AREL – Augmented Reality–based enriched learning experience

In present era, teaching occur either on a chalkboard or on a projected power point presentation on the wall. Traditional teaching methods such as blackboards and power point presentations are being phased out in favor of enriched learning experiences provided by emerging edtech. With the closure of schools due to COVID-19, the demand for online educational platforms has also increased. Furthermore, some of the recent trends in edtech include personalized learning, gamification and immersive learning with eXtended Reality (XR) technologies. Due to its immersive experience, XR is a pioneering technology in education, with multiple benefits including greater motivation, a positive attitude toward learning, concrete learning of concepts, and so on. Existing Augmented Reality (AR) based education applications often rely on unimodal input such as marker-based trigger to launch the educational content. Hence, this work proposes a multi-modal interface to enable the content delivery through marker and speech recognition-based content delivery. Additionally, the proposed work is designed as mobile based AR platform with the regional language support to increase the ubiquitous accessibility of the AR content. Thus, the proposed mobile AR based enriched learning (AREL) platform provides a multi-modal mobile based educational AR platform for primary students. Based on the feedback received after the usage, it is observed that AREL improves the learning experience of the students. © 2022 International Measurement Confederation (IMEKO). All rights reserved.

Knowledge Retrieval using Question Answering approach on Epidemiology data

The tried and tested way for effective Knowledge Retrieval is by posting questions and retrieving data from the huge information repository. In the recent past the prevalence of pandemics and the spread of COVID-19, has led people to rigorously question the various forms of epidemiology data available on different sources. In general, the amount of information gathered is proportionate to the questioning patterns by the knowledge seeker. Question answering (QA) system is useful during unexpected situations, especially during a pandemic. In this paper, we have proposed a Knowledge Retrieval Question Answering system (KRQA) for answering the queries of users related to COVID-19. The KRQA system is divided into two modules. The first module consists of preprocessing (tokenization, stemming, bag of words) of the question to produce a word vector. The second module involves building, training, and testing the data repository. Feedforward neural network is used to extract the most relevant answer from a repository of all possible answers. The volume and quality of information about the pandemic scenario around the world are increased at a tremendous rate. Hence our work focuses on effective knowledge retrieval using question and answering approach. Our experimental results are found to give better results based on Percentage closeness, precision, and recall parameters. KRQA has the novelty of retrieving more relevant answers with good quality. © 2022 IEEE.

Face Mask Monitoring for Educational Institutions and Organizations

In the year 2020, we had seen a disastrous effect on the society by the outbreak of coronavirus which has demanded the world to mandatorily wear a mask. Therefore, one major protection for people is to wear mask in public areas. Thus, we proposed a face mask monitoring system, which uses convolution neural networks to train the model, Caffe-based DL detector with MobileNetV2 architecture to extract the facial features for mask detection and allowing our monitoring application to be deployed on any embedded system easily. The main objective of this paper is to automate face mask monitoring so that it reduces time and human effort administered in this process and, thus, helps in controlling the spread of virus. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Safety and efficacy of a Siddha Medicine fixed regimen for the treatment of asymptomatic and mild COVID-19 patients.

Background: The Coronavirus disease 2019 (COVID-19) pandemic caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is a massive threat to public health worldwide. Siddha system of medicine is one of the traditional medicines of South India. The recommended formulations in Siddha Sasthric Medicines- Fixed Regimen (SSM-FiRe) are Amukkura tablets, Kaba Sura Kudineer (KSK) for asymptomatic COVID-19 positive (RT-PCR) patients, and Athimathuram tablets, Adathodai Manappagu syrup, Thippili Rasayanam, Brahmananda Bairavam tablet, and Notchi Kudineer for mild symptomatic patients. The core objective of the trial was to document the efficacy of SSM-FiRe in the prevention of asymptomatic and mild COVID-19 disease progression to the next level of severity, reduce the severity of symptoms and revert to RT-PCR Negative. Methods: An exploratory, prospective, open-labeled, single-arm, non-randomized trial was designed as per GCP guidelines to assess the efficacy of SSM-FiRe. Sixty RT-PCR positive participants who were asymptomatic or with mild COVID-19 symptoms were recruited for the study at the Siddha COVID Care Centre, Vyasarpadi, Chennai from June to August 2020. Nasal and oropharyngeal swab tests were performed on the 0, 7th, and 14th days. All participants were treated with SSM - FiRe regimen. All the participants were also assessed based on Siddha Yakkkaiyin Ilakkanam, which included Clinical symptoms and vitals. Laboratory investigations such as Haemogram, Liver Function Test, Renal Function Test, HbA1C, Electrolytes, Inflammatory markers, Cardiac profile, Immunoglobulins, and anti-SARS-CoV-2 antibody tests were performed. Results: 83% of COVID-19 patients turned RT-PCR negative on the 7th day and in most of the cases, symptoms were reduced within the first 5 days of admission. The RT-PCR cycle threshold (ct) value increased significantly (<0.001) after treatment and all the participants were RT-PCR negative, except one, who was positive even after 14 days. Anti-SARS-CoV-2 antibodies developed significantly (p-value - 0.006). LFT, RFT, CBC, Total proteins, and electrolytes continued to be in the normal range after treatment, indicating the safety of the intervention. Conclusion: Asymptomatic and mild COVID-19 disease can be well managed by SSM - FiRe treatment, Further studies could be taken up to strengthen the findings.