This research deals with the idea of how the poetic reading can be a
rich field for producing the potential meanings in each text, through observing
the connection of the words and their link with other, thus composes, from the
collection of these interlaced meanings, what is called the poetic significant
(Symbolic) elaboration which deals with the reader of the text by regarding
him as a producer not as a consumer who can read a conscious reading, and
be diligent to solve the problem of the links of the relations among the
inspiring words because the language of poetry is an inspired language which
is capable of diversity and multiplicity of readings which is called the Symbolic
elaboration.

This study analyses six political cartoons selected based on their relevance to current Iraqi political issues, specifically the period between 2005 and 2015, from American online newspapers (calgecartooms.com). The selection criteria included the cartoons' satirical elements, visual rhetoric, and their ability to engage with themes such as power dynamics, social issues, and public opinion. It sheds light on how these cartoons can function as mediators of meanings between the cartoonists and the readers. The data is examined using multimodal discourse analysis (MDA), which combines language study with the analysis of other visual elements, like colors, gestures, and images, to understand meaning (O’Halloran et al., 2011). The Visual Socia

The challenges facing today's multi-customer and this is due to the multiplicity of products and speed in launching new products so search came to reveal the  reveal the of the new product classification standards through a relationship (good products, low interest products, useful products and products desired) and the customer emotionally blackmail through deportation (fear, obligation and guilt). dentified the problem of the research in several questions focused on the nature of the relationship between the variables of research, and for that outline supposedly to search it expresses the head of one hypothesis and branched out of which four hypotheses subset, but in order to ensure the validity of the ass

The vegetable cover plays an important role in the environment and Earth resource sciences. In south Iraq, the region is classified as arid or semiarid area due to the low precipitations and high temperature among the year. In this paper, the Landat-8 satellite imagery will be used to study and estimate the vegetable area in south Iraq. For this purpose many vegetation indices will be examined to estimate and extract the area of vegetation contain in and image. Also, the weathering parameters must be investigated to find the relationship between these parameters and the arability of vegetation cover crowing in the specific area. The remote sensing packages and Matlab written subroutines may be use to evaluate the results.

A simple ,accurate and sensitive spectrophotometric method has been developed the determination of Cobalt(II) and Cupper (II) .The method is based on the chelation of Co(II) and Cu(II) ions with 4-(4´-pyrazolon azo) -2-Naphthol(APAN) in aqueous medium . The complexes have a maximum absorption at (513) and (506) nm and ? max 0.531×10 4 and 0.12×10 5 L.mol -1.cm -1 for Co(II) and Cu(II) respectively .The reagent and two complexes have been prepared in ethanolic solution.The stoichiometry of both complexes were found to be 1:2 (metal :legend) .The effects of various cations and anions on Co(II) and Cu(II) determination have been investigated .The stability constants and standard deviations for Co(II) and Cu(II) 0.291 x107 ,0.909X108 L.mol

In the image processing’s field and computer vision it’s important to represent the image by its information. Image information comes from the image’s features that extracted from it using feature detection/extraction techniques and features description. Features in computer vision define informative data. For human eye its perfect to extract information from raw image, but computer cannot recognize image information. This is why various feature extraction techniques have been presented and progressed rapidly. This paper presents a general overview of the feature extraction categories for image.

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class