Introduction: In the evaluation of Decision Making Units (DMUs) using Data Envelopment Analysis (DEA) models, more than one DMU may be identified as efficient. So ranking them is necessary for Decision Makers (DM). One of the main problems in ranking DMUs, by using Data Envelopment Analysis, is the ranking of non-extreme efficient DMUs. Most of the existing methods can only rank extreme DMUs.Aim: In this paper, we propose a method to rank non-extreme DMUs in Tv.Materials and Methods: We rank non-extreme DMUs by finding a positive convex combination (with the best score) of extreme efficient DMUs located on the minimum face containing the non-extreme DMU.Results: Our proposed method can rank all efficient DMUs in 3 steps: at first, extreme and non-extreme efficient DMUs must be identified (It can be done by AP model). Ranking related score for each extreme DMU can be attained by one of the existing ranking methods that can rank extreme DMUs. Then for obtaining ranking related score for non-extreme DMU, we consider the face with minimum dimension, containing the non-extreme DMU. At last, by solving a model or its dual, and based on the ranking related scores of extreme efficient DMUs located on the minimum face containing the non-extreme DMU, a ranking related score for non-extreme DMUs can be obtained.Conclusion: Although, we rarely have got observed non-extreme efficient DMUs, we must theoretically be able to rank them, because, all virtual efficient DMUs are almost non-extreme. Our method can rank non-extreme efficient DMUs as same as extreme efficient DMUs.

Introduction: Exchange rate volatility can affect the performance of macroeconomics, especially the competitiveness of countries. Real exchange rate volatility indicates the instability and uncertainty in relative prices. It creates an unstable and uncertain environment in the economy. Therefore, the study of the impacts of exchange rate volatility has a great importance. In order to study its effect, it is necessary to first measure the volatility as a quantitative variable. For this purpose, various econometric methods have been introduced, such as the Generalized Autoregressive Conditional Heterogeneity (GARCH). In general, choosing an accurate method for modeling and predicting volatility in economic variables has always been one of the goals of many studies. If volatility is not calculated accurately, misleading experimental results are obtained. After the critique of Lucas (1976), it became important to pay attention to models with time variable coefficients. One of the implications of Lucas' critique is that the estimated coefficients to express the relationship between the variables cannot be stable. This issue is especially important in developing countries where the process of changing economic structures is faster and wider. So, the purpose of this study is to introduce a time-varying GARCH model to calculate the exchange rate volatility in Iran. Methodology: The research was based on the monthly exchange rate data (US dollar to Rial) in the market during 1985-2019. The data were extracted from the online database of the Central Bank of Iran. For the calculation of the volatility in economic variables, the tendency to use GARCH models is greater than other models. Among the GARCH models, GARCH (1, 1) is the most popular. However, according to Stock and Watson (2008), because of structural breaks, the most important problems of GARCH models is that they cannot make accurate predictions over the time. This gave more attention to time-varying parameter models and Markov chain Monte Carlo models. In these models, estimation coefficients can change over time. Also, the study of the financial time series shows that most of them are influenced by domestic or foreign political, economic and social events, such as financial crisis, oil shocks, war, political instability and sudden changes in foreign exchange policies. The effects of these events sometimes remain in the market for a long time. Therefore, it can be said that models with fixed coefficients do not have the ability to formulate the behavior of exchange rates, especially in the long-term horizons. Thus, it is necessary to use time-varying models with variable coefficients over time. In this study, in addition to conventional GARCH models, a time varying GARCH (TVGARCH) is introduced to show the different behaviors of exchange rate over time. For this purpose, the TVP-SVM model based on the model introduced by Koopman and Hol Uspensky (2002) is used to examine the exchange rate volatility in Iran. In this study, following Chan (2017), the Monte Carlo Markov Chain (MCMC) approach is used to estimate fixed coefficients and variable coefficients over time. Also, the Bayesian approach and the Markov chain algorithm have been used to simulate the prior distribution if common functions. Results and Discussion: In order to calculate exchange rate volatility using GARCH family models, the ARIMA model was first estimated using the Box-Jenkins method, and then the GARCH model was estimated on the ARIMA model residuals. The results of the Zivot-Andrews unit root test showed that the exchange rate has a non-stationary level. The test also confirmed the existence of a structural break in the time series. The estimated values ​​for the coefficients of the GARCH and EGARCH models showed that the conditional volatility in this period is positively affected by the amount of variance in the previous period. Also, more than 95% of the variance of each period is transferred to the next period. The estimated coefficients also showed that there is a significant difference between the effect of good and bad news on exchange rate volatility, good news (i. e., the news that increases the dollar price) compared to bad news (i. e., the news that decreases the dollar price) have greater impacts. As the results of the TVGARCH model showed, the volatility average was 0. 358 with 90% confidence, and the logarithm of the variance index was, thus, in the range of-0. 79 to 1. 557. In the calculations, ϕ represented the effect of the variance of the previous period on the variance of the current period. It was positive and indicated that approximately 96% of the volatility created in each period was transferred to the next period. Also, α represented the relationship between the exchange rate volatility and the exchange rate in each period. The average obtained for this coefficient was positive, implying that, in periods when the exchange rate increases, the exchange rate volatility is higher. According to the comparisons performed on the sample and based on the MSE criterion, TVGARCH is the most accurate, and GARCH is more accurate than EGARCH. Moreover, according to the QLIKE criterion, the TVGARCH model is more powerful than the other two conventional models, and the EGARCH model has a higher accuracy than GARCH. Conclusion: According to the results, the TV-GARCH model is more powerful than conventional GARCH models. This indicates structural failure and changes in the behavior of the exchange rate in the Iranian economy. It has caused the relationship between the components of the conditional variance to change over time. In other words, there are different values ​​for GARCH coefficients in different periods. According to the results of the TV-GARCH model, the relationship between exchange rate and volatility has been varied over the time, which implies changes in the behavior and motivation of economic agents and the structural changes in the Iranian economy. According to the results, the use of the TV-GARCH model instead of the conventional GARCH with fixed coefficients is recommended.

