Time filter

Source Type

Lanzhou, China

Fang S.Y.,Xian University of Science and Technology | Yang J.,Gansu Academy of science
Advanced Materials Research | Year: 2014

So far, the definitions of slope debris flow are cinders and divergent, even, some scholars equate it with the hill slope debris flow/landslide-induced debris flow and other similar terms. This article summarizes research on the slope debris flow, from the definition and classification of debris flow, study on the classification of slope debris flow, analyzes the formation conditions, properties and characteristics of slope debris flow, at last, use the definition method of attribute and kind, tentatively give the preliminary definition of the slope debris flow. © (2014) Trans Tech Publications, Switzerland.

Wang Z.,Lanzhou University | Wang S.,Lanzhou University | Zhu Y.,Gansu Academy of science | Ma Y.,Lanzhou University
Archives of Computational Methods in Engineering | Year: 2015

Recently, many researchers have paid their more attention to image fusion technique based on pulse coupled neural network (PCNN). In order to make the researchers to rapidly understand the research development of image fusion based on PCNN, it is systematically reviewed in the paper. On the basis of statistical analysis on published papers, firstly, PCNN and some modified models are introduced. Then we review the PCNN’s applications in the field of image fusion. Subsequently, some existing problems are summarized, while we give some suggestions for the future research. © 2015 CIMNE, Barcelona, Spain

Fang S.-Y.,Xian University of Science and Technology | Yang J.,Gansu Academy of science
Applied Mechanics and Materials | Year: 2014

Study on the unique activity rules of earthquake induced by coal mining(EICM) is the foundation of earthquake prevention and disaster reduction. Based on the record data of EICM in northern Shaanxi from 2009 to 2012,the time-space distribution rules of seismic events is investigated by statistical methods; the trend of activities is predicted by analysis of magnitude-frequency relationship and creep curves sequence of EICM; the formation mechanics is discussed by using energy principle, the results show that: the corresponding relationship between EICM and on-site mining activity patterns is obvious, with the coal mining scale and depth increasing, EICM is inevitable, caused by the roof fall collapse, its intensity (the maximum magnitude of possible is ML 4.4) and frequency will increase further in the next period of time. © (2014) Trans Tech Publications, Switzerland.

Yu L.,Lanzhou University | Xue W.,Lanzhou University | Cui L.,Lanzhou University | Xing W.,Gansu Academy of science | And 2 more authors.
International Journal of Biological Macromolecules | Year: 2014

Fe3O4 nanoparticles were modified with Hydroxypropyl-β-cyclodextrin (HP-β-CD) and Polyethylene glycol 400 (PEG400) by a facile one-pot homogeneous precipitation method, and were used as a novel nano-adsorbent for the removal of congo red (CR) from aqueous solutions. The polymer-modified composites were characterized by FTIR, TEM, TGA, XRD and VSM, and showed excellent adsorption efficiency for CR. The value of the maximum adsorption capacity calculated according to the Langmuir isotherm model were 1.895g/g, which are much high and about 19 times that of Fe3O4 nanoparticles. Desorption study further indicates the good regeneration ability of the nanocomposites. The results suggest that the HP-β-CD/PEG400-modified Fe3O4 nanoparticles is a promising adsorbent for CR removal from aqueous solutions, and it is easily recycled owing to its large specific surface area and unique magnetic responsiveness. © 2013.

Wang Z.,Lanzhou University | Li H.,Lanzhou University | Zhu Y.,Gansu Academy of science | Xu T.,Lanzhou University
Archives of Computational Methods in Engineering | Year: 2016

Plant recognition is closely related to people’s life. The operation of the traditional plant identification method is complicated, and is unfavorable for popularization. The rapid development of computer image processing and pattern recognition technology makes it possible for computer’s automatic recognition of plant species based on image processing. There are more and more researchers drawing their attention on the computer’s automatic identification technology based on plant images in recent years. Based on this, we have carried on a wide range of research and analysis on the plant identification method based on image processing in recent years. First of all, the research significance and history of plant recognition technologies are introduced in this paper; secondly, the main technologies and steps of plant recognition are reviewed; thirdly, more than 30 leaf features (including 16 shape features, 11 texture features, four color features), and then SVM was used to evaluate these features and their fusion features, and 8 commonly used classifiers are introduced in detail. Finally, the paper is ended with a conclusion of the insufficient of plant identification technologies and a prediction of future development. © 2016 CIMNE, Barcelona, Spain

Discover hidden collaborations