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Bitcoin Prediction with a hybrid model
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. In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction accuracy criterion and matching curve-fitting in this work demonstrated that if the residuals of the revised model are white noise, the forecasts are unbiased. Future work investigating robust hybrid model forecasting using fuzzy neural networks would be very interesting

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Publication Date
Wed Jan 01 2025
Journal Name
Open Veterinary Journal
<b>Histopathological effects of repeated 14-day administration of rizatriptan benzoate in a nitroglycerin-induced migraine rabbit model</b>
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Background: Migraine is one of multiple attack neurological conditions that causes moderate to severe headaches with no defined pathophysiology and few animal models. Aim: Establishing an animal model that reproduces migraine-like action is important in medical research to identify the mechanism underlying this disorder. Additionally, it facilitates the availability and reliability of new models that may act as human surrogate models. Method: Rabbits were divided into four groups. Negative group, migraine group, rizatriptan- nitroglycerin group, and rizatriptan group. The frequency of head scratching and the histopathological changes in the brain, liver, kidney, and heart for groups were evaluated in all groups. Results: T

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Publication Date
Wed Jun 10 2020
Journal Name
Annals Of Tropical Medicine & Public Health
EFFECT OF EUCALYPTUS AND MYRTUS EXTRACTS IDENTIFICATION BY GAS CHROMATOGRAPHY-MASS SPECTROMETRY ON SOME SPECIES OF CANDIDA AS A MODEL OF MEDICAL PLANTS
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The study showed that all extracts (aqueous, ethanolic and acetonic) of the leaves of Eucalyptus and Myrtus plants had a inhibitory effect on the growth of all types of yeasts studied, acetone extract recorded the highest inhibition of yeastat 100ppm concentration,The inhibition was 35mm, 34mm, 24mm and 20mm for Candida parapsilosis, Candida glabrata, Candida tropicalis and Candida albicans respectively, The experiments above showed the least significant differences at 0.05 level.The results ofE. Cammldulensis ethanolic tincture analysis has shown the presence of 44 biologically active substances. The main Eucalyptus leaves component was: 2-Bicyclo (2-2.1) heptanol (12.37%), Ledol (8.23%),1,2,4- Benzenetriol (8.45%) and that contain spathul

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Publication Date
Fri Jan 31 2025
Journal Name
Open Veterinary Journal
<b>Histopathological effects of repeated 14-day administration of rizatriptan benzoate in a nitroglycerin-induced migraine rabbit model</b>
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Background: Migraine is one of multiple attack neurological conditions that causes moderate to severe headaches with no defined pathophysiology and few animal models. Aim: Establishing an animal model that reproduces migraine-like action is important in medical research to identify the mechanism underlying this disorder. Additionally, it facilitates the availability and reliability of new models that may act as human surrogate models. Method: Rabbits were divided into four groups. Negative group, migraine group, rizatriptan- nitroglycerin group, and rizatriptan group. The frequency of head scratching and the histopathological changes in the brain, liver, kidney, and heart for groups were evaluated in all groups. Results: T

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Publication Date
Mon Feb 01 2021
Journal Name
Journal Of Physics: Conference Series
Bayesian Computational Methods of the Logistic Regression Model
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Abstract<p>In this paper, we will discuss the performance of Bayesian computational approaches for estimating the parameters of a Logistic Regression model. Markov Chain Monte Carlo (MCMC) algorithms was the base estimation procedure. We present two algorithms: Random Walk Metropolis (RWM) and Hamiltonian Monte Carlo (HMC). We also applied these approaches to a real data set.</p>
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Publication Date
Sat Oct 01 2022
Journal Name
Baghdad Science Journal
COVID-19 Diagnosis System using SimpNet Deep Model
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After the outbreak of COVID-19, immediately it converted from epidemic to pandemic. Radiologic images of CT and X-ray have been widely used to detect COVID-19 disease through observing infrahilar opacity in the lungs. Deep learning has gained popularity in diagnosing many health diseases including COVID-19 and its rapid spreading necessitates the adoption of deep learning in identifying COVID-19 cases. In this study, a deep learning model, based on some principles has been proposed for automatic detection of COVID-19 from X-ray images. The SimpNet architecture has been adopted in our study and trained with X-ray images. The model was evaluated on both binary (COVID-19 and No-findings) classification and multi-class (COVID-19, No-findings

