Mapping 3D-super-enhancers with machine learning to pinpoint regulators of cell identity

Scientists usually study the molecular machinery that controls gene expression from the perspective of a linear, two-dimensional genome—even though DNA and its bound proteins function in three ...

Machine learning finds four behavior symptom profiles tied to early dementia processes

Behavioral changes—such as anxiety, depression, irritability, apathy or agitation, collectively known as neuropsychiatric ...
Devdiscourse

Why AI systems struggle with identities that resist fixed labels

A new academic study argues that the structural reliance of artificial intelligence (AI) systems on classification models creates significant challenges when AI systems attempt to represent fluid and ...
CERN Courier

A thousand anomalies hiding in plain sight

Systematic human inspection of the millions of source cutouts in the Hubble Legacy Archive is impossible – but artificial ...
EE World Online

The difference between physical AI and machine learning in power electronics

Physical artificial intelligence (PAI) is the application of AI and machine learning (ML) algorithms to enable autonomous ...
Rolling Stone

The Label That Launched Taylor Swift Is Changing Hands — Again

Change is once again afoot at Big Machine Records. The label’s founder, Scott Borchetta, announced on Thursday that he’s exiting HYBE America, which acquired Big Machine Label Group (BMLG) as part of ...
IEEE

Hierarchical Multi-Class and Multi-Label Text Classification for Crime Report: A Traditional Machine Learning Approach

Abstract: Large amounts of digital data are produced daily through society’s use of government and private companies. Digital transformation contributes to the increasing amount of structured and ...
Scientific Research Publishing

Comparative Research in Sentiment Analysis Using Machine Learning Technique ()

In today’s digital background, sentiment analysis has become an essential factor of Natural Language Processing (NLP), offering valuable insights from vast online data sources. This paper presents a ...
IEEE

Learning With Partial-Label and Unlabeled Data: Contrastive With Negative Example Separation

Abstract: Semi-Supervised Partial Label Learning (SSPLL) is an important branch of weakly supervised learning, where the data consists of both partial label examples and unlabeled ones. In SSPLL, the ...
Law

Training Alone Is Not Enough: Lessons From 'Recentive' and USPTO AI Examples on Patent Eligible Machine-Learning Claims

The Recentive decision exemplifies the Federal Circuit’s skepticism toward claims that dress up longstanding business problems in machine-learning garb, while the USPTO’s examples confirm that ...
Scientific Research Publishing

Research on Fault Detection and Classification of Industrial Equipment Based on Machine Learning ()

In the context of the rapid development of intelligent manufacturing, the stable operation of mechanical equipment is crucial for maintaining industrial production continuity and achieving economic ...
Ohsonline.com

Hazard Communication: Using GHS to Improve Health and Safety

I once had an experience working with a manufacturing operation that included painting processes for the main production line and a small spray-painting area in the repair section. The facility ...