In this paper, a new hybridization of supervised principal component analysis (SPCA) and stochastic gradient descent techniques is proposed, and called as SGD-SPCA, for real large datasets that have a small number of samples in high dimensional space. SGD-SPCA is proposed to become an important tool that can be used to diagnose and treat cancer accurately. When we have large datasets that require many parameters, SGD-SPCA is an excellent method, and it can easily update the parameters when a new observation shows up. Two cancer datasets are used, the first is for Leukemia and the second is for small round blue cell tumors. Also, simulation datasets are used to compare principal component analysis (PCA), SPCA, and SGD-SPCA. The results sh

E-learning has recently become of great importance, especially after the emergence of the Corona pandemic, but e-learning has many disadvantages. In order to preserve education, some universities have resorted to using blended learning. Currently, the Ministry of Higher Education and Scientific Research in Iraq has adopted e-learning in universities and schools, especially in scientific disciplines that need laboratories and a spatial presence. In this work, we collected a dataset based on 27 features and presented a model utilizing a support vector machine with regression that was enhanced with the KNN method, which identifies factors that have a substantial influence on the model for the type of education, whether blended or traditiona

This paper proposes a new methodology for improving network security by introducing an optimised hybrid intrusion detection system (IDS) framework solution as a middle layer between the end devices. It considers the difficulty of updating databases to uncover new threats that plague firewalls and detection systems, in addition to big data challenges. The proposed framework introduces a supervised network IDS based on a deep learning technique of convolutional neural networks (CNN) using the UNSW-NB15 dataset. It implements recursive feature elimination (RFE) with extreme gradient boosting (XGB) to reduce resource and time consumption. Additionally, it reduces bias toward

     Automated medical diagnosis is an important topic, especially in detection and classification of diseases. Malaria is one of the most widespread diseases, with more than 200 million cases, according to the 2016 WHO report. Malaria is usually diagnosed using thin and thick blood smears under a microscope. However, proper diagnosis is difficult, especially in poor countries where the disease is most widespread. Therefore, automatic diagnostics helps in identifying the disease through images of red blood cells, with the use of machine learning techniques and digital image processing. This paper presents an accurate model using a Deep Convolutional Neural Network build from scratch. The paper also proposed three CNN

This research aims to show the nature of the impact of proactive and analytical strategic orientation in the dimensions of tax organizational excellence (leadership, strategic planning, information and analysis and knowledge management, focus on taxpayers, focus on operations, focus on workforce, business results), in the General Tax Authority  The questionnaire was used as a tool to collect data and information from the sample of (110) who are (Associate Director General, Head of Department, Under-Head of First Division, Under-Head of Second Section, Division Officer).  Arithmetic mean, intestinal deviation the research has reached a number of conclusions, the most prominent of which are: -

1. There is an effect of

This study was carried out at the Dept. Hortic. and Land.Gard., Coll. Agric. Eng.Sci., University of Baghdad during fall season of 2019-2020, in order to evaluate the effect of nutrient solution type under hydroponic system (NFT) on growth, yield and quality of broccoli Brassica oleracea var.italica. Two experiments were carried out which were the standard solution experiment (Cooper) and the alternative solution experiment (ABEER) prepared from fertilizers. Results revealed that  the type of solution used in the hydroponics system had non significant effect on the leaves content of N,K, Mg, Fe, Cu, B, Chlorophyll, leaves number, root length, weight of the main heads, number of side heads were not significantly affected. 13nt, refl

Abstract

In this research we study the wavelet characteristics for the important time series known as Sunspot, on the aim of verifying the periodogram that other researchers had reached by the spectral transform, and noticing the variation in the period length on one side and the shifting on another.

A continuous wavelet analysis is done for this series and the periodogram in it is marked primarily. for more accuracy, the series is partitioned to its the approximate and the details components to five levels, filtering these components by using fixed threshold on one time and independent threshold on another, finding the noise series which represents the difference between

Source, sedimentation, coagulation, flocculation, filter, and tank are parts of a water treatment plant. As a result, some issues threaten the process and affect the drinking water quality, which is required to provide clean drinking water according to special standards and international and local specifications, determined by laboratory results from physical, chemical, and biological tests. In order to keep the water safe for drinking, it is necessary to analyze the risks and assess the pollution that occurs in every part of the plant. The method is carried out in a common way, which is monitoring through laboratory tests, and it is among the standards of the global and local health regulators

New series of metal ions complexes have been prepared from the new ligand [4-Amino-N-(5-methyl-isaxazol-3-yl)-benzenesulfonamide] derived from Sulfamethoxazole and 3-aminophenol. Accordingly, mono-nuclear Mn(II), Fe(III), Co (II), and Rh(III) complexes were prepared by the reaction of previous ligand with MnCl₂.4H₂O, CoCl₂.6H₂O, FeCl₃.6H₂O and RhCl₃H₂O, respectively. The compounds have been characterized by Fourier-transform infrared (FTIR), ultraviolet–visible (UV–vis), mass,  ¹H-, and ¹³C-nuclear magnetic resonance (NMR) spectra and thermo gravimetric analysis (TGA& DSC) curve, Bohr magnetic (B.M.), elemental microanal

Artificial neural networks usage, as a developed technique, increased in many fields such as Auditing business. Contemporary auditor should cope with the challenges of the technology evolution in the business environment by using computerized techniques such as Artificial neural networks, This research is the first work made in the field of modern techniques of the artificial neural networks in the field of auditing; it is made by using thesample of neural networks as a sample of the artificial multi-layer Back Propagation neural networks in the field of detecting fundamental mistakes of the financial statements when making auditing. The research objectives at offering a methodology for the application of theartificial neural networks wi