Word Study

My primary objective in undertaking this Honors project in word study was to increase my command and capabilities in utilizing words. Understandably, as one progress in his education and life, the need for words--more precise meanings, more vivid and appropriate words--are needed. It is an open-ended endeavor. In order to accomplish this objective, I undertook as my requirement for each week to study and fully comprehend the definition of one hundred words. This was efficiently accomplished through the book, Word Mastery Made Simple by Arthur Waldhorn, Ph.D. an Arthur zeiger, Ph.D. Each chapter has a core list of fifty words, plus supplementary information about the English language (i.e. prefixes, suffixes, synonyms, etc.). Included in each chapter are Word Mastery Tests that help the student to understand the words and their uses more fully. Two chapters were required per week along with a conference time each week was used as a time to discuss the words and their meanings, and clean up anything that might be confusing

Financial Aid Director: Educator, Leader, or Manager

The landscape of higher education is ever-evolving, and the financial aid office, in particular, has experienced drastic changes throughout the years in order to become the massive and complex system that is known today. Considering that financial aid can directly influence major institutional benchmarks such as enrollment and graduation rates, and the fact the position of financial aid director is not standardized across institutions of higher education, a further look into the primary role of a financial aid director is important and necessary. This study will allow for a better understanding of what behavioral characteristics are most closely associated with directors of financial aid who are members of the Coalition of State University Aid Administrators (COSUAA). More specifically, the primary purpose of this study is to better understand whether the COSUAA financial aid directors identify primarily as educators, leaders, or managers. The framework presented by Gregory Elkins during his research on student affairs officers served as the conceptual framework behind this study. Elkins (2006) pulled from the theoretical perspective of Winston et al. (2001), which outlined that student affairs administration focuses on three roles or domains: an educator, a leader, and a manager. The web-based survey adapted for this study was sent to COSUAA financial aid directors over a two week period in July 2019. The results yielded a 48.9% response rate, and the data collected was able to identify that directors of financial aid at COSUAA institutions primarily consider themselves to be leaders, most admire leaders, and perceive their overall responsibilities as those of a leader. However, the data also revealed that the manager domain best describes their time spent daily, as well as what is most essential for aspiring financial aid directors. Nine one-way ANOVAs were conducted using Bonferroni adjusted alpha levels of .05, and this analysis suggested a significant difference in how directors who self-identify as a leader and directors who self-identify as a manager view their overall responsibilities as a manager; the time spent daily as a manager; the time spent daily as a leader; and the essentialness of the manager domain to aspiring aid directors. Advisor: Brent Cejd

Edge-Cloud Computing for IoT Data Analytics: Embedding Intelligence in the Edge with Deep Learning

Rapid growth in numbers of connected devices including sensors, mobile, wearable, and other Internet of Things (IoT) devices, is creating an explosion of data that are moving across the network. To carry out machine learning (ML), IoT data are typically transferred to the cloud or another centralized system for storage and processing; however, this causes latencies and increases network traffic. Edge computing has the potential to remedy those issues by moving computation closer to the network edge and data sources. On the other hand, edge computing is limited in terms of computational power and thus is not well suited for ML tasks. Consequently, this paper aims to combine edge and cloud computing for IoT data analytics by taking advantage of edge nodes to reduce data transfer. In order to process data close to the source, sensors are grouped according to locations, and feature learning is performed on the close by edge node. For comparison reasons, similarity-based processing is also considered. Feature learning is carried out with deep learning: the encoder part of the trained autoencoder is placed on the edge and the decoder part is placed on the cloud. The evaluation was performed on the task of human activity recognition from sensor data. The results show that when sliding windows are used in the preparation step, data can be reduced on the edge up to 80% without significant loss in accuracy

Alexandra Leaving: An Exploration into Sherlock Holmes and the Writer, Reader, Character Relationship

