Digital Commons Network^™

Victory By The Weakest: Effects Of Negative Advertising In N>2 Candidate Campaigns, Jesse T. Richman

Political Science & Geography Faculty Publications

The truel, or three way duel, has distinct properties from duels: the weakest contestant often has a very good chance to win. This paper explores application of the logic of truels to election campaigns involving negative advertising. We show that negative campaigning that pits the leading candidates against each other can create circumstances in which the third (or worse) place candidate wins in one or more of the Nash equilibria of the game. We then study whether the simulated existence of an opportunity for Nash equilibrium victory by third place candidates predicts such outcomes in U.S. state-wide elections.

Using A Cross-Cutting Theoretical Framework To Explore Difficulties Learning Human Anatomy And Physiology, Tara Nicole Slominski

Biological Sciences

Across the United States, Human Anatomy and Physiology (HA&P) courses typically have some of the highest withdrawal and failure rates on college campuses. These high enrollment course typically serve as gate-keepers for those individuals with aspirations of entering the medical field. In light of the growing national shortage of healthcare professionals, there is a pressing need to improve the state of HA&P education at a national scale. The goal of this dissertation is to understand why undergraduate students struggle to succeed in HA&P courses. I leveraged multiple frameworks from biology education research, physics education research, and cognitive psychology to understand …

Method Lawyering: Immersion Teaching Illustrated, Kris Franklin

Articles & Chapters

Immersive law teaching uses simulated client experiences to drive the learning of legal doctrine, while enriching comprehension and mastery by integrating of a range of lawyering competencies. In an effort to “show, don’t tell,” this Article provides an immersive introduction to immersive teaching though the lens of a family law course. A series of vignettes illustrate student work in the class. The vignettes become jumping off points for more specific discussion of the nuts and bolts of teaching and learning the law in the course, and for broader consideration of possibilities for immersive learning in legal education.

Near-Bottom Currents At Station M In The Northeast Pacific, Thomas Connolly, Paul Mcgill, Richard Henthorn, Drew Burrier, Cynthia Michaud

Faculty Research, Scholarly, and Creative Activity

No abstract provided.

Utilizing The Concerns Based Adoption Model To Support Teachers In Implementing The Mtss Behavior Pathway, Amanda Mae Henry

Education

Schools and educators are faced with the tremendous task of preparing students to be successful in school and beyond in a fast-paced, ever changing world. Behavioral skills, just as academic skills are critical for student success. While the West Fargo secondary schools have established a systematic and effective structure of support for academic success, known as MTSS academics, no such structure exists to address the behavioral needs of students. Further, there is no system in place for the training of teachers to begin the implementation of the MTSS behavior supports. Without teacher training during the implementation of the program, teachers …

Exploring The Relationship Between Dual Credit Experience And Self-Efficacy: The Perspective Of First-Generation College Students, Laura Marie Kiemele

Education

Dual credit options allow high school students to enter college with college credits earned, as well as gain lived experience of the role expectations, academic rigor, and time it takes to complete college-level work. While past studies have identified benefits of dual credit for first-generation college students in particular, few have investigated the nature of that relationship. This qualitative study examined the relationship between first-generation students’ dual credit experiences and academic self-efficacy. Interviews were conducted with three first-generation college students in fall 2019. Findings indicate first-generation students who engage in a rigorous dual credit experience that results in mastery experience …

Examining The Relationship Between Elementary School Teachers' Multicultural Attitudes And Self-Efficacy For Teaching English Language Learners, Daisy Mae Figueroa

Education

An increase in English Language Learners (ELLs) in public schools across the nation is forcing stakeholders to reexamine how teachers are being prepared to effectively teach culturally and linguistically diverse students. It is unclear to what extent inservice teachers feel prepared to work with ELLs and what factors impact their feelings of preparedness. The purpose of this study was to examine the relationships between teachers’ self-efficacy for teaching ELLs, general teaching self-efficacy, and multicultural attitudes. The study also explored whether teachers’ self-efficacy for teaching ELLs could be explained by variables that include years of teaching experience, highest degree earned, perception …

The Effect Of Fatty Acid Unsaturation On Properties And Performance Of Monomers And Latex Polymers From Plant Oils, Zoriana Demchuk

