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Intrusion Detection With an Autoencoder and ANOVA Feature Selector
(North Dakota State University, 2021)
Intrusion detection systems are systems that aim at identifying malicious activities or violation of policies in a network. The problem of high dimensionality in intrusion detection systems is a barrier in processing data ...
Soil Moisture Prediction Using Meteorological Data, Satellite Imagery, and Machine Learning in the Red River Valley of the North
(North Dakota State University, 2021)
Weather stations provide key information related to soil moisture and have been used by farmers to decide various field operations. We first evaluated the discrepancies in soil moisture between a weather stations and nearby ...
Increasing the Predictive Potential of Machine Learning Models for Enhancing Cybersecurity
(North Dakota State University, 2021)
Networks have an increasing influence on our modern life, making Cybersecurity an important field of research. Cybersecurity techniques mainly focus on antivirus software, firewalls and intrusion detection systems (IDSs), ...
Ex-Ante Temporal Optimization in Soybean Origination: An Overdetermined Approach Through Deep Learning
(North Dakota State University, 2021)
Digitization is influencing commodity trading and agricultural markets and as they transition towards extreme liquidity, agribusiness risk exposures increase, and traditional competitive advantages diminish. In commodity ...
Machine Vision Methods for Evaluating Plant Stand Count and Weed Classification Using Open-Source Platforms
(North Dakota State University, 2021)
Evaluating plant stand count or classifying weeds by manual scouting is time-consuming, laborious, and subject to human errors. Proximal remote sensed imagery used in conjunction with machine vision algorithms can be used ...