To achieve sustainable development, detailed planning, control and management of land cover changes that occur naturally or by human caused artificial factors, are essential. Urban managers and planners need a tool that represents them the information accurate, fast and in exact time. In this study, land use changes of 3 periods, 1994-2002, 2002-2009, 2009-2015 and predictions of 2009, 2015 and 2023 were assessed. In this paper, Maximum Likelihood method was used to classify the images, so that after evaluation of accuracy, amount of overall accuracy for images of 2013 was 85.55% and its Kappa coefficient was 80.03%. To predict land use changes, Markov-CA model was used after assessing the accuracy, and the amount of overall accuracy for 2009 was 82.57% and for 2015 was 93.865%. Then web GIS application was designed via map server application and evoked shape files through map file and open layers to browser environment and for design of appearance of website CSS, HTML and JavaScript languages were used. HTML is  responsible for creating the foundation and overall structure of webpage but beautifying and layout design on CSS. 

In this study, the influence of sewage sludge ash (SSA) waste particle contents on the mechanical properties and interlaminar fracture toughness for mode I and mode II delamination of S-glass fiber-reinforced epoxy composites was investigated. Composite laminate specimens for tensile, flexural double-cantilever beam (DCB), and end-notched fracture (ENF) tests were prepared and tested according to ASTM standards with 5, 10, 15, and 20 wt% SSA-filled S-glass/epoxy composites. Property improvement reasons were explained based on optical and scanning electron microscopy. The highest improvement in tensile and flexural strength was obtained with a 10 wt% content of SSA. The highest mode I and mode II interlaminar fracture toughness’s were obtained with 15 wt% content of SSA. The mode I and mode II interlaminar fracture toughness improved by 33% and 63.6%, respectively, compared to the composite without SSA.

The cross wire projection welding of wires (Al 5182, = 4 mm) performed using the conventional (i.e. pneumatic) electrode force system was subjected to thorough numerical analysis. Calculations were performed until one of adopted boundary conditions, i.e., maximum welding time, maximum penetration of wires, the occurrence of expulsion or the exceeding of the temperature limit in the contact between the electrode and the welded material was obtained. It was observed that the ring weld was formed within the entire range of welding parameters. The process of welding was subjected to optimisation through the application of a new electromechanical electrode force system and the use of a special hybrid algorithm of electrode force and/or displacement control. Comparative numerical calculations were performed (using SORPAS software) for both electrode force systems. Technological welding tests were performed using inverter welding machines (1 kHz) provided with various electrode force systems. The research also involved the performance of metallographic and strength (peeling) tests as well as measurements of welding process characteristic parameters (welding current and voltage).
The welding process optimisation involving the use of the electromechanical force system and the application of the hybrid algorithm of force control resulted in i) more favourable space distribution of welding power, ii) energy concentration in the central zone of the weld, iii) favourable (desired) melting of the material within the entire weld transcrystallisation zone and iv) obtainment of a full weld nugget.

In order to improve the quality and efficiency of heat treatment in welds of power stations, this paper summarizes the current situation of 600 MW supercritical power plant welding site heat treatment and puts forward the improved methods and measures accordingly. The heat treatment of welding holes in the construction site Play a certain guiding role.

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 project of returning farmland to forest is a new project of increasing farmers' income, ecological efficiency and

benefiting the country. The key to the success of returning farmland to forest project is to strictly control the key technologies such as regional planning, forest species selection, tree species selection, good seedling, structural configuration, meticulous soil preparation, serious planting, tending and management. According to the actual

situation of Yuanling County, suitable for the tree, choose the market prospects, fast-growing tree species afforestation,

reasonable adjustment of forest structure, ecological benefits and economic benefits simultaneously, take high-

quality high-yield and efficient forestry development. Returning farmland to forest project has played huge ecological benefits, economic and social benefits.