Rhetorics of Functionally Applicative Game Design: Designing and Testing the Project Management Game \u3ci\u3eScrummage\u3c/i\u3e

In this project, I designed and tested Scrummage, a tabletop game to teach the scrum project management system to undergraduate students. The project grew from the gaps in both academic literature and pedagogical tools for project management and collaboration in the technical communication classroom. Although the field of technical communication places significance on project management, research shows that many employers find the project management skills and knowledge of recent graduates to be under-developed. Situated in the fields of game design, game studies, project management, and technical communication, this project asks how we as educators can improve the project management learning outcomes for technical communication graduates. After conducting research into the forms of project management, I make the argument that using a game designed using vetted game design and playtesting techniques from the field of game design could be a possible solution to this problem. I argue for term “functionally applicative games” (instead of educational, serious, or transformative games) as a way to define games designed with objectives that extend beyond the gameplay itself. I develop a series of rhetorics of functionally applicative games to guide the development and design of these types of games. To demonstrate these rhetorics of functionally applicative game design, I developed Scrummage, a four-player cooperative game in which players work together to complete a project scenario using scrum project management. My project utilizes a dual methodological approach. The first set of methods--used for playtesting Scrummage--describe the process of crafting, designing, and revising Scrummage over a series of three playtesting sessions with undergraduate students. The second set of methods draw from instructional design testing schema and test the presumed learning outcomes of Scrummage in regards to scrum project management with a separate group of students. The results not only provide insight into development and testing a functionally applicative game, but also how the processes of introducing, teaching, and reviewing games as learning tools need a heuristic that can be utilized by educators wishing to incorporate them into the classroom

TED-style Talk: Flying Blind: Creating a Library ORCID Integration Pilot

As part of the UNLV Libraries’ goal to determine an appropriate level of engagement with ORCID, our pre-pilot investigated the feasibility of a Libraries-led service to populate faculty ORCID profiles with citations for scholarly works, allowing UNLV to better track and promote their research. This project sought to test the requirements and scalability of using currently-available data to populate researcher profiles via the ORCID API, gauging the benefits against the cost in Library resources. We performed a field survey of similar institutions using ORCID, engaged with Libraries faculty for volunteers to create dummy profiles in the ORCID testing environment, and updated these profiles with real publication and employment data, iterating through technical issues and creating a report of our findings at the close of the pre-pilot. This presentation will cover the process and findings of the pre-pilot, including successes, lessons learned, and next steps

Bayesian modelling and quantification of Raman spectroscopy

Raman spectroscopy can be used to identify molecules such as DNA by the characteristic scattering of light from a laser. It is sensitive at very low concentrations and can accurately quantify the amount of a given molecule in a sample. The presence of a large, nonuniform background presents a major challenge to analysis of these spectra. To overcome this challenge, we introduce a sequential Monte Carlo (SMC) algorithm to separate each observed spectrum into a series of peaks plus a smoothly-varying baseline, corrupted by additive white noise. The peaks are modelled as Lorentzian, Gaussian, or pseudo-Voigt functions, while the baseline is estimated using a penalised cubic spline. This latent continuous representation accounts for differences in resolution between measurements. The posterior distribution can be incrementally updated as more data becomes available, resulting in a scalable algorithm that is robust to local maxima. By incorporating this representation in a Bayesian hierarchical regression model, we can quantify the relationship between molecular concentration and peak intensity, thereby providing an improved estimate of the limit of detection, which is of major importance to analytical chemistry

Focusing on the Big Picture: Insights into a Systems Approach to Deep Learning for Satellite Imagery

Deep learning tasks are often complicated and require a variety of components working together efficiently to perform well. Due to the often large scale of these tasks, there is a necessity to iterate quickly in order to attempt a variety of methods and to find and fix bugs. While participating in IARPA's Functional Map of the World challenge, we identified challenges along the entire deep learning pipeline and found various solutions to these challenges. In this paper, we present the performance, engineering, and deep learning considerations with processing and modeling data, as well as underlying infrastructure considerations that support large-scale deep learning tasks. We also discuss insights and observations with regard to satellite imagery and deep learning for image classification.Comment: Accepted to IEEE Big Data 201

Histone methylation is critical in monocyte to macrophage differentiation

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/136760/1/febs14074_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/136760/2/febs14074.pd

An Analysis of Dialogue Repair in Virtual Voice Assistants

Language speakers often use what are known as repair initiators to mend fundamental disconnects that occur between them during verbal communication. Previous research in this field has mainly focused on the human-to-human use of repair initiator. We proposed an examination of dialogue repair structure wherein the dialogue initiator is human and the party that initiates or responds to the repair is a virtual assistant. This study examined the use of repair initiators in both English and Spanish with two popular assistants, Google Assistant and Apple's Siri. Our aim was to codify the differences, if any, in responses by voice assistants to dialogues in need of repair as compared to human-human dialogues also in need of repair. Ultimately the data demonstrated that not only were there differences between human-assistant and human-human dialogue repair strategies, but that there were likewise differences among the assistants and the languages studied.Comment: 2021, non-print, unpublished versio

Designing Collaborative and Mediated Experiences with Networked Circuit-Bent Devices

Circuit bending provides creative methods of generating sound by subverting a device’s normal operation through hacking. While the means of interacting with hacked devices in performance are primarily limited to tactile controls and explicitly mapped actions, exploring alternative methods of engaging with these instruments would allow for mediation systems and collaborative performance design to enhance the use of nostalgic devices in audio/visual art. This paper discusses the artistic benefits of blending the musical and aesthetic practices of circuit bending with the field of networked musical performance. We present the artistic benefits of traditional circuit bending and methods of extending networked performance techniques to the practice. This is followed by a discussion of Bendit_I/O—a framework for designing cyber-hacked readymades—opening the door to innovative design practices for using hacked hardware in collaborative environments. We also discuss Pepper\u27s Ghost, a multimedia installation created with networked circuit-bent devices with the goal of exploring these concepts

Readily accessible sp3-rich cyclic hydrazine frameworks exploiting nitrogen fluxionality

Increased molecular complexity correlates with improved chances of success in the drug development process. Here, a strategy for the creation of sp3-rich, non-planar heterocyclic scaffolds suitable for drug discovery is described that obviates the need to generate multiple stereogenic centers with independent control. Asymmetric transfer hydrogenation using a tethered Ru-catalyst is used to efficiently produce a range of enantiopure cyclic hydrazine building blocks (up to 99% ee). Iterative C–N functionalization at the two nitrogen atoms of these compounds produces novel hydrazine and hydrazide based chemical libraries. Wide chemical diversification is possible through variation in the hydrazine structure, use of different functionalization chemistries and coupling partners, and controlled engagement of each nitrogen of the hydrazine in turn. Principal Moment of Inertia (PMI) analysis of this small hydrazine library reveals excellent shape diversity and three-dimensionality. NMR and crystallographic studies confirm these frameworks prefer to orient their substituents in three-dimensional space under the control of a single stereogenic center through exploitation of the fluxional behavior of the two nitrogen atoms