FCML-gait: fog computing and machine learning inspired human identity and gender recognition using gait sequences.

Security threats are always there if the human intruders are not identified and recognized well in time in highly security-sensitive environments like the military, airports, parliament houses, and banks. Fog computing and machine learning algorithms on Gait sequences can prove to be better for restricting intruders promptly. Gait recognition provides the ability to observe an individual unobtrusively, without any direct cooperation or interaction from the people, making it very attractive than other biometric recognition techniques. In this paper, a Fog Computing and Machine Learning Inspired Human Identity and Gender Recognition using Gait Sequences (FCML-Gait) are proposed. Internet of things (IoT) devices and video capturing sensors are used to acquire data. Frames are clustered using the affinity propagation (AP) clustering technique into several clusters, and cluster-based averaged gait image(C-AGI) feature is determined for each cluster. For training and testing of datasets, sparse reconstruction-based metric learning (SRML) and Speeded Up Robust Features (SURF) with support vector machine (SVM) are applied on benchmark gait database ADSC-AWD having 80 subjects of 20 different individuals in the Fog Layer to improve the processing. The performance metrics, for instance, accuracy, precision, recall, F-measure, C-time, and R-time have been measured, and a comparative evaluation of the projected method with the existing SRML technique has been provided in which the proposed FCML-Gait outperforms and attains the highest accuracy of 95.49%.

Indian government initiatives on cyberbullying: A case study on cyberbullying in Indian higher education institutions.

In the digitally empowered society, increased internet utilization leads to potential harm to the youth through cyberbullying on various social networking platforms. The cyberbullying stats keep on rising each year, leading to detrimental consequences. In response to this online threat, the Indian Government launched different helplines, especially for the children and women who need assistance, various complaint boxes, cyber cells, and made strict legal provisions to curb online offenses. This research evaluates the relevant initiatives. Additionally, a survey is conducted to get insights into cyberbullying in higher education institutions, discussing multiple factors responsible for youth and adolescents being cyberbullied and a few measures to combat it in universities/colleges.

Artificial intelligence inspired multilanguage framework for note-taking and qualitative content-based analysis of lectures.

With the advent of technology and digitization, the use of Information and Communication Technology (ICT) and its tools for the imperative dissemination of information to learners are gaining more ground. During the process of the conveyance of lectures, it is mostly observed that students (learners) are supposed to take notes (minutes) of the subject matter being delivered to them. The existence of different factors like disturbance (noise) from the environment, learner's lack of interest, problems with the tutor's voice, and pronunciation, or others, may hinder the practice of preparing (or taking) lecture notes effectively. To tackle such an issue, we propose an artificial intelligence-inspired multilanguage framework for the generation of the lecture script (of complete) and minutes (only important contents) of the lecture (or speech). We also aimed to perform a qualitative content-based analysis of the lecture's content. Furthermore, we have validated the performance(accuracy) of the proposed framework with that of the manual note-taking method. The proposed framework outperforms its counterpart in terms of note-taking and performing the qualitative content-based analysis. In particular, this framework will assist the tutors in getting insights into their lecture delivery methods and materials. It will also help them improvise to a better approach in the future. The students will be benefited from the outcomes as they do not have to invest valuable time in note-taking/preparation.

Sustainable Development Goal for Quality Education (SDG 4): A study on SDG 4 to extract the pattern of association among the indicators of SDG 4 employing a genetic algorithm.

Sustainable Development Goals (SDG) are at the forefront of government initiatives across the world. The SDGs are primarily concerned with promoting sustainable growth via ensuring wellbeing, economic growth, environmental legislation, and academic advancement. One of the most prominent goals of the SDG is to provide learners with high-quality education (SDG 4). This paper aims to look at the perspectives of the Sustainable Development Goals improvised to provide quality education. We also analyze the existing state of multiple initiatives implemented by the Indian government in the pathway to achieving objectives of quality education (SDG 4). Additionally, a case study is considered for understanding the association among the observed indicators of SDG4. For this purpose, exploratory data analysis, and numerical association rule mining in combination with QuantMiner genetic algorithm approaches have been applied. The outcomes reveal the presence of a significant degree of association among these parameters pointing out the fact that understanding the impact of one (or more) indicator on other related indicators is critical for achieving SDG 4 goals (or factors). These findings will assist governing bodies in taking preventive measures while modifying existing policies and ensuring the effective enactment of SDG 4 goals, which also will subsequently aid in the resolution of issues related to other SDGs.

Indian government E-learning initiatives in response to COVID-19 crisis: A case study on online learning in Indian higher education system.

Recently, the whole world has faced the deadliest and dangerous consequences due to the transmission of infectious novel coronavirus (nCov). With the outbreak of COVID-19, the education learners, practitioners, and other stakeholders were at the sake of a loss, as it causes the suspension of physical classes and physical interaction of the learners. In these circumstances, Electronic learning (E-learning), Online learning, and the use of Information and Communications Technology (ICT) tools came in handy. It helped the learners in the dissemination of ideas, conducting online classes, making online discussion forums, and taking online examinations. Like the government of each country, the Indian government was also caught off-guard but the existing E-learning infrastructure was able to leverage on while devising plans to tailor them to new situations and launching new ones. The initiatives at the forefront of this noble battle launched by the Department of School Education and Literacy, Ministry of Human Resources Development (MHRD) includes Diksha, Swayam Prabha Channel, Shiksha Van, E-Pathshala, and National Repository of Open Educational Resources (NROER). It worth noting that apart from the Indian central government efforts, each state has various online education initiatives that are tailored to their needs. This research evaluated each of these initiatives commenced by central and state governments and present a detailed analysis of most of the relevant initiatives. Additionally, a survey is conducted to get insights of learners in concern to online learning. Despite the issues raised in this learning, the outcomes come to be satisfactorily favoring online learning.