Digital Commons Network^™

Personalizing Student Graduation Paths Using Expressed Student Interests, Nicolas Charles Dobbins

Masters Theses

"This work proposes an intelligent recommender approach to facilitate personalized education and help students in planning their path to graduation. The original research contribution of this work is to develop a recommender approach that pervasively personalizes and optimizes a student’s path to graduation by accounting for the student’s career interests and academic background. The approach is a multi-objective optimization problem, subject to institutional constraints, with the goal of optimizing the graduation path with respect to one or more criteria, such as time-to-graduation, credit hours taken, and alignment with student’s career interests. The efficacy of the approach is illustrated and verified …

Understanding Charge Effects On Marked Ball Wear Rates – A Corrosion Study, John Bailey Fletcher

Masters Theses

"To measure the wear rates of grinding balls within a ball mill, marked ball wear tests (MBWTs) have been used extensively. Using the wear rates from a MBWT, operators select the most cost-effective media for their grinding application. One factor that a MBWT does not account for is the possible interaction between different media materials which could affect their corrosion rates. Galvanic coupling between dissimilar metals can cause significant changes in their corrosion rates. While galvanic interactions between minerals and grinding media have been studied, the interaction between dissimilar media has not. Corrosion rates and potentials of modern high carbon …

A Novel Approach To Estimate Rock Strength Parameters From Multistage Triaxial Tests (The A-Has Method), Abo Taleb T. Al-Hameedi, Husam H. Alkinani, Shari Dunn-Norman, Munir Aldin, Sudarshan Govindarajan

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Rock strength parameters are vital to creating robust geomechanical models for wellbore stability, sand production, and hydraulic fracturing. Static rock strength parameters can be estimated from single stage triaxial tests (SST) or multistage triaxial tests (MST). Although SST tests are the most accurate way to estimate rock strength parameters, SST tests require at least four to five core plugs to estimate rock strength parameters. Thus, MST tests are used as an alternative method to estimate rock strength parameters from only one core plug to overcome the limitation of materials and save time and money. However, the currently used method to …

Replacing Combustion Engines With Hydrogen Fuel Cells To Power Mining Haul Trucks: Challenges And Opportunities, Ayorinde Akinrinlola

Masters Theses

"With the proven advantage of higher energy density in hydrogen fuel cells over batteries, there is potential to apply fuel cells to power mining haul trucks. This study aims to evaluate the technical and economic feasibility of hydrogen fuel cell electric mine trucks as an alternative to current mine haul trucks. Specifically, the project: (1) developed an economic framework for evaluating the integration of renewable energy powered haul trucks into mining; and (2) applied vehicle drivetrain and energy simulation in Matlab/Simulink to elucidate the challenges and opportunities of incorporating hydrogen fuel cell technology into the current form factors of mine …

Modeling The Reactor Time-Dependent Delayed Particle Tail With Monte Carlo N-Particle (Mcnp) Version 6.2, Eli James Boland

Masters Theses

"Energy is deposited into experiment packages due to post-shutdown decay heat created from delayed particles. Modeling these delayed particles in a reactor assists researchers in quantifying the expected energy deposition sources to an experiment package before irradiation. This paper focuses on modeling the delayed particles in a reactor in MCNP6.2 by capturing a reactor as a source, converting this source capture to a source definition, applying appropriate physics such as activation and photonuclear interactions, and finally using proper tallies to create the expected delayed particle tail of a reactor.

