This study seeks to shed light on the aspects of visual pollution and its impact on the aesthetics of the town of Al-Eizariya known to suffer from the phenomenon. In order to identify the real causes of the problem which develops in various forms and patterns, threatening not only the aesthetic appearance of the towns, but also causes the emergence of new problems and phenomena that will have negative repercussions on the population. The researcher uses the analytical descriptive method to analyze the phenomenon of visual pollution in terms of reality, development, manifestations and spread and uses photos which document the visual pollution and its impact on the aesthetics of the known. The study concluded the existence of a strong rela

Sheikh Hanafi was born in one of the popular shops of Baghdad with interlocking social relations, and had a profound impact this camp where his talents in the first Venco loving to Mahalah and Baghdad and was born with this development since his days looked forward to the folklore and folk. In the middle of his youth, including authoring loves the heritage of folk legacies began in motion, from Baghdad, books, articles, research has brought him wide acclaim were not possible without the seriousness and diligence, independence and self-Asamath that mushroom on them
The trip was one of his tools in the scientific fame has gone to many Eastern and Asian countries and visited religious and literary institutes and delivered the lectures an

The problem of divorce from the phenomena that characterized the nature of privacy,
although their impact beyond the individual to include the community as a whole, the parties
to the relationship affected by divorce caused them harm moral and material for a long time,
resulting imbalance in the personal relationship and family and social relations because of the
high divorce rates, particularly in Iraq high rates of 28690 thousand cases in 2004 to 59 515
thousand cases in 2011 and an increase of more than (100%) during the period above, and this
rise caused by aggravation of many of the problems led the reasons for social, economic and
incompatibility spouses, health and lack of reproduction, not spending The wife a

The meniscus has a crucial function in human anatomy, and Magnetic Resonance Imaging (M.R.I.) plays an essential role in meniscus assessment. It is difficult to identify cartilage lesions using typical image processing approaches because the M.R.I. data is so diverse. An M.R.I. data sequence comprises numerous images, and the attributes area we are searching for may differ from each image in the series. Therefore, feature extraction gets more complicated, hence specifically, traditional image processing becomes very complex. In traditional image processing, a human tells a computer what should be there, but a deep learning (D.L.) algorithm extracts the features of what is already there automatically. The surface changes become valuable when

<p>The current work investigated the combustion efficiency of biodiesel engines under diverse ratios of compression (15.5, 16.5, 17.5, and 18.5) and different biodiesel fuels produced from apricot oil, papaya oil, sunflower oil, and tomato seed oil. The combustion process of the biodiesel fuel inside the engine was simulated utilizing ANSYS Fluent v16 (CFD). On AV1 diesel engines (Kirloskar), numerical simulations were conducted at 1500 rpm. The outcomes of the simulation demonstrated that increasing the compression ratio (CR) led to increased peak temperature and pressures in the combustion chamber, as well as elevated levels of CO₂ and NO mass fractions and decreased CO emission values un

       In the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from      Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial