In this paper, integrated quantum neural network (QNN), which is a class of feedforward

neural networks (FFNN’s), is performed through emerging quantum computing (QC) with artificial neural network(ANN) classifier. It is used in data classification technique, and here iris flower data is used as a classification signals. For this purpose independent component analysis (ICA) is used as a feature extraction technique after normalization of these signals, the architecture of (QNN’s) has inherently built in fuzzy, hidden units of these networks (QNN’s) to develop quantized representations of sample information provided by the training data set in various graded levels of certainty. Experimental results presented here show that

     Machine learning-based techniques are used widely for the classification of images into various categories. The advancement of Convolutional Neural Network (CNN) affects the field of computer vision on a large scale. It has been applied to classify and localize objects in images. Among the fields of applications of CNN, it has been applied to understand huge unstructured astronomical data being collected every second. Galaxies have diverse and complex shapes and their morphology carries fundamental information about the whole universe. Studying these galaxies has been a tremendous task for the researchers around the world. Researchers have already applied some basic CNN models to predict the morphological classes

This study included a survey and review of the scientific names of the marsh insects (aquatic and surrounding it) for the purpose of unifying and updating the database. The survey reveals 109 species under 77 genera that belong to 32 families and 7 orders as follow: Coleoptera (44 species), Diptera (7 species) Ephemeroptera (2 species), Hemiptera (14 species), Hymenoptera (11 species), Lepidoptera (2 species) and Odonata with 29 species. Information of specimens' collection for each species, synonyms and geographical distribution were provided.

This study included a survey and review of the scientific names of the marsh insects (aquatic and surrounding it) for the purpose of unifying and updating the database.
The survey reveals 109 species under 77 genera that belong to 32 families and 7 orders as follow: Coleoptera (44 species), Diptera (7 species) Ephemeroptera (2 species), Hemiptera (14 species), Hymenoptera (11 species), Lepidoptera (2 species) and Odonata with 29 species.
Information of specimens' collection for each species, synonyms and geographical distribution were provided.

The maximization of the net present value of the investment in oil field improvements is greatly aided by the optimization of well location, which plays a significant role in the production of oil. However, using of optimization methods in well placement developments is exceedingly difficult since the well placement optimization scenario involves a large number of choice variables, objective functions, and restrictions. In addition, a wide variety of computational approaches, both traditional and unconventional, have been applied in order to maximize the efficiency of well installation operations. This research demonstrates how optimization approaches used in well placement have progressed since the last time they were examined. Fol

Background: Neudesin is a peptide secreted in brain and adipose tissues that has neural and metabolic functions. Its role as regulator of energy expenditure leads to assumption that its level may be regulated depending on thyroid gland pathology. Objective: This study aimed to investigate serum neudesin levels in patients with thyroidism and to evaluate1 any possible relationship between plasma neudesin levels and thyroid hormone levels. Methods: The study included 100 women with newly diagnosed thyroidisim were subdivided into two groups: hyperthyroidism group (50 female patients with age ranged from 18 to 60 years) and hypothyroidism group (50 female patients with age ranged from 18 to 75 years). A control group (30 healthy females with a

The Objective of the research is to identify the Strategic Vigilance and effect in the Managerial Decision Quality, by knowing the interest of the organization influence the Strategic Vigilance in the Managerial Decision Quality, adopted four dimensions of the Strategic Vigilance is (Environmental Vigilance, Commercial, Competitiveness & Technology) to indicate the extent individually and collectively impact in the Managerial Decision Quality, The questionnaire was used as a main tool to survey the views of a sample of 45 managers, was named Supreme Judicial Council society for research, and the statistical program SPSS, and research found a clear positive impact dimensions Strategic Vigilance in the Manageri

DBNRHM Sami, International Journal of Research in Social Sciences and Humanities, 2020