Discrimination of green tea quality using the electronic nose technique and the human panel test, comparison of linear and nonlinear classification tools

Electronic nose (E-nose) technique was attempted to discriminate green tea quality instead of human panel test in this work. Four grades of green tea, which were classified by the human panel test, were attempted in the experiment. First, the E-nose system with eight metal oxide semiconductors gas sensors array was developed for data acquisition; then, the characteristic variables were extracted from the responses of the sensors; next, the principal components (PCs), as the input of the discrimination model, were extracted by principal component analysis (PCA); finally, three different linear or nonlinear classification tools, which were K-nearest neighbors (KNN), artificial neural network (ANN) and support vector machine (SVM), were compared in developing the discrimination model. The number of PCs and other model parameters were optimized by cross-validation. Experimental results showed that the performance of SVM model was superior to other models. The optimum SVM model was achieved when 4 PCs were included. The back discrimination rate was equal to 100% in the training set, and predictive discrimination rate was equal to 95% in the prediction set, respectively. The overall results demonstrated that E-nose technique with SVM classification tool could be successfully used in discrimination of green tea's quality, and SVM algorithm shows its superiority in solution to classification of green tea's quality using E-nose data.     

On the decoding of binary cyclic codes with the Newton identities

We revisit in this paper the concept of decoding binary cyclic codes with Gröbner bases. These ideas were first introduced by Cooper, then Chen, Reed, Helleseth and Truong, and eventually by Orsini and Sala. We discuss here another way of putting the decoding problem into equations: the Newton identities. Although these identities have been extensively used for decoding, the work was done manually, to provide formulas for the coefficients of the locator polynomial. This was achieved by Reed, Chen, Truong and others in a long series of papers, for decoding quadratic residue codes, on a case-by-case basis. It is tempting to automate these computations, using elimination theory and Gröbner bases.Thus, we study in this paper the properties of the system defined by the Newton identities, for decoding binary cyclic codes. This is done in two steps, first we prove some facts about the variety associated with this system, then we prove that the ideal itself contains relevant equations for decoding, which lead to formulas.Then we consider the so-called online Gröbner basis decoding, where the work of computing a Gröbner basis is done for each received word. It is much more efficient for practical purposes than preprocessing and substituting into the formulas. Finally, we conclude with some computational results, for codes of interesting length (about one hundred).     

Identification and quantification of different vapours using a single polymer chemoresistor and the novel dual transient temperature modulation technique

This paper presents a novel signal processing technique for a square wave temperature modulated carbon black/polymer composite sensor. The technique consists of only two mathematical operations: summing the off- and on-transients of the conductance signals, and subtracting the steady-state conductance signal. The technique has been verified through its application to a carbon black/polyvinylpyrrolidone composite chemoresistor. Identification of water, methanol and ethanol vapours was successfully demonstrated using the peak time of the resultant curves. Furthermore, quantification of those vapours was found to be possible using the height of the peak heights, which was linearly proportional to concentration. The technique does not require zero-gas calibration and thus is superior to previously reported techniques.     

Quadratic optimal neural fuzzy control for synchronization of uncertain chaotic systems

This paper presents a novel quadratic optimal neural fuzzy control for synchronization of uncertain chaotic systems via H^∞ approach. In the proposed algorithm, a self-constructing neural fuzzy network (SCNFN) is developed with both structure and parameter learning phases, so that the number of fuzzy rules and network parameters can be adaptively determined. Based on the SCNFN, an uncertainty observer is first introduced to watch compound system uncertainties. Subsequently, an optimal NFN-based controller is designed to overcome the effects of unstructured uncertainty and approximation error by integrating the NFN identifier, linear optimal control and H^∞ approach as a whole. The adaptive tuning laws of network parameters are derived in the sense of quadratic stability technique and Lyapunov synthesis approach to ensure the network convergence and H^∞ synchronization performance. The merits of the proposed control scheme are not only that the conservative estimation of NFN approximation error bound is avoided but also that a suitable-sized neural structure is found to sufficiently approximate the system uncertainties. Simulation results are provided to verify the effectiveness and robustness of the proposed control method.     

Limitations of nonlinear discrete periodic control for disturbance attenuation and robust stabilization

This paper presents a performance analysis of nonlinear periodically time-varying discrete controllers acting upon a linear time-invariant discrete plant. Time-invariant controllers are distinguished from strictly periodically time-varying controllers. For a given nonlinear periodic controller, a time-invariant controller is constructed. Necessary and sufficient conditions are given under which the time-invariant controller gives strictly better control performance than the time-invariant controller from which it was obtained, for the attenuation of l_p exogenous disturbances and the robust stabilization of l_p unstructured perturbations, for all p[1,∞].     

