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Ce 742-102: Geotechniques Of Earthquake Engineering, Jay Meegoda Jan 2022

Ce 742-102: Geotechniques Of Earthquake Engineering, Jay Meegoda

Civil and Environmental Engineering Syllabi

No abstract provided.


Ce 321-002: Water Resources Engineering, Thomas Olenik Jan 2022

Ce 321-002: Water Resources Engineering, Thomas Olenik

Civil and Environmental Engineering Syllabi

No abstract provided.


Ce 443-002: Foundation Design, Andrew Ciancia Jan 2022

Ce 443-002: Foundation Design, Andrew Ciancia

Civil and Environmental Engineering Syllabi

No abstract provided.


Ene 262-002: Introduction To Environmental Engineering, Michael Furrey Jan 2022

Ene 262-002: Introduction To Environmental Engineering, Michael Furrey

Civil and Environmental Engineering Syllabi

No abstract provided.


Ene 662-852: Site Remediation, Michael Hornsby Jan 2022

Ene 662-852: Site Remediation, Michael Hornsby

Civil and Environmental Engineering Syllabi

No abstract provided.


Ene 663-102: Water Chemistry, Lucia Rodriguez Freire Jan 2022

Ene 663-102: Water Chemistry, Lucia Rodriguez Freire

Civil and Environmental Engineering Syllabi

No abstract provided.


Mech 234-002: Engineering Mechanics, Geraldine Milano Jan 2022

Mech 234-002: Engineering Mechanics, Geraldine Milano

Civil and Environmental Engineering Syllabi

No abstract provided.


Mech 234-004: Engineering Mechanics, Geraldine Milano Jan 2022

Mech 234-004: Engineering Mechanics, Geraldine Milano

Civil and Environmental Engineering Syllabi

No abstract provided.


Mech 237-002: Strength Of Materials, Eduardo Castro Jan 2022

Mech 237-002: Strength Of Materials, Eduardo Castro

Civil and Environmental Engineering Syllabi

No abstract provided.


Mech 237-004: Strength Of Materials, Eduardo Castro Jan 2022

Mech 237-004: Strength Of Materials, Eduardo Castro

Civil and Environmental Engineering Syllabi

No abstract provided.


Mech 237-010: Strength Of Materials, Eduardo Castro Jan 2022

Mech 237-010: Strength Of Materials, Eduardo Castro

Civil and Environmental Engineering Syllabi

No abstract provided.


Mech 237-012: Strength Of Materials, Eduardo Castro Jan 2022

Mech 237-012: Strength Of Materials, Eduardo Castro

Civil and Environmental Engineering Syllabi

No abstract provided.


Mech 237-106: Strength Of Materials, Eduardo Castro Jan 2022

Mech 237-106: Strength Of Materials, Eduardo Castro

Civil and Environmental Engineering Syllabi

No abstract provided.


Mech 237-108: Strength Of Materials, Eduardo Castro Jan 2022

Mech 237-108: Strength Of Materials, Eduardo Castro

Civil and Environmental Engineering Syllabi

No abstract provided.


Mech 237-006: Strength Of Materials, Geraldine Milano Jan 2022

Mech 237-006: Strength Of Materials, Geraldine Milano

Civil and Environmental Engineering Syllabi

No abstract provided.


Mech 237-008: Strength Of Materials, Geraldine Milano Jan 2022

Mech 237-008: Strength Of Materials, Geraldine Milano

Civil and Environmental Engineering Syllabi

No abstract provided.


Mech 237-102: Strength Of Materials, Geraldine Milano Jan 2022

Mech 237-102: Strength Of Materials, Geraldine Milano

Civil and Environmental Engineering Syllabi

No abstract provided.


Mech 237-104: Strength Of Materials, Geraldine Milano Jan 2022

Mech 237-104: Strength Of Materials, Geraldine Milano

Civil and Environmental Engineering Syllabi

No abstract provided.


