he current research aims to analyze the relationship and the level of influence of labor relations in reducing the cases of job withdrawal in private colleges in Baghdad. (265) individuals from department heads, university professors, and teaching staff in (7) private colleges located in the capital, Baghdad, and based on the Stephen Thompson equation for small samples, the sample size was determined by (157) teachers, and the questionnaire was adopted as a main tool for collecting data and information After ensuring the validity and reliability of its contents, and to test the relationship of influence, correlation and interaction between the research variables, two main hypotheses were formulated from which (5) sub-hypotheses eman

Background: Plants used in folk medicine for
the treatment of peptic ulcer diseases is a very
promising approach to overcome the limitations of
classical medicines.
Aim: To explore the efficacy of medicinal
plants, namely turmeric, garlic and marshmallow,
in eradication of H. pylori.
Methods: This prospective study was carried out
on 225 of well-known dyspeptic patients who were
divided into four groups; a control group (received
classical medical therapy) and three other groups
that received one of the three medicinal plants,
plus the same therapy used in the control group.
The follow up was done by using a questionnaire
form, endoscopic examination, and determination
of serum levels of anti

The research discusses the need to find the innovative structures and methodologies for developing Human Capital (HC) in Iraqi Universities. One of the most important of these structures is Communities of Practice (CoPs) which contributes to develop HC by using learning, teaching and training through the conversion speed of knowledge and creativity into practice. This research has been used the comparative approach through employing the methodology of Data Envelopment Analysis (DEA) by using (Excel 2010 - Solver) as a field evidence to prove the role of CoPs in developing HC. In light of the given information, a researcher adopted on an archived preliminary data about (23) colleges at Mosul University as a deliberate sample for t

This research aims to clarify the importance of an accounting information system that uses artificial intelligence to detect earnings manipulation. The research problem stems from the widespread manipulation of earning in economic entities, especially at the local level, exacerbated by the high financial and administrative corruption rates in Iraq due to fraudulent accounting practices. Since earning manipulation involves intentional fraudulent acts, it is necessary to implement preventive measures to detect and deter such practices. The main hypothesis of the research assumes that an accounting information system based on artificial intelligence cannot effectively detect the manipulation of profits in Iraqi economic entities. The researche

The current research tries to study the reasons for lying since its
inception, as it is interesting to a child's moral growth, which can benefit from
the results of this research by institutions of socialization, parents and
teachers in the treatment and care of children.
The objective of this research is to highlight the reasons for lying to the
children from the viewpoint of teachers and the answer to the paragraphs of
research designed research instrument (questionnaire) was distributed to a
sample of teachers was clear from the analysis that the reasons lie that
received a high percentage of members of the sample are: -
- The fear of severe punishment
- Child rid himself of a specific problem
- To sat

<span>Dust is a common cause of health risks and also a cause of climate change, one of the most threatening problems to humans. In the recent decade, climate change in Iraq, typified by increased droughts and deserts, has generated numerous environmental issues. This study forecasts dust in five central Iraqi districts using machine learning and five regression algorithm supervised learning system framework. It was assessed using an Iraqi meteorological organization and seismology (IMOS) dataset. Simulation results show that the gradient boosting regressor (GBR) has a mean square error of 8.345 and a total accuracy ratio of 91.65%. Moreover, the results show that the decision tree (DT), where the mean square error is 8.965, c

Machine learning models have recently provided great promise in diagnosis of several ophthalmic disorders, including keratoconus (KCN). Keratoconus, a noninflammatory ectatic corneal disorder characterized by progressive cornea thinning, is challenging to detect as signs may be subtle. Several machine learning models have been proposed to detect KCN, however most of the models are supervised and thus require large well-annotated data. This paper proposes a new unsupervised model to detect KCN, based on adapted flower pollination algorithm (FPA) and the k-means algorithm. We will evaluate the proposed models using corneal data collected from 5430 eyes at different stages of KCN severity (1520 healthy, 331 KCN1, 1319 KCN2, 1699 KCN3 a