Numerical simulations are carried out to assess the quality of the circular and square apodize apertures in observing extrasolar planets. The logarithmic scale of the normalized point spread function of these apertures showed sharp decline in the radial frequency components reaching to 10-36 and 10-34 respectively and demonstrating promising results. This decline is associated with an increase in the full width of the point spread function. A trade off must be done between this full width and the radial frequency components to overcome the problem of imaging extrasolar planets.

Background: Conventional  MR imaging is essential for diagnosis and evaluation of the posterior fossa tumors  Objectives: To assess the value of diffusion weighted imaging and apparent diffusion coefficient in making distinction between different histological types of posterior fossa tumors.

Type of the study: Cross-sectional study.

Methods: Brain MRI and DWI assessed 19 patients (12 female and 7 male) with MRI diagnosis of posterior fossa tumors. absolute ADC values of contrast -enhancing solid tumor region and ADC ratio of solid tumor to ADC of normal -appearing deep White matter were compared with histological diagnosis postoperatively .The m

This research proposes the application of the dragonfly and fruit fly algorithms to enhance estimates generated by the Fama-MacBeth model and compares their performance in this context for the first time. To specifically improve the dragonfly algorithm's effectiveness, three parameter tuning approaches are investigated: manual parameter tuning (MPT), adaptive tuning by methodology (ATY), and a novel technique called adaptive tuning by performance (APT). Additionally, the study evaluates the estimation performance using kernel weighted regression (KWR) and explores how the dragonfly and fruit fly algorithms can be employed to enhance KWR. All methods are tested using data from the Iraq Stock Exchange, based on the Fama-French three-f

In this paper, we used four classification methods to classify objects and compareamong these methods, these are K Nearest Neighbor's (KNN), Stochastic Gradient Descentlearning (SGD), Logistic Regression Algorithm(LR), and Multi-Layer Perceptron (MLP). Weused MCOCO dataset for classification and detection the objects, these dataset image wererandomly divided into training and testing datasets at a ratio of 7:3, respectively. In randomlyselect training and testing dataset images, converted the color images to the gray level, thenenhancement these gray images using the histogram equalization method, resize (20 x 20) fordataset image. Principal component analysis (PCA) was used for feature extraction, andfinally apply four classification metho

This paper proposes a better solution for EEG-based brain language signals classification, it is using machine learning and optimization algorithms. This project aims to replace the brain signal classification for language processing tasks by achieving the higher accuracy and speed process. Features extraction is performed using a modified Discrete Wavelet Transform (DWT) in this study which increases the capability of capturing signal characteristics appropriately by decomposing EEG signals into significant frequency components. A Gray Wolf Optimization (GWO) algorithm method is applied to improve the results and select the optimal features which achieves more accurate results by selecting impactful features with maximum relevance

The research aims to improve operational performance through the application of the Holonic Manufacturing System (HMS) in the rubber products factory in Najaf. The problem was diagnosed with the weakness of the manufacturing system in the factory to meet customers' demands on time within the available resources of machines and workers, which led to time delays of Processing and delivery, increased costs, and reduced flexibility in the factory, A case study methodology used to identify the reality of the manufacturing system and the actual operational performance in the factory. The simulation was used to represent the proposed (HMS) by using (Excel 2010) based on the actual data and calculate the operational performance measures

The investigation of signature validation is crucial to the field of personal authenticity. The biometrics-based system has been developed to support some information security features.Aperson’s signature, an essential biometric trait of a human being, can be used to verify their identification. In this study, a mechanism for automatically verifying signatures has been suggested. The offline properties of handwritten signatures are highlighted in this study which aims to verify the authenticity of handwritten signatures whether they are real or forged using computer-based machine learning techniques. The main goal of developing such systems is to verify people through the validity of their signatures. In this research, images of a group o

Examining and comparing the image quality of degenerative cervical spine diseases through the application of three MRI sequences; the Two-Dimension T2 Weighed Turbo Spin Echo (2D T2W TSE), the Three-Dimension T2 Weighted Turbo Spin Echo (3D T2W TSE), and the T2 Turbo Field Echo (T2_TFE). Thirty-three patients who were diagnosed as having degenerative cervical spine diseases were involved in this study. Their age range was 40-60 years old. The images were produced via a 1.5 Tesla MRI device using (2D T2W TSE, 3D T2W TSE, and T2_TFE) sequences in the sagittal plane. The image quality was examined by objective and subjective assessments. The MRI image characteristics of the cervical spines (C4-C5, C5-C6, C6-C7) showed significant difference

     In this work, the detection of zinc (Zn) ions that cause water pollution is studied using the CSNPs- Linker-alkaloids compound that was prepared by linking extracted alkaloids from Iraqi Catharanthus roseus plant with Chitosan nanoparticles (CSNPs) using maleic anhydride. This compound is characterized by an X-ray diffractometer (XRD) which shows that it has an orthorhombic structure with crystallite size in the nano dimension. Zeta Potential results show that the CSNPs-Linker-alkaloids carried a positive charge of 54.4 mV, which means it possesses high stability.  The Fourier transform infrared spectroscopy (FTIR) shows a new distinct band at 1708.93 cm-1 due to C=O esterification. Scanning electron microscope (SEM) image

In this work, wide band range photo detector operating in UV, Visible and IR was fabricated using carbon nanotubes (MWCNTs, SWCNTs) decorated with silver nanoparticles (Ag NPs). Silicon was used as a substrate to deposited CNTs/Ag NPs by the drop casting technique. Polyamide nylon polymer was used to coat CNTs/Ag NPs to enhance the photo-response of the detector. The electro-exploding wire technology was used to synthesize Ag NPs. Good dispersion of silver NPs achieved by a simple chemistry process on the surface of CNTs. The optical, structure and electrical characteristic of CNTs decorated with Ag NPs were characterized by X-Ray diffraction and Field Emission Scanning Electron Microscopy.  X-ray diffra