Digital Commons Network^™

Assessment Of Post-Wildfire Erosion Risk And Effects On Water Quality In South-Western Australia, David Blake, Petter Nyman, Helen Nice, Frances M.L. D'Souza, Christopher R.J. Kavazos, Pierre Horwitz

Research outputs 2014 to 2021

Investigations of wildfire impact on water resources have escalated globally over the last decade owing to an awareness of climate-related vulnerabilities. Within Australia, research into post-wildfire erosion has focused on water supply catchments in the south-eastern region. Here, we examine post-wildfire erosion risk and its potential for water quality impacts in a catchment in south-western Australia. The catchment of the Harvey River, which drains from forested escarpments onto an agricultural coastal plain and into valuable coastal wetlands, was burnt by wildfire in 2016. The aims of this study were to determine erosion risk across contrasting landforms and variable fire severity, …

Pollen Adaptation To Ant Pollination – A Case Study From The Proteaceae, Nicola Delnevo, Eddie Van Etten, Nicola Clemente, Luna Fogu, Evelina Pavarani, Margaret Byrne, William Stock

Research outputs 2014 to 2021

Background and aims:

Ant-plant associations are widely diverse and distributed throughout the world, leading to antagonistic and/or mutualistic interactions. Ant pollination is a rare mutualistic association and reports of ants as effective pollinators are limited to a few studies. Conospermum (Proteaceae) is an insect-pollinated genus well represented in the south-western Australia biodiversity hotspot, and here we aimed to evaluate the role of ants as pollinators of C. undulatum.

Methods:

Pollen germination after contact with several species of ants and bees was tested for C. undulatum and five co-flowering species for comparison. We then sampled the pollen load of floral …

A Novel Penalty-Based Wrapper Objective Function For Feature Selection In Big Data Using Cooperative Co-Evolution, A.N.M. Bazlur Rashid, Mohiuddin Ahmed, Leslie F. Sikos, Paul Haskell-Dowland

Research outputs 2014 to 2021

The rapid progress of modern technologies generates a massive amount of high-throughput data, called Big Data, which provides opportunities to find new insights using machine learning (ML) algorithms. Big Data consist of many features (also called attributes); however, not all these are necessary or relevant, and they may degrade the performance of ML algorithms. Feature selection (FS) is an essential preprocessing step to reduce the dimensionality of a dataset. Evolutionary algorithms (EAs) are widely used search algorithms for FS. Using classification accuracy as the objective function for FS, EAs, such as the cooperative co-evolutionary algorithm (CCEA), achieve higher accuracy, even …

Missing Data Imputation Of High-Resolution Temporal Climate Time Series Data, Eben Afrifa-Yamoah, Ute A. Mueller, S. M. Taylor, A. J. Fisher

Research outputs 2014 to 2021

© 2020 The Authors. Meteorological Applications published by John Wiley & Sons Ltd on behalf of the Royal Meteorological Society. Analysis of high-resolution data offers greater opportunity to understand the nature of data variability, behaviours, trends and to detect small changes. Climate studies often require complete time series data which, in the presence of missing data, means imputation must be undertaken. Research on the imputation of high-resolution temporal climate time series data is still at an early phase. In this study, multiple approaches to the imputation of missing values were evaluated, including a structural time series model with Kalman smoothing, …

Migrating From Partial Least Squares Discriminant Analysis To Artificial Neural Networks: A Comparison Of Functionally Equivalent Visualisation And Feature Contribution Tools Using Jupyter Notebooks, Kevin M. Mendez, David I. Broadhurst, Stacey N. Reinke

Research outputs 2014 to 2021

Introduction:

Metabolomics data is commonly modelled multivariately using partial least squares discriminant analysis (PLS-DA). Its success is primarily due to ease of interpretation, through projection to latent structures, and transparent assessment of feature importance using regression coefficients and Variable Importance in Projection scores. In recent years several non-linear machine learning (ML) methods have grown in popularity but with limited uptake essentially due to convoluted optimisation and interpretation. Artificial neural networks (ANNs) are a non-linear projection-based ML method that share a structural equivalence with PLS, and as such should be amenable to equivalent optimisation and interpretation methods.

