In this study, the authors hypothesized that closed-circuit television images could be stored with improved resolution by using enhanced deep residual (EDSR) networks.
Read More...Deep residual neural networks for increasing the resolution of CCTV images
In this study, the authors hypothesized that closed-circuit television images could be stored with improved resolution by using enhanced deep residual (EDSR) networks.
Read More...The Effects of Confinement on the Associative Learning of Gallus gallus domesticus
This study aimed to determine if confinement affects associative learning in chickens. The research found that the difference in time lapsed before chickens began to consume cottage cheese before and after confinement was significant. These results suggest that confinement distresses chickens, as it impairs associative learning without inducing confusion.
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...Predicting clogs in water pipelines using sound sensors and machine learning linear regression
The authors looked the ability of sound sensors to predict clogged pipes when the sound intensity data is run through a machine learning algorithm.
Read More...Stress-induced genetic memory inheritance and retention in Planarian biological model
This study explored whether planaria, known for their regenerative abilities, can retain learned memories after regeneration and how stressors like alcohol affect memory.
Read More...Analyzing market dynamics and optimizing sales performance with machine learning
This study uses interpretable machine learning models, lasso and ridge regression with Shapley analysis, to identify key sales drivers for Corporación Favorita, Ecuador’s largest grocery chain. The results show that macroeconomic factors, especially labor force size, have the greatest impact on sales, though geographic and seasonal variables like city altitude and holiday proximity also play important roles. These insights can help businesses focus on the most influential market conditions to enhance competitiveness and profitability.
Read More...Advancements in glioma segmentation: comparing the U-Net and DeconvNet models
This study compares the performance of two deep learning models, U-Net and DeconvNet, for segmenting gliomas from MRI scans.
Read More...Comparing transformer and RNN models in BCIs for handwritten text decoding via neural signals
Brain-Computer Interface (BCI) allows users, especially those with paralysis, to control devices through brain activity. This study explored using a custom transformer model to decode neural signals into handwritten text for individuals with limited motor skills, comparing its performance to a traditional RNN-based BCI.
Read More...Analyzing the relationships between years of experience and performance anxiety in teen volleyball players
Athletes with performance anxiety may struggle to play their best and enjoy the game. Various factors may impact how much anxiety an athlete feels, including how much experience they have in the sport. Concha-Ortiz and Navins survey teenage club volleyball players to look for relationships between years of experience and performance anxiety symptoms.
Read More...The precision of machine learning models at classifying autism spectrum disorder in adults
Autism spectrum disorder (ASD) is hard to correctly diagnose due to the very subjective nature of diagnosing it: behavior analysis. Due to this issue, we sought to find a machine learning-based method that diagnoses ASD without behavior analysis or helps reduce misdiagnosis.
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