Objecte The study aims to test the effect of using the appropriate quantitative method of demand forecasting in improving the performance of supply chain of the aviation fuel product ( The study sample), One of the products of the Doura refinery (The study site), By testing a set of quantitative methods of demand forecasting using forecasting error measurements, and choosing the least faulty, most accurate and reliable method and adept it in the building  chain.

Is the study of problem through a starting with the fol

The development of the perforated fin had proposed in many studies to enhance the heat transfer from electronic pieces. This paper presents a novel derivative method to find the temperature distribution of the new design (inclined perforated) of the pin fin. Perforated with rectangular section and different angles of inclination was considered. Signum Function is used for modeling the variable heat transfer area. Set of parameters to handle the conduction and convection area were calculated. Degenerate Hypergeometric Equation (DHE) was used for modeling the Complex energy differential equation and then solved by Kummer’s series. In the validation process, Ansys 16.0-Steady State Thermal was used. Two geometric models were consider

In the present study, a pressure drop technique was used to identify the phase inversion point of oil-in-water to water-in-oil flows through a horizontal pipe and to study the effect of additives (nanoparticles, cationic surfactant and blend  nanoparticles-surfactant) on the critical dispersed volume fraction (phase inversion point). The measurements were carried  for mixture velocity ranges from 0.8 m/sec to 2.3 m/sec. The results showed that at low mixture velocity 0.8 and 1 m/sec there is no effect of additives and velocity on phase inversion point, while at high mixture velocities the phase inversion point for nanoparticles and blend (nanoparticles/surfactant) systems was delayed (postponed) to a higher value of the dispers

Field experiment was conducted during 2007 in the experimental field of crop science Department/ Collage of Agriculture/ University of Baghdad, in order to identify the mechanism of compensation of cotton plant of Lashata Variety, with different levels of fruiting form removal in various time intervals and the effect of this factor on yield component. We use complete randomized block design with three replications. To compare the treatments: (control), 50% bud removal for one, two and three successive weeks, and 100% bud removal for one, two and three successive weeks, 50% flower removal for one, two and three successive weeks and 100% flower removal for one, two and three successive weeks, 50% boll removal for one, two and three successive

This study aimed to determine the possibility of culturing genus Artemia in under laboratory conditions for locally culturing and producing. Different salinity concentrations were used, ranging from 5-40g/l . the results showed that the concentration 30g/l is the best for hatching. This concentration recorded hatching efficiency of 68800 nauplii/g cysts and hatching percentage of 45.86%, while the concentration 5g/l recorded less hatching efficiency and hatching percentage of 20266 nauplii/g and 13.5% respectively . Investigating the effect of salinity on individuals survival and growth using saline concentrations ranging from 30to 100g/l, revealed that the best percentage was 75.00% in the first week with 70g/l, whilst the best rates of

Tetragonal compound CuAl0.4Ti0.6Se2 semiconductor has been prepared by
melting the elementary elements of high purity in evacuated quartz tube under low
pressure 10-2 mbar and temperature 1100 oC about 24 hr. Single crystal has been
growth from this compound using slowly cooled average between (1-2) C/hr , also
thin films have been prepared using thermal evaporation technique and vacuum 10-6
mbar at room temperature .The structural properties have been studied for the powder
of compound of CuAl0.4Ti0.6Se2u using X-ray diffraction (XRD) . The structure of the
compound showed chalcopyrite structure with unite cell of right tetragonal and
dimensions of a=11.1776 Ao ,c=5.5888 Ao .The structure of thin films showed

Objectives: To assess the knowledge and practice of thalassemic patients about desferal administration and
complications of iron overload.
Methodology: The present study composed of (50) thalssemic patient who are registered in center and was
performed in Ibn Al-Atheer center for congenital anemia for the period from 15/12/2006 to 1/4/2007.
Results: The result of the study showed highly significant difference at (160.05) for knowledge of thalassemic
patients and also appear highly significant difference at (P<O.O5) for practice of thalassemic patients.
Recommendations: The study recommends that there is necessity to increase the knowledge and practice of
thalassemic patient about desferal administration to minimiz

Convolutional Neural Networks (CNN) have high performance in the fields of object recognition and classification. The strength of CNNs comes from the fact that they are able to extract information from raw-pixel content and learn features automatically. Feature extraction and classification algorithms can be either hand-crafted or Deep Learning (DL) based. DL detection approaches can be either two stages (region proposal approaches) detector or a single stage (non-region proposal approach) detector. Region proposal-based techniques include R-CNN, Fast RCNN, and Faster RCNN. Non-region proposal-based techniques include Single Shot Detector (SSD) and You Only Look Once (YOLO). We are going to compare the speed and accuracy of Faster RCNN,

     Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod

The current research aims to identify the effect of the program to develop the skill of friendship among kindergarten children, as well as the scope of the impact of the program on the sample. To achieve the objectives of the research, the researcher hypothesizes there is no significant difference between the average scores of the sample members on the friendship skill scale for the dimensional scale according to the experimental and control group. The research sample consisted of (60) girl and boy with age ranges (4-6) who were randomly selected from the Kindergarten Unity at Baghdad city/ Rusafa 1. The children were distributed into an experimental and control group, each group consists of (30) girl and boy. The two groups were chosen