Objectives:

We hypothesise that …

Development Of An Infrared Pollution Index To Identify Ground-Level Compositional, Particle Size, And Humidity Changes Using Himawari-8, M. Sowden, D. Blake, D. Cohen, A. Atanacio, Ute Mueller

Research outputs 2014 to 2021

Speciated air quality data informs health studies and quantitates impacts. However, monitoring is concentrated around populated regions whilst, large remote and rural regions remain unmonitored despite risks of dust-storms or wild-fires. Sub-hourly, infrared, geostationary data, such as the 10-min data from Himawari 8, could potentially be used to quantify regional air quality continually. Monitoring of Aerosol Optical Depth (AOD) is restricted to visible spectra (i.e. daytime only), while newer quantification methods using geostationary infrared (IR) data have focused on detecting the presence, or absence, of an event. Limited attention has been given to the determination of particle size and aerosol …

2020 Georgia Southern University Men's Soccer Roster, Georgia Southern University

Men's Soccer Records

• Georgia Southern University Athletics 2020 Men's Soccer Roster

2020 Georgia Southern University Softball Media Guide, Georgia Southern University

Women's Softball Records

• Georgia Southern Softball 2020 Media Guide

2019-2020 Georgia Southern University Women's Swimming And Diving Roster, Georgia Southern University

Women's Swimming Records

• 2019-20 Swimming and Diving Roster

Effect Of Subsurface Microseismicity On The Motion Of Surrounding Dispersed Droplets -- Data, Chao Zeng, Wen Deng

Effect of Subsurface Microseismicity on the Motion of Surrounding Dispersed Droplets – Data

Spreadsheet - Data plotted in Figure 4 and Figure 5

Supporting information

Evolution Of Integration, Build, Test, And Release Engineering Into Devops And To Devsecops, Vishnu Pendyala

Faculty Research, Scholarly, and Creative Activity

Software engineering operations in large organizations are primarily comprised of integrating code from multiple branches, building, testing the build, and releasing it. Agile and related methodologies accelerated the software development activities. Realizing the importance of the development and operations teams working closely with each other, the set of practices that automated the engineering processes of software development evolved into DevOps, signifying the close collaboration of both development and operations teams. With the advent of cloud computing and the opening up of firewalls, the security aspects of software started moving into the applications leading to DevSecOps. This chapter traces the journey …

Near-Bottom Currents At Station M In The Northeast Pacific, Thomas Connolly, Paul Mcgill, Richard Henthorn, Drew Burrier, Cynthia Michaud

Faculty Research, Scholarly, and Creative Activity

No abstract provided.

Biology Ii, Steelman Library, Sheila P. Abraham Dr.

Syllabus Repository

No abstract provided.

Jiann-Ping Hsu College Of Public Health Magazine, Georgia Southern University

College of Public Health: News & Publications

• Message from the Dean: Stuart Tedders, PhD
• Dean Stuart Tedders: Welcome
• One-On-One Telfair in conversation with Tarasenko: Working for WHO as a Chronic Disease Epidemiologist
• Student research shows Georgia was home to four of nation’s ten highest counties for mortality rate from COVID-19
• One the front lines: Reports from our Alumni and Students working on the front lines of COVID-19
• Robert Vogel, PhD: Leaves legacy of wit and knowledge
• Center for Addiction Recovery Hosts seventh annual Southeastern Collegiate Recovery Summit
• Karl E. Peace Center for Biostatistics and Survey Research Working together: Biostatistics collaborations
• Center for Public Health Practice and Research …

Enhanced Electrochemical Performance Of Li-Ion Battery Cathodes By Atomic Layer Deposition, Yan Gao

Doctoral Dissertations

”Li-ion battery now plays an irreplaceable role in supplying green and convenient energy. In this work, atomic layer deposition (ALD) was used to modify Li-ion battery cathode particles for performance enhancement.

An ultrathin and conductive CeO₂ ALD film was deposited on Li-rich layered cathode particles, of which the specific capacity and cyclic stability were significantly improved. On the same cathode particles, FeO_x ALD and post-annealing resulted in a stable and conductive surface spinel phase to improve the performance.

Synergetic TiN coating and Ti doping were performed on a LiFePO₄ (LFP) cathode and extended its cycle life. The …

Optimal Adaptive Control Of Time-Delay Dynamical Systems With Known And Uncertain Dynamics, Rohollah Moghadam

Doctoral Dissertations

"Delays are found in many industrial pneumatic and hydraulic systems, and as a result, the performance of the overall closed-loop system deteriorates unless they are explicitly accounted. It is also possible that the dynamics of such systems are uncertain. On the other hand, optimal control of time-delay systems in the presence of known and uncertain dynamics by using state and output feedback is of paramount importance. Therefore, in this research, a suite of novel optimal adaptive control (OAC) techniques are undertaken for linear and nonlinear continuous time-delay systems in the presence of uncertain system dynamics using state and/or output feedback. …

Deep Learning For Digitized Histology Image Analysis, Sudhir Sornapudi

Doctoral Dissertations

“Cervical cancer is the fourth most frequent cancer that affects women worldwide. Assessment of cervical intraepithelial neoplasia (CIN) through histopathology remains as the standard for absolute determination of cancer. The examination of tissue samples under a microscope requires considerable time and effort from expert pathologists. There is a need to design an automated tool to assist pathologists for digitized histology slide analysis. Pre-cervical cancer is generally determined by examining the CIN which is the growth of atypical cells from the basement membrane (bottom) to the top of the epithelium. It has four grades, including: Normal, CIN1, CIN2, and CIN3. In …

