Historic graphic design at RIT

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Comparative Stylistic Fanfiction Analysis: Popular and Unpopular Fics across Eleven Fandoms

Abstract: This study analyses 545 sample fanfiction stories (fics) in their stylistic feature variation by popularity and across eleven ‘fandoms’ in creative writing forums. Lexical richness, average sentence and paragraph lengths are isolated as promising measures for a text classifier to use in predicting a fic’s likely popularity in its fandom. Résumé: Cette étude analyse un échantillon de 545 chapitres d‘œuvres de fanfiction (fics) selon leur variation stylistique et leur popularité dans onze ‘fandoms’ différents. La richesse lexicale, longueur moyenne de phrase et longueur moyenne de paragraphe ont été choisis comme traits stylistiques propres à différencier les fics populaires des fics impopulaires

Recertification of the air and methane storage vessels at the Langley 8-foot high-temperature structures tunnel

This center operates a number of sophisticated wind tunnels in order to fulfill the needs of its researchers. Compressed air, which is kept in steel storage vessels, is used to power many of these tunnels. Some of these vessels have been in use for many years, and Langley is currently recertifying these vessels to insure their continued structural integrity. One of the first facilities to be recertified under this program was the Langley 8-foot high-temperature structures tunnel. This recertification involved (1) modification, hydrotesting, and inspection of the vessels; (2) repair of all relevant defects; (3) comparison of the original design of the vessel with the current design criteria of Section 8, Division 2, of the 1974 ASME Boiler and Pressure Vessel Code; (4) fracture-mechanics, thermal, and wind-induced vibration analyses of the vessels; and (5) development of operating envelopes and a future inspection plan for the vessels. Following these modifications, analyses, and tests, the vessels were recertified for operation at full design pressure (41.4 MPa (6000 psi)) within the operating envelope developed

Phone a Friend or Ask Alexa? Children’s Trust in Voice-Activated Devices

Voice-activated devices such as Google Home, Siri, and Alexa are in many homes and children are interacting with these devices. It is unclear if they treat these devices the way they treat human informants. Children prefer human informants that are reliable and familiar. This study examined whether children believe voice-activated devices provide accurate information. Participants included 40 4- and 5-year-olds and 40 7- and 8-year-olds. Children were introduced to two informants: the experimenter’s good friend and the experimenter’s new device. Children heard questions about personal information (e.g., the experimenter’s favorite color), facts that do not change (e.g., the color of a kiwano fruit), and timely information (e.g., which state had the most rain yesterday). After the informant provided an answer, the child indicated whether the answer was correct. Older children were significantly more likely to trust the device’s stable fact responses and the human informant’s personal fact responses. Surprisingly, younger children did not show greater trust for either informant for stable facts, but were significantly more likely to trust personal facts given by the device. These findings suggest that younger children have greater difficulty than older children trusting the appropriate informant, and thus need more guidance from adults to understand and use voice-activated devices.https://ir.library.louisville.edu/uars/1036/thumbnail.jp

Cupping Therapy Does Not Influence Healthy Adult\u27s Hamstring Range of Motion Compared to Control or Sham Conditions

International Journal of Exercise Science 13(3): 216-224, 2020. Cupping therapy, a form of traditional Chinese medicine, has recently gained popularity as a therapeutic modality among sports medicine clinicians. While the use of cupping therapy to decrease musculoskeletal pain is supported by recent research findings, evaluations on the use of cupping therapy to influence range of motion (ROM) are limited. The purpose of the study was to identify if cupping therapy applied passively for 10 minutes increases flexibility compared to sham treatment or control conditions. Twenty-five participants with hamstring ROM less than 80° and no previous cupping therapy experience completed the study. Participants reported to the laboratory on three occasions for one of three randomly assigned treatment conditions (cupping, sham, or control) for 10 minutes while prone. Hamstring flexibility was evaluated three times (pre-treatment, post-treatment, and 10-minutes post-treatment) via ROM measured during an active straight leg raise. Participants returned on two other occasions to receive the remaining treatment conditions. A 3 (treatment condition) x 3 (time) repeated measures analysis of variance was utilized for statistical analysis. There was no interaction between condition and time (p= 0.78). Within-subjects effects for time (p= 0.76) was not significant. Post hoc pairwise comparison of treatment conditions found no differences between control and cupping (p= 0.36), cupping and sham (p= 0.35), or control and sham (p=0.98) conditions. Cupping therapy applied statically for 10 minutes does not increase hamstring flexibility compared to a sham treatment or control condition

