ABSTRACT
Education is a valuable aspect of society, but COVID-19 made a drastic impact on the education system. It necessitated a flexible approach among institutions, Teachers, and students. For managing education effectively, institutions have initiated to apply electronic mode in the education system and comparable features are available on many platforms. It is argued that students are not aware of such platforms and they also pass from Fear, Anxiety, and control addiction. Further, Focus upon Training of Teachers with the articulation of particular Curriculum is necessitated and also course has not designed in a different language to increase their reach and more opportunities for the youth of rural India. Low Internet interpretation demands much investment for making sufficient digital infrastructure and there are certain societal barriers to online education. Still, faith in private players’ investment in education is not supported due to their profit-oriented nature. Present chapters attract the adoption of online education to respond to the recent pandemics, particularly in Higher Education in India. For this purpose, some factors of digitalization that are in use in Indian Universities try to evaluate based on static analysis of Factors Awareness, Anxiety, Network Issues, Problems of students are facing not having required technology along with language barriers. On the other hand Training of Teachers, and the process of online education at Indian University. The present chapter attracts, how managing Education in pandemic based on an empirical study regarding paramount factors of higher education in the Indian Universities. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
ABSTRACT
This paper is prepared to identify the influence of the Internet of things and its aspects in digital marketing during the COVID-19 pandemic. The research examines the various aspects of digital marketing before and after the pandemic. The paper also evaluates the tools of IoT for digital marketing. The COVID-19 pandemic has inevitably resulted in digital technologies due to social distancing customs and nationwide lockdowns. It has been found that the COVID-19 outbreak has had an impact on marketing in general and digital marketing in particular. IoT and digital technologies have become essential enablers of connectivity, allowing people to maintain their everyday lives while connecting in digital ways to which they have never been connected before. In this research, the investigator uses secondary data to obtain reliable results. This research methodology employs a descriptive qualitative approach to analyze diverse digital marketing and IoT. In addition, this study proposes a more straightforward method for predicting customer tastes and preferences on digital platforms. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
ABSTRACT
The automotive sector is one of the top energy consumers globally compared with any other sector where oil plays the main role. According to statista. corn (an online platform that displays the stats on oil consumption and reserves), in 2016, the demand for crude oil was about 85.3 million barrels per day worldwide. In 2019, the demand almost reached 100 barrels per day, and then it was reduced to 91 million per day during the 2020 global COVID-19 crisis. However, it was predicted that the global crude oil requirements will exceed 100 million barrels per day by 2023 and will continue to raise. Also, geographically, not all countries worldwide have the oil reservoirs or the technology to extract oil from the reservoirs. Although the oil demand worldwide is increasing every year, researchers have estimated that there are only 47 years of oil left on the planet earth if the current oil consumption will raise this way. Researchers are looking for finding alternative fuels, such as electrochemical energy (electric vehicles), biodiesel, electricity, ethanol, hydrogen, natural gas, propane, emerging fuels, or the use of such fuels in the existing engines to minimize the use of nonrenewable energy resources. However, researchers are also looking more at fuels based on hybrid nanoparticles added to emulsified fuels. Due to the limitations of utilizing electrochemical energy or biofuels include high charging time, limited millage, harmful exhaust emissions, complicated production process, engine efficiency, the cost of fuel, and the advantages over hybrid nanoparticles added emulsified fuels than biofuels. Hence, after going through numerous researches, in this present experimentation, "hybrid nanoparticles (MgO and Al2O3) added water-in-diesel emulsion" are formulated to enhance the quality of emission and improve the performance of the compression ignition engine. The best combination of diesel, MgO, and Al2O3, a water-in-diesel (W/D) emulsion blend, is proposed. The results were further validated using deep neural network-based spotted hyena optimization (DNN-SHO) prediction and compared with traditional machine learning approaches artificial neural network (ANN), convolution neural network (CNN), regression-based network (RBN), recurrent neural network (RNN), and DNN. As a result, the best proportions of the proposed nanoparticles added into the W/D bend are identified to be 10% W/D, 50 ppm of MgO, and 50 ppm of Al2O in terms of engine performance and emission characteristics brake thermal efficiency 30.7%, brake-specific fuel consumption 0.29 kg/kW-h, CO 0.027 vol%, NOx 855 ppm vol, and HC 12 ppm vol. Besides this, the DNN-SHO-based validated outcomes are in good agreement with the experimental values and out-performed other traditional approaches ANN, CNN, RBN, RNN, and DNN used in this study.