In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction acc

Objective (s): To determine factors associated with the pregnancy complications (Maternal age, education,
obstetrical history, gravidity, birth space interval, and smoking).
Methodology: A cross-sectional study conducted at Al- washash & Bab-almoadham primary health care
centers. The sample was (non probability convenient sample) which included (550) pregnant women. The
study started from 1st April 2014 to 1
st of April 2015. The data was collected by direct interview using
special questionnaire to obtain socio-demographic information.
Results: the result shows that mean age of the subjects was 26.5± 4.39 years, 57.8% were housewives, the
sample included 103 premature uterine contractions, 98 pregnancy induce

. In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction a

Spelling correction is considered a challenging task for resource-scarce languages. The Arabic language is one of these resource-scarce languages, which suffers from the absence of a large spelling correction dataset, thus datasets injected with artificial errors are used to overcome this problem. In this paper, we trained the Text-to-Text Transfer Transformer (T5) model using artificial errors to correct Arabic soft spelling mistakes. Our T5 model can correct 97.8% of the artificial errors that were injected into the test set. Additionally, our T5 model achieves a character error rate (CER) of 0.77% on a set that contains real soft spelling mistakes. We achieved these results using a 4-layer T5 model trained with a 90% error inject

Objective(s): evaluation of effectiveness of cardiac rehabilitation instructional program on health-related quality of life and to find out the relationship between health-related quality of life and patient’s socio-demographic and clinical characteristics. 

Methodology: A descriptive study design was carried out from 8^th August, 2022 to 10^th January, 2023.

A non-probability purposive sample of (50) patients undergone coronary artery bypass graft surgery at Iraqi center for heart diseases using pre-experimental design. The data were collected by direct interview with sample using questionnaire composed of three parts: part (1) Socio-demographic and clinical ch

Objective(s): evaluation of effectiveness of cardiac rehabilitation instructional program on health-related quality of life and to find out the relationship between health-related quality of life and patient’s socio-demographic and clinical characteristics.  Methodology: A descriptive study design was carried out from 8th August, 2022 to 10th January, 2023. A non-probability purposive sample of (50) patients undergone coronary artery bypass graft surgery at Iraqi center for heart diseases using pre-experimental design. The data were collected by direct interview with sample using questionnaire composed of three parts: part (1) Socio-demographic and clinical characteristics which included 11 items. Part (2) Knowledge r

Hepatitis C virus (HCV) is a liver disease that affects14 million people. Feasible research was conducted for identifying the genotypes and allele frequency of some single nucleotide polymorphisms (SNPs) of the IL-28β genes and their predictive role in disease incidence in Iraqi patients. The SNPs (rs28416813, rs4803219, rs11881222, and rs8103142) of IL-28β have been associated with susceptibility to several diseases. Ninety eight (98) HCV patients were included in this research; with average age ± SE (42.28 ± 3.44) years. Also, 80 healthy people (with average age ± SE (29.40 ± 2.84) years) were included as a control group. The SNPs were detected by allele-specific PCR (polymerase chain reaction) using specific primers. The re

This research includes the study of dual data models with mixed random parameters, which contain two types of parameters, the first is random and the other is fixed. For the random parameter, it is obtained as a result of differences in the marginal tendencies of the cross sections, and for the fixed parameter, it is obtained as a result of differences in fixed limits, and random errors for each section. Accidental bearing the characteristic of heterogeneity of variance in addition to the presence of serial correlation of the first degree, and the main objective in this research is the use of efficient methods commensurate with the paired data in the case of small samples, and to achieve this goal, the feasible general least squa