Possibilities and Challenges of Online Education in India During the COVID-19 Pandemic

The undergraduate and postgraduate studies of colleges and universities in India have been affected badly amidst the lockdowns for COVID-19 pandemic. The Government has insisted to start the academic activity through online platforms. The biggest concern for the academic institutions now is to select an appropriate e-learning platform. This paper compares different features and facilities available in some widely used online platforms and analyze their suitability from the perspective of socio-economic constraints of students in India. A generic framework for conducting online classes is described that meets the special requirements of the unprivileged students. Some strategic plans to overcome the challenges are identified and suggested. A technical solution for implementation of time-bound assessment module is also proposed.

Integrated Smart Home Model

Today, in the realm of Industry 4.0, vastly diverse Internet of Things (IoT) technology are integrated everywhere, not to mention included in academic programs in schools and universities. Domain ratio of the final year projects in Universiti Teknologi Mara exposes a staggering hype in IoT as compared to other domains despite not having IoT included in any of the courses. Meanwhile, to fulfill the needs of the student in exploring this technology, an integrated IoT learning platform is developed. It integrates an IoT smart home model and a web-based interface as a learning platform to inspire hands-on learning for the students. The raspberry pi, motion sensor, analog gas sensor, atmospheric sensor, ultrasonic proximity sensor, and rain detector sensor are integrated together in a Lego-built smart home model where its connectivity and readings are displayed in a simple web interface to enable and inspire learning. A manual to set up the entire model is also prepared as a guide for students to set up and further explore the functionalities and operabilities of “things”.

Relationship between Computer-mediated Communication Competence and Attitude toward Using Frog VLE among Secondary School Teachers

This study aims at examining the relationship between teacher computer-mediated communication (CMC) competence and teacher attitude toward using Frog VLE a virtual learning platform. This is a non-experimental research using a cross-sectional survey technique through the administration of a set of questionnaire that comprised teacher demographic variables, teacher CMC competence and teacher attitude toward using Frog VLE. The participants in this study are 351 secondary school teachers from Klang district, Selangor. The results indicated that teachers showed medium level of attitude and medium level of CMC competence toward using Frog VLE. Results showed that there is statistically significant direct causal relationship between teacher CMC competence and teacher attitude toward using Frog VLE. CMC motivation and CMC knowledge are the two direct factors of teachers’ affective and behavioural attitude toward using Frog VLE and CMC motivation predict teachers’ cognitive attitudes toward using Frog VLE.

Relationship Between Computer-Mediated Communication Competence and Attitude Toward Using Frog VLE Among Secondary School Teachers

This study aims at examining the relationship between teacher computer-mediated communication (CMC) competence and teacher attitude toward using Frog VLE a virtual learning platform. This is a non-experimental research using a cross-sectional survey technique through the administration of a set of questionnaire that comprised teacher demographic variables, teacher CMC competence and teacher attitude toward using Frog VLE. The participants in this study are 351 secondary school teachers from Klang district, Selangor. The results indicated that teachers showed medium level of attitude and medium level of CMC competence toward using Frog VLE. Results showed that there is statistically significant direct causal relationship between teacher CMC competence and teacher attitude toward using Frog VLE. CMC motivation and CMC knowledge are the two direct factors of teachers’ affective and behavioural attitude toward using Frog VLE and CMC motivation predict teachers’ cognitive attitudes toward using Frog VLE.

Academia : Web Platform for E-learning.

This paper illustrates how we can improve the existing manual system with the help of E-learning management system. The method aims to build an E-learning web application having better and safer user experience and provides an interactive teaching-learning platform for students and teachers. E-learning Management System is way of solving the educational problems using the modern technologies. It gives an error free, secure, reliable and fast management system. It can assist the user to concentrate on learning rather to concentrate on the record keeping and other stuff. It will help organization in better utilization of resources. Keywords: Web application, Database, backend, frontend, platform, E-learning, Frameworks

