Digital Commons Network^™

Early Wildfire Detection With Line Sensors, Virginia Yan

Master's Theses

Over the last few years, wildfires have become more devastating to communities as the fires are inevitably destructive to many homes, businesses, and ecosystems. Frequent wildfires also pose a significant threat to power grids and nearby residents as they can damage transmission lines and other electrical equipment, which in turn can cause major power shutdowns. Especially in western U.S., severe drought conditions and weather variability cause residents to become more vulnerable to wildfire disasters as their safety is threatened. We are incompetent to control the wildfires effectively despite existing advanced technologies. Hence, an algorithm based on energy conservation and heat …

Development Of A Robust Methodology To Obtain And Assess Myogenic Precursor Cells For Their Use In Regenerative Therapies, Ricardo Lasa

Master's Theses

Peripheral arterial occlusive disease (PAOD) is characterized by buildup of atherosclerotic plaque in peripheral arteries that leads to an occlusion that can interrupt the supply of blood to the peripheral tissue, causing downstream tissue ischemia/hypoxia. PAOD is estimated to affect over 200 million patients worldwide. Current surgical revascularization treatments can be effective in about half of the patient population, leading to a significant number of patients with no treatment options beyond pharmacological intervention and lifestyle modification. The decrease in blood flow downstream of the occlusion leads to increased blood pressure gradient in the microvasculature, specifically in vessels that connect arterial …

Brain Tumor Detection And Classification From Mri Images, Anjaneya Teja Sarma Kalvakolanu

Master's Theses

A brain tumor is detected and classified by biopsy that is conducted after the brain surgery. Advancement in technology and machine learning techniques could help radiologists in the diagnosis of tumors without any invasive measures. We utilized a deep learning-based approach to detect and classify the tumor into Meningioma, Glioma, Pituitary tumors. We used registration and segmentation-based skull stripping mechanism to remove the skull from the MRI images and the grab cut method to verify whether the skull stripped MRI masks retained the features of the tumor for accurate classification. In this research, we proposed a transfer learning based approach …

Ram Air-Turbine Of Minimum Drag, Raymond Akagi

Master's Theses

The primary motivation for this work was to predict the conditions that would yield minimum drag for a small Ram-Air Turbine used to provide a specified power requirement for a small flight test instrument called the Boundary Layer Data System. Actuator Disk Theory was used to provide an analytical model for this work.

Classic Actuator Disk Theory (CADT) or Froude’s Momentum Theory was initially established for quasi-one-dimensional flows and inviscid fluids to predict the power output, drag, and efficiency of energy-extracting devices as a function of wake and freestream velocities using the laws of Conservations of Mass, Momentum, and Energy. …

A Light In Students’ Lives: K-12 Teachers’ Experiences (Re)Building Caring Relationships During Remote Learning, Karyn E. Miller

Faculty Publications

This study illuminates the experiences of K-12 educators as they strove to (re)build caring relationships with students during the COVID-19 pandemic. The study was conducted during a graduate course for experienced K-12 teachers in the spring of 2020 at a four-year comprehensive university in the United States. Data was collected from reflective learning journals and asynchronous peer discussions, which captured educators’ experiences as they transitioned to remote learning in real-time. Qualitative content analysis was used to identify pertinent themes. Findings suggest that remote learning revealed relationships in need of repair. Educators practiced authentic care and cultivated connectedness by (a) acting …

Role Of Contrast Enhanced Computed Tomography In Assessing Cervical Lymph Node Metastases In Oral Cavity Squamous Cell Carcinoma, Talha Ahmed Qureshi, Muhammad Wasif, Mohammad Sohail Awan, Adnan Yar Muhammad, Ainulakbar Mughal, Abdullah Ameen

