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Telling or not telling story clearly distinguishes between narrative and non-narrative texts. As in narrative texts, there is a narrator, so there should be at least one audience. The most important factors, which determine the characteristics of the audience can be enumerated as: “level of narrative”, “level of narrator’s participation” and “level of his/her perception”. Here, in addition to explanation of two kinds of inter- and extra- text audience, we try to introduce direct and indirect signs of the presence of the audience. Thus the essential questions, which form the foundation of our study, are: “What is the difference between narrative and non-narrative texts?”, “How direct and indirect signs of the presence of the audience manifest in a story?” and the last question is: “What’s the meaning of inter- and extra- text audience in a text?”. This study through descriptive-analytic method and use of library resources represents direct and indirect signs of presence of the audience and it also explains differences between inside and outside the text audience in stories and narrative texts. The results of this study show that inside the text audience is identical with imagery addressee and outside the text audience is a real reader.

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Quality of coastal water is of great importance in environment and other applications. Therefore, studying the quality of this water is quite vital. Traditional methods of water quality studies are time consuming processes that lead to pixel-based information and also impose a great deal of costs. Using stelllite images and remote sensing can play an important role in enhancing the outcome of these studies. In this research, by field sampling of secchi depth, simultaneous to the satellite pass; an experimental statistic-mathematical model was fitted for the acquired data in the field and the processed images of the IRS-LISS-III sensor. The results indicated good relations between the Secchi depth and the radiance received by the sensor. The fitted model can be used to map Secchi depth in coastal areas.

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Total Perceptible Water (TPW) is an important parameter in climatology and weather forecasting and is directly related to any climate process. There are three approaches to estimate this parameter i.e. using radiosonde, using GPS and calculating from satellite images where the first two are localized and the last one can give an instant view of TPW in a vast region. The algorithm used for the TPW calculation from MODIS images is related to the ratio of the reflectance in a water vapor absorbing channel and the reflectance in a non-absorbing channel. Due to strong horizontal variation in the surface reflectance in non-absorbing channels, the retrieved TPW varies strongly from one pixel to its neighboring pixels while it is believed that the horizontal gradient of TPW is very weak. To solve this problem, a damping coefficient was added to the non-absorbing channel reflectance. It is found that this coefficient differs for different surface covers. The current work presents a procedure for calculating these coefficients. The results of a comparison between modified TPW and those extracted from GPS data showed a R² of 0.81 whilst this was about 0.67 for non-modified MODIS TPW.