Diode laser technology is well established for biomedicine applications which demand high-power pulse-wave. They are extensively utilized from medical imaging and testing to surgical therapies and the latest aesthetic processes. For medical therapeutic practices, diode lasers have become the ideal laser source for this particular purpose. In the last previous years, semiconductor laser technology has evolved to produce high-repetitions rate near-infrared pulsed lasers diodes that are dependable, low-cost, portable, and small-weight, about few grams. In this paper, we review the recent development and demonstration of diode laser devices for biomedical applications recorded in the latest years taking into account the power, wavelength, and p

Background: Osteogenesis imperfecta (OI) is a rare congenital condition that results in bone fragility, recurrent fractures, and various extra-skeletal manifestations. Currently, intravenous bisphosphonate is the mainstay of medical treatment in OI. Objective: To identify the effect of current management strategies on Iraqi children diagnosed with OI. Methods: A retrospective study enrolled OI patients who were registered in Central Child Teaching Hospital, Baghdad, Iraq, from January 2015 to December 2022. We enrolled confirmed OI cases (either clinically and/or radiologically) who received cyclic pamidronate therapy for at least 3 cycles. They neither received other types of bisphosphonates nor underwent surgical intervention. Res

In networking communication systems like vehicular ad hoc networks, the high vehicular mobility leads to rapid shifts in vehicle densities, incoherence in inter-vehicle communications, and challenges for routing algorithms. It is necessary that the routing algorithm avoids transmitting the pockets via segments where the network density is low and the scale of network disconnections is high as this could lead to packet loss, interruptions and increased communication overhead in route recovery. Hence, attention needs to be paid to both segment status and traffic. The aim of this paper is to present an intersection-based segment aware algorithm for geographic routing in vehicular ad hoc networks. This algorithm makes available the best route f

Software-defined networking (SDN) presents novel security and privacy risks, including distributed denial-of-service (DDoS) attacks. In response to these threats, machine learning (ML) and deep learning (DL) have emerged as effective approaches for quickly identifying and mitigating anomalies. To this end, this research employs various classification methods, including support vector machines (SVMs), K-nearest neighbors (KNNs), decision trees (DTs), multiple layer perceptron (MLP), and convolutional neural networks (CNNs), and compares their performance. CNN exhibits the highest train accuracy at 97.808%, yet the lowest prediction accuracy at 90.08%. In contrast, SVM demonstrates the highest prediction accuracy of 95.5%. As such, an

Massive multiple-input multiple-output (m-MIMO) is considered as an essential technique to meet the high data rate requirements of future sixth generation (6G) wireless communications networks. The vast majority of m-MIMO research has assumed that the channels are uncorrelated. However, this assumption seems highly idealistic. Therefore, this study investigates the m-MIMO performance when the channels are correlated and the base station employs different antenna array topologies, namely the uniform linear array (ULA) and uniform rectangular array (URA). In addition, this study develops analyses of the mean square error (MSE) and the regularized zero-forcing (RZF) precoder under imperfect channel state information (CSI) and a realist