Physical Sciences and Mathematics Commons^™

Ua12/2/2 Talisman: Movement, Wku Student Affairs

WKU Administration Documents

2018 Talisman yearbook.

• Good, Hannah. Movement
• Kinser, Nicholas. Tunnel Trap
• Cozer, Claire. A Day in the Life of a Food Truck – Mike Wilson, Pop’s Street Eats
• Fletcher, Griffin. Beauty in Power – WKU Women’s Rugby Club
• Gordon, Zora. The Mixed Experience
• Hornsby, Morgan. Bonfire
• Waters, Adrianna. Mispoken – Communication Disorders
• Chu, Phi. Home Base – Jessica Barks
• Cooksey, Catrina. Rerouted – Sydney Clark, Austin Clark, Blake Perkins, Sheila Flener, Handicapped Persons
• Good, Hannah. Not Safe for Work – Prostitution
• Chu, Phi. Transfigured Night
• Carter, De’inara. Passing the Plate – International Students, Recipes
• Robb, Hayley. From Sole to Soul – …

Time Sensitive Functionals Of Marked Random Measures In Real Time, Kizza M. Nandyose Frisbee

Theses and Dissertations

In this dissertation, we study marked random measures that model stochastic networks (under attacks), status of queueing systems during vacation modes, responses to cancer treatments (such as chemotherapy and radiation), hostile actions in economics and warfare. We extend the recently developed time sensitivity technique for investigating the processes’ behavior about a fixed threshold to a novel time sensitive technique in three important directions: (1) real-time monotone stochastic processes; (2) two-dimensional signed random measures; and (3) antagonistic stochastic games with two active players and one passive player. The need for the time sensitive feature in our study (i.e., an analytical association …

Fully Convolutional Neural Networks For Pixel Classification In Historical Document Images, Seth Andrew Stewart

Theses and Dissertations

We use a Fully Convolutional Neural Network (FCNN) to classify pixels in historical document images, enabling the extraction of high-quality, pixel-precise and semantically consistent layers of masked content. We also analyze a dataset of hand-labeled historical form images of unprecedented detail and complexity. The semantic categories we consider in this new dataset include handwriting, machine-printed text, dotted and solid lines, and stamps. Segmentation of document images into distinct layers allows handwriting, machine print, and other content to be processed and recognized discriminatively, and therefore more intelligently than might be possible with content-unaware methods. We show that an efficient FCNN with …

Fully Convolutional Neural Networks For Pixel Classification In Historical Document Images, Seth Andrew Stewart

Theses and Dissertations

We use a Fully Convolutional Neural Network (FCNN) to classify pixels in historical document images, enabling the extraction of high-quality, pixel-precise and semantically consistent layers of masked content. We also analyze a dataset of hand-labeled historical form images of unprecedented detail and complexity. The semantic categories we consider in this new dataset include handwriting, machine-printed text, dotted and solid lines, and stamps. Segmentation of document images into distinct layers allows handwriting, machine print, and other content to be processed and recognized discriminatively, and therefore more intelligently than might be possible with content-unaware methods. We show that an efficient FCNN with …

Development And Use Of Lipidomics And Proteomics Methods To Identify And Measure Pro-Survival Metabolic Pathways In Cancer, Monique Merilyn Speirs

Theses and Dissertations

Throughout society’s continual war against cancer, we have attempted pharmacological intervention only to find that tumors develop modes of resistance. It is well known that genetics play an integral role in cancer. Technological advances have greatly improved our ability to study cancer biochemistry beyond the genome by measuring changes in the expression and activity of RNA, proteins, and lipids in experimental models and human patients. As our techniques and technology to perform cancer research progresses, it is becoming more evident that cancer cells develop stress tolerance mechanisms at multiple levels within the central dogma, including altering mRNA expression, enzyme concentrations, …

The Effects Of Metacognitive Training On Algebra Students’ Calibration Accuracy, Achievement, And Mathematical Literacy, Deana J. Ford

