The aim of the research is to find out the effect of the SPAWN strategy on the life skills of second-intermediate-grade students. This study stage represented the research community within the intermediate and secondary governmental daytime schools affiliated with the Directorate of Education of Diwaniyah. The experiment was applied in Al-Razai Intermediate School on a sample of second-grade intermediate students, including 66 students distributed into two groups: (32) students within the experimental group and (34) students within the control group. The two groups were equivalent with a number of variables (chronological age, intelligence test, previous information test, life skills scale). The results indicated that the two groups were

The research stems from its goal of identifying the impact of visual management on the strategic acceleration of business organizations and the state of this effect through the knowledge embedding in the Iraqi oil companies. The oil sector was tested, represented by (3) oil companies, and a sample of (151) individuals who participated in activating the visual management, distributed in higher management levels. The research relied on the descriptiveanalytical approach and the questionnaire was a main tool for collecting data and information. The results showed that visual management positively affects strategic acceleration. Moreover, This effect is amplified by the mediating role played by Embedding Knowledge.

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

The main object of this article is to study and introduce a subclass of meromorphic univalent functions with fixed second positive defined by q-differed operator. Coefficient bounds, distortion and Growth theorems, and various are  the obtained results.

In every country in the world, there are a number of amputees who have been exposed to some accidents that led to the loss of their upper limbs. The aim of this study is to suggest a system for real-time classification of five classes of shoulder girdle motions for high-level upper limb amputees using a pattern recognition system. In the suggested system, the wavelet transform was utilized for feature extraction, and the extreme learning machine was used as a classifier. The system was tested on four intact-limbed subjects and one amputee, with eight channels involving five electromyography channels and three-axis accelerometer sensor. The study shows that the suggested pattern recognition system has the ability to classify the sho

During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve