Digital Commons Network^™

Fallen Ears From Introductory Statistics, Yoon G. Kim

KAUPA Letters

No abstract provided.

Gradual Memory Safety, Jack Phillips

All NMU Master's Theses

This paper extends the theory of Gradual Types to include memory safe Region-Types and Region-Based Memory Management. It also makes advancements in the capabilities of Region-Based systems. Lastly, it presents the Svejk language and Hasek Type System.

Ursinus Magazine, Spring 2024, Robyn E. Hannigan, Ed Moorhouse, David Eberle, Ben Seal, Talia Argondezzi

Ursinus Magazine, 1995–Present

Out of this world • Freedom fellow • Teachers mentoring teachers • Standout students • Above and beyond • Top Bear • Reimagining Main Street • Bear bites • Cape crusader: Molly Serfass-Carr '14 discovers Delaware parks' true treasures • School of thought: Student and faculty researchers from across academic disciplines advance our knowledge of the brain • Wall Street dreams • A source of hope • Congrats, Class of '24 • Digitizing Gilot • Neverland reimagined • On view at the Berman • National stage • Rolling out the red and gold carpet • Introducing the Athletics Advisory Council …

Evidence Of Seattle Fault Earthquakes From Patterns In Deep-Seated Landslides, Erich Herzig, Alison Duvall, Adam Booth, Ian Stone, Erin Wirth, Sean Lahusen, Joseph Wartman, Alex Grant

Geology Faculty Publications and Presentations

Earthquake‐induced landslides can record information about the seismic shaking that generated them. In this study, we present new mapping, Light Detection and Ranging‐derived roughness dating, and analysis of over 1000 deep‐seated landslides from the Puget Lowlands of Washington, U.S.A., to probe the landscape for past Seattle fault earthquake information. With this new landslide inventory, we observe spatial and temporal evidence of landsliding related to the last major earthquake on the Seattle fault ∼1100 yr before present. We find spatial clusters of landslides that correlate with ground motions from recent 3D kinematic models of Seattle fault earthquakes. We also find temporal …

Perspectives Of Special Education Teachers On The Transition Of Students With Special Needs From High School To University, Noor Abdulkader Mamich

Theses

Post-secondary transition is a significant phase in the life of high school students with special needs. Special education teachers play a crucial role in supporting students in this process. This study aims at exploring the perspectives of special education teachers on transitioning high school students with special needs into university. Semi-structured interviews were conducted with four special education teachers in Al Ain city in the United Arab Emirates. The teachers were asked questions on four themes: their skills on postsecondary transition, their post-secondary transition planning, the barriers they face during post-secondary transition, and finally the facilitation of smooth post-secondary transition …

Unveiling The Origins Of Source Code Through Authorship Attribution: A Comparative Study Of Ai And Human Coding Patterns, Shamma Humaid Alalawi

Theses

In recent years, Artificial Intelligence (AI) techniques have been used for source code authorship attribution, which is the process of identifying the original author of a given piece of code. With the advancement of AI technologies like ChatGPT, which can generate code, there is a need to accurately identify whether a piece of code is written by a human or generated by a machine. This is crucial for intellectual property protection, cybersecurity, and software forensics. The main objective of this thesis is to review existing research on source code authorship attribution and conduct several experiments to determine the best AI …

Transformer-Based Deep Learning Model For Sign Language Recognition, Ganzorig Batnasan

Theses

Sign language recognition research aims to develop systems and tools that can interpret and translate sign language into text or spoken language. During the past two decades, the challenges faced in this domain are multifaceted. The first and foremost challenge is the complexity of sign language, which includes intricate hand gestures, facial expressions, and body movements. Recognizing and interpreting these components accurately is challenging. The second challenge is variability among different regions and communities, leading to variations in signs and gestures. This variability poses a challenge for developing universal recognition systems.
Limited data is another challenge which makes it difficult …

An Evaluation Of The Equitable Practices For Stem Education To Prepare All Students For The 21st Century, Elizabeth Simpson

Dissertations

We are almost a quarter of the way through the 21st Century, yet most education institutions do not provide STEM education for all students. Science, technology, engineering, and math (STEM) have been a special focus of both industry and federal education initiatives in recent years. STEM is a proven way of building student skills needed for the workforce of tomorrow. The purpose of this study is to determine why education decision-makers resist implementing STEM programs equitably for all students. The context of this inquiry is district and school-based leaders throughout the United States, from elementary to high school, who have …

An Evaluation Of The Elements Needed In A New Teacher Induction Program To Prepare And Retain Second Career Educators, Bianka Newkirk

Dissertations

According to García and Weiss (2019), the United States faces a critical teacher shortage. There are not enough students majoring in or graduating with degrees in education. A solution to the teacher shortage is to fill the vacancies by recruiting and training secondcareer educators. If teachers are trained and mentored during the early stages of their careers, students will reap the benefits. Teachers who participate in a comprehensive new teacher induction program remain in the teaching profession longer and have tremendous success in terms of student achievement. Through my study, I aimed to research the elements needed in a new …

My Legacy Document: A Story Told Through A Pedagogical Lens Of Three Landscapes. School, Work, And Faith, Debra Williams

Dissertations

Too often professionals, when answering the question “Who are you?”, resort to listing what they do. Although individuals are gifted, experienced, and qualified, as these persons influence and significantly impact others, one could get lost as a person and be unfulfilled. That’s a problem.

