The scholars of Iraq in the modern and contemporary era have been interested in the definition of tremendous knowledge treasures left by the successive Iraqi civilizations on Mesopotamia and around the cities, through the census and extrapolation of manuscript heritage and even printed, they compiled indexes,evidence

     Islamic manuscripts are considered an identity for the civilizational, cognitive and cultural development of nations and the Islamic world as a whole, and to identify this identity

The increasing rates of consumption of cigarettes harmful, to health in the world in general, and in Iraq in particular, and because of the costs borne by individuals, and the state as a result of addressing its damage, as well as Iraq's commitment, to international conventions against cigarettes, and demands of the World Health Organization, to raise prices to reduce consumption. Therefore, the tax Selectivity is one of the most important ways of regulating the consumption of this commodity on the one hand and increasing the tax revenue on the other. The research aims to shed light on the issue of selective tax on cigarettes and the impact of their application in increasing tax revenues and identify the effectiveness of the application

     Islamic manuscripts are considered an identity for the civilizational, cognitive and cultural development of nations and the Islamic world as a whole, and to identify this identity, the closing statement usually written at the end of the manuscript helps us with this, meaning that the closing entries serve as the identity document of the manuscript

استخلص عامل التلزن من E. faecalis EM1 بعد تكسير الخلايا بعدة طرق واختيار الطريقة التي تعطي اعلى قيمة تلزن والترسيب بالكحول الاثيلي , واجري فحص التلزن وقياسه للمستخلص  مع انواع من البكتريا السالبة لملون غرام تضمنت     Escherichia coli  و Klebsiella  pneumoniae  و Serratia

Deepfake is a type of artificial intelligence used to create convincing images, audio, and video hoaxes and it concerns celebrities and everyone because they are easy to manufacture. Deepfake are hard to recognize by people and current approaches, especially high-quality ones. As a defense against Deepfake techniques, various methods to detect Deepfake in images have been suggested. Most of them had limitations, like only working with one face in an image. The face has to be facing forward, with both eyes and the mouth open, depending on what part of the face they worked on. Other than that, a few focus on the impact of pre-processing steps on the detection accuracy of the models. This paper introduces a framework design focused on this asp

Human posture estimation is a crucial topic in the computer vision field and has become a hotspot for research in many human behaviors related work. Human pose estimation can be understood as the human key point recognition and connection problem. The paper presents an optimized symmetric spatial transformation network designed to connect with single-person pose estimation network to propose high-quality human target frames from inaccurate human bounding boxes, and introduces parametric pose non-maximal suppression to eliminate redundant pose estimation, and applies an elimination rule to eliminate similar pose to obtain unique human pose estimation results. The exploratory outcomes demonstrate the way that the proposed technique can pre

       Rumors are typically described as remarks whose true value is unknown. A rumor on social media has the potential to spread erroneous information to a large group of individuals. Those false facts will influence decision-making in a variety of societies. In online social media, where enormous amounts of information are simply distributed over a large network of sources with unverified authority, detecting rumors is critical. This research proposes that rumor detection be done using Natural Language Processing (NLP) tools as well as six distinct Machine Learning (ML) methods (Nave Bayes (NB), random forest (RF), K-nearest neighbor (KNN), Logistic Regression (LR), Stochastic Gradient Descent (SGD) and Decision Tree (

A substantial portion of today’s multimedia data exists in the form of unstructured text. However, the unstructured nature of text poses a significant task in meeting users’ information requirements. Text classification (TC) has been extensively employed in text mining to facilitate multimedia data processing. However, accurately categorizing texts becomes challenging due to the increasing presence of non-informative features within the corpus. Several reviews on TC, encompassing various feature selection (FS) approaches to eliminate non-informative features, have been previously published. However, these reviews do not adequately cover the recently explored approaches to TC problem-solving utilizing FS, such as optimization techniques.

Palm vein recognition technology is a one of the most effective biometric technologies for personal identification. Palm acquisition techniques are either contact-based or contactless-based. The contactless-based palm vein system is considered more accurate and efficient when used in modern applications, but it may suffer from problems like pose variations and the delay in the matching process. This paper proposes a contactless-based identification system for palm vein that involves two main steps; First, the central region of the palm is cropped using fast extract region of interest algorithm, then the features are extracted and classified using altered structure of Residual Attention Network, which is a developed version of convolution