Corrosion Resistance Enhancement for low carbon steel is very important to extend its life service, the coating process is one of the methods which can using to achieve this, and it's the most important in surface treatments to improve the properties of metals and alloys surfaces such as corrosion resistance. In this work, low carbon steel was nitrided and coated with nano zinc using gas phase coating technical, to enhance the resistance of corrosion. The process included adding two layers. The first, a nitride layer, was added by precipitating nitrogen (N) gas, and the second, a zinc (Zn) layer, was added by precipitating Zn. The process of precipitating was carried out at different periods (5, 10, and 15 minutes). Scan electron mi

Transformers are a specific category of neural network design. Transformers often depend on extensive pre-training on a large scale and exhibit a notable degree of computational complexity. The disadvantage of using this method is a significant increase in computational complexity, which necessitates a significant commitment of time and computing resources in order to successfully work with these models. Transformer networks possess the desirable benefit of extracting distant characteristics effectively via their self-attention mechanism. In this paper, the Global Self-Attention Transformer module is applied to tackle these issues. The model is based on a segmentation problem called Brain-GS that works as a mechanism and encompasses

Self-driving automobiles are prominent in science and technology, which affect social and economic development. Deep learning (DL) is the most common area of study in artificial intelligence (AI). In recent years, deep learning-based solutions have been presented in the field of self-driving cars and have achieved outstanding results. Different studies investigated a variety of significant technologies for autonomous vehicles, including car navigation systems, path planning, environmental perception, as well as car control. End-to-end learning control directly converts sensory data into control commands in autonomous driving. This research aims to identify the most accurate pre-trained Deep Neural Network (DNN) for predicting the steerin

The performance of the pavement in terms of vehicle safety and tire wear is affected by the friction behavior of the pavement. To highlight the main characteristics that affect the production of better friction resistance of the pavement surface in this work. The micro-texture and macro-texture of the asphalt surface of Baghdad Airport highway were studied using two methods: (sand patch method and the British pendulum test). The sand patch was examined by drawing sand grains of a specific volume, while the micro-texture was analyzed using a BPT under dry and wet surface conditions. All data obtained from the two examinations were analyzed and modelled statistically using SPSS 25 software. Results show that skid resistance of pavemen

An intrusion detection system (IDS) is key to having a comprehensive cybersecurity solution against any attack, and artificial intelligence techniques have been combined with all the features of the IoT to improve security. In response to this, in this research, an IDS technique driven by a modified random forest algorithm has been formulated to improve the system for IoT. To this end, the target is made as one-hot encoding, bootstrapping with less redundancy, adding a hybrid features selection method into the random forest algorithm, and modifying the ranking stage in the random forest algorithm. Furthermore, three datasets have been used in this research, IoTID20, UNSW-NB15, and IoT-23. The results are compared with the three datasets men