Digital Commons Network^™

Far-End Crosstalk Modeling And Prediction For High-Speed Pcb Design With Inhomogeneous Dielectric Layers (Idls), Yuanzhuo Liu

Doctoral Dissertations

"Far-end crosstalk (FEXT) noise is a critical factor that affects signal integrity performance in high-speed systems. The FEXT level is sensitive to the inhomogeneity of the dielectric layers in fabricated printed circuit boards (PCB). The stripline is laminated by multiple inhomogeneous dielectric layers (IDL). The dielectric layers of the stripline are laminated with epoxy resin and glass bundles. The dielectric permittivity of the epoxy resin and glass bundles are different, which causes the inhomogeneity of the dielectric layers while also increasing the FEXT magnitude. The dielectric of the microstrip in printed circuit boards (PCB) fabrication usually consists of two layers: …

Application Of Machine Learning In Geophysics: Ranking Teleseismic Shear Wave Splitting Measurements And Classifying Different Types Of Earthquakes, Yanwei Zhang

Doctoral Dissertations

"During the past decades, applications of Machine Learning have been explosively developed to solve various academic and industrial problems, and over-human performance has been shown in diverse areas. In geophysical research, Machine Learning, especially Convolutional Neural Network (CNN), has been applied in numerous studies and demonstrated considerable potential. In this study, we applied CNN to solve two geophysical problems, ranking teleseismic shear splitting (SWS) measurements and classifying different types of earthquakes.

For ranking teleseismic SWS measurements, we utilized a CNN-based method to automatically select reliable SWS measurements. The CNN was trained by human-verified teleseismic SWS measurements and tested using synthetic …

Disorder Effects In Frustrated Magnets And Absorbing State Transitions, Xuecheng Ye

Doctoral Dissertations

"Correlation, topology, and disorder can fundamentally affect the properties of interacting many-particle systems. After a short introduction which covers the basic concepts of phase transitions and scaling as well as the physics of Josephson junctions, the dissertation focuses on three separate projects.

The first project is motivated by the stripe and nematic phases observed e.g. in cuprate superconductors and iron pnictides. To understand the effects of disorder on such phases, we have investigated the behavior of the diluted J₁-J₂ Ising model. Spinless impurities generate a random-field disorder for the spin-density (stripe) order parameter, which destroys the stripe …

Sensitivity Of The Two-Fluid Model To Constitutive Correlations For Large Diameter Pipes, Alexander Lee Swearingen

Doctoral Dissertations

"Multiphase flows are a significant factor in nuclear reactor operations. In order to understand this behavior in reactor systems, system analysis codes are used to simulate reactor conditions. Due to the nature of the nuclear industry, simulations predicting the void development in the core are required to be highly accurate. This work evaluated the sensitivity of the void fraction and interfacial area concentration predictions to changes in correlations used to calculate three parameters that are used to complete the interfacial drag calculation. The three parameters evaluated were drift-flux, void fraction covariance, and interfacial area concentration. The change in drift-flux correlation …

A Variable Node Optimization Model For Byzantine Fault Tolerant Systems, Ian Robert Fulton

Masters Theses

“Byzantine Fault Tolerance (BFT) has been a major subject of study over the last two decades with increasing societal dependance on secure, correct, and reliable computer systems and online services. This research presents a model for high-level optimization of emerging systems that rely on these BFT algorithms and use a variable numbers of decision nodes. The model highlights the relationship between the security of a system and its efficiency. Two experiments were performed to determine system performance by varying the number of compromised nodes, decision nodes, and total nodes. They examine the probability that a transaction will be compromised based …

Predicting Radiated Emissions From A Cable Harness Through Component Level Tests, Fuwei Ma

Masters Theses

“In this work, a procedure is developed to predict the radiated emissions from a cable harness using component-level tests. Direct measurement on the engine control unit is utilized to accurately characterize the equivalent common mode source voltages and impedance associated with the device. The cable harness geometry is reduced using the equivalent cable bundle approach by lumping wires according to the source and load impedance compared with characteristic impedance of the harness, which dramatically reduces the measurement effort and allows practical 3D full-wave simulation of the radiated emissions. Radiated emissions are predicted from an engine control unit (ECU) and an …

