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1810.04452 | Sharif Amit Kamran | Sharif Amit Kamran, Ahmed Imtiaz Humayun, Samiul Alam, Rashed Mohammad
Doha, Manash Kumar Mandal, Tahsin Reasat and Fuad Rahman | AI Learns to Recognize Bengali Handwritten Digits: Bengali.AI Computer
Vision Challenge 2018 | 5 pages, 3 figures | null | null | null | cs.CV | http://creativecommons.org/licenses/by/4.0/ | Solving problems with Artificial intelligence in a competitive manner has
long been absent in Bangladesh and Bengali-speaking community. On the other
hand, there has not been a well structured database for Bengali Handwritten
digits for mass public use. To bring out the best minds working in machine
learning and use their expertise to create a model which can easily recognize
Bengali Handwritten digits, we organized Bengali.AI Computer Vision
Challenge.The challenge saw both local and international teams participating
with unprecedented efforts.
| [{'version': 'v1', 'created': 'Wed, 10 Oct 2018 10:59:28 GMT'}] | 2018-10-11 | [['Kamran', 'Sharif Amit', ''], ['Humayun', 'Ahmed Imtiaz', ''], ['Alam', 'Samiul', ''], ['Doha', 'Rashed Mohammad', ''], ['Mandal', 'Manash Kumar', ''], ['Reasat', 'Tahsin', ''], ['Rahman', 'Fuad', '']] |
1601.06680 | Jos\'e A. R. Fonollosa | Jos\'e A. R. Fonollosa | Conditional distribution variability measures for causality detection | NIPS 2013 workshop on causality | null | null | null | stat.ML cs.LG | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | In this paper we derive variability measures for the conditional probability
distributions of a pair of random variables, and we study its application in
the inference of causal-effect relationships. We also study the combination of
the proposed measures with standard statistical measures in the the framework
of the ChaLearn cause-effect pair challenge. The developed model obtains an AUC
score of 0.82 on the final test database and ranked second in the challenge.
| [{'version': 'v1', 'created': 'Mon, 25 Jan 2016 17:14:31 GMT'}] | 2016-01-26 | [['Fonollosa', 'José A. R.', '']] |
1805.11383 | Prado Martin-Moruno | Prado Martin-Moruno | Monologue of a graviton in identity crisis. Or on Alternative Theories
of Gravity. (In Spanish) | 4 pages. In Spanish. This is an invited contribution to be published
in the Spanish Journal of Physics (Royal Spanish Physics Society) | Vol 32, No 3 (2018): Revista Espa\~nola de F\'isica | null | null | physics.pop-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The era of high precision Cosmology has shown our ignorance about the
composition of the Universe. In this context, there has been a renewed interest
on Alternative Theories of Gravity. Through the experience of a graviton
measured by the LIGO collaboration, we shall understand the conceptual
framework of those theories. They provide us with a theoretical construction
where we can contrast the predictions of General Relativity and a possible
scenario to describe the accelerated expansion of our Universe without assuming
the existence of dark components. During the dawn of gravitational wave
astronomy, gravitation is already promising to be one of the most fascinating
fields of research of the XXI century.
| [{'version': 'v1', 'created': 'Tue, 29 May 2018 12:21:39 GMT'}] | 2018-12-11 | [['Martin-Moruno', 'Prado', '']] |
1405.4480 | Sergio G\'omez | Clara Granell, Sergio Gomez, Alex Arenas | Competing spreading processes on multiplex networks: awareness and
epidemics | 7 pages, 7 figures | Physical Review E 90 (2014) 012808 | 10.1103/PhysRevE.90.012808 | null | physics.soc-ph cond-mat.stat-mech cs.SI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Epidemic-like spreading processes on top of multilayered interconnected
complex networks reveal a rich phase diagram of intertwined competition
effects. A recent study by the authors [Granell et al. Phys. Rev. Lett. 111,
128701 (2013)] presented the analysis of the interrelation between two
processes accounting for the spreading of an epidemics, and the spreading of
information awareness to prevent its infection, on top of multiplex networks.
The results in the case in which awareness implies total immunization to the
disease, revealed the existence of a metacritical point at which the critical
onset of the epidemics starts depending on the reaching of the awareness
process. Here we present a full analysis of these critical properties in the
more general scenario where the awareness spreading does not imply total
immunization, and where infection does not imply immediate awareness of it. We
find the critical relation between both competing processes for a wide spectrum
of parameters representing the interaction between them. We also analyze the
consequences of a massive broadcast of awareness (mass media) on the final
outcome of the epidemic incidence. Importantly enough, the mass media makes the
metacritical point to disappear. The results reveal that the main finding i.e.
existence of a metacritical point, is rooted on the competition principle and
holds for a large set of scenarios.
| [{'version': 'v1', 'created': 'Sun, 18 May 2014 09:59:53 GMT'}] | 2014-07-16 | [['Granell', 'Clara', ''], ['Gomez', 'Sergio', ''], ['Arenas', 'Alex', '']] |
2110.15133 | Ahmed Kebaier | Mohamed Ben Alaya and Ahmed Kebaier and Djibril Sarr | Deep Calibration of Interest Rates Model | null | null | null | null | q-fin.ST cs.LG | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | For any financial institution it is a necessity to be able to apprehend the
behavior of interest rates. Despite the use of Deep Learning that is growing
very fastly, due to many reasons (expertise, ease of use, ...) classic rates
models such as CIR, or the Gaussian family are still being used widely. We
propose to calibrate the five parameters of the G2++ model using Neural
Networks. To achieve that, we construct synthetic data sets of parameters drawn
uniformly from a reference set of parameters calibrated from the market. From
those parameters, we compute Zero-Coupon and Forward rates and their
covariances and correlations. Our first model is a Fully Connected Neural
network and uses only covariances and correlations. We show that covariances
are more suited to the problem than correlations. The second model is a
Convulutional Neural Network using only Zero-Coupon rates with no
transformation. The methods we propose perform very quickly (less than 0.3
seconds for 2 000 calibrations) and have low errors and good fitting.
| [{'version': 'v1', 'created': 'Thu, 28 Oct 2021 14:08:45 GMT'}] | 2021-10-29 | [['Alaya', 'Mohamed Ben', ''], ['Kebaier', 'Ahmed', ''], ['Sarr', 'Djibril', '']] |
2209.15555 | Vladimir Li | Vladimir Li and Atsuto Maki | Towards a Unified View of Affinity-Based Knowledge Distillation | null | null | null | null | cs.CV | http://creativecommons.org/licenses/by-nc-nd/4.0/ | Knowledge transfer between artificial neural networks has become an important
topic in deep learning. Among the open questions are what kind of knowledge
needs to be preserved for the transfer, and how it can be effectively achieved.
Several recent work have shown good performance of distillation methods using
relation-based knowledge. These algorithms are extremely attractive in that
they are based on simple inter-sample similarities. Nevertheless, a proper
metric of affinity and use of it in this context is far from well understood.
In this paper, by explicitly modularising knowledge distillation into a
framework of three components, i.e. affinity, normalisation, and loss, we give
a unified treatment of these algorithms as well as study a number of unexplored
combinations of the modules. With this framework we perform extensive
evaluations of numerous distillation objectives for image classification, and
obtain a few useful insights for effective design choices while demonstrating
how relation-based knowledge distillation could achieve comparable performance
to the state of the art in spite of the simplicity.
| [{'version': 'v1', 'created': 'Fri, 30 Sep 2022 16:12:25 GMT'}] | 2022-10-03 | [['Li', 'Vladimir', ''], ['Maki', 'Atsuto', '']] |
physics/0609158 | Esteban Moreno | Esteban Moreno, F. J. Garcia-Vidal, Sergio G. Rodrigo, L.
Martin-Moreno, Sergey I. Bozhevolnyi | Channel plasmon-polaritons: modal shape, dispersion, and losses | 4 pages, 4 figures | Opt. Lett. 31(23), 3447, December 2006 | 10.1364/OL.31.003447 | null | physics.optics | null | We theoretically study channel plasmon-polaritons (CPPs) with a geometry
similar to that in recent experiments at telecom wavelengths (Bozhevolnyi et
al., Nature 440, 508 (2006)). The CPP modal shape, dispersion relation, and
losses are simulated using the multiple multipole method and the finite
difference time domain technique. It is shown that, with the increase of the
wavelength, the fundamental CPP mode shifts progressively towards the groove
opening, ceasing to be guided at the groove bottom and becoming hybridized with
wedge plasmon-polaritons running along the groove edges.
| [{'version': 'v1', 'created': 'Tue, 19 Sep 2006 09:51:27 GMT'}] | 2009-11-13 | [['Moreno', 'Esteban', ''], ['Garcia-Vidal', 'F. J.', ''], ['Rodrigo', 'Sergio G.', ''], ['Martin-Moreno', 'L.', ''], ['Bozhevolnyi', 'Sergey I.', '']] |
1204.4652 | Konstantin Zloshchastiev | Konstantin G. Zloshchastiev | Volume element structure and roton-maxon-phonon excitations in
superfluid helium beyond the Gross-Pitaevskii approximation | 9 pages, 6 figures | Eur. Phys. J. B (2012) 85: 273 | 10.1140/epjb/e2012-30344-3 | null | cond-mat.other physics.atm-clus quant-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | We propose a theory which deals with the structure and interactions of volume
elements in liquid helium II. The approach consists of two nested models linked
via parametric space. The short-wavelength part describes the interior
structure of the fluid element using a non-perturbative approach based on the
logarithmic wave equation; it suggests the Gaussian-like behaviour of the
element's interior density and interparticle interaction potential. The
long-wavelength part is the quantum many-body theory of such elements which
deals with their dynamics and interactions. Our approach leads to a unified
description of the phonon, maxon and roton excitations, and has noteworthy
agreement with experiment: with one essential parameter to fit we reproduce at
high accuracy not only the roton minimum but also the neighboring local maximum
as well as the sound velocity and structure factor.
