The issue of the development of Qur'anic studies for the tasks, and the first thought of minds and multiple understandings, and the most precious ideas, and the alternatives were floated, and varied visions, especially as we live in an era exploding knowledge, and complicate secretions, and scramble his ideas, and to devise intellectual approaches To achieve the witnesses of civilization in the words of the Almighty (to be martyrs on the people) Surat Al - Baqarah / 143 attendance and participation in the achievement and a positive interaction with the participants of humanity and civilization in the light of the meaning (to know) rooms / 13.
Therefore, we must emerge from the one-dimensional view of the Koran to the complex mindset t

William Shakespeare's play Coriolanus explores the journey of power and the transformation of a skilled warrior into a statesman. This paper employs Machiavelli’s framework of pragmatic statecraft to analyse Coriolanus’s tragic failure as a political leader despite his unparalleled prowess as a Roman general. It analyses Coriolanus's political career, revealing how his military skills, while effective in warfare, do not translate into political success. The paper shows that Coriolanus’s contempt for performative politics, refusal to adopt civic diplomacy, and failure to soften aristocratic pride with populist appeal turn plebeians against him and alienate patricians. His upholding of martial honour — fostered by his mother Volumnia

A seasonal study of periphytic algae attached to the surface of river boats was conducted in Tigris river in Al Aadhamiya site for the period from October 2016 to May 2017. A total of 107 taxa of periphytic algae were identified belonging to the four classes of algae. The periphytic algae community dominated by Bacillariophyceae was (60.7%) followed by Chlorophyceae (20.5%) and Cyanophyceae (17.7%) Chrysophyceae was constituted (0.9%) of the total number. During the whole period of study filamentous taxa such as Oscillatoria amphibian, Phormidium spp., Spirulinagigantean, Cladophoreglomerata and Melosira roeseana remained the dominant colonizer which may be reflect the ability of this species to grow multiplies under different environmental

Background: The skull offers a high resistance of adverse environmental conditions over time, resulting in the greater stability of the dimorphic features as compared to other skeletal bony pieces. Sex determination of human skeletal considered an initial step in its identification. The present study is undertaken to evaluate the validity of 3D reconstructed computed tomographic images in sex differentiation by using craniometrical measurements at various parts of the skull. Materials and Method: 3D reconstructed computed tomographic scanning of 100 Iraqi subject, (50 males and 50 females) were analyzed with their age range from20-70 years old. Craniometrical linear measurements were located and marked on both side of the 3D skull images.

Abstract

 The objective of image fusion is to merge multiple sources of images together in such a way that the final representation contains higher amount of useful information than any input one.. In this paper, a weighted average fusion method is proposed. It depends on using weights that are extracted from source images using counterlet transform. The extraction method is done by making the approximated transformed coefficients equal to zero, then taking the inverse counterlet transform to get the details of the images to be fused. The performance of the proposed algorithm has been verified on several grey scale and color test  images, and compared with some present methods.

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

In the age of information and communication revolution, education as one of life aspects has influenced with that revolution by integrating technology in education, which have become as an important learning tools of the whole educational process . Technology, when used appropriately, can help make science classroom a site of active learning and critical thinking, furthering student inquiry and connections with different materials. It is necessary to develop human rights education programs and materials for discretionary and extracurricular activities as it provide them with the skills and tools so that they are empowered to take action to realize their rights. Human rights education is a critical means of instilling the knowledge، skil

The way artists deal with body in their artistic works has had so many forms and methods, whether as an object for their drawings or as a material to create live artistic performances that relate to the idea of correspondence and interaction between different artistic categories such as: drama, dance, and painting as it is the case of the artist Marina Abramovic who has always used her body as an artistic unit to generate meaning and to perform her lively shows.
To go deeper into her career, our work was divided into 3 sections:
The first section was devoted to follow the main artistic stages that her body had gone through, starting with paintings she performed using concepts based on acting, simulation and nudity and ending wi

Heart disease is a significant and impactful health condition that ranks as the leading cause of death in many countries. In order to aid physicians in diagnosing cardiovascular diseases, clinical datasets are available for reference. However, with the rise of big data and medical datasets, it has become increasingly challenging for medical practitioners to accurately predict heart disease due to the abundance of unrelated and redundant features that hinder computational complexity and accuracy. As such, this study aims to identify the most discriminative features within high-dimensional datasets while minimizing complexity and improving accuracy through an Extra Tree feature selection based technique. The work study assesses the efficac