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- Creators: Computer Science and Engineering Program
In the last decade, California’s imprisoned population of women has increased by nearly 400% (Chesney-Lind, 2012). The focus of this thesis is to discuss the treatment—or lack thereof—of women within California’s criminal justice system and sentencing laws. By exploring its historical approach to two criminal actions related to women, the Three Strikes law (including non-violent drug crimes) and the absence of laws accounting for experiences of female victims of domestic violence who killed their abusers, I explore how California’s criminal code has marginalized women, and present a summary of the adverse effects brought about by the gender invisibility that is endemic within sentencing policies and practice. I also discuss recent attempted and successful reforms related to these issues, which evidence a shift toward social dialogue on sentencing aiming to address gender inequity in the sentencing code. These reforms were the result of activism; organizations, academics and individuals successfully raised awareness regarding excessive and undue sentencing of women and compelled action by the legislature.
By method of a feminist analysis of these histories, I explore these two pertinent issues in California; both are related to women who, under harsh sentencing laws, were incarcerated under the state’s male-focused legislation. Responses to the inequalities found in these laws included attempts toward both visibility for women and reform related to sentencing. I analyze the ontology of sentencing reform as it relates to activism in order to discuss the implications of further criminal code legislation, as well as the implications of the 2012 reforms in practice. Through the paper, I focus upon how women have become a target of arrest and long sentences not because they are strategically arrested to equalize their representation behind bars, but because the “tough on crime” framework in the criminal code cast a wide and fixed net that incarcerated increasingly more women following the codification of both mandatory minimums and a male-oriented approach to sentencing (Chesney-Lind et. al, 2012).
memory cue and the prospective memory intention. Based on literature suggesting that aspects of prospective memory are reliant on executive control functioning, the current study examined the possibility that executive control depletion would affect prospective memory ability on subsequent tasks. Results showed that depletion of executive control resources, measured objectively, did not impair prospective memory in either a low or
high cue-association condition. However, participants‟ subjective assessment of their own fatigue correlated significantly with their subsequent prospective memory performance, regardless of association condition. The results of the study indicate that depletion studies that fail to account for both objective and subjective measures suffer from an unclear interpretation of effects, and that recognition of perceived expectancies
of cognitive resource limitation can assist in improving prospective memory ability.
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.
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.
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.
The NCAA is changing the current rules and regulations around a student-athlete’s name, image, and likeness. Previously, student-athletes were not allowed to participate in business activities or noninstitutional promotional activities. With the new rule changes, student-athletes will be able to engage in business activities related to their own name, image, and likeness. The goal of the team was to help “prepare athletes to understand and properly navigate the evolving restrictions and guidelines around athlete name, image, and likeness”. In order to accomplish this, the team had to understand the problems student-athletes face with these changing rules and regulations. The team conducted basic market research to identify the problem. The problem discovered was the lack of communication between student-athletes and businesses. In order to verify this problem, the team conducted several interviews with Arizona State University Athletic Department personnel. From the interviews, the team identified that the user is the student-athletes and the buyer is the brands and businesses. Once the problem was verified and the user and buyer were identified, a solution that would best fit the customers was formulated. The solution is a platform that assists student-athletes navigate the changing rules of the NCAA by providing access to a marketplace optimized to working with student-athletes and offering an ease of maintaining relationships between student-athletes and businesses. The solution was validated through meetings with interested brands. The team used the business model and market potential to pitch the business idea to the brands. Finally, the team gained traction by initiating company partnerships.
A project about developing software for learning turned into a project for learning about software development. The submission here only includes the journal. However, the journal has a link to the public GitHub repository containing the source code for the thesis. The source code implements a program to facilitate self-study by allowing the user to create quizzes. The journal contains my experience working on the project (both successes and failures).
Education has been at the forefront of many issues in Arizona over the past several years with concerns over lack of funding sparking the Red for Ed movement. However, despite the push for educational change, there remain many barriers to education including a lack of visibility for how Arizona schools are performing at a legislative district level. While there are sources of information released at a school district level, many of these are limited and can become obscure to legislators when such school districts lie on the boundary between 2 different legislative districts. Moreover, much of this information is in the form of raw spreadsheets and is often fragmented between government websites and educational organizations. As such, a visualization dashboard that clearly identifies schools and their relative performance within each legislative district would be an extremely valuable tool to legislative bodies and the Arizona public. Although this dashboard and research are rough drafts of a larger concept, they would ideally increase transparency regarding public information about these districts and allow legislators to utilize the dashboard as a tool for greater understanding and more effective policymaking.