This research aims to solve the problem of selection using clustering algorithm, in this research optimal portfolio is formation using the single index model, and the real data are consisting from the stocks Iraqi Stock Exchange in the period 1/1/2007 to 31/12/2019. because the data series have missing values ,we used the two-stage missing value compensation method, the knowledge gap was inability the portfolio models to reduce The estimation error , inaccuracy of the cut-off rate and the Treynor ratio combine stocks into the portfolio that caused to decline in their performance, all these problems required employing clustering technic to data mining and regrouping it within clusters with similar characteristics to outperform the portfolio

Abstract

In this work, diabetic glucose concentration level control under disturbing meal has been controlled using two set of advanced controllers. The first set is sliding mode controllers (classical and integral) and the second set is represented by optimal LQR controllers (classical and Min-, ax). Due to their characteristic features of disturbance rejection, both integral sliding mode controller and LQR Minmax controller are dedicated here for comparison. The Bergman minimal mathematical model was used to represent the dynamic behavior of a diabetic patient’s blood glucose concentration to the insulin injection. Simulations based on Matlab/Simulink, were performed to verify the performance of each controll

The need for quick airborne transportation is critical, especially in emergencies. Drones with suspended payloads might be used to accomplish quick airborne transportation. Due to the environment or the drone's motion, the slung load may oscillate and lead the drone to fall. The altitude and attitude controls are the backbones of the drone's stability, and they must be adequately designed. Because of their symmetrical and simple structure, quadrotor helicopters are one of the most popular drone classes. In this work, a genetic algorithm with two weighted terms fitness function is used to adjust a Proportional-Integral-Derivative (PID) controller to compensate for the altitude and attitude controllers in a quadrotor drone with a slun

The need for quick airborne transportation is critical, especially in emergencies. Drones with suspended payloads might be used to accomplish quick airborne transportation. Due to the environment or the drone's motion, the slung load may oscillate and lead the drone to fall. The altitude and attitude controls are the backbones of the drone's stability, and they must be adequately designed. Because of their symmetrical and simple structure, quadrotor helicopters are one of the most popular drone classes. In this work, a genetic algorithm with two weighted terms fitness function is used to adjust a Proportional-Integral-Derivative (PID) controller to compensate for the altitude and attitude controllers in a quadrotor drone

Patients infected with the COVID-19 virus develop severe pneumonia, which typically results in death. Radiological data show that the disease involves interstitial lung involvement, lung opacities, bilateral ground-glass opacities, and patchy opacities. This study aimed to improve COVID-19 diagnosis via radiological chest X-ray (CXR) image analysis, making a substantial contribution to the development of a mobile application that efficiently identifies COVID-19, saving medical professionals time and resources. It also allows for timely preventative interventions by using more than 18000 CXR lung images and the MobileNetV2 convolutional neural network (CNN) architecture. The MobileNetV2 deep-learning model performances were evaluated

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

To accommodate utilities in buildings, different sizes of openings are provided in the web of reinforced concrete deep beams, which cause reductions in the beam strength and stiffness. This paper aims to investigate experimentally and numerically the effectiveness of using carbon fiber reinforced polymer (CFRP) strips, as a strengthening technique, to externally strengthen reinforced concrete continuous deep beams (RCCDBs) with large openings. The experimental work included testing three RCCDBs under five-point bending. A reference specimen was prepared without openings to explore the reductions in strength and stiffness after providing large openings. Openings were created symmetrically at the center of spans of the other specimens

Big data analysis is essential for modern applications in areas such as healthcare, assistive technology, intelligent transportation, environment and climate monitoring. Traditional algorithms in data mining and machine learning do not scale well with data size. Mining and learning from big data need time and memory efficient techniques, albeit the cost of possible loss in accuracy. We have developed a data aggregation structure to summarize data with large number of instances and data generated from multiple data sources. Data are aggregated at multiple resolutions and resolution provides a trade-off between efficiency and accuracy. The structure is built once, updated incrementally, and serves as a common data input for multiple mining an