In Operando Mechanism Analysis On Nanocrystalline Silicon Anode Material For Reversible And Ultrafast Sodium Storage, 2018 University of Wollongong

#### In Operando Mechanism Analysis On Nanocrystalline Silicon Anode Material For Reversible And Ultrafast Sodium Storage, Lei Zhang, Xianluo Hu, Chaoji Chen, Haipeng Guo, Xiaoxiao Liu, Gengzhao Xu, Haijian Zhong, Shuang Cheng, Peng Wu, Jiashen Meng, Yunhui Huang, Shi Xue Dou, Hua-Kun Liu

*Australian Institute for Innovative Materials - Papers*

Presently, lithium-ion batteries (LIBs) are the most promising commercialized electrochemical energy storage systems. Unfortunately, the limited resource of Li results in increasing cost for its scalable application and a general consciousness of the need to find new type of energy storage technologies. Very recently, substantial effort has been invested to sodium-ion batteries (SIBs) due to their effectively unlimited nature of sodium resources. Furthermore, the potential of Li/Li+ is 0.3 V lower than that of Na/Na+, which makes it more effective to limit the electrolyte degradation on the outer surface of the electrode.[1] Nevertheless, one major obstacle ...

Iterative Matrix Factorization Method For Social Media Data Location Prediction, 2018 Harvey Mudd College

#### Iterative Matrix Factorization Method For Social Media Data Location Prediction, Natchanon Suaysom

*HMC Senior Theses*

Since some of the location of where the users posted their tweets collected by social media company have varied accuracy, and some are missing. We want to use those tweets with highest accuracy to help fill in the data of those tweets with incomplete information. To test our algorithm, we used the sets of social media data from a city, we separated them into training sets, where we know all the information, and the testing sets, where we intentionally pretend to not know the location. One prediction method that was used in (Dukler, Han and Wang, 2016) requires appending one-hot ...

Recursive Non-Local Means Filter For Video Denoising, 2017 University of Dayton

#### Recursive Non-Local Means Filter For Video Denoising, Redha A. Ali, Russell C. Hardie

*Electrical and Computer Engineering Faculty Publications*

In this paper, we propose a computationally efficient algorithm for video denoising that exploits temporal and spatial redundancy. The proposed method is based on non-local means (NLM). NLM methods have been applied successfully in various image denoising applications. In the single-frame NLM method, each output pixel is formed as a weighted sum of the center pixels of neighboring patches, within a given search window.

The weights are based on the patch intensity vector distances. The process requires computing vector distances for all of the patches in the search window. Direct extension of this method from 2D to 3D, for video ...

Cybercrime Deterrence And International Legislation: Evidence From Distributed Denial Of Service Attacks, 2017 Singapore Management University

#### Cybercrime Deterrence And International Legislation: Evidence From Distributed Denial Of Service Attacks, Kai-Lung Hui, Seung Hyun Kim, Qiu-Hong Wang

*Research Collection School Of Information Systems*

In this paper, we estimate the impact of enforcing the Convention on Cybercrime (COC) on deterring distributed denial of service (DDOS) attacks. Our data set comprises a sample of real, random spoof-source DDOS attacks recorded in 106 countries in 177 days in the period 2004-2008. We find that enforcing the COC decreases DDOS attacks by at least 11.8 percent, but a similar deterrence effect does not exist if the enforcing countries make a reservation on international cooperation. We also find evidence of network and displacement effects in COC enforcement. Our findings imply attackers in cyberspace are rational, motivated by ...

Asymptotic Counting Formulas For Markoff-Hurwitz Tuples, 2017 The Graduate Center, City University of New York

#### Asymptotic Counting Formulas For Markoff-Hurwitz Tuples, Ryan Ronan

*All Graduate Works by Year: Dissertations, Theses, and Capstone Projects*

The Markoff equation is a Diophantine equation in 3 variables first studied in Markoff's celebrated work on indefinite binary quadratic forms. We study the growth of solutions to an n variable generalization of the Markoff equation, which we refer to as the Markoff-Hurwitz equation. We prove explicit asymptotic formulas counting solutions to this generalized equation with and without a congruence restriction. After normalizing and linearizing the equation, we show that all but finitely many solutions appear in the orbit of a certain semigroup of maps acting on finitely many root solutions. We then pass to an accelerated subsemigroup of ...

