Minjiang College

Fuzhou, China

Minjiang College

Fuzhou, China
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Wu X.,Minjiang College | Ye G.,Fujian Agriculture and forestry University | Zhang S.,Xiamen University | Lin Y.,Xiamen University | Zhang L.,CAS Yantai Institute of Coastal Zone Research
Chinese Journal of Applied and Environmental Biology | Year: 2011

Contents of some mineral elements and their resorption efficiencies in Casuarina equisetifolia branchlets across a coastal gradient were studied at the Chishan Forestry Center of Dongshan County, Fujian Province, China. The results showed that the distance to coast had a significant effect on the contents of mineral elements and their resorption efficiencies. Resorption efficiencies of K element (RE K) were all positive across the coastal gradient, with the lowest value found at the coastline sampling site, while Fe and Zn resorption efficiencies (RE Fe and RE Zn) were all negative across the coastal gradient. Ca, Mg and Na resorption efficiencies (RE Ca, RE and RE Na), which were contrary to Mn (RE Mn), were negative in seaward plantations and positive in inland plantations. It was suggested that the resorption efficiencies of the mineral nutrients significantly decreased with severer environmental stresses. There were also significant positive correlations between the K and Mg content and their resorption efficiencies in mature branchlets while the correlations between the Na and Fe content and their resorption efficiencies were significantly negative. In senescent branchlets, the content of all the elements and their resorption efficiencies except for K were negatively correlated. In addition, the correlation was positive between RE Zn and RE Mn, while negative between RE Zn and resorption efficiencies of other elements. No correlation was found between RE Mn and resorption efficiencies of other elements. These results showed that nutrient conditions in branchlets had different effects on their resoption efficiencies for different mineral nutrients.

Zhao C.,Nanjing University of Science and Technology | Zhao C.,Minjiang College | Liu C.,Nanjing University of Science and Technology | Lai Z.,Nanjing University of Science and Technology
Neurocomputing | Year: 2011

Multi-scale gist (MS-gist) feature manifold for building recognition is presented in the paper. It is described as a two-stage model. In the first stage, we extract the multi-scale gist features that represent the structural information of the building images. Since the MS-gist features are extrinsically high dimensional and intrinsically low dimensional, in the second stage, an enhanced fuzzy local maximal marginal embedding (EFLMME) algorithm is proposed to project MS-gist feature manifold to low-dimensional subspace. EFLMME aims to preserve local intra-class geometry and maximize local interclass margin separability of MS-gist feature manifold of different classes at the same time. To evaluate the performance of our proposed model, experiments were carried out on the Sheffield buildings database, compared with the existing works: (a) the visual gist based building recognition model (VGBR) and (b) the hierarchical building recognition model (HBR). Moreover, EFLMME is evaluated on Sheffield buildings database compared with some linear dimensionality reduction methods. The results show that the proposed model is superior to other models in practice of building recognition and can handle the building recognition problem caused by rotations, variant lighting conditions and occlusions very well. © 2011 Elsevier B.V.

Zhao C.,Nanjing University of Science and Technology | Zhao C.,Minjiang College | Lai Z.,Nanjing University of Science and Technology | Liu C.,Nanjing University of Science and Technology | And 2 more authors.
Soft Computing | Year: 2012

In graph-based linear dimensionality reduction algorithms, it is crucial to construct a neighbor graph that can correctly reflect the relationship between samples. This paper presents an improved algorithm called fuzzy local maximal marginal embedding (FLMME) for linear dimensionality reduction. Significantly differing from the existing graph-based algorithms is that two novel fuzzy gradual graphs are constructed in FLMME, which help to pull the near neighbor samples in same class nearer and nearer and repel the far neighbor samples of margin between different classes farther and farther when they are projected to feature subspace. Through the fuzzy gradual graphs, FLMME algorithm has lower sensitivities to the sample variations caused by varying illumination, expression, viewing conditions and shapes. The proposed FLMME algorithm is evaluated through experiments by using the WINE database, the Yale and ORL face image databases and the USPS handwriting digital databases. The results show that the FLMME outperforms PCA, LDA, LPP and local maximal marginal embedding. © 2011 Springer-Verlag.

