Engineering Commons^™

Nano-Enhanced Bioremediation For Oil Spills: A Review, Amber J. Pete, Bhuvnesh Bharti, Michael G. Benton

Chemical and Biochemical Engineering Faculty Research & Creative Works

Oil seepage and spills have lasting detrimental effects on the environment, especially on nearby marine ecosystems. Despite quick and safe removal of contaminating oil being of utmost importance, remediation methods have remained largely unchanged over the last 20+ years. Removal methods such as skimmers, in situ burning, and sorbents can be difficult to implement in inclement weather. Marine microorganisms consume spilled oil as a primary energy source in a method known as bioremediation. Recently the introduction of nanoparticles to areas contaminated by oil has emerged as a potential method to enhance the efficacy of oil degradation by marine microorganisms. Nanoparticles …

Optimization Of Organizational Design, Dyin Mabe, Guilherme Esmael, Manoel Burg, Patricia Soares, Leila Halawi

Publications

This study aims to present new techniques that airlines can use to gain efficiency through human resources allocation and keep up on track with the aviation industry’s challenging and constant- moving environment. The classical hierarchical structure that dominates most airlines today is not a prone environment for the proposed changes. The authors explore human resources optimization using the optimization software Lindo, mixed with Agile Methodology concepts and techniques. The authors also utilize evaluation score and talent mapping to develop a model for the best match between a Brazilian airline’s employees and tasks. The model considers productivity and cost.

Rebalancing Shared Mobility Systems By User Incentive Scheme Via Reinforcement Learning, Matthew Brian Schofield

Theses and Dissertations

Shared mobility systems regularly suffer from an imbalance of vehicle supply within the system, leading to users being unable to receive service. If such imbalance problems are not mitigated some users will not be serviced. There is an increasing interest in the use of reinforcement learning (RL) techniques for improving the resource supply balance and service level of systems. The goal of these techniques is to produce an effective user incentivization policy scheme to encourage users of a shared mobility system to slightly alter their travel behavior in exchange for a small monetary incentive. These slight changes in user behavior …

College Of Engineering News, Georgia Southern University

College of Engineering & Computing: News & Publications (2010-2023)

• James O'hara won a national award(CUR Engineering Division Student Research Video Contest)
• Austin Brant won a national award( CU Engineering Division Student Research Video Contest)

Urban Aerosol Size Distributions: A Global Perspective, Tianren Wu, Brandon E. Boor

Purdue University Libraries Open Access Publishing Fund

Urban aerosol measurements are necessary to establish associations between air pollution and human health outcomes and to evaluate the efficacy of air quality legislation and emissions standards. The measurement of urban aerosol particle size distributions (PSDs) is of particular importance as they enable characterization of size-dependent processes that govern a particle's transport, transformation, and fate in the urban atmosphere. PSDs also improve our ability to link air pollution to health effects through evaluation of particle deposition in the respiratory system and inhalation toxicity. To inform future measurements of urban aerosol observations, this paper reviews and critically analyzes the current state …

Computing Accurate Probabilistic Estimates Of One-D Entropy From Equiprobable Random Samples, Hoshin V. Gupta, Mohammed Reza Ehsani, Tirthankar Roy, Maria A. Sans-Fuentes, Uwe Ehret, Ali Behrangi

Department of Civil and Environmental Engineering: Faculty Publications

We develop a simple Quantile Spacing (QS) method for accurate probabilistic estimation of one-dimensional entropy from equiprobable random samples, and compare it with the popular Bin-Counting (BC) and Kernel Density (KD) methods. In contrast to BC, which uses equal-width bins with varying probability mass, the QS method uses estimates of the quantiles that divide the support of the data generating probability density function (pdf) into equal-probability-mass intervals. And, whereas BC and KD each require optimal tuning of a hyper-parameter whose value varies with sample size and shape of the pdf, QS only requires specification of the number of quantiles to …

Online Classrooms During Covid-19 Pandemic: A Survey Of Industrial Engineering Instructors In Indonesia, Ardiyanto Ardiyanto, Taufik Mulyadin, Adinda Mutiara Santi, I Gusti Bagus Budi Dharma

Higher Learning Research Communications

Objectives: The purpose of this descriptive study was to understand the instructional methods, quality, and challenges in online instruction as industrial engineering instructors in Indonesia transitioned from face-to-face to fully online instruction during the COVID-19 pandemic.

