The integration of medical images is the process of registering and fusing them to obtain a greater amount of diagnostic information. In this work an analysis is performed for the integration of images obtained through computed axial tomography and magnetic resonance imaging, for which a tool was developed in the Matlab program, where the registration is implemented through equivalent features; in addition, the pairs of images are compared by several fusion rules, with a view to identify the best algorithm in which the resulting fused image contains the most information from the original representations.

Coal is important basic energy and important raw materials, the development of coal industry to support the rapid development of the national economy. In the 1950s and 1960s, the proportion of coal in China's primary energy production and consumption structure accounted for 90% and 80% respectively, and the proportion of coal in 2004 was 75.6% and 67.7% respectively. In recent years, with the rapid development of fully mechanized mining equipment manufacturing technology, fully mechanized mining equipment to heavy, strong and automated, so that the reliability of the equipment is guaranteed, a strong impetus to the development of large mining technology, new round of coal mining technology revolution, the current in the East, Jincheng and other mining areas have been the first in the thick coal seam f = 1.5-5 use of large mining height fully mechanized mining equipment, to achieve the highest efficiency, the lowest cost of tons of coal. The main points of this paper are: in the production of coal enterprises to improve the competitiveness of the coal market. Conditions and conditions of coal storage conditions should be allowed to give priority to the use of large mining and mining methods.

This paper mainly uses the idea of pedigree clustering analysis, gray prediction and principal component analysis. The clustering analysis model, GM (1,1) model and principal component analysis model were established by using SPSS software to analyze the correlation matrices and principal component analysis. MATLAB software was used to calculate the correlation matrices. In January, The difference in price changes of major food prices in cities is calculated, and had forecasted the various food prices in June 2016. For the first issue, the main food is classified and the data are processed. After that, the SPSS software is used to classify the 27 kinds of food into four categories by using the pedigree cluster analysis model and the system clustering. The four categories are made by EXCEL. The price of food changes over time with a line chart that analyzes the characteristics of food price volatility. For the second issue, the gray prediction model is established based on the food classification of each kind of food price. First, the original data is cumulated, test and processed, so that the data have a strong regularity, and then establish a gray differential equation, and then use MATLAB software to solve the model. And then the residual test and post-check test, have C <0.35, the prediction accuracy is better. Finally, predict the price trend in June 2016 through the function. For the third issue, we analyzed the main components of 27 kinds of food types by celery, octopus, chicken (white striped chicken), duck and Chinese cabbage by using the data of principal given and analyzed by principal component analysis. It can be detected by measuring a small amount of food, this predict CPI value relatively accurate. Through the study of the characteristics of the region, select Shanghai and Shenyang, by looking for the relevant CPI and food price data, using spss software, principal component analysis, the impact of the CPI on several types of food, and then calculated by matlab algorithm weight, and then the data obtained by the analysis and comparison, different regions should be selected for different types of food for testing.

The impact of human activities on the quality of urban environment has become increasingly prominent and urban soil pollution problems on the health of local residents also gradually prominent. In addition, the study of heavy metal pollution in urban surface soil is an important part of the evolution model of urban geological environment so it is necessary to analyze the heavy metal pollution in urban soil. In this paper, the data of the given samples are processed and analyzed by MATLAB software and EXCEL spreadsheet. The three - dimensional image model and the planar model of metal element space are established by interpolation method. The spatial distribution of eight kinds of heavy metal elements in the city is presented in detail. For the urban environment, especially the macro-grasp of soil pollution, regulation provides a simple and accurate three-dimensional spatial distribution model of pollutants. Combined with data analysis of the urban area of different areas of heavy metal pollution to make a preliminary judgment. The data show that in the five types of cities, heavy soil pollution is the most serious in industrial areas. A method of imagination of the data analysis is boldly used and then combined with the distribution map, they found a source of pollution. For the spatial distribution of heavy metal elements, this paper uses EXCEL to calculate the data and MATLAB to map the data which showed a detailed and intuitive distribution map according to the distribution map can be analyzed in different areas of pollution; For the second question, this paper uses a method of design to deal with the data, part of the data for the results of the more effective show to determine the cause of pollution. For the third question, this article will be more serious pollution or a wider range of local screening, analysis, and then speculate the location of pollution sources. For other pollution information, this article is based on the modeling process encountered in the thought of the factors given.

In this paper, all the forests, woodlands and trees in the administrative area of Zhaoling Township in Chuzhou City of Huai'an City were collected and analyzed. The total area of the administrative area is 4852 hectares, the forest coverage rate is 22.07%, and the forest greening rate is 26.13%. This index has exceeded 20% of the forest coverage rate of the well - off society. Tree species is particularly serious. In the forest system (pure forest), the area of pure forest of poplar is accounted for 99.9% of the whole forest area. In the four tree systems, the number of poplar trees accounted for 80% of the total number of trees in the whole tree, and the total amount of poplar trees accounted for 98%. The poplar pure forest age group structure disorders, the unit area is low. The ratio of total area of poplar pure forest in Zhongling and young forests was 92.9%, and the ratio of total area of poplar pure forest and mature forest was 7.1%. The ratio of mature forest and the ratio of mature forest was 0.7%, and the proportion of each group was obviously abnormal.

In recent years, the foundry sector has been showing an increased interest in reclamation of used sands. Grain shape, sieve analysis, chemical and thermal characteristics must be uniform while molding the sand for better casting characteristics. The problem that tackled by every foundry industry is that of processing an adequate supply of sand which has the properties to meet many requirements imposed upon while molding and core making. Recently, fluidized bed combustors are becoming core of ‘clean wastes technology’ due to their efficient and clean burning of sand. For proven energy efficient sand reclamation processing, analysis of heating system in fluidized bed combustor (FBC) is required. The objective of current study is to design heating element and analysis of heating system by calculation of heat losses and thermal analysis offluidized bed combustorfor improving efficiency.