Fire incidences are classed as catastrophic events, which mean that persons may experience mental distress and trauma. The development of a robotic vehicle specifically designed for fire extinguishing purposes has significant implications, as it not only addresses the issue of fire but also aims to safeguard human lives and minimize the extent of damage caused by indoor fire occurrences. The primary goal of the AFRC is to undergo a metamorphosis, allowing it to operate autonomously as a specialized support vehicle designed exclusively for the task of identifying and extinguishing fires. Researchers have undertaken the tasks of constructing an autonomous vehicle with robotic capabilities, devising a universal algorithm to be employed

An Intelligent Internet of Things network based on an Artificial Intelligent System, can substantially control and reduce the congestion effects in the network. In this paper, an artificial intelligent system is proposed for eliminating the congestion effects in traffic load in an Intelligent Internet of Things network based on a deep learning Convolutional Recurrent Neural Network with a modified Element-wise Attention Gate. The invisible layer of the modified Element-wise Attention Gate structure has self-feedback to increase its long short-term memory. The artificial intelligent system is implemented for next step ahead traffic estimation and clustering the network. In the proposed architecture, each sensing node is adaptive and able to

Aerial Robot Arms (ARAs) enable aerial drones to interact and influence objects in various environments. Traditional ARA controllers need the availability of a high-precision model to avoid high control chattering. Furthermore, in practical applications of aerial object manipulation, the payloads that ARAs can handle vary, depending on the nature of the task. The high uncertainties due to modeling errors and an unknown payload are inversely proportional to the stability of ARAs. To address the issue of stability, a new adaptive robust controller, based on the Radial Basis Function (RBF) neural network, is proposed. A three-tier approach is also followed. Firstly, a detailed new model for the ARA is derived using the Lagrange–d’A

The research tried to show the importance of  Administrative Control being one of the important means in administrative work; they work on the review and audit work done and error handling explored in the work and prevent the occurrence and ascertain the extent of implementation of the planned targets, and therefore this is reflected in raising the efficiency of the performance of the tax examiner and complete the work as soon as possible and the highest efficiency and reduce the gaps that may occur between the parties of the tax settling accounts and dealt with in the theoretical side of the search to the research problem, namely with whether operating management oversight to improve the performance and increase the efficiency of t

A Multiple System Biometric System Based on ECG Data

Recommendation systems are now being used to address the problem of excess information in several sectors such as entertainment, social networking, and e-commerce. Although conventional methods to recommendation systems have achieved significant success in providing item suggestions, they still face many challenges, including the cold start problem and data sparsity. Numerous recommendation models have been created in order to address these difficulties. Nevertheless, including user or item-specific information has the potential to enhance the performance of recommendations. The ConvFM model is a novel convolutional neural network architecture that combines the capabilities of deep learning for feature extraction with the effectiveness o

These days, it is crucial to discern between different types of human behavior, and artificial intelligence techniques play a big part in that.  The characteristics of the feedforward artificial neural network (FANN) algorithm and the genetic algorithm have been combined to create an important working mechanism that aids in this field. The proposed system can be used for essential tasks in life, such as analysis, automation, control, recognition, and other tasks. Crossover and mutation are the two primary mechanisms used by the genetic algorithm in the proposed system to replace the back propagation process in ANN. While the feedforward artificial neural network technique is focused on input processing, this should be based on the proce

This study aimed to prepare a healthy Nutella rich in specific fatty acids (e.g., oleic, palmitic, and stearic acids) and fat-soluble vitamins (A, E, K, and D) by replacing sunflower oil with anhydrous milk fat (ghee) at substitution levels of 10%, 20%, and 30%. The effect of this substitution on the physicochemical and sensory properties of the laboratoryproduced Nutella was investigated. The chemical composition analysis revealed significant differences (p < 0.05) in fatty acid profiles and vitamin content among the treatments, while some other compositional parameters showed no significant differences. The percentages of oleic, palmitic, stearic, and linolenic fatty acids increased significantly with increasing substitution levels of anh