Methods: Instructors were invited to complete a survey that requested perceptions on methods, perceived quality, and challenges regarding course delivery and assessment in their online classrooms.

Results: Despite the fact that more than half of the participants (59%) had some training, the majority (63%) reported that they had no experience in conducting online classrooms. Furthermore, more than 50% of the participants described the quality …

The Feasibility Of 18f-Fdg Labeled Rbc And Pet/Ct Imaging Blood Perfusion And Vascular Dysfunction Measurements In Pre-Clinical Research, Shaowei Wang

USF Tampa Graduate Theses and Dissertations

Heart disease, dementia, and stroke are significant public health issues and leading causes of mortality and morbidity worldwide. Abnormalities in blood perfusion and vascular structures are seen in varieties of pathologies, including cerebrovascular diseases like stroke and dementia, hypertension, cardiovascular disease like atherosclerosis, diabetes, peripheral artery disease, and vasculitis, and tumor angiogenesis. Imaging perfusion/vascular abnormalities in these patients often plays a vital role in clinical diagnosis and treatment decisions.

Vascular diseases typically present as macrovascular or microvascular diseases. Microvascular disease (MVD) refers to vascular disease primarily affecting the arterioles, venules, and capillaries in various organs. Furthermore, MVD is widely found …

Windows Kernel Hijacking Is Not An Option: Memoryranger Comes To The Rescue Again, Igor Korkin

Journal of Digital Forensics, Security and Law

The security of a computer system depends on OS kernel protection. It is crucial to reveal and inspect new attacks on kernel data, as these are used by hackers. The purpose of this paper is to continue research into attacks on dynamically allocated data in the Windows OS kernel and demonstrate the capacity of MemoryRanger to prevent these attacks. This paper discusses three new hijacking attacks on kernel data, which are based on bypassing OS security mechanisms. The first two hijacking attacks result in illegal access to files open in exclusive access. The third attack escalates process privileges, without applying …

Alzheimer’S Disease Diagnostic Support Tool, Chelsea Fernandes, Shreya Venkatesh, Aiyushi Kumar

Computer Science and Engineering Senior Theses

Alzheimer’s Disease is the 6th leading cause of death overall and the most common cause of dementia in older people in the US. The prevalence of the disease is projected to increase in the next few decades and disproportionately impact low/middle income populations. Unfortunately, specialized doctors, such as neurologists, may not be present in situations where a diagnosis is necessary, resulting in the possibility of AD being overlooked at its early and most treatable stages. Our proposed application is a tool that can aid doctors in determining a probable AD diagnosis using an inputted combination of imaging data, biomarkers, patient …

Improved Hyperparameter Tuning For Graph Learning With Warm-Start Configuration, Drew Ligman

Computer Science and Engineering Senior Theses

With the increasing size and complexity of machine learning datasets, obtaining highly performing prediction models in various tasks has become increasingly difficult. In particular, the processs of hyperparameter optimization (HPO) contributes a significant portion of this cost. This work examines a specific graph-machine learning model, graph convolutional networks (GCN), to derive a hyperparameter configuration with optimal performance across a variety of datasets. We motivate our configuration theoretically and validate it empirically through comprehensive experimentation. We find that for GCN semi-supervised classification tasks, our configuration performs nearly optimally when compared against traditional HPO while only requiring a fraction of the budget. …

Bluetooth Security Of Colocated Apps On Android, Sean Kelker, Omar Garcia

Computer Science and Engineering Senior Theses

The Bluetooth protocol is used millions of times per day, as a means of short-range wireless communication. Many of these connections are between a phone running the Android operating system and an external device. Due to Android’s implementation of Bluetooth, however, unrelated applications that are co-located on the phone have the potential to stealthily send and receive communications from any device that is connected. Our project involves creating malicious applications to investigate the effectiveness of this attack on real-world devices, and we show that the vulnerability above has practical applications. We also create a defense against this attack by modifying …

Predictive Energy Optimization Model For Grid-Interactive Residential Buildings, Patrick J. Mccurdy