Positioning myself as the study of research, utilizing autoethnography as the chosen methodology, my doctoral journey is chronicled. Three landscapes, school, work, and faith, serve as the areas of emphasis.

A Roadmap For Applying The Contextual Integrity Framework In Qualitative Privacy Research, Priya C. Kumar, Michael Zimmer, Jessica Vitak

Computer Science Faculty Research and Publications

Privacy is an important topic in HCI and social computing research, and the theory of contextual integrity (CI) is increasingly used to understand how sociotechnical systems-and the new kinds of information flows they introduce-can violate privacy. In empirical research, CI can serve as a conceptual framework for explaining the contextual nature of privacy as well as an analytical framework for evaluating privacy attitudes and behaviors. Analytical applications of CI in HCI primarily employ quantitative methods to identify appropriate information flows but rarely engage with the full CI framework to evaluate such flows. In this paper, we present a roadmap to …

Remote, Rugged Field Scenarios For Archaeology And The Field Sciences: Object Avoidance And 3d Flight Planning With Suas Photogrammetry, Carla Klehm, Malcolm D. Williamson, Leland C. Bement, Brandi Bethke

Center for Advanced Spatial Technologies Publications and Presentations

Advances built into recent sUASs (drones) offer a compelling possibility for field-based data collection in logistically challenging and GPS-denied environments. sUASs-based photogrammetry generates 3D models of features and landscapes, used extensively in archaeology as well as other field sciences. Until recently, navigation has been limited by the expertise of the pilot, as objects, like trees, and vertical or complex environments, such as cliffs, create significant risks to successful documentation. This article assesses sUASs’ capability for autonomous obstacle avoidance and 3D flight planning using data collection scenarios carried out in Black Mesa, Oklahoma. Imagery processed using commercial software confirmed that the …

Multifunctional Nanomaterial Analysis Using Inexpensive Techniques, Casey Jordan , '24

Senior Theses, Projects, and Awards

Designing methods to comprehensively understand nanomaterial interactions is of paramount importance as nanomaterials gain widespread use and their environmental impact becomes a concern. While current characterization methods are suitable for initial assessments, there is a need for comprehensive techniques to evaluate end-of-use scenarios and environmental effects. This report emphasizes the potential of electrochemistry as a versatile measurement tool for nanomaterial analysis. Two projects are presented, showcasing innovative analytical architectures to overcome the limitations of existing techniques. Project 1 integrates linear sweep stripping voltammetry (LSSV) and particle impact voltammetry (PIV) to achieve kinetic resolution and size analysis of silver nanoparticles (AgNPs) …

Differences In The Metabolic Outputs Of Caulobacter Crescentus Modify The Kinetics Of Silver Nanoparticle Dissolution, Tyler M. Hicks , '24

Senior Theses, Projects, and Awards

Silver nanoparticles (AgNPs) are widely used within commercial products due to their distinct antibacterial and antimicrobial properties. As their utilization continues to increase, their inevitable improper disposal could present lasting environmental ramifications due to their nonspecific biotoxicity. One microorganism of interest is Caulobacter crescentus, a common freshwater bacterium found in locations where AgNPs end after their disposal. C. crescentus has two distinct cell types—a stalked and a swarmer form—each with their own unique function and metabolic outputs. Approximately 15% of the C. crescentus metabolome varies with cell cycle, thus making this an interesting and environmentally relevant model organism for …

From Visual Data To Auditory Landscapes In Arcgis Pro, Grace Hegland , '24

Senior Theses, Projects, and Awards

Data visualization is a central component to understanding spatial information in ArcGIS Pro. However, visualization creates an accessibility issue for visually impaired users. While ArcGIS supports two screen readers, JAWS and Microsoft Narrator, their ability to convey spatial relationships is limited to reading textual summaries and textual pop ups of spatial data [1]. This Senior Design project explores using data sonification to map ArcGIS data to piano pitches to create an auditory model of visually displayed map data. This auditory model allowed users to find facts and discover geospatial data trends. Ensuring fair access to information is essential for an …

Network Level Detection Of Iot Attacks Via Time Series Shape Mining, Srijani Basu

Masters Theses

This research proposes a method, for detecting intrusions in the Internet of Things (IoT) realm. This approach was specifically tested using datasets containing both benign, and attacks on smart home devices like the Belkin Wemo Power Switch, Lifx Smart Bulb, Amazon Echo, and Netatmo Welcome Camera. These attacks consist of specification-compliant volumetric DDoS attacks, which can be both direct and reflective, with very low traffic volumes implemented in an ON-OFF pattern. Here, the ON-OFF pattern can be referred to as a pulse attack strategy.

