Estimating air temperature is one of the important issues in agricultural planning and in water resources management which can be accomplished by using different methods such as empirical, semi-empirical and intelligent methods. In the present study, Adaptive Neuro Fuzzy Inference System, Artificial Neural Networks and Genetic Programming were used to estimate air temperature in the synoptic station of Tabriz City, northwest of Iran. Considering the statistical indices, all three models were able to estimate accurately minimum, mean and maximum air temperature. In spite of slight differences in the prediction accuracy and errors by the models, Adaptive Neuro Fuzzy Inference System, Artificial Neural Networks and Genetic Programming were in the order of priority. Also explicit solutions that show the relation between input and output variables are presented based on Genetic Programming. This adds to the superiority of Genetic Programming over the other two models.

Climate change is one of the most significant issues for researchers and media in recent decades. This phenomenon is slowly expanding whole over the world and affecting all relevant parameters. Hence, the main objective of this study is evaluating the impacts of global warming on minimum temperatures of Iran. To do so, daily minimum temperature of 47 synoptic stations were extracted during the 1961-1990. In order to investigate global warming impact, output of the HADCM3 model for 2015-2045 based on A2 and B2 scenarios was downscaling using SDSM model. Results illustrated that base on the relationship between predictor and predictable variables, created model between these variables are partially capable of producing climate data for future periods. Correlation coefficient (r) between observed and generated data during the 1976-1990 was 0.95. Furthermore, results of variance and correlation tests indicated that there is significant similarity between observed and generated data. Finally, the model demonstrated that minimum temperature in studied statins will be increased during 2015-2045. Temperature will be increased about 0.8 and 0.5oC based on the A2 and B2 scenarios, respectively. The stations will experience different temperature changes.

Due to the importance of meteorological data and limitations of data gathering from ground stations, remote sensing can play an important role in the preparation of these data. The purpose of this study was to quantitatively evaluate the Land Surface Temperature (LST) obtained from Moderate Resolution Imaging Spectroradiometer (MODIS) sensor images for estimating the maximum and minimum daily air temperature in the Taleghan watershed. For this purpose, the maximum and minimum daily air temperature data of three existing ground stations for the period 2009 to 2015 were obtained. Day and night LST and Normalized Difference Vegetation Index (NDVI) values ​​of MODIS were also prepared. The relationships between each of the effective variables and maximum and minimum daily air temperature in ground stations have been extracted using multiple linear regression method. The results showed that there was a significant correlation between maximum and minimum daily temperature of ground stations with day and night LST and NDVI from MODIS sensor. Therefore, these variables were used in regression relationships. The results of validation showed that the established relationships with all effective variables had the most accuracy. Therefore, the best model for estimating the maximum daily air temperature had , NSE and RMSE values ​​of 0.74, 0.74, and +4.7, respectively and for estimating the minimum daily air temperature had 0.71, 0.72 and +2.9, respectively. Therefore, by converting the surface temperature obtained from MODIS sensor images, the air temperature can be estimated with high accuracy on a daily and monthly scales for various studies.

Climate is a large system which is produced due to the relation and action between other large systems. If a change occurs in one of these systems, other systems will coordinate themselves with the change fast or slowly. The consequences of this coordination will impress the system that is starter of this change and an endless continuum of the links connects these systems together. According to the nature of the climate elements used in the form of different time scales, the time variations of climate elements are very important. Study of the time changes are performed via different models such as trend, seasonal, periodic and random models.....

The soil temperature is one of the most important properties. This factor has directly or indirectly affects on herbal growing and in some cases, herbal growing has a great task towards the air temperature. Soil temperature is varied in different but certain depths of daily and annual exchanges. In this study, we tried to analyze the temperature for different depths and its correlation in the soil rate with a side air temperature in Ardebil. We received the data records on temperature, etc., from Meteorological organization of Ardebil for the time period of 1372 to 1384. We then calculated correlation of the air temperature with the soil rate. This was followed by drawing linear estimation graphs. The results show that daily air temperature variations have a great contribution on the soil until 20 cm and the variations domain decreases with depth increasing. Temperature monthly variations in different depths show an adaptive state between soil rate variations and radiated energy variations which is lower in great soil depths. Annual temperature cycle shows time delay and temperature domain decay with depth. Generally, this study shows a meaningful correlation between minimum air temperature and minimum rate of land. But, temperature variations are not smooth in different depths of the soil.

