20566 research outputs found
Sort by
Creative Brief for WK Kellogg\u27s Co
Get PDFIn recent years, cereal, the once classic and essential breakfast food has been losing its market share and overall sales in the breakfast category. WK Kellogg’s cereal brands include Frosted Flakes, Froot Loops, Frosted Mini Wheats, Special K, Rice Krispies, Raisin Bran, Corn Flakes, and more, yet their sales have been falling. They now face a challenge, as consumers become more cost and health conscious, how can cereal be made fun again? What ways can they engage with new audiences and further excite current customers? After conducting research, I have developed a creative brief and strategic pitch that include solutions to help WK Kellogg Co effectively meet the desires of younger generations
A 360 Perspective About Corporate Finance
Get PDFThis thesis provides a comprehensive reflection on the author\u27s experience in the “Finance 360” rotational internship program at Burns & McDonnell, a program designed to expose interns to the diverse functions within a corporate finance and accounting department. Over the course of 10 weeks, the author completed 12 different rotations, gaining hands-on experience across various financial disciplines. This paper highlights five rotations—Operational Financial Analysts, Financial Analytics, Internal Audit, Project Accounting, and Investments—that had the greatest impact on reshaping the author’s understanding of corporate finance. These experiences revealed the deep integration of finance with accounting, analytics, and strategic decision-making, far beyond the textbook concepts initially understood. In addition to technical exposure, the program emphasized mentorship, professional development, and the company’s strong employee-ownership culture. The experience not only deepened the author\u27s knowledge of corporate finance but also clarified future career interests and demonstrated the value of rotational internships in shaping career readiness
Cornelius Nepos: Fortune, Biography, and the Late Roman Republic
Get PDFAbstract: This paper examines ancient biography and the late Roman Republic by analyzing the surviving writings of Cornelius Nepos. Cornelius Nepos was a late Republican intellectual and friend of several of the most prominent literary figures of his day. The literature on Nepos tended to be dismissive of the author until the 1980s, when it began to shift towards viewing Nepos through the lens of ancient biography. By examining the theme of fortuna [fortune] throughout Nepos’ work and contrasting it with usage of the theme in other Latin authors or Greek historians, this paper demonstrates that Nepos adapts a longstanding historical theme to his own project and time in a number of ways. These include treating fortuna as a phenomenon that takes place at the level of the individual and focusing on how the invidia (jealousy) of one’s peers in response to good fortune can prove dangerous. These findings indicate that Nepos was an author with unique insights into the events of his own lifetime
IcyLib: A Scalable Solution for Reproducible Image Classification Workflows
Get PDFWith the rapid expansion of e-commerce over time, ensuring the diversity and quality of product images has become a critical challenge infeasible for human completion. In conjunction with Walmart Global Tech for the Team 1 Data Science Practicum Project, image classification models were trained to assess product image sets, but training and deploying such models often involves repetitive code and inefficient processes. This thesis presents a reusable modeling library, named IcyLib, designed to streamline the training, validation, and testing of image classification models as well as dataset importation using PyTorch. IcyLib provides a structured yet flexible approach for model implementation, currently supporting ResNet and EfficientNet architectures with minimal user effort through JSON configuration files. By automating dataset handling, model training, and performance evaluation, IcyLib significantly reduces redundancy and potential errors while improving usability, reproducibility, and readability of code. Experimental results demonstrate the efficiency and efficacy of this framework in classifying Walmart.com product images, offering a scalable solution for future applications in e-commerce image analysis
Balancing Growth and Identity: Tourism, Culture, and Economic Development in Dangriga, Belize
Get PDFThis thesis examines the interplay between tourism development and cultural preservation in Dangriga, Belize. Dangriga is a town with a rich Garifuna heritage, and its residents take great pride in maintaining and sharing their traditions with both future generations and visitors. However, Dangriga remains relatively underdeveloped as a tourist destination. By conducting interviews with community stakeholders, my team and I created a needs analysis focused on the most prominent concerns voiced by residents, while offering an outside perspective. In addition to our experiences in Belize, I conducted independent research on the potential impacts of cruise tourism, the benefits of community-based tourism models, and the critical role of government engagement in shaping sustainable and inclusive tourism development. Ultimately, this thesis aims to support tourism practices that preserve Dangriga’s heritage while addressing the town’s long-standing developmental challenges
Understanding the Effects of Aging on Skin Tissue Mechanics and Collagen Organization through Quantitative Polarized Light Imaging