Summary Ground penetrating radar (GPR) method is a non-destructive method for detecting shallow subsurface objectives based on the transmission of electromagnetic waves into the earth and the recording of received reflections from the sent waves. Noise recording of GPR data is inevitable. Noise attenuation is one of the most important and most significant steps in GPR processing. GPR data contains a variety of noise types. Random noise during data acquisition affects the quality of the data. Several noise reduction techniques have been proposed in various papers. In this paper, two methods of total variation (TV) and group sparsity total variation (GSTV) are used to reduce noise from GPR data in rational dilation wavelet transform (RADWT) and dual-tree rational dilation wavelet transform (DTRADWT) spaces. The TV method is an inversion method for noise attenuation of data. The developed type of TV is called GSTV. TV and GSTV methods are very effective in noise attenuation. However, due to the presence of random noise in all frequencies of the data, it is difficult to reduce noise in the data...

In the evaluation of decision making units (DMUs), by using the ordinary data envelopment analysis models, the projected point may be considered as a target point. Various orientations lead to various targets. The selection of one of these projected points or other designated efficient points as targets, is a considerable problem in target setting. There are different criteria for the selection of such suitable targets. In this article, we introduce a method for target setting, on the basis of ranking in Tv. Since most of the designated points for targets are non-extreme, we propose a method for ranking non-extreme DMUs, based on a convex combination (with the best score) of extreme efficient DMUs, located on the minimum face containing the non-extreme DMUs.

