The aim of this research is to compare traditional and modern methods to obtain the optimal solution using dynamic programming and intelligent algorithms to solve the problems of project management.

It shows the possible ways in which these problems can be addressed, drawing on a schedule of interrelated and sequential activities And clarifies the relationships between the activities to determine the beginning and end of each activity and determine the duration and cost of the total project and estimate the times used by each activity and determine the objectives sought by the project through planning, implementation and monitoring to maintain the budget assessed 

A system was used to detect injuries in plant leaves by combining machine learning and the principles of image processing. A small agricultural robot was implemented for fine spraying by identifying infected leaves using image processing technology with four different forward speeds (35, 46, 63 and 80 cm/s). The results revealed that increasing the speed of the agricultural robot led to a decrease in the mount of supplements spraying and a detection percentage of infected plants. They also revealed a decrease in the percentage of supplements spraying by 46.89, 52.94, 63.07 and 76% with different forward speeds compared to the traditional method.

Although the majority of trends confirm the design aspects of the performance, functional and aesthetic design of the product. However, the attention was more focused on the nature of the plastic for those results, it is through the appearance of formal and guaranteed career such as designing Achieved adopt us the extent of the impact Relations Association between the elements and principles of design to achieve complementarity in the completed design of aesthetic and functional significance expressive and symbolic and in doing so has introduced a lot of new concepts for the arrangement and organization, coordination and functional classification of the unfinished design gave way to show diversity trends in the design of industrial produ

This Study is conducted to evaluate effects of (leaves, fruits) powder and (oil, alcohol) extract of Coriander (Coriandrum sativum) plant on some biological and physiological aspects of House fly, Musca domestica at laboratory conditions. Result show that these preparations caused biological effects represented in high dead percentage in second instar, fed on different concentrations of food treated with them reached to 27.6, 55.3 at concentration 20% of leaf and fruit powder respectively and 67.3, 77.2% at 10% of oil and alcohol extract of fruit, respectively. Furthermore, study also show reduction in pupation and adults emergence percentage. However, leafs powder had slighter effect than powder and extract of fruit of tested plant. The st

The aim of this study to investigate the tongue morphology and histology in house gecko Hemidactylus flaviviridis using light and scanning electron –microscopy (SEM ) technique.The morphology result revealed the presence of three parts : apex , body and lingual root .The light microscopy result showed that the tongue is covered with mucous membrane composed of non keratinized stratified squamous epithelium based on lamina propria which contain bundles of striated muscles its fibers in different directions including connective tissue , blood vessels and nerves. The lingual mucosa of the dorsal surface is covered with different pattern of lingual papillae which are widely distributed all over the dorsal surface except the apex. Noticed on t

Challenges facing the transition of traditional cities to smart: Studying the challenges faced by the transition of a traditional area such as Al-Kadhimiya city center to the smart style

The field of Optical Character Recognition (OCR) is the process of converting an image of text into a machine-readable text format. The classification of Arabic manuscripts in general is part of this field. In recent years, the processing of Arabian image databases by deep learning architectures has experienced a remarkable development. However, this remains insufficient to satisfy the enormous wealth of Arabic manuscripts. In this research, a deep learning architecture is used to address the issue of classifying Arabic letters written by hand. The method based on a convolutional neural network (CNN) architecture as a self-extractor and classifier. Considering the nature of the dataset images (binary images), the contours of the alphabet