Zinc Plating From Alkaline Non-Cyanide Bath, Abdul J. Mohammed

Masters Theses

“Alkaline non-cyanide zinc plating baths are preferred when trying to avoid the toxicity of cyanide baths or corrosivity of acid baths. Without additives, alkaline zincate baths produce powdery non-adherent deposits which have no use in commercial plating. Additives must be added at optimum concentrations to produce adherent, bright and uniform zinc deposits. In this study electrochemical tests were used to determine effects of additives on cathodic polarization, throwing power and morphology of deposits. Current density distribution in a unique bath of 37.5 g L^-1 Zn and 210 g L^-1 NaOH was modelled using COMSOL and validated two plating …

Characterization Of Cermet Fuel For Nuclear Thermal Propulsion (Ntp), James Floyd Mudd

Masters Theses

“A manned flight to Mars is met with many technical challenges, not the least of which is the development of propulsion technology capable of moving a transit vehicle from Earth orbit to Mars orbit. NASA is investigating Nuclear Thermal Propulsion (NTP) as a way of reducing flight time and providing the option for a mid-mission abort. NTP, which uses a high temperature nuclear reactor to heat a propellant, requires advanced fuel materials capable of withstanding temperatures well in excess of 2000 K. Among the fuel options are ceramic metal (cermet) composites composed of refractory metals and Ultra-High Temperature Ceramics (UHTCs). …

Industry 4.0 Remanufacturing: A Novel Approach Towards Smart Remanufacturing, Prashansa Ragampeta

Masters Theses

“Smart remanufacturing has become more popular in recent years as a result of its multiple benefits and the growing need for society to encourage a circular economy that leads to sustainability. One of the most common end-of-life (EoL) choices that can lead to a circular economy is remanufacturing. As a result, at the end-of-life stage of a product, it is critical to prioritize this choice over other accessible options because it is the only recovery option that retains the same quality as a new product. This work focuses on the numerous technologies that can aid in the improvement of smart …

Validation Of Athlet-Cd With Cora-28 Test, Murat Tuter

Masters Theses

“Following the incidents at Chernobyl and Fukushima, severe accidents at nuclear power plants (NPP) have become a global concern. These accidents generally occur because of a failure in the reactor cooling system (RCS) and result in the melting of the reactor core and fission product release. This event is mostly caused by a LOCA, loss of flow accident, station blackout or loss of heat sink. During a severe accident, generation of hydrogen as a result of steam-zircaloy fuel cladding is a significant safety concern. To better understand and prevent the hydrogen generation issue, safety related experiments and safety related codes …

Several Problems In Nonlinear Schrödinger Equations, Tim Van Hoose

Masters Theses

“We study several different problems related to nonlinear Schrödinger equations….

We prove several new results for the first equation: a modified scattering result for both an averaged version of the equation and the full equation, as well as a set of Strichartz estimates and a blowup result for the 3d cubic problem.

We also present an exposition of the classical work of Bourgain on invariant measures for the second equation in the mass-subcritical regime”--Abstract, page iv.

Numerical Investigations Of 2-D Magnetic Nozzles On Pulsed Plasma Plumes, Joshua Daniel Burch

Masters Theses

"This research presents studies of a novel type of magnetic nozzle that allows for three-dimensional (3-D) steering of a plasma plume. Numerical simulations were performed using Tech-X's USim® software to quantify the nozzle's capabilities. A2-D planar magnetic nozzle was applied to plumes of a nominal pulsed inductive plasma (PIP) source with discharge parameters similar to those of Missouri S&T's Missouri Plasmoid Experiment (MPX). Argon and xenon plumes were considered. Simulations were verified and validated through a mesh convergence study as well as comparison with available experimental data. Periodicity was achieved over the simulation run time and phase angle samples were …

Comprehensive Evaluation Of Novel Medium-Temperature And High-Temperature Resistant Re-Crosslinkable Preformed Particle Gels For Conformance Control, Zhanmiao Zhai

Masters Theses

"Gel treatment has been widely used to control excessive water production and improve oil recovery in mature oilfields. In comparison to traditional preformed particle gel (PPG), re-cross linkable preformed particle gel (RPPG) has a significant advantage in treating abnormal features such as open fractures, fracture-like channels, and void space conduits (VSC). This research provides a comprehensive evaluation of two novel RPPG products developed in our lab: medium-temperature resistant RPPG (MT-RPPG) for a Middle East reservoir and a high-temperature resistant RPPG (HT-RPPG) for North Sea reservoirs (130 ^oC).

