Assessing Crucial Shaking Parameters in the Mechanical Harvesting of Nut Trees: A Review

– Mohsen Farajijalal; Ali Abedi; Cristian Manzo; Amir Kouravand; Mohammadmehdi Maharlooei; Arash Toudeshki; Reza Ehsani

A definition and taxonomy of digital twins: case studies with machine learning and scientific applications

– Adam Weingram; Carolyn Cui; Stephanie Lin; Samuel Munoz; Toby Jacob; Joshua Viers; Xiaoyi Lu

Inclusive Innovation in Agriculture: Redesigning Agtech Ecosystems for All

– Mock, Sarah; Bowen, Connie; Weinberg, Ben; Reddy, Suma; Wyne, Jamil; Gowani, Fayzan

Advancing grape chemical analysis through machine learning and multi-sensor spectroscopy

– Ricardo de Castro and Reza Ehsani

Iman Ebrahimi, Ricardo de Castro, Reza Ehsani, Luca Brillante, Shuang Feng,
Advancing grape chemical analysis through machine learning and multi-sensor spectroscopy,
Journal of Agriculture and Food Research,
Volume 16,
2024,
101085,
ISSN 2666-1543,
https://doi.org/10.1016/j.jafr.2024.101085.

Rateless-Enabled Link Adaptation for LoRa Networking

– Kang Yang and Wan Du

K. Yang, M. Liu and W. Du, “: Rateless-Enabled Link Adaptation for LoRa Networking,” in IEEE/ACM Transactions on Networking, doi: 10.1109/TNET.2024.3392342.
keywords: {Encoding;Signal to noise ratio;Sensors;Predictive models;Peer-to-peer computing;Optimization;Adaptation models;Low-power wide-area networks;LoRaWAN;rateless coding;data rate adaptation},