The significant addition of immersive technologies, Virtual Reality (VR), Augmented Reality(AR) and Mixed Reality(MR) are transforming the domain of design education. Still, finding an equilibrium between these new tools alongside with traditional methods of teaching is a menace which educational institutes needs to solve. This paper proposes a structure that would help the ease with which to include immersive technologies within design education, keeping in mind the solid points of more conventional pedagogical methods. Based on a survey of interior design programs, this research highlights the potential for VR, AR and MR in student engagement, creativity skills and professional practices. The results suggest that adoption of an im
... Show MoreEuphemisms are advantageous in people’s social life by turning sensitive into a more acceptable ones so that resentful feelings and embarrassment can be avoided. This study investigates the ability of Iraqi English learners in using euphemistic expressions, meanwhile, raising their awareness and the faculty members in English teaching faculties regarding the relevance of discussing the topics that demand euphemisation. This study comprised three stages: initial test, explicit instruction with activities, and a final test for the students’ development in this domain. A test has been distributed among 50 respondents, who are at the fourth year of their undergraduate study at the University of Babylon/ College of Basic Education. The lo
... Show MoreMost recognition system of human facial emotions are assessed solely on accuracy, even if other performance criteria are also thought to be important in the evaluation process such as sensitivity, precision, F-measure, and G-mean. Moreover, the most common problem that must be resolved in face emotion recognition systems is the feature extraction methods, which is comparable to traditional manual feature extraction methods. This traditional method is not able to extract features efficiently. In other words, there are redundant amount of features which are considered not significant, which affect the classification performance. In this work, a new system to recognize human facial emotions from images is proposed. The HOG (Histograms of Or
... Show MoreHartha Formation is an overburdened horizon in the X-oilfield which generates a lot of Non-Productive Time (NPT) associated with drilling mud losses. This study has been conducted to investigate the loss events in this formation as well as to provide geological interpretations based on datasets from nine wells in this field of interest. The interpretation was based on different analyses including wireline logs, cuttings descriptions, image logs, and analog data. Seismic and coherency data were also used to formulate the geological interpretations and calibrate that with the loss events of the Hartha Fm.
The results revealed that the upper part of the Hartha Fm. was identified as an interval capable of creating potentia
... Show MoreRenewal is generally considered an urgent requirement of life, and a section of its continuation, because renewal means that life exists and continues, and just as renewal is in life, renewal is in science, and in this research the issue of renewal in the science of interpretation, and showed through research that renewal in This science was an urgent demand throughout the Islamic ages, as the research showed the necessity of renewal in the material of interpretation, its method and methods, and the researcher presented the opinions of schools about renewal in the interpretation of the Noble Qur’an inferred by living models that refer to their owners.
This research aims to understand complexity management and its impact on the use of the dynamic capabilities of a sample of private colleges. Private colleges are currently facing many crises, changes, unrest and high competitive pressures. Which is sometimes difficult or even impossible to predict. The recruitment of dynamic capabilities is also one of the challenges facing senior management at private colleges to help them survive and survive. Thus, the problem of research was (there is a clear insufficiency of interest in Complexity Management and trying to employ it in improving the dynamic capabilities of Colleges that have been discussed?). A group of private colleges was selected as a
... Show MoreAim: The purpose of this study was to analyze the patterns of facial fractures in children and to compare them between preschool- and school-aged children. Materials and methods: This retrospective observational study included 57 children with facial fractures. The variables analyzed were the age of the patients—divided into a preschool-aged group (0–5 years) and a school-aged group (6–12 years)—gender, cause of trauma, the facial bones involved, the pattern of fracture, the modality of treatment used, the time between injury and treatment, and the postoperative complications. Results: The incidence of facial fractures in children ≤12 years was 30.2%. The patients consisted of 40 (70.2%) males and 17 (29.8%) females, and most pati
... Show MoreVehicular Ad Hoc Networks (VANETs) are integral to Intelligent Transportation Systems (ITS), enabling real-time communication between vehicles and infrastructure to enhance traffic flow, road safety, and passenger experience. However, the open and dynamic nature of VANETs presents significant privacy and security challenges, including data eavesdropping, message manipulation, and unauthorized access. This study addresses these concerns by leveraging advancements in Fog Computing (FC), which offers lowlatency, distributed data processing near-end devices to enhance the resilience and security of VANET communications. The paper comprehensively analyzes the security frameworks for fog-enabled VANETs, introducing a novel taxonomy that c
... Show MoreData scarcity is a major challenge when training deep learning (DL) models. DL demands a large amount of data to achieve exceptional performance. Unfortunately, many applications have small or inadequate data to train DL frameworks. Usually, manual labeling is needed to provide labeled data, which typically involves human annotators with a vast background of knowledge. This annotation process is costly, time-consuming, and error-prone. Usually, every DL framework is fed by a significant amount of labeled data to automatically learn representations. Ultimately, a larger amount of data would generate a better DL model and its performance is also application dependent. This issue is the main barrier for