Mechanical Engineering Master's Theses

The consumption and production of energy are more dynamic as distributed energy resources (DER) such as solar photovoltaic (PV) are deployed within the electric distribution system. The traditional energy price at a predetermined rate cannot accommodate these dynamics and can lead to wasted energy and higher costs for both utility companies and consumers. Commercial building and residential energy management systems are usually on a fixed schedule and are not able to respond to changes in energy price instantaneously. There is a need for a real-time pricing structure that can accommodate the fluctuating cost of energy based on supply and demand, …

Dynamic Shading System, Alexander Kravtsov, Walker Battey

Interdisciplinary Design Senior Theses

Long exposure to UV-light radiation can lead to accelerated skin aging and skin cancer. Children are the most susceptible group to the dangers of high UV radiation because of their sensitive skin. Solar shading can provide the staff and clients of Kids on Campus with a way to prevent over-exposure to UV-light radiation by replacing the existing shading structure with a structure that offers significantly better protection from harmful rays. This new structure is also cost-effective, sustainable, and automated. By using a light calibrating sensor that calculates the UV index, we created a dynamic shading system to control and reduce …

Machine Learning Based Model For The Detection Of Brain Aneurysms From Mr Angiography, Katherine Becknell, Claire Bushnell, Rachel Fitzsimmons, Emily Sumner

Interdisciplinary Design Senior Theses

A brain aneurysm is a thin or weak spot on a blood vessel wall that expands and fills with blood. Brain aneurysms are very dangerous due to the fact that in most cases, patients do not show any symptoms. Because of this, aneurysms are difficult to diagnose unless it becomes very large or ruptures, resulting in fatal hemorrhage.

Aneurysms can be detected by a number of different brain imaging methods including Magnetic Resonance Imaging (MRI), Magnetic Resonance Angiography (MRA), Computed Tomography Angiography (CTA) and other imaging methods but for the sake of this report we will only be focusing on …

Chorine Conversion: Biological And Water Quality Impact On Activated Carbon Block Point Of Use Filters, Horace S. Jakpa

USF Tampa Graduate Theses and Dissertations

Point-of-use (POU) activated carbon (AC) filters are ubiquitous in many U.S. households. AC can reduce concentrations of lead, other heavy metals, and mitigate taste and odor issues. However, AC filters also remove residual disinfectants, thus allowing for the proliferation of microbes in the filter. In chloraminated systems, this can lead to localized, filter-induced nitrification. Most notably, high nitrite and nitrate in drinking water can cause methemoglobinemia (blue baby syndrome) in children under the age of three, raising public health concerns.

As a control measure for nitrification within distribution systems, utilities practice periodic, short-term secondary disinfectant switches from chloramine to free …

Artificial Intelligent Risk-Aware Autonomous Decision-Making In Resource-Constrained Computing Systems, Pavlos Athanasios Apostolopoulos

Electrical and Computer Engineering ETDs

Artificial Intelligent autonomous systems are becoming increasingly ubiquitous in daily life. Mobile devices for example provide mechanical-generated intelligent support to humans, with various degrees of autonomy, and are a key part of the recent autonomous revolution. Autonomous intelligent systems aim to understand and interact with their users in a timely manner, while many of them are characterized by constrained resources. Despite that, the average person does not act in a formulaic and risk-neutral manner but instead exhibits risk-aware attitudes when performing a task that includes sources of uncertainties. When humans make decisions, they explore their surroundings, understand the emerging risks, …

Spatiotemporal Interactions Between Surface Coal Mining And Land Cover And Use Changes, Nikolaos Paraskevis, Aikaterini Servou, Christos Roumpos, Francis Pavloudakis

Journal of Sustainable Mining

Long-term surface mining and land cover and use changes have been evidenced to have a critical relationship. This study conducts trend and correlation analysis by statistical tools to quantitatively evaluate this relationship in the Ptolemais (Northern Greece) coal mining area for the period 1990-2018. Firstly, based on Corine data and satellite images, a relative spatial indicator (RSI) was adopted to describe the mineral land areas. Secondly, land cover and use changes were spatially defined using Corine data and ArcGIS tools. The active mining area was then distinguished by dumping area, using Landsat satellite imagery and mining maps, and finally, mine …

Evaluating The Performance Of Extreme Learning Machine Technique For Ore Grade Estimation, Clara Akalanya Abuntori, Sulemana Al-Hassan, Daniel Mireku-Gyimah, Yao Yevenyo Ziggah

