A group of acceptance sampling to testing the products was designed when the life time of an item follows a log-logistics distribution. The minimum number of groups (k) required for a given group size and acceptance number is determined when various values of Consumer’s Risk and test termination time are specified. All the results about these sampling plan and probability of acceptance were explained with tables.

In this paper, we provide some types of - -spaces, namely, - ( )- (respectively, - ( )- , - ( )- and - ( )-) spaces for minimal structure spaces which are denoted by ( -spaces). Some properties and examples are given.
The relationships between a number of types of - -spaces and the other existing types of weaker and stronger forms of -spaces are investigated. Finally, new types of open (respectively, closed) functions of -spaces are introduced and some of their properties are studied.

Vitamins k is an important fat-soluble vitamin that can be obtained from plants, bacteria and animals and is necessary for the blood clotting. It plays a key function as a cofactor in the synthesizing of blood clotting proteins in the liver; recently, the interest for its functions in extra-hepatic tissue has increased. Vitamin k deficiency is usually caused by abnormal absorption rather than in the lack of vitamin in food. Apart from its impact on clotting, chronic subclinical deficiency of vitamin K maybe a risk factor for many diseases such as osteoporosis, atherosclerosis, cancer, insulin resistance, neurodegenerative diseases and others, while current food intake guidelines be focused on the daily dose necessary to avoid blood loss.

A good performance of reinforced concrete structures is ensured by the bond between steel and concrete, which makes the materials work together, forming a part of solidarity. The behavior of the bond between the reinforcing bar and the surrounding concrete is significant to evaluate the cracking control in serviceability limit state and load capacity in the ultimate limit state. In this investigation, the bond stresses between reinforcing bar and reactive powder concrete (RPC) was considered to compare it with that of normal strength concrete (NSC). The push-out test with short embedment length is considered in this study to evaluate the bond strength, bond stress-slip relationship, and bond stress-crack width relationsh

This study includes six species related to the genus Echinops L. (composite) grown in Iraq which are listed below: E.armatus Boiss. & Hausskn., E. bicolor Nabelek, E. cephalotes DC., E.haussknechtii Boiss., E. moulensis Rech., E. nitens Bornm., the geographical distribution and ecological preferences' were documented.
It has been also observed that this genus was distributed near waterfalls, vallies, road side, dry limestone, clay soil and hard rocky soil in Different heights. The most separated species was E.armatus and the least separated one was E.haussknechtii, the species was listed in diagram and distributed on a map.

Studying extreme precipitation is very important in Iraq. In particular, the last decade witnessed an increasing trend in extreme precipitation as the climate change. Some of which caused a disastrous consequences on social and economic environment in many parts of the country. In this paper a statistical analysis of rainfall data is performed. Annual maximum rainfall data obtained from monthly records for a period of 127 years (1887-2013 inclusive) at Baghdad metrology station have been analyzed. The three distributions chosen to fit the data were Gumbel, Fréchet and the generalized Extreme Value (GEV) distribution. Using the maximum likelihood method, results showed that the GEV distribution was the best followed by Fréchet distribut

This research deals with unusual approach for analyzing the Simple Linear Regression via Linear Programming by Two - phase method, which is known in Operations Research: “O.R.”. The estimation here is found by solving optimization problem when adding artificial variables: Ri. Another method to analyze the Simple Linear Regression is introduced in this research, where the conditional Median of (y) was taken under consideration by minimizing the Sum of Absolute Residuals instead of finding the conditional Mean of (y) which depends on minimizing the Sum of Squared Residuals, that is called: “Median Regression”. Also, an Iterative Reweighted Least Squared based on the Absolute Residuals as weights is performed here as another method to

It is well-known that the existence of outliers in the data will adversely affect the efficiency of estimation and results of the current study. In this paper four methods will be studied to detect outliers for the multiple linear regression model in two cases :  first, in real data; and secondly,  after adding the outliers to data and the attempt to detect it. The study is conducted for samples with different sizes, and uses three measures for  comparing between these methods . These three measures are : the mask, dumping and standard error of the estimate.

Surface water samples from different locations within Tigris River's boundaries in Baghdad city have been analyzed for drinking purposes. Correlation coefficients among different parameters were determined. An attempt has been made to develop linear regression equations to predict the concentration of water quality constituents having significant correlation coefficients with electrical conductivity (EC). This study aims to find five regression models produced and validated using electrical conductivity as a predictor to predict total hardness (TH), calcium (Ca), chloride (Cl), sulfate (SO₄), and total dissolved solids (TDS). The five models showed good/excellent prediction ability of the parameters mentioned

     The present study investigates the implementation of machine learning models on crop data to predict crop yield in Rajasthan state, India. The key objective of the study is to identify which machine learning model performs are better to provide the most accurate predictions. For this purpose, two machine learning models (decision tree and random forest regression) were implemented, and gradient boosting regression was used as an optimization algorithm. The result clarifies that using gradient boosting regression can reduce the yield prediction mean square error to 6%. Additionally, for the present data set, random forest regression performed better than other models. We reported the machine learning model's performance using Mea