Coatings and Polymeric Materials

The interest in renewable natural resources, including plant oils, has become increasingly appealing due to the oil abundance, availability, and wide range of applications for polymers and polymeric materials thereof. In this dissertation, a library of plant oil-based acrylic monomers (POBMs) with a broad range of unsaturation was synthesized using a one-step transesterification. It is demonstrated that the unsaturation degree of plant oil remains preserved during the synthesis and determines the structure and properties of POBMs. The life cycle assessment (LCA) was conducted in this study to evaluate the environmental impact of soybean oil-based acrylic monomer (SBM) production. LCA was …

Investigation Of Novel Approaches For Improved Amphiphilic Fouling-Release Coatings, Alireza Rahimi

Coatings and Polymeric Materials

Marine biofouling has troubled mankind, both environmentally and economically, since they set sail, resulting in many undesired consequences such as increased drag, reduced maneuverability, increased fuel consumption and greenhouse gas emissions, and heightened maintenance costs. This problem is highly complex as it involves more than 4000 marine organisms with varying modes of adhesion and surface preferences as well as many aquatic environments. The common state-of-the-art approaches to contend with marine biofouling on the submerged surfaces of ships in seawater has antifouling (AF) and fouling-release (FR) surfaces. As AF coating systems utilize biocides which are often toxic to the environment to …

Power-Efficient Adaptive Memory Design And Optimization For Video And Deep Learning, Hritom Das

Electrical and Computer Engineering

Memory devices such as Static Random-Access Memory (SRAM) and Dynamic Random-Access Memory (DRAM) are dominating members of today’s semiconductor industry. Most of the silicon area in a digital system is occupied by memory devices. The video decoder and deep learning are especially constrained by memory devices to process a large amount of data. For example, memory devices are consuming lots of power for video processing. Nowadays, all mobile electronics, such as mobile phones and laptops, are using video data a lot. Due to that, the battery life of mobile devices is highly dependent on power consumption of memory devices. To …

Development Of Performance Optimized Rotation Tolerant Viola-Jones Based Blackbird Detection, A Throughput Optimized Asynchronous Mac Implementation, And Automated Wheat Lodging Estimation, Nauman Jalil

Electrical and Computer Engineering

The research described in this doctoral dissertation focuses on three main topics:1) performance optimization of the Viola-Jones Algorithm (VJA) for red-winged blackbird (Agelaius phoeniceus) detection, 2) further increasing performance of an already optimized asynchronous Multiply and Accumulate (MAC) unit, and 3) development of a framework to differentiate between lodging and non-lodging areas of a field from visible and multispectral aerial drone images. The first topic explores VJA rotational robustness, since VJA object detection is inherently not invariant to in-plane object rotation. An efficient method to detect rotated blackbirds is developed, which provides a balance between detection accuracy and computational cost. …

Extraction Of Electromagnetic Properties Of Metamaterials With Branch Compensation From Phase Tracking, Jacob Christian Lewis

Electrical and Computer Engineering

In the field of electromagnetism, there are materials known as metamaterials which exhibit unique properties that can be exploited. Permittivity, defined as capacitance per meter, of a metamaterial can vary over frequency , time, or even be negative. This can be useful for tuning antennas, changing their operating frequency or direction of propagation, or even designing cloaking systems. However, the theory behind metamaterials needs to be studied further. One of the biggest issues to address is in determining the constitutive parameters of metamaterials which may be varying. Previous research has shown the issue of branches, or mathematical discontinuities, occurring in …

Lithium Ionic Conductivity And Stability Of Cubic Li7la3zr2o12 Solid Electrolyte A First-Principles Study, Sudipto Saha

Electrical and Computer Engineering

Garnet structured cubic LLZO crystal (Li56La24Zr16O96) is one of the most promising solid electrolytes for next-generation solid-state lithium-ion batteries. Ab initio molecular dynamics simulations have been employed to study the impacts of lithium vacancy defect and doping concentration on the lithium ionic conductivity and stability of LLZO. The number of lithium atoms in a unit cell of LLZO has been reduced from 56 to 53, where 56 lithium atoms represent the structure of stoichiometric LLZO, i.e., Li7La3Zr2O12. Similarly, the effect of Al and Ga doping on the conductivity and stability of LLZO material was also investigated. Our computational results confirm …

Using Classification And Clustering To Predict And Understand Student Behavior In An Innovation-Based Learning Course, Lauren Nichole Singelmann

