Development of calibration models for quality control in the production of ethylene/propylene copolymers by FTIR spectroscopy,multivariate statistical tools,and artificial neural networks

Principal component regression (PCR), partial least squares (PLS), StepWise ordinary least squares regression (OLS), and back‐propagation artificial neural network (BP‐ANN) are applied here for the determination of the propylene concentration of a set of 83 production samples of ethylene–propylene copolymers from their infrared spectra. The set of available samples was split into (a) a training set, for models calculation; (b) a test set, for selecting the correct number of latent variables in PCR and PLS and the end point of the training phase of BP‐ANN; (c) a production set, for evaluating the predictive ability of the models. The predictive ability of the models is thus evaluated by genuine predictions. The model obtained by StepWise OLS turned out to be the best one, both in fitting and prediction. The study of the breakdown number of samples to be included in the training set showed that at least 52 experiments are necessary to build a reliable and predictive calibration model. It can be concluded that FTIR spectroscopy and OLS can be properly employed for monitoring the synthesis or the final product of ethylene–propylene copolymers, by predicting the concentration of propylene directly along the process line. © 2008 Wiley Periodicals, Inc. J Appl Polym Sci, 2008     

Influence of third monomer on the crystal phase transition behavior of ethylene-tetrafluoroethylene copolymer

Crystal phase transition between the low- and high-temperature phases has been investigated for ethylene (E)-tetrafluoroethylene (TFE) alternating copolymer (ETFE) containing the third monomeric species by the temperature dependent measurements of wide-angle X-ray diffraction (WAXD) and small-angle X-ray scattering (SAXS) and differential scanning calorimetry. Nonafluoro-1-hexene (NFH) and hexafluoropropylene (HFP) were chosen as the third monomers, where they are different in the side-branch length, -(CF₂)₃CF₃ and -CF₃, respectively. In the case of E/TFE/NFH copolymer (ET-C4F9), the crystal phase transition temperature of the original ETFE two-components copolymer was not very much affected by the existence of NFH in the range of NFH content from 0.7 to 3 mol%. Contrarily, the crystal phase transition temperature of E/TFE/HFP copolymer (ET-CF3) was found to decrease drastically with increasing HFP content. The melting temperature and the higher-order structure were also affected sensitively depending on the HFP content. This difference in phase transition behavior between ET-C4F9 and ET-CF3 copolymers is reasonably interpreted as follows: the short side groups (-CF₃) of HFP monomeric unit are included in the crystal lattice of E/TFE chains and the unit cell is expanded gradually with an increment of the HFP content, resulting in the decrease in phase transition point because of easier thermal motion of the chains. On the other hand, the long side groups [-(CF₂)₃CF₃] of NFH monomeric units are excluded out of the crystal lattice and located on the lamellar surfaces or in the amorphous region and do not affect very much the phase transition temperature even when the NFH content is increased. In association with such a change in crystal structure, the long period of stacked lamellar structure was found to decrease remarkably in the case of NFH, whereas it does not change very much for HFP, consistent with the interpretation of the above-mentioned WAXD data.     

Reconstruction of reflectance spectra using weighted principal component analysis

The weighted principal component analysis technique is employed for reconstruction of reflectance spectra of surface colors from the related tristimulus values. A dynamic eigenvector subspace based on applying certain weights to reflectance data of Munsell color chips has been formed for each particular sample and the color difference value between the target, and Munsell dataset is chosen as a criterion for determination of weighting factors. Implementation of this method enables one to increase the influence of samples which are closer to target on extracted principal eigenvectors and subsequently diminish the effect of those samples which benefit from higher amount of color difference. The performance of the suggested method is evaluated in spectral reflectance reconstruction of three different collections of colored samples by the use of the first three Munsell bases. The resulting spectra show considerable improvements in terms of root mean square error between the actual and reconstructed reflectance curves as well as CIELAB color difference under illuminant A in comparison to those obtained from the standard PCA method. © 2008 Wiley Periodicals, Inc. Col Res Appl, 33, 360–371, 2008     

Emulsifying Properties of the Total Fraction and the Hydrophobic Fraction of Bovine Milk Proteose-peptones

Since proteose-peptone is a mixture of heterogeneous proteins and peptides, its functional properties have not yet been fully understood. The present study was undertaken to elucidate the emulsifying properties of proteose-peptones and a parallel evaluation was performed of the emulsifying activity of the total fraction prepared from bulk skimmed milk by precipitation with ammonium sulphate and of the most hydrophobic fraction purified by hydrophobic interaction fast protein liquid chromatography. A turbidimetric technique was used and the absorbance value at 500 nm was then directly used as the emulsifying activity index. The results obtained confirmed the good emulsifying activity of this protein fraction of the whey and demonstrated the considerable influence of the concentration on the capacity of the proteose-peptones to stabilize a model oil-in-water emulsion. Moreover, at all the concentrations examined, the purified component 3 showed a higher emulsifying activity than the total unpurified fraction.     

高铅硫化铜精矿的二段焙烧

高铅硫化铜精矿进行湿法铜铅分离时，焙烧过程因有低熔点组份产生，使培砂中铜浸出率仅为73％～82％，达不到工艺要求。经二段焙烧后消除了上述影响，铜浸出率达到97．4％，实现了铜铅分离。     

BP网络模型对人脸朝向的识别

研究BP神经网络模型,通过计算机模拟人脑建立神经元网络,使用一部分人脸朝向信息作为训练的实例集,训练稳健后,可以推广应用判断其他人脸的朝向信息,以实现计算机自动识别人脸朝向。先对图片进行归一化等预处理,再应用主成分分析提取特征信息,每幅提取出的特征信息都是8个数据的列向量,构建一个8个输入、17个隐含、3个输出的三层BP网络模型。将训练实例集的特征向量代入训练,调整参数后保证其性能和收敛速度。最后通过大量实验验证,计算机识别的误判率仅为6.7%,模型可靠。     

基于中值滤波和梯度锐化的边缘检测

实现一种基于中值滤波和梯度锐化的边缘检测方法。首先采用既能过滤噪声又能保护边缘信息的中值滤波对图像进行平滑处理。然后采用梯度锐化加强边缘像素强度,通过简单的二值化获得图像的初始边缘,系统采用连通区域标记的方法去除位于图像封闭边界内的残留黑块。最后通过实验结果与人工提取的结果比较,进行误差分析,找出本文算法的不足之处,以便对该算法进行改进。实践证明,本文的边缘检测方法对含有噪声点且灰度分布比较均匀的图像有很好的效果。     

Customer entrepreneurship on digital platforms: Challenges and solutions for platform business models

Drawing on the mixed methods of qualitative research and agent‐based simulation, this study examines: (a) how end‐users use digital platforms to become customer–entrepreneurs undertaking commercial activities on platforms; and (b) how platform providers can convert this customer entrepreneurship into a revenue stream. Considering that end‐users have traditionally been defined as passive and uncharged actors in platform business models, an in‐depth understanding of their commercial activities and the viable revenue model to monetize this emerging customer practice is warranted. Our qualitative study reveals that customer–entrepreneurs make substantial use of platform offerings to advertise their products; communicate with end‐consumers; and accept payments. These commercial activities are largely exercised for free on platforms, even though they could otherwise serve as a source of revenue. On this point, our simulation results identify two pricing models achieving the generation of nearly identical revenues over time. First, platform providers may charge both advertising and transaction fees, which maximize the survival of professional customer–entrepreneurs. Second, platform businesses may levy advertising fees only, which maximizes the survival of informal customer–entrepreneurs operating on a micro‐scale and part‐time basis. This study offers theoretical, methodological, and managerial implications for platform studies.