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The purpose of this paper is to present and analyze the current literature related to developing and improving the Mahalanobis-Taguchi system (MTS) and to present the shortcomings related to this method for future research.

In this paper, articles in the literature are classified to give an overview on the MT strategy. For this purpose, 46 articles are considered for classification from 2000 to 2013 on the basis of: MTS contribution area, description of the issue, and results.

In this paper a review on the concepts and operations of the MTS was provided as a new method in the field of pattern recognition, multivariable diagnosis, and forecasting. A large number of studies were performed in recent years consisting of developing MTS and MTS case studies. The analysis of the articles showed the fields of MTS which had more potential for future studies and developing. The comparison of the MTS to other methods and the selection of the normal group for constructing the Mahalanobis space have received the most attention by researchers. In addition, several studies concentrated on the use of other methods instead of design of experiments, finding applications for multiclass MTS and finding an alternative for the SN ratio.

This paper contains the publications in the field of MTS chronologically and shows different areas for developing and case studies. It will be useful to researchers and professionals who are interested in pattern recognition, multivariate analysis, and forecasting.

Technological entrepreneurship has been a very significant topic in recent decades. It has a crucial role in economic modernization and growth. The need for technological entrepreneurship is because technology-based industries are expanding rapidly and are replacing traditional industries. Therefore, this study aimed at identifying the factors affecting the success of technological entrepreneurship in Iranian nanotechnology businesses.

The research was conducted through mixed method. The participants in the qualitative section included 17 university experts and executive managers in the field of nanotechnology in Iran, and 75 nanotechnology business managers participated in the quantitative section. The interview and questionnaire were used to collect information. In order to measure and fit the models, the confirmatory factor analysis method and PLS3 software were used.

The results indicated that the key factors affecting the success of the technological entrepreneurship process in nanotechnology were classified into five general categories: organizational, environmental, institutional, individual and technology factors. Moreover, it was shown that all these dimensions had a positive and significant effect on technological entrepreneurship. In addition, the organizational dimension has an essential role.

Companies' ability to engage technological entrepreneurship is a vital factor in human resource management and strategic management. However, technological entrepreneurship in Iranian nanotechnology businesses has not been involved integrally in the context of companies.

Blasting is an economical method for rock breakage in open-pit mines. Backbreak is an undesirable phenomenon induced by blasting operations and has several unsuitable effects such as equipment instability and decreased performance of the blasting. Therefore, accurate estimation of backbreak is required for minimizing the environmental problems. The primary purpose of this paper is to propose a novel predictive model for estimating the backbreak at Shur River Dam region, Iran, using particle swarm optimization (PSO).

For this work, a total of 84 blasting events were considered and five effective factors on backbreak including spacing, burden, stemming, rock mass rating and specific charge were measured. To evaluate the accuracy of the proposed PSO model, multiple regression (MR) model was also developed, and the results of two predictive models were compared with actual field data.

Based on two statistical metrics [i.e. coefficient of determination (R²) and root mean square error (RMSE)], it was found that the proposed PSO model (with R² = 0.960 and RMSE = 0.08) can predict backbreak better than MR (with R² = 0.873 and RMSE = 0.14).

The analysis indicated that the specific charge is the most effective parameter on backbreak among all independent parameters used in this study.

Falling was distinguished as leading cause of fatal and non-fatal injuries among elderly; there is a lack of information regarding the falling risk factors in developing countries. The purpose of this paper is to investigate the falling risk and correlated factors in community-dwelling elderly.

This cross-sectional study was performed on 280 elderly using a multi-sectional questionnaire in Karaj, Iran. The simple stratified random sampling was used. Adult who were over the age of 60, living independently, able to ambulate independently and safely, no cognition problem and speaking in Persian entered in the study. Exclusion criteria were residing in assisted living facility or unwilling to participate. Several statistical tests including logistic regression analysis were used to analyse the data.

The mean age of participants was 69.55±8.82 and 51 per cent of them were female. The results showed that there are significant differences between low-, medium- and high-risk groups regarding age, marital status, diabetes, blood pressure and osteoarthritis (p<0.05). Due to finding, the main predictors to higher chance of falling were age (OR=1.61; 95% CI 1.025–1.097), marital status (OR=1.485; 95% CI 1.170–1.279), vision acuity (OR=1.603; 95% CI 1.297–2.223), activities of daily living (OR=2.10; 95% CI 1.047–3.859), heart disease (OR=1.448; 95% CI 1.268–1.728), osteoarthritis (OR=1.238; 95% CI 1.711–2.127), falling history (OR=1.026; 95% CI 1.015–1.089) and medication (OR=5.975; 95% CI 1.525–23.412).

Better understanding of falling risk factors can lead to the implementation of effective preventive intervention, thus reducing public health expenditure, and improving the quality of life.

This study was conducted for the first time to assess the risk of falling in older people in Iran.

The purpose of this paper is to perform numerical simulations based on the incompressible smoothed particle hydrodynamics (ISPH) method for thermo-diffusion convection in a hexagonal-shaped cavity saturated by a porous medium and suspended by a nano-encapsulated phase change material (NEPCM). Here, the solid particles are inserted into a phase change material to enhance its thermal performance.

Superellipse rotated shapes with variable lengths are embedded inside a hexagonal-shaped cavity. These inner shapes are rotated around their center by a uniform circular velocity and their conditions are positioned at high temperature and concentration. The controlling equations in a non-dimensional form were analyzed by using the ISPH method. At first, the validation of the ISPH results is performed. Afterward, the implications of a fusion temperature, lengths/types of the superellipse shapes, nanoparticles parameter and time parameter on the phase change heat transfer, isotherms, isoconcentration and streamlines were addressed.

The achieved simulations indicated that the excess in the length of an inner superellipse shape augments the temperature, concentration and maximum of the streamlines in a hexagonal-shaped cavity. The largest values of mean Nusselt number are attained at the inner rhombus shape with convex (n = 1.5) and the largest values of mean Sherwood number are attained at the inner rectangle shape with rounded corners (n = 4).

The ISPH method is developed to emulate the influences of the uniform rotation of the novel geometry shapes on heat/mass transport inside a hexagonal-shaped cavity suspended by NEPCM and saturated by porous media.