somayyeh jabbari

In traditional rhetoric, pun and saj’ (Persian rhymed prose) are two figures of speech that shape the beauty of language through musicality of speech. Abdolghaher Jorjani considers the merit of pun in conceptual requirement; it is well received when meaning calls for it. In Masnavi Ma'navi, by Jalaleddin Mohammad Balkhi aka. Rumi, the use of pun and saj’ is remarkable, but the linkage created between these figures of speech and meaning gives a distinctive feature to Rumi’s poetry. This can be observed, for instance, in binary oppositions which have made use of the literary device of pun and saj’. Accordingly, the hypothesis of this research is that many binary oppositions in Masnavi are related to those words which have pun or saj’ in them, and the opposition between verbal balance and conceptual distinction adds to the eloquence. As the theoretical background of the research, a structuralist approach to literary criticism is initially considered to extract binary oppositions, which are then are separated and classified based on the puns and saj/. The research method is descriptive and the results of analyses are as follows: (1) binary oppositions in Masnavi are accompanied by puns and saj’; (2) among all types of binary oppositions in pun and saj’, pun in different initial letters and parallel use of saj’, which both have the strongest sense of musicality,  show the most frequency; (3) many of the binary oppositions appearing in the words with pun or  saj’are not included in diction rules of the language and are Rumi’s poetical innovations; (4) the function of binary oppositions accompanied by pun and saj; is considerable in rhyme making or verse making.

To determine the suitable indices for vegetation cover and production assessment based on the remote sensing data, simultaneous digital data with field data belonging to the spring rangeland of the Semirom-Isfahan province were analyzed. During two years of monitoring the annual, grass, forb, and shrub vegetation cover and the total production data from 86 were collected. The Global Positioning System (GPS) was used to measure the coordinates of plots and transects. Geometric correction and histogram equalization were applied in image processing, and image digital numbers were converted to reflectance numbers. In the next stage, all vegetation indices were calculated from the Advanced Wide Field Sensor (AWiFS) image data and compared with the vegetation cover estimates, at monitoring points, made during field assessments. A linear regression model was used to select suitable vegetation indices. The results showed that there were significant relationships between the satellite data and the vegetative characteristics. Among the indices, the Normalized Difference Vegetation Index (NDVI) consistently showed significant relationships with the vegetation cover. The estimation of the vegetation cover with the NDVI vegetation index was more accurately predicted within rangeland systems. Using the produced model from the NDVI index vegetation crown cover, percentage maps were produced in three class percentages for each image. Generally introduced indices provided accurate quantitative estimation of the parameters. Therefore, it was possible to estimate cover and production as important factors for range monitoring using the AWiFS data. The Remote sensing data and the Geographic Information System are the most effective tools in natural resource management.