Tag: Computer Science

Lolicon and Its Effects on Japanese Society

Presenter(s): Natalie Padilla—Computer science

Co-Presenter(s): Elizabeth Chandler, Jamie Arpan

Session: Prerecorded Poster Presentation

Hypersexualization of minors is a continuous problem prevalent in Japan . This particular brand of hypersexualization is known as Lolicon which is the attraction to prepubescent girls, particularly in anime and manga . Historically, it is derived from the 1955 novel titled Lolita, which depicts a middle- aged man’s dark obsession with a young girl, but Lolicon didn’t become a recognized genre until the 1970’s when fan artists depicted their favorite female characters of the time as underage girls . There is still ongoing debate within Japanese society about its harmful effects, some dubbing it as a “sickness”, while other individuals find no problem with continuing the practice . Regardless, it is still incredibly easy to find openly in Japan, with convenience stores selling magazines containing lolicon imagery . Utilizing academic research, we will showcase how this problem is influencing and normalizing the attraction to underage girls . We will discuss the impact, local and globally, on the acceptance and societal effect of Lolicon, as well as the steps taken to combat its influence in Japan .

Attacker Behavior Modeling and Learning in Security Using Deep Neural Networks

Presenter(s): Alyssa Huque—Mathematics & Computer Science, Political Science

Faculty Mentor(s): Thanh Nguyen

Session: Prerecorded Poster Presentation

A common dilemma many security agencies face is how to effectively allocate limited resources to protect assets . This predicament is known as the Stackelberg Security Games . In order to optimize defense tactics, security agencies need to be able to anticipate adversarial behavior . Currently, there are computer modeling techniques that simulate the Stackelberg Security Games . However, these implementations are not completely optimized for human adversaries . The quantal response model (QR) operates under the assumption that humans act with perfect rationality, a flawed assumption that was improved upon in the SUQR model . The SUQR integrated a subjective utility function (SU) that could take learned parameters, but only from limited data (Nguyen, et . al 2013) . Deep neural networks have the potential to improve further than the SUQR by providing a better prediction of the attacker’s behavior . Deep neural networks can allow for a more robust set of input features that would be able to account for more nuances of human behavior . A model that could accurately predict adversarial actions has the potential to improve resource allocation and enhance the security of valuable assets .

Longitudinal Analysis of Major Video Streaming Services in the US

Presenter(s): Donna Hooshmand—Computer Science, Mathematics

Faculty Mentor(s): Reza Rejaie

Session: Prerecorded Poster Presentation

This study relies on several years of NETFLOW data for exchanged traffic between the University of Oregon network (UOnet) and the Internet to perform a longitudinal analysis on the characteristics of popular Internet Applications . We develop techniques to identify connections related to video streams from their NETFLOW records . We then investigate how the fraction of UOnet traffic associated with (i .e . popularity of) major video streaming applications (e .g . YoutTube, Netflix, Amazon Prime), the basic characteristics of their video (e .g . bandwidth and duration) and their delivery mechanism have evolved over the past few years . Our empirical findings will offer valuable insights into important practical aspects of video streams services and their evolution over time .

Understanding microbial modulation of neuronal morphology in zebrafish

Presenter(s): Max Grice—Computer Science

Faculty Mentor(s): Judith Eisen, Joseph Bruckner

Session 4: Earning your Stripes

Increasing evidence supports a role for the intestinal microbiota in modulating host neurodevelopment and behavior, including complex social behaviors . Recent research has also linked the microbiota to neurological disorders including autism spectrum disorder (ASD), depression, Alzheimer’s Disease, and Parkinson’s Disease . However, the mechanisms of these interactions between the host-associated microbiota and neurodevelopment remain unclear . Using zebrafish raised in the absence of the microbiota, or germ-free (GF), our group has found that the microbiota modulates zebrafish social behavior . Normal social behavior requires neurons in a region of the brain called the ventral telencephalon (vTel) . Therefore, we hypothesized that the microbiota may modulate social behavior by altering development of vTel neurons, resulting in changes in vTel neuron morphology . To measure morphology of vTel neurons, we combined sparse mosaic labelling and high- resolution confocal microscopy to image individual vTel neurons . We used Imaris software to segment individual neurons and extract morphological measurements and adapted several software packages to warp and register individual neurons to an average reference brain in each condition . We found that vTel neurons from GF fish are significantly more complex than vTel neurons from their conventionally raised siblings . Together, this work suggests that the microbiota may modulate social behavior by restraining complexity of ventral forebrain neurons . Understanding the specific mechanism through which the microbiota normally modulates social behavior will allow us to better understand microbial modulation of neurodevelopment and therefore construct more effective treatments for neurological disorders that may result from dysbiosis of the host-associated microbiota .

Demonstrating the Importance of Implementing Reusing, Recycling, and Sustainable Practices in Creative and Accessible Ways

Presenter(s): Garrett Bunkers—Computer Science

Co-Presenter(s): Michael Chung, Isabella Flynn, Anna Jatsura, Hannah Weaver

Faculty Mentor(s): Sarah Stoeckl

Session 1: Environmental Leaders ARC

Sustainable and zero-waste lifestyle practices are stereotypically portrayed as expensive, inaccessible, and difficult to maintain . Our project demonstrates that this is not necessarily true — we plan on making a video to teach people how to use discarded, recyclable, household materials as a base in creating personal planters . We will use local recyclable, or unwanted materials of variable sizes and show our own personal decorations . We will include prefered type of soil and a lesson on how to find fertile dirt in your backyard . We will be working in tandem with both the Sustainability Center and the UO Zero Waste program . In collaborating with the Sustainability Center we will have the opportunity to effectively teach the students and families about at-home sustainability and recycling with easily accessible and safe materials such as used containers of varying material types . The UO Zero Waste program can inform us where the recycled materials are transported after they are recycled and provide insight on what material would be best for a planter . We plan to inform friends, families, and classmates about the video we will post . Our goal is to educate people on recycling, repurposing from a creative perspective, and inspiring them to do similar projects at their homes . We believe that people should frequently be reminded about sustainability, and, through environmental consciousness, challenge their creativity . When people are taught to be sustainable while also igniting their imaginations, they can continue to grow into excellent environmental leaders in their household