Time filter

Source Type

Wang J.Y.,Hunan Biological and Electromechanical Polytechnic
Applied Mechanics and Materials | Year: 2014

The development of circular economy is an important way to sustainable human development. The SMEs can use the mode of circular economy to improve their competitiveness. Through the analysis symbiotic relationship between small and medium enterprises, the development environment for SMEs, and the system which SMEs in, we found that SMEs can innovate organizational structure, organizational processes, organizational culture based on circular economy. The SMEs may be change their survival and development if they innovate the companies’ organization from these three aspects. © (2014) Trans Tech Publications, Switzerland.


Wang X.,Hunan Biological and Electromechanical Polytechnic | Liu J.J.,Changsha University of Science and Technology
Applied Mechanics and Materials | Year: 2014

Building a resource-conserving and environment-friendly industrial system not only conforms to the external demand of the international economic environment changes, but also meets the internal needs of the domestic economic transformation and the adjustment of economic growth pattern. It is also an inevitable requirement to realize two-oriented society in Hunan province. This paper expound the necessity of constructing two-oriented industry system from the respects of relations between different fields and the development trend, and explore the constructing ideas of two-oriented industrial system in Hunan province. © (2014) Trans Tech Publications, Switzerland.


Cao L.,Hunan Biological and Electromechanical Polytechnic | Wen Z.,Hunan Agricultural University | Shen L.,Hunan Agricultural University
Nongye Jixie Xuebao/Transactions of the Chinese Society of Agricultural Machinery | Year: 2010

Non-destructive detection methods of sugar content and valid acidity of Gongchuan Wenzhou citrus fruits were investigated based on computer vision. Factors which influenced the accuracy of detection were studied. Citrus fruit images from computer vision system were cut, the background was removed and conversion from RGB to HSI space was made. These images were segmented according to hue value ranges which are 0°-20°, 20°-40°, 40°-60°, 60°-80°, 80°-100° and 100°-120° hue. Fractal dimensions of each segment were calculated as inputs of BP neural network which modeled sugar content and valid acidity of citrus fruits. Results of 167 test samples showed the correctness for accuracy ±1.5°Brix of sugar content is 66.6175%, for valid acidity, the correctness for accuracy ±0.5 is 73.9275%. From these results it concluded that sugar content and valid acidity of Gongchuan Wenzhou citrus fruits has significant correlation with fractal dimension of hue value of fruit pericarp. Computer vision can be utilized to non-destructively detect these two parameters.


Cao L.,Hunan Biological and Electromechanical Polytechnic
Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering | Year: 2010

Citrus fruit variety recognition is an important issue for automated operations including diseases and insect pests prevention and cure, fertilization management and fruit picking. In order to evaluate the feasibility of automatic recognition of various fruits, samples of the citrus unshiu Marc.cv. unbergii Nakai, Skaggs Bonanza Navel orange and Luxi seedless Ponkan were studied. Images of calyx surfaces and the profile were acquired from sample fruits. Pixel numbers of fruit image contour and region were used as the perimeters and areas of fruits, and fractal dimensions of fruits were obtained by the perimeter-area method. Perimeters, areas and fractal dimensions were taken as the character values of three varieties of citrus fruits. A wavelet neural network model was presented to recognize different type of fruits based on these character values. The results showed that the correctnesses of the citrus unshiu Marc.cv. unbergii Nakai, Skaggs Bonanza Navel orange and Luxi seedless Ponkan were 95%, 95%, 97.5%, respectively. From the results we conclude that these three cultivars of citrus fruits can be automatically recognized and have a high correctness with three character values.


Wang J.,Hunan Biological and Electromechanical Polytechnic
Applied Mechanics and Materials | Year: 2013

In recent years, green economy is promoting global economic growth mode transformation with its powerful strength. China is no exception, and agreed to construct a demonstration region of the CHANGSHA-ZHUZHOU-XIANGTAN city-cluster in Hunan province. The region is named Two-oriented society which is resource-saving and environment-friendly. The paper studied High-tech small and medium enterprises (SMEs), which are the main body of the implementation of the Two-oriented society, analyzed of the interaction between the green economy, as well as two types of social construction and SMEs. Through these studies, we concluded those SMEs and government how to achieve environmental and economic interest's win-win model in the two-oriented society construction process. © (2013) Trans Tech Publications, Switzerland.


Wen Z.,Hunan Agricultural University | Cao L.,Hunan Biological and Electromechanical Polytechnic
Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery | Year: 2014

The investigation proposed a new algorithm to automatize the identification process of pests and insects disease of Citrus reticulata Blanco var. Ponkan, in which multi-fractal spectra of image hue were set as inputs of wavelet neural network model. In the new algorithm, image boundary of damage pattern of Ponkan was extracted with improved watershed algorithm, and discontinuous boundary was processed with boundary following, meanwhile over-segmentation region was merged and boundary was marked, at last, damage pattern image was generated. After the work above, firstly, hue range 0°~120° of damage pattern image was equally segmented into 4 regions to generate 4 binary images. And then these binary images were analyzed by multi-fractal method to calculate the widths and heights of multi-fractal spectra of scale invariance region. In the end, the widths and heights of multi-fractal spectra were set as the inputs of wavelet neural network model to identify the pest and insects disease of citrus fruit. Test results showed that the accurate rate of identification of 5 pests and insects disease is about 87%, which means that widths and heights of multi-fractal spectra are sufficient to characterize the damage pattern of citrus fruit, and this method is applicable in machine automatic recognition for pests and insects disease of citrus fruit.


