In light of the intellectual and technological progress within the current developments of time, as well as the emergence of digital tools and means of display and communication, which had a major role in the shifts of the time of globalization in various commercial and economic fields, as well as areas of transferring the design image and its stages of development to customers and the convergence of views between the customer and the interior designer, which are the most important pillars of the design process As a whole, and accordingly, there is an urgent need for a process of intellectual balance between them through digital tools from the technical side and through social media from the intellectual side. Customer comments via socia

Abstract
Disturbs the social system in any society specially in Iraq other than
other Islamic and Arabic countries. That is according to the abnormal
conditions that Iraq has past through as wars and blockage, and lastly the
invasion. Therefore it has been necessary to put this phenomenon under
study and analysis to discover Juvenile Delinquency is one of the most
prominent social phenomenon that the important reasons behind it, and trying
to treat what can be treated of the effects of it upon society.
This study is mainly concerned with the explaining the social factors
leading toward juvenile delinquency trying to crystallize the problem of the
study in the following question: (What are the psychological,

BACKGROUND: Mental health problems are reflected and linked to human behavior in many aspects. Medical students are susceptible to a wide variety of events that compromise their mental well-being, social life as well as their academic achievements. AIM: This study aimed to find the impact of social support on medical students’ behavior in Iraq via assessing their depression, anxiety, and stress status. METHODS: A cross-sectional online survey-based study targeted all medical students in Iraq. The employed questionnaires covered mental health status of participants by evaluating their perceptions of depression, anxiety, and stress using. Data were analyzed using the Statistical Analysis System. RESULTS: The study revealed a signifi

اهمية البحث والحاجة اليه:

       تكتسب الدراسات الخاصة بالتعليم العالي ، اهمية حيوية من حيث كونها تتطرق الى محور مهم من محاور العلم والثقافة في المجتمع الذي يحدد اتجاه ومدى حركة التقدم الاقتصادي والاجتماعي  والعلمي فيه ، فضلا عن كونه تعبيرا مباشرا عن آمال وطموحات المجتمع  وتوفير ماتحتاجه عملية البناء والتقدم والتطور في جميع مجالات الحياة وفي جميع التخصصات0

Lung cancer is one of the most serious and prevalent diseases, causing many deaths each year. Though CT scan images are mostly used in the diagnosis of cancer, the assessment of scans is an error-prone and time-consuming task. Machine learning and AI-based models can identify and classify types of lung cancer quite accurately, which helps in the early-stage detection of lung cancer that can increase the survival rate. In this paper, Convolutional Neural Network is used to classify Adenocarcinoma, squamous cell carcinoma and normal case CT scan images from the Chest CT Scan Images Dataset using different combinations of hidden layers and parameters in CNN models. The proposed model was trained on 1000 CT Scan Images of cancerous and non-c

Steganography is a technique of concealing secret data within other quotidian files of the same or different types. Hiding data has been essential to digital information security. This work aims to design a stego method that can effectively hide a message inside the images of the video file.  In this work, a video steganography model has been proposed through training a model to hiding video (or images) within another video using convolutional neural networks (CNN). By using a CNN in this approach, two main goals can be achieved for any steganographic methods which are, increasing security (hardness to observed and broken by used steganalysis program), this was achieved in this work as the weights and architecture are randomized. Thus,

Cutting forces are important factors for determining machine serviceability and product quality. Factors such as speed feed, depth of cut and tool noise radius affect on surface roughness and cutting forces in turning operation. The artificial neural network model was used to predict cutting forces with related to inputs including cutting speed (m/min), feed rate (mm/rev), depth of cut (mm) and work piece hardness (Map). The outputs of the ANN model are the machined cutting force parameters, the neural network showed that all (outputs) of all components of the processing force cutting force FT (N), feed force FA (N) and radial force FR (N) perfect accordance with the experimental data. Twenty-five samp

A content-based image retrieval (CBIR) is a technique used to retrieve images from an image database. However, the CBIR process suffers from less accuracy to retrieve images from an extensive image database and ensure the privacy of images. This paper aims to address the issues of accuracy utilizing deep learning techniques as the CNN method. Also, it provides the necessary privacy for images using fully homomorphic encryption methods by Cheon, Kim, Kim, and Song (CKKS). To achieve these aims, a system has been proposed, namely RCNN_CKKS, that includes two parts. The first part (offline processing) extracts automated high-level features based on a flatting layer in a convolutional neural network (CNN) and then stores these features in a

Solar energy is one of the immeasurable renewable energy in power generation for a green, clean and healthier environment. The silicon-layer solar panels absorb sun energy and converts it into electricity by off-grid inverter. Electricity is transferred either from this inverter or from transformer, consumed by consumption unit(s) available for residential or economic purposes. The artificial neural network is the foundation of artificial intelligence and solves many complex problems which are difficult by statistical methods or by humans. In view of this, the purpose of this work is to assess the performance of the Solar - Transformer - Consumption (STC) system. The system may be in complete breakdown situation due to failure of both so

In this paper we present a method to analyze five types with fifteen wavelet families for eighteen different EMG signals. A comparison study is also given to show performance of various families after modifying the results with back propagation Neural Network. This is actually will help the researchers with the first step of EMG analysis. Huge sets of results (more than 100 sets) are proposed and then classified to be discussed and reach the final.