We assessed the effect of the monomer types and concentration, pH, salinity, …

Integrating Remote Sensing And Model-Based Datasets In A Machine Learning Model To Map Global Subsidence Associated With Groundwater Withdrawal, Md Fahim Hasan

Masters Theses

"Quantifying groundwater storage loss is becoming increasingly essential globally due limited availability of this major hydrologic component and its long recharge time. Groundwater overdraft gives rises to multiple adverse impacts including land subsidence and permanent groundwater storage loss. In absence of spatially dense monitoring network, publicly available in-situ data, and uniform monitoring strategies, it is challenging to assess the sustained losses from overexploitation of this resource. Remote sensing based techniques have the capacity to fill this gap to increase our groundwater monitoring capacities. Exploring the interrelation between groundwater pumping and land subsidence using remote sensing datasets can be a very …

Improving Virtual Synchronous Generator Control In Microgrids Using Fuzzy Logic Control, Oroghene Oboreh-Snapps, Rui Bo, Buxin She, Fangxing Fran Li, Hantao Cui

Electrical and Computer Engineering Faculty Research & Creative Works

Virtual synchronous generators (VSG) are designed to mimic the inertia and damping characteristics of synchronous generators (SG), which can improve the frequency response of a microgrid. Unlike synchronous generators whose inertia and damping are restricted by the physical characteristics of the SG, VSG parameters can be more flexibly controlled to adapt to different disturbances. This paper therefore proposes a fuzzy logic controller designed to adaptively set the parameters of the VSG during a frequency event to ensure an improved frequency nadir and rate of change of frequency (ROCOF) response. The proposed control method is implemented and tested on the power …

Two-Level Targeter Convergence Study For Collinear Libration Point Spacecraft Formations, Donna Jennings, Henry J. Pernicka

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Spacecraft formation flying has attracted an increasing amount attention over the past several decades including a growing interest in relative motion at the collinear lib ration points. This current work builds on previous efforts by further developing and characterizing a two-level targeting (TLT) algorithm used to determine relative motion at lib ration points by performing a convergence study. A parametric study was conducted to identify the sensitivity of the algorithm to a variety of inputs and constraints. The parametric study revealed that the two-level targeting algorithm convergence properties significantly improve when using a higher order initialization estimate. The size of …

Monetization For Content Generation And User Engagement On Social Media Platforms: Evidence From Paid Q&A, Jonathan Hua Ye, Cecil Eng Huang Chua

Business and Information Technology Faculty Research & Creative Works

Social media platforms want to increase their valuation in terms of total content quantity and user engagement. Monetization is often used to induce user content generation. However, research documents that while monetization increases the quantity of specific kinds of content, it does not necessarily increase the total content quantity or user engagement (i.e., platform value). Furthermore, the impact of monetization may depend on the social status of content creators. This article investigates paid question and answer (paid Q&A). Based on expectancy theory and relevant research, this article hypothesizes the effects of introducing paid Q&A on both total content quantity and …

Noise Resilient Learning For Attack Detection In Smart Grid Pmu Infrastructure, Prithwiraj Roy, Shameek Bhattacharjee, Sahar Abedzadeh, Sajal K. Das

Computer Science Faculty Research & Creative Works

Falsified data from compromised Phasor Measurement Units (PMUs) in a smart grid induce Energy Management Systems (EMS) to have an inaccurate estimation of the state of the grid, disrupting various operations of the power grid. Moreover, the PMUs deployed at the distribution layer of a smart grid show dynamic fluctuations in their data streams, which make it extremely challenging to design effective learning frameworks for anomaly-based attack detection. In this paper, we propose a noise resilient learning framework for anomaly-based attack detection specifically for distribution layer PMU infrastructure, that show real time indicators of data falsifications attacks while offsetting the …

Cansafe: An Mtd Based Approach For Providing Resiliency Against Dos Attack Within In-Vehicle Networks, Ayan Roy, Sanjay Kumar Madria

