ST Alawi, NA Mustafa, Al-Mustansiriyah Journal of Science, 2013

Abstract

Our description of the wxperience of any poet depends on the nature the anture of his writing or his style in terms of factors affecting his experience . We have found that al- Maghout is characterized by important poetis properties that characterized all of his poetry such as the ease in compositions that are formed the vocabulary of daily life . This is what constitutes his poetic lexicon that depends on the vocabulary of space , time , and anture . Hispoetry derives its aesthetics from revealing that strains in the text for the sake of surprise and amazement with a simple realism.

            The widespread use of the Internet of things (IoT) in different aspects of an individual’s life like banking, wireless intelligent devices and smartphones has led to new security and performance challenges under restricted resources. The Elliptic Curve Digital Signature Algorithm (ECDSA) is the most suitable choice for the environments due to the smaller size of the encryption key and changeable security related parameters. However, major performance metrics such as area, power, latency and throughput are still customisable and based on the design requirements of the device.

The present paper puts forward an enhancement for the throughput performance metric by p

In the present work, the image and representation of Adela, the youngest daughter of the family of the Casa de Bernarda Alba, one of the most popular works of the Spanish author Federico García Lorca (1898-1936), will be analyzed. In this work, there are different themes, but what concerns us is to show the repression, oppression and rebellion of this character in a context of customs of the 1920s in Spain. They are revealing elements in that period in which women were relegated to the background, despite the fact that a feminist movement had already begun in Spain. By studying Adela, we seek to see how a single woman confronts her family and the society that surrounds her to fight for freedom, although its end is finally linked to

There is no doubt that the achievement of the manuscripts is important in a place as it is based on reviving the heritage of the Islamic nation, as well as engaging in the prophetic hadith and its sciences pride for every Muslim, and this prompted me to achieve a manuscript message that serves this aspect i.e. the science of the prophetic hadith, and in an important subject that needs to stand on Each of the people, as well as the one who cares about the science of hadith and this topic is: Explaining the hadith of the people is partners in three, to the scholar Muhammad bin Ismail, famous for the Prince Al-Sanani, mentioning his methods and evidence, and their degree of health and weakness, and the statement of what is intended of him,

In the latest years there has been a profound evolution in computer science and technology, which incorporated several fields. Under this evolution, Content Base Image Retrieval (CBIR) is among the image processing field. There are several image retrieval methods that can easily extract feature as a result of the image retrieval methods’ progresses. To the researchers, finding resourceful image retrieval devices has therefore become an extensive area of concern. Image retrieval technique refers to a system used to search and retrieve images from digital images’ huge database. In this paper, the author focuses on recommendation of a fresh method for retrieving image. For multi presentation of image in Convolutional Neural Network (CNN),

The issue of image captioning, which comprises automatic text generation to understand an image’s visual information, has become feasible with the developments in object recognition and image classification. Deep learning has received much interest from the scientific community and can be very useful in real-world applications. The proposed image captioning approach involves the use of Convolution Neural Network (CNN) pre-trained models combined with Long Short Term Memory (LSTM) to generate image captions. The process includes two stages. The first stage entails training the CNN-LSTM models using baseline hyper-parameters and the second stage encompasses training CNN-LSTM models by optimizing and adjusting the hyper-parameters of