The research sought to demonstrate the effectiveness of monetary policy in banking stability by measuring the impact of monetary policy in the composite index of banking stability in Iraq for the period 2010/2017, as the stability of the financial system is one of the main objectives that the Central Bank is keen to achieve along with other objectives to ensure the performance Effective for all economic units, this is what prompted the central banks to give more attention in ensuring the safety, durability and stability of their financial systems, and the increasing interest by the Central Bank of Iraq in the subject of financial stability stems from its responsibility in ensuring a sound and stable financial system. Maintain it and mini

The Marshlands cover an area of ​​about 24% of the land area of ​​Iraq, which gives it special importance to the country with its resources, resources and human capabilities, and because the conditions of this region are different from other areas environmentally and living necessitates subject to certain design principles achieve sustainable environmental integration to maintain them from For future generations, the idea of ​​research is crystallized by the interest of environmental organizations and urban designers in planning and establishing special laws to exploit the region environmentally, economically and tourism, especially after the current focus of the country's economic revival. T tourism and begin the development

The Hopfield network is one of the easiest types, and its architecture is such that each neuron in the network connects to the other, thus called a fully connected neural network. In addition, this type is considered auto-associative memory, because the network returns the pattern immediately upon recognition, this network has many limitations, including memory capacity, discrepancy, orthogonally between patterns, weight symmetry, and local minimum. This paper proposes a new strategy for designing Hopfield based on XOR operation; A new strategy is proposed to solve these limitations by suggesting a new algorithm in the Hopfield network design, this strategy will increase the performance of Hopfield by modifying the architecture of t

Abstract

In this research provide theoretical aspects of one of the most important statistical distributions which it is Lomax, which has many applications in several areas, set of estimation methods was used(MLE,LSE,GWPM) and compare with (RRE) estimation method ,in order to find out best estimation method set of simulation experiment (36) with many replications  in order  to get mean square error and used it to make compare , simulation experiment  contrast with (estimation method, sample size ,value of location and shape parameter) results show that estimation method effected by simulation experiment factors and ability of using other estimation methods such as(Shrinkage, jackknif

Public-private partnership (PPP) has been used over the past 20-30 years by governments in developed countries to meet the public demand for infrastructural services. In Iraq, the PPP concept is comparatively new to the Government of Iraq (GoI), where the government has historically taken most of the responsibility for providing public services. There are few PPP projects in Iraq. However, the number is increasing. Recently the Iraqi market has experienced a number of attempts of PPP in different sectors, especially after the new investment law in 2006. The aim of this paper is to evaluate the investment environment in Iraq and to indicate the main factors affecting PPP in particular for infrastructure projects. Some literature review and

This research aims to identify the level of extension administration performance under comprehensive quality standards from the perspective of the working staff in agricultural extension at the level of the general extension body and agricultural directorates and agricultural division.this was to identify the extension administration performance under comprehensive quality standards from the perspective of vegetables growers , random sample was selected from the central region governorates Baghdad , Diyala , Babel , karbala and Al-Najaf , a random sample from the workers in the general body numbered 56 employee , sample of staff working in agricultural extension was selected at the level of agricultural directorates in proportion

Credit derivatives (CDs) have been increasingly acknowledged as an important requirement to hedge and transfer credit risk CR. Nonetheless, they have been extensively criticized for destabilizing the whole economic system bringing about the latest subprime credit crisis. The study’s main aim is to investigate the reason for the use of (CDs), whether it is used for hedging or trade purpose, for four of the US international financial institutions that had made it through the 2007 crisis to resume functioning post-crisis. This will be for three different and critical periods, namely the pre, during and after crisis periods (Q1, 2000-Q1, 2014). Adopting the SUR technique, the investigation of the factors that influence the net position of (CD

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

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