Underwater Wireless Sensor Networks (UWSNs) play a vital role in ocean monitoring and exploration. However, harsh underwater conditions and frequent topology changes caused by node and sink mobility pose significant challenges for reliable routing. Conventional routing protocols that depend on global route reconstruction and static paths generate excessive control overhead and degrade performance in large-scale underwater environments. In this paper, we propose an energy-efficient virtual cell-based mobile-sink adaptive routing (VC-MAR) protocol for UWSNs. The sensing field is logically partitioned into a three-dimensional grid of virtual cells, where a cell-gateway is elected in each cell to construct a low-overhead routing backbon

The current research aims to know the complementary use of the paper book and the digital book by defining the paper book and the digital book and knowing the methods and methods of obtaining each of them and indicating the extent of their use and for what purpose and knowing the difficulties that researchers face in using each of them and which is better using the paper book or the digital book in preparing research Studies and for no reason. The research relied on the descriptive approach and the questionnaire as a tool for data collection, and it was distributed to professors and students of Iraqi universities. The research sample reached (219) individuals and reached a set of results, the most important of which are: Preference for the

Manual probing and periodontal charting are the gold standard for periodontal diagnosis that have been used in practice over a century. These methods are affordable and reliable but they are associated with some drawbacks that cannot be avoided. Among these issues is their reliance on operator’s skills, time-consuming and tedious procedure, lack sensitivity especially in cases of early bone loss, and causing discomfort to the patient. Availability of a wide range of biomarkers in the oral biofluids, dental biofilm, and tissues that potentially reflect the periodontal health and disease accurately encouraged their use as predictive/diagnostic/monitoring tools. Analysing biomarkers during care-giving to the patient using chairside kits i

Self-repairing technology based on micro-capsules is an efficient solution for repairing cracked cementitious composites. Self-repairing based on microcapsules begins with the occurrence of cracks and develops by releasing self-repairing factors in the cracks located in concrete. Based on previous comprehensive studies, this paper provides an overview of various repairing factors and investigative methodologies. There has recently been a lack of consensus on the most efficient criteria for assessing self-repairing based on microcapsules and the smart solutions for improving capsule survival ratios during mixing. The most commonly utilized self-repairing efficiency assessment indicators are mechanical resistance and durab

This paper proposes a self organizing fuzzy controller as an enhancement level of the fuzzy controller. The adjustment mechanism provides explicit adaptation to tune and update the position of the output membership functions of the fuzzy controller. Simulation results show that this controller is capable of controlling a non-linear time varying system so that the performance of the system improves so as to reach the desired state in a less number of samples.

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

Distributed Denial of Service (DDoS) attacks on Web-based services have grown in both number and sophistication with the rise of advanced wireless technology and modern computing paradigms. Detecting these attacks in the sea of communication packets is very important. There were a lot of DDoS attacks that were directed at the network and transport layers at first. During the past few years, attackers have changed their strategies to try to get into the application layer. The application layer attacks could be more harmful and stealthier because the attack traffic and the normal traffic flows cannot be told apart. Distributed attacks are hard to fight because they can affect real computing resources as well as network bandwidth. DDoS attacks

Reinforced concrete (RC) beams containing a longitudinal cavity have become an innovative development and advantage for economic purposes of light-weight members without largely affecting their resistance against the applied loads. This type of openings can also be used for maintenance purposes and usage space of communication lines, pipelines, etc. RC beams are primarily loaded in the plane of the members, which are two-dimensional in a plane stress state and the dominant structural behaviours include bending, shear, or combination of both. In the present study, six numerical models of RC beams with and without openings were simulated by using commercial finite element software ANSYS to evaluate the structural behaviours of those b