7,087 research outputs found
Monte Carlo Simulation of the Semimetal-Insulator Phase Transition in Monolayer Graphene
A 2+1 dimensional fermion field theory is proposed as a model for the
low-energy electronic excitations in monolayer graphene. The model consists of
N=2 four-component Dirac fermions moving in the plane and interacting via a
contact interaction between charge densities. For strong couplings there is a
continuous transition to a Mott insulting phase. We present results of an
extensive numerical study of the model's critical region, including the order
parameter, its associated susceptibility, and for the first time the
quasiparticle propagator. The data enables an extraction of the critical
exponents at the transition, including the dynamical critical exponent, which
are hypothesised to be universal features of a quantum critical point. The
relation of our model with others in the literature is discussed, along with
the implications for physical graphene following from our value of the critical
coupling.Comment: 19 page
Physiologically-Motivated Feature Extraction Methods for Speaker Recognition
Speaker recognition has received a great deal of attention from the speech community, and significant gains in robustness and accuracy have been obtained over the past decade. However, the features used for identification are still primarily representations of overall spectral characteristics, and thus the models are primarily phonetic in nature, differentiating speakers based on overall pronunciation patterns. This creates difficulties in terms of the amount of enrollment data and complexity of the models required to cover the phonetic space, especially in tasks such as identification where enrollment and testing data may not have similar phonetic coverage. This dissertation introduces new features based on vocal source characteristics intended to capture physiological information related to the laryngeal excitation energy of a speaker. These features, including RPCC, GLFCC and TPCC, represent the unique characteristics of speech production not represented in current state-of-the-art speaker identification systems. The proposed features are evaluated through three experimental paradigms including cross-lingual speaker identification, cross song-type avian speaker identification and mono-lingual speaker identification. The experimental results show that the proposed features provide information about speaker characteristics that is significantly different in nature from the phonetically-focused information present in traditional spectral features. The incorporation of the proposed glottal source features offers significant overall improvement to the robustness and accuracy of speaker identification tasks
Flexible structure control laboratory development and technology demonstration
An experimental structure is described which was constructed to demonstrate and validate recent emerging technologies in the active control and identification of large flexible space structures. The configuration consists of a large, 20 foot diameter antenna-like flexible structure in the horizontal plane with a gimballed central hub, a flexible feed-boom assembly hanging from the hub, and 12 flexible ribs radiating outward. Fourteen electrodynamic force actuators mounted to the hub and to the individual ribs provide the means to excite the structure and exert control forces. Thirty permanently mounted sensors, including optical encoders and analog induction devices provide measurements of structural response at widely distributed points. An experimental remote optical sensor provides sixteen additional sensing channels. A computer samples the sensors, computes the control updates and sends commands to the actuators in real time, while simultaneously displaying selected outputs on a graphics terminal and saving them in memory. Several control experiments were conducted thus far and are documented. These include implementation of distributed parameter system control, model reference adaptive control, and static shape control. These experiments have demonstrated the successful implementation of state-of-the-art control approaches using actual hardware
Image-Specific Information Suppression and Implicit Local Alignment for Text-based Person Search
Text-based person search (TBPS) is a challenging task that aims to search
pedestrian images with the same identity from an image gallery given a query
text. In recent years, TBPS has made remarkable progress and state-of-the-art
methods achieve superior performance by learning local fine-grained
correspondence between images and texts. However, most existing methods rely on
explicitly generated local parts to model fine-grained correspondence between
modalities, which is unreliable due to the lack of contextual information or
the potential introduction of noise. Moreover, existing methods seldom consider
the information inequality problem between modalities caused by image-specific
information. To address these limitations, we propose an efficient joint
Multi-level Alignment Network (MANet) for TBPS, which can learn aligned
image/text feature representations between modalities at multiple levels, and
realize fast and effective person search. Specifically, we first design an
image-specific information suppression module, which suppresses image
background and environmental factors by relation-guided localization and
channel attention filtration respectively. This module effectively alleviates
the information inequality problem and realizes the alignment of information
volume between images and texts. Secondly, we propose an implicit local
alignment module to adaptively aggregate all pixel/word features of image/text
to a set of modality-shared semantic topic centers and implicitly learn the
local fine-grained correspondence between modalities without additional
supervision and cross-modal interactions. And a global alignment is introduced
as a supplement to the local perspective. The cooperation of global and local
alignment modules enables better semantic alignment between modalities.
Extensive experiments on multiple databases demonstrate the effectiveness and
superiority of our MANet
Understanding person acquisition using an interactive activation and competition network
Face perception is one of the most developed visual skills that humans display, and recent work has attempted to examine the mechanisms involved in face perception through noting how neural networks achieve the same performance. The purpose of the present paper is to extend this approach to look not just at human face recognition, but also at human face acquisition. Experiment 1 presents empirical data to describe the acquisition over time of appropriate representations for newly encountered faces. These results are compared with those of Simulation 1, in which a modified IAC network capable of modelling the acquisition process is generated. Experiment 2 and Simulation 2 explore the mechanisms of learning further, and it is demonstrated that the acquisition of a set of associated new facts is easier than the acquisition of individual facts in isolation of one another. This is explained in terms of the advantage gained from additional inputs and mutual reinforcement of developing links within an interactive neural network system. <br/
Critical Behavior in Light Nuclear Systems: Experimental Aspects
An extensive experimental survey of the features of the disassembly of a
small quasi-projectile system with 36, produced in the reactions of 47
MeV/nucleon Ar + Al, Ti and Ni, has been carried
out. Nuclei in the excitation energy range of 1-9 MeV/u have been investigated
employing a new method to reconstruct the quasi-projectile source. At an
excitation energy 5.6 MeV/nucleon many observables indicate the presence
of maximal fluctuations in the de-excitation processes. The fragment
topological structure shows that the rank sorted fragments obey Zipf's law at
the point of largest fluctuations providing another indication of a liquid gas
phase transition. The caloric curve for this system shows a monotonic increase
of temperature with excitation energy and no apparent plateau. The temperature
at the point of maximal fluctuations is MeV. Taking this
temperature as the critical temperature and employing the caloric curve
information we have extracted the critical exponents , and
from the data. Their values are also consistent with the values of the
universality class of the liquid gas phase transition. Taken together, this
body of evidence strongly suggests a phase change in an equilibrated mesoscopic
system at, or extremely close to, the critical point.Comment: Physical Review C, in press; some discussions about the validity of
excitation energy in peripheral collisions have been added; 24 pages and 32
figures; longer abstract in the preprin
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