Teaching & Learning Theses & Dissertations

This dissertation describes an empirical study that investigated how metacognitive training influenced lower achieving Algebra students’ calibration accuracy, achievement, and development of mathematics literacy. Multiple methods were used to collect and analyze the data. Close analysis of students’ work and classroom observations revealed that students that were exposed to the metacognitive training had significantly higher prediction accuracy and made gains in their understanding of the mathematics word problems than did students who did not receive the metacognitive training. Overall, however, both the intervention and comparison groups improved in their academic performance and became more mathematically literate and accurate in their …

Interpretable Multimodal Retrieval For Fashion Products, Lizi Liao, Xiangnan He, Bo Zhao, Chong-Wah Ngo, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Deep learning methods have been successfully applied to fashion retrieval. However, the latent meaning of learned feature vectors hinders the explanation of retrieval results and integration of user feedback. Fortunately, there are many online shopping websites organizing fashion items into hierarchical structures based on product taxonomy and domain knowledge. Such structures help to reveal how human perceive the relatedness among fashion products. Nevertheless, incorporating structural knowledge for deep learning remains a challenging problem. This paper presents techniques for organizing and utilizing the fashion hierarchies in deep learning to facilitate the reasoning of search results and user intent. The novelty of …

Mixed-Reality For Object-Focused Remote Collaboration, Martin Feick, Anthony Tang, Scott Bateman

Research Collection School Of Computing and Information Systems

In this paper we outline the design of a mixed-reality system to support object-focused remote collaboration. Here, being able to adjust collaborators' perspectives on the object as well as understand one another's perspective is essential to support effective collaboration over distance. We propose a low-cost mixed-reality system that allows users to: (1) quickly align and understand each other's perspective; (2) explore objects independently from one another, and (3) render gestures in the remote's workspace. In this work, we focus on the expert's role and we introduce an interaction technique allowing users to quickly manipulation 3D virtual objects in space.

Geometry-Aware Similarity Learning On Spd Manifolds For Visual Recognition, Zhiwu Huang, R. Wang, X. Li, W. Liu, S. Shan, Gool L. Van, X Chen

Research Collection School Of Computing and Information Systems

Symmetric positive definite (SPD) matrices have been employed for data representation in many visual recognition tasks. The success is mainly attributed to learning discriminative SPD matrices encoding the Riemannian geometry of the underlying SPD manifolds. In this paper, we propose a geometry-aware SPD similarity learning (SPDSL) framework to learn discriminative SPD features by directly pursuing a manifold-manifold transformation matrix of full column rank. Specifically, by exploiting the Riemannian geometry of the manifolds of fixed-rank positive semidefinite (PSD) matrices, we present a new solution to reduce optimization over the space of column full-rank transformation matrices to optimization on the PSD manifold, …

Interpretable Multimodal Retrieval For Fashion Products, Lizi Liao, Xiangnan He, Bo Zhao, Chong-Wah Ngo, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Deep learning methods have been successfully applied to fashion retrieval. However, the latent meaning of learned feature vectors hinders the explanation of retrieval results and integration of user feedback. Fortunately, there are many online shopping websites organizing fashion items into hierarchical structures based on product taxonomy and domain knowledge. Such structures help to reveal how human perceive the relatedness among fashion products. Nevertheless, incorporating structural knowledge for deep learning remains a challenging problem. This paper presents techniques for organizing and utilizing the fashion hierarchies in deep learning to facilitate the reasoning of search results and user intent. The novelty of …

Overfitting In Semantics-Based Automated Program Repair, Dinh Xuan Bach Le, Ferdian Thung, David Lo, Claire Le Goues

Research Collection School Of Computing and Information Systems

The primary goal of Automated Program Repair (APR) is to automatically fix buggy software, to reduce the manual bug-fix burden that presently rests on human developers. Existing APR techniques can be generally divided into two families: semantics- vs. heuristics-based. Semantics-based APR uses symbolic execution and test suites to extract semantic constraints, and uses program synthesis to synthesize repairs that satisfy the extracted constraints. Heuristic-based APR generates large populations of repair candidates via source manipulation, and searches for the best among them. Both families largely rely on a primary assumption that a program is correctly patched if the generated patch leads …

