Abu Zitar, Raed
A Novel Deep Learning Technique for Detecting Emotional Impact in Online Education
2022, Abu Zitar, Raed, AlZu’bi, Shadi, Hawashin, Bilal, Abu Shanab, Samia, Zraiqat, Amjed, Mughaid, Ala, Almotairi, Khaled H., Abualigah, Laith
Emotional intelligence is the automatic detection of human emotions using various intelligent methods. Several studies have been conducted on emotional intelligence, and only a few have been adopted in education. Detecting student emotions can significantly increase productivity and improve the education process. This paper proposes a new deep learning method to detect student emotions. The main aim of this paper is to map the relationship between teaching practices and student learning based on emotional impact. Facial recognition algorithms extract helpful information from online platforms as image classification techniques are applied to detect the emotions of student and/or teacher faces. As part of this work, two deep learning models are compared according to their performance. Promising results are achieved using both techniques, as presented in the Experimental Results Section. For validation of the proposed system, an online course with students is used; the findings suggest that this technique operates well. Based on emotional analysis, several deep learning techniques are applied to train and test the emotion classification process. Transfer learning for a pre-trained deep neural network is used as well to increase the accuracy of the emotion classification stage. The obtained results show that the performance of the proposed method is promising using both techniques, as presented in the Experimental Results Section.
Design Research Insights on Text Mining Analysis: Establishing the Most Used and Trends in Keywords of Design Research Journals
2022, Zitar, Raed, Nusir, Muneer, Louati, Ali, Louati, Hassen, Tariq, Usman, Abualigah, Laith, Gandomi, Amir H
Design research topics attract exponentially more attention and consideration among researchers. This study is the first research article that endeavors to analyze selected design research publications using an advanced approach called “text mining”. This approach speculates its results depending on the existence of a research term (i.e., keywords), which can be more robust than other methods/approaches that rely on contextual data or authors’ perspectives. The main aim of this research paper is to expand knowledge and familiarity with design research and explore future research directions by addressing the gaps in the literature; relying on the literature review, it can be stated that the research area in the design domain still not built-up a theory, which can unify the field. In general, text mining with these features allows increased validity and generalization as compared to other approaches in the literature. We used a text mining technique to collect data and analyzed 3553 articles collected in 10 journals using 17,487 keywords. New topics were investigated in the domain of design concepts, which included attracting researchers, practitioners, and journal editorial boards. Such issues as co-innovation, ethical design, social practice design, conceptual thinking, collaborative design, creativity, and generative methods and tools were subject to additional research. On the other hand, researchers pursued topics such as collaborative design, human-centered design, interdisciplinary design, design education, participatory design, design practice, collaborative design, design development, collaboration, design theories, design administration, and service/product design areas. The key categories investigated and reported in this paper helped in determining what fields are flourishing and what fields are eroding.
Recent Advances in Harris Hawks Optimization: A Comparative Study and Applications
2022, Zitar, Raed, Hussie, Abdelazim, Abualig, Laith, Hashim, Fatma, Amin, Mohamed, Saber, Abeer, Almotair, Khaled, Gandomi, Am
The Harris hawk optimizer is a recent population-based metaheuristics algorithm that simulates the hunting behavior of hawks. This swarm-based optimizer performs the optimization procedure using a novel way of exploration and exploitation and the multiphases of search. In this review research, we focused on the applications and developments of the recent well-established robust optimizer Harris hawk optimizer (HHO) as one of the most popular swarm-based techniques of 2020. Moreover, several experiments were carried out to prove the powerfulness and effectivness of HHO compared with nine other state-of-art algorithms using Congress on Evolutionary Computation (CEC2005) and CEC2017. The literature review paper includes deep insight about possible future directions and possible ideas worth investigations regarding the new variants of the HHO algorithm and its widespread applications.