OrganoID: a versatile deep learning platform for organoid image analysis

Organoids are three-dimensional in vitro tissue models that closely represent the native heterogeneity, microanatomy, and functionality of an organ or diseased tissue. Analysis of organoid morphology, growth, and drug response is challenging due to the diversity in shape and size of organoids, movement through focal planes, and limited options for live-cell staining. Here, we present OrganoID, an open-source image analysis platform that automatically recognizes, labels, and tracks single organoids in brightfield and phase-contrast microscopy. The platform identifies organoid morphology pixel by pixel without the need for fluorescence or transgenic labeling and accurately analyzes a wide range of organoid types in time-lapse microscopy experiments. OrganoID uses a modified u-net neural network with minimal feature depth to encourage model generalization and allow fast execution. The network was trained on images of human pancreatic cancer organoids and was validated on images from pancreatic, lung, colon, and adenoid cystic carcinoma organoids with a mean intersection-over-union of 0.76. OrganoID measurements of organoid count and individual area concurred with manual measurements at 96% and 95% agreement respectively. Tracking accuracy remained above 89% over the duration of a four-day validation experiment. Automated single-organoid morphology analysis of a dose-response experiment identified significantly different organoid circularity after exposure to different concentrations of gemcitabine. The OrganoID platform enables straightforward, detailed, and accurate analysis of organoid images to accelerate the use of organoids as physiologically relevant models in high-throughput research.

Face to face education to virtual classroom in the health sector during covid pandemic

The lockdown posed a great impact on teaching and learning process which aided in the shift of face to face education to virtual classroom. As the e- learning was newly introduced, it was difficult to execute initially due to prior unpreparedness. We put forth this study to analyse student's perspective and challenges faced in online education during pandemic times.The study was done in medical and allied health science colleges of Chennai and Puducherry. This is cross-sectional study conducted between June and August 2020. This is an online survey conducted through google forms circulated to undergraduates and post graduates of medical and allied health science courses. Frequencies and percentages were used to express the data. Statistical Analyses were done by SPSS software and graphs were made by Microsoft excel. We received response from 419 participants. Mobile phone was the widely used gadget to access online class. Most of the institutes conducted online class daily and assessment twice weekly. In student’s point of view, though e- learning had several disadvantages like poor net connectivity, clinical training inadequacy, difficulty in attending class for longer duration and unfavourable learning environment, it proved constructive at pandemic time. On improvement in the design of the learning environment and teaching system, the online learning platform would better to serve its purpose in future pandemic.

The Increase of The Relative Amount of Nodular Calcification In Femoral Plaques is Associated With Milder Lower Extremity Arterial Disease

Vascular calcification exists in different forms that reflect variable clinical and histological implications. Categories of calcification have not been quantified in relation to the clinical presentation of lower extremity arterial disease. The study analyzed 51 femoral plaques collected during femoral endarterectomy, characterized by > 90% stenosis. The plaques were longitudinally sectioned, stained with Hematoxylin and Eosin and digitized for a deep learning platform for quantification of the relative area of nodular calcification to the plaque section area. Vessel measurements and quantity of each calcification category was compared to the clinical risk factors and outcomes. nodular calcification area proportion is associated with reduced risk of severely lowered toe pressure (< 30mmHg) (OR=0.910, 95%CI =0.835-0992, p<0.05), severely lowered ankle brachial index (<0.4), (OR=0.912, 95%CI=0.84-0.986, p<0.05), and semi-urgent operation (OR=0.882, 95%CI=0.797-0.976, p<0.05). The analysis was adjusted by age, gender, hypertension, diabetes and dyslipidaemia. Increase of the relative amount of nodular calcification in femoral plaques with over 90% stenosis is associated with protection against severe LEAD, identified by severely lowered toe pressure and ankle brachial index and semi-urgent operations. Nodular calcification may contribute to a slower obstruction, hence milder obstructive ischaemic presentation.

Design of a Personalized Recommendation System for Learning Resources based on Collaborative Filtering

At present, personalized recommendation system has become an indispensable technology in the fields of e-commerce, social network and news recommendation. However, the development of personalized recommendation system in the field of education and teaching is relatively slow with lack of corresponding application.In the era of Internet Plus, many colleges have adopted online learning platforms amidst the coronavirus (COVID-19) epidemic. Overwhelmed with online learning tasks, many college students are overload by learning resources and unable to keep orientation in learning. It is difficult for them to access interested learning resources accurately and efficiently. Therefore, the personalized recommendation of learning resources has become a research hotspot. This paper focuses on how to develop an effective personalized recommendation system for teaching resources and improve the accuracy of recommendation. Based on the data on learning behaviors of the online learning platform of our university, the authors explored the classic cold start problem of the popular collaborative filtering algorithm, and improved the algorithm based on the data features of the platform. Specifically, the data on learning behaviors were extracted and screened by knowledge graph. The screened data were combined with the collaborative filtering algorithm to recommend learning resources. Experimental results show that the improved algorithm effectively solved the loss of orientation in learning, and the similarity and accuracy of recommended learning resources surpassed 90%. Our algorithm can fully satisfy the personalized needs of students, and provide a reference solution to the personalized education service of intelligent online learning platforms.