This research introduce a study with application on Principal Component Regression obtained from some of the explainatory variables to limitate Multicollinearity problem among these variables and gain staibilty in their estimations more than those which yield from Ordinary Least Squares. But the cost that we pay in the other hand losing a little power of the estimation of the predictive regression function in explaining the essential variations. A suggested numerical formula has been proposed and applied by the researchers as optimal solution, and vererifing the its efficiency by a program written by the researchers themselves for this porpuse through some creterions: Cumulative Percentage Variance, Coefficient of Determination, Variance

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

Fabrication of a photodetector consists of the conjugated polymer "MEH-PPV"- poly (2-methoxy-5-(2'-ethylhexyloxy)-1,4-phenlenevinylene) and MEH-PPV:MWCNT nanocomposite thin film. The volume ratio investigated was 0.75:0.25. MEH-PPV was dissolved in chloroform solvent and doped with MWCNTs. The spin coating method was used to achieve a facile and low cost photodetector. The absorption spectrum decreases by adding the CNTs. The PL spectrum detected recombination curve results by doping the polymer with CNTs, and AFM measurement showed an increase of roughness average from (0.168 to 2.43nm) of "MEH-PPV" and "MEH-PPV:CNTs", respectively. The doping ratio 0.25, which has a higher photoresponsivity, was evaluated at 1.70 A/W and 2.14 A/W of th

This review is concluded of 8-Hydroxyquinline (8HQ) compound and derivatives which has a very significant interests with a strong fluorescence , furthermore the relationship between divalent metal ions and characteristic of chelating . In the same way coordinated features have increase of its organic action and inorganic behavior by giving many samples of compounds which are a good chelating agents ligands with more capable of forming very stable complexes.Therefore, the role of (8HQ) is not limited on complexes only but its applications in different fields so this review will focus on demonstration preparation methods and properties of (8HQ) derivatives with their complexes and applications, hopefully that we will cover a part of scientifi

This paper  deals  to how to estimate points non measured spatial data when the number of its terms (sample spatial) a few, that are not preferred for the estimation process, because we also know that whenever if the data is large, the estimation results of the points non measured to be better and thus the variance estimate less, so the idea of this paper is how to take advantage of the data other secondary (auxiliary), which have a strong correlation with the primary data (basic) to be estimated single points of non-measured, as well as measuring the variance estimate, has been the use of technique Co-kriging in this field to build predictions spatial estimation process, and then we applied this idea to real data in th

   Regarding to the computer system security, the intrusion detection systems are fundamental components for discriminating attacks at the early stage. They monitor and analyze network traffics, looking for abnormal behaviors or attack signatures to detect intrusions in early time. However, many challenges arise while developing flexible and efficient network intrusion detection system (NIDS) for unforeseen attacks with high detection rate. In this paper, deep neural network (DNN) approach was proposed for anomaly detection NIDS. Dropout is the regularized technique used with DNN model to reduce the overfitting. The experimental results applied on NSL_KDD dataset. SoftMax output layer has been used with cross entropy loss funct

Rhythm is considered one of the creative concepts in the recent architectural thought; it has emerged clearly as a mean of creating the highest levels of creativity in architecture, especially in contemporary architectural movements. The importance of rhythm has  emerged, especially, when the architecture , its beginnings concentrated on the principle of the links with poetic structures. Many architectural studies deal with concept of rhythm in architecture with different ways various according to the trend of each study, this show the importance of studying the concept of rhythm in the architectural field in general. This study try to focus on the utilization of rhythm as creative system in architecture of heritage and contemporary