The problem of the tagged research (experimentation in the works of the artist Muhammad al-Kinani is an analytical study) dealt with the nature of the concept of experimentation and its work in the works of Muhammad al-Kinani. Which adopts the removal of the concept of style and artistic style and takes the experience away from the pattern of repetition The importance of the research comes through the identification of the materials founding the artistic work. The current research benefits the specialists in the field of arts from the students of studies with a new and renewed formulation of creativity. The research objectives shed light on the contemporary experiences of the artist Muhammad Al-Kinani and its importance in benefiting res

The interest in art for young ages is seen as an obvious breakthrough and as revealing of psychological and health feelings in addition to emotions, and it is a treatment for those who suffer from behavioral disorders. The problem arose with the following question: What is the role of artistic expression in diagnosing behavioral disorders for primary school pupils? The aim of the research is to detect the behavioral disorders in the artistic expression of the female students' paintings from the teachers' point of view. The descriptive analytical approach was adopted as it is the appropriate method for identifying and estimating the characteristics and features related to people, places and things, and analyzing situations or phenomena as a

Background: With the increasing demand on esthetic orthodontic appliances, discoloration of clear elastomeric chains and modules remains an issue which concerns both orthodontics and patients. This in vitro study was conducted to evaluate the effect of exposing stretched clear elastomeric chains from six different companies (Ortho Technology, Ormco, Ortho Organizer, American Orthodontics, Opal and G&H companies) to three types of dietary media (tea, coffee and turmeric). Materials and methods: A total of 960 lengths of six modules were cut from short type elastomeric chain; 160 pieces from each brand. The specimens were stretched 50%, placed on plastic boards, and incubated in water at 37°C for 1 day, 7 days, 14 days and 28 days. Once a

Addressed the problem of the research is marked (technical openness in the formation of post-modernism - Pop Art an Example) the nature of the technical expansion of the output artifacts postmodern, and the nature of the raw materials taken as components of its sensual. The search came in four sections: general framework for research and identified the research problem and the need for him. With an indication of the importance of his presence. From then select the search goal (revealed openness to hire technical material in the art of Pop Art), followed by the establishment of the three search limits (objectivity, the temporal and spatial) were then determine the terms related to the title. Then provide the theoretical framework and indi

 Represent choices Behaviorism available to the Managerial leaders one of the prerequisites to run any beginnings of a psychological or dilemmas Managerial barriers to working in the field of work has been varied these options until it had taken several kinds of which contributed to the left different impacts on the alleviation of these problems, which prompted the researcher to raising the problem of study within the framework of questionable content how to contribute to that shown by Choices Behaviorism accredited to the Managerial leaders in the management of frustration

The method of predicting the electricity load of a home using deep learning techniques is called intelligent home load prediction based on deep convolutional neural networks. This method uses convolutional neural networks to analyze data from various sources such as weather, time of day, and other factors to accurately predict the electricity load of a home. The purpose of this method is to help optimize energy usage and reduce energy costs. The article proposes a deep learning-based approach for nonpermanent residential electrical ener-gy load forecasting that employs temporal convolutional networks (TCN) to model historic load collection with timeseries traits and to study notably dynamic patterns of variants amongst attribute par

Natural gas and oil are one of the mainstays of the global economy. However, many issues surround the pipelines that transport these resources, including aging infrastructure, environmental impacts, and vulnerability to sabotage operations. Such issues can result in leakages in these pipelines, requiring significant effort to detect and pinpoint their locations. The objective of this project is to develop and implement a method for detecting oil spills caused by leaking oil pipelines using aerial images captured by a drone equipped with a Raspberry Pi 4. Using the message queuing telemetry transport Internet of Things (MQTT IoT) protocol, the acquired images and the global positioning system (GPS) coordinates of the images' acquisition are

Optimum perforation location selection is an important study to improve well production and hence in the reservoir development process, especially for unconventional high-pressure formations such as the formations under study. Reservoir geomechanics is one of the key factors to find optimal perforation location. This study aims to detect optimum perforation location by investigating the changes in geomechanical properties and wellbore stress for high-pressure formations and studying the difference in different stress type behaviors between normal and abnormal formations. The calculations are achieved by building one-dimensional mechanical earth model using the data of four deep abnormal wells located in Southern Iraqi oil fields. The magni

Metasurface polarizers are essential optical components in modern integrated optics and play a vital role in many optical applications including Quantum Key Distribution systems in quantum cryptography. However, inverse design of metasurface polarizers with high efficiency depends on the proper prediction of structural dimensions based on required optical response. Deep learning neural networks can efficiently help in the inverse design process, minimizing both time and simulation resources requirements, while better results can be achieved compared to traditional optimization methods. Hereby, utilizing the COMSOL Multiphysics Surrogate model and deep neural networks to design a metasurface grating structure with high extinction rat

This research describes a new model inspired by Mobilenetv2 that was trained on a very diverse dataset. The goal is to enable fire detection in open areas to replace physical sensor-based fire detectors and reduce false alarms of fires, to achieve the lowest losses in open areas via deep learning. A diverse fire dataset was created that combines images and videos from several sources. In addition, another self-made data set was taken from the farms of the holy shrine of Al-Hussainiya in the city of Karbala. After that, the model was trained with the collected dataset. The test accuracy of the fire dataset that was trained with the new model reached 98.87%.