7,929 research outputs found
Sinkless: A Preliminary Study of Stress Propagation in Group Project Social Networks using a Variant of the Abelian Sandpile Model
We perform social network analysis on 53 students split over three semesters
and 13 groups, using conventional measures like eigenvector centrality,
betweeness centrality, and degree centrality, as well as defining a variant of
the Abelian Sandpile Model (ASM) with the intention of modeling stress
propagation in the college classroom. We correlate the results of these
analyses with group project grades received; due to a small or poorly collected
dataset, we are unable to conclude that any of these network measures relates
to those grades. However, we are successful in using this dataset to define a
discrete, recursive, and more generalized variant of the ASM. Abelian Sandpile
Model, College Grades, Self-organized Criticality, Sinkless Sandpile Model,
Social Network Analysis, Stress PropagationComment: 11 pages, 8 figure
PerformanceNet: Score-to-Audio Music Generation with Multi-Band Convolutional Residual Network
Music creation is typically composed of two parts: composing the musical
score, and then performing the score with instruments to make sounds. While
recent work has made much progress in automatic music generation in the
symbolic domain, few attempts have been made to build an AI model that can
render realistic music audio from musical scores. Directly synthesizing audio
with sound sample libraries often leads to mechanical and deadpan results,
since musical scores do not contain performance-level information, such as
subtle changes in timing and dynamics. Moreover, while the task may sound like
a text-to-speech synthesis problem, there are fundamental differences since
music audio has rich polyphonic sounds. To build such an AI performer, we
propose in this paper a deep convolutional model that learns in an end-to-end
manner the score-to-audio mapping between a symbolic representation of music
called the piano rolls and an audio representation of music called the
spectrograms. The model consists of two subnets: the ContourNet, which uses a
U-Net structure to learn the correspondence between piano rolls and
spectrograms and to give an initial result; and the TextureNet, which further
uses a multi-band residual network to refine the result by adding the spectral
texture of overtones and timbre. We train the model to generate music clips of
the violin, cello, and flute, with a dataset of moderate size. We also present
the result of a user study that shows our model achieves higher mean opinion
score (MOS) in naturalness and emotional expressivity than a WaveNet-based
model and two commercial sound libraries. We open our source code at
https://github.com/bwang514/PerformanceNetComment: 8 pages, 6 figures, AAAI 2019 camera-ready versio
Phase sensitivity at the Heisenberg limit in an SU(1,1) interferometer via parity detection
We theoretically investigate the phase sensitivity with parity detection on
an SU(1,1) interferometer with a coherent state combined with a squeezed vacuum
state. This interferometer is formed with two parametric amplifiers for beam
splitting and recombination instead of beam splitters. We show that the
sensitivity of estimation phase approaches Heisenberg limit and give the
corresponding optimal condition. Moreover, we derive the quantum Cram\'er-Rao
bound of the SU(1,1) interferometer.Comment: 9 pages, 2 figures, 3 table
The Role of Sketch Finish and Style in User Responses to Early Stage Design Concepts
Conceptual sketches of design alternatives are often employed as a tool for eliciting feedback from design stakeholders, including potential end-users. However, such sketches can vary widely in their level of finish and style, thus potentially affecting how users respond to a concept. This paper presents a study of user responses to three objects drawn in styles ranging from rough hand sketches to CAD drawings. This study also considers the amount of design time required to create the sketches. Results show that respondents generally ranked realistic, “clean” hand sketches the highest over other types of sketches, particularly “rough” sketches. These types of sketches took longer than other types of hand sketches to create, but were still much faster than CAD renderings. Results also suggest that the complexity and familiarity of an object can influence how users respond to a sketch.National Science Foundation (U.S.) (Award CMMI-0830134
Safety awareness educational topics for the construction of power transmission systems with smart grid technologies
Power transmission facilities in the U.S. are undergoing a transformation due to the increased use of distributed generation sources such as wind and solar power. The current power grid system is also antiquated and in need of substantial retrofits to make it more efficient and reliable. The new energy transmission system being designed and built to optimize power delivery is known as “Smart Grid”. The increased activity in the construction of power transmission facilities and installation of new technologies into the current power system raises potential safety concerns. Existing construction management curriculum may include general information about safety training, but does not typically include information about this specialized sector. The objective of this study was to work with industry to identify key safety topics appropriate for inclusion in an introductory industrial construction course. Results of interviews with industry identified numerous hazards that are not typically covered in typical construction curricula. A joint undergraduate and graduate course in industrial construction was created to address these and additional concepts. A survey of the students was performed to determine the effectiveness of the course and also to determine their thoughts about the smart grid technologies and safety training. Information on electrical system hazards is presented along with results of the student surveys
Effects of Low Intensity Focused Ultrasound on Liposomes Containing Channel proteins.
The ability to reversibly and non-invasively modulate region-specific brain activity in vivo suggests Low Intensity Focused Ultrasound (LIFU) as potential therapeutics for neurological dysfunctions such as epilepsy and Parkinson's disease. While in vivo studies provide evidence of the bioeffects of LIFU on neuronal activity, they merely hint at potential mechanisms but do not fully explain how this technology achieves these effects. One potential hypothesis is that LIFU produces local membrane depolarization by mechanically perturbing the neuronal cell membrane, or activating channels or other proteins embedded in the membrane. Proteins that sense mechanical perturbations of the membrane, such as those gated by membrane tension, are prime candidates for activating in response to LIFU and thus leading to the neurological responses that have been measured. Here we use the bacterial mechanosensitive channel MscL, which has been purified and reconstituted in liposomes, to determine how LIFU may affect the activation of this membrane-tension gated channel. Two bacterial voltage-gated channels, KvAP and NaK2K F92A channels were also studied. Surprisingly, the results suggest that ultrasound modulation and membrane perturbation does not induce channel gating, but rather induces pore formation at the membrane protein-lipid interface. However, in vesicles with high MscL mechanosensitive channel concentrations, apparent decreases in pore formation are observed, suggesting that this membrane-tension-sensitive protein may serve to increase the elasticity of the membrane, presumably because of expansion of the channel in the plane of the membrane independent of channel gating
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