| [{'version': 'v1', 'created': 'Fri, 20 Apr 2012 14:56:32 GMT'}, {'version': 'v2', 'created': 'Fri, 10 Aug 2012 13:35:44 GMT'}] | 2012-08-13 | [['Zloshchastiev', 'Konstantin G.', '']] |
2201.06435 | Selahattin Cansiz | Selahattin Cansiz, Cem Kesim, Sevval Nur Bektas, Zeynep Kulali, Murat
Hasanreisoglu, Cigdem Gunduz-Demir | FourierNet: Shape-Preserving Network for Henle's Fiber Layer
Segmentation in Optical Coherence Tomography Images | null | IEEE Journal of Biomedical and Health Informatics, vol. 27, no. 2,
pp. 1036-1047, Feb. 2023 | 10.1109/JBHI.2022.3225425 | null | cs.CV | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The Henle's fiber layer (HFL) in the retina carries valuable information on
the macular condition of an eye. However, in the common practice, this layer is
not separately segmented but rather included in the outer nuclear layer since
it is difficult to perceive HFL contours on standard optical coherence
tomography (OCT) imaging. Due to its variable reflectivity under an imaging
beam, delineating the HFL contours necessitates directional OCT, which requires
additional imaging. This paper addresses this issue by introducing a
shape-preserving network, FourierNet, that achieves HFL segmentation in
standard OCT scans with the target performance obtained when directional OCT
scans are used. FourierNet is a new cascaded network design that puts forward
the idea of benefiting the shape prior of HFL in the network training. This
design proposes to represent the shape prior by extracting Fourier descriptors
on the HFL contours and defining an additional regression task of learning
these descriptors. It then formulates HFL segmentation as concurrent learning
of regression and classification tasks, in which Fourier descriptors are
estimated from an input image to encode the shape prior and used together with
the input image to construct the HFL segmentation map. Our experiments on 1470
images of 30 OCT scans reveal that quantifying the HFL shape with Fourier
descriptors and concurrently learning them with the main task of HFL
segmentation lead to better results. This indicates the effectiveness of
designing a shape-preserving network to improve HFL segmentation by reducing
the need to perform directional OCT imaging.
| [{'version': 'v1', 'created': 'Mon, 17 Jan 2022 14:50:26 GMT'}] | 2023-03-01 | [['Cansiz', 'Selahattin', ''], ['Kesim', 'Cem', ''], ['Bektas', 'Sevval Nur', ''], ['Kulali', 'Zeynep', ''], ['Hasanreisoglu', 'Murat', ''], ['Gunduz-Demir', 'Cigdem', '']] |
physics/0508221 | Gordon Chalmers Dr | Gordon Chalmers | Mass Patterns in the Fermion Spectrum | 3 pages, LaTeX | null | null | null | physics.gen-ph | null | All of the known fermions fit a simple formula which is presented here. The
simple formula appears to indicate a topological origin to mass generation, and
it is globally accurate to an approximate percent. Instantons or a quantized
two Higgs mechanism, as in the MSSM model, could give a simple origin to the
masses.
| [{'version': 'v1', 'created': 'Tue, 30 Aug 2005 16:26:40 GMT'}] | 2007-05-23 | [['Chalmers', 'Gordon', '']] |
1804.04010 | Bhola Dwivedi Prof | K. Wilhelm, B.N. Dwivedi | Impact models of gravitational and electrostatic forces: Potential
energies, atomic clocks, gravitational anomalies and redshift | 21 Pages, 7 Figures | null | null | null | physics.gen-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The far-reaching gravitational force is described by a heuristic impact model
with hypothetical massless entities propagating at the speed of light in vacuum
and transferring momentum and energy be- tween massive bodies through
interactions on a local basis. In the original publication (Wilhelm et al.
2013), a spherical symmetric emission of secondary entities had been
postulated. The potential energy problems in gravitationally and
electrostatically bound two-body systems have been studied in the framework of
this im- pact model of gravity and of a proposed impact model of the
electrostatic force (Wilhelm et al. 2014). These studies have indicated that an
anti-parallel emission of a secondary entity - now called graviton - with
respect to the incoming one is more appropriate. This article is based on the
latter choice and presents the modifications resulting from this change. The
model has been applied to multiple interactions of gravitons in large mass
conglomerations in several publications. They will be summarized here taking
the modified interaction process into account. In addition, the speed of
photons as a function of the gravitational potential are considered in this
context together with the dependence of atomic clocks and the redshift on the
gravitational potential.
| [{'version': 'v1', 'created': 'Tue, 10 Apr 2018 03:12:07 GMT'}] | 2018-04-12 | [['Wilhelm', 'K.', ''], ['Dwivedi', 'B. N.', '']] |
2212.12114 | Nan Xi | Angelos Vasilopoulos and Nan Miles Xi | Predicting Survival of Tongue Cancer Patients by Machine Learning Models | null | null | null | null | q-bio.QM cs.LG | http://creativecommons.org/licenses/by/4.0/ | Tongue cancer is a common oral cavity malignancy that originates in the mouth
and throat. Much effort has been invested in improving its diagnosis,
treatment, and management. Surgical removal, chemotherapy, and radiation
therapy remain the major treatment for tongue cancer. The survival of patients
determines the treatment effect. Previous studies have identified certain
survival and risk factors based on descriptive statistics, ignoring the
complex, nonlinear relationship among clinical and demographic variables. In
this study, we utilize five cutting-edge machine learning models and clinical
data to predict the survival of tongue cancer patients after treatment.
Five-fold cross-validation, bootstrap analysis, and permutation feature
importance are applied to estimate and interpret model performance. The
prognostic factors identified by our method are consistent with previous
clinical studies. Our method is accurate, interpretable, and thus useable as
additional evidence in tongue cancer treatment and management.
| [{'version': 'v1', 'created': 'Fri, 23 Dec 2022 03:00:20 GMT'}] | 2022-12-26 | [['Vasilopoulos', 'Angelos', ''], ['Xi', 'Nan Miles', '']] |
2201.02198 | Xuequan Lu | Di Shao, Xuequan Lu, Xiao Liu | 3D Intracranial Aneurysm Classification and Segmentation via
Unsupervised Dual-branch Learning | under review (corresponding: {[email protected]}) | null | null | null | eess.IV cs.CV cs.LG | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Intracranial aneurysms are common nowadays and how to detect them
intelligently is of great significance in digital health. While most existing
deep learning research focused on medical images in a supervised way, we
introduce an unsupervised method for the detection of intracranial aneurysms
based on 3D point cloud data. In particular, our method consists of two stages:
unsupervised pre-training and downstream tasks. As for the former, the main
idea is to pair each point cloud with its jittered counterpart and maximise
their correspondence. Then we design a dual-branch contrastive network with an
encoder for each branch and a subsequent common projection head. As for the
latter, we design simple networks for supervised classification and
segmentation training. Experiments on the public dataset (IntrA) show that our
unsupervised method achieves comparable or even better performance than some
state-of-the-art supervised techniques, and it is most prominent in the
detection of aneurysmal vessels. Experiments on the ModelNet40 also show that
our method achieves the accuracy of 90.79\% which outperforms existing
state-of-the-art unsupervised models.
| [{'version': 'v1', 'created': 'Thu, 6 Jan 2022 02:03:25 GMT'}, {'version': 'v2', 'created': 'Mon, 17 Jan 2022 02:17:48 GMT'}] | 2022-01-19 | [['Shao', 'Di', ''], ['Lu', 'Xuequan', ''], ['Liu', 'Xiao', '']] |
physics/0008200 | Michael Zeitlin | Antonina N. Fedorova, Michael G. Zeitlin | Multiresolution Representations for Solutions of Vlasov-Maxwell-Poisson
Equations | 3 pages, 2 figures, JAC2000.cls, presented at LINAC2000, paper MOE15 | eConf C000821 (2000) MOE15 | null | null | physics.acc-ph math-ph math.MP nlin.PS physics.comp-ph | null | We present the applications of variational-wavelet approach for computing
multiresolution/multiscale representation for solution of some approximations
of Vlasov-Maxwell-Poisson equations.
| [{'version': 'v1', 'created': 'Sun, 20 Aug 2000 13:12:29 GMT'}] | 2007-05-23 | [['Fedorova', 'Antonina N.', ''], ['Zeitlin', 'Michael G.', '']] |
1809.04618 | Mert G\"urb\"uzbalaban | Xuefeng Gao, Mert G\"urb\"uzbalaban, Lingjiong Zhu | Global Convergence of Stochastic Gradient Hamiltonian Monte Carlo for
Non-Convex Stochastic Optimization: Non-Asymptotic Performance Bounds and
Momentum-Based Acceleration | null | null | null | null | math.OC cs.LG | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Stochastic gradient Hamiltonian Monte Carlo (SGHMC) is a variant of
stochastic gradient with momentum where a controlled and properly scaled
Gaussian noise is added to the stochastic gradients to steer the iterates
towards a global minimum. Many works reported its empirical success in practice
for solving stochastic non-convex optimization problems, in particular it has
been observed to outperform overdamped Langevin Monte Carlo-based methods such
as stochastic gradient Langevin dynamics (SGLD) in many applications. Although
asymptotic global convergence properties of SGHMC are well known, its
finite-time performance is not well-understood. In this work, we study two
variants of SGHMC based on two alternative discretizations of the underdamped
Langevin diffusion. We provide finite-time performance bounds for the global
convergence of both SGHMC variants for solving stochastic non-convex
optimization problems with explicit constants. Our results lead to
non-asymptotic guarantees for both population and empirical risk minimization
problems. For a fixed target accuracy level, on a class of non-convex problems,
we obtain complexity bounds for SGHMC that can be tighter than those for SGLD.
