Computer-aided diagnosis (CAD) has proved to be an effective and accurate method for diagnostic prediction over the years. This article focuses on the development of an automated CAD system with the intent to perform diagnosis as accurately as possible. Deep learning methods have been able to produce impressive results on medical image datasets. This study employs deep learning methods in conjunction with meta-heuristic algorithms and supervised machine-learning algorithms to perform an accurate diagnosis. Pre-trained convolutional neural networks (CNNs) or auto-encoder are used for feature extraction, whereas feature selection is performed using an ant colony optimization (ACO) algorithm. Ant colony optimization helps to search for the bes

The paper probes into minute identification of the data of the methods followed in the electronic newspapers that aim to promote terrorist organizations like Al Qaeda and ISIS to draw emotional empathy and sympathy with them.
The paper aims at identifying:
How emotional empathy was utilized by terrorists in E-newspapers.
How useful utilizing emotional empathy was in attracting supporters. The sample that is used in the paper is based on the opening articles of E-newspapers that propagate Al Qaeda and ISIS, e.g. (Sawtu el jihad) “The Sound of Fighting in the Name of God”, (Mua’skar el Battar wal Shamikha wal Khansaa) “Camps of Al Battar, Shamika, and Khansaa”, “Inspire” and (Thurwatu el Sanam, Dabiq, and Rumiyah)

Churning of employees from organizations is a serious problem. Turnover or churn of employees within an organization needs to be solved since it has negative impact on the organization. Manual detection of employee churn is quite difficult, so machine learning (ML) algorithms have been frequently used for employee churn detection as well as employee categorization according to turnover. Using Machine learning, only one study looks into the categorization of employees up to date.  A novel multi-criterion decision-making approach (MCDM) coupled with DE-PARETO principle has been proposed to categorize employees. This is referred to as SNEC scheme. An AHP-TOPSIS DE-PARETO PRINCIPLE model (AHPTOPDE) has been designed that uses 2-stage MCDM s

This review is concluded of 8-Hydroxyquinline (8HQ) compound and derivatives which has a very significant interests with a strong fluorescence , furthermore the relationship between divalent metal ions and characteristic of chelating . In the same way coordinated features have increase of its organic action and inorganic behavior by giving many samples of compounds which are a good chelating agents ligands with more capable of forming very stable complexes.Therefore, the role of (8HQ) is not limited on complexes only but its applications in different fields so this review will focus on demonstration preparation methods and properties of (8HQ) derivatives with their complexes and applications, hopefully that we will cover a part of scientifi

This paper present the fast and robust approach of English text encryption and decryption based on Pascal matrix. The technique of encryption the Arabic or English text or both and show the result when apply this method on plain text (original message) and how will form the intelligible plain text to be unintelligible plain text in order to secure information from unauthorized access and from steel information, an encryption scheme usually uses a pseudo-random enecryption key generated by an algorithm. All this done by using Pascal matrix. Encryption and decryption are done by using MATLAB as programming language and notepad ++to write the input text.This paper present the fast and robust approach of English text encryption and decryption b

Semantic segmentation is an exciting research topic in medical image analysis because it aims to detect objects in medical images. In recent years, approaches based on deep learning have shown a more reliable performance than traditional approaches in medical image segmentation. The U-Net network is one of the most successful end-to-end convolutional neural networks (CNNs) presented for medical image segmentation. This paper proposes a multiscale Residual Dilated convolution neural network (MSRD-UNet) based on U-Net. MSRD-UNet replaced the traditional convolution block with a novel deeper block that fuses multi-layer features using dilated and residual convolution. In addition, the squeeze and execution attention mechanism (SE) and the s

The goal of current research to identify the implications of intellectual and psychological drawings of women in prison in Sulaimaniya province through her paint and collected through cooperation with the creativity of the development organization of women in Sulaimaniya, consisted search of five chapters, the first chapter contains the goals of the research and its problem and its significance in addition to its limits and determine the terminology, while the second chapter included the theoretical framework and the literature on the subject of the search, and in the third quarter where he explained the researchers research methodology and procedures, either in the fourth quarter may offer researchers graphics prisoners and then read th

This study measures the indicators of social and environmental performance of the contents of the administration's prepared reports on its social and environmental performance by comparing the actual performance with the indicators set within the standards of the Global Reports Initiative (GRI), In preparing this research, the researchers relied on studying the criteria of the Global Reporting Initiative, which aims to achieve a high level of performance disclosure under sustainability, In light of contemporary global trends towards achieving sustainable development and its disclosure and the orientations of economic institutions and units in different countries towards emphasizing the extent of commitment during practicing its a

This study aims to identfy virtual plastic art exhibitions in light of the challenges of the Corona pandemic. It used a descriptive analytical method through several questions and examining future challenges via the Internet in publishing virtual plastic art exhibitions in many parts of the world in light of the challenges of the Corona pandemic. For that, it used Arab and foreign references.
The study reached many results, the most important of which are: The detection of virtual reality applications and their impact on the plastic arts exhibitions sector. Besides, the insights gained from future art gallery research with VR technology could provide direct and practical value for this sector. By using a technology, similar to the “