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Tomato Flower Detection And Three-Dimensional Mapping For Precision Pollination, Kaitlyn Mckensie Nelms
Tomato Flower Detection And Three-Dimensional Mapping For Precision Pollination, Kaitlyn Mckensie Nelms
Masters Theses
It is estimated that nearly 75% of major crops have some level of reliance on pollination. Humans are reliant on fruit and vegetable crops for many vital nutrients. With the intensification of agricultural production in response to human demand, native pollinator species are not able to provide sufficient pollination services, and managed bee colonies are in decline due to colony collapse disorder, among other issues. Previous work addresses a few of these issues by designing pollination systems for greenhouse operations or other controlled production systems but fails to address the larger need for development in other agricultural settings with less …
Power System Stability Assessment With Supervised Machine Learning, Mirka Mandich
Power System Stability Assessment With Supervised Machine Learning, Mirka Mandich
Masters Theses
Power system stability assessment has become an important area of research due to the increased penetration of photovoltaics (PV) in modern power systems. This work explores how supervised machine learning can be used to assess power system stability for the Western Electricity Coordinating Council (WECC) service region as part of the Data-driven Security Assessment for the Multi-Timescale Integrated Dynamics and Scheduling for Solar (MIDAS) project. Data-driven methods offer to improve power flow scheduling through machine learning prediction, enabling better energy resource management and reducing demand on real-time time-domain simulations. Frequency, transient, and small signal stability datasets were created using the …
Primary User Emulation Attacks In Cognitive Radio - An Experimental Demonstration And Analysis, Benjamin James Ealey
Primary User Emulation Attacks In Cognitive Radio - An Experimental Demonstration And Analysis, Benjamin James Ealey
Masters Theses
Cognitive radio networks rely on the ability to avoid primary users, owners of the frequency, and prevent collisions for effective communication to take place. Additional malicious secondary users, jammers, may use a primary user emulation attacks to take advantage of the secondary user's ability to avoid primary users and cause excessive and unexpected disruptions to communications. Two jamming/anti-jamming methods are investigated on Ettus Labs USRP 2 radios. First, pseudo-random channel hopping schemes are implemented for jammers to seek-and-disrupt secondary users while secondary users apply similar schemes to avoid all primary user signatures. In the second method the jammer uses adversarial …