Computer Science Faculty Research & Creative Works

Trending towards autonomous transportation systems, modern vehicles are equipped with hundreds of sensors and actuators that increase the intelligence of the vehicles with a higher level of autonomy, as well as facilitate increased communication with entities outside the in-vehicle network. However, increase in a contact point with the outside world has exposed the controller area network (CAN) of a vehicle to remote security vulnerabilities. In particular, an attacker can inject fake high priority messages within the CAN through the contact points, while preventing legitimate messages from controlling the CAN (Denial-of-Service (DoS) attack). In this paper, we propose a Moving Target …

Rssafe: Personalized Driver Behavior Prediction For Safe Driving, Bhumika, Debasis Das, Sajal K. Das

Computer Science Faculty Research & Creative Works

While the increased demand for taxi services like Uber, Lyft, Hailo, Ola, Grab, Cabify etc. provides livelihood to many drivers, the desire to raise income forces the drivers to work very hard without rest. However, continuous journeys not only affect their health, but also lead to abnormal driving behavior such as rash driving, swerving, sideslipping, sudden brakes, or weaving, leading to accidents in the worst cases. Motivated by the severity of rising accidents and health issues among drivers, this paper proposes a recommendation system, called RsSafe, for the safety of drivers. Aiming to improve the driving quality and the driver's …

Toward Feature-Preserving Vector Field Compression, Xin Liang, Sheng Di, Franck Cappello, Mukund Raj, Chunhui Liu, Kenji Ono, Zizhong Chen, Tom Peterka, Hanqi Guo

Computer Science Faculty Research & Creative Works

The objective of this work is to develop error-bounded lossy compression methods to preserve topological features in 2D and 3D vector fields. Specifically, we explore the preservation of critical points in piecewise linear and bilinear vector fields. We define the preservation of critical points as, without any false positive, false negative, or false type in the decompressed data, (1) keeping each critical point in its original cell and (2) retaining the type of each critical point (e.g., saddle and attracting node). The key to our method is to adapt a vertex-wise error bound for each grid point and to compress …

Delivery With Uavs: A Simulated Dataset Via Ats, Giulio Rigoni, Cristina M. Pinotti, Bhumika, Debasis Das, Sajal K. Das

Computer Science Faculty Research & Creative Works

We consider a delivery food service operated by Unmanned Aerial Vehicles (UAVs). Due to the absence of a dataset on UAVs deliveries in the literature, and since it is not possible to perform real tests, we create a dataset using an open-Air Traffic Simulator (ATS). Precisely, we converted a set of food deliveries operated by wheeled vehicles, proposed in the literature [1], into a set of simulated UAVs deliveries. For each delivery, we ran a UAV flight from the source to the destination. The results showed that, as expected, the UAV's course is shorter than the vehicle trajectory on the …

Active Learning Augmented Folded Gaussian Model For Anomaly Detection In Smart Transportation, Venkata Praveen Kumar Madhavarapu, Prithwiraj Roy, Shameek Bhattacharjee, Sajal K. Das

Computer Science Faculty Research & Creative Works

Smart transportation networks have become instrumental in smart city applications with the potential to enhance road safety, improve the traffic management system and driving experience. A Traffic Message Channel (TMC) is an IoT device that records the data collected from the vehicles and forwards it to the Roadside Units (RSUs). This data is further processed and shared with the vehicles to inquire the fastest route and incidents that can cause significant delays. The failure of the TMC sensors can have adverse effects on the transportation network. In this paper, we propose a Gaussian distribution-based trust scoring model to identify anomalous …

Improving Age Of Information With Interference Problem In Long-Range Wide Area Networks, Preti Kumari, Hari Prabhat Gupta, Tanima Dutta, Sajal K. Das

Computer Science Faculty Research & Creative Works

Low Power Wide Area Networks (LPWAN) offer a promising wireless communications technology for Internet of Things (IoT) applications. Among various existing LPWAN technologies, Long-Range WAN (LoRaWAN) consumes minimal power and provides virtual channels for communication through spreading factors. However, LoRaWAN suffers from the interference problem among nodes connected to a gateway that uses the same spreading factor. Such interference increases data communication time, thus reducing data freshness and suitability of LoRaWAN for delay-sensitive applications. To minimize the interference problem, an optimal allocation of the spreading factor is requisite for determining the time duration of data transmission. This paper proposes a …

Mobility Management In Industrial Iot Environments, Marco Pettorali, Francesca Righetti, Carlo Vallati, Sajal K. Das, Giuseppe Anastasi

