Azarbaijan Shahid Madani University

About: Azarbaijan Shahid Madani University is a education organization based out in Tabriz, Iran. It is known for research contribution in the topics: Graphene & Nanocomposite. The organization has 1477 authors who have published 3186 publications receiving 30278 citations. The organization is also known as: Azarbaijan University.

Classification of two and three dimensional Lie superbialgebras

Abstract: Using adjoint representation of Lie superalgebras, we obtain the matrix form of super-Jacobi and mixed super-Jacobi identities of Lie superbialgebras. By direct calculations of these identities, and use of automorphism supergroups of two and three dimensional Lie superalgebras, we obtain and classify all two and three dimensional Lie superbialgebras.

A novel approach based on combining deep learning models with statistical methods for COVID-19 time series forecasting.

Abstract: The COVID-19 pandemic has disrupted the economy and businesses and impacted all facets of people's lives. It is critical to forecast the number of infected cases to make accurate decisions on the necessary measures to control the outbreak. While deep learning models have proved to be effective in this context, time series augmentation can improve their performance. In this paper, we use time series augmentation techniques to create new time series that take into account the characteristics of the original series, which we then use to generate enough samples to fit deep learning models properly. The proposed method is applied in the context of COVID-19 time series forecasting using three deep learning techniques, (1) the long short-term memory, (2) gated recurrent units, and (3) convolutional neural network. In terms of symmetric mean absolute percentage error and root mean square error measures, the proposed method significantly improves the performance of long short-term memory and convolutional neural networks. Also, the improvement is average for the gated recurrent units. Finally, we present a summary of the top augmentation model as well as a visual representation of the actual and forecasted data for each country.

Hydrodynamic theory of partially degenerate electron-hole fluids in semiconductors

Abstract: A quantum hydrodynamic (QHD) theory for high-frequency electron-hole Langmuir and acoustic-like oscillations as well as static charge shielding effects in arbitrarily doped semiconductors is presented. The model includes kinetic corrections to the quantum statistical pressure and to the quantum Bohm potential for partially degenerate electrons and holes at finite temperatures. The holes contribute to the oscillations and screening effects in semiconductors in a similar manner as real particles. The dielectric functions are derived in the high-frequency limit for wave excitations and in the low-frequency limit for the study of static screening. The dispersion relation for the Langmuir and acoustic-like oscillations is examined for different parameters of doped silicon (Si). Some interesting properties and differences of electron hole dynamical behavior in N- and P-type Si are pointed out. Holes are also observed to enhance an attractive charge shielding effect when the semiconductor is highly acceptor-doped.