Machine learning to predict how fast biodegradable plastics break down in nature

Testing how quickly a biodegradable plastic actually breaks down in the environment can take months, sometimes years, of lab ...
technologynetworks

Single-Cell RNA-Seq Data Analysis With AI: Tools, Workflows, and Biological Interpretation

Single-cell RNA-seq AI analysis has become the default way to make sense of the millions of expression measurements a single experiment can now generate. Turning raw sequencing counts into ...
TechCrunch

Exclusive: Google deepens Thinking Machines Lab ties with new multibillion-dollar deal

Former OpenAI executive Mira Murati’s startup, Thinking Machines Lab, has signed a new multibillion-dollar agreement to expand its use of Google Cloud’s AI infrastructure, including systems powered by ...
IEEE

Research on Intelligent Evaluation of Pear Fruit Quality Based on Machine Learning

Abstract: This study proposes a PCA-machine learning fusion model to address the inefficiency and subjectivity of traditional pear quality evaluation. A standardized dataset was constructed by ...
GitHub

GitHub - Pagnoncelliander/Email_Classification: Organize, prepare, classify using PCA, standardization, and normalization, and apply the appropriate machine learning method for ...

PCA was applied to reduce the dimensionality, and StandardScaler was used for data normalization. For machine learning, I tested multiple models to achieve 99% accuracy. The Random Forest model, which ...
IEEE

A Hybrid Machine Learning-Based Framework for Data Injection Attack Detection in Smart Grids Using PCA and Stacked Autoencoders

Abstract: Cyberattacks, especially data injection attacks, are becoming more common as smart grids are increasingly interconnected. In addition, accurate and unbiased high-quality data is required for ...
Scientific Research Publishing

Malhi, A. and Gao, R.X. (2004) PCA-Based Feature Selection Scheme for Machine Defect Classification. IEEE Transactions on Instrumentation and Measurement, 53, 1517-1525.

ABSTRACT: One exciting area within computer vision is classifying human activities, which has diverse applications like medical informatics, human-computer interaction, surveillance, and task ...