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Publication Date
Wed Jun 20 2018
Journal Name
Al-academy
Achieving an Iraqi model in contemporary fashion design
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The Iraqi outfit is characterized by special features and identity that are closely related to the traditions, customs, religious and social beliefs and other references of the Iraqi environment and its factors affecting the individual and society. Every place in Iraq has its own uniform, which differs in terms of its artistic, aesthetic and functional components from place to place.

The abaya, especially worn by women, is especially distinct in terms of the design of the uniform, the nature of the cloth made of it, as well as the color of the abaya, which is dominated by black in most designs. The Dar Al-Taros Center and Textile Research initiated the construction of theoretical and practical bases in the design of contemporary

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Publication Date
Sun Dec 07 2008
Journal Name
Baghdad Science Journal
Optimal Color Model for Information Hidingin Color Images
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In present work the effort has been put in finding the most suitable color model for the application of information hiding in color images. We test the most commonly used color models; RGB, YIQ, YUV, YCbCr1 and YCbCr2. The same procedures of embedding, detection and evaluation were applied to find which color model is most appropriate for information hiding. The new in this work, we take into consideration the value of errors that generated during transformations among color models. The results show YUV and YIQ color models are the best for information hiding in color images.

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Publication Date
Fri Jul 28 2017
Journal Name
Iraqi Journal Of Science
3D Building Reconstruction Using DEM and Mosaic Model
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A digital elevation model (DEM) is a digital representation of ground surface topography or terrain. It can be represented as a raster (a grid of squares) and it is commonly estimated by utilizing remote sensing techniques, or from land surveying. In this research a 3D building of Baghdad university campus have been performed using DEM, where the easting, northing, and elevation of 400 locations have been obtained by field survey using global positioning system (GPS). The image of the investigated area has been extracted from QuickBird satellite sensor (with spatial resolution of 0.6 m). This image has been geo-referenced by selecting ground control points of the GPS. The rectification is running, using 1st order polynomial transformation.

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Publication Date
Tue Oct 19 2021
Journal Name
International Journal Of Online And Biomedical Engineering (ijoe)
Object Tracking Using Adaptive Diffusion Flow Active Model
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Object tracking is one of the most important topics in the fields of image processing and computer vision. Object tracking is the process of finding interesting moving objects and following them from frame to frame. In this research, Active models–based object tracking algorithm is introduced. Active models are curves placed in an image domain and can evolve to segment the object of interest. Adaptive Diffusion Flow Active Model (ADFAM) is one the most famous types of Active Models. It overcomes the drawbacks of all previous versions of the Active Models specially the leakage problem, noise sensitivity, and long narrow hols or concavities. The ADFAM is well known for its very good capabilities in the segmentation process. In this

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Publication Date
Thu Jan 21 2021
Journal Name
Recent Innovations In Chemical Engineering (formerly Recent Patents On Chemical Engineering)
Soap Production Using Vacuum Reactive Distillation: Batch Model
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Introduction: Although soap industry is known from hundreds of years, the development accompanied with this industry was little. The development implied the mechanical equipment and the additive materials necessary to produce soap with the best specifications of shape, physical and chemical properties. Objectives: This research studies the use of vacuum reactive distillation VRD technique for soap production. Methods: Olein and Palmitin in the ratio of 3 to 1 were mixed in a flask with NaOH solution in stoichiometric amount under different vacuum pressures from -0.35 to -0.5 bar. Total conversion was reached by using the VRD technique. The soap produced by the VRD method was compared with soap prepared by the reaction - only method which

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