These results show that acceleration with momentum is possible in the context
of global non-convex optimization.
| [{'version': 'v1', 'created': 'Wed, 12 Sep 2018 18:08:15 GMT'}, {'version': 'v2', 'created': 'Wed, 21 Aug 2019 00:38:48 GMT'}, {'version': 'v3', 'created': 'Thu, 22 Aug 2019 15:44:21 GMT'}, {'version': 'v4', 'created': 'Wed, 18 Nov 2020 01:46:53 GMT'}] | 2020-11-19 | [['Gao', 'Xuefeng', ''], ['Gürbüzbalaban', 'Mert', ''], ['Zhu', 'Lingjiong', '']] |
1605.04704 | Jose Jorge Gil | Jose J. Gil | On optimal filtering of measured Mueller matrices | 6 pages | null | 10.1364/AO.55.005449 | null | physics.optics | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | While any two-dimensional mixed state of polarization of light can be
represented by a combination of a pure state and a fully random state, any
Mueller matrix can be represented by a convex combination of a pure component
and three additional components whose randomness is scaled in a proper and
objective way. Such characteristic decomposition constitutes the appropriate
framework for the characterization of the polarimetric randomness of the system
represented by a given Mueller matrix, and provides criteria for the optimal
filtering of noise in experimental polarimetry.
| [{'version': 'v1', 'created': 'Mon, 16 May 2016 10:03:14 GMT'}, {'version': 'v2', 'created': 'Mon, 20 Jun 2016 17:10:43 GMT'}, {'version': 'v3', 'created': 'Mon, 3 Apr 2017 16:55:08 GMT'}] | 2017-04-05 | [['Gil', 'Jose J.', '']] |
2107.08140 | Yang Li | Yang Li, Kevin B Korb, Lloyd Allison | Markov Blanket Discovery using Minimum Message Length | null | null | null | null | cs.LG stat.ML | http://creativecommons.org/licenses/by/4.0/ | Causal discovery automates the learning of causal Bayesian networks from data
and has been of active interest from their beginning. With the sourcing of
large data sets off the internet, interest in scaling up to very large data
sets has grown. One approach to this is to parallelize search using Markov
Blanket (MB) discovery as a first step, followed by a process of combining MBs
in a global causal model. We develop and explore three new methods of MB
discovery using Minimum Message Length (MML) and compare them empirically to
the best existing methods, whether developed specifically as MB discovery or as
feature selection. Our best MML method is consistently competitive and has some
advantageous features.
| [{'version': 'v1', 'created': 'Fri, 16 Jul 2021 22:58:50 GMT'}] | 2021-07-20 | [['Li', 'Yang', ''], ['Korb', 'Kevin B', ''], ['Allison', 'Lloyd', '']] |
1712.07222 | Ryan Gabrys | Ryan Gabrys and Frederic Sala | Codes Correcting Two Deletions | null | null | null | null | cs.IT math.IT | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | In this work, we investigate the problem of constructing codes capable of
correcting two deletions. In particular, we construct a code that requires
redundancy approximately 8 log n + O(log log n) bits of redundancy, where n is
the length of the code. To the best of the author's knowledge, this represents
the best known construction in that it requires the lowest number of redundant
bits for a code correcting two deletions.
| [{'version': 'v1', 'created': 'Tue, 19 Dec 2017 21:26:52 GMT'}, {'version': 'v2', 'created': 'Mon, 30 Apr 2018 20:25:59 GMT'}] | 2018-05-02 | [['Gabrys', 'Ryan', ''], ['Sala', 'Frederic', '']] |
1802.10083 | Chenghao Mou | Jinshuo Liu, Chenghao Mou, Donghong Ji | Discovering Key Nodes in a Temporal Social Network | null | null | null | null | cs.SI physics.soc-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | [Background]Discovering key nodes plays a significant role in Social Network
Analysis(SNA). Effective and accurate mining of key nodes promotes more
successful applications in fields like advertisement and recommendation.
[Methods] With focus on the temporal and categorical property of users' actions
- when did they re-tweet or reply a message, as well as their social intimacy
measured by structural embeddings, we designed a more sensitive PageRank-like
algorithm to accommodate the growing and changing social network in the pursue
of mining key nodes. [Results] Compared with our baseline PageRank algorithm,
key nodes selected by our ranking algorithm noticeably perform better in the
SIR disease simulations with SNAP Higgs dataset. [Conclusion] These results
contributed to a better understanding of disseminations of social events over
the network.
| [{'version': 'v1', 'created': 'Tue, 27 Feb 2018 05:56:04 GMT'}, {'version': 'v2', 'created': 'Thu, 1 Mar 2018 02:26:26 GMT'}] | 2018-03-02 | [['Liu', 'Jinshuo', ''], ['Mou', 'Chenghao', ''], ['Ji', 'Donghong', '']] |
2105.07114 | Qiaoxia Xing | Qiaoxia Xing, Chaoyu Song, Chong Wang, Yuangang Xie, Shenyang Huang,
Fanjie Wang, Yuchen Lei, Xiang Yuan, Cheng Zhang, Lei Mu, Yuan Huang, Faxian
Xiu and Hugen Yan | Tunable terahertz plasmons in graphite thin films | null | Physical Review Letters 126, 147401 (2021) | 10.1103/PhysRevLett.126.147401 | null | physics.optics | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Tunable terahertz plasmons are essential for reconfigurable photonics, which
have been demonstrated in graphene through gating, though with relatively weak
responses. Here, we demonstrate strong terahertz plasmons in graphite thin
films via infrared spectroscopy, with dramatic tunability by even a moderate
temperature change or an in-situ bias voltage. Meanwhile, through
magneto-plasmon studies, we reveal that massive electrons and massless Dirac
holes make comparable contributions to the plasmon response. Our study not only
sets up a platform for further exploration of two-component plasmas, but also
opens an avenue for terahertz modulation through electrical bias or all-optical
means.
| [{'version': 'v1', 'created': 'Sat, 15 May 2021 01:37:54 GMT'}] | 2021-05-18 | [['Xing', 'Qiaoxia', ''], ['Song', 'Chaoyu', ''], ['Wang', 'Chong', ''], ['Xie', 'Yuangang', ''], ['Huang', 'Shenyang', ''], ['Wang', 'Fanjie', ''], ['Lei', 'Yuchen', ''], ['Yuan', 'Xiang', ''], ['Zhang', 'Cheng', ''], ['Mu', 'Lei', ''], ['Huang', 'Yuan', ''], ['Xiu', 'Faxian', ''], ['Yan', 'Hugen', '']] |
2105.08907 | Chrisogonas Odhiambo Mr. | Chrisogonas Odhiambo (1 and 3), Pamela Wright (2 and 3), Cindy Corbett
(2 and 3), Homayoun Valafar (1 and 3) ((1) Computer Science and Engineering
Department, (2) College of Nursing, (3) University of South Carolina) | MedSensor: Medication Adherence Monitoring Using Neural Networks on
Smartwatch Accelerometer Sensor Data | null | null | null | null | cs.AI cs.HC cs.LG | http://creativecommons.org/licenses/by-nc-nd/4.0/ | Poor medication adherence presents serious economic and health problems
including compromised treatment effectiveness, medical complications, and loss
of billions of dollars in wasted medicine or procedures. Though various
interventions have been proposed to address this problem, there is an urgent
need to leverage light, smart, and minimally obtrusive technology such as
smartwatches to develop user tools to improve medication use and adherence. In
this study, we conducted several experiments on medication-taking activities,
developed a smartwatch android application to collect the accelerometer hand
gesture data from the smartwatch, and conveyed the data collected to a central
cloud database. We developed neural networks, then trained the networks on the
sensor data to recognize medication and non-medication gestures. With the
proposed machine learning algorithm approach, this study was able to achieve
average accuracy scores of 97% on the protocol-guided gesture data, and 95% on
natural gesture data.
| [{'version': 'v1', 'created': 'Wed, 19 May 2021 03:42:30 GMT'}] | 2021-05-20 | [['Odhiambo', 'Chrisogonas', '', '1 and 3'], ['Wright', 'Pamela', '', '2 and 3'], ['Corbett', 'Cindy', '', '2 and 3'], ['Valafar', 'Homayoun', '', '1 and 3']] |
1211.6674 | Alexandre Renaux | Dinh Thang Vu, Alexandre Renaux, Remy Boyer, Sylvie Marcos | Some results on the Weiss-Weinstein bound for conditional and
unconditional signal models in array processing | null | null | null | null | cs.IT math.IT stat.AP | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | In this paper, the Weiss-Weinstein bound is analyzed in the context of
sources localization with a planar array of sensors. Both conditional and
unconditional source signal models are studied. First, some results are given
in the multiple sources context without specifying the structure of the
steering matrix and of the noise covariance matrix. Moreover, the case of an
uniform or Gaussian prior are analyzed. Second, these results are applied to
the particular case of a single source for two kinds of array geometries: a
non-uniform linear array (elevation only) and an arbitrary planar (azimuth and
elevation) array.
| [{'version': 'v1', 'created': 'Wed, 28 Nov 2012 17:36:46 GMT'}] | 2012-11-29 | [['Vu', 'Dinh Thang', ''], ['Renaux', 'Alexandre', ''], ['Boyer', 'Remy', ''], ['Marcos', 'Sylvie', '']] |
1603.09064 | Edith Cohen | Edith Cohen | Semi-Supervised Learning on Graphs through Reach and Distance Diffusion | 13 pages, 5 figures | null | null | null | cs.LG | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Semi-supervised learning (SSL) is an indispensable tool when there are few
labeled entities and many unlabeled entities for which we want to predict
labels. With graph-based methods, entities correspond to nodes in a graph and
edges represent strong relations. At the heart of SSL algorithms is the
specification of a dense {\em kernel} of pairwise affinity values from the
graph structure. A learning algorithm is then trained on the kernel together
with labeled entities. The most popular kernels are {\em spectral} and include
the highly scalable "symmetric" Laplacian methods, that compute a soft labels
using Jacobi iterations, and "asymmetric" methods including Personalized Page
Rank (PPR) which use short random walks and apply with directed relations, such
as like, follow, or hyperlinks.
We introduce {\em Reach diffusion} and {\em Distance diffusion} kernels that
build on powerful social and economic models of centrality and influence in
networks and capture the directed pairwise relations that underline social
influence. Inspired by the success of social influence as an alternative to
spectral centrality such as Page Rank, we explore SSL with our kernels and
develop highly scalable algorithms for parameter setting, label learning, and
sampling. We perform preliminary experiments that demonstrate the properties
and potential of our kernels.
| [{'version': 'v1', 'created': 'Wed, 30 Mar 2016 07:51:58 GMT'}, {'version': 'v2', 'created': 'Mon, 23 May 2016 18:21:01 GMT'}, {'version': 'v3', 'created': 'Sat, 13 Aug 2016 05:57:56 GMT'}, {'version': 'v4', 'created': 'Mon, 26 Sep 2016 07:08:42 GMT'}, {'version': 'v5', 'created': 'Fri, 20 Jan 2017 18:34:52 GMT'}] | 2017-01-23 | [['Cohen', 'Edith', '']] |
2302.01535 | Hanbyul Lee | Hanbyul Lee, Qifan Song, Jean Honorio | Support Recovery in Sparse PCA with Non-Random Missing Data | arXiv admin note: text overlap with arXiv:2205.15215 | null | null | null | stat.ML cs.LG | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | We analyze a practical algorithm for sparse PCA on incomplete and noisy data
under a general non-random sampling scheme. The algorithm is based on a
semidefinite relaxation of the $\ell_1$-regularized PCA problem. We provide
theoretical justification that under certain conditions, we can recover the
support of the sparse leading eigenvector with high probability by obtaining a
unique solution. The conditions involve the spectral gap between the largest
and second-largest eigenvalues of the true data matrix, the magnitude of the
noise, and the structural properties of the observed entries. The concepts of
algebraic connectivity and irregularity are used to describe the structural
properties of the observed entries. We empirically justify our theorem with
synthetic and real data analysis. We also show that our algorithm outperforms
several other sparse PCA approaches especially when the observed entries have
good structural properties. As a by-product of our analysis, we provide two
theorems to handle a deterministic sampling scheme, which can be applied to
other matrix-related problems.
