This research aims to study and reveal the influence of Bauhaus principles in contemporary graphic design. The researcher determined the objective/spatial/temporal limit: Study of the Bauhaus influence in the design of the graphic poster in Germany in 2020. The theoretical framework in the first section dealt with (the emergence and factors of the emergence of the Bauhaus school and its characteristics), while the second topic dealt with (the intellectual, functional and aesthetic data of the Bauhaus School), after which the indicators that resulted from the theoretical framework were produced.

He mentioned four previous studies, one of them was discussed in detail. In the third chapter he defined the methodology, society, and sam

The interior spaces were and still represent the changing intellectual physical entity that uses its changing elements to renew its constants in formulas that respond to the needs and requirements, and with the passage of time the interior spaces have become not based on the size and type of their content only, but their design has become a design and artistic value that corresponds to its content and surpasses it with unfamiliar processes. As its designers led the creative of design with a variety of thinking methods from thought to reality to manifest itself in its tangible form, so we conducted a study that dealt with the problem of research, and purpose, and the theoretical framework included two topics, the first: Intellectual luxury a

Autism is a lifelong developmental deficit that affects how people perceive the world and interact with each others. An estimated one in more than 100 people has autism. Autism affects almost four times as many boys than girls. The commonly used tools for analyzing the dataset of autism are FMRI, EEG, and more recently "eye tracking". A preliminary study on eye tracking trajectories of patients studied, showed a rudimentary statistical analysis (principal component analysis) provides interesting results on the statistical parameters that are studied such as the time spent in a region of interest. Another study, involving tools from Euclidean geometry and non-Euclidean, the trajectory of eye patients also showed interesting results. In this

This study has dealt with, the issue of classification of rural road network , in addition to prepare a suggested for the classification for this network in Iraq , this classification account , the specifications and characteristics of rural roads, population, and the range taking of settlements , then this classification was applied on the rural road network in the Najaf province there are four categories of classification ,the first is major arterial rural roads divided into two major arterial and minor arterial roads , while the second category collected roads which was divided into minor arterial roads and main collected roads. The third category was represented by Local Roads , it has been divided into paved roads and unpaved, the f

In the present work, pattern recognition is carried out by the contrast and relative variance of clouds. The K-mean clustering process is then applied to classify the cloud type; also, texture analysis being adopted to extract the textural features and using them in cloud classification process. The test image used in the classification process is the Meteosat-7 image for the D3 region.The K-mean method is adopted as an unsupervised classification. This method depends on the initial chosen seeds of cluster. Since, the initial seeds are chosen randomly, the user supply a set of means, or cluster centers in the n-dimensional space.The K-mean cluster has been applied on two bands (IR2 band) and (water vapour band).The textural analysis is used

Diabetic retinopathy is an eye disease in diabetic patients due to damage to the small blood vessels in the retina due to high and low blood sugar levels. Accurate detection and classification of Diabetic Retinopathy is an important task in computer-aided diagnosis, especially when planning for diabetic retinopathy surgery. Therefore, this study aims to design an automated model based on deep learning, which helps ophthalmologists detect and classify diabetic retinopathy severity through fundus images. In this work, a deep convolutional neural network (CNN) with transfer learning and fine tunes has been proposed by using pre-trained networks known as Residual Network-50 (ResNet-50). The overall framework of the proposed