TTU Published Journals @ Volpe Library
Not a member yet
971 research outputs found
Sort by
*WINNER* The European Question in America, 1861-1865
No full textInternational relations have been a major aspect of almost all countries. Such was the case for the Confederate States of America as they needed foreign recognition to secure their hope of becoming their own country after breaking away from the United States of America. To achieve this, the Confederate government approached Great Britain in hopes of securing diplomatic relations, foreign recognition, and an ally in the American Civil War. On one hand, foreign relations with the Confederate States of America seemed positive due to Confederate cotton. However, the British government ultimately decided that it would be too costly for them to enter into such a position. Ultimately, Great Britain's recognition of the Confederate States of America would have sparked a nationwide famine from the loss of United States wheat, the decline of their international image due to them supporting a country that has institutionalized slavery, and the unrest of the British population due to there being an anti-war consensus after the Crimean War. Thus, the British government decided to keep their relations with the United States rather than formally recognizing or making treaties with the Confederate States of America
Development of Forest Health Curriculum for Private Landowners
No full textOur team in the 2021-22 Environmental and Sustainability Capstone created curricula for several topics of interest to Upper Cumberland. Our primary focus was to help female private woodland landowners who may not have the resources available to them to learn their land better. Even though our main focus is women, our curriculum is open to anyone with the desire to learn. The topics we covered are: carbon sequestration, soil health, native and invasive plant species, plant species identification and foraging, and grants and funding. When managing their forestland, whether leaving the land be or harvesting timber, owners need to understand carbon sequestration and the identification and management of natural and invasive species. Soil health is vital to tree health. In addition, there are financial resources available to land owners, but most people do not know where to find the resources. The goal of this research is to provide resources for landowners that want to learn how to best care for their forestlands in this area
*WINNER* Microstructures in faulted sandstone near Spencer, Tennessee
No full textRoad construction along State Route 111 north of Spencer, Tennessee exposed 150 meters of fresh outcrop of Pennsylvanian Sewanee Conglomerate. Here, the Sewanee is a 40-meter thick cross-bedded conglomeratic quartz sandstone that is yellowish-gray to yellowish-brown in color. The outcrops on the east and west side of the road contain numerous strike-slip and thrust faults associated with Alleghenian deformation and the formation of the Appalachian Mountains. Fault-damage zones of white friable cataclasite occur in proximity to closely spaced strike-slip faults. These zones may represent internal deformation of the regional Cumberland Plateau overthrust. Point-counting analysis of nine samples collected from the outcrop reveals that pressure-solution microstructures are the most common microstructure, affecting nearly 95% of the quartz grains. Microcracks, representing brittle deformation microstructures, affect 25-52% of the grains and are most abundant in fault-damage zones. Cataclastic bands are localized zones of intense brittle deformation and are associated with faulting. The assemblage of microstructures indicates that rock deformation during the Alleghanian orogeny occurred at low temperature (<300°C) and shallow depth (<10 km)
*WINNER* Synthesis of near-infrared pigments for novel sensor applications
No full textCalcium copper silicate, known as Egyptian Blue (EB), is a pigment that exhibits a strong near-IR fluorescent emission when exposed to a strong light source. This property makes it a novel candidate for use as a basis for dissolved ion sensors, as its IR signal is very strong in comparison with current commonly used IR reporters, such as gold shell nanoparticles. Most commercially available samples; however, are created with dyeing and pigmentation in mind, rather than chemical application. To apply EB as a sensor lens component, it must be synthesized to form a reproducible and laboratory grade sample, free from compounds present in dyes that can affect the adherence and emission of an EB coating on a lens. In order to synthesize a sample of EB, a solid-state reaction was employed to react powdered crystalline solids under a high temperature environment. The resulting sample is then characterized through x-ray diffraction to determine the success of the solid-state synthesis
Effects of Social, Professional, and Spiritual Support on Anger and Irritability Among Physical Abuse Survivors
No full textChildhood abuse is a rampant concern throughout the nation. After reviewing the literature, a potential gap and opportunity to examine and better understand the trauma symptom of anger and irritability among childhood physical abuse survivors revealed itself. The purpose of this research was to examine the relationship between social support coping mechanisms, professional support coping mechanisms, and spiritual support coping mechanisms and anger and irritability among survivors of childhood physical abuse controlling for sex and race. The research study utilized a descriptive correlational design using multiple regression to analyze data from the National Data Archive on Child Abuse and Neglect (NDACAN) dataset 170 titled Longitudinal Studies of Child Abuse and Neglect (LONGSCAN) Assessments 0-18 (Runyan et al., 2014). These data have been collected from survivors, their caregivers, and educators in the Southwest, East, and Northwest regions of the United States between 1991 and 2012. Findings suggest that some coping mechanisms do have a predictive effect on anger and irritability scores of physically abused adolescents. Identifying and understanding these coping mechanisms can inform future supports developed to aid adolescent survivors of physical abuse struggling with anger and irritability
