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Harvesting labor is a major cost factor in the production of specialty crops. Today accruing harvest labors is still done by hands, which is error-prone and costly. By integrating cloud-based web application with purposely designed labor monitoring devices (LMDs), we developed a harvest management system for monitoring and accruing harvest labors. The system comprises of two major components: an in-orchard...
Harvest labor has became a prevailing cost in cherry and other Specialty Crops industry. We developed an integrated solution that provided real-time labor monitoring, payroll accrual, and labor-data-based analysis. At the core of our solution is a cloud-based information system that collects labor data from purposely designed labor monitoring devices, and visualizes real-time labor productivity data...
In this paper, we propose novel adaptive function expansion recursive least square (RLS) algorithms, which can dynamically choose filter channels for coefficient updates for nonlinear active noise control while still maintaining the compromised performance degradation for nonlinear active noise control. The algorithms are developed based on a multi-channel structure using a channel selection scheme...
In this paper, we propose adaptive second-order Volterra filtered-X recursive least square (RLS) algorithms using sequential and partial updates for nonlinear active noise control. Recent research advancement has demonstrated that nonlinear active control is feasible for applications where the noise to be controlled may be a nonlinear and deterministic noise process such as chaotic noise rather than...
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