This article is devoted to the cognitive study of ironic metonymy in Russian and Arabic. Metonymy and irony have traditionally been seen as parallel linguistic phenomena. But their formation and interpretation are based on different cognitive mechanisms. At the formal and functional level, metonymy and irony have a number of significant differences. Metonymy is an artistic technique, the mechanism of which is based on obvious, easily traced connections between objects and phenomena of the surrounding world. Irony is a satirical technique or a rhetorical figure that is used to create a certain artistic image, aimed at forming the hidden meaning of the statement. A native speaker intuitively feels the difference between metonymy and irony

This paper presents the Extended State Observer (ESO) based repetitive control (RC) for piezoelectric actuator (PEA) based nano-positioning systems. The system stability is proved using Linear Matrix Inequalities (LMIs), which guarantees the asymptotic stability of the system. The ESObased RC used in this paper has the ability to eliminate periodic disturbances, aperiodic disturbances and model uncertainties. Moreover, ESO can be tuned using only two parameters and the model free approach of ESO-based RC, makes it an ideal solution to overcome the challenges of nano-positioning system control. Different types of periodic and aperiodic disturbances are used in simulation to demonstrate the effectiveness of the algorithm. The comparison studi

The fiscal position of governments in rentier economies depends heavily on oil revenues. The relationship between oil prices and the budget surplus or deficit is often nonlinear and characterized by complex temporal dependencies, which may limit the predictive capability of conventional econometric models. Accordingly, this study aims to forecast the Iraqi budget surplus and deficit and compare the predictive performance of the ARDL, NARDL, LSTM, 1D-CNN, and hybrid 1D-CNN-LSTM models using oil prices as the primary predictive variable. The hybrid model integrates the feature-extraction capability of One-Dimensional Convolutional Neural Networks (1D-CNN) with the ability of Long Short-Term Memory (LSTM) networks to capture long-term

The most important function of a prosthetic hand is their ability to perform tasks in a manner similar to a natural hand, so it is necessary to perform kinematic analysis to determine the performance and the ability of the prosthetic human finger design to work normally and smoothly when it's drive by two sets of links that embedded in its structure and pulled by a servomotor, so the Denvit-Hartenberg method was used to analyse the forward kinematics for the prosthetic finger joints to deduction the trajectory of the fingertip and the velocity of the joints was computed by using the Jacobian matrix. The prosthetic finger was modelled by the Solidwork - 2018 program and the results of kinematics were verified using MATLAB. The analys

The automatic estimation of speaker characteristics, such as height, age, and gender, has various applications in forensics, surveillance, customer service, and many human-robot interaction applications. These applications are often required to produce a response promptly. This work proposes a novel approach to speaker profiling by combining filter bank initializations, such as continuous wavelets and gammatone filter banks, with one-dimensional (1D) convolutional neural networks (CNN) and residual blocks. The proposed end-to-end model goes from the raw waveform to an estimated height, age, and gender of the speaker by learning speaker representation directly from the audio signal without relying on handcrafted and pre-computed acou