Mech 320-102: Statics And Mechanics Of Materials, Medhat Attara Jan 2022

Mech 320-102: Statics And Mechanics Of Materials, Medhat Attara

Civil and Environmental Engineering Syllabi

No abstract provided.


Stem For Success Inaugural Annual Report, James Lipuma, Bruce G. Bukiet, Cristo Leon Jan 2022

Stem For Success Inaugural Annual Report, James Lipuma, Bruce G. Bukiet, Cristo Leon

STEM for Success Resources

Report on the work done in 2022 by STEM for Success


Exposing And Fixing Causes Of Inconsistency And Nondeterminism In Clustering Implementations, Xin Yin Dec 2021

Exposing And Fixing Causes Of Inconsistency And Nondeterminism In Clustering Implementations, Xin Yin

Dissertations

Cluster analysis aka Clustering is used in myriad applications, including high-stakes domains, by millions of users. Clustering users should be able to assume that clustering implementations are correct, reliable, and for a given algorithm, interchangeable. Based on observations in a wide-range of real-world clustering implementations, this dissertation challenges the aforementioned assumptions.

This dissertation introduces an approach named SmokeOut that uses differential clustering to show that clustering implementations suffer from nondeterminism and inconsistency: on a given input dataset and using a given clustering algorithm, clustering outcomes and accuracy vary widely between (1) successive runs of the same toolkit, i.e., nondeterminism, and …


Model Checks For Two-Sample Location-Scale, Atefeh Javidialsaadi Dec 2021

Model Checks For Two-Sample Location-Scale, Atefeh Javidialsaadi

Dissertations

Two-sample location-scale refers to a model that permits a pair of standardized random variables to have a common distribution. This means that if X1 and X2 are two random variables with means µ1 and µ2 and standard deviations ?1 and ?2, then (X1 - µ1)/?1 and (X2 - µ2)/?2 have some common unspecified standard or base distribution F0. Function-based hypothesis testing for these models refers to formal tests that would help determine whether or not two samples may have come from some location-scale …


On Performance Optimization And Prediction Of Parallel Computing Frameworks In Big Data Systems, Haifa Alquwaiee Dec 2021

On Performance Optimization And Prediction Of Parallel Computing Frameworks In Big Data Systems, Haifa Alquwaiee

Dissertations

A wide spectrum of big data applications in science, engineering, and industry generate large datasets, which must be managed and processed in a timely and reliable manner for knowledge discovery. These tasks are now commonly executed in big data computing systems exemplified by Hadoop based on parallel processing and distributed storage and management. For example, many companies and research institutions have developed and deployed big data systems on top of NoSQL databases such as HBase and MongoDB, and parallel computing frameworks such as MapReduce and Spark, to ensure timely data analyses and efficient result delivery for decision making and business …


Coherent Control Of Dispersive Waves, Jimmie Adriazola Dec 2021

Coherent Control Of Dispersive Waves, Jimmie Adriazola

Dissertations

This dissertation addresses some of the various issues which can arise when posing and solving optimization problems constrained by dispersive physics. Considered here are four technologically relevant experiments, each having their own unique challenges and physical settings including ultra-cold quantum fluids trapped by an external field, paraxial light propagation through a gradient index of refraction, light propagation in periodic photonic crystals, and surface gravity water waves over shallow and variable seabeds. In each of these settings, the physics can be modeled by dispersive wave equations, and the technological objective is to design the external trapping fields or propagation media such …


Private And Federated Deep Learning: System, Theory, And Applications For Social Good, Han Hu Dec 2021

Private And Federated Deep Learning: System, Theory, And Applications For Social Good, Han Hu

Dissertations

During the past decade, drug abuse continues to accelerate towards becoming the most severe public health problem in the United States. The ability to detect drug­abuse risk behavior at a population scale, such as among the population of Twitter users, can help to monitor the trend of drug­abuse incidents. However, traditional methods do not effectively detect drug­abuse risk behavior in tweets, mainly due to the sparsity of such tweets and the noisy nature of tweets. In the first part of this dissertation work, the task of classifying tweets as containing drug­abuse risk behavior or not, is studied. Millions of public …


