Open Access. Powered by Scholars. Published by Universities.®
- Discipline
-
- Engineering (5)
- Civil and Environmental Engineering (3)
- Geography (2)
- Physical and Environmental Geography (2)
- Social and Behavioral Sciences (2)
-
- Transportation Engineering (2)
- Agricultural Science (1)
- Agriculture (1)
- Agronomy and Crop Sciences (1)
- Chemical Engineering (1)
- Civil Engineering (1)
- Climate (1)
- Electrical and Computer Engineering (1)
- Geographic Information Sciences (1)
- Health and Medical Physics (1)
- Human Geography (1)
- Life Sciences (1)
- Medicine and Health Sciences (1)
- Oceanography and Atmospheric Sciences and Meteorology (1)
- Physical Sciences and Mathematics (1)
- Plant Sciences (1)
- Power and Energy (1)
- Process Control and Systems (1)
- Public Health (1)
- Remote Sensing (1)
- Signal Processing (1)
- Spatial Science (1)
- Publication Type
Articles 1 - 9 of 9
Full-Text Articles in Entire DC Network
Machine Learning Based Applications For Data Visualization, Modeling, Control, And Optimization For Chemical And Biological Systems, Yan Ma
LSU Doctoral Dissertations
This dissertation report covers Yan Ma’s Ph.D. research with applicational studies of machine learning in manufacturing and biological systems. The research work mainly focuses on reaction modeling, optimization, and control using a deep learning-based approaches, and the work mainly concentrates on deep reinforcement learning (DRL). Yan Ma’s research also involves with data mining with bioinformatics. Large-scale data obtained in RNA-seq is analyzed using non-linear dimensionality reduction with Principal Component Analysis (PCA), t-Distributed Stochastic Neighbor Embedding (t-SNE), and Uniform Manifold Approximation and Projection (UMAP), followed by clustering analysis using k-Means and Hierarchical Density-Based Spatial Clustering with Noise (HDBSCAN). This report focuses …
Within-Field Yield Prediction For Sugarcane And Rice Focused On Precision Agriculture Applications, Felippe Hoffmann Silva Karp
Within-Field Yield Prediction For Sugarcane And Rice Focused On Precision Agriculture Applications, Felippe Hoffmann Silva Karp
LSU Master's Theses
Food and energy security are two main topics when it comes to the on-growing world population. Rice and sugarcane play an important role in this scenario since sugarcane can be used for energy production and rice is one of major staple cereals. In this scenario, Precision Agriculture (PA) management strategies aims to improve productivity, efficiency, profitability, and sustainability, and can help agriculture to fulfill the needs of the growing population in a sustainable way. However, yield maps are essential for PA, but its adoption is still very low. Thus, the main objective of this study was to evaluate the potential …
Development Of A Low Power, Low Cost Rural Railway Intersection Smart Detection And Warning System, Sara Ahmed, Samer Dessouky, Raymond Downing
Development Of A Low Power, Low Cost Rural Railway Intersection Smart Detection And Warning System, Sara Ahmed, Samer Dessouky, Raymond Downing
Data
This project explores a different approach to provide preemptive warning for train detection at grade-crossings to increase safety and reduce motor vehicle congestion. The development of a novel, low cost, low power, and off rail right-of-way (ROW) detection and warning system will be presented. A background of track circuits, which is the rail industries standard for train detection, will also be provided to highlight the benefits and challenges of the rail industry installing a system at every grade-crossings that lack any type of active warning. The benefits of using thermal imaging instead of traditional video for computer vision will also …
Development Of A Low Power, Low Cost Rural Railway Intersection Smart Detection And Warning System, Sara Ahmed, Samer Dessouky, Raymond Downing
Development Of A Low Power, Low Cost Rural Railway Intersection Smart Detection And Warning System, Sara Ahmed, Samer Dessouky, Raymond Downing
Publications
This project explores a different approach to provide preemptive warning for train detection at grade-crossings to increase safety and reduce motor vehicle congestion. The development of a novel, low cost, low power, and off rail right-of-way (ROW) detection and warning system will be presented. A background of track circuits, which is the rail industries standard for train detection, will also be provided to highlight the benefits and challenges of the rail industry installing a system at every grade-crossings that lack any type of active warning. The benefits of using thermal imaging instead of traditional video for computer vision will also …
Parallel And Asynchronous Distributed Optimization For Power Systems Operation, Ali Mohammadi
Parallel And Asynchronous Distributed Optimization For Power Systems Operation, Ali Mohammadi
LSU Doctoral Dissertations
Distributed optimization approaches are gaining more attention for solving power systems energy management functions, such as optimal power flow (OPF). Preserving information privacy of autonomous control entities and being more scalable than centralized approaches are two primary reasons for developing distributed algorithms. Moreover, distributed/ decentralized algorithms potentially increase power systems reliability against failures of components or communication links.
