On the foundation of analysis on immanent connection of industrialization and information,based on related theories,the paper selecs index to measure the level of Shanxi industrialization and information respectively. The result is that the industrialization and information level of Shanxi province is in the intermediate stage. The paper applies the Grey correlation method to analyze the association degree between industrialization and information of Shanxi province,concluding that industrialization and information of Shanxi province is not highly connected,information industry is relatively backward,the advantages of industrialization is not fully played,there is no better for information to promote industrialization.
The quality of potato is directly related to their edible value and industrial value. Hollow heart of potato, as a physiological disease occurred inside the tuber, is difficult to be detected. This paper put forward a non-destructive detection method by using semi-transmission hyperspectral imaging with support vector machine (SVM) to detect hollow heart of potato. Compared to reflection and transmission hyperspectral image, semi-transmission hyperspectral image can get clearer image which contains the internal quality information of agricultural products. In this study, 224 potato samples (149 normal samples and 75 hollow samples) were selected as the research object, and semi-transmission hyperspectral image acquisition system was constructed to acquire the hyperspectral images (390-1 040 nn) of the potato samples, and then the average spectrum of region of interest were extracted for spectral characteristics analysis. Normalize was used to preprocess the original spectrum, and prediction model were developed based on SVM using all wave bands, the accurate recognition rate of test set is only 87. 5%. In order to simplify the model competitive.adaptive reweighed sampling algorithm (CARS) and successive projection algorithm (SPA) were utilized to select important variables from the all 520 spectral variables and 8 variables were selected (454, 601, 639, 664, 748, 827, 874 and 936 nm). 94. 64% of the accurate recognition rate of test set was obtained by using the 8 variables to develop SVM model. Parameter optimization algorithms, including artificial fish swarm algorithm (AFSA), genetic algorithm (GA) and grid search algorithm, were used to optimize the SVM model parameters: penalty parameter c and kernel parameter g. After comparative analysis, AFSA, a new bionic optimization algorithm based on the foraging behavior of fish swarm, was proved to get the optimal model parameter (c=10. 659 1, g=0. 349 7), and the recognition accuracy of 10% were obtained for the AFSA-SVM model. The results indicate that combining the semi-transmission hyperspectral imaging technology with CARS-SPA and AFSA-SVM can accurately detect hollow heart of potato, and also provide technical support for rapid non-destructive detecting of hollow heart of potato.
The present paper put forward a non-destructive detection method which combines semi-transmission hyperspectral imaging technology with manifold learning dimension reduction algorithm and least squares support vector machine (LSSVM) to recognize internal and external defects in potatoes simultaneously. Three hundred fifteen potatoes were bought in farmers market as research object, and semi-transmission hyperspectral image acquisition system was constructed to acquire the hyperspectral images of normal external defects (bud and green rind) and internal defect (hollow heart) potatoes. In order to conform to the actual production, defect part is randomly put right, side and back to the acquisition probe when the hyperspectral images of external defects potatoes are acquired. The average spectrums (390-1,040 nm) were extracted from the region of interests for spectral preprocessing. Then three kinds of manifold learning algorithm were respectively utilized to reduce the dimension of spectrum data, including supervised locally linear embedding (SLLE), locally linear embedding (LLE) and isometric mapping (ISOMAP), the low-dimensional data gotten by manifold learning algorithms is used as model input, Error Correcting Output Code (ECOC) and LSSVM were combined to develop the multi-target classification model. By comparing and analyzing results of the three models, we concluded that SLLE is the optimal manifold learning dimension reduction algorithm, and the SLLE-LSSVM model is determined to get the best recognition rate for recognizing internal and external defects potatoes. For test set data, the single recognition rate of normal, bud, green rind and hollow heart potato reached 96.83%, 86.96%, 86.96% and 95% respectively, and he hybrid recognition rate was 93.02%. The results indicate that combining the semi-transmission hyperspectral imaging technology with SLLE-LSSVM is a feasible qualitative analytical method which can simultaneously recognize the internal and external defects potatoes and also provide technical reference for rapid on-line non-destructive detecting of the internal and external defects potatoes.
Calibration transfer is an effective approach to solve model invalidation problems caused by the change of instruments or the prediction samples. However, most studies on calibration transfer were based on different instruments, and models were established by Near Infrared Spectroscopy. In this study, hyperspectral detecting model of pork pH value was established, and in order to enhance the applicability of model to different breeds of pork samples; a new transfer algorithm based on spectra Mahalanobis distance, sync correction of spectrum and prediction value (CSPV), has been proposed, and was compared with model updating method. Equations with correlation coefficient of prediction (rp) > or = 0.837 and residual prediction deviation (RPD) > or = 1.9 were considered as applicable to predict pork quality. In this paper, three breeds, duchangda, maojia and linghao pork were researched, and a pH detecting model of duchangda (the primary breed) was established using partial least squares (PLS) regression method with r(c) of 0.922, r(p) of 0.904, root mean squared error of cross validation (RMSECV) of 0.045, root mean squared error of prediction (RMSEP) of 0.046 and RPD of 2.380. However, the prediction of the model to samples from maojia and linghao breeds (the secondary breeds) was very poor with rp of 0. 770 and 0.731 respectively, RMSEP of 0.111 and 0.209, RPD reached only 1.533 and 1.234 separately. Obviously, the PLS model of duchangda was unable to achieve the prediction to maojia and linghao samples. With the transformation of CSPV algorithm to duchangda model, only 9 and 10 standard samples from maojia and linghao breeds were used respectively, the prediction ability was improved with r(c) of 0.889 and 0.900, RPD grew to 2.071 and 2.231, which met the requirement of r(p) 0.837 and RPD > or = 1.9. While with model updating method, when 11 and 9 representative samples fromitaojia and linghao breeds were added to calibration set of duchangda model, r(c) increased to 0.869 and 0.845, but RPD only raised to 1.934 and 1.804 exclusively, even though tally r(p) > or = 0.837, it didn't meet that RPD > or = 1.9. The results demonstrate that CSPV transfer algorithm could realize the pH value prediction of duchangda model to maojia and linghao samples, while model updating method was only applicable for maojia samples instead of linghao samples, and the performance of CSPV transfer algorithm was better than model updating.
The Chinese rural government operation mechanism consists of the village committee, the village branch of the CPC, the town government, the town branch of the CPC and the economic cooperation organizations. There are several problems influencing the current mechanism, including interferences to the democratic elections, unclear relationships between the organizations, malfunction of different organizations, and etc. From the perspectives of the theory of incentive mechanism, based on the analysis of the farmers ' behavioral motives, we have concluded that it is the incompatibility of different incentives which caused the above stated problems within the current Chinese rural government operation mechanism. The incompatibility of incentives includes the incentives between democratic election participation incentives and the constraint factors to guarantee a fair election, the incentives of the abuses of power from the vil-lage leaders and the dysfunction of the authority control mechanism, and the incentives between the village leaders working for the town government and protecting the farmers' interests. This study proposes five solutions to optimize the rural government operation mecha-nism including rebuild the villagers' autonomous representative conference, form the task forces of the village affairs, recruit rural civil servants, develop villagers' cooperative economic organizations, and enforce the Party core leadership.
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