Iraq is considered one of the countries most susceptible to the negative impacts of climate change. According to international reports, it is classified as among the top five most affected by climate change in the world, leading to economic resource shortages and an increase in water scarcity, which exposes societal stability in Iraq to a threat. This may result in social disintegration and civil conflicts, so climate changes are considered one of the most dangerous crises affecting societal stability in Iraq during this stage. In this context, the research attempts to trace the causes of climate change and their effects on societal stability in Iraq and suggest some necessary measures to confront them in the future. The research sums up the findings of the study, the most important of which is the need to take comprehensive institutional measures to mitigate the harmful effects of environmental degradation, such as the intensity of greenhouse gas emissions, and to develop treatments, such as legislating the necessary laws for water management to ward off immediate and future risks resulting from societal stability due to climate impacts in order to maintain a better level of societal stability.
Generally, statistical methods are used in various fields of science, especially in the research field, in which Statistical analysis is carried out by adopting several techniques, according to the nature of the study and its objectives. One of these techniques is building statistical models, which is done through regression models. This technique is considered one of the most important statistical methods for studying the relationship between a dependent variable, also called (the response variable) and the other variables, called covariate variables. This research describes the estimation of the partial linear regression model, as well as the estimation of the “missing at random” values (MAR). Regarding the
... Show MorePlants commonly used in traditional medicine are assumed to be safe. This safety is based on their long usage in the treatment of diseases according to knowledge accumulated over centuries. One such plants is Aloe vera which has been used medicinally for centuries. Recent widespread importance of commercial Aloe vera has encouraged scientists to scientifically assess these products since it contains the anthraquinones which associated with considerable risks. In present study oral administration of 20 μl of Aloe vera extract (experimental group) (G) was given for 21 days to immature male Swiss Webster mice at weaning period. While the control groups (C) were given by the same dose and rout of administration with normal saline only. Afte
... Show MoreBanking reforms in many countries have focused on the efficiency enhance of the banking sector, including Iraq, in terms of indicative steps based on recommendations, policies and standards developed by international organizations, foremost of which are Basel III. In this paper, it has tried to highlight the reforms in Basel III and the impact of these reforms on the stability of the banking system in Iraq. As the research derives its importance from the idea that the sound banking system consists of a group of banks capable of employing their assets and obligations efficiently in financial intermediation and enjoying financial solvency. The stability of the banking system is an important factor in achieving the leading role of t
... Show MoreIn this paper a mathematical model that analytically as well as numerically
the flow of infection disease in a population is proposed and studied. It is
assumed that the disease divided the population into five classes: immature
susceptible individuals (S1) , mature individuals (S2 ) , infectious individual
(I ), removal individuals (R) and vaccine population (V) . The existence,
uniqueness and boundedness of the solution of the model are discussed. The
local and global stability of the model is studied. Finally the global dynamics of
the proposed model is studied numerically.
Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class
... Show MoreIn this paper, the goal of proposed method is to protect data against different types of attacks by unauthorized parties. The basic idea of proposed method is generating a private key from a specific features of digital color image such as color (Red, Green and Blue); the generating process of private key from colors of digital color image performed via the computing process of color frequencies for blue color of an image then computing the maximum frequency of blue color, multiplying it by its number and adding process will performed to produce a generated key. After that the private key is generated, must be converting it into the binary representation form. The generated key is extracted from blue color of keyed image then we selects a c
... Show MoreImage classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class
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