Arterial aneurism and stenosis are disorders that lead to circulation malfunction. Stenosis often leads to hypoxia of the organ depending on the affected artery, whilst aneurism can lead to dissection with known lethal consequences. On both cases, the pulse wave produced by the contracting heart is reflected at these discontinuities, and estimating the size of these reflected waves using wave intensity analysis (WIA) is the main aim of this work. We also aim to measure wave speed, or pulse wave velocity (PWV) as more commonly known within the discontinuities. We manufactured 4 stenosis and 4 aneurism silicon sections, connected one at a time to a mother tube, and tested in vitro. Pressure and flow were measured proximal to the discontinuity

All-optical canonical logic units at 40 Gb/s using bidirectional four-wave mixing (FWM) in highly nonlinear fiber are proposed and experimentally demonstrated. Clear temporal waveforms and correct pattern streams are successfully observed in the experiment. This scheme can reduce the amount of nonlinear devices and enlarge the computing capacity compared with general ones. The numerical simulations are made to analyze the relationship between the FWM efficiency and the position of two interactional signals. © 2015 Chinese Laser Press

In this work, radius of shock wave of plasma plume (R) and speed of plasma (U) have been calculated theoretically using Matlab program.

In this paper a theoretical attempt is made to determine whether changes in the aorta diameter at different location along the aorta can be detected by brachial artery measurement.  The aorta is divided into six main parts, each part with 4 lumps of 0.018m length. It is assumed that a desired section of the aorta has a radius change of 100,200, 500%. The results show that there is a significant change for part 2 (lumps 5-8) from the other parts. This indicates that the nearest position to the artery gives the significant change in the artery wave pressure while other parts of the aorta have a small effect.

This paper compare  the accurecy of HF propagation  prediction programs for  HF circuits links between Iraq and  different points world wide  during August 2018 when  solar cycle 24 (start 2009 end 2020) is at minimun activity and also find out the best communication mode  used. The prediction   programs like Voice of America Coverage Analysis Program (VOACAP) and ITU Recommendation RS 533 (REC533 )  had been used to generat HF circuit link  parameters like Maximum Usable Frequency ( MUF) and Frequency of Transsmision (FOT) .Depending  on the predicted parameters (data)  , real radio contacts had been done using a radio transceiver from Icom  model IC 7100 with 100W RF

The study using Nonparametric methods for roubust to estimate a location and scatter it is depending  minimum covariance determinant of multivariate regression model , due to the presence of outliear values and increase the sample size and presence of more than after the model regression multivariate therefore be difficult to find a median location .       

It has been the use of genetic algorithm Fast – MCD – Nested Extension and compared with neural Network Back Propagation of multilayer in terms of accuracy of the results and speed in finding median location ,while the best sample to be determined by relying on less distance (Mahalanobis distance)has the stu

It is believed that Organizations around the world should be prepared for the transition to IPv6 and make sure they have the " know how" to be able to succeed in choosing the right migration to start time. This paper focuses on the transition to IPv6 mechanisms. Also, this paper proposes and tests a deployment of IPv6 prototype within the intranet of the University of Baghdad (BUniv) using virtualization software. Also, it deals with security issues, improvements and extensions of IPv6 network using firewalls, Virtual Private Network ( VPN), Access list ( ACLs). Finally, the performance of the obtainable intrusion detection model is assessed and compared with three approaches.

This study proposes a hybrid predictive maintenance framework that integrates the Kolmogorov-Arnold Network (KAN) with Short-Time Fourier Transform (STFT) for intelligent fault diagnosis in industrial rotating machinery. The method is designed to address challenges posed by non-linear and non-stationary vibration signals under varying operational conditions. Experimental validation using the FALEX multispecimen test bench demonstrated a high classification accuracy of 97.5%, outperforming traditional models such as SVM, Random Forest, and XGBoost. The approach maintained robust performance across dynamic load scenarios and noisy environments, with precision and recall exceeding 95%. Key contributions include a hardware-accelerated K