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Che 260-001: Fluid Flow, David Venerus

Chemical and Materials Engineering Syllabi

No abstract provided.

Phen 603-101: Pharmeceutical Unit Operations: Processing Of Liquid And Dispersed-Phase Systems, Piero Armenante

Chemical and Materials Engineering Syllabi

No abstract provided.

Che 472-Hm1: Process And Plant Design, Nellone Reid

Chemical and Materials Engineering Syllabi

No abstract provided.

Che 489-101: Process Dynamics And Control, Sagnik Basuray

Chemical and Materials Engineering Syllabi

No abstract provided.

Che 349-001: Kinetics And Reactor Design, Xianqin Wang

Chemical and Materials Engineering Syllabi

No abstract provided.

Che 722-101: Additive Manufacturing And Applications, Murat Guvendiren

Chemical and Materials Engineering Syllabi

No abstract provided.

Che 472-001: Process And Plant Design, Nellone Reid

Chemical and Materials Engineering Syllabi

No abstract provided.

Che 626-101: Math Methods In Chemical Engineering, Ecevit Bilgili

Chemical and Materials Engineering Syllabi

No abstract provided.

Phys 121-005: Physics Ii, George Georgiou

Physics Syllabi

No abstract provided.

Phys 122-001: Electricity And Magnetism For Ece Applications, Andrew Gerrard

Physics Syllabi

No abstract provided.

Phys 122-003: Electricity And Magnetism For Ece Applications, Andrew Gerrard

Physics Syllabi

No abstract provided.

Phys 122-005: Electricity And Magnetism For Ece Applications, Andrew Gerrard

Physics Syllabi

No abstract provided.

Mtse 719-001: Physical Principles Of Characterization Of Solids, N. M. Ravindra

Physics Syllabi

No abstract provided.

Phil 334-451: Engineering Ethics, Daniel Estrada

Humanities Syllabi

No abstract provided.

Phil 334-453: Engineering Ethics, Daniel Estrada

Humanities Syllabi

No abstract provided.

Phil 334-455: Engineering Ethics, Daniel Estrada

Humanities Syllabi

No abstract provided.

Chem 336-101: Quantum Chemistry, Farnaz Shakib

Chemistry, Environmental and Forensic Science Syllabi

No abstract provided.

Chem 658-101: Advanced Physical Chemistry, Farnaz Shakib

Chemistry, Environmental and Forensic Science Syllabi

No abstract provided.

Biol 368-H01: Ecology & Evolution Of Disease, Gareth Russell

Biology Syllabi

No abstract provided.

Frsc 359-001: Physical Methods Of Forensics & Lab, Kevin Parmalee

Chemistry, Environmental and Forensic Science Syllabi

No abstract provided.

Colloidal Quantum Dot (Cqd) Based Mid-Wavelength Infrared Optoelectronics, Shihab Bin Hafiz

Dissertations

Colloidal quantum dot (CQD) photodetectors are a rapidly emerging technology with a potential to significantly impact today’s infrared sensing and imaging technologies. To date, CQD photodetector research is primarily focused on lead-chalcogenide semiconductor CQDs which have spectral response fundamentally limited by the bulk bandgap of the constituent material, confining their applications to near-infrared (NIR, 0.7-1.0 um) and short-wavelength infrared (SWIR, 1-2.5 um) spectral regions. The overall goal of this dissertation is to investigate a new generation of CQD materials and devices that advances the current CQD photodetector research toward the technologically important thermal infrared region of 3-5 ?m, known as …

On Non-Linear Network Embedding Methods, Huong Yen Le

Dissertations

As a linear method, spectral clustering is the only network embedding algorithm that offers both a provably fast computation and an advanced theoretical understanding. The accuracy of spectral clustering depends on the Cheeger ratio defined as the ratio between the graph conductance and the 2nd smallest eigenvalue of its normalizedLaplacian. In several graph families whose Cheeger ratio reaches its upper bound of Theta(n), the approximation power of spectral clustering is proven to perform poorly. Moreover, recent non-linear network embedding methods have surpassed spectral clustering by state-of-the-art performance with little to no theoretical understanding to back them.

The dissertation includes work …

Advances In Modeling Gas Adsorption In Porous Materials For The Characterization Applications, Max A. Maximov

Dissertations

The dissertation studies methods for mesoporous materials characterization using adsorption at various levels of scale and complexity. It starts with the topic introduction, necessary notations and definitions, recognized standards, and a literature review.