To capture the source distribution, the FMESH capability within MCNP was …

Ds-Menet For The Classification Of Citrus Disease, Xuyao Liu, Yaowen Hu, Guoxiong Zhou, Weiwei Cai, Mingfang He, Jialei Zhan, Yahui Hu, Liujun Li

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Affected by various environmental factors, citrus will frequently suffer from diseases during the growth process, which has brought huge obstacles to the development of agriculture. This paper proposes a new method for identifying and classifying citrus diseases. Firstly, this paper designs an image enhancement method based on the MSRCR algorithm and homomorphic filtering algorithm optimized by Laplacian (HFLF-MS) to highlight the disease characteristics of citrus. Secondly, we designed a new neural network DS-MENet based on the DenseNet-121 backbone structure. In DS-MENet, the regular convolution in Dense Block is replaced with depthwise separable convolution, which reduces the network parameters. The ReMish …

Ds-Menet For The Classification Of Citrus Disease, Xuyao Liu, Yaowen Hu, Guoxiong Zhou, Weiwei Cai, Mingfang He, Jialei Zhan, Yahui Hu, Liujun Li

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Affected by various environmental factors, citrus will frequently suffer from diseases during the growth process, which has brought huge obstacles to the development of agriculture. This paper proposes a new method for identifying and classifying citrus diseases. Firstly, this paper designs an image enhancement method based on the MSRCR algorithm and homomorphic filtering algorithm optimized by Laplacian (HFLF-MS) to highlight the disease characteristics of citrus. Secondly, we designed a new neural network DS-MENet based on the DenseNet-121 backbone structure. In DS-MENet, the regular convolution in Dense Block is replaced with depthwise separable convolution, which reduces the network parameters. The ReMish …

Mdam-Drnet: Dual Channel Residual Network With Multi-Directional Attention Mechanism In Strawberry Leaf Diseases Detection, Tingjing Liao, Ruoli Yang, Peirui Zhao, Wenhua Zhou, Mingfang He, Liujun Li

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

The growth of strawberry plants is affected by a variety of strawberry leaf diseases. Yet, due to the complexity of these diseases' spots in terms of color and texture, their manual identification requires much time and energy. Developing a more efficient identification method could be imperative for improving the yield and quality of strawberry crops. To that end, here we proposed a detection framework for strawberry leaf diseases based on a dual-channel residual network with a multi-directional attention mechanism (MDAM-DRNet). (1) In order to fully extract the color features from images of diseased strawberry leaves, this paper constructed a color …

Mdam-Drnet: Dual Channel Residual Network With Multi-Directional Attention Mechanism In Strawberry Leaf Diseases Detection, Tingjing Liao, Ruoli Yang, Peirui Zhao, Wenhua Zhou, Mingfang He, Liujun Li

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

The growth of strawberry plants is affected by a variety of strawberry leaf diseases. Yet, due to the complexity of these diseases' spots in terms of color and texture, their manual identification requires much time and energy. Developing a more efficient identification method could be imperative for improving the yield and quality of strawberry crops. To that end, here we proposed a detection framework for strawberry leaf diseases based on a dual-channel residual network with a multi-directional attention mechanism (MDAM-DRNet). (1) In order to fully extract the color features from images of diseased strawberry leaves, this paper constructed a color …

Region-Adaptive, Error-Controlled Scientific Data Compression Using Multilevel Decomposition, Qian Gong, Ben Whitney, Chengzhu Zhang, Xin Liang, Anand Rangarajan, Jieyang Chen, Lipeng Wan, Paul Ullrich, Qing Liu, Robert Jacob, Sanjay Ranka, Scott Klasky

Computer Science Faculty Research & Creative Works

The increase of computer processing speed is significantly outpacing improvements in network and storage bandwidth, leading to the big data challenge in modern science, where scientific applications can quickly generate much more data than that can be transferred and stored. As a result, big scientific data must be reduced by a few orders of magnitude while the accuracy of the reduced data needs to be guaranteed for further scientific explorations. Moreover, scientists are often interested in some specific spatial/temporal regions in their data, where higher accuracy is required. The locations of the regions requiring high accuracy can sometimes be prescribed …

Wikimarks: Harvesting Relevance Benchmarks From Wikipedia, Laura Dietz, Shubham Chatterjee, Connor Lennox, Sumanta Kashyapi, Pooja Oza, Ben Gamari