Section of Otolaryngology, Head & Neck Surgery

Objective: To evaluate the diagnostic accuracy of contrast-enhanced computed tomography scan in detecting cervical nodal metastasis in oral cavity squamous cell carcinoma.
Methods: The retrospective cross-sectional study was conducted at Aga Khan University Hospital, Karachi, Pakistan. and comprised records from January 1, 2015, to October 31, 2016, of patients diagnosed with oral cavity squamous cell carcinoma and who underwent surgical resection of primary tumour along with neck dissection after having a contrast-enhanced computed tomography scan of head and neck. Diagnostic accuracy of the scans was calculated using final histopathology as the gold standard. All scans were reviewed by a consultant …

The Perilous Road To Justice: An Interview With Prof. Peter Mclaren, Peter Mclaren

Education Faculty Articles and Research

No abstract provided.

Color-Compressive Bilateral Filter And Nonlocal Means For High-Dimensional Images, Christina Karam, Kenjiro Sugimoto, Keigo Hirakawa

Electrical and Computer Engineering Faculty Publications

We propose accelerated implementations of bilateral filter (BF) and nonlocal means (NLM) called color-compressive bilateral filter (CCBF) and color-compressive nonlocal means (CCNLM). CCBF and CCNLM are random filters, whose Monte-Carlo averaged output images are identical to the output images of conventional BF and NLM, respectively. However, CCBF and CCNLM are considerably faster because the spatial processing of multiple color channels are combined into a single random filtering process. This implies that the complexity of CCBF and CCNLM is less sensitive to color dimension (e.g., hyperspectral images) relatively to other BF and NLM methods. We experimentally verified that the execution time …

Deep Learning For Anisoplanatic Optical Turbulence Mitigation In Long-Range Imaging, Matthew A. Hoffmire, Russell C. Hardie, Michael A. Rucci, Richard Van Hook, Barry K. Karch

Electrical and Computer Engineering Faculty Publications

We present a deep learning approach for restoring images degraded by atmospheric optical turbulence. We consider the case of terrestrial imaging over long ranges with a wide field-of-view. This produces an anisoplanatic imaging scenario where turbulence warping and blurring vary spatially across the image. The proposed turbulence mitigation (TM) method assumes that a sequence of short-exposure images is acquired. A block matching (BM) registration algorithm is applied to the observed frames for dewarping, and the resulting images are averaged. A convolutional neural network (CNN) is then employed to perform spatially adaptive restoration. We refer to the proposed TM algorithm as …

Inferior Vena Cava Collapsibility Index Versus Passive Leg Raise For The Assessment Of Fluid Responsiveness In Non-Intubated Spontaneously Breathing Septic Patients, Anne-Marie Githaiga

Master of Medicine in Anaesthesiology

Background: Sepsis can cause deleterious organ deterioration due to deranged patient’s response to infection. Rapid fluid loading at diagnosis is part of standard treatment. While inadequate fluid administration may lead to tissue hypoperfusion and organ failure, excessive fluid administration may cause fluid overload and pulmonary oedema. Predictive tools of fluid responsiveness are therefore required to guide fluid resuscitation. The Passive Leg Raise (PLR) manoeuvre can predict fluid responsiveness in non-intubated patients with sepsis-induced hypotension but is challenging to perform in clinical practice. The Inferior Vena Cava Collapsibility Index (IVCCI) on the other hand is a non-invasive test that can be …

Dallas Diversity And Inclusion Study, Patricia Gándara, Gary Orfield

Mission Foods Texas-Mexico Center Research

Dallas, one of the nation’s largest central cities in its most rapidly growing metropolitan areas, has had a shrinking school district in the midst of major housing development. A surge in housing costs since the Great Recession has led to the return of middle class and white families to a number of communities but that has not been reflected in the student population. In response to the challenge of closing more schools and losing out to expanding charters, the DISD leadership decided to create some new schools and restart some older ones with programs designed both to attract new and …

Approaching Difficult Topics With Patients Panel Discussion, Lynn M. Wilson Do, Jeremy Fischer, S Carter, Rob Danoff

Department of Family Medicine

No abstract provided.

