76,583 research outputs found
Relation between directed polymers in random media and random bond dimer models
We reassess the relation between classical lattice dimer models and the
continuum elastic description of a lattice of fluctuating polymers. In the
absence of randomness we determine the density and line tension of the polymers
in terms of the bond weights of hard-core dimers on the square and the
hexagonal lattice. For the latter, we demonstrate the equivalence of the
canonical ensemble for the dimer model and the grand-canonical description for
polymers by performing explicitly the continuum limit. Using this equivalence
for the random bond dimer model on a square lattice, we resolve a previously
observed discrepancy between numerical results for the random dimer model and a
replica approach for polymers in random media. Further potential applications
of the equivalence are briefly discussed.Comment: 6 pages, 3 figure
Superfluid-Mott-Insulator Transition in a One-Dimensional Optical Lattice with Double-Well Potentials
We study the superfluid-Mott-insulator transition of ultracold bosonic atoms
in a one-dimensional optical lattice with a double-well confining trap using
the density-matrix renormalization group. At low density, the system behaves
similarly as two separated ones inside harmonic traps. At high density,
however, interesting features appear as the consequence of the quantum
tunneling between the two wells and the competition between the "superfluid"
and Mott regions. They are characterized by a rich step-plateau structure in
the visibility and the satellite peaks in the momentum distribution function as
a function of the on-site repulsion. These novel properties shed light on the
understanding of the phase coherence between two coupled condensates and the
off-diagonal correlations between the two wells.Comment: 5 pages, 7 figure
Diving Deep into Sentiment: Understanding Fine-tuned CNNs for Visual Sentiment Prediction
Visual media are powerful means of expressing emotions and sentiments. The
constant generation of new content in social networks highlights the need of
automated visual sentiment analysis tools. While Convolutional Neural Networks
(CNNs) have established a new state-of-the-art in several vision problems,
their application to the task of sentiment analysis is mostly unexplored and
there are few studies regarding how to design CNNs for this purpose. In this
work, we study the suitability of fine-tuning a CNN for visual sentiment
prediction as well as explore performance boosting techniques within this deep
learning setting. Finally, we provide a deep-dive analysis into a benchmark,
state-of-the-art network architecture to gain insight about how to design
patterns for CNNs on the task of visual sentiment prediction.Comment: Preprint of the paper accepted at the 1st Workshop on Affect and
Sentiment in Multimedia (ASM), in ACM MultiMedia 2015. Brisbane, Australi
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A micro-electro-mechanical-system-based thermal shear-stress sensor with self-frequency compensation
By applying the micro-electro-mechanical-system (MEMS) fabrication technology, we developed a micro-thermal sensor to measure surface shear stress. The heat transfer from a polysilicon heater depends on the normal velocity gradient and thus provides the surface shear stress. However, the sensitivity of the shear-stress measurements in air is less than desirable due to the low heat capacity of air. A unique feature of this micro-sensor is that the heating element, a film 1 Âľm thick, is separated from the substrate by a vacuum cavity 2 Âľm thick. The vacuum cavity prevents the conduction of heat to the substrate and therefore improves the sensitivity by an order of magnitude. Owing to the low thermal inertia of the miniature sensing element, this shear-stress micro-sensor can provide instantaneous measurements of small-scale turbulence. Furthermore, MEMS technology allows us make multiple sensors on a single chip so that we can perform distributed measurements. In this study, we use multiple polysilicon sensor elements to improve the dynamic performance of the sensor itself. It is demonstrated that the frequency-response range of a constant-current sensor can be extended from the order of 100 Hz to 100 kHz
Accurate determination of tensor network state of quantum lattice models in two dimensions
We have proposed a novel numerical method to calculate accurately the
physical quantities of the ground state with the tensor-network wave function
in two dimensions. We determine the tensor network wavefunction by a projection
approach which applies iteratively the Trotter-Suzuki decomposition of the
projection operator and the singular value decomposition of matrix. The norm of
the wavefunction and the expectation value of a physical observable are
evaluated by a coarse grain renormalization group approach. Our method allows a
tensor-network wavefunction with a high bond degree of freedom (such as D=8) to
