Demand forecasting remains one of the most complex challenges in retail management. As consumer behavior evolves rapidly, ...
A forecasting-driven framework integrates ARIMA, LSTM, and ensemble learning to optimize cloud resource scheduling. By predicting CPU, memory, ...
Background: Plant-based diets with reduced animal protein intake are increasingly recommended for health and sustainability reasons that have potential implications for nutrient intake, including ...
Introduction: Enriching egg yolks with n-3 polyunsaturated fatty acids (n-3 PUFAs) enhances their nutritional value. While phytobiotics like hemp seed, turmeric, and black pepper show potential for ...
Abstract: Energy system researchers are concentrating on reserve systems and reserve synthesis as these subjects show good potential for reducing the price of sustainable energy production. Especially ...
Artificial intelligence (AI) is playing a huge role in heat rate optimization. In some cases, AI-driven models have analyzed operational data to recommend control settings that reduce heat rates by ...
Abstract: Generative diffusion models, famous for their performance in image generation, are useful in various cross-domain applications. However, their use in the communication community has been ...
In machine learning, sequence models are designed to process data with temporal structure, such as language, time series, or signals. These models track dependencies across time steps, making it ...
Most existing automated training systems focus solely on optimizing parallelism configurations, while rarely taking memory optimization techniques—such as offloading, ZeRO, and activation ...
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