Controller Modeling And Stability Analysis Of Multiple Input Single Output Dc-Dc Converter, Astha Adhikari

Master's Theses

This thesis entails the stability analysis of the Multiple Input Single Output (MISO) DC-DC converter developed for the DC House Project at Cal Poly. A frequency domain control system model of the MISO converter was designed and constructed using MATLAB Simulink. Transfer functions were derived and modeled for each stage of the converter to best fit the converter circuit system used in the original MISO circuit. Stability metrics such as overshoot, undershoot, rise time, phase margin and gain margin were measured to evaluate and analyze the stability of the converter. These metrics were measured with the original model including the …

Physics Engine On The Gpu With Opengl Compute Shaders, Quan Huy Minh Bui

Master's Theses

Any kind of graphics simulation can be thought of like a fancy flipbook. This notion is, of course, nothing new. For instance, in a game, the central computing unit (CPU) needs to process frame by frame, figuring out what is happening, and then finally issues draw calls to the graphics processing unit (GPU) to render the frame and display it onto the monitor. Traditionally, the CPU has to process a lot of things: from the creation of the window environment for the processed frames to be displayed, handling game logic, processing artificial intelligence (AI) for non-player characters (NPC), to the …

Natural And Experimental Noise Affects Acoustic Communication In Songbirds, Veronica Arlene Reed

Master's Theses

Background noise is ubiquitous and can impair acoustic communication and influence signaling behavior in animals. Despite evidence demonstrating myriad effects of anthropogenic noise on animal communication, precisely how natural background noise influences communication and behavior remains unclear. Yet, natural sources of background noise, such as rushing rivers or crashing ocean surf, share similar power spectra to sources of anthropogenic noise and can occur at high amplitudes, potentially masking acoustic signals.

To investigate the effects of water-generated noise on songbird behavior, we experimentally broadcast landscape-level playbacks of ocean surf and river noise in coastal California, USA, and riparian habitat in Idaho, …

Comparing Radiation Shielding Potential Of Liquid Propellants To Water For Application In Space, John Czaplewski

Master's Theses

The radiation environment in space is a threat that engineers and astronauts need to mitigate as exploration into the solar system expands. Passive shielding involves placing as much material between critical components and the radiation environment as possible. However, with mass and size budgets, it is important to select efficient materials to provide shielding. Currently, NASA and other space agencies plan on using water as a shield against radiation since it is already necessary for human missions. Water has been tested thoroughly and has been proven to be effective. Liquid propellants are needed for every mission and also share similar …

Part-Scale Thermal Simulation Of Laser Powder Bed Fusion Using Graph Theory: Effect Of Thermal History On Porosity, Microstructure Evolution, And Recoater Crash, Reza Yavari, Ziyad Smoqi, Alex Riensche, Ben Bevans, Humaun Kobir, Heimdall Mendoza, Hyeyun Song, Kevin Cole, Prahalada Rao

Department of Mechanical and Materials Engineering: Faculty Publications

Flaw formation in laser powder bed fusion (LPBF) is influenced by the spatiotemporal temperature distribution – thermal history – of the part during the process. Therefore, to prevent flaw formation there is a need for fast and accurate models that can predict the thermal history as a function of the part shape and processing parameters. In previous work, a thermal modeling approach based on graph theory was used to predict the thermal history in LPBF parts in less-than 20% of the time required by finite element-based models with error within 10% of experimental measurements. The present work transitions toward the …

What Documents Cannot Do: Revisiting Michael Polanyi And The Tacit Knowledge Dilemma, C. Sean Burns

Information Science Faculty Publications

Our culture is dominated by digital documents in ways that are easy to overlook. These documents have changed our worldviews about science and have raised our expectations of them as tools for knowledge justification. This article explores the complexities surrounding the digital document by revisiting Michael Polanyi’s theory of tacit knowledge—the idea that “we can know more than we can tell.” The theory presents to us a dilemma: if we can know more than we can tell, then this means that the communication of science via the document as a primary form of telling will always be incomplete. This dilemma …

Upstream Tax Planning: A Case Study Of Why Congress Should Institute A General Anti-Abuse Rule, Jay A. Soled

North Carolina Law Review

No abstract provided.

