Objective: To identify causes of maternal death in Mizan Aman and Gebretsadik shawo general hospitals
Methodology: A case control study on 595 charts, 119 cases and 476 controls was conducted in Mizan
Aman & Gebretsadik shawo general hospitals. Data was analyzed by STATA 13.1. Propensity score
matching analysis was used to see causes of maternal death.
Results: Hemorrhage were the main direct causes of maternal death which accounts 47.9% (β =0.58
(95% CI (0.28,0.87)) in hospital but when projected to population based the sample (β =0.26 (95% CI
(0.22,0.31)). Followed by infection 36 (25.21%) (β = 0.50 (95% CI (0.08, 0.92)). when projected to
population based the sample PIH 7.6%) is significant cause (β = 0.16 (95% CI (0.13, 0.19). Most death
(74.8%) occurred during post-partum period.
Recommendation: The health professionals must work on awareness creation on early arrival at health
institution for delivery before development of different complications
The research aims to evaluate the direct deduction department’s procedures for the process of collecting income tax using the direct deduction method for state departments and the public sector in light of direct deduction tax instructions No. (1) of 2007 and Income Tax Law No. (113) of 1982 (amended) through Giving a clear idea of the reality of tax collection procedures because this type of tax is one of great importance because it contributes to the provision of financial revenues to the state to finance its expenses and direct the economy towards achieving its social, economic and political goals. The researcher makes comparisons between the procedures of the General Tax Authority in collecting the tax and what was approved b
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Scientists and researchers, in the field of psychology, have relied a lot on this language (body language). And some of them put
... Show MoreCodes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an object under de
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