Finite Time Suboptimal Control Design Of Nonlinear Systems With Θ-D Technique And Implementation To Aerospace Applications, Jie Yao

Doctoral Dissertations

“A finite time suboptimal control strategy (named θ - D approximated algorithm) was proposed in this study, which can provide the control engineers with a novel effective and efficient design tool from the finite time optimal perspective. Based on the framework of this proposed method, the original nonlinear dynamics were formulated in pseudo-linear form, and the performance index was denoted by a linear quadratic regulator prototype in this research. After that, the approximated solutions to intractable Hamilton-Jacobi-Bellman (HJB) equation were acquired by putting vanishing perturbation terms into the performance index. By tuning the parameters in perturbation terms, semi-global stability and …

Attention Mechanism In Deep Neural Networks For Computer Vision Tasks, Haohan Li

Doctoral Dissertations

“Attention mechanism, which is one of the most important algorithms in the deep Learning community, was initially designed in the natural language processing for enhancing the feature representation of key sentence fragments over the context. In recent years, the attention mechanism has been widely adopted in solving computer vision tasks by guiding deep neural networks (DNNs) to focus on specific image features for better understanding the semantic information of the image. However, the attention mechanism is not only capable of helping DNNs understand semantics, but also useful for the feature fusion, visual cue discovering, and temporal information selection, which are …

Exploring Wellbore And Reservoir Temperature Profiles In Fluid Circulation And Production Operations, Ahmed Qasim Al Saedi

Doctoral Dissertations

"The wellbore heat flow occurs during different well operations resulting from any temperature differences between the wellbore fluid and the adjacent formation. Understanding the direction and mechanism of heat flow whether it is conduction or convection help to represent this heat exchange mathematically. However, the only available factor used to understand the heat flow behavior is the measured wellbore temperature which can be obtained from the direct measurement while drilling or circulation operations, well logging, well test, or from the production operations. Also, the initial geothermal formation temperature resulting from the geothermal gradient will help to understand the undistributed formation …

Geophysical Assessment Of The Lake Chesterfield Site, Missouri, Diya Ali Ahmad Alfuqara

Doctoral Dissertations

"Since construction of the Lake Chesterfield, Missouri in 1986, significant leaks have occurred causing the lake to lose substantive volumes of water. Mitigation efforts, have not solved the problem. Indeed, in June of 2017, the water level in Lake Chesterfield dropped at an alarmingly rapid rate. Prior to authorizing additional mitigation work, the Lake Chesterfield. Home Owners Association (LCHOA) decided to acquire geophysical data across the drained and dry lake bed. These information would help a geotechnical engineering firm determine the most appropriate mitigation plan.

In the summer of 2018, electrical resistivity tomography, multichannel analysis of surface wave, and spontaneous-potential …

Operation And Analysis Of High-Voltage-Gain Dc-Dc Converters With Voltage Multipliers, Mohammad Rashed M. Altimania

Doctoral Dissertations

"This research analyzes and investigates the steady-state operations of four different high-voltage-gain step-up dc- dc converters to achieve a high gain. These topologies consist of a two-phase interleaved boost stage with three various voltage multiplier (VM) stages. The first stage of the first three topologies is the same, which is a two-phase interleaved boost stage implemented by using inductors. The first family used in this research is based on a modified Dickson charge pump voltage multiplier stage, and this family has been studied in discontinuous conduction mode (DCM). The second family relies on a non-inverting or inverting diode-capacitors voltage multiplier …

Investigating The Factors Impacting The Success Of Immiscible Carbon Dioxide Injection In Unconventional Shale Reservoirs: An Experimental Study, Sherif M. Fakher

Doctoral Dissertations

"Unconventional shale reservoirs are currently gaining significant interest due to the huge hydrocarbon volumes that they bear. Enhanced oil recovery (EOR) techniques have been suggested to increase recovery from shale reservoirs. One of the most promising EOR methods is gas EOR (GEOR), most notably carbon dioxide (CO₂). Not only can CO₂ increase oil recovery by interacting with the oil and the shale, but it has also been shown to adsorb to the shale rock and thus is effective in both EOR applications and also carbon storage purposes. This research aims to experimentally investigate several of the interactions …

Computational Model For Neural Architecture Search, Ram Deepak Gottapu

Doctoral Dissertations

"A long-standing goal in Deep Learning (DL) research is to design efficient architectures for a given dataset that are both accurate and computationally inexpensive. At present, designing deep learning architectures for a real-world application requires both human expertise and considerable effort as they are either handcrafted by careful experimentation or modified from a handful of existing models. This method is inefficient as the process of architecture design is highly time-consuming and computationally expensive.