| [{'version': 'v1', 'created': 'Fri, 3 Feb 2023 04:20:25 GMT'}] | 2023-02-06 | [['Lee', 'Hanbyul', ''], ['Song', 'Qifan', ''], ['Honorio', 'Jean', '']] |
1503.05272 | Abhisek Ukil | A. Ukil, J. Bernasconi, H. Braendle, H. Buijs, S. Bonenfant | Improved Calibration of Near-Infrared Spectra by Using Ensembles of
Neural Network Models | 7 pages | IEEE Sensors Journal, vol. 10, no. 3, pp. 578-584, 2010 | 10.1109/JSEN.2009.2038124 | null | cs.NE | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | IR or near-infrared (NIR) spectroscopy is a method used to identify a
compound or to analyze the composition of a material. Calibration of NIR
spectra refers to the use of the spectra as multivariate descriptors to predict
concentrations of the constituents. To build a calibration model,
state-of-the-art software predominantly uses linear regression techniques. For
nonlinear calibration problems, neural network-based models have proved to be
an interesting alternative. In this paper, we propose a novel extension of the
conventional neural network-based approach, the use of an ensemble of neural
network models. The individual neural networks are obtained by resampling the
available training data with bootstrapping or cross-validation techniques. The
results obtained for a realistic calibration example show that the
ensemble-based approach produces a significantly more accurate and robust
calibration model than conventional regression methods.
| [{'version': 'v1', 'created': 'Wed, 18 Mar 2015 02:54:04 GMT'}] | 2015-03-19 | [['Ukil', 'A.', ''], ['Bernasconi', 'J.', ''], ['Braendle', 'H.', ''], ['Buijs', 'H.', ''], ['Bonenfant', 'S.', '']] |
2206.03141 | Lujun Hong | Lujun Hong, Yazhou Wang, Abubakar Isa Adamu, Md. Selim Habib,
Mengqiang Cai, Jie Xu, Jianfeng Li, Christos Markos | Impact of Third Order Dispersion on Dissipative Soliton Resonance | null | null | null | null | physics.optics nlin.PS | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Dissipative soliton resonance (DSR) is a promising way for high-energy pulse
generation typically having a symmetrical square pulse profile. While this
method is well known, the impact of third order dispersion (TOD) on DSR is yet
to be fully addressed in the literature. In this article, the impact of TOD on
DSR is numerically investigated under the frame of the complex cubic-quintic
Ginzburg-Landau equation (CQGLE). Our numerical investigations indicate that
DSR can stably exist under TOD with nearly the same pulse amplitude, but with a
(significantly) different pulse duration. Depending on the value of chromatic
dispersion, the pulse duration can be notably longer or shorter due to the
presence of TOD. The TOD effect also alters the dependence of pulse duration on
the nonlinear gain. Another impact of TOD on DSR is that the DSR exists with an
asymmetric pulse profile, leading to steepening of one edge of the DSR pulse,
while flattening of the other. Our results indicate that TOD has a critical
role for realizing DSR in mode-locked lasers and it should be taken into
consideration during design and development of DSR-based lasers.
| [{'version': 'v1', 'created': 'Tue, 7 Jun 2022 09:28:47 GMT'}] | 2022-06-08 | [['Hong', 'Lujun', ''], ['Wang', 'Yazhou', ''], ['Adamu', 'Abubakar Isa', ''], ['Habib', 'Md. Selim', ''], ['Cai', 'Mengqiang', ''], ['Xu', 'Jie', ''], ['Li', 'Jianfeng', ''], ['Markos', 'Christos', '']] |
1309.5422 | Sina Yamac Caliskan | Sina Y. Caliskan, Paulo Tabuada | Compositional Transient Stability Analysis of Multi-Machine Power
Networks | null | null | null | null | cs.SY math.OC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | During the normal operation of a power system all the voltages and currents
are sinusoids with a frequency of 60 Hz in America and parts of Asia, or of
50Hz in the rest of the world. Forcing all the currents and voltages to be
sinusoids with the right frequency is one of the most important problems in
power systems. This problem is known as the transient stability problem in the
power systems literature.
The classical models used to study transient stability are based on several
implicit assumptions that are violated when transients occur. One such
assumption is the use of phasors to study transients. While phasors require
sinusoidal waveforms to be well defined, there is no guarantee that waveforms
will remain sinusoidal during transients. In this paper, we use energy-based
models derived from first principles that are not subject to hard-to-justify
classical assumptions. In addition to eliminate assumptions that are known not
to hold during transient stages, we derive intuitive conditions ensuring the
transient stability of power systems with lossy transmission lines.
Furthermore, the conditions for transient stability are compositional in the
sense that one infers transient stability of a large power system by checking
simple conditions for individual generators.
| [{'version': 'v1', 'created': 'Sat, 21 Sep 2013 03:12:30 GMT'}, {'version': 'v2', 'created': 'Mon, 30 Sep 2013 22:46:02 GMT'}, {'version': 'v3', 'created': 'Tue, 7 Jan 2014 20:24:49 GMT'}, {'version': 'v4', 'created': 'Sun, 2 Feb 2014 23:03:06 GMT'}] | 2014-02-04 | [['Caliskan', 'Sina Y.', ''], ['Tabuada', 'Paulo', '']] |
2003.12949 | Yiming Li | Yiming Li, Changhong Fu, Fangqiang Ding, Ziyuan Huang, Geng Lu | AutoTrack: Towards High-Performance Visual Tracking for UAV with
Automatic Spatio-Temporal Regularization | 2020 IEEE Conference on Computer Vision and Pattern Recognition
(CVPR) | null | null | null | cs.CV | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Most existing trackers based on discriminative correlation filters (DCF) try
to introduce predefined regularization term to improve the learning of target
objects, e.g., by suppressing background learning or by restricting change rate
of correlation filters. However, predefined parameters introduce much effort in
tuning them and they still fail to adapt to new situations that the designer
did not think of. In this work, a novel approach is proposed to online
automatically and adaptively learn spatio-temporal regularization term.
Spatially local response map variation is introduced as spatial regularization
to make DCF focus on the learning of trust-worthy parts of the object, and
global response map variation determines the updating rate of the filter.
Extensive experiments on four UAV benchmarks have proven the superiority of our
method compared to the state-of-the-art CPU- and GPU-based trackers, with a
speed of ~60 frames per second running on a single CPU.
Our tracker is additionally proposed to be applied in UAV localization.
Considerable tests in the indoor practical scenarios have proven the
effectiveness and versatility of our localization method. The code is available
at https://github.com/vision4robotics/AutoTrack.
| [{'version': 'v1', 'created': 'Sun, 29 Mar 2020 05:02:25 GMT'}] | 2020-03-31 | [['Li', 'Yiming', ''], ['Fu', 'Changhong', ''], ['Ding', 'Fangqiang', ''], ['Huang', 'Ziyuan', ''], ['Lu', 'Geng', '']] |
2111.12526 | Shudong Yang | Shudong Yang (1), Miaomiao Liu (1) ((1) Dalian University of
Technology) | Mining Meta-indicators of University Ranking: A Machine Learning
Approach Based on SHAP | 4 pages, 1 figure | null | null | null | stat.AP cs.LG stat.ML | http://creativecommons.org/licenses/by-nc-nd/4.0/ | University evaluation and ranking is an extremely complex activity. Major
universities are struggling because of increasingly complex indicator systems
of world university rankings. So can we find the meta-indicators of the index
system by simplifying the complexity? This research discovered three
meta-indicators based on interpretable machine learning. The first one is time,
to be friends with time, and believe in the power of time, and accumulate
historical deposits; the second one is space, to be friends with city, and grow
together by co-develop; the third one is relationships, to be friends with
alumni, and strive for more alumni donations without ceiling.
| [{'version': 'v1', 'created': 'Wed, 24 Nov 2021 14:49:19 GMT'}] | 2021-11-25 | [['Yang', 'Shudong', ''], ['Liu', 'Miaomiao', '']] |
1908.00962 | Birger Horstmann | Fabian Single, Birger Horstmann, Arnulf Latz | Theory of Impedance Spectroscopy for Lithium Batteries | 21 pages, 8 figures | The Journal of Physical Chemistry C 123 (2020) 27327-27343 | 10.1021/acs.jpcc.9b07389 | null | physics.chem-ph physics.comp-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | In this article, we derive and discuss a physics-based model for impedance
spectroscopy of lithium batteries. Our model for electrochemical cells with
planar electrodes takes into account the solid-electrolyte interphase (SEI) as
porous surface film. We present two improvements over standard impedance
models. Firstly, our model is based on a consistent description of lithium
transport through electrolyte and SEI. We use well-defined transport
parameters, e.g., transference numbers, and consider convection of the
center-of-mass. Secondly, we solve our model equations analytically and state
the full transport parameter dependence of the impedance signals. Our
consistent model results in an analytic expression for the cell impedance
including bulk and surface processes. The impedance signals due to
concentration polarizations highlight the importance of electrolyte convection
in concentrated electrolytes. We simplify our expression for the complex
impedance and compare it to common equivalent circuit models. Such simplified
models are good approximations in concise parameter ranges. Finally, we compare
our model with experiments of lithium metal electrodes and find large
transference numbers for lithium ions. This analysis reveals that lithium-ion
transport through the SEI has solid electrolyte character.
| [{'version': 'v1', 'created': 'Fri, 2 Aug 2019 17:29:43 GMT'}] | 2020-04-03 | [['Single', 'Fabian', ''], ['Horstmann', 'Birger', ''], ['Latz', 'Arnulf', '']] |
1602.04184 | Andrew Critch PhD | Andrew Critch | Parametric Bounded L\"ob's Theorem and Robust Cooperation of Bounded
Agents | Corrected typos, added grant acknowledgement, updated citation style
to author-year | null | null | null | cs.GT cs.LO | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | L\"ob's theorem and G\"odel's theorems make predictions about the behavior of
systems capable of self-reference with unbounded computational resources with
which to write and evaluate proofs. However, in the real world, systems capable
of self-reference will have limited memory and processing speed, so in this
paper we introduce an effective version of L\"ob's theorem which is applicable
given such bounded resources. These results have powerful implications for the
game theory of bounded agents who are able to write proofs about themselves and
one another, including the capacity to out-perform classical Nash equilibria
and correlated equilibria, attaining mutually cooperative program equilibrium
in the Prisoner's Dilemma. Previous cooperative program equilibria studied by
Tennenholtz (2004) and Fortnow (2009) have depended on tests for program
equality, a fragile condition, whereas "L\"obian" cooperation is much more
robust and agnostic of the opponent's implementation.
