Identifying breast cancer utilizing artificial intelligence technologies is valuable and has a great influence on the early detection of diseases. It also can save humanity by giving them a better chance to be treated in the earlier stages of cancer. During the last decade, deep neural networks (DNN) and machine learning (ML) systems have been widely used by almost every segment in medical centers due to their accurate identification and recognition of diseases, especially when trained using many datasets/samples. in this paper, a proposed two hidden layers DNN with a reduction in the number of additions and multiplications in each neuron. The number of bits and binary points of inputs and weights can be changed using the mask configuration

The Next-generation networks, such as 5G and 6G, need capacity and requirements for low latency, and high dependability. According to experts, one of the most important features of (5 and 6) G networks is network slicing. To enhance the Quality of Service (QoS), network operators may now operate many instances on the same infrastructure due to configuring able slicing QoS. Each virtualized network resource, such as connection bandwidth, buffer size, and computing functions, may have a varied number of virtualized network resources. Because network resources are limited, virtual resources of the slices must be carefully coordinated to meet the different QoS requirements of users and services. These networks may be modifie

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

Abstract: The aim of this study is to assess the effectiveness of 940 nm diode laser in comparison to Endoactivator in elimination of smear layer in terms of radicular dentin permeability and ultra-structural changes of root canal walls by SEM evaluation. Twenty-eight single-rooted extracted lower premolars were instrumented up to size X4 (protaper Next, Dentsaply) and divided into two experimental groups according to the irrigation system, G1; activated by EndoActivator and G2; activated by Diode laser 940 nm, CW mode, 1.7 W. Afterward, the roots were made externally impermeable, filled with 2%methylene blue dye, divided horizontally into three segments representing the apical, middle, and coronal thirds then examined under stereo- micr

Dam break is series phenomenon that can result in fatal consequences and loss of properties. Unfortunately, the observed consequences can only be available after the dam breaks. Therefore, it is important to anticipate what will happen prior to dam break to issue suitable warning and locate the possible risk areas. This study attempts to simulate the case of dam break in Blue Nile at Roseires dam and see its consequences downstream. Roseires dam lies at a distance of 630 km south of Khartoum, Sennar dam lies at about 260 km downstream of Roseires dam. In this study hydraulic model is developed based of Hydraulic Engineering Centre (HEC), River Analysis System (RAS), and HEC- RAS. The HEC-RAS based model is calibrated and validated usi

The auditory system can suffer from exposure to loud noise and human health can be affected. Traffic noise is a primary contributor to noise pollution. To measure the noise levels, 3 variables were examined at 25 locations. It was found that the main factors that determine the increase in noise level are traffic volume, vehicle speed, and road functional class. The data have been taken during three different periods per day so that they represent and cover the traffic noise of the city during heavy traffic flow conditions. Analysis of traffic noise prediction was conducted using a simple linear regression model to accurately predict the equivalent continuous sound level. The difference between the predicted and the measured noise shows that

This paper introduces a Laplace-based modeling approach for the study of transient converter-grid interactions. The proposed approach is based on the development of two-port admittance models of converters and other components, combined with the use of numerical Laplace transforms. The application of a frequency domain method is aimed at the accurate and straightforward computation of transient system responses while preserving the wideband frequency characteristics of power components, such as those due to the use of high frequency semiconductive switches, electromagnetic interaction between inductive and capacitive components, as well as wave propagation and frequency dependence in transmission systems.