Computer Science Faculty Research & Creative Works

We provide a resource for automatically harvesting relevance benchmarks from Wikipedia - which we refer to as "Wikimarks"to differentiate them from manually created benchmarks. Unlike simulated benchmarks, they are based on manual annotations of Wikipedia authors. Studies on the TREC Complex Answer Retrieval track demonstrated that leaderboards under Wikimarks and manually annotated benchmarks are very similar. Because of their availability, Wikimarks can fill an important need for Information Retrieval research. We provide a meta-resource to harvest Wikimarks for several information retrieval tasks across different languages: paragraph retrieval, entity ranking, query-specific clustering, outline prediction, and relevant entity linking and many more. …

An Explicit Time-Domain Finite-Element Boundary Integral Method For Analysis Of Electromagnetic Scattering, Ming Dong, Liang Chen, Lijun Jiang, Ping Li, Hakan Bagci

Electrical and Computer Engineering Faculty Research & Creative Works

A numerical scheme, which hybridizes the element-level dual-field time-domain finite-element domain decomposition method (ELDDM) and the time-domain boundary integral (TDBI) method to accurately and efficiently analyze open-region transient electromagnetic scattering problems, is proposed. Element-level decomposition decouples Maxwell equations on a discretization element from those on its neighboring elements using equivalent currents defined on their faces. For any element inside the computation domain, the equivalent currents are obtained from fields in the neighboring elements. For any element on the boundary of the computation domain, the equivalent currents are obtained using the fields generated by TDBI. To generate these fields, TDBI 'radiates' …

Foldy-Wouthuysen Transformation In Strong Magnetic Fields And Relativistic Corrections For Quantum Cyclotron Energy Levels, Albert Wienczek, Christopher Moore, Ulrich D. Jentschura

Physics Faculty Research & Creative Works

We carry out a direct iterative Foldy-Wouthuysen transformation of a general Dirac Hamiltonian coupled to an electromagnetic field, including the anomalous magnetic moment. The transformation is carried out through an iterative disentangling of the particle and antiparticle Hamiltonians in the expansion for higher orders of the momenta. The time-derivative term from the unitary transformation is found to be crucial in supplementing the transverse component of the electric field in higher orders. Final expressions are obtained for general combined electric and magnetic fields, including strong magnetic fields. The time derivative of the electric field is shown to enter only in the …

Internal Energy Balance And Aerodynamic Heating Predictions For Hypersonic Turbulent Boundary Layers, Matthew Barone, Gary L. Nicholson, Lian Duan

Mechanical and Aerospace Engineering Faculty Research & Creative Works

The elemental equation governing heat transfer in aerodynamic flows is the internal energy equation. For a boundary layer flow, a double integration of the Reynolds-averaged form of this equation provides an expression of the wall heat flux in terms of the integrated effects, over the boundary layer, of various physical processes: turbulent dissipation, mean dissipation, turbulent heat flux, etc. Recently available direct numerical simulation data for a Mach 11 cold-wall turbulent boundary layer allows a comparison of the exact contributions of these terms in the energy equation to the wall heat flux with their counterparts modeled in the Reynolds-averaged Navier-Stokes …

A Proactive Risk Assessment Framework To Maximize Schedule Benefits Of Modularization In Construction Projects, Mohamad Abdul Nabi, Islam H. El-Adaway

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Various studies developed models and decision support tools to assess the feasibility and optimize the use of modularization. However, none has explored the schedule benefits of modular construction. This paper fills this knowledge gap. To this end, the authors completed the following: (1) analyzed the criticalities of the various modular risk factors on potential schedule savings using data collected from 48 industry professionals, (2) investigated the schedule savings associated with the use of modularization using data collected from 68 modular construction projects, and (3) developed an interrelated assessment model to calculate the schedule savings of using modularization. The provided model …

Life Cycle Cost Analysis Of High Friction Surface Treatment Applications, Eslam Deef-Allah, Korrenn Broaddus, Magdy Abdelrahman

