Determining proper strategies for Iran’s dimensional stone mines: a SWOT–AHP analysis

Iran has very high potential for production and export of dimension stone (rock quarried to size and shape specifications); nevertheless, in spite of growing mine production during the past decade, in many instances this potential has been overlooked. Construction, decorative, and facing stones of Iran are among the highest-quality products in the world. In this paper, Iran’s dimensional stone mines are analyzed using strengths, weaknesses, opportunities and threats (SWOT) analysis in combination with analytic hierarchy process (AHP). SWOT analysis is a tool commonly used for analyzing both the internal and external environments in order to attain a systematic approach and support for a decision situation. Conventionally, SWOT analysis is qualitative and does not quantify the effect of the factors. Consequently, it is not effective in priority setting. To overcome this limitation, SWOT analysis has been used in combination with other quantitative multi-criteria decision making methods especially the AHP. In this study, first an environment analysis was performed by an expert team familiar with these mines. In this way, the SWOT factors were identified and the subfactors which had very significant effects on the success of these mines were determined. Using the SWOT subfactors, the SWOT matrix and alternative strategies based on these subfactors were developed. Subsequently, the strategies were prioritized and the best strategies for Iran’s dimensional stone mines were determined.     

Comparison of cokriging and adaptive neuro-fuzzy inference system models for suspended sediment load forecasting

The present research was carried out by using artificial neural network (ANN), adaptive neuro-fuzzy inference system (ANFIS), cokriging (CK) and ordinary kriging (OK) using the rainfall and streamflow data for suspended sediment load forecasting. For this reason, the time series of daily rainfall (mm), streamflow (m³/s), and suspended sediment load (tons/day) data were used from the Kojor forest watershed near the Caspian Sea between 28 October 2007 and 21 September 2010 (776 days). Root mean square error, efficiency coefficient, mean absolute error, and mean relative error statistics are used for evaluating the accuracy of the ANN, ANFIS, CK, and OK models. In the first part of the study, various combinations of current daily rainfall, streamflow and past daily rainfall, streamflow data are used as inputs to the neural network and neuro-fuzzy computing technique so as to estimate current suspended sediment. Also, the accuracy of the ANN and ANFIS models are compared together in suspended sediment load forecasting. Comparison results reveal that the ANFIS model provided better estimation than the ANN model. In the second part of the study, the ANN and ANFIS models are compared with OK and CK. The comparison results reveal that CK was a better estimation than the OK. The ANFIS and ANN models also provided better estimation than the OK and CK models.     

Soil Moisture Estimation in a Vegetated Area Using Combination of AIRSAR and Landsat5-TM Images

High difference between dielectric constant of water (dielectric constant about 80) and dielectric constant of dried soil (dielectric constant about 2–3) makes Synthetic Aperture Radar (SAR) highly capable in soil moisture estimation. However, there are other factors which affect on radar backscattering coefficient. The most important parameters are vegetation cover, surface roughness and sensor parameters (frequency, polarization and incidence angle). In this paper, the importance of considering the effects of these parameters on SAR backscatter coefficients is shown by comparing different soil moisture estimation models. Moreover, an experimental soil moisture estimation model is developed. It is shown that this model can be used to estimate soil moisture under a variety of vegetation cover densities. The new developed model is based on combination of different indices derived from Landsat5-Thematic Mapper and AIRSAR images. The AIRSAR image is used for extraction of backscattering coefficient and incidence angle while TM image is used for calculation of Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Normalized Difference Water Index (NDWI) and Brightness Temperature. Then a soil moisture estimation model which is named as Hybrid model is developed based on integration of all of these parameters. The accuracies of this model are assessed in the NDVI ranges of 0–0.2, 0.2–0.4 and 0.4–0.7 by using SAR data in C band and L band frequencies and also in different polarizations of HH, HV, VV and TP. The results show that for instance in L band with HV polarization, R-square values of 0.728, 0.628 and 0.527 are obtained between ground measured soil moisture and estimated soil moisture values using the Hybrid model for NDVI ranges of 0–0.2, 0.2–0.4 and 0.4–0.7, respectively.     

Seismic displacement analysis of embankment dams with reinforced cohesive shell

Suitable materials for use as shell of embankment dams are clean coarse-grained soils or natural rockfill. In some sites these materials may not be available at an economic distance from the dam axis. The use of in-situ cohesive soils reinforced with geotextiles as the shell is suggested in this study for such cases. Dynamic behavior of reinforced embankment dam is evaluated through fully coupled nonlinear effective stress dynamic analysis. A practical pore generation model has been employed to incorporate pore pressure build up during cyclic loading. Parametric analyses have been performed to study the effect of reinforcements on the seismic behavior of the reinforced dam. Results showed that reinforcements placed within the embankment reduce horizontal and vertical displacements of the dam as well as crest settlements. Maximum shear strains within the embankment also decreased as a result of reinforcing. Furthermore, it was observed that reinforcements cause amplification in maximum horizontal crest acceleration.     