Hydrophobically Modified Isosorbide Dimethacrylates As Biomaterials For Bisphenol A Free Dental Fillings, Bilal Marie Dec 2021

Hydrophobically Modified Isosorbide Dimethacrylates As Biomaterials For Bisphenol A Free Dental Fillings, Bilal Marie

Dissertations

Amalgam and Bisphenol A glycerolate dimethacrylate (BisGMA) are the main dental filling materials in use today. Because of the negative perception of amalgam and its lower esthetic appeal, as well as the desire to replace the endocrine disruptor Bisphenol A, which is the building block of BisGMA, there has been a critical need to search for safer alternatives to these dental filling materials.

Isosorbide is a sugar-based molecule generally recognized as safe. It has been extensively studied as a replacement to the Bisphenol A core in various materials. However, isosorbide is extremely hygroscopic, and water uptake in dental fillings causes …


Experimental And Computational Studies Of Functionalized Carbon Nanotubes For Use In Energy Storage Devices And Membranes, Emine S. Karaman Dec 2021

Experimental And Computational Studies Of Functionalized Carbon Nanotubes For Use In Energy Storage Devices And Membranes, Emine S. Karaman

Dissertations

Electrolytes with good interfacial stability are a crucial component of any electrochemical device. The development of novel gel polymer electrolytes (GEs) with good interface stability and better manufacturability is important for the development of the next generation electrochemical devices. Gel electrolytes are hybrid electrolyte materials, combining benefits of both liquid and solid systems. Compared with liquid and solid electrolytes, GEs open new design opportunities and do not require rigorous encapsulation methods. In this dissertation, studies on functionalized carbon nanotubes (fCNTs) and graphene oxide (GO) doped polyvinyl alcohol (PVA) based gel electrolytes (GEs) are reported. The ionic conductivity and mechanical strength …


A Practical Approach To Automated Software Correctness Enhancement, Aleksandr Zakharchenko Dec 2021

A Practical Approach To Automated Software Correctness Enhancement, Aleksandr Zakharchenko

Dissertations

To repair an incorrect program does not mean to make it correct; it only means to make it more-correct, in some sense, than it is. In the absence of a concept of relative correctness, i.e. the property of a program to be more-correct than another with respect to a specification, the discipline of program repair has resorted to various approximations of absolute (traditional) correctness, with varying degrees of success. This shortcoming is concealed by the fact that most program repair tools are tested on basic cases, whence making them absolutely correct is not clearly distinguishable from making them relatively more-correct. …


Parameter Estimation And Inference Of Spatial Autoregressive Model By Stochastic Gradient Descent, Gan Luan Dec 2021

Parameter Estimation And Inference Of Spatial Autoregressive Model By Stochastic Gradient Descent, Gan Luan

Dissertations

Stochastic gradient descent (SGD) is a popular iterative method for model parameter estimation in large-scale data and online learning settings since it goes through the data in only one pass. While SGD has been well studied for independent data, its application to spatially-correlated data largely remains unexplored. This dissertation develops SGD-based parameter estimation and statistical inference algorithms for the spatial autoregressive (SAR) model, a common model for spatial lattice data.

This research contains three parts. (I) The first part concerns SGD estimation and inference for the SAR mean regression model. A new SGD algorithm based on maximum likelihood estimator (MLE) …


Scalable Scientific Data Management On High-Performance Computing Systems, Zhenbo Qiao Dec 2021

Scalable Scientific Data Management On High-Performance Computing Systems, Zhenbo Qiao

Dissertations

As high-performance computing (HPC) is being scaled up to exascale to accommodate new modeling and simulation needs, I/O has continued to be a major bottleneck in the end-to-end scientific processes. To bridge the widening gap between compute and I/O, and enable data to be more efficiently stored and analyzed, simulation outputs need to be refactored, reduced, and appropriately mapped to storage tiers. Also, a major question that the community is striving to answer is how to co-design data storage and complex physics-rich analytics in a way that the time to knowledge can be minimized in post-processing. As HPC storage systems …