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The scientific view and analysis of folk culture causes to the understanding and recognition of nature of internal elements and factors in fluential in the process of oral culture. Storytelling is one of the oldest forms of oral folk literature. In ancient times, the storytellers used to transfer their history, traditions, religion, customs, heroism, and ethnic Pride from one generation to other generation. Basically, the story is created and objected when it is quoted from the language of its narrator. The storyteller or narrator finds his/her ego in the story, and in order to attract the reader or listener, employs the best of his/ her artistic taste and talent to help to further define the story. This cause changes in the structure and content of the story. The present study explores the role of story teller in the formation of the story, and seeks to find the teasons encouraging to make changes in course of creating a story. A note worthy point obsersved the authors during the recording and collecting the collecting the Amureh stories within the last two decades is that there are a huge lurden of various narrations of a single story due to the multiplicity of story tellers and their possible manipulation of the story.

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The diversity and abundance of quality characteristics of agricultural products, has been the main reason for the development of non-destructive methods. Machine vision and artificial intelligence are powerful techniques for diagnosing most physical, mechanical and chemical properties of agricultural products. Before export fruits are classified by shape, volume and weight. Ranking fruit through taste (sweet or tart) non-destructively plays an important role in marketing, choice power and its application. In this research, it was detect the taste of Thompson orange while combining artificial intelligence (AI) and visual machine technique. A closed circuit digital installed in special frame, under specific height and light was used to take picture from samples vertically. Also, an algorithm (program) based on AI was developed to diagnose the variety and taste of Thompson orange through apparent characteristics in Matlab software. The results showed that the success rate of taste determination for Thompson orange using ANFIS and ANN-GA (Artificial Neural Network-Genetic Algorithm) was 96.67 and 90.0% respectively.