In this work, the superconducting CuBa2LaCa2Cu4O11+δ compound was prepared by citrate precursor method and the electrical and structural properties were studied. The electrical resistivity has been measured using four probe test to find the critical temperature Tc(offset) and Tc(onset). It was found that Tc (offset) at zero resistivity has 101 K and Tc (onset) has 116 K. The X-ray diffraction (XRD) analysis exhibited that a prepared compound has a tetragonal structure. The crystal size and microscopic strain due to lattice deformation of CuBa2LaCa2Cu4O11+δ were estimated by four methods, namely Scherer(S), Halder-Wagner(H-W), size-strain plot (SSP) and Williamson-Hall, (W-H) methods. Results of crystal sizes obtained by these meth

One of the most important challenges facing the development of laser weapons is represented by the attenuation of the laser beam as it passed through the layers of atmosphere.This paper presents a theoretical study to simulate the effect of turbulence attenuation and calculates the decrease of laser power in Iraq. The refractive index structure C_n^2 is very important parameter to measure the strength of the atmospheric turbulence, which is affected by microclimate conditions, propagation path, season and time in the day. The results of measurements and predictions are based on the Kolmogorov turbulence theory. It was demonstrated by simulations that the laser weapons in Iraq were severely affected due to the large change in temperatures,

    In this article, the research presents a general overview of deep learning-based AVSS (audio-visual source separation) systems. AVSS has achieved exceptional results in a number of areas, including decreasing noise levels, boosting speech recognition, and improving audio quality. The advantages and disadvantages of each deep learning model are discussed throughout the research as it reviews various current experiments on AVSS. The TCD TIMIT dataset (which contains top-notch audio and video recordings created especially for speech recognition tasks) and the Voxceleb dataset (a sizable collection of brief audio-visual clips with human speech) are just a couple of the useful datasets summarized in the paper that can be used to test A

The microstructure and wear properties of 392 Al alloy with different Mg contents were studied using centrifugal casting. All melted alloys were heated to 800 ºC and poured into the preheated centrifugal casting mold (200-250 ^ºC) at different mould rotational speeds (1500, 1900 and 2300 r.p.m).  It is clear from the results obtained that wear rate was dependent on the Mg content, applied load and mould rotational speed. Furthermore, wear test showed that the minimum wear rate was found in the inner layer of produced rings at mould rotational speed of 1900 r.p.m and Mg content of 5%.

The aim of the present study was to distinguish between healthy children and those with epilepsy by electroencephalography (EEG). Two biomarkers including Hurst exponents (H) and Tsallis entropy (TE) were used to investigate the background activity of EEG of 10 healthy children and 10 with epilepsy. EEG artifacts were removed using Savitzky-Golay (SG) filter. As it hypothesize, there was a significant changes in irregularity and complexity in epileptic EEG in comparison with healthy control subjects using t-test (p< 0.05). The increasing in complexity changes were observed in H and TE results of epileptic subjects make them suggested EEG biomarker associated with epilepsy and a reliable tool for detection and identification of this di

The recent emergence of sophisticated Large Language Models (LLMs) such as GPT-4, Bard, and Bing has revolutionized the domain of scientific inquiry, particularly in the realm of large pre-trained vision-language models. This pivotal transformation is driving new frontiers in various fields, including image processing and digital media verification. In the heart of this evolution, our research focuses on the rapidly growing area of image authenticity verification, a field gaining immense relevance in the digital era. The study is specifically geared towards addressing the emerging challenge of distinguishing between authentic images and deep fakes – a task that has become critically important in a world increasingly reliant on digital med