Ultrasound imaging has some problems with image properties output. These affects the specialist decision. Ultrasound noise type is the speckle noise which has a grainy pattern depending on the signal. There are two parts of this study. The first part is the enhancing of images with adaptive Weiner, Lee, Gamma and Frost filters with 3x3, 5x5, and 7x7 sliding windows. The evaluated process was achieved using signal to noise ratio (SNR), peak signal to noise ratio (PSNR), mean square error (MSE), and maximum difference (MD) criteria. The second part consists of simulating noise in a standard image (Lina image) by adding different percentage of speckle noise from 0.01 to 0.06. The supervised classification based minimum di

    Feature selection represents one of the critical processes in machine learning (ML). The fundamental aim of the problem of feature selection is to maintain performance accuracy while reducing the dimension of feature selection. Different approaches were created for classifying the datasets. In a range of optimization problems, swarming techniques produced better outcomes. At the same time, hybrid algorithms have gotten a lot of attention recently when it comes to solving optimization problems. As a result, this study provides a thorough assessment of the literature on feature selection problems using hybrid swarm algorithms that have been developed over time (2018-2021). Lastly, when compared with current feature selection procedu

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The research deals with the statement of the importance of unanimous in Islamic Sharia in terms of being the third source of Islamic legislation after the Holy Qur’an and the Sunnah of the Prophet, and the extent of interest of the scholars of interpretation in it, and those who took great interest in mentioning what was agreed upon in every site that necessitated mentioning its issues within, or mentioning an event that has encountered an unanimous, and in various sciences, to extract and extrapolate Sharia rules when these rules are lost in the texts, because it is based on them and derived from them. Among these distinguished scholars is Muhammad bin Jarir al-Tabari. Besides, the research discusses in

The research aims to determine the effectiveness of auditing in light of the relationship between the governance of investment policy and the cost of debt in companies listed on the Iraqi Stock Exchange. The problem of the research is to raise the question about the effect of the governance of investment policy and the cost of debt on the effectiveness of auditing and auditors. During the research, the most important of them were: the existence of an impact relationship on the effectiveness of auditing through the relationship between the governance of investment policy and the cost of debt. The companies listed in the Iraqi Stock Exchange lack an effective proposed guide or framework dealing with the governance of investment policy desp

      Political Discourse Analysis is an important linguistic study approach used by politicians to gain people support. The present paper sheds light on the figures of speech  of emphasis in the televised debate between the two presidential elections candidates, Emmanuel Macron and Marine Le Pen and the distinctive effect they add to the political discourse to win general public support as well as the presidential elections.

       The present paper provides a rudimentary definition and an analysis of the terms “discourse” and “political discourse” and traces the significant role played by politically directed televised Media and internet to support political pa

Merging biometrics with cryptography has become more familiar and a great scientific field was born for researchers. Biometrics adds distinctive property to the security systems, due biometrics is unique and individual features for every person. In this study, a new method is presented for ciphering data based on fingerprint features. This research is done by addressing plaintext message based on positions of extracted minutiae from fingerprint into a generated random text file regardless the size of data. The proposed method can be explained in three scenarios. In the first scenario the message was used inside random text directly at positions of minutiae in the second scenario the message was encrypted with a choosen word before ciphering

Currently, the prominence of automatic multi document summarization task belongs to the information rapid increasing on the Internet. Automatic document summarization technology is progressing and may offer a solution to the problem of information overload. 

Automatic text summarization system has the challenge of producing a high quality summary. In this study, the design of generic text summarization model based on sentence extraction has been redirected into a more semantic measure reflecting individually the two significant objectives: content coverage and diversity when generating summaries from multiple documents as an explicit optimization model. The proposed two models have been then coupled and def

Recently, the phenomenon of the spread of fake news or misinformation in most fields has taken on a wide resonance in societies. Combating this phenomenon and detecting misleading information manually is rather boring, takes a long time, and impractical. It is therefore necessary to rely on the fields of artificial intelligence to solve this problem. As such, this study aims to use deep learning techniques to detect Arabic fake news based on Arabic dataset called the AraNews dataset. This dataset contains news articles covering multiple fields such as politics, economy, culture, sports and others. A Hybrid Deep Neural Network has been proposed to improve accuracy. This network focuses on the properties of both the Text-Convolution Neural

Objective This research investigates Breast Cancer real data for Iraqi women, these data are acquired manually from several Iraqi Hospitals of early detection for Breast Cancer. Data mining techniques are used to discover the hidden knowledge, unexpected patterns, and new rules from the dataset, which implies a large number of attributes. Methods Data mining techniques manipulate the redundant or simply irrelevant attributes to discover interesting patterns. However, the dataset is processed via Weka (The Waikato Environment for Knowledge Analysis) platform. The OneR technique is used as a machine learning classifier to evaluate the attribute worthy according to the class value. Results The evaluation is performed using