The nuclear level density parameter  in non Equi-Spacing Model (NON-ESM), Equi-Spacing Model (ESM) and the Backshifted Energy Dependent Fermi Gas model (BSEDFG) was determined for 106 nuclei; the results are tabulated and compared with the experimental works. It was found that there are no recognizable differences between our results and the experimental -values. The calculated level density parameters have been used in computing the state density as a function of the excitation energies for ⁵⁸Fe and ²⁴⁶Cm nuclei. The results are in a good agreement with the experimental results from earlier published work.

Materials with external dimensions of one or more nanometers are referred to as nanomaterials. These structures result from a number of manufacturing processes. They are used in many industries, including pharmaceuticals, which is the most significant one. Numerous variables, including size, shape, surface morphology, crystallinity, solubility, etc., affect physical properties. While new physical and chemical processes are being created constantly, the biological method is the ideal strategy for synthesizing nanoparticles since it is straightforward, safe, and economical. Different kinds of nanoparticles can be metabolically synthesized by a wide variety of biological sources, including plants, bacteria, fungi, and yeast. There are

The introduction of the research on the science of training and the physiology of sports was addressed from important sciences, where the physical effort drew the attention of scientists since the past centuries when they studied how the body performs its functions when performing physical exertion and observe the changes that occur in it and write down and study especially the positive effects of the practice of daily sports The aim of the study was to investigate the effect of plank exercises on the lipid component and the metabolic rate (bmr) of the female students of the Higher Institute for Security and Management Development. As for the third chapter, the two researchers used the experimental method on a sample of the female s

      Investment in high education is considered to be most important factors of production which the return an individual and social than economic returns found by searching the growing problem of unemployment, especially among youth graduates, where the unemployment rate in 2010 (50%) of these high rates have led to increased migration of scientific minds graduate recently, "to search for job opportunities outside Iraq for not hiring functions and this is in vain" clear "in the human and financial resources lead to structural imbalances in the Iraqi economy.  When calculating the correlation coefficient between the graduates and the unemployment rate where it reached (0.21) emerged from the results of

Medicine is one of the fields where the advancement of computer science is making significant progress. Some diseases require an immediate diagnosis in order to improve patient outcomes. The usage of computers in medicine improves precision and accelerates data processing and diagnosis. In order to categorize biological images, hybrid machine learning, a combination of various deep learning approaches, was utilized, and a meta-heuristic algorithm was provided in this research. In addition, two different medical datasets were introduced, one covering the magnetic resonance imaging (MRI) of brain tumors and the other dealing with chest X-rays (CXRs) of COVID-19. These datasets were introduced to the combination network that contained deep lea

Background: Nasopharyngeal carcinoma (NPC) is one of the most challenging tumors because of their relative inaccessibility and that their spread can occur without significant symptoms with few signs, but Radiotherapy (RT) has a role in treatment of it.
Objectives: To show that RT is still the modality of choice in the treatment of NPC, to study modes of presentations, commonest histopathological types and their percentages, to show differences in the sensitivities of these types to RT and to find out a 5 year survival rate(5YSR) and its relation with lymph node involvement.
Methods: This is a retrospective study of 44 patients with NPC who were treated with routine RT from 1988-2007 at the institute of radiology and nuclear medicin

Its well known that understanding human facial expressions is a key component in understanding emotions and finds broad applications in the field of human-computer interaction (HCI), has been a long-standing issue. In this paper, we shed light on the utilisation of a deep convolutional neural network (DCNN) for facial emotion recognition from videos using the TensorFlow machine-learning library from Google. This work was applied to ten emotions from the Amsterdam Dynamic Facial Expression Set-Bath Intensity Variations (ADFES-BIV) dataset and tested using two datasets.

    In this article, the research presents a general overview of deep learning-based AVSS (audio-visual source separation) systems. AVSS has achieved exceptional results in a number of areas, including decreasing noise levels, boosting speech recognition, and improving audio quality. The advantages and disadvantages of each deep learning model are discussed throughout the research as it reviews various current experiments on AVSS. The TCD TIMIT dataset (which contains top-notch audio and video recordings created especially for speech recognition tasks) and the Voxceleb dataset (a sizable collection of brief audio-visual clips with human speech) are just a couple of the useful datasets summarized in the paper that can be used to test A

   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