Electrical and Computer Engineering

One of the Grand Challenges for Engineering is advancing personalized learning, but challenges remain to identify and understand potential student pathways. This is especially difficult in complex, open-ended learning environments such as innovation-based learning courses. Student data from an iteration of an innovation-based learning course were analyzed using two educational data mining techniques: classification and clustering. Classification was used to predict student success in the course by creating a model that was both interpretable and robust (accuracy over 0.8 and ROC AUC of over 0.95). Clustering grouped student behavior into four main categories: Innovators, Learners, Surveyors, and Surface Level. Furthermore, …

Continuous Deployment Transitions At Scale, Laurie Williams, Kent Beck, Jeffrey Creasey, Andrew Glover, James Holman, Jez Humble, David Mclaughlin, John Thomas Micco, Brendan Murphy, Jason A. Cox, Vishnu Pendyala, Steven Place, Zachary T. Pritchard, Chuck Rossi, Tony Savor, Michael Stumm, Chris Parnin

Faculty Research, Scholarly, and Creative Activity

Predictable, rapid, and data-driven feature rollout; lightning-fast; and automated fix deployment are some of the benefits most large software organizations worldwide are striving for. In the process, they are transitioning toward the use of continuous deployment practices. Continuous deployment enables companies to make hundreds or thousands of software changes to live computing infrastructure every day while maintaining service to millions of customers. Such ultra-fast changes create a new reality in software development. Over the past four years, the Continuous Deployment Summit, hosted at Facebook, Netflix, Google, and Twitter has been held. Representatives from companies like Cisco, Facebook, Google, IBM, Microsoft, …

Advancing Gender Equity In Stem: Antenarratives And Feminist Leadership Practices In Policy Work, Ashleigh Ryann Petts

English

While the field technical and professional communication (TPC) has long been concerned with workplace writing and policy writing, few studies have addressed the process of policy writing within an academic context. Using antenarrative and apparent feminism methodologies, this dissertation explores the policy writing process and feminist leadership practices of the DESIGN Committee, a group of women academics who worked to propose new policy to address gender inequity in the science, technology, engineering, and mathematics (STEM) fields for faculty working in their statewide educational system (SES). Employing methods of observation, participant observation, semi-structured interviews, and artifact collection over a period of …

Testing Gene-Environment Interactions For Rare And/Or Common Variants In Sequencing Association Studies., Zihan Zhao, Jianjun Zhang, Qiuying Sha, Han Hao

Michigan Tech Publications, Part 1

The risk of many complex diseases is determined by a complex interplay of genetic and environmental factors. Advanced next generation sequencing technology makes identification of gene-environment (GE) interactions for both common and rare variants possible. However, most existing methods focus on testing the main effects of common and/or rare genetic variants. There are limited methods developed to test the effects of GE interactions for rare variants only or rare and common variants simultaneously. In this study, we develop novel approaches to test the effects of GE interactions of rare and/or common risk, and/or protective variants in sequencing association studies. We …

Developing And Validating Active Learning Engagement Strategies To Improve Students' Understanding Of Programming And Software Engineering Concepts, Tamaike Mariane Brown

Computer Science

Introductory computer programming course is one of the fundamental courses in computer science. Students enrolled in computer science courses at the college or university have been reported to lack motivation, and engagement when learning introductory programming (CS1). Traditional classrooms with lecture-based delivery of content do not meet the needs of the students that are being exposed to programming courses for the first time. Students enrolled in first year programming courses are better served with a platform that can provide them with a self-paced learning environment, quicker feedback, easier access to information and different level of learning content/assessment that can keep …

Identifying & Analyzing Security Vulnerabilities While Integration Of Data From Cloud To Sql Dbms An Industrial Case Study, Simranjit Kaur

Computer Science

Data integration defines propulsion of data from numerous sources into a database system in a way that yields the information representing powerful analytics. Various industries are always working towards keeping their data confidential and in a manner that will let them mine it later & retrieve strong statistics out of it for procuring future profits. This research will discuss about using SaaS (Software as a service) and SQL (Structured Query Language) as a combined model for storing inspections data to achieve the above-mentioned goals that the companies are on the road to. Since SaaS and SQL comes into play, a …

A Realistic And Reliable Approach For Real Time Monitoring Of Infrastructure, Rakhen Garg