| [{'version': 'v1', 'created': 'Fri, 12 Feb 2016 19:51:54 GMT'}, {'version': 'v2', 'created': 'Fri, 19 Feb 2016 06:23:45 GMT'}, {'version': 'v3', 'created': 'Thu, 31 Mar 2016 21:55:25 GMT'}, {'version': 'v4', 'created': 'Mon, 4 Apr 2016 19:59:04 GMT'}, {'version': 'v5', 'created': 'Wed, 24 Aug 2016 05:22:57 GMT'}] | 2016-08-25 | [['Critch', 'Andrew', '']] |
2109.11371 | Xi-Dan Hu | Zheng-Xin Guo, Xi-Dan Hu, Xue-Jia Yu, and Zhi Li | Dynamics in an exact solvable quantum magnet: benchmark for quantum
computer | 15 pages, 7 figures | null | null | null | quant-ph cond-mat.mtrl-sci physics.app-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Quantum magnets are never short of novel and fascinating dynamics, yet its
simulation by classical computers requires exponentially-scaled computation
resources, which renders the research on large-scale many-body dynamics
fiendishly difficult. In this letter, we explore the dynamic behavior of 2D
large-scale ferromagnetic J1-J2 Heisenberg model both theoretically and
experimentally. First, the analytical solution of magnon dynamics is obtained
to show an obvious ballistic propagation of magnon, which is typical for
quantum walk. Then, we verify the dynamic behavior of the system through
numerical approach of exact diagonalization and tensor network method. We also
calculate out-of-time ordered correlators and butterfly velocities among
different lattice points, finding that they can well depict the competition
between different couplings. Finally, a quantum walk experiment is designed and
conducted on the basis of IBM programmable quantum processors, and the
experimental results are in consistence with our theoretical predictions. Since
the analytical results can be used, in principle, to predict the behavior of
large-scale quantum many-body systems and even those infinitely large, this
work will help facilitate further research on quantum walk and quantum
many-body dynamics in large-scale lattice systems, guide future design of
quantum computers, as well as popularize quantum computers until they are known
and available to every household in the world.
| [{'version': 'v1', 'created': 'Thu, 23 Sep 2021 13:32:45 GMT'}, {'version': 'v2', 'created': 'Sun, 21 Nov 2021 02:17:25 GMT'}, {'version': 'v3', 'created': 'Sun, 5 Dec 2021 05:04:48 GMT'}, {'version': 'v4', 'created': 'Wed, 2 Mar 2022 08:29:20 GMT'}, {'version': 'v5', 'created': 'Mon, 28 Mar 2022 03:12:51 GMT'}] | 2022-03-29 | [['Guo', 'Zheng-Xin', ''], ['Hu', 'Xi-Dan', ''], ['Yu', 'Xue-Jia', ''], ['Li', 'Zhi', '']] |
2210.08994 | Seng-Beng Ho | Seng-Beng Ho, Zhaoxia Wang, Boon-Kiat Quek, Erik Cambria | Knowledge Representation for Conceptual, Motivational, and Affective
Processes in Natural Language Communication | 8 pages, 7 figures | null | null | null | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Natural language communication is an intricate and complex process. The
speaker usually begins with an intention and motivation of what is to be
communicated, and what effects are expected from the communication, while
taking into consideration the listener's mental model to concoct an appropriate
sentence. The listener likewise has to interpret what the speaker means, and
respond accordingly, also with the speaker's mental state in mind. To do this
successfully, conceptual, motivational, and affective processes have to be
represented appropriately to drive the language generation and understanding
processes. Language processing has succeeded well with the big data approach in
applications such as chatbots and machine translation. However, in human-robot
collaborative social communication and in using natural language for delivering
precise instructions to robots, a deeper representation of the conceptual,
motivational, and affective processes is needed. This paper capitalizes on the
UGALRS (Unified General Autonomous and Language Reasoning System) framework and
the CD+ (Conceptual Representation Plus) representational scheme to illustrate
how social communication through language is supported by a knowledge
representational scheme that handles conceptual, motivational, and affective
processes in a deep and general way. Though a small set of concepts,
motivations, and emotions is treated in this paper, its main contribution is in
articulating a general framework of knowledge representation and processing to
link these aspects together in serving the purpose of natural language
communication for an intelligent system.
| [{'version': 'v1', 'created': 'Mon, 26 Sep 2022 01:37:50 GMT'}, {'version': 'v2', 'created': 'Thu, 20 Oct 2022 07:08:26 GMT'}] | 2022-10-21 | [['Ho', 'Seng-Beng', ''], ['Wang', 'Zhaoxia', ''], ['Quek', 'Boon-Kiat', ''], ['Cambria', 'Erik', '']] |
2008.02900 | Mohammad-Parsa Hosseini | Chelsea Villanueva, Joshua Vincent, Alexander Slowinski,
Mohammad-Parsa Hosseini | Respiratory Sound Classification Using Long-Short Term Memory | null | null | null | null | eess.AS cs.LG cs.SD | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Developing a reliable sound detection and recognition system offers many
benefits and has many useful applications in different industries. This paper
examines the difficulties that exist when attempting to perform sound
classification as it relates to respiratory disease classification. Some
methods which have been employed such as independent component analysis and
blind source separation are examined. Finally, an examination on the use of
deep learning and long short-term memory networks is performed in order to
identify how such a task can be implemented.
| [{'version': 'v1', 'created': 'Thu, 6 Aug 2020 23:11:57 GMT'}] | 2020-08-10 | [['Villanueva', 'Chelsea', ''], ['Vincent', 'Joshua', ''], ['Slowinski', 'Alexander', ''], ['Hosseini', 'Mohammad-Parsa', '']] |
1610.06053 | Taraka Rama Kasicheyanula | Taraka Rama | Chinese Restaurant Process for cognate clustering: A threshold free
approach | null | null | null | null | cs.CL | http://creativecommons.org/licenses/by/4.0/ | In this paper, we introduce a threshold free approach, motivated from Chinese
Restaurant Process, for the purpose of cognate clustering. We show that our
approach yields similar results to a linguistically motivated cognate
clustering system known as LexStat. Our Chinese Restaurant Process system is
fast and does not require any threshold and can be applied to any language
family of the world.
| [{'version': 'v1', 'created': 'Wed, 19 Oct 2016 15:09:21 GMT'}] | 2016-10-20 | [['Rama', 'Taraka', '']] |
1802.06655 | Antonios Anastasopoulos | Antonios Anastasopoulos and David Chiang | Tied Multitask Learning for Neural Speech Translation | accepted at NAACL-HLT 2018 | null | null | null | cs.CL | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | We explore multitask models for neural translation of speech, augmenting them
in order to reflect two intuitive notions. First, we introduce a model where
the second task decoder receives information from the decoder of the first
task, since higher-level intermediate representations should provide useful
information. Second, we apply regularization that encourages transitivity and
invertibility. We show that the application of these notions on jointly trained
models improves performance on the tasks of low-resource speech transcription
and translation. It also leads to better performance when using attention
information for word discovery over unsegmented input.
| [{'version': 'v1', 'created': 'Mon, 19 Feb 2018 14:49:42 GMT'}, {'version': 'v2', 'created': 'Thu, 26 Apr 2018 07:19:25 GMT'}] | 2018-04-27 | [['Anastasopoulos', 'Antonios', ''], ['Chiang', 'David', '']] |
2004.11243 | Monica Arul | Monica Arul and Ahsan Kareem | Applications of shapelet transform to time series classification of
earthquake, wind and wave data | 24 pages, 14 figures. arXiv admin note: text overlap with
arXiv:1911.09086 | Eng. Struct 228 (2021) 111564 | 10.1016/j.engstruct.2020.111564 | null | cs.LG eess.SP stat.ML | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Autonomous detection of desired events from large databases using time series
classification is becoming increasingly important in civil engineering as a
result of continued long-term health monitoring of a large number of
engineering structures encompassing buildings, bridges, towers, and offshore
platforms. In this context, this paper proposes the application of a relatively
new time series representation named "Shapelet transform", which is based on
local similarity in the shape of the time series subsequences. In consideration
of the individual attributes distinctive to time series signals in earthquake,
wind and ocean engineering, the application of this transform yields a new
shape-based feature representation. Combining this shape-based representation
with a standard machine learning algorithm, a truly "white-box" machine
learning model is proposed with understandable features and a transparent
algorithm. This model automates event detection without the intervention of
domain practitioners, yielding a practical event detection procedure. The
efficacy of this proposed shapelet transform-based autonomous detection
procedure is demonstrated by examples, to identify known and unknown earthquake
events from continuously recorded ground-motion measurements, to detect pulses
in the velocity time history of ground motions to distinguish between
near-field and far-field ground motions, to identify thunderstorms from
continuous wind speed measurements, to detect large-amplitude wind-induced
vibrations from the bridge monitoring data, and to identify plunging breaking
waves that have a significant impact on offshore structures.
| [{'version': 'v1', 'created': 'Wed, 22 Apr 2020 10:17:24 GMT'}] | 2021-01-19 | [['Arul', 'Monica', ''], ['Kareem', 'Ahsan', '']] |
1707.08307 | Hans De Raedt | H. De Raedt, K. Michielsen and K. Hess | The photon identification loophole in EPRB experiments: computer models
with single-wing selection | Corrected typo's and added two references | Open Physics 15, 713 - 733, 2017 | null | null | quant-ph physics.comp-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Recent Einstein-Podolsky-Rosen-Bohm experiments [M. Giustina et al. Phys.