Moment tensor inversion of nine events in Iran using INSN data

In this research, moment tensor (MT) inversion procedure in frequency domain is applied to nine events in order to evaluate the data efficiencies in computing source parameters of earthquakes in Iran. The events are recorded by Iranian National Seismological Network (INSN) stations, currently comprising 22 broadband stations. For the purpose of this study, first, the inversion procedure is applied to obtain source parameters. Then, the results obtained here are compared with those of Harvard global centroid moment tensors (GCMT) in order to estimate their reliabilities. The results show reasonable consistencies with those of Harvard GCMT within 0.075 uncertainties in logarithmic scalar moment or 0.05 in moment magnitude and 20° in Kagan angle for focal angles. Furthermore, according to the present research, the calculated source parameters are not significantly sensitive to the azimuthal gap.     

Ellipsoidal Neumann geodetic boundary-value problem based on surface gravity disturbances: case study of Iran

An ellipsoidal Neumann type geodetic boundary-value problem (GBVP) for the computation of disturbing potential on the surface of the Earth based on the surface gravity disturbance as the boundary data is formulated. The solution methodology of the GBVP can be algorithmically summarized as follows: (i) using global navigation satellite systems (GNSS) coordinates of the gravity stations, the surface gravity disturbances are generated as the boundary data. (ii) Applying the deflection correction to the gravity disturbances to arrive at the derivative of the surface disturbing potential along the ellipsoidal normal. (iii) Removing the low frequencies part of the gravity field using harmonic expansion to degree and order 110. (iv) Using the short wavelength part of the corrected gravity disturbances derived in the previous section as the boundary data within the constructed GBVP to derive the short wavelength disturbing potential over the Earth surface. (v) The computed shortwave length signals of disturbing potentials are converted to disturbing potential values by restoring the removed effects.     

Isolation and characterization of two crude oil-degrading yeast strains, Yarrowia lipolytica PG-20 and PG-32, from the Persian Gulf

Among six crude oil-degrading yeasts that were isolated from an oil-polluted area in the Persian Gulf, two yeast strains showed high degradation activity of aliphatic hydrocarbons. From an analysis of 18S rRNA sequences and biochemical characteristics, these strains were identified as Yarrowia lipolytica strains PG-20 and PG-32. Gas Chromatography (GC) analysis of the crude oil remaining in the culture medium after 1 week at 30°C showed that the strains PG-20 and PG-32 degraded 68% and 58% of crude oil, respectively. The optimal growth condition and biodegradation of hydrocarbons was in ONR medium with an acidic pH (pH5). These two strains may degrade aliphatic hydrocarbons more efficiently than aromatic hydrocarbons, although strain PG-20 had better degradation than strain PG-32. The two Y. lipolytica strains reduce surface tension when cultured on hydrocarbon substrates (1% v/v). These strains showed a cell surface hydrophobicity higher than 70%. These results suggested that Y. lipolytica strains PG-20 and PG-32 have high crude oil degrading activity due to their high emulsifying activity and cell hydrophobicity. In conclusion, these yeast strains can be useful for the bioremediation process in the Persian Gulf and decreasing oil pollution in this marine ecosystem.     

伊朗锡斯坦地区沙漠灾害区划(英文)

Desertification process as a great problem affects most of the countries in the world.This process has a high rate in arid and semiarid areas.Today,human societies are encountering the desertification phenomenon as a serious problem which causes various irreparable damages to economic and social sectors.In order to assess desertification results in production of different regional models for their application in another region the indices should be re-investigated and adjusted to local conditions.Several models have been developed for desertification evaluation.The present study,attempts to assess quantitatively the desertification process has in an area located at Sistan plain of Iran(Niatak region as a case study) by using Modified MEDALUS method.The obtained results indicated that of the whole studied region(comprising 4819.6 acres),2651.56 acres(55%) are located in medium desertification intensity class,1269.48 acres(26.34%) are positioned in severe desertification intensity class,and 898.54 acres(18.64%) are placed in vary severe desertification intensity class.     

Enhanced nonlinear static analysis with the drift pushover procedure for tall buildings

In this study a new method for nonlinear static analysis based on the relative displacements of stories is proposed that is able to be implemented in a single stage analysis and considers the effects of an arbitrary number of higher modes. The method is called the extended drift pushover analysis procedure (EDPA). To define the lateral load pattern, values of the relative displacements of stories are calculated using the elastic modal analysis and the modal combination factors introduced. For determining the combination factors, six different approaches are examined. Buildings evaluated in this study consist of four special steel moment-resisting frames with 10–30 stories. Responses including relative displacements of stories, story shear forces and rotation of plastic hinges in each story are calculated using the proposed approaches in addition to modal pushover analysis and nonlinear dynamic time history analyses. The nonlinear dynamic analysis is implemented using ten consistent earthquake records that have been scaled with regard to ASCE7-10. Distribution of response errors of story shears and plastic hinge rotations show that a major part of error corresponds to the second half of the buildings studied. Thus, the mentioned responses are corrected systematically. The final results of this study show that implementing the EDPA procedure using the third approach of this research is able to effectively overcome the limitations of both the traditional and the modal pushover analyses methods and predict the seismic demands of tall buildings with good accuracy.