We combined non-linear statistical moving averages, and Dynamic Time Warping into a single framework that can …

Tools For Biomolecular Modeling And Simulation, Xin Yang

Mathematics Theses and Dissertations

Electrostatic interactions play a pivotal role in understanding biomolecular systems, influencing their structural stability and functional dynamics. The Poisson-Boltzmann (PB) equation, a prevalent implicit solvent model that treats the solvent as a continuum while describes the mobile ions using the Boltzmann distribution, has become a standard tool for detailed investigations into biomolecular electrostatics. There are two primary methodologies: grid-based finite difference or finite element methods and body-fitted boundary element methods. This dissertation focuses on developing fast and accurate PB solvers, leveraging both methodologies, to meet diverse scientific needs and overcome various obstacles in the field.

Accurate Characterization Of Binding Kinetics And Allosteric Mechanisms For The Hsp90 Chaperone Inhibitors Using Ai-Augmented Integrative Biophysical Studies, Chao Xu, Xianglei Zhang, Lianghao Zhao, Gennady M. Verkhivker, Fang Bai

Mathematics, Physics, and Computer Science Faculty Articles and Research

The binding kinetics of drugs to their targets are gradually being recognized as a crucial indicator of the efficacy of drugs in vivo, leading to the development of various computational methods for predicting the binding kinetics in recent years. However, compared with the prediction of binding affinity, the underlying structure and dynamic determinants of binding kinetics are more complicated. Efficient and accurate methods for predicting binding kinetics are still lacking. In this study, quantitative structure–kinetics relationship (QSKR) models were developed using 132 inhibitors targeting the ATP binding domain of heat shock protein 90α (HSP90α) to predict the dissociation rate …

Prevention Innovations Spring 2024 News, Prevention Innovations Research Center

PIRC Newsletter

No abstract provided.

Now I See You, Now I Know You: How Constructions Of Space And The Self Navigate The Tension Between Reenchantment Of The World And Intimate Communion In Autobiographical Performance, Huong Nguyen

Theatre and Dance Honors Projects

The transformative power of live performances lies in their reenchantment of the world: how they allow us to see special qualities of everyday objects and phenomena. Autobiographical theatre, rather than trying to find new ways of seeing, aims to transform the audience to “[make] the stranger less strange”. How do these qualities co-exist in autobiographical performance, and how does such a style of performance navigate them? By centralizing a comparative analysis of stagecraft in Aya Ogawa’s The Nosebleed and my honors project, Anti-Cartesian Variety Show, I demonstrate how constructions of space and the self help collapse the boundary between reenchantment …

Abolition Economics, Jessica Wolpaw Reyes, René Reyes

Michigan Journal of Race and Law

Over the past several decades, Law & Economics has established itself as one of the most well-known branches of interdisciplinary legal scholarship. The tools of L&E have been applied to a wide range of legal issues and have even been brought to bear on Critical Race Theory in an attempt to address some of CRT’s perceived shortcomings. This Article seeks to reverse this dynamic of influence by applying CRT and related critical perspectives to the field of economics. We call our approach Abolition Economics. By embracing the abolitionist ethos of “dismantle, change, and build,” we seek to break strict …

2024 (Spring) Ensi Informer Magazine, Morehead State University. Engineering Sciences Department

ENSI Informer Magazine Archive

The ENSI Informer Magazine published in the spring of 2024.

Effect Of Different Parameters On Powell-Eyring Fluid Peristaltic Flow With The Influence Of A Rotation And Heat Transform In An Inclined Asymmetric Channel, Rana Ghazi Ibraheem, Liqaa Zeki Hummady

Baghdad Science Journal

In this article, the effect of the rotation variable and other variables on the peristaltic flow of Powell-Eyring fluid in an inclined asymmetric channel with an inclining magnetic field through a porous medium with heat transfer is examined. Long wavelength and low Reynolds number are assumed, where the perturbation approach is used to solve the nonlinear governing equations in the Cartesian coordinate system to produce series solutions. distributions of velocity and pressure gradients are expressed mathematically. Through the collection of figures, the impact of various criteria is explained and graphically represented. These numerical results were attained using the mathematical application …

Editorial: Applied Computing 2023, Yousra Abdul Alsahib S. Aldeen, Yusliza Yusoff, Samira Naji Kadhim