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Life cycle cost analyses for high friction surface treatment (HFST) applications were executed relying on a Microsoft Excel program developed by the researchers. Calcined bauxite (CB), five CB alternatives, and epoxy binder were utilized in the HFST applications. The aggregates' performances were evaluated through the aggregate image measurement system (AIMS) before and after Micro-Deval polishing. The performance of the HFST applications was evaluated by the dynamic friction tester (DFT) and British pendulum (BP). The major purpose of this program was to present a rational method for converting different input data (project and material specifics) to comparable output data (net present …

Quantification Of The State Of Practice Of Offsite Construction And Related Technologies: Current Trends And Future Prospects, Rayan H. Assaad, Islam H. El-Adaway, Makarand Hastak, Kim Lascola Needy

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Although some researchers and practitioners have perceived that the current reliance on offsite construction methods is high, other studies have hypothesized that the use of offsite construction techniques is still considered to be somehow limited. To this end, this paper aims to quantify the state of practice of offsite construction in terms of current trends and future prospects for the overall industry as well as the following main sectors: industrial, building and commercial, and infrastructure. First, a questionnaire was formed, pilot-tested, distributed, and completed by 100 construction practitioners. Second, the questionnaire's internal and external validity and reliability were examined using …

The Impact Of Offsite Construction On The Workforce: Required Skillset And Prioritization Of Training Needs, Rayan H. Assaad, Islam H. El-Adaway, Makarand Hastak, Kim Lascola Needy

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Offsite construction has showed great potential in addressing many of the industry's problems. While multiple research efforts have been directed at examining different offsite construction aspects, few studies investigated the workforce-related aspects. Therefore, this study aims to address this knowledge gap by examining the impact of offsite construction on the workforce, as represented by the following five workforce categories: offsite, onsite, engineering and design, construction and fabrication, and administrative workforce. To this end, this paper (1) determined the impact of offsite construction on the skillset (reskilling or upskilling) and the demand (shrink or growth) for the offsite and onsite construction …

Mgard+: Optimizing Multilevel Methods For Error-Bounded Scientific Data Reduction, Xin Liang, Ben Whitney, Jieyang Chen, Lipeng Wan, Qing Liu, Dingwen Tao, James Kress, David Pugmire, Matthew Wolf, Norbert Podhorszki, Scott Klasky

Computer Science Faculty Research & Creative Works

Nowadays, data reduction is becoming increasingly important in dealing with the large amounts of scientific data. Existing multilevel compression algorithms offer a promising way to manage scientific data at scale but may suffer from relatively low performance and reduction quality. In this paper, we propose MGARD+, a multilevel data reduction and refactoring framework drawing on previous multilevel methods, to achieve high-performance data decomposition and high-quality error-bounded lossy compression. Our contributions are four-fold: 1) We propose to leverage a level-wise coefficient quantization method, which uses different error tolerances to quantize the multilevel coefficients. 2) We propose an adaptive decomposition method which …

Classification Of Teleseismic Shear Wave Splitting Measurements: A Convolutional Neural Network Approach, Yanwei Zhang, Stephen S. Gao

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Shear wave splitting (SWS) analysis is widely used to provide critical constraints on crustal and mantle structure and dynamic models. In order to obtain reliable splitting measurements, an essential step is to visually verify all the measurements to reject problematic measurements, a task that is increasingly time consuming due to the exponential increase in the amount of data. In this study, we utilized a convolutional neural network (CNN) based method to automatically select reliable SWS measurements. The CNN was trained by human-verified teleseismic SWS measurements and tested using synthetic SWS measurements. Application of the trained CNN to broadband seismic data …

Ultrasmall Nanodiamonds: Perspectives And Questions, Shery L.Y. Chang, Philipp Reineck, Anke Krueger, Vadym Mochalin

