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Seismic hazard maps may overestimate earthquake intensity

Los Angeles CA (SPX) May 03, 2024 -
A study conducted by researchers from Northwestern University has revealed a discrepancy in seismic hazard maps, which are instrumental in guiding the construction of earthquake-resistant structures ....

United States , Los Angeles , Clarence Oxford , Leah Salditch , Norman Abrahamson , University Of California , Northwestern University , California Historical Intensity Mapping Project , Science Advances , Data Augmentation , Landsat Water , Earth News , Earth Sciences , Climate Change , Nergy Technology , Nvironment News ,

ACM and IMS Release First Issues of Journal of Data Science - High-Performance Computing News Analysis

New York, March 27, 2024 – ACM, the Association for Computing Machinery, and IMS, the Institute of Mathematical Statistics, have announced the publication [.] ....

New York , United States , San Diego , Sanjay Krishnan , Renata Borovica Gajic , Alkis Polyzotis , Mert Pilanci , Iavor Bojinov , Zhuoran Yang , Ihabf Ilyas , Jonas Peters , Armin Karbasi , Paul Mineiro , Dongruo Zhou , Chao Chen , Andrej Risteski , Odest Chadwicke Jenkins , Lili Wu , Anthony Opipari , Frederic Koehler , Yi Sun , Stephenh Bach , Alexander Volfovsky , Sharad Goel , Shoutian Wang , John Lafferty ,

New Electronics - New standards, new specifications

In the light of new regulations how do we verify and validate AI in safety critical systems. By Lucas Garcia. ....

Lucas Garcia , Software Considerations In Airborne Systems , Software Considerations , Airborne Systems , Equipment Certification , Black Box , Importance Analysis , Data Augmentation , Data Balancing , Product Manager ,

"State of charge estimation for lithium-ion batteries based on data aug" by Chunsheng Hu, Fangjuan Cheng et al.

Ever-increasing efforts in state of charge (SOC) of lithium-ion battery estimation techniques have been centered on machine learning-based methods, and a prerequisite guaranteeing the effectiveness of these methods demands an abundance of high-quality datasets. However, performing battery-related experiments is time-consuming and expensive, and manufacturers are reluctant to release their datasets due to confidentiality constraints. This limited data availability has hindered further research in this area. This paper proposes a time series augmentation model (TS-DCGAN) based on a deep convolutional generative adversarial framework. By converting the data generation problem into image generation and utilizing the advancements in GAN-based image generation, the proposed method can produce high-quality battery data. The distributional similarity and diversity of generated datasets are evaluated quantitatively and qualitatively with several metrics. The SOC estimator trained on the synthet ....

Battery Management , Data Augmentation , Eep Convolutional Generative Adversarial Networks , Lithium Ion Batteries , State Of Charge , Ime Series Generation ,

AONDevices™ Unveils AONx360™: A Pioneering Platform for High-Accuracy and Super Low-Power Edge AI Development

/PRNewswire/ AONDevices, a leader in super low-power, high-accuracy edge AI solutions, today announced the launch of AONx360™. This innovative online. ....

Mouna Elkhatib , Edge Ai Development , Source Aondevices Inc , Edge Ai Integration Across Industries , Enabling Scalable , Always On Edge , Data Collection , Data Augmentation , Time Monitoring , Receiver Operating Characteristic ,