Abstract: The purpose of this paper is to investigate the industrial wage inequalities based on Krugman model. For this, we’ve employed a panel method for 30 Iranian provinces during time period 2003-2007. The estimation results suggest that the new economic geography provides a good description of the spatial structure of wages in the provinces of Iran. Our findings indicate that market size and distance-weighted will have positive relationship with wages. The overall result of this study corroborates the notion of centralization in the Iranian economy. The large wage variations explained by economic geography could cause significant internal migration.

Abstract: Free energy calculations to predict binding ability of molecules to receptors are a main subject for drug design. A wide range of theoretical methods has been applied to the calculation of binding constants. This mini-review seeks to identify such methods to better achieve correct predictions for drug candidates.

Abstract: Present paper describes with the bulk arrival retrial queueing M^X / G₁, G₂, / 1 model with two phase service and Bernoulli vacation schedule wherein first phase service is essential and the next second phase service is optional. If the second phase service is not demanded by arriving customer then the single server takes a vacation period according to Bernoulli vacation schedule in order to utilize it to complete some supplementary work and such type of vacation is assumed working vacation. In the queueing model taken into present consideration, the concepts of Bernoulli vacation schedule and next optional service have been incorporated along with realistic provision that the server has an option to avail a vacation with probability p (q) or may continue to serve the next customer, if any with complementary probability just after the completion of first phase essential service i.e. before the commencement of second phase optional service. In the present paper, our central goal is to investigate the steady state behavior of the bulk arrival retrial queueing M^X / G₁, G₂, / 1 model with two phase service and Bernoulli vacation schedule. By introducing supplementary variables, Chapman Kolmogorov equations are established and then the probability generating functions (PGFs) for first phase essential service (FPES), next phase optional service (NPOS) and working vacation and for the number of the customers in the orbit at an arbitrary epoch are investigated successfully. Besides investigating PGF for different states of the queueing system taken into consideration, performance measures such as the long run probabilities for which the server is in idle state, FPES state, NPOS state and in working vacation state are also explored in order to focus the application aspect of the investigated PGFs. By the end of the present paper, some numerical illustrations of the investigated results for M^X / E_k / 1 model as special case of M^X / G₁, G₂, / 1 have been presented in Table 1 and Table 2 for varying parameters.

Abstract: A novel field of data mining has been spatio-temporal clustering focused on the new methods and techniques, which are able to adapt previous methods and solutions to the new problems. A set of geo-referenced time series are data generated by several devices like GPS, sensor station, cell phones and many other sensing device. This paper defines the the new K-means clustering grouping spatially and temporally correlated geo-referenced time series obtained from sensors in a specific geographic area. For all time series in the cluster, choosing the best forecasting parameters, we apply one of the most accurate and most efficient forecasting models of time series called ARIMA. This paper investigates a new mechanism to determine spatio-temporal distances measure between sensor stations in the same spatio-temporal neighborhood (cluster). By calculating, the best forecasting parameters applied for all time series in the same cluster proposed algorithm obtains more accurate and more efficient forecasting results, than forecasting time series independently one from other in space and time. We studied the accuracy of proposed model comparing it to the already known applied to compute prediction of time series and applying it to real life data.

Abstract: Present paper demonstrates mathematical modeling and evaluation of performance measures of k-out of-n repairable system wherein the most influencing constraints of human error and common-cause failure have been taken into consideration. Firstly the mathematical modeling is developed for performance analysis of k-out of-n repairable system with standby units involving human and common-cause failure. Then, a successful attempt has been made to evaluate various important performance measures such as availability of system, steady state availability and mean time of system failure (MTSF), mean operational time(MOT), expected busy period (EBP) and steady state busy period etc. Using the supplementary variable technique, Laplace transforms of various state probabilities are explored. Moreover, a particular case when repair rate follows exponential distribution has also been discussed. In addition, numerical illustration has also been presented in order to enable a better mode for understanding and testing the outcomes explored herein. Finally, tables and graphs for investigated results are displayed for drawing some significant conclusive observations for testing their validity and consistency.