Inflation is one of the important issues that the economic authorities in all countries of the world care about, where the loss of money for its function is one of the most important and largest inflationary effects that this phenomenon leaves on the economy, and Iraq, like other countries, has had its share of the problem of inflation for a long time due to the circumstances that He went through it, whether it was the wars he fought or the economic blockade that was imposed on him in the nineties of the last century. Economically, the problem of inflation is addressed through the use of fiscal policy tools, including tax increases in order to abso

                Inflation is one of the important issues that the economic authorities in all countries of the world care about, where the loss of money for its function is one of the most important and largest inflationary effects that this phenomenon leaves on the economy, and Iraq, like other countries, has had its share of the problem of inflation for a long time due to the circumstances that He went through it, whether it was the wars he fought or the economic blockade that was imposed on him in the nineties of the last century. Economically, the problem of inflation is addressed through the use of fiscal policy tools, including tax increases in order to abso

In this work we present a technique to extract the heart contours from noisy echocardiograph images. Our technique is based on improving the image before applying contours detection to reduce heavy noise and get better image quality. To perform that, we combine many pre-processing techniques (filtering, morphological operations, and contrast adjustment) to avoid unclear edges and enhance low contrast of echocardiograph images, after implementing these techniques we can get legible detection for heart boundaries and valves movement by traditional edge detection methods.

In this paper, a fast lossless image compression method is introduced for compressing medical images, it is based on splitting the image blocks according to its nature along with using the polynomial approximation to decompose image signal followed by applying run length coding on the residue part of the image, which represents the error caused by applying polynomial approximation. Then, Huffman coding is applied as a last stage to encode the polynomial coefficients and run length coding. The test results indicate that the suggested method can lead to promising performance.

Features is the description of the image contents which could be corner, blob or edge. Corners are one of the most important feature to describe image, therefore there are many algorithms to detect corners such as Harris, FAST, SUSAN, etc. Harris is a method for corner detection and it is an efficient and accurate feature detection method. Harris corner detection is rotation invariant but it isn’t scale invariant. This paper presents an efficient harris corner detector invariant to scale, this improvement done by using gaussian function with different scales. The experimental results illustrate that it is very useful to use Gaussian linear equation to deal with harris weakness.

The intelligent buildings provided various incentives to get highly inefficient energy-saving caused by the non-stationary building environments. In the presence of such dynamic excitation with higher levels of nonlinearity and coupling effect of temperature and humidity, the HVAC system transitions from underdamped to overdamped indoor conditions. This led to the promotion of highly inefficient energy use and fluctuating indoor thermal comfort. To address these concerns, this study develops a novel framework based on deep clustering of lagrangian trajectories for multi-task learning (DCLTML) and adding a pre-cooling coil in the air handling unit (AHU) to alleviate a coupling issue. The proposed DCLTML exhibits great overall control and is

  In this paper, we investigate the connection between the hierarchical models and the power prior distribution in quantile regression (QReg). Under specific quantile, we develop an expression for the power parameter ( ) to calibrate the power prior distribution for quantile regression to a corresponding hierarchical model. In addition, we estimate the relation between the  and the quantile level via hierarchical model. Our proposed methodology is illustrated with real data example.

Background: Neonatal period is a very vulnerable period of life due to many problems, In spite of advances in perinatal and neonatal care still, the mortality rate of neonate high especially in developing country The World Health Organization estimates that globally four million neonatal deaths per year, Developing countries account for around 99% of the neonatal mortality in the world, In Iraq. Neonatal mortality rate about 19 per 1000 live births which represent 56% of child death below 5 years age in 2012. The hospital in the study represents the larger pediatric hospital in Iraq. It contains 400 children's beds and 24 neonatal incubators.

Aims of the study: are to determine the institutional

Objective: The aim of the present study is to assess the practices of nurses towards standard precautions at Azady
Teaching Hospital in the City of Kirkuk.
Methodology: A descriptive study, which uses the assessment approach and it was conducted on nurses from January
18th, 2009 to September 30th, 2009, using non-probability sampling a purposive sample of (37) subject (male and
female nurses) who worked at surgical wards in Azady Teaching Hospital in Kirkuk city was selected. Two study
instruments were utilized for proper data collection [questionnaire and observational checklist]; a questionnaire was
developed for the purpose of the study. It was comprised of two parts which included the nurses' demographic
characte