No full textIntrinsic aging causes changes in the structure and mechanical properties in skin, yet the complex organization of the collagen fibers in the dermis makes it challenging to fully understand how these fibers behave and interact as skin gets older. In this study, we used the single-shot Quantitative Polarized Light Imaging (ssQPLI) system developed by Quinn Lab to measure the changes in collagen structure between young and old mice in response to mechanical testing. Our results showed that young skin was more effective at reorganizing when stretched. Specifically, young skin showed greater changes in directional variance (DV) and more fiber rotation toward the direction of loading, meaning the collagen structure could maintain its strength and flexibility under strain. In contrast, old skin showed smaller changes in DV and fiber rotation, suggesting that collagen fibers were less capable of adapting to mechanical forces. Our observed results did not always follow patterns found in previous studies, showing that collagen behaves in complex, non-uniform ways. Overall, these findings suggest that intrinsic aging impairs the ability of collagen to reorient under stress, and these results could help guide novel therapeutic methods focused on improving wound healing and enhancing the functions of the skin
Sustainability: Buzz Word or Future of Fashion? Measuring the Feasibility of Outright Sustainability among Fast Fashion’s Biggest Agents
Get PDFAbstract
The fashion industry is currently experiencing unsustainable rates of pollution within its supply chains. The rapid increase in demand for short lead times perpetrated by large-scale retailers has led to hazardous practices negatively affecting both the environmental conditions and working conditions of producing countries. With this increased pressure, relationships between brands and suppliers have become untenable. Limited transparency and imbalanced power dynamics at the hand of the industry’s leading retailers require restructuring in order to build more sustainable and equitable supply-chain practices. Further, governmental regulation is currently limited in its capacity to enforce sustainable business practices on a global scale. This analysis is applicable for the restructuring of the global supply chain and offers guidance to the necessary steps to build a truly circular fashion economy. Findings from this paper conclude that adoption of circular practices by fashion retailers must begin with investment in long-term sustainable production methods. These methods are shown to offer profitability when adopted through a diversified low-impact materials portfolio, more efficient energy sources, and improved utilization of excess materials created throughout the production process. Governmental bodies must enact more stringent regulatory measures to ensure the adoption of these practices while offering equitability to companies leading the charge in this transition, a process displayed by the efforts of the European Union. The results of this work show a feasible and profitable path towards outright sustainability within the fashion industry when encompassing all necessary measures
Cross-Facility Reliable Deep Learning Based Beef Marbling Assessment Via Unsupervised Domain Adaptation Regression
Get PDFBeef is one of the most important sources of animal protein and plays a crucial role in daily diets to support muscle growth, energy production and overall health. Historically, each beef carcass was evaluated by 3-5 skilled United States Department of Agriculture (USDA) meat graders, which are still considered as the gold standard for grading. Since 2009, electronic imaging grading systems have been approved by the USDA and have been gradually adopted in the grading facilities. Accurate and consistent beef grading plays a critical role in maintaining the quality, market value, and consumer trust in U.S. beef products. The USDA beef grading system, primarily based on fat marbling characteristics, has long served as the industry standard for classifying beef quality. However, traditional grading methods relying on human visual inspection have been prone to variability among graders and inconsistencies across processing plants. To address these challenges, this study developed a deep learning based solution to predict USDA beef grades by analyzing fat marbling patterns in carcass images collected from multiple processing facilities. The dataset provided by the USDA, which includes expert-graded images of beef carcasses from seven processing plants, provides numerical scores on a range of 0-1500, which was used to train convolutional neural networks (CNNs) such as ResNet, VGG, and Inception. Additionally, this study proposes a unified unsupervised domain adaptation regression method, which was employed to enhance the models’ ability to generalize across different environments. The dataset reflected real-world variability, such as differences in lighting, equipment, and operational practices, ensuring the models could adapt to diverse plant conditions. By correlating image-based features with USDA grades, the models successfully identified intricate marbling patterns and reduced variability compared to human graders. Statistical analyses showed that the deep learning based approach provided more uniform results across plants, addressing the inconsistencies of traditional methods. In comparison with commonly utilized generic CNN deep learning models, the newly proposed unsupervised domain adaptation model achieves a significantly better marbling score prediction performance in different processing facilities. This study not only automated the beef grading process but also introduced a scalable and efficient solution for the industry. The integration of domain adaptation ensured robust performance in varying plant environments, making the system practical for widespread adoption. Beyond reducing labor costs and improving grading accuracy, this research contributed to a fairer system for producers by further standardizing grading criteria across facilities. By bridging advanced technology with traditional practices, this study provides a framework for policy makers to regulate and approve deep learning based beef grading protocol into commonplace beef grading practices.https://scholarworks.uark.edu/hnrcsturpc25/1041/thumbnail.jp