Synthesis of novel materials requires tailoring of the characterization methods and their thorough testing. The second chapter presents a nitrogen adsorption characterization study for silica colloidal crystals (synthetic opals). These materials have cage-like pores in the range of tens of nanometers. The adsorption model can be described within a macroscopic approach, based on the Derjaguin-Broekhoff-de Boer (DBdB) theory of capillary condensation. A kernel of theoretical isotherms is …

Exploring, Understanding, Then Designing: Twitter Users’ Sharing Behavior For Minor Safety Incidents, Mashael Yousef Almoqbel

Dissertations

Social media has become an integral part of human lives. Social media users resort to these platforms for various reasons. Users of these platforms spend a lot of time creating, reading, and sharing content, therefore, providing a wealth of available information for everyone to use. The research community has taken advantage of this and produced many publications that allow us to better understand human behavior. An important subject that is sometimes discussed and shared on social media is public safety. In the past, Twitter users have used the platform to share incidents, share information about incidents, victims and perpetrators, and …

Gradient Free Sign Activation Zero One Loss Neural Networks For Adversarially Robust Classification, Yunzhe Xue

Dissertations

The zero-one loss function is less sensitive to outliers than convex surrogate losses such as hinge and cross-entropy. However, as a non-convex function, it has a large number of local minima, andits undifferentiable attribute makes it impossible to use backpropagation, a method widely used in training current state-of-the-art neural networks. When zero-one loss is applied to deep neural networks, the entire training process becomes challenging. On the other hand, a massive non-unique solution probably also brings different decision boundaries when optimizing zero-one loss, making it possible to fight against transferable adversarial examples, which is a common weakness in deep learning …

Solar Flares As Observed In The Low Frequency Microwave Gyrosynchrotron Emission, Shaheda Begum Shaik

Dissertations

Solar flares involve the sudden catastrophic release of magnetic energy stored in the Sun’s corona. This dissertation focuses on investigating the low frequency, optically-thick gyrosynchrotron emission during solar flares for its spatial and spectral dynamics, characteristics, and role in the flare process.

The first part of this dissertation first addresses the spectral dynamics and characteristics of the source morphology. The high-resolution spectra of a set of microwave bursts observed by the Expanded Owens Valley Solar Array (EOVSA) during its commissioning phase in the 2.5-18 GHz frequency range with 1-s time resolution are presented here. Out of the 12 events analyzed …

Multi-Stage Stochastic Optimization And Reinforcement Learning For Forestry Epidemic And Covid-19 Control Planning, Sabah Bushaj

Dissertations

This dissertation focuses on developing new modeling and solution approaches based on multi-stage stochastic programming and reinforcement learning for tackling biological invasions in forests and human populations. Emerald Ash Borer (EAB) is the nemesis of ash trees. This research introduces a multi-stage stochastic mixed-integer programming model to assist forest agencies in managing emerald ash borer insects throughout the U.S. and maximize the public benets of preserving healthy ash trees. This work is then extended to present the first risk-averse multi-stage stochastic mixed-integer program in the invasive species management literature to account for extreme events. Significant computational achievements are obtained using …

Towards Adversarial Robustness With 01 Lossmodels, And Novel Convolutional Neural Netsystems For Ultrasound Images, Meiyan Xie

Dissertations

This dissertation investigates adversarial robustness with 01 loss models and a novel convolutional neural net systems for vascular ultrasound images.

In the first part, the dissertation presents stochastic coordinate descent for 01 loss and its sensitivity to adversarial attacks. The study here suggests that 01 loss may be more resilient to adversarial attacks than the hinge loss and further work is required.

In the second part, this dissertation proposes sign activation network with a novel gradient-free stochastic coordinate descent algorithm and its ensembling model. The study here finds that the ensembling model gives a high minimum distortion (as measured by …

Stochastic Programming And Agent-Based Simulation Approaches For Epidemics Control And Logistics Planning, Xuecheng Yin

Dissertations

This dissertation addresses the resource allocation challenges of fighting against infectious disease outbreaks. The goal of this dissertation is to formulate multi-stage stochastic programming and agent-based models to address the limitations of former literature in optimizing resource allocation for preventing and controlling epidemics and pandemics. In the first study, a multi-stage stochastic programming compartmental model is presented to integrate the uncertain disease progression and the logistics of resource allocation to control a highly contagious infectious disease. The proposed multi-stage stochastic program, which involves various disease growth scenarios, optimizes the distribution of treatment centers and resources while minimizing the total expected …

Modeling Dewetting, Demixing, And Thermal Effects In Nanoscale Metal Films, Ryan Howard Allaire

Dissertations

Thin film dynamics, particularly on the nanoscale, is a topic of extensive interest. The process by which thin liquids evolve is far from trivial and can lead to dewetting and drop formation. Understanding this process involves not only resolving the fluid mechanical aspects of the problem, but also requires the coupling of other physical processes, including liquid-solid interactions, thermal transport, and dependence of material parameters on temperature and material composition. The focus of this dissertation is on the mathematical modeling and simulation of nanoscale liquid metal films, which are deposited on thermally conductive substrates, liquefied by laser heating, and subsequently …