Pointwise Bounds for Steklov Eigenfunctions

Let (Ω,g) be a compact, real-analytic Riemannian manifold with real-analytic boundary ∂Ω. The harmonic extensions of the boundary Dirichlet-to-Neumann eigenfunctions are called Steklov eigenfunctions. We show that the Steklov eigenfunctions decay exponentially into the interior in terms of the Dirichlet-to-Neumann eigenvalues and give a sharp rate of decay to first order at the boundary. The proof uses the Poisson representation for the Steklov eigenfunctions combined with sharp h-microlocal concentration estimates for the boundary Dirichlet-to-Neumann eigenfunctions near the cosphere bundle S∗∂Ω. These estimates follow from sharp estimates on the concentration of the FBI transforms of solutions to analytic pseudodifferential equations Pu=0 near the characteristic set {σ(P)=0}

Kepler Presearch Data Conditioning II - A Bayesian Approach to Systematic Error Correction

With the unprecedented photometric precision of the Kepler Spacecraft, significant systematic and stochastic errors on transit signal levels are observable in the Kepler photometric data. These errors, which include discontinuities, outliers, systematic trends and other instrumental signatures, obscure astrophysical signals. The Presearch Data Conditioning (PDC) module of the Kepler data analysis pipeline tries to remove these errors while preserving planet transits and other astrophysically interesting signals. The completely new noise and stellar variability regime observed in Kepler data poses a significant problem to standard cotrending methods such as SYSREM and TFA. Variable stars are often of particular astrophysical interest so the preservation of their signals is of significant importance to the astrophysical community. We present a Bayesian Maximum A Posteriori (MAP) approach where a subset of highly correlated and quiet stars is used to generate a cotrending basis vector set which is in turn used to establish a range of "reasonable" robust fit parameters. These robust fit parameters are then used to generate a Bayesian Prior and a Bayesian Posterior Probability Distribution Function (PDF) which when maximized finds the best fit that simultaneously removes systematic effects while reducing the signal distortion and noise injection which commonly afflicts simple least-squares (LS) fitting. A numerical and empirical approach is taken where the Bayesian Prior PDFs are generated from fits to the light curve distributions themselves.Comment: 43 pages, 21 figures, Submitted for publication in PASP. Also see companion paper "Kepler Presearch Data Conditioning I - Architecture and Algorithms for Error Correction in Kepler Light Curves" by Martin C. Stumpe, et a

Software Assists in Responding to Anomalous Conditions

Fault Induced Document Retrieval Officer (FIDO) is a computer program that reduces the need for a large and costly team of engineers and/or technicians to monitor the state of a spacecraft and associated ground systems and respond to anomalies. FIDO includes artificial-intelligence components that imitate the reasoning of human experts with reference to a knowledge base of rules that represent failure modes and to a database of engineering documentation. These components act together to give an unskilled operator instantaneous expert assistance and access to information that can enable resolution of most anomalies, without the need for highly paid experts. FIDO provides a system state summary (a configurable engineering summary) and documentation for diagnosis of a potentially failing component that might have caused a given error message or anomaly. FIDO also enables high-level browsing of documentation by use of an interface indexed to the particular error message. The collection of available documents includes information on operations and associated procedures, engineering problem reports, documentation of components, and engineering drawings. FIDO also affords a capability for combining information on the state of ground systems with detailed, hierarchically-organized, hypertext- enabled documentation

Kepler Presearch Data Conditioning I - Architecture and Algorithms for Error Correction in Kepler Light Curves

Kepler provides light curves of 156,000 stars with unprecedented precision. However, the raw data as they come from the spacecraft contain significant systematic and stochastic errors. These errors, which include discontinuities, systematic trends, and outliers, obscure the astrophysical signals in the light curves. To correct these errors is the task of the Presearch Data Conditioning (PDC) module of the Kepler data analysis pipeline. The original version of PDC in Kepler did not meet the extremely high performance requirements for the detection of miniscule planet transits or highly accurate analysis of stellar activity and rotation. One particular deficiency was that astrophysical features were often removed as a side-effect to removal of errors. In this paper we introduce the completely new and significantly improved version of PDC which was implemented in Kepler SOC 8.0. This new PDC version, which utilizes a Bayesian approach for removal of systematics, reliably corrects errors in the light curves while at the same time preserving planet transits and other astrophysically interesting signals. We describe the architecture and the algorithms of this new PDC module, show typical errors encountered in Kepler data, and illustrate the corrections using real light curve examples.Comment: Submitted to PASP. Also see companion paper "Kepler Presearch Data Conditioning II - A Bayesian Approach to Systematic Error Correction" by Jeff C. Smith et a