Rev. Lett. 115, 250401 (2015); L. K. Shalm et al. Phys. Rev. Lett. 115, 250402
(2015)] that claim to be loophole free are scrutinized and are shown to suffer
a photon identification loophole. The combination of a digital computer and
discrete-event simulation is used to construct a minimal but faithful model of
the most perfected realization of these laboratory experiments. In contrast to
prior simulations, all photon selections are strictly made, as they are in the
actual experiments, at the local station and no other "post-selection" is
involved. The simulation results demonstrate that a manifestly non-quantum
model that identifies photons in the same local manner as in these experiments
can produce correlations that are in excellent agreement with those of the
quantum theoretical description of the corresponding thought experiment, in
conflict with Bell's theorem. The failure of Bell's theorem is possible because
of our recognition of the photon identification loophole. Such identification
measurement-procedures are necessarily included in all actual experiments but
are not included in the theory of Bell and his followers.
| [{'version': 'v1', 'created': 'Wed, 26 Jul 2017 07:27:10 GMT'}, {'version': 'v2', 'created': 'Tue, 1 Aug 2017 09:08:37 GMT'}] | 2017-12-04 | [['De Raedt', 'H.', ''], ['Michielsen', 'K.', ''], ['Hess', 'K.', '']] |
1506.07273 | Hojjat Mostafanasab | Hojjat Mostafanasab and Negin Karimi | $(1-2u^2)$-constacyclic codes over
$\mathbb{F}_p+u\mathbb{F}_p+u^2\mathbb{F}_p$ | 8 pages | null | null | null | cs.IT math.IT | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Let $\mathbb{F}_p$ be a finite field and $u$ be an indeterminate. This
article studies $(1-2u^2)$-constacyclic codes over the ring
$\mathbb{F}_p+u\mathbb{F}_p+u^2\mathbb{F}_p$, where $u^3=u$. We describe
generator polynomials of this kind of codes and investigate the structural
properties of these codes by a decomposition theorem.
| [{'version': 'v1', 'created': 'Wed, 24 Jun 2015 08:00:27 GMT'}] | 2015-06-25 | [['Mostafanasab', 'Hojjat', ''], ['Karimi', 'Negin', '']] |
1906.03919 | David Tourigny | David S. Tourigny | Dynamic metabolic resource allocation based on the maximum entropy
principle | 36 pages including 4 figures, appendix, and references: v5 correct
typos, journal ref and link to code
https://gitlab.com/davidtourigny/resource-allocation | J. Math. Biol. 2020; 80, 2395-2430 | 10.1007/s00285-020-01499-6 | null | q-bio.MN math.DS physics.bio-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Organisms have evolved a variety of mechanisms to cope with the
unpredictability of environmental conditions, and yet mainstream models of
metabolic regulation are typically based on strict optimality principles that
do not account for uncertainty. This paper introduces a dynamic metabolic
modelling framework that is a synthesis of recent ideas on resource allocation
and the powerful optimal control formulation of Ramkrishna and colleagues. In
particular, their work is extended based on the hypothesis that cellular
resources are allocated among elementary flux modes according to the principle
of maximum entropy. These concepts both generalise and unify prior approaches
to dynamic metabolic modelling by establishing a smooth interpolation between
dynamic flux balance analysis and dynamic metabolic models without regulation.
The resulting theory is successful in describing `bet-hedging' strategies
employed by cell populations dealing with uncertainty in a fluctuating
environment, including heterogenous resource investment, accumulation of
reserves in growth-limiting conditions, and the observed behaviour of yeast
growing in batch and continuous cultures. The maximum entropy principle is also
shown to yield an optimal control law consistent with partitioning resources
between elementary flux mode families, which has important practical
implications for model reduction, selection, and simulation.
| [{'version': 'v1', 'created': 'Mon, 10 Jun 2019 11:57:29 GMT'}, {'version': 'v2', 'created': 'Mon, 24 Jun 2019 12:51:58 GMT'}, {'version': 'v3', 'created': 'Thu, 5 Dec 2019 21:23:09 GMT'}, {'version': 'v4', 'created': 'Fri, 3 Apr 2020 17:09:03 GMT'}, {'version': 'v5', 'created': 'Tue, 7 Jul 2020 15:52:09 GMT'}] | 2020-07-08 | [['Tourigny', 'David S.', '']] |
2202.05994 | Sangeeta Srivastava | Sangeeta Srivastava, Samuel Olin, Viktor Podolskiy, Anuj Karpatne,
Wei-Cheng Lee, Anish Arora | Physics-Guided Problem Decomposition for Scaling Deep Learning of
High-dimensional Eigen-Solvers: The Case of Schr\"{o}dinger's Equation | 9 pages, Submitted to SIGKDD in Feb 2022 | null | null | null | cs.LG cs.NA math.NA | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Given their ability to effectively learn non-linear mappings and perform fast
inference, deep neural networks (NNs) have been proposed as a viable
alternative to traditional simulation-driven approaches for solving
high-dimensional eigenvalue equations (HDEs), which are the foundation for many
scientific applications. Unfortunately, for the learned models in these
scientific applications to achieve generalization, a large, diverse, and
preferably annotated dataset is typically needed and is computationally
expensive to obtain. Furthermore, the learned models tend to be memory- and
compute-intensive primarily due to the size of the output layer. While
generalization, especially extrapolation, with scarce data has been attempted
by imposing physical constraints in the form of physics loss, the problem of
model scalability has remained.
In this paper, we alleviate the compute bottleneck in the output layer by
using physics knowledge to decompose the complex regression task of predicting
the high-dimensional eigenvectors into multiple simpler sub-tasks, each of
which are learned by a simple "expert" network. We call the resulting
architecture of specialized experts Physics-Guided Mixture-of-Experts (PG-MoE).
We demonstrate the efficacy of such physics-guided problem decomposition for
the case of the Schr\"{o}dinger's Equation in Quantum Mechanics. Our proposed
PG-MoE model predicts the ground-state solution, i.e., the eigenvector that
corresponds to the smallest possible eigenvalue. The model is 150x smaller than
the network trained to learn the complex task while being competitive in
generalization. To improve the generalization of the PG-MoE, we also employ a
physics-guided loss function based on variational energy, which by quantum
mechanics principles is minimized iff the output is the ground-state solution.
| [{'version': 'v1', 'created': 'Sat, 12 Feb 2022 05:59:08 GMT'}, {'version': 'v2', 'created': 'Tue, 15 Feb 2022 15:49:21 GMT'}] | 2022-02-16 | [['Srivastava', 'Sangeeta', ''], ['Olin', 'Samuel', ''], ['Podolskiy', 'Viktor', ''], ['Karpatne', 'Anuj', ''], ['Lee', 'Wei-Cheng', ''], ['Arora', 'Anish', '']] |
2005.07374 | Cecilia Huertas-Cerdeira | Cecilia Huertas-Cerdeira, Andres Goza, John E. Sader, Tim Colonius and
Morteza Gharib | Dynamics of an inverted cantilever plate at moderate angle of attack | Submitted to Journal of Fluid Mechanics | J. Fluid Mech. 909 (2021) A20 | 10.1017/jfm.2020.922 | null | physics.flu-dyn | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The dynamics of a cantilever plate clamped at its trailing edge and placed at
a moderate angle ($\alpha \leq 30^{\circ}$) to a uniform flow are investigated
experimentally and numerically, and a large experimental data set is provided.
The dynamics are shown to differ significantly from the zero-angle-of-attack
case, commonly called the inverted-flag configuration. Four distinct dynamical
regimes arise at finite angles: a small oscillation around a small-deflection
equilibrium (deformed regime), a small-amplitude flapping motion, a
large-amplitude flapping motion and a small oscillation around a
large-deflection equilibrium (deflected regime). The small-amplitude flapping
motion appears gradually as the flow speed is increased and is consistent with
a limit-cycle oscillation caused by the quasi-steady fluid forcing. The
large-amplitude flapping motion is observed to appear at a constant critical
flow speed that is independent of angle of attack. Its characteristics match
those of the large-amplitude vortex-induced vibration present at zero angle of
attack. The flow speed at which the plate enters the deflected regime decreases
linearly as the angle of attack is increased, causing the flapping motion to
disappear for angles of attack greater than $\alpha \approx 28^{\circ}$.
Finally, the effect of aspect ratio on the plate dynamics is considered, with
reduced aspect ratio plates being shown to lack sharp distinctions between
regimes.
| [{'version': 'v1', 'created': 'Fri, 15 May 2020 06:36:42 GMT'}] | 2020-12-30 | [['Huertas-Cerdeira', 'Cecilia', ''], ['Goza', 'Andres', ''], ['Sader', 'John E.', ''], ['Colonius', 'Tim', ''], ['Gharib', 'Morteza', '']] |
1804.06398 | Anton Setzer | Anton Setzer | Modelling Bitcoin in Agda | 27 pages | null | null | null | cs.CR | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | We present two models of the block chain of Bitcoin in the interactive
theorem prover Agda. The first one is based on a simple model of bank accounts,
while having transactions with multiple inputs and outputs. The second model
models transactions, which refer directly to unspent transaction outputs,
rather than user accounts. The resulting blockchain gives rise to a transaction
tree. That model is formalised using an extended form of induction-recursion,
one of the unique features of Agda. The set of transaction trees and
transactions is defined inductively, while simultaneously recursively defining
the list of unspent transaction outputs. Both structures model standard
transactions, coinbase transactions, transaction fees, the exact message to be
signed by those spending money in a transaction, block rewards, blocks, and the
blockchain, and the second structure models as well maturation time for
coinbase transactions and Merkle trees. Hashing and cryptographic operations
and their correctness are dealt with abstractly by postulating corresponding
operations. An indication is given how the correctness of this model could be
specified and proven in Agda.
| [{'version': 'v1', 'created': 'Tue, 17 Apr 2018 17:52:46 GMT'}] | 2018-04-18 | [['Setzer', 'Anton', '']] |
2212.08493 | Alex Corbett | Sharika Mohanan, Alexander D. Corbett | Understanding the limits of remote focusing | 14 pages, 8 figures | null | null | null | physics.optics | http://creativecommons.org/licenses/by-nc-sa/4.0/ | It has previously been demonstrated in both simulation and experiment that
well aligned remote focusing microscopes exhibit residual spherical aberration
outside the focal plane. In this work, compensation of the residual spherical
aberration is provided by the correction collar on the primary objective,
controlled by a high precision stepper motor. A Shack-Hartmann wave front
sensor is used to demonstrate the magnitude of the spherical aberration
generated by the correction collar matches that predicted by an optical model
of the objective lens. The limited impact of spherical aberration compensation
on the diffraction limited range of the remote focusing system is described
through a consideration of both on-axis and off-axis comatic and astigmatic
aberrations, which are an inherent feature of remote focusing microscopes.
| [{'version': 'v1', 'created': 'Fri, 16 Dec 2022 14:18:04 GMT'}, {'version': 'v2', 'created': 'Wed, 18 Jan 2023 12:31:12 GMT'}] | 2023-01-19 | [['Mohanan', 'Sharika', ''], ['Corbett', 'Alexander D.', '']] |
2106.16102 | Victor Zitian Chen | Victor Zitian Chen, Felipe Montano-Campos, Wlodek Zadrozny, and Evan
Canfield | Machine Reading of Hypotheses for Organizational Research Reviews and
Pre-trained Models via R Shiny App for Non-Programmers | null | null | null | null | cs.IR | http://creativecommons.org/licenses/by/4.0/ | The volume of scientific publications in organizational research becomes
exceedingly overwhelming for human researchers who seek to timely extract and
review knowledge. This paper introduces natural language processing (NLP)
models to accelerate the discovery, extraction, and organization of theoretical
developments (i.e., hypotheses) from social science publications. We illustrate
and evaluate NLP models in the context of a systematic review of stakeholder
value constructs and hypotheses. Specifically, we develop NLP models to
automatically 1) detect sentences in scholarly documents as hypotheses or not
(Hypothesis Detection), 2) deconstruct the hypotheses into nodes (constructs)
and links (causal/associative relationships) (Relationship Deconstruction ),
and 3) classify the features of links in terms causality (versus association)
and direction (positive, negative, versus nonlinear) (Feature Classification).
