Browsing by Subject "machine learning"
Now showing items 1-16 of 16
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A Conditional Random Field (CRF) Based Machine Learning Framework for Product Review Mining
(North Dakota State University, 2019)The task of opinion mining from product reviews has been achieved by employing rule-based approaches or generative learning models such as hidden Markov models (HMMs). This paper introduced a discriminative model using ... -
Detecting Insider and Masquerade Attacks by Identifying Malicious User Behavior and Evaluating Trust in Cloud Computing and IoT Devices
(North Dakota State University, 2019)There are a variety of communication mediums or devices for interaction. Users hop from one medium to another frequently. Though the increase in the number of devices brings convenience, it also raises security concerns. ... -
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 ... -
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 ... -
High Performance Static Random Access Memory Design for Emerging Applications
(North Dakota State University, 2018)Memory wall is becoming a more and more serious bottleneck of the processing speed of microprocessors. The mismatch between CPUs and memories has been increasing since three decades ago. SRAM was introduced as the bridge ... -
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), ... -
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 ... -
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 ... -
On the Feasibility of Machine Learning Algorithms Towards Low-Cost Flow Cytometry
(North Dakota State University, 2023-08-01)Utilization low cost, scalable architectures for detection of specific cells for both mass flow and minute incidence analysis is something that is attractive for the clinical researcher, in order to expand access to otherwise ... -
Optimal Seeding Rates for New Hard Red Spring Wheat Cultivars in Diverse Environments
(North Dakota State University, 2019)Seeding rate in hard red spring wheat (HRSW) (Triticum aestivum L.) production impacts input cost and grain yield. Predicting the optimal seeding rate (OSR) for HRSW cultivars can aid growers and eliminate the need for ... -
Rangeland Forage Growth Prediction, Logistics, Energy, and Economics Analysis and Tool Development Using Open-Source Software
(North Dakota State University, 2022)Forage availability was crucial for livestock production across the United States. Rangelands occupied vast areas 31 % of land and were the primary source of forage for livestock. However, extreme climatic conditions such ... -
Ranking Risk Factors in Financial Losses From Railroad Incidents: A Machine Learning Approach
(2023)The reported financial losses from railroad accidents since 2009 have been more than US$4.11 billion dollars. This considerable loss is a major concern for the industry, society, and the government. Therefore, identifying ... -
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 ... -
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 ... -
Using Machine Learning and Graph Mining Approaches to Improve Software Requirements Quality: An Empirical Investigation
(North Dakota State University, 2019)Software development is prone to software faults due to the involvement of multiple stakeholders especially during the fuzzy phases (requirements and design). Software inspections are commonly used in industry to detect ... -
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 ...