Unearthing The X-Streams: Visualizing Water Contamination, Akangsha Bandalkul, Angad Srivastava, Kishan Bharadwaj Shridhar, Jason Guan Jie Ong, Yanrong Zhang

Research Collection School Of Computing and Information Systems

The datasets released for VAST 2018 Mini Challenge 2 pertain to sensor readings capturing chemical concentrations and physical properties from water bodies in the Boonsong Lekagul wildlife preserve. This challenge is in continuation to the VAST 2017 Challenge, where the company Kasios was identified as the culprit in dumping the chemical - Methylosmoline. In the absence of actual chemical measurements in the soil, challenge participants need to visualize chemical contamination based on the proximal water bodies to identify trends of interest. A horizon plot developed helps to narrow down the complete list of 106 chemicals provided to only 7, …

Traffic-Cascade: Mining And Visualizing Lifecycles Of Traffic Congestion Events Using Public Bus Trajectories, Agus Trisnajaya Kwee, Meng-Fen Chiang, Philips Kokoh Prasetyo, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

As road transportation supports both economic and social activities in developed cities, it is important to maintain smooth traffic on all highways and local roads. Whenever possible, traffic congestions should be detected early and resolved quickly. While existing traffic monitoring dashboard systems have been put in place in many cities, these systems require high-cost vehicle speed monitoring instruments and detect traffic congestion as independent events. There is a lack of low-cost dashboards to inspect and analyze the lifecycle of traffic congestion which is critical in assessing the overall impact of congestion, determining the possible the source(s) of congestion and its …

Optimal In-Place Suffix Sorting, Zhize Li, Jian Li, Hongwei Huo

Research Collection School Of Computing and Information Systems

The suffix array is a fundamental data structure for many applications that involve string searching and data compression. Designing time/space-efficient suffix array construction algorithms has attracted significant attentions and considerable advances have been made for the past 20 years. We obtain the first in-place linear time suffix array construction algorithms that are optimal both in time and space for (read-only) integer alphabets. Our algorithm settles the open problem posed by Franceschini and Muthukrishnan in ICALP 2007. The open problem asked to design in-place algorithms in $o(n \log n)$ time and ultimately, in $O(n)$ time for (read-only) integer alphabets with $|\Sigma| …

Efficient Attribute-Based Encryption With Blackbox Traceability, Shengmin Xu, Guomin Yang, Yi Mu, Ximeng Liu

Research Collection School Of Computing and Information Systems

Traitor tracing scheme can be used to identify a decryption key is illegally used in public-key encryption. In CCS’13, Liu et al. proposed an attribute-based traitor tracing (ABTT) scheme with blackbox traceability which can trace decryption keys embedded in a decryption blackbox/device rather than tracing a well-formed decryption key. However, the existing ABTT schemes with blackbox traceability are based on composite order group and the size of the decryption key depends on the policies and the number of system users. In this paper, we revisit blackbox ABTT and introduce a new primitive called attribute-based set encryption (ABSE) based on key-policy …

Visforum: A Visual Analysis System For Exploring User Groups In Online Forums, Siwei Fu, Yong Wang, Yi Yang, Qingqing Bi, Fangzhou Guo, Huamin Qu

Research Collection School Of Computing and Information Systems

User grouping in asynchronous online forums is a common phenomenon nowadays. People with similar backgrounds or shared interests like to get together in group discussions. As tens of thousands of archived conversational posts accumulate, challenges emerge for forum administrators and analysts to effectively explore user groups in large-volume threads and gain meaningful insights into the hierarchical discussions. Identifying and comparing groups in discussion threads are nontrivial, since the number of users and posts increases with time and noises may hamper the detection of user groups. Researchers in data mining fields have proposed a large body of algorithms to explore user …

Correlates Of Rate Heterogeneity In Avian Ecomorphological Traits, A. M. Chira, C. R. Cooney, Jen A. Bright, E. J. R. Capp, E. C. Hughes, C. J. A. Moody, L. O. Nouri, Z. K. Varley, G. H. Thomas

