The Current research aims to identify ( the effect of Carin model in the achievement of the first intermediate Grade Students and their Reflective Thinking in physics Subject ) the researcher selected the experimental design with a partial adjust , The research sample consisted of ( 47 ) Students with ( 23 ) Students in the experimental group and ( 24 ) Students in the control group , The two groups rewarded in the variables chronological age in months , Reflective Thinking and the degrees in physics in the first course. The researcher coined the purposes of behavioral which belong to chapter fifth, sixth, and seventh of physics books scheduled of the school year ( 2015-2016 ) and prepared appropriate lesson plans for the two experimenta

Has influenced technology contact on social values in the Arab community in general and
the Iraqi community in particular whether this positive change or a negative effect on the level
of the individual and society is reflected this influence through socialization and human
relations as well as the behavior of individuals and dealing with others, where the world was
to soon pass changes slow, and the amounts that can be measured and trends can be calculated
and the effect of points can be identified and controlled, but the technological changes and
openness cognitive features that seemed evident in the last decade of the twentieth century
brought about a change in all scales and distances traditional considerations.<

The use of real-time machine learning to optimize passport control procedures at airports can greatly improve both the efficiency and security of the processes. To automate and optimize these procedures, AI algorithms such as character recognition, facial recognition, predictive algorithms and automatic data processing can be implemented. The proposed method is to use the R-CNN object detection model to detect passport objects in real-time images collected by passport control cameras. This paper describes the step-by-step process of the proposed approach, which includes pre-processing, training and testing the R-CNN model, integrating it into the passport control system, and evaluating its accuracy and speed for efficient passenger flow

New trends in teaching and learning theory are considered a theoretical axis
from which came the background that depends on any source, or practice sample or
teaching plane, accuracy and simplicity prevent the development of the teaching
process. Many attempts have come to scene to illuminate the teaching background,
but they have not exceed those remarkable patterns and methods. Thus, the
appearance of the teaching theory have been hindered.
This led to the need for research and development in the field of teaching to
find out a specific teaching theory according to the modern trends and concepts.
Teaching is regarded a humanitarian process which aims at helping those who
want to acquire knowledge, since teach

The rise of Industry 4.0 and smart manufacturing has highlighted the importance of utilizing intelligent manufacturing techniques, tools, and methods, including predictive maintenance. This feature allows for the early identification of potential issues with machinery, preventing them from reaching critical stages. This paper proposes an intelligent predictive maintenance system for industrial equipment monitoring. The system integrates Industrial IoT, MQTT messaging and machine learning algorithms. Vibration, current and temperature sensors collect real-time data from electrical motors which is analyzed using five ML models to detect anomalies and predict failures, enabling proactive maintenance. The MQTT protocol is used for efficient com

       In the pandemic era of COVID19, software engineering and artificial intelligence tools played a major role in monitoring, managing, and predicting the spread of the virus. According to reports released by the World Health Organization, all attempts to prevent any form of infection are highly recommended among people. One side of avoiding infection is requiring people to wear face masks. The problem is that some people do not incline to wear a face mask, and guiding them manually by police is not easy especially in a large or public area to avoid this infection. The purpose of this paper is to construct a software tool called Face Mask Detection (FMD) to detect any face that does not wear a mask in a specific

Deep learning convolution neural network has been widely used to recognize or classify voice. Various techniques have been used together with convolution neural network to prepare voice data before the training process in developing the classification model. However, not all model can produce good classification accuracy as there are many types of voice or speech. Classification of Arabic alphabet pronunciation is a one of the types of voice and accurate pronunciation is required in the learning of the Qur’an reading. Thus, the technique to process the pronunciation and training of the processed data requires specific approach. To overcome this issue, a method based on padding and deep learning convolution neural network is proposed to

Computer-aided diagnosis (CAD) has proved to be an effective and accurate method for diagnostic prediction over the years. This article focuses on the development of an automated CAD system with the intent to perform diagnosis as accurately as possible. Deep learning methods have been able to produce impressive results on medical image datasets. This study employs deep learning methods in conjunction with meta-heuristic algorithms and supervised machine-learning algorithms to perform an accurate diagnosis. Pre-trained convolutional neural networks (CNNs) or auto-encoder are used for feature extraction, whereas feature selection is performed using an ant colony optimization (ACO) algorithm. Ant colony optimization helps to search for the bes