The research aims to build an integrated frame of knowledge for the basic research topics, represented by (assimilation of knowledge, strategic clarity) and their basic variables, by examining the most important scientific propositions on these topics in administrative thought, and framing the knowledge contained in them, in a serious attempt to provide appropriate answers to questions The research dilemma, and the research was applied in the Iraqi Airways Company, whose number is (1200) employees, and the descriptive and analytical approach was adopted in conducting the research. A valid form for statistical analysis, i.e., with a retrieval rate of (92%). The two researchers used the (SPSS & AMOS) program for

A field experiment was carried out in the College of Agricultural Engineering Sciences - University of Baghdad, during the fall season of 2021 to find out which cultivated cultivars of maize are efficient under nitrogen fertilization. The experiment was applied according to an RCBD (split-plot design with three replications). The cultivars of the experiment (Baghdad, 5018, Sarah) supply three levels of nitrogen fertilizer, which are N1 (100 kg.N/ha), N2 (200 kg.N/ha) and N3 (300 kg.N/ha). The statistical analysis results showed the superiority of the Sarah genotype, which gave the highest value of SOD and CAT enzymes, reaching 11.59 units mg-1 and 10.76 units mg-1 . Protein sequentially, while cultivar5018 outperformed as it gave th

The aim of this study is to recognize the influence of model of active thinking in achievement ofeighth grade students andtheir visual thinking in science.The finds of this research show the superiority students of the experimental group who studied the science material by using the active thinking model on the students of the control group who studied by usual method, in the achievement test. Also the finds show that the students of the experimental group are more successful than students of control group in the test of visual thinking, so the two null hypotheses have been rejected. In light of the results of the research, numbers of recommendations were made.

 This research was to determine the effect of rare earth metal (REM) on the as-cast microstructure of Mg-4Al alloy. The rare earth metal used here is Lanthanum to produce Mg-4Al-1.5La alloy. The microstructure was characterized by optical microscopy. The phases of this alloy were identified by X-ray diffraction. The microstructure of Mg-4Al consists of α-Mg and grain boundaries with precipitated phase particles. With the addition of Lanthanum, three distinct phases were identified in the X-ray diffraction patterns of the as cast Mg-4Al-1.5La:  Mg, Al₁₁La₃, Al₄La. The Mg₁₇Al₁₂ phase was not detected. The addition of Lanthanium increases the hardness and dec

يهدف البحث الى دراسة تأثير مؤشرات الاستقرار المالي على قيمة اسهم القطاع المصرفي لسوق العراق للأوراق المالية ، اذ تعد مؤشرات الاستقرار المالي اداة مفيدة لفحص سلامة وصحة القطاع المصرفي , وكذلك اداء لقياس مؤشر الاستقرار المصرفي المتكون من اربع مؤشرات فرعية (مؤشر كفاية راس المال ، مؤشر جودة الموجودات ، مؤشر السيولة ، مؤشر الربحية) ومؤشر الاقتصاد الكلي ، ومؤشر سوق راس ، ومؤشر الدورة المالية للفترة (2015_2020) ، وتمثل ا

Reducing a structure’s self-weight is the main goal and a major challenge for most civil constructions, especially in tall buildings and earthquake-affected buildings. One of the most adopted techniques to reduce the self-weight of concrete structures is applying voids in certain positions through the structure, just like a voided slab or BubbleDeck slab. This research aims to study, experimentally and theoretically, the structural behavior of BubbleDeck reinforced concrete slabs under the effect of harmonic load. Tow-way BubbleDeck slab of 2500mm×2500m×200mm dimensions and uniformly distributed bubbles of 120mm diameter and 160mm spacing c/c was tested experimentally under the effect of harmonic load. Numerical analysis was als

     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