Chemistry Faculty Research & Creative Works

Nanodiamonds are at the heart of a plethora of emerging applications in areas ranging from nanocomposites and tribology to nanomedicine and quantum sensing. The development of alternative synthesis methods, a better understanding, and the availability of ultrasmall nanodiamonds of less than 3 nm size with a precisely engineered composition, including the particle surface and atomic defects in the diamond crystal lattice, would mark a leap forward for many existing and future applications. Yet today, we are unable to accurately control nanodiamond composition at the atomic scale, nor can we reliably create and isolate particles in this size range. In this …

Ultrafast Error-Bounded Lossy Compression For Scientific Datasets, Xiaodong Yu, Sheng Di, Kai Zhao, Jiannan Tian, Dingwen Tao, Xin Liang, Franck Cappello

Computer Science Faculty Research & Creative Works

Today's scientific high-performance computing applications and advanced instruments are producing vast volumes of data across a wide range of domains, which impose a serious burden on data transfer and storage. Error-bounded lossy compression has been developed and widely used in the scientific community because it not only can significantly reduce the data volumes but also can strictly control the data distortion based on the user-specified error bound. Existing lossy compressors, however, cannot offer ultrafast compression speed, which is highly demanded by numerous applications or use cases (such as in-memory compression and online instrument data compression). In this paper, we propose …

Characterization Of Competing Halogen- And Hydrogen-Bonding Motifs In Simple Mixed Dimers Of Hcn And Hx (X = F, Cl, Br, And I), Morgan A. Perkins, Gregory S. Tschumper

Chemistry Faculty Research & Creative Works

This work performs the first systematic comparison of hydrogen- and halogen-bonded configurations of the HCN/HX mixed dimer, where X = F, Cl, Br, and I. Eleven different minima have been characterized for these four heterogeneous dimers near the CCSD(T) complete basis set (CBS) limit. For each complex, two different hydrogen-bonded minima were identified: the global minimum where HX acts as the hydrogen bond donor and a local minimum where HX acts as the hydrogen bond acceptor. A halogen-bonded local minimum was also identified for all but the fluorine mixed dimer. To the best of our knowledge, three of the minima …

Complex Rupture And Triggered Aseismic Creep During The 14 August 2021 Haiti Earthquake From Satellite Geodesy, Jeremy Maurer, R. Dutta, A. Vernon, S. Vajedian

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

The 2021 August 14 MW 7.2 Nippes, Haiti earthquake occurred 75 km west of the epicenter of the 2010 Leogane earthquake (Haiti) on the transpressive Caribbean - North America plate boundary. We present an updated fault map for Hispaniola and model coseismic and early postseismic fault slip using Interferometric Synthetic Aperture Radar and pixel offsets. We find the earthquake ruptured multiple segments of the Enriquillo-Plantain Garden Fault Zone. Slip occurred in two main sub-events on either side of a restraining bend at Pic Macaya, with ∼2.7 m of peak reverse-slip east of the bend. To the west, slip jumps the …

Mpc-Stanet: Alzheimer’S Disease Recognition Method Based On Multiple Phantom Convolution And Spatial Transformation Attention Mechanism, Yujian Liu, Kun Tang, Weiwei Cai, Aibin Chen, Guoxiong Zhou, Liujun Li, Runmin Liu

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Alzheimer's disease (AD) is a progressive neurodegenerative disease with insidious and irreversible onset. The recognition of the disease stage of AD and the administration of effective interventional treatment are important to slow down and control the progression of the disease. However, due to the unbalanced distribution of the acquired data volume, the problem that the features change inconspicuously in different disease stages of AD, and the scattered and narrow areas of the feature areas (hippocampal region, medial temporal lobe, etc.), the effective recognition of AD remains a critical unmet need. Therefore, we first employ class-balancing operation using data expansion and …

Mpc-Stanet: Alzheimer’S Disease Recognition Method Based On Multiple Phantom Convolution And Spatial Transformation Attention Mechanism, Yujian Liu, Kun Tang, Weiwei Cai, Aibin Chen, Guoxiong Zhou, Liujun Li, Runmin Liu

