he research aims to determine the competencies that must be met in the digital media literacy curriculum, which contributes to a great extent in developing the skills of criticism and analysis of the media contents of the students. The study of the two researchers according to the methodology of the media survey. The research tools were: the questionnaire tool, which distributed on 86 . The main objectives of the research were:
1. Knowing the best strategy in teaching the digital media literacy curriculum.
2. Knowing which education fits the digital media literacy curriculum.
3. Identifying the cognitive, educational, media, technical skills, and emotional competencies required for the digital media literacy curriculum from the perspective of Iraqi university professors.
4. Disclosing the vocabulary to be available in the competencies required by the digital media literacy curriculum.
The research concludes, the most important of which were:
1. Identifying the knowledge competencies in the digital media literacy curriculum, by focusing on topics based on growing knowledge, mental skills, comprehension and comprehension. This means that the vocabulary of digital media literacy gives the student an open mind and better access to how the different media form their perception.
2. The educational competencies are defined in the digital media literacy curriculum by activating the processes of creativity, learning communication skills and developing the moral motivation of the student, as well as reinforcing the spirit of the active citizen that will create an educated student who can deal with different media.
3. Determining the media competencies by teaching students how the digital media would work, learn about the skills of digital media, production of media materials and content, as well as the knowing of the concept of digital media literacy. The student must learn about the ethics of the media profession, that adjusts the digital media work.
4. Identifying the emotional competencies in the digital media literacy curriculum within the field of activating the processes of motivation, development of trends, directions and needs, because motivation is an important factor in the media work, specifically digital media literacy and the process of shaping trends and meet the needs.
The ongoing COVID‐19 pandemic caused by SARS‐CoV‐2 is associated with high morbidity and mortality. This zoonotic virus has emerged in Wuhan of China in December 2019 from bats and pangolins probably and continuing the human‐to‐human transmission globally since last two years. As there is no efficient approved treatment, a number of vaccines were developed at an unprecedented speed to counter the pandemic. Moreover, vaccine hesitancy is observed that may be another possible reason for this never ending pandemic. In the meantime, several variants and mutations were identified and causing multiple waves globally. Now the safety and efficacy of these vaccines are debatable and recommended to d
Manganese sulfate and Punica granatum plant extract were used to create MnO2 nanoparticles, which were then characterized using techniques like Fourier transform infrared spectroscopy, ultraviolet-visible spectroscopy, atomic force microscopy, X-ray diffraction, transmission electron microscopy, scanning electron microscopy, and energy-dispersive X-ray spectroscopy. The crystal's size was calculated to be 30.94nm by employing the Debye Scherrer equation in X-ray diffraction. MnO2 NPs were shown to be effective in adsorbing M(II) = Co, Ni, and Cu ions, proving that all three metal ions may be removed from water in one go. Ni(II) has a higher adsorption rate throughout the board. Co, Ni, and Cu ion removal efficiencies were 32.79%, 75
... Show MoreThe successful implementation of deep learning nets opens up possibilities for various applications in viticulture, including disease detection, plant health monitoring, and grapevine variety identification. With the progressive advancements in the domain of deep learning, further advancements and refinements in the models and datasets can be expected, potentially leading to even more accurate and efficient classification systems for grapevine leaves and beyond. Overall, this research provides valuable insights into the potential of deep learning for agricultural applications and paves the way for future studies in this domain. This work employs a convolutional neural network (CNN)-based architecture to perform grapevine leaf image classifi
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