![A study of South Korean international school students: Impact of COVID-19 on anxiety and learning habits](/rails/active_storage/representations/proxy/eyJfcmFpbHMiOnsibWVzc2FnZSI6IkJBaHBBak1KIiwiZXhwIjpudWxsLCJwdXIiOiJibG9iX2lkIn19--6344137756464b727c547b332237ce206e0eeae6/eyJfcmFpbHMiOnsibWVzc2FnZSI6IkJBaDdCem9MWm05eWJXRjBTU0lJYW5CbkJqb0dSVlE2QzNKbGMybDZaVWtpRFRZd01IZzJNREErQmpzR1ZBPT0iLCJleHAiOm51bGwsInB1ciI6InZhcmlhdGlvbiJ9fQ==--a3b53ba1a0f83efef18f6e75a8d4ce784384bee2/posted%20photo%20(both).jpg)
In this study, the authors investigate the effects of the COVID-19 pandemic on South Korean international school students' anxiety, well being and their learning habits.
Read More...A study of South Korean international school students: Impact of COVID-19 on anxiety and learning habits
In this study, the authors investigate the effects of the COVID-19 pandemic on South Korean international school students' anxiety, well being and their learning habits.
Read More...Using data science along with machine learning to determine the ARIMA model’s ability to adjust to irregularities in the dataset
Auto-Regressive Integrated Moving Average (ARIMA) models are known for their influence and application on time series data. This statistical analysis model uses time series data to depict future trends or values: a key contributor to crime mapping algorithms. However, the models may not function to their true potential when analyzing data with many different patterns. In order to determine the potential of ARIMA models, our research will test the model on irregularities in the data. Our team hypothesizes that the ARIMA model will be able to adapt to the different irregularities in the data that do not correspond to a certain trend or pattern. Using crime theft data and an ARIMA model, we determined the results of the ARIMA model’s forecast and how the accuracy differed on different days with irregularities in crime.
Read More...The effect of floating plant on water purification: Comparison of the water purification capability of Water Hyacinth, Duckweed, and Azolla
Clean water is a necessity for every household, yet water pollution is a serious problem in many parts of the world and plays a major role in compromising water security in the 21st century. In this paper, the authors address the utility of several plants as natural water purifiers. They estimate the effectiveness of duckweed, hyacinth, and azolla in improving the quality of water from the Mithi river in India by measuring several metrics. They conclude that all three plants are effective in improving water quality, suggesting that these plants as eco-friendly options for water treatment.
Read More...The Effects of Barley Straw (Hordeum vulgare) Extract and Barley Straw Pellets on Algal Growth and Water Quality
Algal overgrowth often threatens to clog irrigation pipes and drinking water lines when left unchecked, as well as releasing possible toxins that threaten plant and human health. It is thus important to find natural, non-harmful agents that can decrease algal growth without threatening the health of plants and humans. In this paper, the authors test the efficacy of barely extract in either liquid or pellet form in decreasing algal growth. While their results were inconclusive, the experimental set-up allows them to investigate a wider range of agents as anti-algal treatments that could potentially be adopted on a wider scale.
Read More...Redesigning an Experiment to Determine the Coefficient of Friction
In a common high school experiment to measure friction coefficients, a weighted mass attached to a spring scale is dragged across a surface at a constant velocity. While the constant velocity is necessary for an accurate measurement, it can be difficult to maintain and this can lead to large errors. Here, the authors designed a new experiment to measure friction coefficients in the classroom using only static force and show that their method has a lower standard deviation than the traditional experiment.
Read More...Towards an Integrated Solution for Renewable Water and Energy
An integrated plant that would generate energy from solar power and provide clean water would help solve multiple sustainability issues. The feasibility of such a plant was investigated by looking at the efficacy of several different modules of such a plant on a small scale.
Read More...Transfer Learning with Convolutional Neural Network-Based Models for Skin Cancer Classification
Skin cancer is a common and potentially deadly form of cancer. This study’s purpose was to develop an automated approach for early detection for skin cancer. We hypothesized that convolutional neural network-based models using transfer learning could accurately differentiate between benign and malignant moles using natural images of human skin.
Read More...Locating sources of a high energy cosmic ray extensive air shower using HiSPARC data
Using the data provided by the University of Twente High School Project on Astrophysics Research with Cosmics (HiSPARC), an analysis of locations for possible high-energy cosmic ray air showers was conducted. An example includes an analysis conducted of the high-energy rain shower recorded in January 2014 and the use of Stellarium™ to discern its location.
Read More...An explainable model for content moderation
The authors looked at the ability of machine learning algorithms to interpret language given their increasing use in moderating content on social media. Using an explainable model they were able to achieve 81% accuracy in detecting fake vs. real news based on language of posts alone.
Read More...Differential MERS-CoV response in different cell types
The authors compare RNA expression profiles across three human cell types following infection with MERS-CoV
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