Total quality management  considers one of the modern scientific entrances  which practiced by productivity service organizations alike to provide appropriate quality required outputs according to the needs and desires of customers manage , enable the organization seeking to continue and grow in light of the increasing competition from the satisfy and provide the appropriate total quality management requirements whenever led to face risks that they may have  in a manner in which they can be addressed and find ways to avoid them in the future when repeated.                          &n

Human resources constitute the most important recourses that the organization owned today, as it may have developed financial and technology resources to achieve their goals, but they are not able to use it with required efficiency and effective and quality desired unless there is human resources that have good skills, experiences and talents that able to directing and exploited ideally that compatible  with market requirements, where today's market and business organizations which compete naturally inherent talent, so the task is to attracting and developing talented resources and preservation these talented resources from the challenges that facing organizations. 

The research seek to achieve

The Financial authority is considered as one of  the most of benefited parts from financial statements  which depends on it in process of accounting  in taxes as basis to determine The Tax Base , but no confidence from financial authority part in objectivity of income financial information in them for many of limited companies led to no dependence on them to specify taxation contain & dependence on yearly regulations that issued them. To enhance the confidence of financial authority to these lists must meet its requirements, because the menus Fulfill the requirements of the financial authority increases the confidence in these statements and therefore reliable in determining the tax base. So this research aims to speci

Abstract:

It is essential to provide health care directly or indirectly based on laboratory tests in order of diagnosing diseases. There is an urgent need for the results of such tests to be accurate and reliable. Therefore, the International Organization for Standardization has prepared special standards for medical laboratories to prove their efficiency, presented in standards 15189: 2012. The aim of the research is to determine the possibility of the Al-alwiya Women's Hospital in meeting the requirements of the standards 15189: 2012, which includes administrative requirements consisting of fifteen items and technical requirements consisting of ten items. The research is important because laboratories shou

The study aims to determine the responsibility of nursing staff for medical errors that accompany the surgery at the hospital , which is one of the important issues that the importance of determining the responsibility of landlords nursing medical errors in the hospital was the rationale in choosing the subject. Since study included cases of errors nursing staff of (22) case. While the checklist distributed to a sample of nursing Angel Group in Sadr Teaching Hospital 's (100) nurs According to the problem, the study in determining the responsibility of nursing staff for medical errors that are not important for the hospitals. Has shown results of the study agreement members of the study sample that the clarity of the power posses

Machine learning is considered a powerful technique in many applications such as classification, clustering, recognition and prediction. Deep learning is a modern, vital and superior machine learning that gives stunning performance, especially with huge data. Stock market price prediction is the process of determining the future value of a prospect of a financial instrument traded in the market, to gain a great profit a successful prediction must be conducted, in order to achieve that machine learning is used, in this article, two approaches are proposed to predict the stock market prices and movement using two datasets, the first approach employs two machine learning models (J48 & logistic regression) while the second approach based on rec

To determine the evaluation of education program on women's knowledge regarding managing BSE. The present quasi- experimental study, Non-probability (purposive), sample consisting of (260) women who are employee, and students in both colleges (Nursing college, Medical and Health Techniques College). The sample consist of two groups, study group (130) including those in (Nursing college), and control group (130) in (Medical and Health Techniques College). A questionnaire was constructed which included, Demographic information, Reproductive information, Family history, Previous medical history, and information about women's knowledge toward management of breast self examination (BSE). Instrument validity and reliability was determined. Data w

Ovarian cancer has a high mortality and delayed diagnosis. Several immunological alterations take place during ovarian carcinogenesis, and can be of value in the surveillance of the diseases. This research was conducted to evaluate serum immunoglobulin levels in women with ovarian cancer and to assess their role in disease process. The present study is composed of 85 women (mean age = 62.03±12.4 yrs) with clinically and pathologically confirmed ovarian cancer and 65 healthy females as a control group (mean age = 61±12.1 yrs). ELISA test was achieved for the determination of serum [IgG, IgA, IgM]. The findings of current study illustrated significant (P=0.001) increase in serum IgG, IgA, and IgM levels as compared to co

Channel estimation (CE) is essential for wireless links but becomes progressively onerous as Fifth Generation (5G) Multi-Input Multi-Output (MIMO) systems and extensive fading expand the search space and increase latency. This study redefines CE support as the process of learning to deduce channel type and signal-tonoise ratio (SNR) directly from per-tone Orthogonal Frequency-Division Multiplexing (OFDM) observations,with blind channel state information (CSI). We trained a dual deep model that combined Convolutional Neural Networks (CNNs) with Bidirectional Recurrent Neural Networks (BRNNs). We used a lookup table (LUT) label for channel type (class indices instead of per-tap values) and ordinal supervision for SNR (0–20 dB,5-dB steps). T