Journal of Sustainable Mining

Due to the complex geology of vein deposits and their erratic grade distributions, there is the tendency of overestimating or underestimating the ore grade. These estimated grade results determine the profitability of mining the ore deposit or otherwise. In this study, five Extreme Learning Machine (ELM) variants based on hard limit, sigmoid, triangular basis, sine and radial basis activation functions were applied to predict ore grade. The motive is that the activation function has been identified to play a key role in achieving optimum ELM performance. Therefore, assessing the extent of influence the activation functions will have on the final …

Selection Mining Methods Via Multiple Criteria Decision Analysis Using Topsis And Modification Of The Ubc Method, Mahrous Ali Mohamed Ali, Jong-Gwan Kim

Journal of Sustainable Mining

Mine designers often face difficulties in selecting an appropriate mining method; however, such a method should be selected based on ore and rock characteristics. The selection of mining methods can be considered a type of multi-criteria decision making, and this depends on many factors used in the selection process. The general method used in this field is the University of British Columbia (UBC) method, which determines the criteria of the properties that are compared to determine the best and worst of several mining methods. In this paper we used as new technique which define as Technique for Order of Preference …

Can Agricultural Management Induced Changes In Soil Organic Carbon Be Detected Using Mid-Infrared Spectroscopy?, Jonathan Sanderman, Kathleen Savage, Shree R.S. Dangal, Gabriel Duran, Charlotte Rivard, Michel A. Cavigelli, Hero T. Gollany, Virginia L. Jin, Mark A. Liebig, Emmanuel Chiwo Omondi, Yichao Rui, Catherine Stewart

Agricultural and Environmental Sciences Faculty Research

A major limitation to building credible soil carbon sequestration programs is the cost of measuring soil carbon change. Diffuse reflectance spectroscopy (DRS) is considered a viable low-cost alternative to traditional laboratory analysis of soil organic carbon (SOC). While numerous studies have shown that DRS can produce accurate and precise estimates of SOC across landscapes, whether DRS can detect subtle management induced changes in SOC at a given site has not been resolved. Here, we leverage archived soil samples from seven long-term research trials in the U.S. to test this question using mid infrared (MIR) spectroscopy coupled with the USDA-NRCS Kellogg …

Is Social Diversity Related To Misinformation Resistance? An Empirical Study On Social Communities, I Chang, Orion Sun, Jasper Sang Ahn

Computer Science and Engineering Senior Theses

Misinformation has become a pervasive issue on online social media. Whether it is spread purposefully with ill intent or accidentally through ignorance, misinformation can be dangerous and create confusion in those who are affected by it. The investigation presented in this paper found that no research has been performed that directly examine the correlation between a social community’s misinformation resistance and diversity. This project utilizes CrowdTangle, a tool to gather data from Facebook groups, along with machine learning models to determine if this correlation can be drawn. We were able to find correlations between some diversity metrics with misinformation resistance …

Development And Prospect Of Simulation Research In China, Xiaogang Qiu, Duan Hong, Xie Xu, Mengna Zhu

Journal of System Simulation

Abstract: It is important to treat modeling and simulation (M&S) as a discipline to advance its development. In China, M&S has been researched and applied over 40 years, and is gradually becoming an independent discipline. Modeling and simulating the complex systems are the challenge, however, this also brings grand opportunity for M&S to widen and improve itself. Since 1980s, the M&S community in China has realized the broad applications of M&S, comprehended M&S from multiple perspectives, conducted extensive research on basic questions, and discussed the composition of the basic simulation theory. By summarizing these achievements, the future works that have …

Multiple Object Tracking And Kinematic Simulation For Short Track Speed Skating, Li Qi, Hanlin Mo, Xiangdong Wang, Li Hua

Journal of System Simulation

Abstract: Aiming at the problem that it is difficult to obtain the motion data of each athlete in the short track speed skating competition, an algorithm flow of multiple object tracking and kinematic simulation is proposed. A local matching metric is proposed to deal with the partial occlusion in monocular video and improve the tracking stability and robustness. The motion simulation method based on homography mapping and derivative of fitted curve is realized to estimate kinematic parameters such as velocity and acceleration. The experiments on Skating Track Multiple ObjectTracking (STMOT) verified the effectiveness and superiority of the proposed methods.