A Reporting Format For Leaf-Level Gas Exchange Data And Metadata, Kim S. Ely, Alistair Rogers, Deborah A. Agarwal, Elizabeth A. Ainsworth, Loren P. Albert, Ashehad Ali, Jeremiah Anderson, Michael J. Aspinwall, Chandra Bellasio, Carl Bernacchi, Steve Bonnage, Thomas N. Buckley, James Bunce, Angela C. Burnett, Florian A. Busch, Amanda Cavanagh, Lucas A. Cernusak, Robert Crystal-Ornelas, Joan Damerow, Kenneth J. Davidson, Martin G. De Kauwe, Michael C. Dietze, Tomas F. Domingues, Mirindi Eric Dusenge, David S. Ellsworth, John R. Evans, Paul P.G. Gauthier, Bruno O. Gimenez, Elizabeth P. Gordon, Christopher M. Gough, Aud H. Halbritter, David T. Hanson, Mary Heskel, J. Aaron Hogan, Jason R. Hupp, Kolby Jardine, Jens Kattge, Trevor Keenan, Johannes Kromdijk, Dushan P. Kumarathunge, Julien Lamour, Andrew D.B. Leakey, David S. Lebauer, Qianyu Li, Marjorie R. Lundgren, Nate Mcdowell, Katherine Meacham-Hensold, Belinda E. Medlyn, David J.P. Moore, Robinson Negrón-Juárez, Ülo Niinemets, Colin P. Osborne, Alexandria L. Pivovaroff, Hendrik Poorter, Sasha C. Reed, Youngryel Ryu, Alvaro Sanz-Saez, Stephanie C. Schmiege, Shawn P. Serbin, Thomas D. Sharkey, Martijn Slot, Nicholas G. Smith, Balasaheb V. Sonawane, Paul F. South, Daisy C. Souza, Joseph Ronald Stinziano, Ellen Stuart-Haëntjens, Samuel H. Taylor, Mauricio D. Tejera, Johan Uddling, Vigdis Vandvik, Charuleka Varadharajan, Anthony P. Walker, Berkley J. Walker, Jeffrey M. Warren, Danielle A. Way, Brett T. Wolfe, Jin Wu, Stan D. Wullschleger, Chonggang Xu, Zhengbing Yan, Dedi Yang

Faculty Publications

© 2021 The Authors Leaf-level gas exchange data support the mechanistic understanding of plant fluxes of carbon and water. These fluxes inform our understanding of ecosystem function, are an important constraint on parameterization of terrestrial biosphere models, are necessary to understand the response of plants to global environmental change, and are integral to efforts to improve crop production. Collection of these data using gas analyzers can be both technically challenging and time consuming, and individual studies generally focus on a small range of species, restricted time periods, or limited geographic regions. The high value of these data is exemplified by …

Learning With Limited Labeled Data In Biomedical Domain By Disentanglement And Semi-Supervised Learning, Prashnna Kumar Gyawali

Theses

In this dissertation, we are interested in improving the generalization of deep neural networks for biomedical data (e.g., electrocardiogram signal, x-ray images, etc). Although deep neural networks have attained state-of-the-art performance and, thus, deployment across a variety of domains, similar performance in the clinical setting remains challenging due to its ineptness to generalize across unseen data (e.g., new patient cohort).

We address this challenge of generalization in the deep neural network from two perspectives: 1) learning disentangled representations from the deep network, and 2) developing efficient semi-supervised learning (SSL) algorithms using the deep network.

