This paper will cover topics regarding remote work. More specifically, remote work for the field of logistics. It will also dive into remote work platforms themselves e.g., Slack, Zoom, etc. Microsoft Teams, the specific software we used while I was at my internship, will be analyzed as well. I will, specifically, be analyzing the fundamental issues that occurred during my internship, developing a feasible solution with a laid-out process for each one. After the proper execution of these processes, I will discuss my results. I found that time is the most critical component of an optimal transition to remote work. Finally, I will conclude with reflections on my findings, insights from current working supply chain professionals, and prompt further research that could be done.

Supply chain management is becoming an increasingly vital component in the success of an organization. Business and government leaders continue to recognize the importance of having robust and resilient supply chains. This trend has been accelerated by the COVID-19 pandemic which brought to light the fragility of the modern global supply chain network. Decades of offshoring has led to the inability of businesses to adequately manufacture critical supplies in times of crisis. This reality is most prevalent in the healthcare industry. Antibiotics, pharmaceuticals, PPE, testing equipment are almost entirely sourced from Chinese manufacturers. Building a more resilient healthcare supply chain requires a revaluation of critical items, cooperation between businesses and government, and recognizing the precarious situation for the United States which has become completely reliant on foreign manufacturers. <br/> Businesses are looking to develop more resilient supply chains which can respond and predict unforeseen market circumstances. The federal government is reckoning the national security concern of sourcing nearly all antibiotics, and pharmaceuticals from Chinese manufacturers. Aligning the goals of key stakeholders and developing the necessary incentive structure to encourage domestic manufacturing is necessary to respond to this crisis. As the global economy becomes increasingly interconnected and dependent on changes to markets anywhere on the globe, a renewed focus on proactive strategies is necessary to ensure the security and resiliency of the United States healthcare supply chain.

Affective computing allows computers to monitor and influence people’s affects, in other words emotions. Currently, there is a lot of research exploring what can be done with this technology. There are many fields, such as education, healthcare, and marketing, that this technology can transform. However, it is important to question what should be done. There are unique ethical considerations in regards to affective computing that haven't been explored. The purpose of this study is to understand the user’s perspective of affective computing in regards to the Association of Computing Machinery (ACM) Code of Ethics, to ultimately start developing a better understanding of these ethical concerns. For this study, participants were required to watch three different videos and answer a questionnaire, all while wearing an Emotiv EPOC+ EEG headset that measures their emotions. Using the information gathered, the study explores the ethics of affective computing through the user’s perspective.

Cryptojacking is a process in which a program utilizes a user’s CPU to mine cryptocurrencies unknown to the user. Since cryptojacking is a relatively new problem and its impact is still limited, very little has been done to combat it. Multiple studies have been conducted where a cryptojacking detection system is implemented, but none of these systems have truly solved the problem. This thesis surveys existing studies and provides a classification and evaluation of each detection system with the aim of determining their pros and cons. The result of the evaluation indicates that it might be possible to bypass detection of existing systems by modifying the cryptojacking code. In addition to this classification, I developed an automatic code instrumentation program that replaces specific instructions with functionally similar sequences as a way to show how easy it is to implement simple obfuscation to bypass detection by existing systems.

For our project, we explored the growth of the ASU BioDesign Clinical Testing Laboratory (ABCTL) from a standard university research lab to a COVID-19 testing facility through a business lens. The lab has pioneered the saliva-test in the Western United States. This thesis analyzes the laboratory from various business concepts and aspects. The business agility of the lab and it’s quickness to innovation has allowed the lab to enjoy great success. Looking into the future, the laboratory has a promising future and will need to answer many questions to remain the premier COVID-19 testing institution in Arizona.

The contemporary world is motivated by data-driven decision-making. Small 501(c)3 nonprofit organizations are often limited in their reach due to their size, lack of funding, and a lack of data analysis expertise. In an effort to increase accessibility to data analysis for such organizations, a Founders Lab team designed a product to help them understand and utilize geographic information systems (GIS) software. This product – You Got GIS – strikes the balance between highly technical documentation and general overviews, benefiting 501(c)3 nonprofits in their pursuit of data-driven decision-making. Through the product’s use of case studies and methodologies, You Got GIS serves as a thought experiment platform to start answering questions regarding GIS. The product aims to continuously build partnerships in an effort to improve curriculum and user engagement.

This paper is centered on the use of generative adversarial networks (GANs) to convert or generate RGB images from grayscale ones. The primary goal is to create sensible and colorful versions of a set of grayscale images by training a discriminator to recognize failed or generated images and training a generator to attempt to satisfy the discriminator. The network design is described in further detail below; however there are several potential issues that arise including the averaging of a color for certain images such that small details in an image are not assigned unique colors leading to a neutral blend. We attempt to mitigate this issue as much as possible.