Interesting Engineering on MSN

Korean scientists detect hidden defects in solar cells with 1,000x sensitivity boost

Korean researchers have developed a new analysis method capable of detecting “hidden defects” in semiconductors with a ...
Futurism

Malware Is Now Using AI to Rewrite Its Own Code to Avoid Detection

Researchers at Google’s Threat Intelligence Group (GTIG) have discovered that hackers are creating malware that can harness the power of large language models (LLMs) to rewrite itself on the fly. An ...
TechSpot

Hyte tells Thicc Q80 Trio AIO owners to stop using the cooler due to leakage defect

In brief: One of the best-looking coolers available today is being taken off the market and owners are advised to cease using it immediately. Hyte's Thicc Q80 Trio, a $350 360mm AIO with an integrated ...
Frontiers

Real defect partial discharge identification method for power cables joints based on integrated PJS-M and GA-SVM algorithm with multi-source fusion

School of Electrical Engineering, Shanghai University of Electric Power, Shanghai, China Previous studies on 10 kV cable intermediate joint defects have mainly focused on typical defect types and ...
EDN

Real-time AI fuels faster, smarter defect detection

TDK SensEI’s edgeRX Vision system, powered by advanced AI, accurately detects defects in components as small as 1.0×0.5 mm in real time. Operating at speeds up to 2000 parts per minute, it reduces ...
Semiconductor Engineering

Detecting Slips, Scratches, Cracks In Wafers And Dies Becoming Harder

Defect detection requirements on the order of 10 defective parts per million (DPPM) are driving improvements in inspection tools’ resolution and throughput at foundries and OSATs. However, defects ...
Semiconductor Engineering

Can Your ATPG Do This? Cut Defects Escaping Detection With ML

Chipmakers worldwide consider Automatic Test Pattern Generation (ATPG) their go-to method for achieving high test coverage in production. ATPG generates test patterns designed to detect faults in the ...
Frontiers

Enhanced heart sound anomaly detection via WCOS: a semi-supervised framework integrating wavelet, autoencoder and SVM

Anomaly detection is a typical binary classification problem under the condition of unbalanced samples, which has been widely used in various fields of data mining. For example, it can help detect ...