Wen Z.,Hunan Agricultural University | Cao L.,Hunan Biological and Electromechanical Polytechnic
Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering | Year: 2013

Plant pests and diseases image recognition is one of the key technologies of digital agricultural information collection and processing. Usually, based on pest infestation-like plant, it is carried out according to the size, shape, color, texture, etc., or a combination of several parameters. Machine recognition of diseases and insect pests needs to use digitalized characteristics without overlapping. Multi-fractal analysis of Fourier transform spectra was adopted to investigate the possibility of extraction of damage pattern characteristics for Citrus reticulata Blanco var. Ponkan. First, images of the boundary of a damaged pattern are extracted with an improved watershed algorithm and region merging. Secondly, a Discrete Fourier Transform (DFT) was applied to the damaged fruit image. With reference to the boundary of a damaged pattern, a fruit image magnitude spectrum was extracted. Thirdly, a fruit image magnitude spectrum was multi-fractiously analyzed and the multi-fractal spectrum of DFT magnitude spectrum was quadratic fitted. Height, width, and centroid coordinate of a fitting parabolic section were chosen feature values to identify the diseases and insect damage of fruits, with these three feature values as inputs of a BP neural network identifying diseases and insect damage of Ponkan, and the accuracy was up to 92.67%. Finally, the amplitude spectrum of the Fourier transform was adopted for multifractal analysis and multi-fractal spectrum of a quadratic fit; fit parabola segment height, width, and centroid coordinates were regarded as pests' Eigen values, and then used as input variables to establish a BP citrus pest identification neural network model for pest identification. Among 5 classes of pests, in 30 groups of test samples, such as Pezothrips Kellyanus, Oxycetonia Jucunda, Oraesia Emarginata, Polyphagotarsonemus Latus, Colletotrichum Gloeoporioides Penz, the highest recognition rate was for Oraesia Emarginata, that is 96.67%, Polyphagotarsonemus Latus was the lowest at 86.67%, and the average correct recognition rate was 92.67%. The test came to the conclusion that the height, width, and centroid of a multi-fractal spectrum of a Fourier transform spectrum of damaged fruit image better illustrates the features of the disease and insect damage of fruits, such as a complicated biological entity. This method is possibly applicable to automatic recognition of disease and insect damage of Citrus reticulata Blanco var. Ponkan, and it's able to be applied to disease and insect damage recognition for other plants.


Yu F.X.,Hunan Biological and Electromechanical Polytechnic | Huang Z.P.,Hunan Biological and Electromechanical Polytechnic | Tan J.Q.,Hunan Biological and Electromechanical Polytechnic
Advanced Materials Research | Year: 2014

This study aimed to use the Chemometrics approach, namely cluster analysis(CA), discriminant analysis (DA) and Vectorial Angle Method (VAM) to analyze palm oil in rice bran oil (RBO). RBO was extracted from fresh rice bran in China and palm oil from Malaysia. Simulated adulteration of palm oil in RBO was designed and the amounts of fatty acid content under different adulteration were detected by gas chromatography(GC). DA and CA were used for the classification of RBO and RBO mixed with palm oil based on GC data. The VAM was exploited for the quantification of palm in RBO. The clustering analysis showed that no misclassification for RBO and RBO mixed with palm oil when adulteration is over 9%, and discriminant analysis reached a maximum classification accuracy of 100%. © (2014) Trans Tech Publications, Switzerland.


PubMed | CAS Institute of Subtropical Agriculture, Academy of Military Medical Science and Hunan Biological and Electromechanical Polytechnic
Type: Journal Article | Journal: Toxicology and industrial health | Year: 2016

Apoptosis triggered by ricin toxin (RT) has previously been associated with certain cellular organellar compartments, but the diversity in the composition of the organellar proteins remains unclear. Here, we applied a shotgun proteomics strategy to examine the differential expression of proteins in the mitochondria, nuclei, and cytoplasm of HeLa cells treated and not treated with RT. Data were combined with a global bioinformatics analysis and experimental confirmations. A total of 3107 proteins were identified. Bioinformatics predictors (Proteome Analyst, WoLF PSORT, TargetP, MitoPred, Nucleo, MultiLoc, and k-nearest neighbor) and a Bayesian model that integrated these predictors were used to predict the locations of 1349 distinct organellar proteins. Our data indicate that the Bayesian model was more efficient than the individual implementation of these predictors. Additionally, a Biomolecular Interaction Network (BIN) analysis was used to identify 149 BIN subnetworks. Our experimental confirmations indicate that certain apoptosis-related proteins (e.g. cytochrome c, enolase, lamin B, Bax, and Drp1) were found to be translocated and had variable expression levels. These results provide new insights for the systematic understanding of RT-induced apoptosis responses.


PubMed | Shenzhen University, CAS Institute of Subtropical Agriculture, Nanjing Agricultural University and Hunan Biological and Electromechanical Polytechnic
Type: | Journal: Journal of animal science and biotechnology | Year: 2016

The current study was carried out to provide a reference for monitory of aflatoxin BA total of 443 feed ingredients, including 220 corn, 24 wheat, 24 domestic distillers dried grains with soluble (DDGS), 55 bran, 20 wheat shorts and red dog, 37 imported DDGS, 34 corn germ meal and 29 soybean meal as well as 127 complete feeds including 25 pig complete feed (powder), 90 pig complete feed (pellet), six duck complete feed and six cattle complete feed were randomly collected from different Province in China, respectively, by high-performance chromatography in combined with UV or fluorescence analysis.The incidence rates of AFBThe current data provide clear evidence that AFB

Loading Hunan Biological and Electromechanical Polytechnic collaborators
Loading Hunan Biological and Electromechanical Polytechnic collaborators