School of Geosciences Faculty and Staff Publications

Heterogeneity in rates of trait evolution is widespread, but it remains unclear which processes drive fast and slow character divergence across global radiations. Here, we test multiple hypotheses for explaining rate variation in an ecomorphological trait (beak shape) across a globally distributed group (birds). We find low support that variation in evolutionary rates of species is correlated with life history, environmental mutagenic factors, range size, number of competitors, or living on islands. Indeed, after controlling for the negative effect of species' age, 80% of variation in species‐specific evolutionary rates remains unexplained. At the clade level, high evolutionary rates are associated …

An Acoustical Analogue Of A Galactic-Scale Gravitational-Wave Detector, Michael T. Lam, Joseph D. Romano, Joey Key, M. E. Normandin, ‪Jeffrey S. Hazboun

Physics and Astronomy Faculty Publications and Presentations

By precisely monitoring the “ticks” of Nature's most precise clocks (millisecond pulsars), scientists are trying to detect the “ripples in spacetime” (gravitational waves) produced by the inspirals of supermassive black holes in the centers of distant merging galaxies. Here, we describe a relatively simple demonstration that uses two metronomes and a microphone to illustrate several techniques used by pulsar astronomers to search for and detect gravitational waves. An adapted version of this demonstration could be used as an instructional laboratory investigation at the undergraduate level.

Character Sums Of Lee And Weintraub, Brad Isaacson

Publications and Research

We prove two conjectures of Lee and Weintraub and one conjecture of Ibukiyama and Kaneko about character sums arising as fixed point contributions in the Atiyah–Singer holomorphic Lefshetz formula applied to finite group actions on the space of certain Siegel cusp forms.

Characterizing Diatom Biofilms And Their Influence On The Sand Biogeochemistry Of High Energy Beaches, Logan C. Jarrell

Honors Theses

High energy beaches are among the most dynamic ecological settings on Earth. Compared to mudflats, diatoms of high energy beaches have been more neglected in the literature, particularly true of the intertidal biofilms that form and dissipate with nutrient cycling and light intensity over the tidal cycle. Although short lived, the productivity of these biofilms may be critical to the organic-poor sand. Through sediment coring and subsequent analyses of the uppermost sand of three suspected biofilm stations—non-runnel, runnel crest, and runnel trough—along with seemingly bare sand as a control, this study sought to verify the presence of diatom biofilms and …

Developing A New Sensing Technology For Double-Stranded Dna Detection Utilizing Engineered Zinc Finger Proteins And Nanomaterials, Dat Thinh Ha

Masters Theses & Specialist Projects

A specific double-stranded DNA sensing system is of great interest for diagnostic and other biomedical applications. Zinc finger domains, which recognize double-stranded DNA, can be engineered to form custom DNA-binding proteins for recognition of specific DNA sequences. As a proof of concept, a sequence-enabled reassembly of TEM-1 β- lactamase system (SEER-LAC) was previously demonstrated to develop zinc finger protein (ZFP) arrays for the detection of a double-stranded bacterial DNA sequence. Here, we implemented the SEER-LAC system to demonstrate the direct detection of pathogenspecific DNA sequences present in E. coli O157:H7 on the lab-on-a chip. ZFPs customdesigned to detect shiga toxin …

Monitoring And Evaluating The Influences Of Class V Injection Wells On Urban Karst Hydrology, James Adam Shelley

Masters Theses & Specialist Projects

The response of a karst aquifer to storm events is often faster and more severe than that of a non-karst aquifer. This distinction is often problematic for planners and municipalities, because karst flooding does not typically occur along perennial water courses; thus, traditional flood management strategies are usually ineffective. The City of Bowling Green (CoBG), Kentucky is a representative example of an area plagued by karst flooding. The CoBG, is an urban karst area (UKA), that uses Class V Injection Wells to lessen the severity of flooding. The overall effectiveness, siting, and flooding impact of Injection Wells in UKA’s is …

Mass-Transport Deposits In The Northern Gulf Of Mexico And Their Implications For Hydrocarbon Exploration, Michael Raymond Arthur

