The economic units always sought to maintain its market position and Trchinh the technology management and modern methods that will support success factors .vdila about it has become a customer and one profitability analysis of the most practical way benefit of economic units as modern management focus their attention on achieving this satisfaction, as the customers make up the axis of the success of every organization and that there are many government units aiming to profit directs attention to customers and the number of these units increased continuously. The administration used the customer profitability analysis in order to obtain information to assist in making and decision-making process. How to use modern tec

Abstract

Objective / Purpose: Online social relationships through the emergence of Web 2.0 applications have become a new trend for researchers to study the behavior of consumers to shop online, as well as social networking sites are technologies that opened up opportunities for new business models. Therefore, a new trend has emerged, called social trade technology. In order to understand the behavioral intentions of the beneficiaries to adopt the technology of social trade, the current research aims at developing an electronic readiness framework and UTAUT model to understand the beneficiary's adoption of social trade technology.

Design/ methodology/ Approach: To achieve the obje

The facilities layout are among the most important of the most influential factors in the efficiency of the production system, and represents the systematic layout of the various work centers, tools, persons, and other auxiliary services within the factory. Careful selection of the technique that would be used in Re-layout, represents an important step in reaching to the optimum layout that keeps on reducing handling costs and reduce unnecessary movement of materials, as well as the regularity and functioning of the flow of materials through the facilities. The research aims to propose a new layout of (Al-M'ammon Factory / The General Company for Vegetable Oils Industry), and then re-layout according to the new propose layout by using of te

This research includes an analytical and critique study for the version of the University Service Law No.23 for the year 2008, containing all its aspects and failure whether in its legislation or its applications.

يهدف البحث إلى تحضير سلسلة من معقدات العناصر الانتقالية ثنائية التكافؤ(المنغنيز, الكوبلت, النيكل, الخارصين ‏والكادميوم) مع المركب الجديد(‏KL‏) والمشتق من تفاعل ثنائي كبريتيد الكاربون و المركب الوسطي (‏HD‏). شخصت ‏المعقدات ذات الصيغة العامة[‏M(L)2‎‏] بواسطة طيف الرنين النووي المغناطيسي البروتوني والكربوني للمركب الجديد ‏وقياسات الأشعة تحت الحمراء والطيف الإلكتروني ودرجات الانصهار و التوصيلية المولارية و ت

Porosity plays an essential role in petroleum engineering. It controls fluid storage in aquifers, connectivity of the pore structure control fluid flow through reservoir formations. To quantify the relationships between porosity, storage, transport and rock properties, however, the pore structure must be measured and quantitatively described. Porosity estimation of digital image utilizing image processing essential for the reservoir rock analysis since the sample 2D porosity briefly described. The regular procedure utilizes the binarization process, which uses the pixel value threshold to convert the color and grayscale images to binary images. The idea is to accommodate the blue regions entirely with pores and transform it to white in r

Today’s modern medical imaging research faces the challenge of detecting brain tumor through Magnetic Resonance Images (MRI). Normally, to produce images of soft tissue of human body, MRI images are used by experts. It is used for analysis of human organs to replace surgery. For brain tumor detection, image segmentation is required. For this purpose, the brain is partitioned into two distinct regions. This is considered to be one of the most important but difficult part of the process of detecting brain tumor. Hence, it is highly necessary that segmentation of the MRI images must be done accurately before asking the computer to do the exact diagnosis. Earlier, a variety of algorithms were developed for segmentation of MRI images by usin

Deepfake is a type of artificial intelligence used to create convincing images, audio, and video hoaxes and it concerns celebrities and everyone because they are easy to manufacture. Deepfake are hard to recognize by people and current approaches, especially high-quality ones. As a defense against Deepfake techniques, various methods to detect Deepfake in images have been suggested. Most of them had limitations, like only working with one face in an image. The face has to be facing forward, with both eyes and the mouth open, depending on what part of the face they worked on. Other than that, a few focus on the impact of pre-processing steps on the detection accuracy of the models. This paper introduces a framework design focused on this asp

In this paper, a simple fast lossless image compression method is introduced for compressing medical images, it is based on integrates multiresolution coding along with polynomial approximation of linear based to decompose image signal followed by efficient coding. The test results indicate that the suggested method can lead to promising performance due to flexibility in overcoming the limitations or restrictions of the model order length and extra overhead information required compared to traditional predictive coding techniques.

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class