The diesel oil type S-3 specified for diesel engine has limited the suitability for diesel trucks for 8000 km, but didn't clarify its suitability if used in tractor engines.It is known that the work style of farm tractor differs from that of other vehicles where tractors are used for all the activities in sever conditions and under the complete usage of the available power and capability, so there is no sign or indication of the usage period of this oil in tractor's engine. The oil has been used on Cirta C6806 tractors. The manual book of the tractor's engine, Deutz recommends changing the oil every 100 hrs. Therefore the main goal of this research is to give the recommended working hours for S-3 diesel oil when used in farm tractor engines. Five tractors have been used in this research and the engine oil was changed for the interval period of 20 hrs starting from 20, then 40, 60, 80, 100 and 120 hours. At the end of each period the oil of the five tractors was mixed and a sample was taken for testing. This procedure was repeated three times in order to obtain accurate results with statistical analysis. The statistical analysis results showed that the S-3 diesel oil deteriorates after 40 working hours because of the great consumption of the oil after this period and therefore this research recommends that the usage period of S-3 oil should not exceed more than 40 working hours when it is used in tractor's engine.
The present paper, practical methods of professional translation, discusses the most important methods to achieve an accurate effective translation from the source language text to the equivalent target language text.
The present study suggests that practical translation like any literary activity is of six main stages that follow sequential order to achieve an accurate translation: (choosing the foreign text to be translated, the author of the text permission, the text translation, considering the title contextual meaning, reviewing the text translation, and finally finding a good publisher).
چکیده
پژوهش حاضر که با عنوان گامهای عملی یک ترجمهء حر
... Show MoreThe diseases presence in various species of fruits are the crucial parameter of economic composition and degradation of the cultivation industry around the world. The proposed pear fruit disease identification neural network (PFDINN) frame-work to identify three types of pear diseases was presented in this work. The major phases of the presented frame-work were as the following: (1) the infected area in the pear fruit was detected by using the algorithm of K-means clustering. (2) hybrid statistical features were computed over the segmented pear image and combined to form one descriptor. (3) Feed forward neural network (FFNN), which depends on three learning algorithms of back propagation (BP) training, namely Sca
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