The cinematic costume is a qualitative element that transcends the direct function of it. It is an active personality that can become a brand of publicity and transformative signs that dismantle the intellectual system of acts, characters and events and reconstructs them aesthetically. For this reason, the researcher identified the subject of his research with the following address: (cinematic costumes between the function of publicity and Semiotics Significance). The researcher divided the research into the following: The methodological framework. The theoretical framework: The researcher divided it into three topics: the first topic: publicity. Function and concept. The second topic: fashion text and significance. Th

The influence of silver doped n-type polycrystalline CdTe film with thickness of 200 nm and rate deposition of 0.3 nm.s -1 prepared under high vacuum using thermal co-evaporation technique on its some structural and electrical properties was reported. The X- ray analysis showed that all samples are polycrystalline and have the cubic zinc blend structure with preferential orientation in the [111] direction. Films doping with impurity percentages (2, 3, and 4) %Ag lead to a significant increase in the carrier concentration, so it is found to change from 23.493 108 cm -3 to 59.297 108 cm -3 for pure and doped CdTe thin films with 4%Ag respectively. But films doping with impurity percentages above lead to a significant decrease in the electrica

The present research aims at identifying the educational problems and psychological problems of distinguished students at the intermediate level. The research sample consists of (246) students who are randomly selected from four distinguished schools (2) in the Karkh\1 and (2) in the Rusafa\2.

The researcher has constructed two scales for measuring the educational and psychological problems. She ensures the psychometric characteristics of the two scales. Alph-Cronbach and test-retest methodsare used to ensure reliability. Some statistical treatments are used to find out the aims of research. These treatments include the one-sample T-test, two independent samples T-test, and the Pearson correlation coefficient. The results show th

Arabian Political Regimes: Problems of Policies and Rule; An Introduction to Interpreting (The Arabian Spring) The Arab Region witnessed, since 2011, critical changes overthrew a group of Arab regimes in some of its countries, and the reaction of these changes are still going on up to now. These changes were given lots of justifications and interpretations. The current study tries to concentrate on the most important problems which were due to what was known as (The Arab Spring). The study proposes that the crisis which the countries of the area are exposed to is not spontaneous in many of its aspects. It is totally a crisis of rule and policies. Because it is a reflection of the nature of authority in the Arabian regimes on the one hand

Obtaining the computational models for the functioning of the brain gives us a chance to understand the brain functionality thoroughly. This would help the development of better treatments for neurological illnesses and disorders. We created a cortical model using Python language using the Brian simulator. The Brian simulator is specialized in simulating the neuronal connections and synaptic interconnections. The dynamic connection model has multiple parameters in order to ensure an accurate simulation (Bowman, 2016). We concentrated on the connection weights and studied their effect on the interactivity and connectivity of the cortical neurons in the same cortical layer and across multiple layers. As synchronization helps us to mea

Optical spectrum of SN1987A at days 4 from the explosion and its light curve through the first 1444 days after the explosion have been studied. The hydrogen lines present in the spectrum confirms the general characteristics of Type II SN that occur due to core collapse of massive star. Each of the total mass ejected from the explosion and the amount of the total mass of Nickel radioactive isotopes that produced during the explosion as well as the initial velocity of the ejecta and the explosion energy have been determined and compared with different observed and calculated models obtained by different researchers and it’s found that, about 8.8 Mʘ of the progenitor envelope mass had been ejected during the explosion and it’s mixed with

Smart systems are the trend for modern organizations and should meet the quality of services that expect to produce. Internet of Everything (IoE) helped smart systems to adopt microcontrollers for improving the performance. Analyzing and controlling data in such a system are critical issues. In this study, a survey of IoE systems conducted to show how to apply a suitable model that meets such system requirements. The analysis of some microcontroller boards is explored based on known features. Factors for applying IoE devices have been defined such as connectivity, power consumption, compatibility, and cost. Different methods have been explained as an overview of applying IoE systems. Further, different approaches for applying IoE technology

MWCNTs and hybrid nanocomposite ZnO/Se/MWCNTs have been prepared via Solvothermal technique using Parr reactor at the temperature 180°C and SeCl2 as a catalyst. The obtained MWCNTs and ZnO/Se/MWCNTs are investigated using the FE-SEM, XRD, UV-VIS Spectroscopy and Z-Scan. The novelty of this research is studying the nonlinear optical properties for these prepared materials and the results exhibit that the thickness of the deposited film for hybrid nanocomposite ZnO/Se/MWCNTs is increased, which in turn, increase the nonlinear phase shift of the laser beam compared with the MWCNTs.

     Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod

Classifying an overlapping object is one of the main challenges faced by researchers who work in object detection and recognition. Most of the available algorithms that have been developed are only able to classify or recognize objects which are either individually separated from each other or a single object in a scene(s), but not overlapping kitchen utensil objects. In this project, Faster R-CNN and YOLOv5 algorithms were proposed to detect and classify an overlapping object in a kitchen area.  The YOLOv5 and Faster R-CNN were applied to overlapping objects where the filter or kernel that are expected to be able to separate the overlapping object in the dedicated layer of applying models. A kitchen utensil benchmark image database and