This article studies the aerodynamic performance of a novel bypass shock-induced thrust Vector nozzle. An arc-shaped bypass is innovatively designed to optimize nozzle performance and equips a variable shrinkage part. The nozzle performance is investigated numerically under diverse shrinkage area ratios. Computational results indicate that both geometry and friction choking have important effects on the nozzle performance. Normally, in the case of without any bypass shrinkage, the flow choking occurs at the bypass outlet. Very small bypass shrinkage is unable to change the flow choking location. The bypass geometry choking comes up at its throat as the shrinkage area ratio of the bypass reaches 0. 06. According to computational results, the Vectoring angle diminishes with the increasing shrinkage area ratio of the bypass, thrust force ratio, thrust efficiency, specific impulse ratio, and coefficient of discharge increase. As the NPR enlarges, the deflection angle and thrust efficiency decrease, and the thrust force ratio increases.

This paper presents the speed control scheme of indirect Vector controlled of induction motor (IM) drive. Voltage source inverter type space Vector pulse width modulation (SVPWM) is used for PWM controlling scheme. Regarding the capabilities and potentials of intelligent based on Fuzzy logic in the control of non-linear and complex systems, the Fuzzy PID controllers is developed for controlling the speed, torque, and flux of an IM. The performances of the proposed FLC-based IM drives are investigated and compared to those obtained from the conventional proportional-integral (PI) controller-based drives both simulated at different dynamic operating conditions such as step change in command speed, load change, and increase in the rotor resistance. The comparative results show that the FLC is more robust, found to be a suitable replacement of the conventional PI controller for the high-performance industrial drive applications.

To prospect mineral deposits at regional scale, recognition and classification of hydrothermal alteration zones using remote sensing data is a popular strategy. Due to the large number of spectral bands, classification of the hyper spectral data may be negatively affected by the Hughes phenomenon. A practical way to handle the Hughes problem is preparing a lot of training samples until the size of the training set is adequate and comparable with the number of the spectral bands. In order to gather adequate ground truth instances as training samples, a time-consuming and costly ground survey operation is needed. In this situation that preparing enough field samples is not an easy task, using an appropriate classifier which can properly work with a limited training dataset is highly desirable. Among the supervised classification methods, the Support Vector Machine is known as a promising classifier that can produce acceptable results even with limited training data. Here, this capability is evaluated when the SVM is used to classify the alteration zones of Darrehzar district. For this purpose, only 12 sampled instances from the study area are utilized to classify Hyperion hyper spectral data with 165 useable spectral bands. Results demonstrate that if parameters of the SVM, namely C and σ, are accurately adjusted, the SVM can be successfully used to identify alteration zones when field data samples are not available enough.

In this paper, some properties of  pseudoinvex functions, defined by means of  limiting subdifferential, are discussed. Furthermore, the Minty Vector variational-like inequality,  the Stampacchia Vector variational-like inequality, and the  weak formulations of these two inequalities  defined by means of limiting subdifferential are studied. Moreover, some relationships  between the Vector variational-like inequalities and Vector optimization problems are established.