فهرست مطالب mojtaba dehghani

The current research was conducted with the aim of explaining the role of happy programs of the Nasim TV channel in strengthening internal unity and cohesion. The main question in this research is: What role do Nasim's happy programs play in strengthening internal unity and cohesion? In response to the research question, a hypothesis is proposed as follows: Happy programs of the Nasim TV channel play an effective role in strengthening internal unity and cohesion by attracting domestic audiences, paying attention to national culture and identity and expanding public trust in the society. This research is practical and has been done in a descriptive-analytical way. The statistical population of the research included the citizens of Tehran between the ages of 20 and 60 years, and the number of the statistical sample was estimated to be 384 people based on Cochran's formula. Sampling has been done by random method and the data was collected based on fun and periodic programs of the Nasim TV channel which have been broadcasted in different seasons in recent years. The findings indicate that Nasim's happy programs have been effective in terms of attracting domestic audiences, injecting a calming atmosphere in society, strengthening subcultures and national identity, and expanding public trust and it plays a role in strengthening internal unity and cohesion.

Due to the relation of mineralization zones with grade variability in porphyry copper deposits, the preparation of the three-dimensional model of these zones is one of the pre-estimation steps in evaluation this type of deposits. The quality of this model has a significant impact on the quality of the grade estimates, the proper design of long-term extraction and ultimately reducing the problems between the mine and the processing plant. The usual way to prepare this model is to use a constrained modeling technique, which is a complex and time consuming process. One of the possible solutions for the preparation of these models is the use of unconstrained methods, such as intelligent methods. This paper attempts to study the performance of artificial neural network and support vector machine in the separation of mineralization zones (including leached, hypogene and supergene zones) in Miduk copper deposit. The northing co-ordinate, easting co-ordinate and height of the samples are used as input variables, and the observed mineralization zones in them are used as the output variable. Investigating the results of these intelligent algorithms in the separation of geological zones shows that the support vector machine classifier has a better performance than the artificial neural network. The better performance of the support vector machine method is shown by 1) the higher accuracy of this method in the training and testing stages and 2) the comparison between the block model with the grade control observations.