فهرست مطالب a. darzi

With the social media engagement on the rise, the resulting data can be used as a rich resource for analyzing and understanding different phenomena around us. A sentiment analysis system employs these data to find the attitude of social media users towards certain entities in a given document. In this paper we propose a sentiment analysis method for Persian text using Convolutional Neural Network (CNN), a feedforward Artificial Neural Network, that categorize sentences into two and five classes (considering their intensity) by applying a layer of convolution over input data through different filters. We evaluated the method on three different datasets of Persian social media texts using Area under Curve metric. The final results show the advantage of using CNN over earlier attempts at developing traditional machine learning methods for Persian texts sentiment classification especially for short texts.

In this research, the applicability of DRAINMOD model for simulating water table fluctuations and subsurface drain discharge variations was evaluated at the consolidated paddy fields of Sari Agricultural Sciences and Natural Resources University. During free drainage period of a canola season (November 28, 2011- April 2, 2012), water table depths and subsurface drain discharges were measured in three subsurface drainage systems including drainage system with drain depth of 0.9 m and drain spacing of 30 m (0.9L30), drain depth of 0.65 m and drain spacing of 30 m (D0.65L30), and drain depth of 0.65 m and drain spacing of 15 m (D0.65L15). The reliability of the model was tested using the statistics including model efficiency (EF), percent error (PE), coefficient of determination (R2), root mean square error (RMSE) and mean deviation (AD). Mean values of measured and simulated water table depths in the calibration treatment (D0.65L15) were both 32.4 cm. For validation treatments, such values were, respectively, 24.1 and 14.1 cm for D0.65L15and 2.1 and 19.7 cm for D0.9L30. EF, PE, R2, RMSE and AD values for predicted drainage discharges ranged from 5.1 to -1.3, 9.1 to 21.6, 0.2 to 0.35, 0.08 to 0.11 and 0.07 to 0.1, respectively. Comparison of measured values with the simulation results showed that DRAINMOD model can be used as a practical tool for predicting the general pattern of water table and drain discharge variations in the study area.

Subsurface drainage is required to eliminate drainage problems and to provide year-round cropping conditions in large areas of the Northern Iran,spaddy fields.With regard to the specific characteristics of these fields such as presence of hard layer of clay at shallow depth and high rainfall in the wet seasons, using an appropriate equation is important for the design of subsurface drainage systems.In this research, the applicability of four unsteady- state drainage equations including Glover–Dumm, Van-Shilfgard, Dezeeuw– Hellinga, and Kraijenhoff– Maaslandwas evaluated to determine subsurface drain spacing in paddy fields. Measurement of water table depth was made daily during a canola growing season, from November 2011 to April 2012, in different treatments of subsurface drainage pilotof Sari Agricultural Sciences and Natural Resources University. Performance of each equation was evaluated using the statistics including efficiency (EF), percent error (PE), coefficient of determination (R2), root mean square error (RMSE) and mean deviation (AD).Among different equations, the Dezeeuw– Hellinga was the best equationfor estimating water table depth during the study period.

The temperature of water entering the soil or variation in soil temperature has a direct impact on soil hydraulic conductivity via the effect on water viscosity. In this research, the time variability of soil saturated hydraulic conductivity (Ks) was studied. The relation between soil temperature and fluid viscosity with hydraulic conductivity were also studied. The necessary experiments were conducted on Aboureyhan campus research farm located in Pakdasht, 25 km southeast of Tehran. 18 holes were digged in a plot and saturated hydraulic conductivity of soils were measured in these holes using inverse hole method. Experiments were carried out 12 times from 16-Aug-2005 to 14-Jun-2006. Investigations showed that the lowest value of Ks was obtained in winter when the soil and air temperatures are at minimum and by increasing the soil and air temperatures, these values increased too. Statistical analysis of experiments indicated that soil or air temperatures can considerably affect the results. Using the average of measured Ks to design drainage systems showed that neglecting the time variability of Ks may result in over or underestimating of drain spacing by 18.9% and 23.3%, respectively. Using the average of Ks values which was obtained in soil temperature of 16-20 oC had least effect on drain spacing, so it can be used as an average Ks to design drain spacing.

This paper was written on the structure of Inflection Phrase (IP)in Persian. In the Framework of X’ – Theory. IP is the unit of syntax analysis of language. In other words, every sentence is an IP. In Persian TP, MP, AspP and VP are the complements of I, T, Mood and Asp. During the inflection process, the head V cyclicly moves to the above mentioned head to accept the national content of aspect, modality, tense and subject agreement. The markers stand for these notional categories are of auxiliaries, affixes or clitics. In Persian, the only auxiliary verb is “budan” (in three forms: “ast”, “bud” and “bash”) which is appeared in the node of inflection. The other inflectional markers are tense, mode and subject agreement markers. Finally, we have analysed Persian inflection phrase on the basis of x-bar theory.Consequently, some key points and hints are proposed on Persian future tense, continuous aspect and passive voice