A method of predicting the number of clusters using Rand's statistic

Distributional and asymptotic results on the moment of Rand's C_k statistic were derived by DuBien and Warde [1981. Some distributional results concerning a comparative statistic used in cluster analysis. ASA Proceedings of the Social Statistics Section, 309–313.]. Based on those results, a method to predict the number of clusters is suggested by applying various agglomerative clustering algorithms. In the procedure, the methods using different indexes are examined and compared based on the concept of agreement (or, disagreement) between clusterings generated by different clustering algorithms on the set of data. Our method having practical generality works better than the other methods and assigns statistical meaning to C_k values in determining the number of clusters from the comparison.     

炭黑填充导电丁腈橡胶研究

研究了用华光化工厂产导电炭黑填充丁腈橡胶的导电性规律。探讨了配方、加工工艺、混炼胶存放、胶料老化以及测试条件等诸多因素与导电性的关系。优选出了硬度７０左右的胶料，其体积电阻率为２．２２Ω·ｃｍ。     

雨型对东北黑土区坡耕地土壤侵蚀影响的试验研究

降雨雨型对土壤侵蚀过程有重要的影响,也是当前土壤侵蚀研究的热点之一。通过野外原位人工模拟降雨试验,设计了次降雨中平均降雨强度、总降雨量相同的4种不同降雨雨型(均匀型:降雨强度为60mm/h;峰值型:降雨强度分布为30-90-60mm/h;延迟型:降雨强度分布为60-30-90mm/h;减弱型:降雨强度分布为90-60-30mm/h),研究降雨雨型变化对东北黑土区坡耕地土壤侵蚀的影响。结果表明:各雨型条件下休闲坡耕地径流总量的大小顺序为延迟型>减弱性>均匀型>峰值型,而土壤侵蚀总量的大小顺序为减弱型>均匀型>延迟型>峰值型。延迟型雨型的坡面径流总量是其它雨型的1.02~1.45倍,减弱型降雨的侵蚀总量分别是均匀型、延迟型和峰值型的1.03、1.36和2.68倍。同一雨强在不同降雨雨型中出现的位置不同,其产生的坡面径流量和侵蚀量对坡面总径流量、总侵蚀量的贡献率也不同,分布在降雨雨型起始位置的雨强对坡面径流量的贡献率最小;除30mm/h降雨强度外,分布在降雨雨型起始位置的雨强对坡面侵蚀的贡献率最大。研究还发现,试验设计中减弱型降雨雨型与东北黑土区夏季主要侵蚀雨型特点类似,是造成东北黑土区坡耕地土壤侵蚀相对严重的主要雨型。     

薄层层析-紫外分光光度法测定银杏茶中银杏酸含量

采用薄层层析一紫外分光光度法建立了一种银杏茶中银杏酸快速检测的方法．采用正己烷索氏提取银杏茶中的银杏酸;以硅胶G为固定相,石油醚;乙酸乙酯：冰醋酸（18：1：1）为展开剂对银杏酸进行分离纯化;紫外分光光度法测定,波长为307nm．结果表明：该方法测定银杏酸含量的线性关系良好,线性范围为0．009-0．093mg／mL（R^2=0．9997）,精密度RSD为2．15％,平均回收率为100．90％,测定结果同HPLC法结果对照无明显差异,适用于银杏茶中银杏酸含量的测定．     

有机溶剂在湿法磷酸脱色中的应用

为了研究有机溶剂在湿法磷酸脱色的效果,以黑色的湿法磷酸为原料,分别使用四氯化碳、氯仿、柴油对湿法磷酸进行预脱色,再用活性炭对预脱色后的酸进行脱色.实验结果表明,柴油的预脱色效果最明显;最佳脱色条件为：湿法浓磷酸和柴油的质量比为5∶1、萃取分离时间1 h,活性炭的用量为湿法磷酸质量的1.5%、活性炭脱色时的温度为60℃、脱色时间为30 min,采用目测法观察,湿法磷酸从黑色基本变成无色;湿法稀磷酸和柴油的质量比为13∶1、萃取分离时间为20 min,活性炭的用量为湿法磷酸质量的0.25%、活性炭脱色温度为60℃、脱色时间为30 min,湿法稀磷酸从黑色变成无色.