The  purpose of  this study was to investigate the effect of six thinking hats on creative thinking among 10^th grade female students in Tulkarm district. The sample comprises two sections of 10^th grade female students (n=80) in Adawiya secondary School, The two sections were divided into two groups; one as an experimental group which works with six thinking hats, and the second as control group that learns traditionally. Creative thinking exam was used to measure the creative thinking with reliability (0.88).

The results of the study have shown the following:

There were statistically significant differences at (α ≤ 0.05) in the creative thinking among 10^th grade female student

   The time spent in drilling ahead is usually a significant portion of total well cost. Drilling is an expensive operation including the cost of equipment and material used during the penetration of rock plus crew efforts in order to finish the well without serious problems. Knowing the rate of penetration should help in speculation of the cost and lead to optimize drilling outgoings. Ten wells in the Nasiriya oil field have been selected based on the availability of the data. Dynamic elastic properties of Mishrif formation in the selected wells were determined by using Interactive Petrophysics (IP V3.5) software based on the las files and log record provided. The average rate of penetration and average dynamic elastic propert

Knowledge of the distribution of the rock mechanical properties along the depth of the wells is an important task for many applications related to reservoir geomechanics. Such these applications are wellbore stability analysis, hydraulic fracturing, reservoir compaction and subsidence, sand production, and fault reactivation. A major challenge with determining the rock mechanical properties is that they are not directly measured at the wellbore. They can be only sampled at well location using rock testing. Furthermore, the core analysis provides discrete data measurements for specific depth as well as it is often available only for a few wells in a field of interest. This study presents a methodology to generate synthetic-geomechani

Massive multiple-input multiple-output (massive-MIMO) is considered as the key technology to meet the huge demands of data rates in the future wireless communications networks. However, for massive-MIMO systems to realize their maximum potential gain, sufficiently accurate downlink (DL) channel state information (CSI) with low overhead to meet the short coherence time (CT) is required. Therefore, this article aims to overcome the technical challenge of DL CSI estimation in a frequency-division-duplex (FDD) massive-MIMO with short CT considering five different physical correlation models. To this end, the statistical structure of the massive-MIMO channel, which is captured by the physical correlation is exploited to find sufficiently

We are used Bayes estimators for unknown scale parameter  when shape Parameter  is known of Erlang distribution. Assuming different informative priors for unknown scale  parameter. We derived The posterior density with posterior mean and posterior variance using different informative priors for unknown scale parameter  which are the inverse exponential distribution, the inverse chi-square distribution, the inverse Gamma distribution, and the standard Levy distribution as prior. And we derived Bayes estimators based on the general entropy loss function (GELF) is used the Simulation method to obtain the results. we generated different cases for the parameters of the Erlang model, for different sample sizes. The estimates have been comp

This paper investigated the fatigue life behavior of two composite materials subjected to different times of shot peening (2, 4 and 6 min).The first material prepared from unsaturated polyester with E-glass reinforcement by 33% volume fraction. While, the second one was prepared from unsaturated polyester with aluminum powder by2.5% volume fraction. The experimental results showed that the improvement in endurance limit was obtained (for the first material) at 2, 4 and 6 min shot peening times where the percentage of maximum improvement was 25% at shot peening time of 6 min. While, the endurance limit of the second material decreased at shot peening times of 2, 4 and 6 min where the percentage of maximum reduction was 29 % at shot peenin

The development of a future mechanism for sustainable development in Iraq to meet the current and future challenges requires an analysis of the indicators of sustainable development. This research aims at presenting and analyzing the social care aspect and highlighting the important role of taxes with a focus on social sustainable development to determine the extent and direction of changes. Level of progress, the researcher concludes the weakness of the financial allocations to the Ministry of Labor and Social Affairs and in line with the large number of people who apply the conditions and controls, and recommends the researcher the necessity of participation of all segments of society between the public and private sector In terms of o

Objectives: To determine Smartphone addiction among primary school students and its impacts. The samples of the study were240primary school students in derived from stratified random sampling. The questionnaire was used to collect the data. The data were then an- analyzed using correlation statistics. It also caused a negative impact on demic performance of the primary school students.
Methodology: A cross- sectional study in assessment approach in applied in order to achieve the earlier stated objectives. The study was initiated from October 1st, 2019 to April 30th, 2020. Simple random sampling (probability) sample of (240) Pupils study In primary school at Al-Rusafa first directorate schools in Baghdad City.
Results: The study re

Codes 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 ob