be handled accurately and efficiently in the thermodynamic limit. For the
Heisenberg model on a honeycomb lattice, our results for the ground state
energy and the staggered magnetization agree well with those obtained by the
quantum Monte Carlo and other approaches.Comment: 4 pages 5 figures 2 table
Macro aerodynamic devices controlled by micro systems
Micro-ElectroMechanical-Systems (MEMS) have emerged as a major enabling technology across the engineering disciplines. In this study, the possibility of applying MEMS to the aerodynamic field was explored. We have demonstrated that microtransducers can be used to control the motion of a delta wing in a wind tunnel and can even maneuver a scaled aircraft in flight tests. The main advantage of using micro actuators to replace the traditional control surface is the significant reduction of radar cross-sections. At a high angle of attack, a large portion of the suction loading on a delta wing is contributed by the leading edge separation vortices which originate from thin boundary layers at the leading edge. We used microactuators with a thickness comparable to that of the boundary layer in order to alter the separation process and thus achieved control of the global motion by minute perturbations
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Provision of secondary frequency regulation by coordinated dispatch of industrial loads and thermal power plants
Demand responsive industrial loads with high thermal inertia have potential to provide ancillary service for frequency regulation in the power market. To capture the benefit, this study proposes a new hierarchical framework to coordinate the demand responsive industrial loads with thermal power plants in an industrial park for secondary frequency control. In the proposed framework, demand responsive loads and generating resources are coordinated for optimal dispatch in two-time scales: (1) the regulation reserve of the industrial park is optimally scheduled in a day-ahead manner. The stochastic regulation signal is replaced by the specific extremely trajectories. Furthermore, the extremely trajectories are achieved by the day-ahead predicted regulation mileage. The resulting benefit is to transform the stochastic reserve scheduling problem into a deterministic optimization; (2) a model predictive control strategy is proposed to dispatch the industry park in real time with an objective to maximize the revenue. The proposed technology is tested using a real-world industrial electrolysis power system based upon Pennsylvania, Jersey, and Maryland (PJM) power market. Various scenarios are simulated to study the performance of the proposed approach to enable industry parks to provide ancillary service into the power market. The simulation results indicate that an industrial park with a capacity of 500 MW can provide up to 40 MW ancillary service for participation in the secondary frequency regulation. The proposed strategy is demonstrated to be capable of maintaining the economic and secure operation of the industrial park while satisfying performance requirements from the real world regulation market
Public vs private administration of rural health insurance schemes: a comparative study in Zhejiang of China.
: Since 2003, China has experimented in some of the country's counties with the private administration of the New Cooperative Medical Scheme (NCMS), a publicly subsidized health insurance scheme for rural populations. Our study compared the effectiveness and efficiency of private vs public administration in four counties in one of China's most affluent provinces in the initial stage of the NCMS's implementation. The study was undertaken in Ningbo city of Zhejiang province. Out of 10 counties in Ningbo, two counties with private administration for the NCMS (Beilun and Ninghai) were compared with two others counties with public administration (Zhenhai and Fenghua), using the following indicators: (1) proportion of enrollees who were compensated for inpatient care; (2) average reimbursement-expense ratio per episode of inpatient care; (3) overall administration cost; (4) enrollee satisfaction. Data from 2004 to 2006 were collected from the local health authorities, hospitals and the contracted insurance companies, supplemented by a randomized household questionnaire survey covering 176 households and 479 household members. In our sample counties, private administration of the NCMS neither reduced transaction costs, nor improved the benefits of enrollees. Enrollees covered by the publicly administered NCMS were more likely to be satisfied with the insurance scheme than those covered by the privately administered NCMS. Experience in the selected counties suggests that private administration of the NCMS did not deliver the hoped-for results. We conclude that caution needs to be exercised in extending private administration of the NCMS
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