In this paper, recommended spiral passive micromixer was designed and simulated. spiral design has the potential to create and strengthen the centrifugal force and the secondary flow. A series of simulations were carried out to evaluate the effects of channel width, channel depth, the gap between loops, and flowrate on the micromixer performance. These features impact the contact area of the two fluids and ultimately lead to an increment in the quality of the mixture. In this study, for the flow rate of 25 μl/min and molecular diffusion coefficient of 1×10-10 m2/s, mixing efficiency of more than 90% is achieved after 30 (approximately one-third of the total channel length). Finally, the optimized design fabricated using proposed 3D printing method.

Application of the network equivalent concept for external system representation for power system transient analysis is well known. However, the challenge to utilize an equivalent network, approximated by a rational function, is to guarantee the passivity of the corresponding model. In this regard, special techniques are required to enforce the passivity of the equivalent model through a post processing approach that minimizes its impact on the original model characteristics. In this paper, the passivity is enforced by expressing the problem in terms of a convex Optimization problem that guarantees the global optimal solution. The convex Optimization problem is efficiently solved by recently developed numerical interior–point methods. This passivity enforcement is also global which indicates that the passivity enforcement in one region does not lead to passivity violation in other regions.

Background: Ethical banking is a set of banking activities with full respect for human rights, commitment to healthy competition and responsibility and accountability for behaviors. The purpose of this research is to provide a model for optimizing ethical banking training in Iran's Workers' Welfare Bank. Method: Qualitative research method and systematic data-based theory. According to the practical objectives of the research, the statistical community includes officials and experts from different departments of Refah Bank with at least 10 years of working experience in the bank and a master's degree or higher and university professors who have experience working with this bank in the departments They had banking education. To select the sample, the purposeful sampling method was used and 15 people were selected as a sample until theoretical saturation was reached. The tool was semi-structured interviews and data analysis was done in three stages of open, central and selective coding. Findings: Data analysis led to the extraction of 58 concepts, 19 subcategories and finally 8 main categories from the integration and classification of concepts. Conclusion: based on the proposed model, Optimization of ethical banking education as a central category, development of ethical banking as a causal condition, job stimuli as background conditions, educational resources and management factors as intervening conditions, The comprehensiveness of education as a strategy and finally the development of individual performance and the development of organizational performance are considered as the consequences of the implementation of strategies.

Locally Linear model Tree (LOLIMOT) algorithm proposed by Nelles deals with local linear nearo-fuzzy models that is based on divides-and-conquer strategy that a complex modeling problem is divided to a number of smaller and thus simpler sub problems.So the characteristic of such a neuro-fuzzy model depends on division strategy for the original complex problem.For finding the best output the algorithm divides the problem to a number of local linear models (LLMs), then continues with finding the worst LLM and dividing it. LOLIMOT splits the local linear models into two equal halves with an axis-orthogonal decomposition strategy.In this paper a new approach based on extremeal Optimization (EO) is used to optimize the structure of LOLIMOT.Simulation results show the effectiveness of the enhanced LOLIMOT to have a higher precision with optimal number of neurons.

The purpose of the portfolio management is the portfolio selection, the portfolio that acts as guidance to investors in order to achieve to maximum efficiency. In this study for portfolio selection, particle swarm Optimization and Markowitz model are used and a comparison was made between them. Introducing the model to select a portfolio for investors who can make the right choice with evaluation of that model is of our objectives in this study. For this purpose, literature and various studies are verified and a set of measures with regard to the purpose of the research was collected. Among the companies listed on the Tehran Stock Exchange, 65 companies were selected as sample for the period 2009 to 2013 and were analyzed as a statistical sample. To analyze the data, first the data is collected and categorized in software EXCEL and after doing calculations were analyzed using MATLAB software. The results of this research showed that the particle swarm Optimization has a fewer errors in the selection of optimal portfolio compared with Markowitz model. The most important suggestion for future research is to compare the particle swarm Optimization with other models of Optimization such as, colonial competition, meta-heuristic, arbitrage model and etc.

Plant development can be defined as a programmed qualitative change in plant form, which leads plant to maturity, and researchers call it as phasic development or phenology. Recognizing the timing of occurring each development stage is necessary for managing system in order to yield increment. The timing of occurring development stages depend on climate, genotype specifications and sowing date then determination of these times in different regions is difficult and it is only possible through the using of crop simulation models which can predict the timing of occurrence each development stage by integrating effective factors. The model was constructed based on linear equation of plant temperature response. In order to model evaluation two experiments were carried out in agricultural and natural resources research center of Khuzistan in 2003-2004 and 2004-2005 cropping years. Wheat development stages were determined based on Kirby and Appleyard’s scale by stereoscopic microscope and required GDD for each development stage as well. The constructed model was calibrated and run for simulation. Comparison of simulated and observed data showed that the model can strongly predict wheat development stages.

Choosing the right portfolio is a crucial goal for investors. Two key factors to consider when selecting a portfolio are return and portfolio risk. This problem can be written as a mathematical programming equation and can be solved quickly. For instance, some investors choose stocks based on past performance, while others consider factors like liquidity when making their selections. Additionally, fundamental and technical analysis are often used in stock and portfolio selection. However, the strategies and methods used to select stocks and portfolios can vary depending on the current market conditions and the investor's level of knowledge. This article focuses on designing and explaining a portfolio Optimization model using the cuckoo Optimization algorithm. Results show that the best value of the utility function increases as the number of iterations increases. The growth value of the best value of the utility function is higher in the initial iterations and gradually decreases until it reaches zero, indicating that the algorithm has converged to the optimal solution. This research fills a gap in the study of investment portfolio Optimization using nested Optimization models. Additionally, the study finds that shares selected from industries with better performance make up a higher proportion of the portfolio.