Our models have reported high performance metrics for all three tasks. While
our models are built in Python, we have made the pre-trained models fully
accessible for non-programmers. We have provided instructions on installing and
using our pre-trained models via an R Shiny app graphic user interface (GUI).
Finally, we suggest the next paths to extend our methodology for
computer-assisted knowledge synthesis.
| [{'version': 'v1', 'created': 'Wed, 30 Jun 2021 14:47:15 GMT'}, {'version': 'v2', 'created': 'Sun, 11 Jul 2021 01:50:53 GMT'}, {'version': 'v3', 'created': 'Sun, 12 Dec 2021 16:13:13 GMT'}] | 2021-12-14 | [['Chen', 'Victor Zitian', ''], ['Montano-Campos', 'Felipe', ''], ['Zadrozny', 'Wlodek', ''], ['Canfield', 'Evan', '']] |
physics/0612198 | Robert Wicks | R. T. Wicks, S. C. Chapman, R. O. Dendy | Mutual Information as a Tool for Identifying Phase Transitions in
Dynamical Complex Systems With Limited Data | 7 pages, 11 figures | null | 10.1103/PhysRevE.75.051125 | null | physics.data-an physics.bio-ph | null | We use a well known model (T. Vicsek et al. Phys Rev Lett 15, 1226 (1995))
for flocking to test mutual information as a tool for detecting order-disorder
transitions, in particular when observations of the system are limited. We show
that mutual information is a sensitive indicator of the phase transition
location, in terms of the natural dimensionless parameters of the system which
we have identified. When only a few particles are tracked, and when only a
subset of the positional and velocity components are available, mutual
information provides a better measure of the phase transition location than the
susceptibility of the data.
| [{'version': 'v1', 'created': 'Wed, 20 Dec 2006 14:43:05 GMT'}, {'version': 'v2', 'created': 'Fri, 13 Apr 2007 12:21:27 GMT'}] | 2009-11-13 | [['Wicks', 'R. T.', ''], ['Chapman', 'S. C.', ''], ['Dendy', 'R. O.', '']] |
1808.00811 | Jan R\"uth | Jan R\"uth and Torsten Zimmermann and Konrad Wolsing and Oliver
Hohlfeld | Digging into Browser-based Crypto Mining | IMC '18: Internet Measurement Conference | Jan R\"uth, Torsten Zimmermann, Konrad Wolsing, and Oliver
Hohlfeld. 2018. Digging into Browser-based Crypto Mining. In IMC '18:
Internet Measurement Conference, October 31-November 2, 2018, Boston, MA,
USA. ACM, New York, NY, USA, 7 pages | 10.1145/3278532.3278539 | null | cs.CR cs.NI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Mining is the foundation of blockchain-based cryptocurrencies such as Bitcoin
rewarding the miner for finding blocks for new transactions. The Monero
currency enables mining with standard hardware in contrast to special hardware
(ASICs) as often used in Bitcoin, paving the way for in-browser mining as a new
revenue model for website operators. In this work, we study the prevalence of
this new phenomenon. We identify and classify mining websites in 138M domains
and present a new fingerprinting method which finds up to a factor of 5.7 more
miners than publicly available block lists. Our work identifies and dissects
Coinhive as the major browser-mining stakeholder. Further, we present a new
method to associate mined blocks in the Monero blockchain to mining pools and
uncover that Coinhive currently contributes 1.18% of mined blocks having turned
over 1293 Moneros in June 2018.
| [{'version': 'v1', 'created': 'Thu, 2 Aug 2018 13:43:58 GMT'}, {'version': 'v2', 'created': 'Fri, 21 Sep 2018 15:15:27 GMT'}] | 2018-09-24 | [['Rüth', 'Jan', ''], ['Zimmermann', 'Torsten', ''], ['Wolsing', 'Konrad', ''], ['Hohlfeld', 'Oliver', '']] |
2111.00873 | Xiaoxian Guo | Xiaoxian Guo, Xiantao Zhang, Xinliang Tian, Wenyue Lu, Xin Li | Probabilistic prediction of the heave motions of a semi-submersible by a
deep learning problem model | null | null | null | null | cs.LG | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The real-time motion prediction of a floating offshore platform refers to
forecasting its motions in the following one- or two-wave cycles, which helps
improve the performance of a motion compensation system and provides useful
early warning information. In this study, we extend a deep learning (DL) model,
which could predict the heave and surge motions of a floating semi-submersible
20 to 50 seconds ahead with good accuracy, to quantify its uncertainty of the
predictive time series with the help of the dropout technique. By repeating the
inference several times, it is found that the collection of the predictive time
series is a Gaussian process (GP). The DL model with dropout learned a kernel
inside, and the learning procedure was similar to GP regression. Adding noise
into training data could help the model to learn more robust features from the
training data, thereby leading to a better performance on test data with a wide
noise level range. This study extends the understanding of the DL model to
predict the wave excited motions of an offshore platform.
| [{'version': 'v1', 'created': 'Sat, 9 Oct 2021 06:26:42 GMT'}] | 2021-11-02 | [['Guo', 'Xiaoxian', ''], ['Zhang', 'Xiantao', ''], ['Tian', 'Xinliang', ''], ['Lu', 'Wenyue', ''], ['Li', 'Xin', '']] |
1608.06119 | Giora Mikenberg | G. Mikenberg | Particle Physics as a way to bring different cultures to work together
in Science | Invited paper to be published in: Progress of Theoretical and
Experimental Physics (Japan) | null | null | null | physics.soc-ph hep-ex physics.pop-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Science has traditionally played an important role in sharing knowledge among
people. Particle Physics, with its large experiments, has shown that one not
only can share the knowledge among different cultures, but that one can also
work together to achieve this knowledge. The present article gives a few
examples where this has been possible among people that are sometimes in
conflict situations.
| [{'version': 'v1', 'created': 'Mon, 22 Aug 2016 11:01:18 GMT'}] | 2016-08-23 | [['Mikenberg', 'G.', '']] |
2301.05303 | Sunho Jang | Sunho Jang, Necmiye Ozay, Johanna L Mathieu | Probabilistic Constraint Construction for Network-safe Load Coordination | submitted to IEEE Transactions on Power Systems | null | null | null | eess.SY cs.SY | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Distributed Energy Resources (DERs) can provide balancing services to the
grid, but their power variations might cause voltage and current constraint
violations in the distribution network, compromising network safety. This could
be avoided by including network constraints within DER control formulations,
but the entities coordinating DERs (e.g., aggregators) may not have access to
network information, which typically is known only to the utility. Therefore,
it is challenging to develop network-safe DER control algorithms when the
aggregator is not the utility; it requires these entities to coordinate with
each other. In this paper, we develop an aggregator-utility coordination
framework that enables network-safe control of thermostatically-controlled
loads to provide frequency regulation. In our framework, the utility sends a
network-safe constraint set on the aggregator's command without directly
sharing any network information. We propose a constraint set construction
algorithm that guarantees satisfaction of a chance constraint on network
safety. Assuming monotonicity of the probability of network safety with respect
to the aggregator's command, we leverage the bisection method to find the
largest possible constraint set, providing maximum flexibility to the
aggregator. Simulations show that, compared to two benchmark algorithms, the
proposed approach provides a good balance between service quality and network
safety.
| [{'version': 'v1', 'created': 'Thu, 12 Jan 2023 21:29:46 GMT'}] | 2023-01-16 | [['Jang', 'Sunho', ''], ['Ozay', 'Necmiye', ''], ['Mathieu', 'Johanna L', '']] |
1612.06475 | James Cross | James Cross and Liang Huang | Span-Based Constituency Parsing with a Structure-Label System and
Provably Optimal Dynamic Oracles | EMNLP 2016 | null | null | null | cs.CL | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Parsing accuracy using efficient greedy transition systems has improved
dramatically in recent years thanks to neural networks. Despite striking
results in dependency parsing, however, neural models have not surpassed
state-of-the-art approaches in constituency parsing. To remedy this, we
introduce a new shift-reduce system whose stack contains merely sentence spans,
represented by a bare minimum of LSTM features. We also design the first
provably optimal dynamic oracle for constituency parsing, which runs in
amortized O(1) time, compared to O(n^3) oracles for standard dependency
parsing. Training with this oracle, we achieve the best F1 scores on both
English and French of any parser that does not use reranking or external data.
| [{'version': 'v1', 'created': 'Tue, 20 Dec 2016 01:23:00 GMT'}] | 2016-12-21 | [['Cross', 'James', ''], ['Huang', 'Liang', '']] |
1504.01639 | Marc Bola\~nos | Marc Bola\~nos and Petia Radeva | Ego-Object Discovery | 9 pages, 13 figures, Submitted to: Image and Vision Computing | null | null | null | cs.CV cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Lifelogging devices are spreading faster everyday. This growth can represent
great benefits to develop methods for extraction of meaningful information
about the user wearing the device and his/her environment. In this paper, we
propose a semi-supervised strategy for easily discovering objects relevant to
the person wearing a first-person camera. Given an egocentric video/images
sequence acquired by the camera, our algorithm uses both the appearance
extracted by means of a convolutional neural network and an object refill
methodology that allows to discover objects even in case of small amount of
object appearance in the collection of images. An SVM filtering strategy is
applied to deal with the great part of the False Positive object candidates
found by most of the state of the art object detectors. We validate our method
on a new egocentric dataset of 4912 daily images acquired by 4 persons as well
as on both PASCAL 2012 and MSRC datasets. We obtain for all of them results
that largely outperform the state of the art approach. We make public both the
EDUB dataset and the algorithm code.
| [{'version': 'v1', 'created': 'Tue, 7 Apr 2015 15:23:22 GMT'}, {'version': 'v2', 'created': 'Wed, 8 Jul 2015 09:19:48 GMT'}] | 2015-07-09 | [['Bolaños', 'Marc', ''], ['Radeva', 'Petia', '']] |
2204.08714 | Xiaojie Chu | Xiaojie Chu, Liangyu Chen, Wenqing Yu | NAFSSR: Stereo Image Super-Resolution Using NAFNet | null | null | null | null | cs.CV | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Stereo image super-resolution aims at enhancing the quality of
super-resolution results by utilizing the complementary information provided by
binocular systems. To obtain reasonable performance, most methods focus on
finely designing modules, loss functions, and etc. to exploit information from
another viewpoint. This has the side effect of increasing system complexity,
making it difficult for researchers to evaluate new ideas and compare methods.
