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It is essential to use deep learning algorithms for big data to implement a new generation of artificial intelligence. The effective use of deep learning methods depends largely on the number of samples. This work proposes a method combining the Wasserstein generative adversarial network (WGAN) with the specific deep learning model (ResNeXt) network to achieve data enhancement and classification of the Fourier transform infrared (FT-IR) spectra of strawberries. In this method, the data are first preprocessed using convolution, the FT-IR spectral data are augmented by WGAN, and the data are finally classified using the ResNeXt network. For the experimental investigation, 10 types of dimensionalityreduction algorithms combined with nine types of classification algorithms were used for comparing and arranging the 90 groups. The results obtained from these experiments prove that our method of using a combination of WGAN and ResNeXt is highly suitable for the classification of the IR spectra of strawberries and provides a data augmentation idea as a foundation for future research. [ABSTRACT FROM AUTHOR]

The article discusses the rise of computer-generated digital influencers on social media platforms and the potential for businesses to create virtual humans or clones for various purposes. It highlights the public's reaction to these influencers, with some followers unaware that they are interacting with fake personas. The article also explores the development of avatar technology by companies like Apple, Microsoft, and Meta, which allows for real-time communication and the creation of lifelike puppets. Additionally, it mentions the use of AI-powered features by platforms like TikTok and Microsoft, as well as the work of Synthesia in creating avatars and digital clones. The article concludes by suggesting that the future will involve AI clones that can think and communicate like individuals, leading to increased productivity and lower costs for businesses. [Extracted from the article]

The article discusses on the potential of quantum computing technologies, particularly quantum annealing and quantum-hybrid, to help utilities tackle complex optimization challenges caused by extreme weather events and the integration of renewable energy sources. Quantum computing can provide solutions to problems outside the reach of traditional computation methods, enabling utilities to enhance grid stability, resilience and reliability, leading to a flexible power distribution system.