My project explores the relationship between reader, writer, and character. More specifically, I am investigating the character of Sherlock Holmes. Many aficionados of the series entertain themselves by pretending that Holmes was a real historical figure and using Doyle’s suggestions to create theories for solving “problems” or mysteries left by the stories. Why did Watson’s wife call him ‘John’ when we all clearly know his name is James? Could Holmes really survive his fall off of Reichenbach Falls when his death seemed eminent? How did Holmes know so much about the swamp adder when it is not even a real snake? All of these questions are ones of authorial (un)intention, but other players take the game to the next level and try to infer facts about Holmes’ personal life that are out of the scope of Doyle’s writing. Readers want to know if Holmes was ever married or had children. Was Watson secretly the genius all along and Holmes merely took the credit? Did Holmes’ drug use have a deeper and darker side? Like others before me, I attempt to answer questions of this second nature through story and the writing of a novella. While I am writing about Holmes, I am also writing about all authors and their characters as well as comparisons between loving relationships and relationships readers have with books.No embarg

Validating Annual Growth Bands of Deep-Sea Black Corals and Calculating Ocean Reservoir Ages from the Gulf of Mexico and Southeastern United States

Deep–sea black corals have been found to be long-lived and grow in a tree like fashion depositing rings in their skeleton that have been suggested to be annual growth bands. Iodine was used in this study to develop a novel dating method to measure the life spans and growth rates of these black coral, Leiopathes sp. The visual growth band count dating method was conducted on three of the GOM specimens and resulted in life spans ranging from 490 ±50 to 1315 ±130 years with growth rates ranging from 11 ±3 to 16 ±2 μm yr-1. The iodine dating method resulted in life spans of 630 ±65 to 1240 ±125 years and growth rates ranging from 10 ±1 to 19 ±3 μm yr-1. The life spans and growth rates that resulted from the counting of iodine peak generally matched the radiocarbon results, which yielded life spans of 620 ±40 to 2040 ±40 Cal yr. BP (before present 1950). The new iodine dating method in conjunction with radiocarbon and visual ring counts from SEM images validated the annual growth bands in the deep-sea black coral Leiopathes sp. from the GOM and SEUS. Using the independent (iodine) age models in conjunction with the radiocarbon records, ocean reservoir age records can be developed for the last ~500 to 1000 years. These findings provide a rare continuous record through time of highly variable reservoir ages suggestive of changing ocean dynamics in association with climatic events in the late Holocene. The preferred explanation for the variability found in these reservoir ages is that the changes in the reservoir ages reflect changes in the strength of the Yucatan current. This study is the first to validate that the rings deposited in the skeleton of deep-sea black corals, Leiopathes sp., are annual growth bands and that peaks in iodine counts associated with the growth band can be used as an independent dating method if good quality thin sections are made before analyses are conducted

Edge-cloud IoT Data Analytics: Intelligence at the Edge with Deep Learning

Rapid growth in numbers of connected devices, including sensors, mobile, wearable, and other Internet of Things (IoT) devices, is creating an explosion of data that are moving across the network. To carry out machine learning (ML), IoT data are typically transferred to the cloud or another centralized system for storage and processing; however, this causes latencies and increases network traffic. Edge computing has the potential to remedy those issues by moving computation closer to the network edge and data sources. On the other hand, edge computing is limited in terms of computational power and thus is not well suited for ML tasks. Consequently, this thesis aims to combine edge and cloud computing for IoT data analytics by taking advantage of edge nodes to reduce data transfer. Feature learning is performed on the edge with deep learning: the encoder part of the trained autoencoder is placed on the edge to extract relevant features. These features are sent to the cloud where the final ML task is performed directly, or the original features are first restored using the decoder part of the autoencoder. In the single-node model, all data are considered together and processed on a single edge node. In the multi-node model, sensors are grouped according to the IoT device locations or according to similarities between sensors, and different groups are processed on different edge nodes. The evaluation was performed on the task of human activity recognition from sensor data. Results show that data can be reduced on the edge up to 80% without significant loss in accuracy