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Te Hokinga Mai: The Role of Indigenous Knowledge Systems in the Repatriation of Human Remains: A Case Study in Toi Moko from Aotearoa New Zealand
No full textPrior to European colonization, the tradition of mummifying the head of an elite individual was very prevalent in Māori society. Due to the social rankings of these individuals, their heads would be covered in incised and inked markings called moko. With the introduction of Europeans, namely British colonizers, in Aotearoa New Zealand in the late 18th century, these Toi moko (mummified heads) quickly became a commodified item that left their homeland for foreign collecting institutions. This study looks at how these individuals are being brought back to Aotearoa New Zealand through a repatriation practice that is based on tikanga Māori, the Māori system by which correct protocols are defined. Tikanga Māori has influenced how museums in Aotearoa New Zealand, such as the National Museum of New Zealand Te Papa Tongarewa, go about the repatriation process and how the heads of these repatriated individuals are treated once they make their way back home
Nature and the Mind: Understanding the Influence
No full textThis study addressed the potential mental health benefits that being outside in nature can provide to an individual. The task was a 10 minute walk outdoors across two differing conditions. The two independent variables that were manipulated were the location of the task and the company one had during the task. 23 participants were randomly divided into either the nature or urban greenspace location and either the solo or accompanied walk group. Participants took an identical pre and post test to create an evaluation of initial and post task stress levels. The participants were asked additional questions about their experience outdoors and with the task. The results revealed a significant interaction between the two dependent variables of location and company which shows that those who were in the campus condition benefited the most from having company. Location also had statistically significant effects upon stress levels as those who were in the on campus urban greenspace location received greater benefits. The purpose of this study is to investigate the potential positive benefits that nature and natural environments could have on the mind and what natural and urban features may influence those benefits the most
InstaMatch: Influencer Recommendation System for Targeted Apparel Brand Marketing - A Case Study on ASOS
No full textThis paper explores the integration of machine learning (ML) applications in social media influencer marketing, using ASOS as a case study to examine its effectiveness in optimizing influencer-brand collaborations. With the digital marketing landscape rapidly evolving, traditional metrics like follower counts are no longer sufficient for effective influencer selection, particularly when engaging with Generation Z\u27s preference for authenticity and positivity. Given Gen Z\u27s significant role in influencer marketing, it\u27s vital for influencers to align with brand values, reflecting this demographic\u27s authentic preferences. Our study constructs a novel ML-based recommender system designed to enhance the precision of influencer selection by leveraging deep learning and natural language processing techniques. This system categorizes influencers, analyzes engagement rates, and ensures demographic alignment, tackling the scalability and accuracy challenges in influencer marketing. Through a cosine similarity model, we quantitatively evaluate the alignment between influencers and ASOS’s brand identity and goals, measuring the cosine of the angle between feature vectors of both entities. Our analysis, leveraging ASOS\u27s API data and influencers\u27 Instagram metadata, reveals significant improvements. The system achieved an F1 score of 0.74, indicating a balanced enhancement in precision and recall rates compared to a baseline model performance with an F1 score of 0.48. This result underscores the system\u27s efficacy in identifying influencers who resonate with Generation Z, presenting a substantial advancement over traditional selection methods
An Economic Assessment on the Relationship between Human Capital and GDP Per Capita
No full textThe determinants of economic growth and development are of utmost importance to the economist. The Solow growth model, the law of diminishing returns, the endogenous growth model, the catch-up effect, the Lewis Model, and Rostow’s Stages of Growth all serve as models for economic development. Additionally, historical examples like the Great Divergence and the Asian Economic Miracle all provide past examples of how countries have grown wealth. However, there are competing theories regarding what the most optimal conditions are for increased economic growth and development. The research posits that human capital is an instrumental factor in the economic growth and development of the nation. Through data from the World Bank, the model estimates an ordinary least squares and logged regression to determine whether human capital is a significant indicator of GDP per capita. Based on the regressions, human capital is a significant indicator of GDP per capita. A caveat of this notion is that there is not a definitive conclusion that higher human capital is directly casual to higher GDP per capita. Further research may assess the extent to which human capital serves as a casual mechanism for GDP per capita
F**k Your Assimilation: An Exploration of Japanese-American Diasporic Development Through Artistic Mediums
No full textRole of Residues R184 and W273 in 6-HNA and NADH Binding by 6-Hydroxynicotinate 3-Monooxygenase
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Soak Up the Sun: Exploring the Ability of Quantum Dots to Increase PAR Transmission in Seaman Corporation’s Dura-Grow Greenhouse Film to Improve Plant Growth
No full textSynthesis of 7-Substituted Quinolinones from Meta-Substituted Anilines: Investigating Whether the Product Selectivity Increases with Steric Bulk of Aniline R-Groups in an Isoelectronic Series
No full textPredicting Fraud in Accounts Payable using Benford\u27s Law and Neural Networks
No full textIn this thesis, real data from real fraud cases was leveraged to train a machine learning model. With the access to real data, model validation was conducted to prove the model was able to identify fraudulent transactions that it had never seen before leveraging patterns derived from Benford\u27s Law. This law has proven powerful in recognizing patterns of numerical data that are un-natural. This set of work expands on the known powerful capabilities of Benford\u27s Law by layering in related features that help to make the system able to recognize patterns in transactions very effectively. The overall objective is to focus large sets of data that contain very few fraudulent transactions down to a manageable number of high risk transactions to be further investigated