![COVID-19 pandemic impact on emotional aspects of high school students](/rails/active_storage/representations/proxy/eyJfcmFpbHMiOnsibWVzc2FnZSI6IkJBaHBBaVFLIiwiZXhwIjpudWxsLCJwdXIiOiJibG9iX2lkIn19--c248df65f87e4126bf5f56fa64f24f040db17bc1/eyJfcmFpbHMiOnsibWVzc2FnZSI6IkJBaDdCem9MWm05eWJXRjBTU0lKYW5CbFp3WTZCa1ZVT2d0eVpYTnBlbVZKSWcwMk1EQjROakF3UGdZN0JsUT0iLCJleHAiOm51bGwsInB1ciI6InZhcmlhdGlvbiJ9fQ==--52131d7e1d9fc5c464ef2fd793e4b0873b571622/feature-photo.jpeg)
In this study, the impact of shutting down schools on the emotional aspects of high school students was analyzed using survey responses.
Read More...COVID-19 pandemic impact on emotional aspects of high school students
In this study, the impact of shutting down schools on the emotional aspects of high school students was analyzed using survey responses.
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...Interaction of light with water under clear and algal bloom conditions
Here, recognizing the potential harmful effects of algal blooms, the authors used satellite images to detect algal blooms in water bodies in Wyoming based on their reflectance of near infrared light. They found that remote monitoring in this way may provide a useful tool in providing early warning and advisories to people who may live in close proximity.
Read More...A novel deep learning model for visibility correction of environmental factors in autonomous vehicles
Intelligent vehicles utilize a combination of video-enabled object detection and radar data to traverse safely through surrounding environments. However, since the most momentary missteps in these systems can cause devastating collisions, the margin of error in the software for these systems is small. In this paper, we hypothesized that a novel object detection system that improves detection accuracy and speed of detection during adverse weather conditions would outperform industry alternatives in an average comparison.
Read More...Preliminary investigation of Allosauroidea facial integument and the evolution of theropod facial armor
The facial integument, or external skin tissues, were assessed on set of dinosaurs from the Allosauroidea clade to test whether dermal patterns served specific functions.
Read More...Machine Learning Algorithm Using Logistic Regression and an Artificial Neural Network (ANN) for Early Stage Detection of Parkinson’s Disease
Despite the prevalence of PD, diagnosing PD is expensive, requires specialized testing, and is often inaccurate. Moreover, diagnosis is often made late in the disease course when treatments are less effective. Using existing voice data from patients with PD and healthy controls, the authors created and trained two different algorithms: one using logistic regression and another employing an artificial neural network (ANN).
Read More...Identifying factors, such as low sleep quality, that predict suicidal thoughts using machine learning
Sadly, around 800,000 people die by suicide worldwide each year. Dong and Pearce analyze health survey data to identify associations between suicidal ideation and relevant variables, such as sleep quality, hopelessness, and anxious behavior.
Read More...Solving a new NP-Complete problem that resembles image pattern recognition using deep learning
In this study, the authors tested the ability and accuracy of a neural net to identify patterns in complex number matrices.
Read More...The Effect of Delivery Method, Speaker Demographics, and Physical Environment on the Engagement Level of Older Adults
With an increasing older adult population and rapid advancements in technology, it is important that senior citizens learn to use new technologies to remain active in society. A variety of factors on learning were investigated through surveys of senior citizens. Older adults preferred an interactive lesson style, which also seemed to help them retain more course material.
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.
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