In the former, we are interested …

High Dynamic Range (Hdr) Display Perception, Fu Jiang

Theses

Displays have undergone a huge development in the last several decades. From cathode-ray tube (CRT), liquid crystal display (LCD), to organic light-emitting diode (OLED), even Q-OLED, the new configurations of the display bring more and more functions into industry and daily life. In the recent several years, high dynamic range (HDR) displays become popular. HDR displays usually refer to that the black level of the display is darker and the peak being brighter compared with the standard dynamic range (SDR) display. Traditionally, the peak luminance level can be used as the "white" in characterization and calibration. However, for HDR displays, …

Professional Image Of Nursing And Midwifery In East Africa: An Exploratory Analysis, Eunice Ndirangu, Ahmed Sarki, Columba Mbekenga, Grace Edwards

School of Nursing & Midwifery, East Africa

Background: Evidence suggests that there is a negative image of nursing and midwifery that does not promote these professions as attractive career options. Furthermore, there is a paucity of studies documenting how nursing and midwifery is perceived in East Africa and where such studies exist they are country-specific. The aim of this study was to explore views regarding the image of nursing and midwifery among nurses and midwives in three East African countries, Kenya, Tanzania and Uganda.

Methods: An exploratory descriptive cross-sectional study administered online using Survey Monkey Questionnaires assessed the views and perceptions of nurses and midwives regarding the …

Blurring The Lines: How Consolidating School Districts Can Combat New Jersey’S Public‐School Segregation Problem, Anthony J. Lopresti

Seton Hall Journal of Legislation and Public Policy

No abstract provided.

Implementation Of A Nurse Leader Rounding Program In The Emergency Department, John Swanhorst

Student Scholarly Projects

Practice Problem: The identified practice problem was the low “Likelihood to Recommend” patient experience survey scores within the ED at the identified project setting.

PICOT: The PICOT question that guided this project was “In ED patients (P), how does the implementation of Nurse Leader Rounding (I) compared to the prior state of no Nurse Leader Rounding (C) affect the “Likelihood to Recommend” top box score (O) within eight weeks (T)?”

Evidence: In a review of 13 articles, the evidence consistently showed that Nurse Leader Rounding was a proven intervention for increasing patient engagement scores.

Intervention: Nurse Leader Rounding is defined …

Utilization Of Recombinant Viruses And In Silico Protein-Protein Interactions To Investigate The Role Of Herpes Simplex Type-1 (Hsv-1) Us9, Gk, And Ul20 Proteins In Virion Assembly And Egress, Anna Reneé Naquin

Honors Capstones

No abstract provided.

Reviving The Presumption Of Youth Innocence Through A Presumption Of Release: A Legislative Framework For Abortion Of Juvenile Pretrial Detention, Sara Hildebrand

Penn State Law Review (2003 - Present)

No abstract provided.

The Vexing Case Of Venue For Violent Crimes In Aid Of Racketeering, Melvin Otey

Penn State Law Review (2003 - Present)

No abstract provided.

Equality In Dual Enrollment: How Congress Cn Fix The Current Inequalities Created By Dual Enrollment Programs, Emily Laspina

Penn State Law Review (2003 - Present)

No abstract provided.

The Structure Of Rational Basis And Reasonableness Review, R. Randall Kelso

Southern Illinois University Law Journal

In Whole Woman’s Health v. Hellerstedt, Justice Thomas criticized existing Supreme Court doctrine regarding the “tiers of scrutiny,” quoting a passage from an earlier Justice Scalia dissent that the “three basic tiers – ‘rational basis,’ intermediate, and strict scrutiny – ‘are [1] no more scientific than their names suggests, and [2] a further element of randomness is added by the fact that it is largely up to us which test will be applied in each case.’” 136 S. Ct. 2292, 2327 (2016). Justice Thomas added, “But the problem now goes beyond that. If our recent cases illustrate anything, it is …