Fu P.,Minjiang College | Shen R.-J.,Zhejiang University | Shuai G.-J.,Zhejiang Wanma Group Electronic Co. | Guo J.-F.,Zhejiang University | Hu X.-X.,Zhejiang University
Zhendong yu Chongji/Journal of Vibration and Shock | Year: 2013

A 2-DOF spherical traveling wave type ultrasonic motor is a kind of multi-DOF ultrasonic motors. The driving principle and basic structure of this kind of spherical ultrasonic motor were firstly introduced. Then, some basic problems of the motor were presented and the structure of the motor, the optimal structure of its stator and the tuning devices were explained. The stator with a big rake angle on its outer edge, a small rake angle on its inner edge and the tuning method of adjusting rake angles on its outer edge were presented. The contact model of the stator was built for calculation of its mechanical characteristics. Simulation and test results were verified each other for the stator. It was shown that the rotor diameter of the prototype motor is 45 mm and the stator diameter is 30mm, the maximum output torque is 120 mNm, the maximum rotating speed is 12 r/min. The results provided a foundation for design theory and performance improvement of a 2-DOF spherical traveling wave type ultrasonic motor.

Sun X.,Minjiang College
2016 IEEE International Conference on Mechatronics and Automation, IEEE ICMA 2016 | Year: 2016

In the paper, it is proposed that multi-spectral image pure pixel is utilized for completing SAM classification. The classified samples are utilized for electively constructing sparse dictionary, thereby improving the representativeness of the dictionary. Eight surface feature types are set in Landsat8 image. PPI index is used for calculating pure pixel index of each pixel. Pure pixel of each surface feature is further extracted through N-D visualizer, which is used for SAM calculation. Eight kinds of surface feature samples are selected from SAM image for online dictionary learning. Multi-spectral image sparse dictionary is generated. Multi-spectral image sparse coefficient is calculated through dictionary and OMP. Meanwhile, online dictionary and OMP are utilized for obtaining panchromatic image sparse coefficient. Fusion sparse coefficient is generated by maximum values both sparse coefficients. Multi-spectral image sparse dictionary is combined for reconstructing and generating fusion image. Eight quantitative fusion evaluation indicators are adopted for comparing algorithm fusion and weighted fusion in the paper. Fusion method proposed in the paper contains more information, fusion image texture detail information is improved, and better image multi-spectral information is kept. © 2016 IEEE.

Sun X.,Minjiang College
Journal of Remote Sensing | Year: 2013

Six rice reflectance spectra in LOPEX 93 database were used as samples for decomposition into 10-layer signals based on the one-dimensional discrete wavelet types HAAR, DB4 and SYM4. The goals of this work were to reconstruct the signal through wavelet approximation coefficients and to calculate the wavelet fractal dimension of the reconstruction signal using the walking divider method. On each scale, we have determined the wavelet fractal dimension, wavelet detail coefficient variance, wavelet detail coefficient entropy, and approximate wavelet coefficient reconstruction curve variance. The results show fractal characteristics present in rice spectra, and proved the validity of fractal calculation by correlation coefficients greater than 0.9. The four parameters revealed that the turning point of the rice spectral characteristic scale is present on the sixth scale when rice spectral resolution is less than 64 nm, in order to better reflect spectral peak-valley specific features. Through the measurement of 18 rice spectra in the field, this conclusion is further evidenced by two kinds of vegetation indexes and the correlation coefficients of two kinds of vegetation indexes and chlorophyll values on each scale.

Wang Y.,Minjiang College
Advanced Materials Research | Year: 2014

This paper firstly explains concepts of inland port and hinterland, secondly puts forward the innovative concept of inland port - hinterland system, thirdly uses the theory of life cycle to analyzs inland port - hinterland system in different stage of development, finally describes the characteristics in the 5 stages. It is helpful to provide policy advice and decision support system to promote system sustainable development. © (2014) Trans Tech Publications, Switzerland.

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