Baghdad Science Journal

Applied computing utilizes aspects of computer science to solve problems in several disciplines, including business, politics, education, and the environment. Occupied in this field, it will likely use a range of programming, graphic applications, networking, software engineering and operating systems management skills to collect, analyze, store, and deliver information that will help resolve issues for individuals, companies, and groups. Applied computing is the study of both applied computer science and theoretical. Thought the intersection of information technology, computer science, and business, applied computing focuses on technical computing concepts and the occurrence of skills in organizational leadership and business strategy. It …

On Α ̌–Φ ̆-Fuzzy Contractive Mapping In Fuzzy Normed Space, Raghad I. Sabri, Buthainah A. A. Ahmed

Baghdad Science Journal

The idea of fixed points represents one of the most potent mathematical tools. This paper's main purpose is to introduce a new kind of fuzzy contractive mapping in a fuzzy normed space (briefly space) namely "fuzzy contractive mapping". We proved some fixed point results for this mapping in the setting of space using the triangular property of fuzzy norm. Moreover, under specific conditions, some other results for such type of mapping are established. Finally, an example is offered to show the results' usefulness.

Generation, Dynamics, And Interaction Of Quartic Solitary Waves In Nonlinear Laser Systems, Sabrina Hetzel

Mathematics Theses and Dissertations

Solitons are self-reinforcing localized wave packets that have remarkable stability features that arise from the balanced competition of nonlinear and dispersive effects in the medium. Traditionally, the dominant order of dispersion has been the lowest (second), however in recent years, experimental and theoretical research has shown that high, even order dispersion may lead to novel applications. Here, the focus is on investigating the interplay of dominant quartic (fourth-order) dispersion and the self-phase modulation due to the nonlinear Kerr effect in laser systems. One big factor to consider for experimentalists working in laser systems is the effect of noise on the …

Implications Of Minimum Description Length For Adversarial Attack In Natural Language Processing, Kshitiz Tiwari, Lu Zhang

Electrical Engineering and Computer Science Faculty Publications and Presentations

Investigating causality to establish novel criteria for training robust natural language processing (NLP) models is an active research area. However, current methods face various challenges such as the difficulties in identifying keyword lexicons and obtaining data from multiple labeled environments. In this paper, we study the problem of robust NLP from a complementary but different angle: we treat the behavior of an attack model as a complex causal mechanism and quantify its algorithmic information using the minimum description length (MDL) framework. Specifically, we use masked language modeling (MLM) to measure the “amount of effort” needed to transform from the original …

Optimising The Fashion E-Commerce Journey: A Data-Driven Approach To Customer Retention, Hasna Luthfiana Fadhila, Vynska Amalia Permadi, Sylvert Prian Tahalea

Knowledge Engineering and Data Science

A fashion e-commerce company offers a wide range of products from domestic and international brands that are popular with young people. However, there has been an increase in non-organically acquired customers, many of whom do not return to make repeat purchases. This has led to a higher customer churn rate, with a significant proportion of non-organically sourced customers failing to become repeat purchasers. Consequently, a churn analysis and prediction model were developed to address this issue. This paper employs the Recency, Frequency, and Monetary (RFM) framework for churn analysis and prediction. The framework is underpinned by three key dimensions: last …

Random Forest Algorithm To Measure The Air Pollution Standard Index, Ariyono Setiawan, Untung Lestari Wibowo, Ahmad Mubarok, Khoirunnisa Larasati

Knowledge Engineering and Data Science

This study uses the Random Forest algorithm to measure and predict the Air Pollution Standard Index (APSI) at Blimbing Banyuwangi Airport. Air pollution data, including concentrations of O3, CO, NO2, SO2, PM2.5, and PM10, were collected from air monitoring stations at the airport from April 15-30, 2024. APSI measurement followed established formulas by relevant authorities. Data analysis utilized statistical approaches and computational algorithms. The findings reveal that air quality at the airport is generally "Moderate," with occasional "Good" days. The Random Forest algorithm effectively predicts APSI based on existing pollution data. These results provide insights for improving air pollution management …

A Novel Approach To Defect Detection In Arabica Coffee Beans Using Deep Learning: Investigating Data Augmentation And Model Optimization, Yusriel Ardian, Novta Danyel Irawan, Sutoko Sutoko, I Nyoman Gede Arya Astawa

Knowledge Engineering and Data Science

Arabica coffee beans have valuable market worth because of their taste and quality, and there are defects like wholly and partially black beans that can lower the standards of a product, especially in the premium coffee sector. However, the manual processes used to detect the defects take an inordinate amount of time and are inefficient. This study aims to bridge the knowledge gap on the automated detection and recognition of the defects present in the Arabica coffee beans by creating and optimizing a CNN model based on a modified VGG16 architecture. The model applies data augmentation, rotation, cropping, and Bayesian …