The importance of news broadcasts in society has increased after the domination of television over the mass media, especially after emerging the satellite channels, and spreading the satellite dishes among the public at large.

As well as the great role played by the modern technology in the transmission of news and events happening at once. Such role has contributed, significantly, in changing the concept and values ​​of the news. The live broadcast of the events filmed is the news itself.

In the midst of the great transformations and circumstances that Iraq went through after 2003, which witnessed political and security instability, and the large increase in the number of media, especially satellite channels, in Iraq

Classifying an overlapping object is one of the main challenges faced by researchers who work in object detection and recognition. Most of the available algorithms that have been developed are only able to classify or recognize objects which are either individually separated from each other or a single object in a scene(s), but not overlapping kitchen utensil objects. In this project, Faster R-CNN and YOLOv5 algorithms were proposed to detect and classify an overlapping object in a kitchen area.  The YOLOv5 and Faster R-CNN were applied to overlapping objects where the filter or kernel that are expected to be able to separate the overlapping object in the dedicated layer of applying models. A kitchen utensil benchmark image database and

In this work, 332 Al alloy was prepared and reinforced with (0.5% and 1%) nano-Al₂O₃ particles. The prepared unreinforced and reinforced 332 Al alloy with nano-Al₂O₃ were solution heat treated (T6) at 510 ̊C and aged at 225 ̊C with different times (1, 3, and 5 h). Hardness test was performed on all the prepared alloys. All prepared alloys were dry slided under different applied loads (5, 10, 15, and 20 N) against steel counterface surface using pin on disk apparatus. The results showed that refinement effect was observed after addition of nano-Al₂O₃ particles and a change in silicon morphology after performing the solution heat treatment. The results also showed that har

Energy savings are very common in IoT sensor networks because IoT sensor nodes operate with their own limited battery. The data transmission in the IoT sensor nodes is very costly and consume much of the energy while the energy usage for data processing is considerably lower. There are several energy-saving strategies and principles, mainly dedicated to reducing the transmission of data. Therefore, with minimizing data transfers in IoT sensor networks, can conserve a considerable amount of energy. In this research, a Compression-Based Data Reduction (CBDR) technique was suggested which works in the level of IoT sensor nodes. The CBDR includes two stages of compression, a lossy SAX Quantization stage which reduces the dynamic range of the

The solution to the problems and challenges of the twenty-first century requires the absorption of many transformations, such as demographic change, poverty reduction, the expansion of safe and clean energy without affecting the environment, as well as reducing health risks and other transitions. It also requires greater cooperation than is possible in the current global system, because both of these constraints and challenges, even if addressed locally or nationally, are because of the potential for their transnational impact, that is, their impact on the lives of people at the global level, Which is necessary to be fully addressed unless it is guided by a comprehensive global vision. This is what environmental governance provides in te

The research aims to identify the level of functional engagement and hope-based thinking of kindergarten teachers, identify if there is a significant difference in functional engagement and hope-based thinking in terms of specialization and years of service for kindergarten teachers, identify if there is a significant correlation between functional engagement and hope-based thinking of kindergarten teachers. The current research is determined by kindergarten teachers in the Second Rusafa Baghdad Education Directorate for the academic year (2022-2023). In order to achieve the objectives of the research, the researcher prepared a functional engagement scale, which consists of (45) items in three areas: Perceptual and functional engagement

Thyroid disease is a common disease affecting millions worldwide. Early diagnosis and treatment of thyroid disease can help prevent more serious complications and improve long-term health outcomes. However, thyroid disease diagnosis can be challenging due to its variable symptoms and limited diagnostic tests. By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. This study seeks to discover the most recent ML-based and data-driven developments and strategies for diagnosing thyroid disease while considering the challenges associated with imbalanced data in thyroid dise

عانت الغابات في العراق قصوراً واضحاً في مجال إشباع حاجة السكان لمنتجاتها الرئيسية المتمثلة بالأخشاب ومنتجاتها الثانوية المتمثلة بالأغصان والأوراق والنباتات الطبيعية والحيوانات البرية ونواتجها الأخرى، مما يتطلب التفكير بمحاولة إيجاد سبل جديدة لحل هذه المشكلة الاقتصادية المرتبطة بعنصريها الحاجة للأخشاب والأموال المخصصة لتطويرها عموماً.

لقد دمرت مساحات كبيرة من الغابات وحرقت وقطعت من

In the present research synthesis and study of biological activity a series of new polymers modified of chitosan with compounds containing azo group. Beginning diazonium salt produced from 3,3'-dimethyl-[1,1'-biphenyl]-4,4'-diamine reacted with concentrated HCl acid and sodium nitrite. The coupling reaction between diazonium salt with substituted aromatic aldehyde to produce Azo derivatives )1-6(. Azo Schiff bases Chitosan )7-12( were synthesized by condensation of Chitosan with Azo derivatives )1-6( in ethanol with some drops of glacial acetic acid. The structural modifications of Chitosan ring (linked to a bioactive azo moiety) were expected to give new derivatives )7-12( with a diverse range of biological functions. These compounds' st

Deep learning convolution neural network has been widely used to recognize or classify voice. Various techniques have been used together with convolution neural network to prepare voice data before the training process in developing the classification model. However, not all model can produce good classification accuracy as there are many types of voice or speech. Classification of Arabic alphabet pronunciation is a one of the types of voice and accurate pronunciation is required in the learning of the Qur’an reading. Thus, the technique to process the pronunciation and training of the processed data requires specific approach. To overcome this issue, a method based on padding and deep learning convolution neural network is proposed to