Computer Science

Rapid advancements in the field of site reliability engineering in the past few decades have made it an indispensable part of how humans create scalable and highly reliable software systems. The inherent need of a reliable site Infrastructure Monitoring System brings with it a great set of advantages in terms of monitoring availability, latency, performance and efficiency of the services. The main objective of this work is to design and implement an intuitive Real-Time Infrastructure Monitoring System (RIMS) that acts as a one-stop shop for keeping track of overall system’s health, services, downtimes and availability. RIMS extract a wide variety …

Brain Cancer Detection Using Mri Scans, Shanthanreddy Thotapally

Computer Science

An estimate of about 700,000 Americans today live with a brain tumor. Of these, 70% are benign and 30% are malicious. The average survival rate of all the malicious brain tumor patients is 35%. Diagnosing these tumors early on gives the best chance for survival. The Doctors use MRI scans to identify the presence of a tumor and it’s characteristics like the type and size. In this paper, I implemented a Deep learning convolutional neural network model that classifies the brain tumors using MRI scans. We shall use VGG-16 deep-learning approach to implement the machine learning algorithm. The proposed system …

Adaptive Mesh Refinment Applications For Adviction-Diffusion Problems Using Amrex, Venkata Kanumuru

Computer Science

In this paper we implemented an adaptive mesh refinement in high performance computing environment to study a wide range of problems in engineering. They are nonlinear Fisher-Kolmogorov equation, heat equation, advection equation and poisons equation using traditional message passing interface (MPI). We used adaptive mesh refinement library called AMReX for computation. AMReX is a numerical library containing the functionality to write massively parallel, block-structured adaptive mesh refinement (AMR) applications. Our study includes examples to solve poisons equation in traditional MPI approach and compared the performance between the two methods.

Extracting Useful Information And Building Predictive Models From Medical And Health-Care Data Using Machine Learning Techniques, Md Faisal Kabir

Computer Science

In healthcare, a large number of medical data has emerged. To effectively use these data to improve healthcare outcomes, clinicians need to identify the relevant measures and apply the correct analysis methods for the type of data at hand. In this dissertation, we present various machine learning (ML) and data mining (DM) methods that could be applied to the type of data sets that are available in the healthcare area. The first part of the dissertation investigates DM methods on healthcare or medical data to find significant information in the form of rules. Class association rule mining, a variant of …

Image Classification Using Transfer Learning And Convolution Neural Networks, Mohan Burugupalli

Computer Science

In the recent years, deep learning has shown to have a formidable impact on image classification and has bolstered the advances in machine learning research. The scope of image recognition is going to bring big changes in the Information Technology domain. This paper aims to classify medical images by leveraging the advantages of Transfer Learning over Conventional methods. Three types of approaches are used namely, pre-trained CNN as a Feature Extractor, Feature Extractor with Image Augmentation, and Fine-tuning with Image Augmentation. The best pre-trained network architectures such as VGG16, VGG19, ResNet50, Inception, Xception and DenseNet are used for classification with …

Prediction Accuracy Of Financial Data - Applying Several Resampling Techniques, Mohammad Reza Ali

Computer Science

With the help of Data Mining and Machine Learning, prediction has been a very popular and demanding instrument to plan and accomplish a future goal. The financial sector is one of the crucial sectors of present human society. Predicting the correct outcome is a pivotal matter in this sector. In this work, an assessment was done to the prediction efficiency by applying several Machine Learning Classification Algorithms and resampling methods. These techniques were applied to financial data, more specifically to Bank Marketing in order to predict the tendency of clients to subscribe to a bank term deposit. For the correct …

On The Applicability Of Deep Metric Learning To Address Source Code Authorship Attribution Problem Under Simulated Real-World Constraints, Sarim Zafar

Computer Science

Source code authorship attribution is a widely studied research topic in the information security domain. In this dissertation, we develop and evaluate models that enable us to solve source code authorship attribution using deep metric learning. In particular, first, we simulate a real-world setting. Second, we use a number of loss functions from the deep metric learning domain to train neural network models. Thirdly, we evaluate these different models' performance on a benchmark and determine whether there is a quantifiable performance difference between these deep metric loss functions. Lastly, we demonstrate how we can extend our proposed methodology address the …

