Machine learning (ML) is a key component within the broader field of artificial intelligence (AI) that employs statistical methods to empower computers with the ability to learn and make decisions autonomously, without the need for explicit programming. It is founded on the concept that computers can acquire knowledge from data, identify patterns, and draw conclusions with minimal human intervention. The main categories of ML include supervised learning, unsupervised learning, semisupervised learning, and reinforcement learning. Supervised learning involves training models using labelled datasets and comprises two primary forms: classification and regression. Regression is used for continuous output, while classification is employed

    Extraction and preparation of red organic dye from beetroot plant in different concentrations by using the solvent extraction process. Ethanol was the solvent used to prepare five different concentrations at the ratio of (Dye: Ethanol) abbreviated (D: E) 5:0,4:1, 3:2, 2:3,1:4. The optical, structural, and morphological properties are studied for the samples. The results appeared using the UV-Vis spectroscope the maximum peak of absorption (A) spectrum at wavelength A_λmax=480 nm when the transmittance (T) at the same wavelength 25% and the reflectivity 0.8%. Florescent (F) spectrum of beetroot dye is measured at wavelength F_λmax=535nm achieved to redshift about Δλ=55 nm. Also, measured the energy band gap

The aim of this paper, study the effect of carbon nanotubes on the electrical properties of polyvinylchloride. Samples of polyvinylchloride carbon nanotubes composite prepared by using hot press technique. The weight percentages of carbon nanotubes are 0,5,10 and 20wt.%. Results showed that the D.C electrical conductivity increases with increasing of the weight percentages of carbon nanotubes. Also, the D.C electrical conductivity changed with increase temperature for different concentrations of carbon nanotubes. The activation energy of D.C electrical conductivity is decreased with increasing of carbon nanotubes concentration.

Cadmium Oxide and Bi doped Cadmium Oxide thin films are prepared by using the chemical spray pyrolysis technique a glass substrate at a temperature of (400?C) with volumetric concentration (2,4)%. The thickness of all prepared films is about (400±20) nm. Transmittance and Absorbance spectra are recorded in the wave length ranged (400-800) nm. The nature of electronic transitions is determined, it is found out that these films have directly allowed transition with an optical energy gap of (2.37( eV for CdO and ) 2.59, 2.62) eV for (2% ,4%) Bi doped CdO respectively. The optical constants have been evaluated before and after doping.

Refrigerant R134a has been widely utilized in automotive air conditioning systems (AACSs); R134a has a high global warming potential (GWP) of 1430 despite having zero ozone depletion potential (ODP). Coming refrigeration systems must include refrigerants with low GWP and zero ODP. The aim of this experimental study is to evaluate the thermal performance of an (AAC) with different values of compressor speeds, i.e., (1000, 1700, and 2400 rpm) and two thermal loads, i.e., (500 and 1000 Watt) with the absence and presence of liquid suction heat exchanger (LSHX) using R134a. The results showed that adding LSHX enhanced the COP cycle by 7.18%, 10.7%, and 3.09% for the first, second, and third speed, respectively, at 500 Watt, while the en

   SMNs like Facebook, YouTube, Twitter, WhatsApp,..etc. are among the most popular sites on the Internet. These sites can provide a powerful means of sharing, organizing, finding information and knowledge. The popularity of these sites provides an opportunity to measure the use them in knowledge sharing, which needs a special scale, but unfortunately, there is no special scale for that. Thus, this study supposes to use SCT as a scale to measure the use of SMNs in electronic knowledge sharing due to it has been used to measure knowledge sharing with its traditional form. This study can help the decision-makers to use these SMNs to share the academics’ knowledge in educational institutes to the communi

Hepatocellular carcinoma (HCC) is the third most common cause of cancer-related death. Therefore, it is critical for researchers to understand molecular biology in greater depth.  In several diseases including cancer, abnormal miRNA expression has been linked to apoptosis, proliferation, differentiation, and metastasis. Many miRNAs have been studied in relation to cancer, including miR-122, miR-223, and others. Hepatitis B and C viruses are the most important global risk factors for HCC. This study is intended to test whether serum miRNAs serve as a potential biomarker for both HCC and viral infections HBV and C. The expression of miRNA in 64 serum samples was analyzed by RT-qPCR. Compared to healthy volunteers, HCC patients' sera expre

Abstract

Multivariate GARCH Models take several forms , the most important DCC dynamic conditional correlation, and CCC constant conditional correlation , The Purpose of this research is the Comparison for both Models.Using three  financial time series which is a series of daily Iraqi dinar exchange rate indollar, Global daily Oil price in dollar and Global daily gold price in dollarfor the period from 01/01/2014 till 01/01/2016, Where it has been transferred to the three time series returns to get the Stationarity, some tests were conducted including Ljung-Box , JarqueBera  , Multivariate ARCH to Returns Series and Residuals Series for both models In Comparison