Using machine learning to predict the risk of algae bloom
Read More...Using two-step machine learning to predict harmful algal bloom risk
Using machine learning to predict the risk of algae bloom
Read More...Analyzing carbon dividends’ impact on financial security via ML & metaheuristic search
Impact of carbon tax and dividend on financial security
Read More...Practical applications of the Fourier analysis to identify pitches and synthesize sounds in music
In this study the authors looked at the ability of the Discrete Fourier Transform (DFT) to analyze different musical elements. They found that DFT is a powerful method to analyze recorded music.
Read More...Class distinctions in automated domestic waste classification with a convolutional neural network
Domestic waste classification using convolutional neural network
Read More...Investigating AlphaFold’s handling of nanobody-antigen complex prediction
Predicting antibody structures and antibody-antigen complexes using AlphaFold
Read More...Identifying 5-hydroxymethylcytosine as a potential cancer biomarker using FFPE DNA samples
This study used an improved CMS-seq method to profile 5hmC in ormalin-fixed and paraffin-embedded (FFPE) samples from HNC tumors and adjacent normal tissues, identifying three genes (PRKD2, HADHA, and AIPL1) with promising potential as biomarkers for Head and neck cancer (HNC) diagnosis.
Read More...Investigating the connection between free word association and demographics
Utilization of neural network to analyze Free Word Association to predict accurately age, gender, first language, and current country.
Read More...Unit-price anchoring affects consumer purchasing behavior
This study examines how anchoring—providing numerical suggestions like "2 for $4"—can influence consumer purchasing decisions and increase revenue. The researchers tested three types of price anchors on 29 high school students shopping in a mock store.
Read More...Behaviors and attitudes concerning disposable masks and the environment: A D.C. high school case study
The authors looked at student behaviors around disposal of face masks. The goal of the study was to bring awareness to improper mask disposal and how the resulting litter contributes to overall environmental pollution.
Read More...Enhancing marine debris identification with convolutional neural networks
Plastic pollution in the ocean is a major global concern. Remotely Operated Vehicles (ROVs) have promise for removing debris from the ocean, but more research is needed to achieve full effectiveness of the ROV technology. Wahlig and Gonzales tackle this issue by developing a deep learning model to distinguish trash from the environment in ROV images.
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