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Underwriting policy and its impact on the productivity of the life insurance portfolio: Analytical study in the "Iraqi General Insurance Company
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The research aims to study the basic concepts of the underwriting policy with its various indicators. The researcher studies the underwriting policy with its various indicators (sex, health status, age of the insured, insurance amount, The method of acceptance, payment method, and duration of insurance) where each of these indicators constitute an important factor in the productivity of life insurance policies, where the productivity of life insurance policies face many difficulties because insurance is a service and not a tangible material commodity and its benefits and not current. Therefore, the life insurance company needs to use a prudent underwriting policy so as not to endanger its financial position due to the expansion of the underwriting. In line with the research problem, which stipulates the weakness of the underwriting policy, which does not fit in the details of the insurance company and the research sample, as well as the dependence of employees in the issuance department in examining the applications of life insurance received for their company with a view to accepting, rejecting or postponing their coverage, on the accumulated experience. They have without taking into account the economic, social and political changes of the claimants. Accordingly, we will formulate the following question: What is the impact of the underwriting policy on the productivity of life insurance policies? The research hypothesis has been formulated to study and analyze the relationship between the underwriting policy and the life insurance policy of the insurance company. The research sample was determined by the Iraqi General Insurance Company.

The statistical program SPSS-Ver (20) was used to extract the subscription policy for the period (2008-2017) as well as the use of the productivity of life insurance policies. The most prominent results of the research indicate that there is a strong and positive correlation between the underwriting policy and the productivity of life insurance policies. In general, the results of a simple impact analysis indicate that there is an impact between the underwriting policy and the productivity of life insurance policies.

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Publication Date
Thu Feb 11 2016
Journal Name
Journal Of Materials Science: Materials In Electronics
Electrochemical deposition of CdSe-sensitized TiO2 nanotube arrays with enhanced photoelectrochemical performance for solar cell application
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South African Journal Of Chemical Engineering
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Publication Date
Fri Mar 31 2017
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
A Modified Organic Method for Preparation of Ibuprofen Microcapsules As a Sustained Release Solid Dosage Form
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ABSTRACT:
Microencapsulation is used to modify and retard drug release as well as to overcome the unpleasant effect
(gastrointestinal disturbances) which are associated with repeated and overdose of ibuprofen per day.
So that, a newly developed method of microencapsulation was utilized (a modified organic method) through a
modification of aqueous colloidal polymer dispersion method using ethylcellulose and sodium alginate coating materials to
prepare a sustained release ibuprofen microcapsules.
The effect of core : wall ratio on the percent yield and encapsulation efficiency of prepared microcapsules was low, whereas
, the release of drug from prepared microcapsules was affected by core: wall ratio ,proportion of coa

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Publication Date
Fri Jan 01 2016
Journal Name
Aip Conference Proceedings
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Journal Name
Advances In Science And Technology Research Journal
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Publication Date
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Publication Date
Sun Jan 01 2023
Journal Name
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Artificial Intelligence Based Deep Bayesian Neural Network (DBNN) Toward Personalized Treatment of Leukemia with Stem Cells
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The dynamic development of computer and software technology in recent years was accompanied by the expansion and widespread implementation of artificial intelligence (AI) based methods in many aspects of human life. A prominent field where rapid progress was observed are high‐throughput methods in biology that generate big amounts of data that need to be processed and analyzed. Therefore, AI methods are more and more applied in the biomedical field, among others for RNA‐protein binding sites prediction, DNA sequence function prediction, protein‐protein interaction prediction, or biomedical image classification. Stem cells are widely used in biomedical research, e.g., leukemia or other disease studies. Our proposed approach of

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Journal Name
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Sat Sep 01 2018
Journal Name
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