Online learning is not a new concept in education, but it has been used extensively since the Covid-19 pandemic and is still in use now. Every student in the world has gone through this learning process from the primary to the college levels, with both teachers and students conducting instruction online (at home). The goal of the current study is to investigate college students’ attitudes towards online learning. To accomplish the goal of the current study, a questionnaire is developed and adjusted before being administered to a sample of 155 students. Additionally, validity and reliability are attained. Some conclusions, recommendations, and suggestions are offered in the end.
In the light of what is witnessing in the advertising arena of new ways and methods in delivering advertising message to consumers by finding new outlets to communicate with them especially through social networking sites, which became the first choice of advertising companies in order to spread its goods and services. These companies now are relying gradually on celebrities to appear with their products and goods to drive the audience's attention towards them. The thesis aims to find out the attitudes of young people towards the the advertisements that show famous celebrities on social networking sites. The researcher used survey method which aims to record, analyze and interpret the phenomenon after collecting the necessa
... Show MoreThe social contract represents a set of laws and determinants agreed upon by a group of individuals in order to organize society for the better.This agreement guarantees them to live in peace according to the pre-agreed laws, and on the basis of that, it represents the key to resolving the crisis relations between the state and society, and this is what prompted Iraqi society to move towards the formulation of a new social contract through popular protest movements in 2019.To overcome the old social contract that shook the trust between the state and society as a result of its negative outputs at various political, economic and social levels, and many problems emerged that hindered the process of building the social contra
... Show MoreThe COVID-19 pandemic has profoundly affected the healthcare sector and the productivity of medical staff and doctors. This study employs machine learning to analyze the post-COVID-19 impact on the productivity of medical staff and doctors across various specialties. A cross-sectional study was conducted on 960 participants from different specialties between June 1, 2022, and April 5, 2023. The study collected demographic data, including age, gender, and socioeconomic status, as well as information on participants' sleeping habits and any COVID-19 complications they experienced. The findings indicate a significant decline in the productivity of medical staff and doctors, with an average reduction of 23% during the post-COVID-19 period. T
... Show MoreDistributed Denial of Service (DDoS) attacks on Web-based services have grown in both number and sophistication with the rise of advanced wireless technology and modern computing paradigms. Detecting these attacks in the sea of communication packets is very important. There were a lot of DDoS attacks that were directed at the network and transport layers at first. During the past few years, attackers have changed their strategies to try to get into the application layer. The application layer attacks could be more harmful and stealthier because the attack traffic and the normal traffic flows cannot be told apart. Distributed attacks are hard to fight because they can affect real computing resources as well as network bandwidth. DDoS attacks
... Show MoreAbstract
This study aims to identify the empathy of University Students, as well as the significant differences in sympathy in terms of gender and specialization. To achieve the aims of the study, a scale of empathy was administered to a sample of (450) students collected randomly from Baghdad university. The results showed that the study sample has a level of empathy. There is a significant difference between males and females in empathy, in favor of the female students. There is no significant difference in empathy in terms of specialization (scientific, humanities), and the interaction between males and females. The study came out with a number of recommendations and suggestions.
Image compression plays an important role in reducing the size and storage of data while increasing the speed of its transmission through the Internet significantly. Image compression is an important research topic for several decades and recently, with the great successes achieved by deep learning in many areas of image processing, especially image compression, and its use is increasing Gradually in the field of image compression. The deep learning neural network has also achieved great success in the field of processing and compressing various images of different sizes. In this paper, we present a structure for image compression based on the use of a Convolutional AutoEncoder (CAE) for deep learning, inspired by the diversity of human eye
... Show MoreOne study whose importance has significantly grown in recent years is lip-reading, particularly with the widespread of using deep learning techniques. Lip reading is essential for speech recognition in noisy environments or for those with hearing impairments. It refers to recognizing spoken sentences using visual information acquired from lip movements. Also, the lip area, especially for males, suffers from several problems, such as the mouth area containing the mustache and beard, which may cover the lip area. This paper proposes an automatic lip-reading system to recognize and classify short English sentences spoken by speakers using deep learning networks. The input video extracts frames and each frame is passed to the Viola-Jone
... Show MoreWith the vast usage of network services, Security became an important issue for all network types. Various techniques emerged to grant network security; among them is Network Intrusion Detection System (NIDS). Many extant NIDSs actively work against various intrusions, but there are still a number of performance issues including high false alarm rates, and numerous undetected attacks. To keep up with these attacks, some of the academic researchers turned towards machine learning (ML) techniques to create software that automatically predict intrusive and abnormal traffic, another approach is to utilize ML algorithms in enhancing Traditional NIDSs which is a more feasible solution since they are widely spread. To upgrade t
... Show More