The subject of marketing culture and mental image is one of the important topics in the field of management. There is no study that combines these two variables. The research is important because of the increasing importance of the subject. The future direction of the company in question will support the company's economic and marketing responsibilities. And reflect the company's mental image, as a culture that contributes to changing the reality of the organization investigated by polling the views of a sample of managers in the General Company for Vegetable Oil Industry, which (30) out of the (65) individual, and There are two hypotheses of research: There is a significant

The research seeks to identify the image of foreign oil companies operating in Iraq among the public of Basra, and the research aims to clarify the mental image of foreign oil companies among the Iraqi public, and to identify the extent to which the Iraqi public benefit from the social responsibility programs offered by foreign oil companies and their contribution to improving the standard of living and services for the population. Nearby areas and society as a whole, the research is classified within descriptive research, and the researcher used the survey method for the Iraqi public in Basra governorate, which includes the areas in which these companies are located, and he used the scale tool to find out, so he distributed 600 que

Objective: To assess the functional outcome, time to union, shoulder pain, blood loss, operative time, iatrogenic radial nerve injury, hospitalization, and infection. Methodology: It is a prospective randomized study on 30 patients with mid-shaft humerus fracture according to AO classification (1.2A1, 2, 3 and 1,2B) with functioning radial nerve. They were randomly dividing into two groups. Group A were treated by a closed antegrade interlocking nail, and group B treated by open reduction and locked compression plate fixation. The follow-up was up to 6 months, including time to union, shoulder pain, intraoperative blood loss, operative time and iatrogenic radial nerve injury. Functional outcome was assessed by quick DASH score. Resu

The study aims to demonstrate the importance of instructional methods in teaching Arabic language as a second language or teaching the Arabic language to non-native speakers. The study is in line with the tremendous development in the field of knowledge, especially in the field of technology and communication, and the emergence of many electronic media in education in general and language teaching in particular. It employs an image in teaching vocabulary and presenting the experience of the Arabic Language Institute for Non-Speakers-King Abdul-Aziz University. The study follows the descriptive approach to solve the problem represented by the lack of interest in the educational methods when teaching Arabic as a second language. Accordingl

      TV medium derives its formal shape from the technological development taking place in all scientific fields, which are creatively fused in the image of the television, which consists mainly of various visual levels and formations. But by the new decade of the second millennium, the television medium and mainly (drama) became looking for that paradigm shift in the aesthetic formal innovative fields and the advanced expressive performative fields that enable it to develop in treating what was impossible to visualize previously. In the meantime, presenting what is new and innovative in the field of unprecedented and even the familiar objective and intellectual treatments. Thus the TV medium has sought for work

In the image processing’s field and computer vision it’s important to represent the image by its information. Image information comes from the image’s features that extracted from it using feature detection/extraction techniques and features description. Features in computer vision define informative data. For human eye its perfect to extract information from raw image, but computer cannot recognize image information. This is why various feature extraction techniques have been presented and progressed rapidly. This paper presents a general overview of the feature extraction categories for image.

The issue of image captioning, which comprises automatic text generation to understand an image’s visual information, has become feasible with the developments in object recognition and image classification. Deep learning has received much interest from the scientific community and can be very useful in real-world applications. The proposed image captioning approach involves the use of Convolution Neural Network (CNN) pre-trained models combined with Long Short Term Memory (LSTM) to generate image captions. The process includes two stages. The first stage entails training the CNN-LSTM models using baseline hyper-parameters and the second stage encompasses training CNN-LSTM models by optimizing and adjusting the hyper-parameters of

Abstract

 Metal cutting processes still represent the largest class of manufacturing operations. Turning is the most commonly employed material removal process. This research focuses on analysis of the thermal field of the oblique machining process. Finite element method (FEM) software DEFORM 3D V10.2 was used together with experimental work carried out using infrared image equipment, which include both hardware and software simulations. The thermal experiments are conducted with AA6063-T6, using different tool obliquity, cutting speeds and feed rates. The results show that the temperature relatively decreased when tool obliquity increases at different cutting speeds and feed rates, also it

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