ARTIFICIAL SOLAR OXYGEN TREE
Abstract
The reduction in oxygen levels is being felt all over the world. Oxygen deficiency leads to mental and physical disorders not only in humans but also in sea creatures. Planting trees in urban areas is almost impossible with so many skyscrapers and industries already being there. The artificial solar oxygen tree would compensate for this loss to some extent at least. The artificial solar oxygen tree systems follow the sun throughout the day to maximize energy output. The artificial solar oxygen tree is a proven different-axis auto switching technology that has been custom designed to integrate with solar modules and reduce system costs. The multiple Solar panels generates up to 25% more energy than fixed single axis mounting systems and provides a bankable energy production profile preferred by utilities. Aim: Design & Implementation of "Intelligent Artificial Solar Oxygen Tree Using Embedded Technology
Fake News Detection using Machine Learning Algorithm
Abstract
In our modern era where the internet is ubiquitous, everyone relies on various online resources for news. Along with the increase in the use of social media platforms like Facebook,
Twitter, etc. news spread rapidly among millions of users within a very short span of time. The spread of fake news has far-reaching consequences like the creation of biased opinions to swaying election outcomes for the benefit of certain candidates.
Moreover, spammers use appealing news headlines
to generate revenue using advertisements via clickbaits.
In this paper, we aim to perform binary classification of various news articles available online with the help of concepts pertaining to Artificial Intelligence, Natural Language Processing and Machine Learning. We aim to provide the user with the ability to classify the news
as fake or real and also check the authenticity of the website publishing the news.
A COMPARATIVE STUDY OF ONLINE EDUCATION AND LEVEL OF HEALTH PROBLEMS DURING COVID-19 SITUATION
Abstract
ABSTRACT
The research study aims to see whether students in higher educational institutions are satisfied with technology-assisted Online Education during the COVID-19 pandemic and its effect on their physical mental and emotional health. The findings of this study could help policymakers and healthcare professionals develop effective psychological therapies and costefficient recommendations for preventing negative feelings among general people who are solitary at home. Due to the non-normal distribution of the data, a non-parametric test was employed to investigate the significant correlations between sample characteristics and the level of health problems during the COVID-19 outbreak. The connection between gender, education level, and age group vs the stated level of health problems was evaluated using a One-Way ANOVA test for independence. It may indicate distress and an increased abnormal or obsessive tendency like picking nails, sucking the thumb, and pulling the hair. Excessive use of gadgets even resulted in mental health problems, stress sensations, anxiety, excitation or thrill, headaches, tiredness of the muscle, eye and ear strains, obesity or overweight, faintness, irregular sleep patterns, mental disturbance, back pain, aching shoulders, neck, and muscles pain, etc. Online education also affected the physical activity levels of students like bad postures, later bedtimes, longer sleep rise discontinuation, and later waking times which has been associated with motionless and lazy lifestyles. The online survey form was kept open for a week to allow respondents to reply. The participating population does not have a regional boundary
Keywords: COVID-19, Health Crisis, Online Education, One-Way ANOVA, Perception.