يتناول البحث شخصية شعرية وأدبية فذة هو محمد صالح بحر العلوم الشاعر العراقي المعروف والمولود في بيت ثوري من بيوتات النجف المعادية للاستعمار البريطاني في مطلع القرن العشرين، وينحدر من أسرة عريقة مشهورة بالعلم والأدب، عاش بحر العلوم شاعراً ينقل بصوره الجمالية كل ما يقع في حواسه، وتجربته تثري من اتصاله ببيئته فنجد الشاعر اشبه بالمصور يستمد صوره من واقع بيئته المتنوع. ونحن في بحثنا هذا نحاول أن نرصد أهم المصادر التي ارتكز عليها الشاعر في بناء صوره الشعرية.
In this research the Inter-Particle Expectation Values have been studied for atomics Helium (He) and Beryllium (Be) also for He-like ions, Be-like ions (Li-1, B+1? Li+1, Be+2, B+3) by using Hartree-Fock wave functions, We compared the results to some ions which have the same atomic number from each group with atomic number, We compared the results with published calculations to the last studied .
During the 1970s, communicative view of language teaching began to be incorporated into syllabus design. The central question for the proponents of this view was: what does the learner want/need to do with the target language? This lead to the emergence of a teaching method (or approach) called communicative language teaching (CLT) during the late 1970s and early 1980s focusing on the functions that must be incorporated into a classroom. According to Brown (2001:43) CLT is a unified but broadly based, theoretically well informed set of tenets about the nature of language and of language learning and teaching. Harmer (2001:84) states that the communicative approach is the name which was given to a set of beliefs which included not only a
... Show MoreThe deep learning algorithm has recently achieved a lot of success, especially in the field of computer vision. This research aims to describe the classification method applied to the dataset of multiple types of images (Synthetic Aperture Radar (SAR) images and non-SAR images). In such a classification, transfer learning was used followed by fine-tuning methods. Besides, pre-trained architectures were used on the known image database ImageNet. The model VGG16 was indeed used as a feature extractor and a new classifier was trained based on extracted features.The input data mainly focused on the dataset consist of five classes including the SAR images class (houses) and the non-SAR images classes (Cats, Dogs, Horses, and Humans). The Conv
... Show MoreBackground: Body image is one of the most important psychological factors that affects adolescents’ personality and behavior. Body image can be defined as the person’s perceptions, thoughts, and feelings about his or her body.
Objectives: to identify the prevalence of body image concerns among secondary school students and its relation to different factors.
Subjects and methods: A cross-sectional study conducted in which 796 secondary school students participated and body shape concerns was investigated using the body shape questionnaire (BSQ-34).
Results: The prevalence of moderate/marked concern was (21.6%). Moderate/ marked body shape concern was significantly associated
... Show MoreAbstract
Metal cutting processes still represent the largest class of manufacturing operations. Turning is the most commonly employed material removal process. This research focuses on analysis of the thermal field of the oblique machining process. Finite element method (FEM) software DEFORM 3D V10.2 was used together with experimental work carried out using infrared image equipment, which include both hardware and software simulations. The thermal experiments are conducted with AA6063-T6, using different tool obliquity, cutting speeds and feed rates. The results show that the temperature relatively decreased when tool obliquity increases at different cutting speeds and feed rates, also it
... Show MoreImage compression is a serious issue in computer storage and transmission, that simply makes efficient use of redundancy embedded within an image itself; in addition, it may exploit human vision or perception limitations to reduce the imperceivable information Polynomial coding is a modern image compression technique based on modelling concept to remove the spatial redundancy embedded within the image effectively that composed of two parts, the mathematical model and the residual. In this paper, two stages proposed technqies adopted, that starts by utilizing the lossy predictor model along with multiresolution base and thresholding techniques corresponding to first stage. Latter by incorporating the near lossless com
... Show MoreMany approaches of different complexity already exist to edge detection in
color images. Nevertheless, the question remains of how different are the results
when employing computational costly techniques instead of simple ones. This
paper presents a comparative study on two approaches to color edge detection to
reduce noise in image. The approaches are based on the Sobel operator and the
Laplace operator. Furthermore, an efficient algorithm for implementing the two
operators is presented. The operators have been applied to real images. The results
are presented in this paper. It is shown that the quality of the results increases by
using second derivative operator (Laplace operator). And noise reduced in a good
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
... Show MoreImage 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
... Show More