The issue of image captioning, which comprises automatic text generation to understand an image’s visual information, has become feasible with the developments in object recognition and image classification. Deep learning has received much interest from the scientific community and can be very useful in real-world applications. The proposed image captioning approach involves the use of Convolution Neural Network (CNN) pre-trained models combined with Long Short Term Memory (LSTM) to generate image captions. The process includes two stages. The first stage entails training the CNN-LSTM models using baseline hyper-parameters and the second stage encompasses training CNN-LSTM models by optimizing and adjusting the hyper-parameters of

The present theoretical study analyzes the legacy of the Chicago School of Urban Sociology and evaluates it in the light of the growth and development of Chicago City and the establishment of sociology in it. Sociology has become an academic discipline recognized in the United States of America in the late nineteenth century, particularly, after the establishment of the first department of sociology in the University of Chicago in 1892. That was during the period of the rapid industrialization and sustainable growth of the Chicago City. The Chicago School relied on Chicago City in particular, as one of the American cities that grew and expanded rapidly in the first two decades of the twentieth century. At the end of the nineteenth centur

Methods of estimating statistical distribution have attracted many researchers when it comes to fitting a specific distribution to data. However, when the data belong to more than one component, a popular distribution cannot be fitted to such data. To tackle this issue, mixture models are fitted by choosing the correct number of components that represent the data. This can be obvious in lifetime processes that are involved in a wide range of engineering applications as well as biological systems. In this paper, we introduce an application of estimating a finite mixture of Inverse Rayleigh distribution by the use of the Bayesian framework when considering the model as Markov chain Monte Carlo (MCMC). We employed the Gibbs sampler and

AIM: The aim of this study was to measure the prevalence of myeloproliferative disorders in a sample of Iraqi patients and to measure the changes in patients’ blood parameters. BACKGROUND: Myeloproliferative disorders are a group of neoplasms affecting the bone marrow progenitor cells characterized by excess cells with a risk of transforming to acute leukemia. There is a gap in knowledge about the prevalence of Iraqi population. Thus, we investigated the prevalence and distribution of different types of myeloproliferative disorders in a sample of Iraqi patients. MATERIALS AND METHODS: Cross-sectional study is done at the National Center of Hematology from November 2019 till March 2020 on 75 patients who were diagnosed

 This study seeks to highlights on the behavioral approach in organization theory as modern and effective entrance in constructing this theory and reflection extent on the behavior of both the product and the information user (accountant and financial information).

 The study also focus on behavioral approach role in consolidating accounting concepts through making harmony between them so that the accountant can influence the user behavior with the concepts and principles of accounting in an effort to provide quality characteristic of accounting information produced by him in consistent with his behavior and information user and its impact on the decision making process by the latter.

Wind energy is one of the most common and natural resources that play a huge role in energy sector, and due to the increasing demand to improve the efficiency of wind turbines and the development of the energy field, improvements have been made to design a suitable wind turbine and obtain the most energy efficiency possible from wind. In this paper, a horizontal wind turbine blade operating under low wind speed was designed using the (BEM) theory, where the design of the turbine rotor blade is a difficult task due to the calculations involved in the design process. To understand the behavior of the turbine blade, the QBlade program was used to design and simulate the turbine rotor blade during working conditions. The design variables suc

Apium graveolens has been utilized for a multitude of purposes due to its diverse pharmacological characteristics. On the other hand, little is known about how the fatty acids (saturated and unsaturated) terpenes and steroids found in Iraqi Apium graveolens affect the human cancer cells. The purpose of this study was to examine the effects of Iraqi Apium graveolens petroleum ether extract on the human prostate cancer cell line (PC3). Subsidiary extraction and phytochemical analysis by GC/MS were performed.The dry and fresh aerial parts (leaves and stem) of Apium graveolens were extracted using a Soxhlet device with 70 % ethanol, then fractionated with petroleum ether. Then Gas Chromatography System was used to identify the bioactive

This work represents study the rock facies and flow unit classification for the Mishrif carbonate reservoir in Buzurgan oil Field, which located n the south eastern Iraq, using wire line logs, core samples and petrophysical data (log porosity and core permeability). Hydraulic flow units were identified using flow zone indicator approach and assessed within each rock type to reach better understanding of the controlling role of pore types and geometry in reservoir quality variations. Additionally, distribution of sedimentary facies and Rock Fabric Number along with porosity and permeability was analyzed in three wells (BU-1, BU-2, and BU-3). The interactive Petrophysics - IP software is used to assess the rock fabric number, flow zon

Many of the dynamic processes in different sciences are described by models of differential equations. These models explain the change in the behavior of the studied process over time by linking the behavior of the process under study with its derivatives. These models often contain constant and time-varying parameters that vary according to the nature of the process under study in this We will estimate the constant and time-varying parameters in a sequential method in several stages. In the first stage, the state variables and their derivatives are estimated in the method of penalized splines(p- splines) . In the second stage we use pseudo lest square to estimate constant parameters, For the third stage, the rem