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Full-Text Articles in Physical Sciences and Mathematics
Dry Matter Intake, Milk Performance And Production Efficiency From Spring Calving Dairy Cows Offered Grass-Only, Grass-White Clover And Total Mixed Ration Diets, E. Fitzpatrick, Luc Delaby, Trevor J. Gilliland, D. Hennessy
Dry Matter Intake, Milk Performance And Production Efficiency From Spring Calving Dairy Cows Offered Grass-Only, Grass-White Clover And Total Mixed Ration Diets, E. Fitzpatrick, Luc Delaby, Trevor J. Gilliland, D. Hennessy
IGC Proceedings (1997-2023)
In pasture-based dairy production systems, dry matter intake (DMI) is one of the main factors curtailing milk production and production efficiency. The inclusion of white clover (Trifolium repens L.) in swards of perennial ryegrass (PRG; Lolium perenne L.) can increase DMI from increased sward nutritive value over a grass-only sward. Feeding a fully balanced TMR diet can enhance milk production as a result of greater DMI and through greater control of feed quality. Therefore, the objective of this study was to determine the relationship between DMI, milk production, and energy efficiencies for dairy cows consuming different diets. A farm …
Towards Energy-Efficient Edge Computing For Tiny Ai Applications, Vamsi Krishna Bhagavathula
Towards Energy-Efficient Edge Computing For Tiny Ai Applications, Vamsi Krishna Bhagavathula
Theses and Dissertations
As artificial intelligence (AI) applications become more common on the edge of networks, like Raspberry Pi servers, it is crucial to optimize their energy use. This research project investigates how AI algorithms affect energy efficiency and resource usage on Raspberry Pi servers. Two models were created: one predicts resource usage, and the other predicts power consumption of AI algorithms on Raspberry Pi. Several factors are considered like CPU and memory use, algorithm speed, dataset size, and types of algorithms and datasets. Using regression-based methods, we model how these factors affect energy use. By converting categorical factors into numerical ones, we …