The research presents an approach to automate the process of deep learning architecture design through a modeling procedure. In particular, it first introduces a framework that treats …

Observer-Based Event-Triggered And Set-Theoretic Neuro-Adaptive Controls For Constrained Uncertain Systems, Abdul Ghafoor

Doctoral Dissertations

"In this study, several new observer-based event-triggered and set-theoretic control schemes are presented to advance the state of the art in neuro-adaptive controls. In the first part, six new event-triggered neuro-adaptive control (ETNAC) schemes are presented for uncertain linear systems. These comprehensive designs offer flexibility to choose a design depending upon system performance requirements. Stability proofs for each scheme are presented and their performance is analyzed using benchmark examples. In the second part, the scope of the ETNAC is extended to uncertain nonlinear systems. It is applied to a case of precision formation flight of the microsatellites at the Sun-Earth/Moon …

Microgrid Design, Control, And Performance Evaluation For Sustainable Energy Management In Manufacturing, Md. Monirul Islam

Doctoral Dissertations

"This research studies the capacity sizing, control strategies, and performance evaluation of the microgrids with hybrid renewable sources for manufacturing end use customers towards a distributed sustainable energy system paradigm. Microgrid technology has been widely investigated and applied in commercial and residential sector, while for manufacturers, it has been less explored and utilized. To fill the gap, the dissertation first proposes a cost-effective sizing model to identify the capacities as well as control strategies of the components in microgrids considering a commonly used energy tariff, i.e., Time of Use (TOU). Then, the sizing model is extended by integrating control strategies …

Towards Efficacy And Efficiency In Sparse Delay Tolerant Networks, Douglas John Mcgeehan

Doctoral Dissertations

"The ubiquitous adoption of portable smart devices has enabled a new way of communication via Delay Tolerant Networks (DTNs), whereby messages are routed by the personal devices carried by ever-moving people. Although a DTN is a type of Mobile Ad Hoc Network (MANET), traditional MANET solutions are ill-equipped to accommodate message delivery in DTNs due to the dynamic and unpredictable nature of people's movements and their spatio-temporal sparsity. More so, such DTNs are susceptible to catastrophic congestion and are inherently chaotic and arduous. This manuscript proposes approaches to handle message delivery in notably sparse DTNs. First, the ChitChat system [69] …

Strengthening Qc Relaxations Of Optimal Power Flow Problems By Exploiting Various Coordinate Changes, Mohammad Rasoul Narimani

Doctoral Dissertations

"Motivated by the potential for improvements in electric power system economics, this dissertation studies the AC optimal power flow (AC OPF) problem. An AC OPF problem optimizes a specified objective function subject to constraints imposed by both the non-linear power flow equations and engineering limits. The difficulty of an AC OPF problem is strongly connected to its feasible space's characteristics. This dissertation first investigates causes of nonconvexities in AC OPF problems. Understanding typical causes of nonconvexities is helpful for improving AC OPF solution methodologies.

This dissertation next focuses on solution methods for AC OPF problems that are based on convex …

Experimental And Modeling Studies Using Packed Bed Reactors: Liquid Phase Ethylene Production By Hydrogenation Of Acetylene, Humayun Shariff

Doctoral Dissertations

"Gas-phase catalytic hydrogenation of acetylene to produce ethylene, commonly practiced in industries, has green oil formation, which leads to catalyst deactivation and sometimes reactor runaway risks due to high exothermicity. To overcome these issues as well as to increase the selectivity and conversion, liquid-phase hydrogenation of acetylene was investigated in packed bed reactors (PBR) using a commercial catalyst. The reactor performance of two-phase flow PBRs was assessed experimentally complemented by a validated mathematical model at different scales.

The selective hydrogenation of acetylene in the liquid phase over a commercial 0.5 wt% Pd/Al₂O₃ catalyst was investigated in a …

Minimizing The Detrimental Effects Of Hydro-Peaking On Riverbank Instability: The Lower Osage River Case, Wesam Sameer Mohammed-Ali

Doctoral Dissertations

"The fluctuation of water level downstream from dams due to hydropower flow releases negatively affects the riverbank stability. Therefore, this research aims to examine the feasibility of using an optimization technique to mitigate the riverbank instability resulting from the outflow variation of hydropower plants. The effects of the water releases from the Bagnell Dam were investigated by computing a series of safety factors for 78 cross sections along the 81-mile stretch of the lower Osage River in relation to outflow events by using the integrated BSTEM model incorporated into the HEC-RAS model. The 1-D sediment transport and unsteady flow in …