Training and retraining of teachers have become a central issue in Iraq recently especially in-service training of English teachers on the new curricula (Iraq opportunities). English teachers should be objectively evaluated and assessed.
A sample of (40) trained teachers of English is included in the study and a questionnaire is used as the main instrument of the study.
The main findings of the study were the following:
1. The trainees were serious in training on the new course (item 6) the programme helped increase their information (item 4) and motivate them towards better teaching (item 3). The aims of the programme were clear (item1). The programme helped develop their teaching skills (item 2) and was comprehensive (item 5).

Based on the assumption that the more teachers know about brain science, the better
prepared they will be to make instructional decisions.
Mind Mapping is a powerful tool for assisting any form of writing. Language is an
important device and a very beneficial means for human being to communicate with other
people .Writing is one of the language skills that will never be left in education.
The study aims at investigating the Impact of applying mind mapping technique as a prewriting
tool on Iraqi EFL college students in essay writing. To do so, 60 EFL college students
were divided randomly selected and divided into two groups experimental and control. Prior
to treatment, participants of the both groups were given a

An experimental work has been conducted on wall attachment fluidics amplifiers, one of them to study the effect of output pressure or load on the amplifier performance. The output load has been simulated as a piston connected to the device output and the piston can be loaded accordingly. The results shows that the output volume flow rate increases as the supply pressure increases under different load and the output pressure remains constant as the supply pressure increases under constant load.

BN Rashid, AKF Jameel, Al- Ustath: Quarterly Scientific Journal, 2017 - Cited by 15

In this paper, a new equivalent lumped parameter model is proposed for describing the vibration of beams under the moving load effect. Also, an analytical formula for calculating such vibration for low-speed loads is presented. Furthermore, a MATLAB/Simulink model is introduced to give a simple and accurate solution that can be used to design beams subjected to any moving loads, i.e., loads of any magnitude and speed. In general, the proposed Simulink model can be used much easier than the alternative FEM software, which is usually used in designing such beams. The obtained results from the analytical formula and the proposed Simulink model were compared with those obtained from Ansys R19.0, and very good agreement has been shown. I

Traffic loading and environmental factors are among the most serious variables that cause the spoilage of flexible pavements and lead to a decrease in their design life. The objective of this study is to investigate the influence of axle load raise and the change in resilient modulus on the flexible pavement design life. Locally, Highway geometric design code for Iraqi building code has assign certain admissible maximum load limits per every axle truck type that should not be overrun. In this paper nine different axle truck loads (8, 9, 10, 11, 12, 13, 14, 15, and 16) tons, single axle with dual tire and, and two different resilient moduli of asphalt pavement were chosen. The evaluation was carried out assuming high temperature to represent

Concrete pavements are essential to modern infrastructure, but their low tensile and flexural strengths can cause cracking and shrinkage. This study evaluates fiber reinforcement with steel and carbon fibers in various combinations to improve rigid pavement performance. Six concrete mixes were tested: a control mix with no fiber, a mix with 1% steel fiber (SF1%), a mix with 1% carbon fiber (CF1%), and three hybrid mixes with 1% fiber content: 0.75% steel /0.25% carbon fiber (SF0.75CF0.25), 0.25% steel /0.75% carbon fiber (SF0.25CF0.75), and 0.5% steel /0.5% carbon fiber ((SF0.5CF0.5). Laboratory experiments including compressive, flexural, and splitting tensile strength tests were conducted at 7, 28, and 90 days, while Finite Element Analys

Background: Radial neck fractures in children account for 5 to 10% of all elbow fractures in children. They are extra-articular fractures of the radius proximal to the bicipital tuberosity. The physis is typically involved as a Salter-Harris I or II pattern. Alternatively, the fracture sometimes is extraphyseal, through the metaphysis. In children there is considerable potential for remodeling after these fractures. Up to 30° of radial head tilt and up to 3 mm of transverse displacement are acceptable. Many modalities of treatment are available regarding Surgical &Non-Surgical treatments. Objectives: To evaluate the functional outcome after surgical percutaneous joystick reduction therapy of severely angulated radial neck fracture i

Background: Radial neck fractures in children account for 5 to 10% of all elbow fractures in children. They are extra-articular fractures of the radius proximal to the bicipital tuberosity. The physis is typically involved as a Salter-Harris I or II pattern. Alternatively, the fracture sometimes is extraphyseal, through the metaphysis. In children there is considerable potential for remodeling after these fractures. Up to 30° of radial head tilt and up to 3 mm of transverse displacement are acceptable. Many modalities of treatment are available regarding Surgical &Non-Surgical treatments. Objectives: To evaluate the functional outcome after surgical percutaneous joystick reduction therapy of severely angulated radial neck fracture i

Deep learning has recently received a lot of attention as a feasible solution to a variety of artificial intelligence difficulties. Convolutional neural networks (CNNs) outperform other deep learning architectures in the application of object identification and recognition when compared to other machine learning methods. Speech recognition, pattern analysis, and image identification, all benefit from deep neural networks. When performing image operations on noisy images, such as fog removal or low light enhancement, image processing methods such as filtering or image enhancement are required. The study shows the effect of using Multi-scale deep learning Context Aggregation Network CAN on Bilateral Filtering Approximation (BFA) for d