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Alzheimer's disease (AD) is a progressive neurodegenerative disease with insidious and irreversible onset. The recognition of the disease stage of AD and the administration of effective interventional treatment are important to slow down and control the progression of the disease. However, due to the unbalanced distribution of the acquired data volume, the problem that the features change inconspicuously in different disease stages of AD, and the scattered and narrow areas of the feature areas (hippocampal region, medial temporal lobe, etc.), the effective recognition of AD remains a critical unmet need. Therefore, we first employ class-balancing operation using data expansion and …

Analysis Of Federated Scheduling For Integer-Valued Workloads, Marion Sudvarg, Chris Gill

Computer Science Faculty Research & Creative Works

In federated scheduling of parallel real-time tasks on multiprocessor systems, high-utilization tasks are allocated dedicated processors on which they execute exclusively. Several methods exist for allocating a sufficient number of processors to guarantee that each task meets its deadline. In this paper, we propose two new strategies for allocating unit-speed cores to tasks with integer workload and deadline values. The first method can be performed in constant time for each high-utilization task, given the task's total workload, critical-path length, and deadline. The second method exploits the DAG structure of high-utilization tasks, providing a potentially better schedule in pseudo-polynomial time. We …

Pattern Recognition For Steam Flooding Field Applications Based On Hierarchical Clustering And Principal Component Analysis, Na Zhang, Mingzhen Wei, Baojun Bai, Xiaopeng Wang, Jian Hao, Shun Jia

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Steam flooding is a complex process that has been considered as an effective enhanced oil recovery technique in both heavy oil and light oil reservoirs. Many studies have been conducted on different sets of steam flooding projects using the conventional data analysis methods, while the implementation of machine learning algorithms to find the hidden patterns is rarely found. In this study, a hierarchical clustering algorithm (HCA) coupled with principal component analysis is used to analyze the steam flooding projects worldwide. The goal of this research is to group similar steam flooding projects into the same cluster so that valuable operational …

Pattern Recognition For Steam Flooding Field Applications Based On Hierarchical Clustering And Principal Component Analysis, Na Zhang, Mingzhen Wei, Baojun Bai, Xiaopeng Wang, Jian Hao, Shun Jia

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Steam flooding is a complex process that has been considered as an effective enhanced oil recovery technique in both heavy oil and light oil reservoirs. Many studies have been conducted on different sets of steam flooding projects using the conventional data analysis methods, while the implementation of machine learning algorithms to find the hidden patterns is rarely found. In this study, a hierarchical clustering algorithm (HCA) coupled with principal component analysis is used to analyze the steam flooding projects worldwide. The goal of this research is to group similar steam flooding projects into the same cluster so that valuable operational …

Synthesis, Physicochemical Characterization, And Catalytic Evaluation Of Fe3+-Containing Ssz-70 Zeolite, Christopher M. Lew, Cong Yan Chen, Gary J. Long, Fernande Grandjean, Andrew S. Ichimura, Dan Xie, Nicolás A. Grosso-Giordano, Khetpakorn Chakarawet, Howard S. Lacheen, Kurt O. Jensen, Abraham Martinez, Alexander Katz, Bi Zeng Zhan, Stacey I. Zones

Chemistry Faculty Research & Creative Works

Whereas one-dimensional, 10-membered ring zeolites are typically used for hydroisomerization, Fe3⁺-containing SSZ-70 (Fe-SSZ-70) shows remarkable isomerization selectivity for a zeolite containing 12- and partially blocked 14-membered rings, in addition to 10-membered rings. Fe-SSZ-70 was compared to Al3⁺-containing SSZ-70 (Al-SSZ-70) in constraint index and n-decane hydrocracking tests. Fe-SSZ-70 exhibited a 74% total isomer yield (64% yield of monobranched isomers and 10% cracking yield) at 85% conversion compared to 49% total isomer yield (41% yield of monobranched isomers and 36% cracking yield) for Al-SSZ-70 at the same conversion. The selectivity to isomerization is attributed to the weaker acid …