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.

Non-cooperative intelligent control agents (ICAs) with dedicated cost functions, can lead the system to poor performance and in some cases, closed-loop instability. A robust solution to this challenge is to place the ICAs at the feedback Nash equilibrium point (FNEP) of the differential game between them. This paper introduces the designation of a robust decentralized infinite horizon LQR control system based on the FNEP for a linear time-invariant system. For this purpose, two control strategies are defined. The first one is a centralized infinite horizon LQR (CIHLQR) problem (i.e. a supervisory problem), and the second one is a decentralized control problem (i.e. an infinite horizon linear-quadratic differential game). Then, while examining the optimal solution of each of the above strategies on the performance of the other, the necessary and sufficient conditions for the equivalence of the two problems are presented. In the absence of the conditions, by using the least-squares error criterion, an approximated CIHLQR controller is presented. It is shown that the theorems could be extended from a two-agent control system to a multi-agent system. Finally, the results are evaluated using the simulation results of a Two-Area non-reheat power system.

Statistical Shape Models are used to interpret shapes. They include mean and variance of corresponding points of training shapes. One of the most important challenges in building statistical shape models is to establish correct correspondences among landmarks in a training set. In this paper, the non-rigid CPD (Coherent point Drift) method is used to find correct correspondences among points. This method uses both Deterministic Annealing and a non-rigid scheme to register two shapes simultaneously. Then, the statistical shape model is built using a rigid transformation. The proposed method is evaluated using Compactness, Generalization ability and Specificity measures. The built model is compared to models created using the ICP (Iterative Closest point), TPS-RPM (Thin Plate Spline – Robust point Matching) and MDL (Minimum Descreption Length) methods by these metrics. The results show that the proposed method performs like the MDL regarding Specificity measure (0.21±0.06). The Compactness and Generalization ability measures of the proposed method are very similar to those for the MDL method. The run-time of our proposed method is about 68 seconds which is faster than non-rigid TPS-RPM and MDL approaches (390 and 3600 seconds respectively). Our results are superior to the ICP and TPS-RPM algorithms.