The traditional method for studying non-stationary signals is spectrogram based on the short-time Fourier transform (STFT). The well known limitation of the STFT is the inherent trade-off between time and frequency resolution. The Wigner-Ville (WV) distribution has the best time-frequency resolution, but its draw back is generating cross-terms. The matching pursuit (MP) distribution based on using the Gaussian atom is always positive, does not include crossterm, and has convenient resolution. In this paper, we have shown in addition to the known properties, the MP distribution can also remove the additive noise inherently. On the other words, we are able to remove the noise just by limiting the algorithm iterations and without paying any additional cost. Although the MP distribution based on using the Gaussian atoms is always positive and it has convenient resolution, according to the MP the time marginal and the frequency marginal will not be obtained accurately. In this paper, it has been shown that by implementing the minimum cross entropy (MCE) technique according to the MP distribution as a priory positive distribution, the new extracted distribution has the most similarity to the MP distribution and it also satisfies the correct time and frequency marginal.

Internal temperature of allograft kidney at cold ischemic time is very important because it has a direct effect on prognosis of graft survival as well as patient survival. The fit temperature (0-4 centigrade) , prevents ATN. External temperature of allograft kidney at cold ischemic time is due to direct effect of ice and internal temperature in early time of cold ischemic time is due to direct effect of cold irrigation solution. During 1998, twenty cases of allograft kidney were selected randomly. Mter donor nephrectomy, kidney was placed in ice and irrigation with cold solution was begun. In each case 5 tubes were selected. In tube number one some of irrigation solution was poured and temperature of that was measured by automatic thermometer. In number 2 to 5 tubes fluid that exit from vein of allograft kidney flowing each 100 ml solution, gathered and temperature of those measured. Temperature of number 5 tube was nearly the same as cold solution. This study suggests that after flowing minimum 500 ml cold irrigation, internal temperature of allograft kidney (temperature of t1uid exit from vein) and temperature of cold irrigation is close to each other.

The global warming process during last century has not only affected on amount of atmospheric parameters but also affected on onset and end of each atmospheric parameters. The air temperature trend has been increasing during recent decades, especially in the regions such as Iran which is located in dry and semi-dry world belt. In this investigation, using Mann – Kendall statistical test, which is one of the proposed methods of World Meteorological Organization (WMO) for time series analysis, the trend of seasonal maximum and minimum temperatures in Iran will be studied. Hence, In this research, the daily data of maximum and minimum temperature with spatial resolution of 0.5 *0.5 degree received from cell database in the world scale, available in data base: http: //hydro.engr.scu.edu/files/, and converted to utilizable file (.TXT) in mat lab software by using Grads software. In continuation, Mann-Kendall script code, executed for a 21550*2058 matrix to calculating the threshold trend of 95% in Mat lab. We use from Arc GIS software for graphical representation of results. The results of this research indicate that the maximum temperature of northwest and southeast of Iran is without trend (trendless) in every four seasons, and in the winter, north-eastern of Iran have the least area. In the autumn, the increasing trend of maximum temperature seem more in the eastern area and Fars, whereas, the maximum temperature of autumn in without trend (trendless) in central and northwest area of Iran. The minimum temperature has increasing trend in the most regions of Iran. In this relation, the increasing trend of minimum temperature in winter is completely obvious in northwest, Zagros and southeast of Iran.

A vortex tube is a mechanical device for separating a stream of compressed air into two streams of colder and warmer air than the inlet stream at the same time. Simple design, small volume and no need for repair, caused this dual-purpose device to be considered in the industry. In the paper, using simulation and computational fluid dynamics technique, the effect of inlet air pressure on the performance of a vortex tube device has been investigated. To solve the flow field equations, the k-ε,turbulence model is used and the model geometry is considered constant. The results show that each vortex pipe has an optimal working pressure that is both economically and economically justifiable. This working pressure was 4. 8 bar in the current project. The simulation results show that for cooling purposes, using a mass ratio of 0. 3 will cause a higher separation in the cold output and for heating purposes, it is recommended to use a cold mass ratio of about 0. 8.