Decomposition Furnace Outlet Temperature Prediction Based On Elasticnet And Lstm, Guangyu Yu, Xueping Dong, Xiangmin Wang, Gan Min

Journal of System Simulation

Abstract: The outlet temperature of the decomposition furnace is a key indicator in the cement production process. Aiming at the problem that traditional prediction methods only consider the influence of wind, coal, and materials, a temperature prediction model of ElasticNet combined with Long Short-Term Memory (LSTM) neural network is proposed. The ElasticNet-LSTM export temperature prediction model is constructed by using the ElasticNet method to estimate the parameters of different variables, fully considering the influencing factors and realizing the variable screening, and analyzing the influence of the number of hidden layers and nodes on the accuracy of the neural network. Simulation …

A Shared Memory Based Parallel Hierarchical Interest Matching Algorithm, Wenjie Tang, Junwei Cheng, Yiping Yao, Zhu Feng

Journal of System Simulation

Abstract: Interest matching plays an important role in distributed simulation. However, because of huge number of simulation entities and frequent change of regions, interest matching consumes tremendous computation in large scale simulations. The ubiquity of multicore urges us to improve the performance of interest matching by parallelization. A shared memory based parallel hierarchical interest matching algorithm is propose to solve the problem. It maps subscribe regions into a full binary tree, and compares update regions with the tree in parallel. Due to the associative relationship between adjacent nodes, unnecessary comparisons can be eliminated. The experimental results demonstrate that the …

Time-Delay Estimation For Mimo Delay Systems With Unknown Structures, Xuguang Wang, Mengjie Feng, Su Jie, Jiale Quan

Journal of System Simulation

Abstract: In the unknown-structure delay system modeling, time-delays lead to a mismatch between the system inputs and outputs on the timeline and cause low system modeling accuracy. A time-delay estimation method is proposed for the unknown-structure MIMO (Multiple-Input Multiple-Output) delay systems. A general mathematical description is given from the algebraic point of view, the delay correlation function is defined, and a quantitative constraint between system input-output and time-delay is constructed. A greedy time-delay search algorithm is introduced based on the delay correlation function. Simulation experiments and real data experiments show the availability of the proposed method.

Fault Detection Of Wind Turbine Bearing Based On Bo-Sdae Multi-Source Signal, Dinghui Wu, Zhichao Zhu, Xinhong Han

Journal of System Simulation

Abstract: Due to the discrepancy within signals from sensors of wind turbines caused by environmental interference, the fault detection results of wind turbine bearing will be affected and the multi-source signal fault diagnosis method is proposed to improve the reliability of fault detection. The time-domain and frequency-domain features of bearing vibration signals, noise signals and temperature signals are used for feature extraction,and then the features are transmitted to the stacked denoising autoencoders, which are optimized the hidden layer node structure by the Bayesian optimization algorithm to achieve multi-source signal feature fusion. Softmax function is used for classification. Experiments show that …

Rapid Development Technology Of Virtual Maintenance Training Simulation Model For Aviation Equipment, Rongqiang Li, Aibing Wen, Bin Hua, Jiajun Li, Jiang Bing

Journal of System Simulation

Abstract: Taking the practical application of the aircraft virtual maintenance training as the demand, the basic development process and technical means of the aircraft virtual maintenance training simulation model are analyzed, which solves the technical bottleneck in the popularization and application of the large-scale engineering. Aiming at the crucial problems such as the low efficiency in the development of maintenance training simulation model and the difficulties in updating the model, a rapid development process to support the large-scale engineering applications is proposed. The principles and implementation ways of three key technologies supporting the rapid development of virtual maintenance training simulation …

Day-Ahead Dispatching Model Of Source-Load Coordination Based On Response Behavior To Real-Time Pricing, Liu Yun, Han Song, Qiuli Huang

Journal of System Simulation

Abstract: In order to give full play to the regulating role of electricity price on the market, considering the difference of consumers' response behavior to real-time pricing, consumers are divided into short-term consumers, mixed consumers and long-term consumers, and the real-time pricing models of three types of consumers are constructed based on the electricity price elasticity matrix. On this basis, a day-ahead dispatching model of source-load coordination based on consumer’s response behavior to real-time pricing is established. With the help of the MOST toolkits in MATPOWER and the Mosek solver, the arithmetic analysis is developed in a modified IEEE 57-buses …