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The purpose of this paper is to evaluate the locomotion performance of all‐terrain rovers employing rocker‐type suspension system.

In this paper, a robot with advanced mobility features is presented and its locomotion performance is evaluated, following an analytical approach via extensive simulations. The vehicle features an independently controlled four‐wheel‐drive/4‐wheel‐steer architecture and it also employs a passive rocker‐type suspension system that improves the ability to traverse uneven terrain. An overview of modeling techniques for rover‐like vehicles is introduced. First, a method for formulating a kinematic model of an articulated vehicle is presented. Next, a method for expressing a quasi‐static model of forces acting on the robot is described. A modified rocker‐type suspension is also proposed that enables wheel camber change, allowing each wheel to keep an upright posture as the suspension conforms to ground unevenness.

The proposed models can be used to assess the locomotion performance of a mobile robot on rough‐terrain for design, control and path planning purposes. The advantage of the rocker‐type suspension over conventional spring‐type counterparts is demonstrated. The variable camber suspension is shown to be effective in improving a robot's traction and climbing ability.

The paper can be of great value when studying and optimizing the locomotion performance of mobile robots on rough terrain. These models can be used as a basis for advanced design, control and motion planning.

The paper describes an analytical approach for the study of the mobility characteristics of vehicles endowed with articulated suspension systems. A variable camber mechanism is also presented.

The Iranian banking industry has been greatly affected by dramatic changes in macroeconomic conditions over the past several decades owing to volatile oil revenues, changing fiscal and monetary policies, and the imposition of US sanctions. The main objective of this paper is to estimate potential credit losses in the Iranian banking sector due to macroeconomic shocks and assess the minimum economic capital requirements under the baseline and distressed scenarios. The paper also contrasts the applications of linear and nonlinear models in estimating the impacts of macroeconomic shocks on financial institutions.

The paper uses a multistage approach to derive the portfolio loss distribution for banks. In the first step, the dynamic relationship between the selected macroeconomic variables are estimated using a VAR model to generate the stress scenarios. In the second step, the default probabilities are estimated using a quantile regression model and the results are compared with those of the conventional linear models. Finally, the default probabilities are simulated for a one-year time horizon using Monte-Carlo method and the portfolio loss distribution is calculated for hypothetical portfolios. The expected loss includes the loss given default for loans drawn randomly and uniformly distributed and exposed at default values when loans are assigned a fixed value.

The results indicate that the loss distributions under all scenarios are skewed to the right, with the linear model results being very similar to those of quantile at the 50% quantile, but very unlike those at the 10% and 90% quantiles. Specifically, the quantile model for the 90% (10%) quantile generates estimates of minimum economic capital requirement that are considerably higher (lower) than those using the linear model.

The study has focused on credit risk because of lack of data on other types of risk at individual bank level. The future studies can estimate the aggregate economic capital using a risk aggregation approach and a panel data (not presently available), which could further improve the accuracy of the estimates.

The fiscal and monetary authorities in developing countries, specially oil-exporting countries, can follow the risk assessment approach to assess the health of their banking system and adapt policies to mitigate the impacts of large macroeconomic shocks on their financial markets.

This is the first paper estimating the portfolio loss distribution for the Iranian banks under turbulent macroeconomic conditions using linear and nonlinear models. The case study can be applied to other developing and emerging countries, particularly those highly dependent on natural resources, prone to extreme macroeconomic shocks.