Identify and diagnosis of homogenous units and separating them and eventually planning separately for each unit are considered the most principled way to manage units of forests and creating these trustable maps of forest’s types, plays important role in making optimum decisions for managing forest ecosystems in wide areas. Field method of circulation forest and Parcel explore to determine type of forest require to spend cost and much time. In recent years, providing these maps by using digital classification of remote sensing’s data has been noticed. The important tip to create these units is scale of map. To manage more accurate, it needs larger scale and more accurate maps. Purpose of this research is comparing observed classification of methods to recognize and determine type of forest by using data of Land Cover of Modis satellite with 1 kilometer resolution and on images of OLI sensor of LANDSAT satellite with 30 kilometers resolution by using vegetation indicators and also timely PCA and to create larger scale, better and more accurate resolution maps of homogenous units of forest. Eventually by using of verification, the best method was obtained to classify forest in Golestan province’s forest located on north-east of country.

This problem is a solar hut photovoltaic cell in the attached and overhead two installation methods, the type of photovoltaic cells and array mode and inverter type optimization design issues. In question 1, since the photovoltaic cells are attached to the roof and exterior surfaces, the direction and angle of the battery are uniquely determined by the direction and angle of the attached surface. The problem is translated to optimize the installation of a certain type on a single surface area (array) of photovoltaic cells, so that the total amount of solar photovoltaic power generation as much as possible, and the unit power generation costs as small as possible, which is a multi-objective optimization problem. The problem can be discussed in the ideal environment in a single surface area of the battery installation optimization program, and then the actual environment of the multi-surface optimization. In the solution to Problem 1, the unit on the south of the roof of the battery at the moment to accept the solar energy formula is generated. The definition of and is the moment of direct radiation intensity, for the moment the sun and the south of the roof of the plane where the angle, for the level of horizontal radiation intensity, for the south of the roof and the horizontal angle, the planefor the plane, the center of the heart, the vertical upward direction is the axis of the positive coordinate system, obtained with the sun height angle , the sun azimuth , red angle, angle and the sun when the relationship is generated. The conclusion is only installed in the small roof surface type of battery C11, and the rest of the surface is not installed. 35 years of electricity generation is 77126 degrees, the economic benefits of 16,488 yuan, the recovery period of 21.3 years. In question 2, because the photovoltaic cells in the roof and the external wall surface can be installed overhead, the panel orientation and tilt will affect the efficiency of photovoltaic cells. Therefore, in the optimization scheme of Problem 1, the orientation and inclination of the panel on each surface are further adjusted to calculate the optimum orientation and inclination of the panel on each surface. The problem can be in the ideal weather environment to establish the sun running and the battery board efficiency model, and then the measured environment test. The optimal orientation of the panel is southward, and the optimal angle with the ground plane is 39.89 degrees. The conclusion is only installed in the small roof surface type of battery C11, and the rest of the surface is not installed. 35 years of generating capacity of 82165.2 degrees, the economic benefits of 18,998 yuan, the recovery period of 13 years. In question 3, by the optimization of the above two issues, in the building to meet the requirements of the hut under the design of the various aspects of the cabin and battery installation, and further optimize the total power generation of the hut, economic benefits. The whole model solver is run in MATLAB7.0.

The main reason for the formation of nano-biotechnology is due to the penetration of nanotechnology in the biological field, nanotechnology research center is the study of nano-drug carrier. Nano-drug system targeted drug delivery to achieve drug release, increase the insoluble drugs and peptide drug bio-efficiency, reduce the toxicity and application of drugs and other aspects of the development of good prospects, and thus become one of the key research in recent years’ field. Synthesis and application of nanometer drug carriers this review is presented in recent years and its application to provide a comprehensive basis for the treatment process. Describes the nature and preparation of nano-drug carrier methods, in recent years, people have been widely concerned by scholars. Compared with the nano-drug delivery, the general pharmaceutical cannot have to extend the role of drugs, strong efficacy, and the advantages of small drug response. Nano-materials, the specific surface area, surface activity, high catalytic efficiency, surface active center, adsorption capacity and other characteristics, which has many excellent features and new features.

This study analyzes the impact of a high-speed rail line on tax revenues and on the economy of affected regions within the country. The economic impact of infrastructure investment can be induced by changes in tax revenues when the infrastructure is in operation. Accurate regional GDP data are not necessarily available in many Asian countries. However, tax data can be collected. Therefore, this study uses tax revenue dates in order to estimate spillover effects of infrastructure investment. The Kyushu high-speed rail line was constructed in 1991 and was completed in 2003. In 2004, the rail line started operating from Kagoshima to Kumamoto. The entire line was opened in 2011. We estimated its impact in the Kyushu region of Japan by using the differencein- difference method, and compared the tax revenues of regions along the high-speed railway line with other regions that were not affected by the railway line. Our findings show a positive impact on the region’s tax revenue following the connection of the Kyushu rapid train with large cities, such as Osaka and Tokyo. Tax revenue in the region significantly increased during construction in 1991–2003, and dropped after the start of operations in 2004–2010. The rapid train’s impact on the neighboring prefectures of Kyushu is positive. However, in 2004–2013, its impact on tax revenue in places farther from the rapid train was observed to be lower. When the Kyushu railway line was connected to the existing high-speed railway line of Sanyo, the situation changed. The study finds statistically significant and economically growing impact on tax revenue after it was completed and connected to other large cities, such as Osaka and Tokyo. Tax revenues in the regions close to the high-speed train is higher than in adjacent regions. The difference-in-difference coefficient methods reveal that corporate tax revenue was lower than personal income tax revenue during construction. However, the difference in corporate tax revenues rose after connectivity with large cities was completed. Public–private partnership (PPP) has been promoted in many Asian countries. However, PPP-infrastructure in India failed in many cases due to the low rate of return from infrastructure investment. This study shows that an increase of tax revenues is significant in the case of the Kyushu rapid train in Japan. If half of the incremental tax revenues were returned to private investors in infrastructure, the rate of return from infrastructure investment would significantly rise for long period of time. It would attract stable and long-term private investors, such as pension funds and insurance funds into infrastructure investment. The last section of the paper will address how incremental tax revenues created by the spillover effects of infrastructure will improve the performance of private investors in infrastructure investment.