Some Results In Combinatorial Number Theory, 2017 The Graduate Center, City University of New York

#### Some Results In Combinatorial Number Theory, Karl Levy

*All Graduate Works by Year: Dissertations, Theses, and Capstone Projects*

The first chapter establishes results concerning equidistributed sequences of numbers. For a given $d\in\mathbb{N}$, $s(d)$ is the largest $N\in\mathbb{N}$ for which there is an $N$-regular sequence with $d$ irregularities. We compute lower bounds for $s(d)$ for $d\leq 10000$ and then demonstrate lower and upper bounds $\left\lfloor\sqrt{4d+895}+1\right\rfloor\leq s(d)< 24801d^{3} + 942d^{2} + 3$ for all $d\geq 1$. In the second chapter we ask if $Q(x)\in\mathbb{R}[x]$ is a degree $d$ polynomial such that for $x\in[x_k]=\{x_1,\cdots,x_k\}$ we have $|Q(x)|\leq 1$, then how big can its lead coefficient be? We prove that there is a unique polynomial, which we call $L_{d,[x_k]}(x)$, with maximum lead coefficient under these constraints and construct an algorithm that generates $L_{d,[x_k]}(x)$.

Developing Grounded Goals Through Instant Replay Learning, 2017 Swarthmore College

#### Developing Grounded Goals Through Instant Replay Learning, Lisa Meeden, Douglas S. Blank

*Computer Science Faculty Research and Scholarship*

This paper describes and tests a developmental architecture that enables a robot to explore its world, to find and remember interesting states, to associate these states with grounded goal representations, and to generate action sequences so that it can re-visit these states of interest. The model is composed of feed-forward neural networks that learn to make predictions at two levels through a dual mechanism of motor babbling for discovering the interesting goal states and instant replay learning for developing the grounded goal representations. We compare the performance of the model with grounded goal representations versus random goal representations, and find ...

A Weighted Möbius Function, 2017 Portland State University

#### A Weighted Möbius Function, Derek Garton

*Mathematics and Statistics Faculty Publications and Presentations*

Fix an odd prime ℓ and let **G** be the poset of isomorphism classes of finite abelian** ℓ-**groups, ordered by inclusion. If** ξ:G→R ^{≥0} **is a discrete probability distribution on

**G**and

**A ∈ G**, define the

**A**th moment of

**ξ**to be . The question of determining conditions that ensure

**ξ**is completely determined by its moments has been of recent interest in many problems of Cohen–Lenstra type. Furthermore, recovering

**ξ**from its moments requires a new Möbius-type inversion formula on

**G**. In this paper, we define this function, relate it to the classical Möbius function ...

Investigation Into The Formation Of Information Security Influence: Network Analysis Of An Emerging Organisation, 2017 RMIT University

#### Investigation Into The Formation Of Information Security Influence: Network Analysis Of An Emerging Organisation, Duy Dang-Pham, Siddhi Pittayachawan, Vince Bruno

*Siddhi Pittayachawan*

Low-Communication, Parallel Multigrid Algorithms For Elliptic Partial Differential Equations, 2017 University of Colorado, Boulder

#### Low-Communication, Parallel Multigrid Algorithms For Elliptic Partial Differential Equations, Wayne Mitchell

*Applied Mathematics Graduate Theses & Dissertations*

When solving elliptic partial differential equations (PDE's) multigrid algorithms often provide optimal solvers and preconditioners capable of providing solutions with O(N) computational cost, where N is the number of unknowns. As parallelism of modern super computers continues to grow towards exascale, however, the cost of communication has overshadowed the cost of computation as the next major bottleneck for multigrid algorithms. Typically, multigrid algorithms require O((log P)^2) communication steps in order to solve a PDE problem to the level of discretization accuracy, where P is the number of processors. This has inspired the development of new algorithms ...