The State of Adversarial Machine Learning and Its Relevance to Cybersecurity
No full textMachine learning has been utilized for a number of applications in both the public and private sectors and is slated to become even more widely used in years to come. For this reason, the importance of security in this field cannot be understated. There are various ways to exploit and trick machine learning models into behaving in unexpected or unfavorable ways. Adversarial machine learning, the field of study of such methods, can be understood as a form of cyber threat intelligence, which describes the tools, knowledge, and experiences used to better understand cyber-related threats. We will further explain the security implications of adversarial machine learning, evaluate current progress in the field, and discuss a recent example of a related attack and its impact
Generating Explanations for Machine Learning Based Malware Detection Using SHAP
No full textIn recent years, researchers have been analyzing the effectiveness of machine learning models for malware detection. These approaches have ranged from methods such as decision trees and clustering methods, to more complex approaches like support vector machines and neural networks. It is relatively well accepted that for most use cases in this domain, neural networks are the superior approach. This, however, comes with a caveat. Neural networks are notoriously complex, therefore, the decisions that they make are often just accepted without questioning why the model made that specific decision. The black box characteristic of neural networks have challenged researchers to explore methods to explain neural networks and their decision making process. In this work, we deploy the SHAP explainable machine learning approach on a collection of machine learning methods to show why these models make the decisions that they do and which features are the main contributors to these decisions
Predicting Winners of Big Brother Using Predictive Methods of Data Mining
No full textData mining techniques such as classification methods can be used to predict the value of a variable based on other attributes in the same dataset. Prediction models can be used on data like sporting statistics and political polls. One area that prediction has not crossed over into yet is reality television. These shows have winners, many seasons, lots of contestants, and even more information about the players released to the public before the show starts. A great example of this is Big Brother. Before every season, each contestant completes pre-season interviews with the producers, and these answers are released to the public. This information, along with their demographic information, could be used to predict the winner before one player steps foot into the house. Ideally, a dataset would already exist with all this information on each contestant of Big Brother, but it does not. Therefore, the first step needs to be creating this dataset. After this happens, testing can begin. This dataset would be tested with prediction models, specifically classification methods. Once the testing begins, any data revision can occur. For example, if there is not enough data, information about contestants from Big Brother Canada and Big Brother UK can be added to the dataset. Hopefully, in the end, a model will be able to correctly identify a winner, or future winner, of Big Brother
An approach towards consumer power usage pattern using classification technique
Get PDFToday's life is embedded with technology that consumes an enormous amount of electricity. To maintain the uninterrupted electricity supply, keeping track of the consumer demand pattern is a dire necessity, particularly in the case of the smart grid system. Using a load usage pattern as well as the timing of peak electricity usage, an approach is proposed in this paper to estimate energy consumption patterns for residential and industrial consumers. Although in past, tariff structures were mainly applied on the kind of activity among consumers, the kind of activity and electrical behavior of the customer has a very poor relationship. Applying clustering techniques to classify customers according to load curves is more efficient. This paper proposes a two-fold classification algorithm followed by a supervised learning technique to classify electric customers. At First, results are obtained from the classification techniques and compared. A decision matrix is projected to reach the goal of predicting power consumption behavior in the second phase
Synthesis of pharmaceutically relevant terpene derivatives for use as topoisomerase inhibitors
No full textTopoisomerase inhibitors play an important role in the fight against cancer. The focus of this research is to create a suite of pharmaceutically relevant terpene derivatives that can then be evaluated for usefulness in inhibiting topoisomerase. Multiple aldehydes have been chosen to be evaluated, all containing 19F. The targets of this work are terpenoids based on the diterpene carvone. The target molecules have synthetic handles that allow expansion to a known family of topoisomerase inhibiting diterpenes, the trachylobane family. While the inclusion of the 19F label here allows for the analysis of the protein interactions that these terpenoids participate in. The scope of this synthesis and the novel molecules produced were evaluated for reproducibility and usefulness in the inhibition of topoisomerase