Present study used Translog cost function for determining Break point of paddy farms. Requested data set include inputs’ prices and quantities, and production amounts had been acquired from 500 rice farmers of Guilan province at 2009. Model used in this study is seemingly unrelated regressions (SUR). The results showed that labor and pesticides had the highest and lowest share of production costs, respectively. Accordingly, increasing labor wages puts the greatest effect on rice prices. Estimated returns to scale measure (ES) showed that there are increasing returns to scale in investigated paddy farms. Accordingly, splitting paddy farm will increase the cost of rice production and by increasing price of rice competitiveness of farmers reduced in compare with foreign competitors. Present study showed that the Break point of paddy farms was one hectare so farms less than one hectare will increase average production costs, significantly. A policy recommendation is that paddy farms less than one hectare should be integrated.

A strategy that integrates an organization's marketing goals into a cohesive whole, ideally drawn from market research, focuses on the ideal product mix in order to achieve maximum profit potential; the marketing strategy is set out as a marketing plan, a good idea, method, information, object, or service that is the end result of a process and serves as a need or want satisfier. It is usually a bundle of tangible and intangible attributes (benefits, features, functions, uses) that a seller offers to a buyer for purchase .Unlike the business’s variable costs, the fixed costs are not directly related to the creation of the products and services. Fixed costs are the costs incurred as a result of operating the business, such as overhead expenses, depreciation, rent, insurance and taxes. In the present study calculation has been done by assigning different parameter to any organization and finding Break-Even analysis by the use of Matlab Programming (simulation).

Here, the efficiency of the non-destructive Break-Off (BO) test was investigated for assessing the in-place compressive strength of steel fiber reinforced concrete (SFRC). SFRC was studied due to its advantages in increasing toughness and tensile and flexural strength in particular. To provide a through and comprehensive database, 24 mix designs were selected with cement contents of 400, 450 and 500 kg/m3 with constant water/cement ratio of 0. 4 for all mixes, two maximum aggregate sizes of 12. 5 and 25 mm along with steel fiber volume fractions of 0%, 0. 33%, 0. 67% and 1% for ages of 14, 28 and 90 days. A total of 360 BO tests were carried out in this investigation. Then, effective parameters of SFRC and BO test results were evaluated. In the BO method, the force required to Break off an in-place concrete cylinder of 55 mm in diameter and 70 mm long, is related to the compressive strength of the concrete from a predetermined calibration curve developed for concrete mix. The studies showed that volumetric percentage and features of steel fibers had a significant influence on concrete properties as well as BO test results. According to the experimental results it could be generally concluded that the influencing factors, namely, SFRC properties due to presence of steel fibers and BO test significantly affect the results as follows: Generally, for a constant W/C ratio, it can be concluded that raising the cement content increase the mean values of BO strength. It can be stated that the maximum aggregate size within the range of 12. 5– 25 mm has a negligible effect on the BO test results for SFRC with 1% steel fiber volume fractions as the average value of BO strength for 25 mm aggregate concrete was significantly more than the corresponding value for 12. 5 mm aggregate size for plain concrete. Moreover, the improving trend the BO strength with age is observed to be similar for all different concretes. Furthermore, increase of BO strength of SFR concretes respect to corresponding plain value is observed as concrete grows older. In addition, results showed that strength estimation based on a single general calibration curve is not feasible. Therefore, a specific calibration curve for each SFRC should be represented for a realistic assessment and interpretation of results. The coefficient of variation of the BO strength was in range of 4– 11%. The higher values are for concretes with higher amounts of fibers, especially at early ages. The reliability of the method seems to be good in which the coefficient of variation for each group of BO tests are below 11%. It should be noted that even under ideal conditions with a specific calibration it is unlikely that 95% confidence limits of better than ± 15% can be achieved for an absolute prediction of concrete compressive strength. The findings show that higher values are not only due to the lack of precision of the test procedure, but also due to the intrinsic heterogeneity of granular materials like concrete, particularly in presence of higher amounts of fibers.

One of the most widely used statistical topics in research fields is regression problems. In these models, the basic assumption of model errors is their normality, which, in some cases, is different due to asymmetry features or Break points in the data. Piecewise regression models have been widely used in various fields, and it is essential to detect the Breakpoint. The Break points in piecewise regression models are necessary to know when and how the pattern of the data structure changes. One of the major problems is that there is a heavy tail in these data, which has been solved by using some distributions that generalize the normal distribution. In this paper, the piecewise regression model will be investigated based on the scale mixture of the normal distribution. Also, this model will be compared with the standard piecewise regression model derived from normal errors.

Flexural strength test has a significant effect on the determination of failure strengths and cracking moment. According to ASTM-C78, the size and shape of used specimens were cubes by size (700*150*150 mm). Here, the efficiency of the non-destructive Break-Off (BO) and flexural strength tests was investigated for assessing the in-place compressive strength of steel fiber reinforced concrete (SFRC). In order to provide a thorough and comprehensive database, 24 mixtures were designed with various cement content, maximum aggregate size, steel fibre volume fractions and the constant water/ cement ratio of 0.4 for all mixtures. Then, effective parameters of SFRC and Break-Off and flexural strength test results were evaluated. The studies showed that volumetric percentage and features of steel fibers had a significant influence on concrete properties as well as Break-Off and flexural strength test results. According to the experimental results it could be generally concluded that the influencing factors, namely, SFRC properties due to presence of steel fibers and non-destructive tests significantly affect the results as follows: Generally, for a constant W/C ratio, it can be concluded that raising the cement content increases the mean values of Break-Off strength and Flexural strength. It can be stated that increasing the size of the aggregate causes an increase in strength. Also, the steel fibers restrain the development of internal micro-cracks in the concrete and thus contribute to the increase in bending strength, which causes improving Break-Off and flexural strengths. In addition, the conventional numerical regression model was developed in this study. Statistical indices were used to compare the efficiency and accuracy of the model. The result of this study confirmed the accuracy of the artificial neural network models in the determination of the compressive strength of concrete.

In this paper, we analyze the long -run relationship between inflation and Total Factor Productivity (TFP) in the Iranian economy during 1338-1380.For this purpose, we use Gregory -Hansen (1996) Cointegration test. Our Study proceeds at the following steps.1. We set up a multivariate model for the analysis of the long-run relationship between inflation and Total Factor Productivity (TFP). 2. We test the unit root properties of data, and the long-run relationship between variables in the presence of structural Breaks.3. We estimate endogenously the Break point data.Our results from cointegration tests and dynamic ordinary least square estimator show that there is a negative relationship between inflation and productivity.