Rethinking Urban Green Infrastructure As A Means To Promote Avian Conservation, 2017 The University of San Francisco

#### Rethinking Urban Green Infrastructure As A Means To Promote Avian Conservation, Allen Lau

*Master's Projects and Capstones*

There is an under-recognized potential for cities to use urban green infrastructure to contribute to avian biodiversity conservation. At the global scale, climate change and growing urbanization are primary global drivers leading to decline and homogenization in world bird populations. Birds are fundamental and intricate species in ecosystems, and even in urban areas, act as indicator and regulator species contributing to healthy ecosystem function. While many cities have recognized the economic and social benefits associated with green spaces, such as the vast benefits ecosystem services provide to the urban dweller, the use of green spaces to concurrently contribute to avian ...

Comparison Of Visual Datasets For Machine Learning, 2017 Purdue University

#### Comparison Of Visual Datasets For Machine Learning, Kent Gauen, Ryan Dailey, John Laiman, Yuxiang Zi, Nirmal Asokan, Yung-Hsiang Lu, George K. Thiruvathukal, Mei-Ling Shyu, Shu-Ching Chen

*Computer Science: Faculty Publications and Other Works*

One of the greatest technological improvements in recent years is the rapid progress using machine learning for processing visual data. Among all factors that contribute to this development, datasets with labels play crucial roles. Several datasets are widely reused for investigating and analyzing different solutions in machine learning. Many systems, such as autonomous vehicles, rely on components using machine learning for recognizing objects. This paper compares different visual datasets and frameworks for machine learning. The comparison is both qualitative and quantitative and investigates object detection labels with respect to size, location, and contextual information. This paper also presents a new ...

Vertex Weighted Spectral Clustering, 2017 East Tennessee State University

#### Vertex Weighted Spectral Clustering, Mohammad Masum

*Electronic Theses and Dissertations*

Spectral clustering is often used to partition a data set into a specified number of clusters. Both the unweighted and the vertex-weighted approaches use eigenvectors of the Laplacian matrix of a graph. Our focus is on using vertex-weighted methods to refine clustering of observations. An eigenvector corresponding with the second smallest eigenvalue of the Laplacian matrix of a graph is called a Fiedler vector. Coefficients of a Fiedler vector are used to partition vertices of a given graph into two clusters. A vertex of a graph is classified as unassociated if the Fiedler coefficient of the vertex is close to ...

Synthesis And Catalytic Evaluation Of Novel C-Alpha-Methyl-Beta-Proline Analogues, And Concise Synthetic Approach To Nh-Fmoc-S-Trityl-C-Alpha-Methyl Cysteine, 2017 University of Southern Mississippi

#### Synthesis And Catalytic Evaluation Of Novel C-Alpha-Methyl-Beta-Proline Analogues, And Concise Synthetic Approach To Nh-Fmoc-S-Trityl-C-Alpha-Methyl Cysteine, Hari Kiran Kotapati

*Dissertations*

In the field of chemistry there is a growing demand for small molecule organocatalysts such as amino acids, more specifically proline and its analogues, which could catalyze various key chemical reactions in the synthesis of several biologically important molecules. Even though natural proline is reported to catalyze various chemical reactions, its use as organocatalyst is limited mainly due to the solubility issues in the reaction media and high catalyst loadings, which is not very ideal for bulk scale manufacturing. To address these limitations we planned to develop unnatural analogues of proline that could catalyze the reactions with lower catalyst loadings ...

Observing The Quantumbehavior Of Light In An Undergraduate Laboratory, 2017 Utah State University

#### Observing The Quantumbehavior Of Light In An Undergraduate Laboratory, M. S. Neel, J. J. Thorn, V. W. Donato, G. S. Bergreen, Robert E. Davies, M. Beck

*Robert Davies*

While the classical, wavelike behavior of light (interference and diffraction) has been easily observed in undergraduate laboratories for many years, explicit observation of the quantum nature of light (i.e., photons) is much more difficult. For example, while well-known phenomena such as the photoelectric effect and Compton scattering strongly suggest the existence of photons, they are not definitive proof of their existence. Here we present an experiment, suitable for an undergraduate laboratory, that unequivocally demonstrates the quantum nature of light. Spontaneously downconverted light is incident on a beamsplitter and the outputs are monitored with single-photon counting detectors. We observe a ...

