Rapid Estimation of the Epicentral Distance in the Earthquake Early Warning System around the Tehran Region, Iran

ABSTRACT The estimation of epicentral distance is a critical step in earthquake early warning systems (EEWSs) that is necessary to characterize the level of expected ground shaking. In this study, two rapid methodologies, that is, B‐Δ and C‐Δ, are evaluated to estimate the epicentral distance for use in the EEWSs around the Tehran region. Traditionally, the B and C coefficients are computed using acceleration records, however, in this study, we utilize both acceleration and velocity waveforms for obtaining a suitable B‐Δ and C‐Δ relationships for the Tehran region. In comparison with observations from Japan, our measurements fall within the range of scatter. However, our results show a lower trend, which can strongly depend on the few numbers of events and range of magnitude (small‐to‐moderate) of earthquakes used in the current research. To improve our result, we include some large earthquakes from Iran, Italy, and Japan with magnitude larger than 5.9. Although the optimal trend is finally obtained by fitting a line to the distance‐averaged points, we conclude that the same trend and relationship as Japan can be used in Tehran early warning system. We also found that B and C parameters are strongly compatible to each other. As time windows of 3.0 and 0.5 s after the P onset are chosen respectively to compute the B and C values, so by selecting the C parameter as a proxy of B parameter to estimate the epicentral distance, we may save significant time in order of about 2.5 s in any earthquake early warning applications.

Investigating the Effect of Knowledge Management on the Success of using Customer Relationship Management based on the Mediating Role of Organizational Factors (Case Study: Municipality of Tehran, Region 22)

The present research studies the effect of knowledge management on the success of customer relationship management by considering the effects of organizational factors as a mediating factor. The type of research is applied and the method is descriptive survey. The statistical population of the study is the managers and experts of the municipality of Tehran 22nd district, that 207 of them were studied in the form of a statistical sample. Data analysis was performed using single-variable linear regression and confirmatory factor analysis. The results showed that the variables of customer relationship management technology, customer orientation and knowledge management capabilities were significantly influenced by the success of customer relationship management. Also, the variables of customer relationship management experience and organizational factors have a significant effect on the success of customer relationship management.

The main factors affecting the character of housing construction in Iran

The article examines the main objective factors affecting the development of housing construction in Iran. In terms of population per unit area, Iran ranks 21st in the world. However, the density of the population varies by territory, this is because only 30% of the territory has a relatively sufficient amount of water to provide the population. The population is unevenly distributed. It is characteristic that in different regions of Iran the urban population is different in its specific weight. So, in the Tehran region is 27.2%, and in Chakharmakhal and Bakhtiari - 0.87% of the total population. Population growth stimulates the development of cities and will require an increase in the number of dwellings, as well as improving their quality. As you know, the climate of Iran has a pronounced change of seasons, and different geographical regions of Iran differ in their climatic conditions. Particular attention should be given to architectural and construction recommendations that affect the design of medium-height houses in seismically hazardous areas, especially in Central Iran. At present, the state policy of Iran in the field of housing construction is carried out in three directions - three types of construction: free housing, mixed construction, social housing.