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Loftware, Inc.: Loftware and SATO Unveil World's First Cloud-Based RFID Encoding and Logging Solution with NiceLabel Cloud - Vimarsana News

Loftware, Inc.: Loftware and SATO Unveil World's First Cloud-Based RFID Encoding and Logging Solution with NiceLabel Cloud

Solution enables producers of medical devices, pharmaceuticals, and luxury goods to meet stringent traceability requirements PORTSMOUTH, N.H., Nov. 15, 2022 /PRNewswire/ -- Loftware, the

iTWire - Australia's digital future is contingent on ultra low-latency networks - Vimarsana News

iTWire - Australia's digital future is contingent on ultra low-latency networks

GUEST OPINION: New and emerging digital experiences highlight the importance of understanding and optimising how traffic gets to and from an end user....

Source: itwire.com
Amagi launches into South Korea - Vimarsana News

Amagi launches into South Korea

Strengthening its presence in a key territory, cloud-based SaaS broadcast and CTV technology provider Amagi has expanded into South Korea with a sales and custo...

intoPIX SDKs Rev up Performance to Meet the Rapidly Increasing Encoding and Decoding Demand of Software-based Production & Pro-AV - Vimarsana News

intoPIX SDKs Rev up Performance to Meet the Rapidly Increasing Encoding and Decoding Demand of Software-based Production & Pro-AV

intoPIX, the leading provider of innovative compression technologies, today announced important updates to their line of Software Development Kits (SDKs), keeping pace with the rapidly increasing demand

"Optimising Automatic Text Classification Approach in Adaptive Online C" by Ya feng Zheng, Zhang hao Gao et al. - Vimarsana News

"Optimising Automatic Text Classification Approach in Adaptive Online C" by Ya feng Zheng, Zhang hao Gao et al.

A text semantic classification is an essential approach to recognising the verbal intention of online learners, empowering reliable understanding and inquiry for the regulations of knowledge construction amongst students. However, online learning is increasingly switching from static watching patterns to the collaborative discussion. The current deep learning models, such as CNN and RNN, are ineffective in classifying verbal content contextually. Moreover, the contribution of verbal elements to semantics is often considerably varied, requiring the attachment of weights to these elements to inc...

Source: uow.edu.au