Computer Science Faculty Research & Creative Works

The Internet Engineering Task Force (IETF) has defined the 6TiSCH architecture to enable the Industrial Inter-net of Things (IIoT). Unfortunately, 6TiSCH does not provide mechanisms to manage node mobility, while many industrial applications involve mobile devices (e.g., mobile robots or wearable devices carried by workers). In this paper, we consider the Synchronized Single-hop Multiple Gateway framework to manage mobility in 6TiSCH networks. For this framework, we address the problem of positioning Border Routers in a deployment area, which is similar to the "Art Gallery"problem, proposing an efficient deployment policy for Border Routers based on geometrical rules. Moreover, we define a …

Mdz: An Efficient Error-Bounded Lossy Compressor For Molecular Dynamics, Kai Zhao, Sheng Di, Danny Perez, Xin Liang, Zizhong Chen, Franck Cappello

Computer Science Faculty Research & Creative Works

Molecular dynamics (MD) has been widely used in today's scientific research across multiple domains including materials science, biochemistry, biophysics, and structural biology. MD simulations can produce extremely large amounts of data in that each simulation could involve a large number of atoms (up to trillions) for a large number of timesteps (up to hundreds of millions). In this paper, we perform an in-depth analysis of a number of MD simulation datasets and then develop an efficient error-bounded lossy compressor that can significantly improve the compression ratios. The contributions are fourfold. (1) We characterize a number of MD datasets and summarize …

Spade: Multi-Stage Spam Account Detection For Online Social Networks, Federico Concone, Giuseppe Lo Re, Marco Morana, Sajal K. Das

Computer Science Faculty Research & Creative Works

In recent years, Online Social Networks (OSNs) have radically changed the way people communicate. The most widely used platforms, such as Facebook, Youtube, and Instagram, claim more than one billion monthly active users each. Beyond these, news-oriented micro-blogging services, e.g., Twitter, are daily accessed by more than 120 million users sharing contents from all over the world. Unfortunately, legitimate users of the OSNs are mixed with malicious ones, which are interested in spreading unwanted, misleading, harmful, or discriminatory content. Spam detection in OSNs is generally approached by considering the characteristics of the account under analysis, its connection with the rest …

Locality-Aware Qubit Routing For The Grid Architecture, Avah Banerjee, Xin Liang, R. Tohid

Computer Science Faculty Research & Creative Works

Due to the short decohorence time of qubits available in the NISQ-era, it is essential to pack (minimize the size and or the depth of) a logical quantum circuit as efficiently as possible given a sparsely coupled physical architecture. In this work we introduce a locality-aware qubit routing algorithm based on a graph theoretic framework. Our algorithm is designed for the grid and certain 'grid-like' architectures. We experimentally show the competitiveness of algorithm by comparing it against the approximate token swapping algorithm, which is used as a primitive in many state-of-the-art quantum trans pilers. Our algorithm produces circuits of comparable …

Leveraging Spanning Tree To Detect Colluding Attackers In Federated Learning, Priyesh Ranjan, Federico Coro, Ashish Gupta, Sajal K. Das

Computer Science Faculty Research & Creative Works

Federated learning distributes model training among multiple clients who, driven by privacy concerns, perform training using their local data and only share model weights for iterative aggregation on the server. In this work, we explore the threat of collusion attacks from multiple malicious clients who pose targeted attacks (e.g., label flipping) in a federated learning configuration. By leveraging client weights and the correlation among them, we develop a graph-based algorithm to detect malicious clients. Finally, we validate the effectiveness of our algorithm in presence of varying number of attackers on a classification task using a well-known Fashion-MNIST dataset.

Development Of Terminology Of Word-Formation Synthesis. Features Of The Terminological System (Based On The Verbs Of The Sound Of The Russian Language), Irina V. Ivliyeva

Arts, Languages and Philosophy Faculty Research & Creative Works

English Abstract:

The purpose of the research is to present the terminology of word-formation synthesis as an organized system, to identify the stages of development of relevant terms. The scientific novelty of the research lies in the fact that a structured corpus of terms of word-formation synthesis with elements of definitional analysis is introduced into scientific circulation. different stages of research. The system of terms of modification synthesis is applied and studied in practice – in the author's search program for web extraction of verbs of sound from the databases of modern dictionaries and the Russian National Corpus.

Russian Abstract: …