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Background: The first confirmed cases of COVID-19 in Iran were reported on February 19, 2020. This study aimed to analyze the epidemic curves and to investigate the correlation between epidemic parameters and furthermore to analyze the impact of control measures on the spread of COVID-19 in Iran during 365 days of the epidemic. Methods: We used data from February 20, 2020, to February 18, 2021, on the number of COVID-19 cases reported by Iranian governments. Pearson correlation coefficient was applied to investigate the correlation between different epidemic parameters. The number of daily deaths per daily new cases was averaged to calculate daily death rate and the same method was used to investigate the rate of daily positive tests. Furthermore, we employed two different methods to calculate the effective reproduction number using reported data. Results: The results showed that there was a strong correlation between the number of daily deaths and the number of daily new cases (specially the admitted cases). The results also indicated that the mean of daily death rate of COVID-19 during 365 days was 4.9 percent, and averagely 13.9 percent of daily tests results were positive. Furthermore, epidemic curves showed that implementing strict social distancing measures effectively reduced the number of confirmed cases. The effective reproduction curve indicated that social distancing is still necessary to control the spread of COVID-19 in Iran. Conclusions: Analyzing the prevention and control measures indicated that the strict social distancing implemented by the government effectively reduces the number of new cases and deaths. The curve of reproduction number also showed that effective reproduction number is still above one; hence, it is necessary to continue strict social distancing and control travelling to prevent causing another wave of outbreak especially in Persian New Year.

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Coordination is a main issue in software agent systems in particular, and in distributed artificial intelligence (DAI) in general. There are several reasons why multi agents need to be coordinate: Preventing anarchy or chaos, Meeting global constraints, Distributed expertise or resources or information, Dependencies between agents' actions, Efficiency. This paper represents a coordination model for MAS. This model use organizational structuring and negotiation. A coordination model is an formal framework useful to study and understand problems in designing programming languages and software architectures including several agents. In other words, a coordination model defines how agents interact and how their interactions can be controlled. In the model, we develop Linda paradigm and agents can be coordinate and communicate with them. Tuple space has a few partitions and tuple space manager control it. Each partition has precedence. We have been extended the Linda operations in model.