Masters Theses & Specialist Projects

This study investigates Mio-Pliocene mass-transport deposits (MTDs) in an understudied, hydrocarbon-rich region of the northeastern Gulf of Mexico. The research utilizes a high-quality 3D seismic dataset with an area of 635 km2, along with wireline logs and biostratigraphic data. With the help of quantitative seismic geomorphology techniques, detailed mapping of MTDs suggests a complex erosional and depositional history. Deposition of a MTD unit resulted in a 180 m topographic high that substantially influenced the distribution and morphology of subsequent MTDs, specifically the bifurcation of later mass-transport flows. This bifurcation contributed to the generation of a non-shielded erosional remnant with an …

Synthesis And Characterization Of Graphene-Family Mesoporous Nanomaterials For Themal Energy Harvesting And Sensing Applications, Romney Meek

Masters Theses & Specialist Projects

Graphene-family nanomaterials (GFNs) have attracted a great deal of attention both in academia and in industry for a range of applications relevant for homeland security. In this thesis, an array of graphene-based hybrid materials and aerogels are synthesized for use as novel thermo-electrochemical energy harvesters and for ascorbic acid biosensing devices. The graphene-family nanomaterials include graphene oxide-GO, thermally reduced GO-rGOth, nitrogenated functionalized graphene-NFG, graphene aerogel-GA, nitrogen-doped graphene aerogel-NGA, multi-walled carbon nanotube aerogel-MWCNT, single-walled carbon nanotube aerogel-SWCNT, graphene and nanotube combined ‘hybrid’ aerogels-Gr:(SW/MW)CNT of various ratios, along with multilayered nanostructured architectures such as gold (AuNP) and silver nanoparticles (AgNP) decorated NFG …

Controls On Speleogenesis In The Upper-Mississippian Pennington Formation On The Western Cumberland Plateau Escarpment, Hali Steinmann

Masters Theses & Specialist Projects

Much of the pioneering work on caves of the Cumberland Plateau (province spanning Tennessee, Kentucky, Alabama, and Georgia) has been stratigraphically located within the Mississippian Bangor and Monteagle Limestones, wherein some of the region’s largest and most spectacular caves occur. Of interest to the understanding of this karst landscape, but severely underrepresented in the literature thereof, are caves and karst features in a heterogeneous sequence of clastics and carbonates known collectively as the Pennington Formation (Upper Mississippian). This work consisted of a regional study of Pennington caves on the western Cumberland Plateau escarpment (Alabama and Tennessee), and a case study …

Exploring The Effect Of Different Numbers Of Convolutional Filters And Training Loops On The Performance Of Alphazero, Jared Prince

Masters Theses & Specialist Projects

In this work, the algorithm used by AlphaZero is adapted for dots and boxes, a two-player game. This algorithm is explored using different numbers of convolutional filters and training loops, in order to better understand the effect these parameters have on the learning of the player. Different board sizes are also tested to compare these parameters in relation to game complexity. AlphaZero originated as a Go player using an algorithm which combines Monte Carlo tree search and convolutional neural networks. This novel approach, integrating a reinforcement learning method previously applied to Go (MCTS) with a supervised learning method (neural networks) …

Land-Use Impacts On The Hydrology Of The Hidden River Groundwater Subbasin, Horse Cave, Hart County, Kentucky, Cesalea N. Osborne

Masters Theses & Specialist Projects

No abstract provided.

Smt-Based Constraint Answer Set Solver Ezsmt+ For Non-Tight Programs, Da Shen, Yuliya Lierler

Yuliya Lierler

Learning To Love Data (Week): Creating Data Services Awareness On Campus, Katie M. Wissel, Lisa Deluca

Kathryn Wissel, MBA, MI

Competence Assessment And Automated Feedback For Ultrasound-Guided Intervention Training, Matthew Holden

Link Foundation Modeling, Simulation and Training Fellowship Reports

There is an ongoing shift in the medical education community from a time-based model of medical education to a competency-based model. In the competency-based model, trainees’ performance must be continually monitored. But due to constraints on expert scheduling, this is infeasible for expert preceptors. Moreover, despite the advent of structured assessment rubrics, expert assessment remains subjective. This motivates the development of automated assessment methods. This can be complemented by methods for automatic feedback and instruction, which can be used to improve the training process and acceleration learning curves without the presence of an expert preceptor. Ultrasound-guided interventions are particularly challenging …