In this dissertation, we propose multiple distributed optimization algorithms and convergence performance enhancement techniques to solve the OPF problem. We present a multi-level optimization algorithm, based on analytical target cascading, to formulate and solve a collaborative transmission and distribution OPF problem. This …
Southwest Pacific Tropical Cyclone Frequency And Intensity Related To Observed And Modeled Geophysical And Aerosol Variables, Rupsa Bhowmick
Southwest Pacific Tropical Cyclone Frequency And Intensity Related To Observed And Modeled Geophysical And Aerosol Variables, Rupsa Bhowmick
LSU Doctoral Dissertations
The dissertation focuses on western region of Southwest Pacific Ocean (SWPO)
basin (135E - 180, and 5S - 35S) tropical cyclone (TC) climatology using observed
and modeled data. The classification-based machine learning approach
identifies the synoptic geophysical and aerosol environment favorable or unfavorable
for TC intensification and intensity change prior to landfall incorporating
observational and satellite data. A multiple poisson regression model with varying
temporal monthly lags was used to build a relationship between the number of
monthly TC days with basin wide average dust aerosol optical depth (AOD), sea
surface temperature (SST), and upper ocean temperature (UOT). This idea …
Data-Driven And Model-Based Methods With Physics-Guided Machine Learning For Damage Identification, Zhiming Zhang
Data-Driven And Model-Based Methods With Physics-Guided Machine Learning For Damage Identification, Zhiming Zhang
LSU Doctoral Dissertations
Structural health monitoring (SHM) has been widely used for structural damage diagnosis and prognosis of a wide range of civil, mechanical, and aerospace structures. SHM methods are generally divided into two categories: (1) model-based methods; (2) data-driven methods. Compared with data-driven SHM, model-based methods provide an updated physics-based numerical model that can be used for damage prognosis when long-term data is available. However, the performance of model-based methods is susceptible to modeling error in establishing the numerical model, which is usually unavoidable due to model simplification and omission. The major challenge of data-driven SHM methods lies in data insufficiency, e.g., …
Towards Optimizing Quality Assurance Outcomes Of Knowledge-Based Radiation Therapy Treatment Plans Using Machine Learning, Phillip Douglas Hardenbergh Wall
Towards Optimizing Quality Assurance Outcomes Of Knowledge-Based Radiation Therapy Treatment Plans Using Machine Learning, Phillip Douglas Hardenbergh Wall
LSU Doctoral Dissertations
Knowledge-based planning (KBP) techniques have been shown to provide improvements in plan quality, consistency, and efficiency for advanced radiation therapies such as volumetric modulated arc therapy (VMAT). While the potential clinical benefits of KBP methods are generally well known, comparatively less is understood regarding the impact of using these systems on resulting plan complexity and pre-treatment quality assurance (QA) measurements, especially for in-house KBP systems. Therefore, the overarching purpose of this work was to assess QA implications with using an in-house KBP system and explore data-driven methods for mitigating increased plan complexity and QA error rates without compromising dosimetric plan …
Automatic Features Extraction From Time Series Of Passive Microwave Images For Snowmelt Detection Using Deep-Learning – A Bidirectional Long-Short Term Memory Autoencoder (Bi-Lstm-Ae) Approach., Bienvenu Sedin Massamba
Automatic Features Extraction From Time Series Of Passive Microwave Images For Snowmelt Detection Using Deep-Learning – A Bidirectional Long-Short Term Memory Autoencoder (Bi-Lstm-Ae) Approach., Bienvenu Sedin Massamba
LSU Master's Theses
The Antarctic surface snowmelt is prone to the polar climate and is common in its coastal regions. With about 90 percent of the planet's glaciers, if all of the Antarctica glaciers melted, sea levels will rise about 58 meters around the planet. The development of an effective automated ice-sheet snowmelt monitoring system is therefore crucial.
Microwave remote sensing instruments, on the one hand, are very sensitive to snowmelt and can see day and night through clouds, allowing us to distinguish melting from dry snow and to better understand when, where, and for how long melting has taken place. On the …