A Comparative Study On Different Big Data Tools, Sifat Ibtisum

Computer Science

Big data has long been the topic of fascination for computer science enthusiasts around the world, and has gained even more prominence in recent times with the continuous explosion of data resulting from the likes of social media and the quest for tech giants to gain access to deeper analysis. This paper discusses various tools in big data technology and conducts a comparison among them. Different tools namely Sqoop, Apache Flume, Apache Kafka, Hive, Spark and many more are included. Various datasets are used for the experiment and a comparative study is made to figure out which tool works faster …

Credit Card Fraud Detection Predictive Modeling, Nishant Sharma

Computer Science

Finance fraud is a growing problem with consequences in the financial industry and data mining has been successfully applied to huge volume of complex financial datasets to automate and analyze credit card frauds in online transactions. Data Mining is challenging process due to two major reasons–first, profiles of normal and fraudulent behaviors change frequently and second, card fraud data sets are highly skewed. This paper investigates and checks the performance of Random Forest Classifier, AdaBoost Classifier, XGBoost Classifier and LightGBM Classifier on highly skewed credit card fraud data. Dataset of credit card transactions is sourced from European cardholders containing 284,786 …

3d Printing Technology On Spare Parts Business Supply Chain Management: A Case Study In Appliance Industry, Salih Boysan

Dissertations and Theses @ UNI

This study investigates the effects of using Additive Manufacturing (AM), also known as 3D printing, to produce spare parts within the supply chain of an appliance manufacturing company.

This research is based on an analysis of the operation of a spare parts business of an appliance manufacturing company. This research study used real data to investigate the feasibility of using 3D printing to reduce complexity in the spare parts division in terms of supplier rationalization, inventory reduction, and total cost of ownership. The research method used two scenarios: one where manufacturing spare parts traditionally was the baseline model and the …

Quantifying Sources Of Variability In Infancy Research Using The Infant-Directed-Speech Preference, Michael C. Frank, Katherine Jane Alcock, Natalia Arias-Trejo, Gisa Aschersleben, Dare Baldwin, Stéphanie Barbu, Elika Bergelson, Christina Bergmann, Alexis K. Black, Ryan Blything, Maximilian P. Böhland, Petra Bolitho, Arielle Borovsky, Shannon M. Brady, Bettina Braun, Anna Brown, Krista Byers-Heinlein, Linda E. Campbell, Cara Cashon, Mihye Choi, Joan Christodoulou, Laura K. Cirelli, Stefania Conte, Sara Cordes, Christopher Cox, Alejandrina Cristia, Rhodri Cusack, Catherine Davies, Klerk M De, Luche C Delle, Ld Ruiter, Dhanya Dinakar, Kate C. Dixon, Virginie Durier, Samantha Durrant, Christopher Fennell, Brock Ferguson, Alissa Ferry, Paula Fikkert, Teresa Flanagan, Caroline Floccia, Megan Foley, Tom Fritzsche, Rebecca L.A. Frost, Anja Gampe, Judit Gervain, Nayeli Gonzalez-Gomez, Anna Gupta, Laura E. Hahn, Hamlin J Kiley, Ee Hannon, N Havron, J Hay, M Hernik, B Höhle, Dm Houston, Lh Howard, M Ishikawa, S Itakura, I Jackson, Kv Jakobsen, M Jarto, Sp Johnson, C Junge, D Karadag, N Kartushina, Dj Kellier, T Keren-Portnoy, K Klassen, M Kline, E-S Ko, Jf Kominsky, Je Kosie, He Kragness, Aar Krieger, F Krieger, J Lany, Rj Lazo, M Lee, C Leservoisier, C Levelt, C Lew-Williams, M Lippold, U Liszkowski, L Liu, Sg Luke, Ra Lundwall, Cassia V Macchi, N Mani

School of Psychology

Psychological scientists have become increasingly concerned with issues related to methodology and replicability, and infancy researchers in particular face specific challenges related to replicability: For example, high-powered studies are difficult to conduct, testing conditions vary across labs, and different labs have access to different infant populations. Addressing these concerns, we report on a large-scale, multisite study aimed at (a) assessing the overall replicability of a single theoretically important phenomenon and (b) examining methodological, cultural, and developmental moderators. We focus on infants’ preference for infant-directed speech (IDS) over adult-directed speech (ADS). Stimuli of mothers speaking to their infants and to an …