数的关系,最后分析矿石回贫差与无底柱分段崩落法各结构参数的关系,结果表明提出的该矿山的无底柱分段崩落法结构参数为最优值。     

五味子泡腾片的制备工艺及质量评价

研究五味子泡腾片的制备工艺,并对其进行质量评价。以崩解时限、产气量、pH值为评价指标,采用单因素和正交试验优化泡腾崩解剂配比、泡腾崩解剂质量分数、聚乙二醇(polyethylene glycol,PEG)6000的用量,并通过片剂重量差异、崩解时限、pH值、产气量、硬度及脆碎度和五味子醇甲的含量对产品进行质量控制。结果表明,柠檬酸∶碳酸氢钠最佳配比为1∶0.7(质量比),泡腾崩解剂的最佳质量分数为55%,五味子水提物浸膏质量分数26%,PEG 6000的最佳质量分数为5%,甜菊糖苷2%,氯化钠2%,乳糖10%。最优工艺条件下制备的泡腾片,外表呈浅粉色,片剂表面光滑,可迅速溶于水中,产生丰富气泡,汤色呈浅粉色,并伴有五味子特有香气,口味酸甜适中,口感良好,每片泡腾片中五味子醇甲的含量为(9.79±0.18)mg,平均片重(500±20)mg,崩解时限为(87.42±1.91)s,pH值平均值为4.63±0.071,崩解时限、pH值均符合药典规定。     

FDM 3D打印工艺参数对PLA制件力学性能的影响

采用五因素四水平正交试验设计,对16组不同工艺参数(打印层厚、填充密度、打印温度、填充速度、外壳厚度)的FDM 3D打印聚乳酸(PLA)制件力学性能进行了测试和结果分析,确定了影响PLA制件力学性能的主要因素,其中,外壳厚度对制件力学性能影响最为明显,打印温度影响最小,同时分析得到了在打印层厚0.15 mm,填充密度40%,打印温度210℃,填充速度60 mm/s,外壳厚度1.6 mm条件下可获得力学性能最佳的制件。最后对试验数据进行回归分析,拟合得到了FDM打印工艺参数与PLA制件力学性能指标的数学模型;通过对不同打印工艺参数的试样进行试验验证,表明该模型拟合误差小(5%以内),可靠性高,可用来对FDM 3D打印制件的加工提供参考。     

梅花鹿鹿油的提取及成分检测

采用超临界CO2提取法从梅花鹿(Cervus nippon)鹿脂肪中提取鹿油,探讨提取工艺对鹿油提取率的影响。以鹿脂肪为原料,通过单因素试验和正交试验分别研究提取温度、提取压力、提取时间以及CO2流量对鹿油提取率的影响。研究结果表明,最佳的提取工艺为:提取温度45℃、提取压力40 MPa、提取时间150 min、CO2流量14 L/h。此时鹿油的提取率为44.81%。通过气相色谱-质谱法(gas chromatography mass spectrometry,GC-MS)联用对鹿油的成分进行检测,确定其含有16种脂肪酸,其中饱和脂肪酸和不饱和脂肪酸相对含量分别为69.840 9%和30.159 1%,主要脂肪酸有十六烷酸、十八烷酸及十八碳烯酸。