The purpose of this article was to study how the dimensions of the Ashura movement represented in tv. The analysis unit, items and statistical population, included all programs that were broadcast in from channels 1, 2, 3, 4, Amoozesh, Ofogh, Shoma and Jam–e Jam of IRIB in the first 13 days of Muharram in 2019. The sample size was equal to the statistical population of the research and all were talk show and mixed program regarding to the purpose of the research. The results showed that more than half of the studied programs (52.4%) were related to the cognitive aspects and 38.4% were related to the emotional aspects of Imam Hussein movement. Almost 10% of the their times included common items (e.g. Greetings, introducing program and expert, ways to communicate with the program, etc.). The characteristics and abilities of Imam Hussein to save man and society and the expression of moral characteristics of his family and companions were discussed 28.3% of the time. Only 4.5 percent of the expert items were associated to the causes of Imam Hussein's uprising, and this issue as an independent issue was not much considered in the programs. The historical background of the uprising in almost 15% and the events related to the movement in almost one-fifth (18.5%) of the time of programs were discussed. The reasons and goals of the uprising of imam hosein and to critique the conflicting views in this regard, which is the basis of the epistemological dimensions related to the Ashura movement, must be discussed in the future.

Present research is a comparative study of females broadcast quality on Iranian TV (channel3) and on a satellite Gem TV. To reach our goal we have benefited from two methods of content analysis and reverse questionnaire. statistical population of this study consists of 140 broadcasted commercial ads on channel 3 and on Gem TV at 6pm and 11pm everyday over the months of January, February and March 2012 and April, may, June 2013.The figures obtained showed ultimately that both channels additional to displaying female routine functions, have been attempted to make changes in the way of their reflection and the channels have not utilized the females only as a factor for attracting audience.

The procedure of setting the broadcast schedule for TV channels is considered one of the forming and identity-giving parameters of the channel, regardless of the broadcast content. Arranging the programs in an orderly manner, based on a specific logic in terms of thematic, and content factors, and based on the attractiveness and other effective factors, as well as according to the needs and tastes of the audience at different hours of the day, is considered one of the most important tasks and missions of the schedule setting unit in that channel. The goal of the present article is presenting a content model for the broadcast schedule of Omid TV channel (specialized for the teenagers). To collect and analyze the required data, qualitative study and in-depth interview have been applied. In this regard, 25 experts, including academic-research experts and managers and programmers, were purposefully selected as interviewees. Based on the results, different policies in the field of programming structures, the topic of media activity, attention to “time”, attention to structures, content and topic, and the type and extent of geographical coverage, can be effective in determining the identity of the network and selecting programs to be included in the broadcast schedule.

“Institutionalizing” in means providing background and conditions that lead stability, persistency and performance by mutulipile others for desirable behaviors, always an essential issue, in the humanities and especially in management, but institutionalizing is a difficult, complex and long term process. In this condition, TV plays a significant role in influencing human thought and behavior. This study, answerd to this question that how can institutionalize any matter through the TV.Research community consist management experts that familiar with the concepts of media and media pundits that had been familiar with the concept of management. In the base of Grounded Theory and with snowball sampling, thirty expert has interviewed and general model for institutionalizing by TV is extracted. Emerged theory and model suggests that institutionalizing any matter has requires necessary background, creator conditions and adoption of appropriate strategies, although the role of confounding factors in this process do not should be covert out of sight.

Today, the main function of the media is to present their desired image to their audience. Therefore, it is of great importance that the image presented in the media, especially the overseas broadcasting networks, is a believable, multifaceted and aligned with the general policies of the Islamic Republic of Iran. The main question in the current research is that the image presented of Iran on the two websites of France Press TV and France 24 are aligned or in opposition to each other? In the period of February 2020, all the content uploaded on the subject of Iran on the website of Press TV France and France 24 were checked using the content analysis method. The findings of the research showed that the focus of the French Press TV website in presenting the image of Iran was on news and analyzes with political and defense issues. On the other hand, in France 24, the large amount of political content from Iran, along with the small amount of social and cultural news with special bias, presents the image of Iran as a violent and lawless country. It is suggested that France Press TV, while developing quantitatively and qualitatively with more monitoring, should have a faster reaction to the reports of France 24 and pay more attention to non-political programs in addition to political programs.