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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 ...
Using Machine Learning and Text Mining Algorithms to Facilitate Research Discovery of Plant Food Metabolomics and Its Application for Human Health Benefit Targets
(North Dakota State University, 2020)
With the increase in scholarly articles published every day, the need for an automated systematic exploratory literature review tool is rising. With the advance in Text Mining and Machine Learning methods, such data ...
Extracting Useful Information and Building Predictive Models from Medical and Health-Care Data Using Machine Learning Techniques
(North Dakota State University, 2020)
In healthcare, a large number of medical data has emerged. To effectively use these data to improve healthcare outcomes, clinicians need to identify the relevant measures and apply the correct analysis methods for the type ...
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 ...
Soybean Leaf Chlorophyll Estimation and Iron Deficiency Field Rating Determination at Plot and Field Scales Through Image Processing and Machine Learning
(North Dakota State University, 2020)
Iron deficiency chlorosis (IDC) is the most common reason for chlorosis in soybean (Glycine max (L.) Merrill) and causes an average yield loss of 120 million dollars per year across 1.8 million ha in the North Central US ...
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 ...