Industry 4.0 is a current trend of automation and digitalization of industries. The impacts and importance of Industry 4.0 are reflected in all aspects of our lives. The purpose of this article is to analyze the literatures based on a scoping review method. A lack of digital culture, training, knowledge, and language are also challenges faced by Industry 4.0 while implementing its operations. Digital English and Education 4.0 are also employee competencies of Industry 4.0. The authors have reviewed the literature related to Digital English, Education 4.0, and Industry 4.0 from various resources. Astonishingly, the results show that the studies conducted in these areas are so specific focusing only one of the above-mentioned areas; no research article was identified that detailed the interconnections among these areas. From the scoping review, the study has identified the gaps in the literature. Thus, the study concludes that filling up the gaps and conducting research in these areas are useful to sort out a few of the challenges of Industry 4.0 and it recommends that in future, researchers conduct studies based on the interconnections of Digital English and Education 4.0 for Industry 4.0.

Detecting the attacks in Vehicular Ad hoc Network (VANET) system is very important to provide more secure and reliable communication between all vehicles in the system. In this article, an effective Intelligent Intrusion Detection System (IDS) is proposed using machine learning and deep learning approaches such as Adaptive Neuro Fuzzy Inference System (ANFIS) and Convolutional Neural Networks (CNN), respectively. The existing methods focus on detecting only the known attacks in VANET environment. This limitation is overcome by proposing the Intelligent IDS system using soft computing techniques. The proposed method consists of Known IDS (KIDS) and Unknown IDS (UIDS) modules, which detect both known attacks and unknown attacks. The KIDS module uses ANFIS classification module to detect the known malicious attacks, whereas the UIDS module uses a deep learning algorithm to detect the unknown attacks in VANET. Modified LeeNET (MLNET) architecture is proposed in this article to identify the type of unknown attacks. In this work, DoS attacks, Botnet attacks, PortScan attacks, and Brute Force attacks are detected using this hybrid learning algorithm. The proposed system obtains 96.9% of Pr, 98.3% of Se, 98.7% of Sp, and 98.6% of Acc and consumed 1.75 s for detecting the DoS attack on i‐VANET dataset. The proposed system obtains 98.1% of Pr, 98.9% of Se, 98.1% of Sp, and 98.1% of Acc and consumed 0.95 s for detecting the Botnet attack. The proposed system obtains 98.7% of Pr, 99.1% of Se, 98.9% of Sp, and 99.2% of Acc and consumed 1.38 s for detecting the PortScan attack. The proposed system obtains 99.1of Pr, 97.8% of Se, 98.7% of Sp, and 98.5% of Acc and consumed 1.29 s for detecting the Brute Force attack. The developed methodology is tested on the real‐time CIC‐IDS 2017 dataset, and the experimental results are compared with other state‐of‐the‐art methods.

In the present era, women-owned firms are one of India’s fastest increasing entrepreneurial communities in the form of women entrepreneurs. The objective of the study is to identify the factors that influence women’s entrepreneurial orientation and firms’ performance. The research study discusses the influencing factors and their effect on firms’ performance and satisfaction in this regard. The proposed framework and hypotheses have been tested using data gathered from boutiques, beauty parlors, carpet manufacturers, and retail shops in Karnataka, India. Data analysis was done using univariate, bivariate, and multivariate techniques. In Structural Equation Modeling (SEM), paths were created for evaluating the cause-and-effect relationship between different factors viz., social, psychological, financial, and resource factors and entrepreneurial performance and satisfaction. Seven relationships were significant, while two relationships were insignificant in this structural equation. The key finding of the paper is that all factors have a significant impact on the firm’s performance. The implications of research results for researchers and practitioners are discussed, and suggestions have also been made.

Education 4.0 is considered a significant technology for teaching and learning. The present study aims to explore the impact and the importance of Education 4.0 for improving English language learning in the perception of students in India, especially Hyderabad City. Moreover, Education 4.0 has bloomed as an important need to move along with the fast-growing education system of the world. But, it is a fact that many Indian students have complications and difficulties in learning English due to many reasons. The traditional methods of teaching are one of those reasons. Students learn only through the conventional methods, and they may find it boring and not effective. The education and mode of teaching have changed a lot, and it has attained a newer form of using the technology. Moreover, in the current era, where work from home and online teaching has become a new normal throughout the world, the technology used for teaching is inseparable. Hence, the authors are motivated to study the impact of Education 4.0 on improving English learning from Hyderabad, India. The methodology of the study has applied quantitative research. The study has employed pre-tested, close-ended questionnaires and post-assessment to gather data from the respondents to understand students’ performance in English language learning after implying Education 4.0. The five-point Likert scale has been used to analyse the collected data and to get mean values of responses. The total number of respondents is 145 students who pursue their engineering degrees in the select region. Among the collected data, most of them were from urban. The data obtained from the respondents proved that there is a direct correlation between the students’ perception and implementation of Education 4.0 in learning the English language. This study indicated that the respondents upheld Education 4.0 to improve English language learning in Hyderabad, India.

This paper focuses on the influence of ramp locations upstream of a strut-based scramjet combustor under reacting flow conditions that are numerically investigated. In contrast, a computational study is adopted using Reynolds Averaged Navier Stokes (RANS) equations with the Shear Stress Transport (SST) k-ω turbulence model. The numerical results of the Deutsches Zentrum für Luft- und Raumfahrt or German Aerospace Centre (DLR) scramjet model are validated with the reported experimental values that show compliance within the range, indicating that the adopted simulation method can be extended for other investigations as well. The performance of the ramps in the strut-based scramjet combustor is analyzed based on parameters such as wall pressures, combustion efficiency and total pressure loss at various axial locations of the combustor. From the numerical shadowgraph, more shock interactions are observed upstream of the strut injection region for the ramp cases, which decelerates the flow downstream, and additional shock reflections with less intensity are also noticed when compared with the DLR scramjet model. The shock reflection due to the ramps enhances the hydrogen distribution in the spatial direction. The ignition delay is noticed for ramp combustors due to the deceleration of flow compared to the baseline strut only scramjet combustor. However, a higher flame temperature is observed with the ramp combustor. Because more shock interactions arise from the ramps, a marginal increase in the total pressure loss is observed for ramp combustors when compared to the baseline model.

Due to globalization, business collaborations are made throughout the world. Many industries have started adopting new technologies to make their work easier. Therefore, preparing students for the future workforce is necessary. This can only be achieved only by adopting a new education system. The new education system that supports technologies is known as Education 4.0. Education 4.0, which is sustainable, is a self-based education that adopts AI for learning. Exploring many new technologies and English communication is important for anyone entering the workforce in the future. This study aims at developing Business English communication using Education 4.0. ELSA is one of the applications that supports Education 4.0. The novelty of the current study is that ELSA is used for developing Business English communication. This quantitative study employed a quasi-experimental research design, and a purposive-sampling method was used for selecting the participants. Management students from business schools were selected for this research. Ninety-nine students participated in this study. Later, a pre-test was conducted using a questionnaire. Data were collected and documented. The intervention was carried out for four weeks and adopted Education 4.0. After the intervention period, a post-test was conducted using another questionnaire to check for improvement. The pre-test and post-test data of the participants were compared and analyzed in SPSS using a paired sample t-test. The results showed that listening skills were greatly improved using Education 4.0, which is also important for enhancing other skills, and the participants benefited from using Education 4.0. Moreover, we discuss the study’s limitations, which provides opportunities to conduct future research.