Identification Of Extreme Precipitation Threat Across Midlatitude Regions Based On Short-Wave Circulations, 2017 Utah State University

#### Identification Of Extreme Precipitation Threat Across Midlatitude Regions Based On Short-Wave Circulations, Shih-Yu (Simon) Wang, Robert E. Davies, Robert R. Gillies

*Robert Davies*

The most severe thunderstorms, producing extreme precipitation, occur over subtropical and midlatitude regions. Atmospheric conditions conducive to organized, intense thunderstorms commonly involve the coupling of a low-level jet (LLJ) with a synoptic short wave. The midlatitude synoptic activity is frequently modulated by the circumglobal teleconnection (CGT), in which meridional gradients of the jet stream act as a guide for short Rossby waves. Previous research has linked extreme precipitation events with either the CGT or the LLJ but has not linked the two circulation features together. In this study, a circulation-based index was developed by combining (a) the degree of the ...

Connecting Subseasonal Movements Of The Winter Mean Ridge In Western North America To Inversion Climatology In Cache Valley, Utah, 2017 Utah State University

#### Connecting Subseasonal Movements Of The Winter Mean Ridge In Western North America To Inversion Climatology In Cache Valley, Utah, Shi-Yu (Simon) Wang, Robert R. Gillies, Randy Martin, Robert E. Davies, Marty R. Booth

*Robert Davies*

A 10-yr record of PM2.5 (particulate matter of aerodynamic diameter ≤ 2.5 μm), collected in Cache Valley near downtown Logan, Utah, reveals a strong peak in the PM2.5 concentration climatology that is tightly localized in mid-January. The cause of this subseasonal variation in the PM2.5 climatology is investigated through dynamical downscaling and large-scale diagnostics. Climatological analysis of the U.S. winter mean ridge reveals a mid-January subseasonal shift in the zonal direction, likely in response to variations in the Rossby wave source over the central North Pacific Ocean. This displacement of the winter mean ridge, in turn ...

Combining Biomarkers By Maximizing The True Positive Rate For A Fixed False Positive Rate, 2017 University of Washington, Seattle

#### Combining Biomarkers By Maximizing The True Positive Rate For A Fixed False Positive Rate, Allison Meisner, Marco Carone, Margaret Pepe, Kathleen F. Kerr

*UW Biostatistics Working Paper Series*

Biomarkers abound in many areas of clinical research, and often investigators are interested in combining them for diagnosis, prognosis and screening. In many applications, the true positive rate for a biomarker combination at a prespecified, clinically acceptable false positive rate is the most relevant measure of predictive capacity. We propose a distribution-free method for constructing biomarker combinations by maximizing the true positive rate while constraining the false positive rate. Theoretical results demonstrate good operating characteristics for the resulting combination. In simulations, the biomarker combination provided by our method demonstrated improved operating characteristics in a variety of scenarios when compared with ...

Developing Biomarker Combinations In Multicenter Studies Via Direct Maximization And Penalization, 2017 University of Washington, Seattle

#### Developing Biomarker Combinations In Multicenter Studies Via Direct Maximization And Penalization, Allison Meisner, Chirag R. Parikh, Kathleen F. Kerr

*UW Biostatistics Working Paper Series*

When biomarker studies involve patients at multiple centers and the goal is to develop biomarker combinations for diagnosis, prognosis, or screening, we consider evaluating the predictive capacity of a given combination with the center-adjusted AUC (aAUC), a summary of conditional performance. Rather than using a general method to construct the biomarker combination, such as logistic regression, we propose estimating the combination by directly maximizing the aAUC. Furthermore, it may be desirable to have a biomarker combination with similar predictive capacity across centers. To that end, we allow for penalization of the variability in center-specific performance. We demonstrate good asymptotic properties ...

Was Climate Change Involved?, 2017 Iowa State University