Analysis and Study on Characteristics and Detection Methods of Cotton Diseases and Insect Pests

[Objectives]The paper was to find the diseases and insect pests in the process of cotton growth quickly,effectively and timely.[Methods]The growth process of cotton was dynamically monitored by UAV aerial photography,and the aerial data map was converted into geotif image with longitude and latitude and then inputted into the detection system for preprocessing,mainly for image feature extraction and classification.Through deep learning of MATLAB software and BP neural network algorithm,the feature similarity of the images in the established characteristic database of cotton diseases and insect pests was compared.[Results]Through comparative analysis of characteristics of a large number of diseases and insect pests,it was found that deep learning method had high discrimination accuracy and good reliability.[Conclusions]The dynamic detection system using deep learning can well find cotton diseases and insect pests,and achieve early detection and early treatment,so as to effectively improve the yield and quality of cotton.

NEW SCALING METHOD FOR COMPRESSOR MAPS USING AVERAGE INFINITESIMAL STAGE

The estimation of the precise performance of existing multistage axial-flow compressors of gas turbine engines is fast becoming a great concern, as the use of gas turbine engines in the power generation and in the military industry increases, in order to reduce the analysis performance error of the traditional scaling method, a new scaling method for estimating the characteristics of multistage axial flow compressors is proposed. This novel method is based on experimental and partial data provided by engine manufacturers. Taking the effect of density-change into account, we introduce the average infinitesimal stage concept, and thereby divide the compression process into an infinite number of infinitesimal processes corresponding to infinitesimal stages. Subsequently, we adopt the corrected Reynolds analogy method for compressible flow calculation in order to ensure much better compliance with the similarity criterion, Validation checks show that the proposed method has enough precision to predict the off-design performance characteristics of multistage axial flow compressors.

Quick Trickle Permutation Based on Quick Trickle Characteristic Sequence

The concept of quick trickle characteristic sequence is presented, the properties and count of quick trickle characteristic sequence are researched, the mapping relationship between quick trickle characteristic sequence and quick trickle permutation is discussed. Finally, an efficient construction of quick trickle permutation based on quick trickle characteristic sequence is given, by which quick trickle permutation can be figured out after constructing quick trickle characteristic sequence. Quick trickle permutation has good cryptographic properties.

On Singularity of Spline Space Over Morgan-Scott's Type Partition

Multivariate spline function is an important research object and tool in Computational Geometry. The singularity of multivariate spline spaces is a difficult problem that is ineritable in the research of the structure of multivariate spline spaces. The aim of this paper is to reveal the geometric significance of the singularity of bivariate spline space over Morgan-Scott type triangulation by using some new concepts proposed by the first author such as characteristic ratio, characteristic mapping of lines （or ponits）, and characteristic number of algebraic curve. With these concepts and the relevant results, a polished necessary and sufficient conditions for the singularity of spline space S u＋1^u （△MS^u） are geometrically given for any smoothness u by recursion. Moreover, the famous Pascal＇s theorem is generalized to algebraic plane curves of degree n≥3.

A quantitative morphometric comparison of cockpit and doline karst landforms

This study presented a quantitative comparison of cockpit and doline karst by examining the numbers and characteristics of typical types of landform entities that are developed in Guilin（Guangxi, China）, La Alianza（PR, USA）, Avalton（KY, USA）, and Oolitic（IN, USA）. Five types of landform entities were defined： isolated hill（IH）, clustered hills（CHs）, isolated sinkhole（IS）, clustered sinkholes（CSs）, and clustered hills with sinkholes（CHSs）. An algorithm was developed to automatically identify these types of landform entities by examining the contour lines on topographic maps of two cockpit karst areas（Guilin and La Alianza） and two doline karst areas（Oolitic and Avalton）. Within each specific study area, the CHSs is the least developed type yet with a larger size and higher relief. The IH and IS entities are smaller in size, lower in relief, and outnumber their clustered counterparts. The total numbers of these types of entities are quite different in cockpit and doline karst areas. Doline karst is characterized by more negative（IS and CSs） than positive（IH and IHs） landforms and vice versa for cockpit karst. For example, the Guilin study area has 1192 positive landform entities in total, which occupy 9.81% of the total study area. It has only 622 negative landform entities occupying only 3.91% of the total study area. By contrast, the doline karst in Oolitic has 130 negative while only 10 positive landform entities. The positive and negative landforms in Oolitic occupy 12.68% and 2.61% of the total study area, respectively. Furthermore, average relief and slope of the landform entities are much higher and steeper in the cockpit karst than the doline karst areas. For instance, the average slope of CHs in Alvaton is 3.90 degrees while it is 19.78 degrees in La Alianza. The average relief of CSs is 4.07 m and 34.29 m in Oolitic and Guilin respectively. Such a difference within a specific area or between the cockpit and doline karst may reveal different controls on the development of karst landscape.