مطالب

The present study aims at exploring kinship terms and the different ways in which they are used to refer to and address relatives and non-relatives in Hawrami , an Iranian language spoken in Paveh, a border city in Kermanshah province. The relevant linguistic and cultural data are obtained primarily by one of the researchers as a native speaker of the dialect and through field works and interviews with native speakers. In addition to analyzing consanguineal and affinal terms, and words for step-relatives, some space is also devoted to discuss pragmatic aspects of the words, particularly in contexts where the terms are used to address relatives as well as non-relatives. Considering the fact that the authors came across no serious study of Hawrami kinship terminology, the present study might be one of the first preliminary steps to a better understanding of the cultural and anthropological aspects of this Iranian dialect.

This paper is an attempt to explore the prepositions used to encode the agent in Persian passive constructions. According to Givón (1983) the main function of the passive constructions is to defocus the agent. As the general trend in Persian is to omit this defocused agent, we will stylistically divide the passive constructions into two main sub branches, namely unmarked and marked passives according to whether or not the agent is included. Having analyzed the prepositions using in the passive construction (e.g. t { v { ssot-e, be d { st-e, b A , { z suy-e, { z t { r { f-e, and be v { sile-y-e) a complete semantic characterization of the type of agent that normally occurs with these prepositions will be provided. The results indicate that, in contrast to some linguists who treated the prepositions in the passive construction as stylistic forms, they are not always interchangeable; in fact they are meaningful which have a prototype for the type of agent that co-occurs with them.

The aim of this paper is to develop a prediction model of energy demand of Iran’s industrial sector. For that matter a Markov Chain Grey Model (MCGM) has been proposed to forecast such energy demand. To find the effectiveness of the proposed model, it is then compared with Grey Model (GM) and regression model. The comparison reveals that the MCGM model has higher precision than those of the GM and the regression. The MCGM is then used to forecast the annual energy demand of industrial sector in Iran up to the year 2020. The results provide scientific basis for the planned development of the energy supply of industrial sector in Iran.

In this paper we try to give a description of the juridical status of religious minorities, Muslim or otherwise, in the constitution of the Islamic Republic of Iran. We also deal with the question of whether non-Muslim minorities are free to perform their religious practices and the extent of their freedom.

Geographic information and analysis provide a wide range of data and techniques to monitor and manage natural resources. As an important case, in arid and semi-arid areas, water management is critical for both local governance and citizens. As a result, the estimation of water potential brought by snowmelt runoff and rainfalls seems to be very useful and important for these areas. Hydrological modeling needs vast knowledge about integrating all relating parameters. In this work, different data sources including the remote sensing observations, meteorological and geological data are integrated to supply spatially detailed inputs for Snowmelt Runoff Modeling in a watershed, located in Simin-Dasht basin in the northeast of Tehran, Iran. Because of high temporal frequency and suitable spatial coverage, MODIS optical images have been chosen to map snow cover. The MODIS 8-day snow map product with spatial resolution of 500m (MOD10A2.5) is used to compute the snow cover area. In addition, during the snowmelt period in 2006-2007, archived meteorological and geological data are used to provide snow runoff modeling (SRM) parameters and variables. Also Landsat ETM+ images with better spatial resolution (30m) and less temporal coverage (16 days) are used in 2007 snowmelt period to compare the model accuracy with same conditions. Evaluation of the runoff outputs in both of models reveals good agreement with real data that prove SRM capability in modeling basin’s daily and weekly runoff. Model accuracy shows better satisfactory of snow runoff modeling results within snow cover area derived from Landsat ETM+ data and MODIS snow product was less accurate in modeling. Although using MODIS model accuracy was less, but still it is recommended due to less further process and providing better temporal coverage during snowfall and snowmelt season. Future works in this criterion could be concentrated on SRM forecast improvement using fusion with other measurements or combining physical models.