This paper inherits a strong and simple image restoration model, NAFNet, for
single-view feature extraction and extends it by adding cross attention modules
to fuse features between views to adapt to binocular scenarios. The proposed
baseline for stereo image super-resolution is noted as NAFSSR. Furthermore,
training/testing strategies are proposed to fully exploit the performance of
NAFSSR. Extensive experiments demonstrate the effectiveness of our method. In
particular, NAFSSR outperforms the state-of-the-art methods on the KITTI 2012,
KITTI 2015, Middlebury, and Flickr1024 datasets. With NAFSSR, we won 1st place
in the NTIRE 2022 Stereo Image Super-resolution Challenge. Codes and models
will be released at https://github.com/megvii-research/NAFNet.
| [{'version': 'v1', 'created': 'Tue, 19 Apr 2022 07:38:10 GMT'}, {'version': 'v2', 'created': 'Tue, 26 Apr 2022 07:04:33 GMT'}] | 2022-04-27 | [['Chu', 'Xiaojie', ''], ['Chen', 'Liangyu', ''], ['Yu', 'Wenqing', '']] |
0710.3019 | Alexander Pukhov | Naveen Kumar, Alexander Pukhov | New class of self-similar solutions for vacuum plasma expansion
admitting mono-energetic ion spectra | null | null | null | null | physics.plasm-ph physics.acc-ph | null | We report a new class of self-similar solutions for plasma expanding into
vacuum that allows for quasi-monoenergetic ion spectra. A simple analytical
model takes into account externally controlled time-dependent temperature of
the hot electrons. When the laser temporal profile is tailored properly, the
quasi-neutral self-similar expansion of the plasma results in ion concentration
in the phase-space at a particular velocity thus producing a
quasi-monoenergetic spectrum. We prove this analytical prediction using a 1D
partice-in-cell (PIC) simulation where the time-dependent plasma temperature is
controlled by two laser pulses shot at a foil at a suitable time delay.
| [{'version': 'v1', 'created': 'Tue, 16 Oct 2007 11:10:50 GMT'}, {'version': 'v2', 'created': 'Mon, 26 Nov 2007 13:52:46 GMT'}] | 2007-11-26 | [['Kumar', 'Naveen', ''], ['Pukhov', 'Alexander', '']] |
0901.3687 | Syed Nizamuddin Khaderi | S. N. Khaderi, M. G. H. M. Baltussen, P. D. Anderson, D. Ioan, J. M.
J. den Toonder, P. R. Onck | Magnetically-actuated artificial cilia for microfluidic propulsion | To be submitted to the Journal of Mechanics and Physics of Solids | null | null | null | physics.flu-dyn | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Natural cilia are hair-like microtubule-based structures that are able to
move fluid at low Reynolds number through asymmetric motion. In this paper we
follow a biomimetic approach to design artificial cilia lining the inner
surface of microfluidic channels with the goal to propel fluid. The artificial
cilia consist of polymer films filled with magnetic nanoparticles. The
asymmetric, non-reciprocating motion is generated by tuning an external
magnetic field. To obtain the magnetic field and associated magnetization local
to the cilia we solve the Maxwell equations, from which the magnetic torques
can be deduced. To obtain the ciliary motion we solve the dynamic equations of
motion which are then fully coupled to the fluid dynamic equations that
describe fluid flow around the cilia. By doing so we show that by properly
tuning the applied magnetic field, asymmetric ciliary motion can be generated
that is able to propel fluid in a microchannel. The results are presented in
terms of three dimensionless parameters that fully delineate the asymmetry and
cycle time as a function of the relative contribution of elastic, inertial,
magnetic and viscous fluid forces.
| [{'version': 'v1', 'created': 'Fri, 23 Jan 2009 14:02:26 GMT'}] | 2009-09-30 | [['Khaderi', 'S. N.', ''], ['Baltussen', 'M. G. H. M.', ''], ['Anderson', 'P. D.', ''], ['Ioan', 'D.', ''], ['Toonder', 'J. M. J. den', ''], ['Onck', 'P. R.', '']] |
1806.08027 | Tong-Xing Zheng | Tong-Xing Zheng, Hui-Ming Wang, and Jinhong Yuan | Physical-Layer Security in Cache-Enabled Cooperative Small Cell Networks
Against Randomly Distributed Eavesdroppers | 14 pages, 10 figures, accepted for publication on IEEE Transactions
on Wireless Communications | null | null | null | cs.IT math.IT | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | This paper explores the physical-layer security in a small cell network (SCN)
with cooperative cache-enabled small base stations (SBSs) in the presence of
randomly distributed eavesdroppers. We propose a joint design on the caching
placement and the physical-layer transmission to improve the secure content
delivery probability (SCDP). We first put forward a hybrid caching placement
strategy in which a proportion of the cache unit in each SBS is assigned to
store the most popular files (MPFs), while the remaining is used to cache the
disjoint subfiles (DSFs) of the less popular files in different SBSs as a means
to enhance transmission secrecy and content diversity. We then introduce two
coordinated multi-point (CoMP) techniques, namely, joint transmission (JT) and
orthogonal transmission (OT), to deliver the MPFs and DSFs, respectively. We
derive analytical expressions for the SCDP in each transmission scheme,
considering both non-colluding and colluding eavesdropping scenarios. Based on
the obtained analytical results, we jointly design the optimal transmission
rates and the optimal caching assignment for maximizing the overall SCDP.
Various insights into the optimal transmission and caching designs are further
provided. Numerical results are also presented to verify our theoretical
findings and to demonstrate the superiority of the proposed caching and
transmission strategies.
| [{'version': 'v1', 'created': 'Thu, 21 Jun 2018 00:52:36 GMT'}] | 2018-06-22 | [['Zheng', 'Tong-Xing', ''], ['Wang', 'Hui-Ming', ''], ['Yuan', 'Jinhong', '']] |
2103.02087 | Marius Arvinte | Marius Arvinte, Sriram Vishwanath, Ahmed H. Tewfik, and Jonathan I.
Tamir | Deep J-Sense: Accelerated MRI Reconstruction via Unrolled Alternating
Optimization | null | null | null | null | eess.SP cs.LG | http://creativecommons.org/licenses/by/4.0/ | Accelerated multi-coil magnetic resonance imaging reconstruction has seen a
substantial recent improvement combining compressed sensing with deep learning.
However, most of these methods rely on estimates of the coil sensitivity
profiles, or on calibration data for estimating model parameters. Prior work
has shown that these methods degrade in performance when the quality of these
estimators are poor or when the scan parameters differ from the training
conditions. Here we introduce Deep J-Sense as a deep learning approach that
builds on unrolled alternating minimization and increases robustness: our
algorithm refines both the magnetization (image) kernel and the coil
sensitivity maps. Experimental results on a subset of the knee fastMRI dataset
show that this increases reconstruction performance and provides a significant
degree of robustness to varying acceleration factors and calibration region
sizes.
| [{'version': 'v1', 'created': 'Tue, 2 Mar 2021 23:22:22 GMT'}, {'version': 'v2', 'created': 'Thu, 1 Apr 2021 14:35:37 GMT'}, {'version': 'v3', 'created': 'Sun, 11 Apr 2021 17:02:47 GMT'}] | 2021-04-13 | [['Arvinte', 'Marius', ''], ['Vishwanath', 'Sriram', ''], ['Tewfik', 'Ahmed H.', ''], ['Tamir', 'Jonathan I.', '']] |
2010.01717 | Nader Akoury | Nader Akoury, Shufan Wang, Josh Whiting, Stephen Hood, Nanyun Peng,
Mohit Iyyer | STORIUM: A Dataset and Evaluation Platform for Machine-in-the-Loop Story
Generation | Accepted as a long paper to EMNLP 2020 | null | null | null | cs.CL cs.HC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Systems for story generation are asked to produce plausible and enjoyable
stories given an input context. This task is underspecified, as a vast number
of diverse stories can originate from a single input. The large output space
makes it difficult to build and evaluate story generation models, as (1)
existing datasets lack rich enough contexts to meaningfully guide models, and
(2) existing evaluations (both crowdsourced and automatic) are unreliable for
assessing long-form creative text. To address these issues, we introduce a
dataset and evaluation platform built from STORIUM, an online collaborative
storytelling community. Our author-generated dataset contains 6K lengthy
stories (125M tokens) with fine-grained natural language annotations (e.g.,
character goals and attributes) interspersed throughout each narrative, forming
a robust source for guiding models. We evaluate language models fine-tuned on
our dataset by integrating them onto STORIUM, where real authors can query a
model for suggested story continuations and then edit them. Automatic metrics
computed over these edits correlate well with both user ratings of generated
stories and qualitative feedback from semi-structured user interviews. We
release both the STORIUM dataset and evaluation platform to spur more
principled research into story generation.
| [{'version': 'v1', 'created': 'Sun, 4 Oct 2020 23:26:09 GMT'}] | 2020-10-06 | [['Akoury', 'Nader', ''], ['Wang', 'Shufan', ''], ['Whiting', 'Josh', ''], ['Hood', 'Stephen', ''], ['Peng', 'Nanyun', ''], ['Iyyer', 'Mohit', '']] |
1012.0365 | Zhouchen Lin | Zhouchen Lin and Siming Wei | A Block Lanczos with Warm Start Technique for Accelerating Nuclear Norm
Minimization Algorithms | null | null | null | Microsoft Technical Report #MSR-TR-2010-162 | cs.NA cs.AI math.OC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Recent years have witnessed the popularity of using rank minimization as a
regularizer for various signal processing and machine learning problems. As
rank minimization problems are often converted to nuclear norm minimization
(NNM) problems, they have to be solved iteratively and each iteration requires
computing a singular value decomposition (SVD). Therefore, their solution
suffers from the high computation cost of multiple SVDs. To relieve this issue,
we propose using the block Lanczos method to compute the partial SVDs, where
the principal singular subspaces obtained in the previous iteration are used to
start the block Lanczos procedure. To avoid the expensive reorthogonalization
in the Lanczos procedure, the block Lanczos procedure is performed for only a
few steps. Our block Lanczos with warm start (BLWS) technique can be adopted by
different algorithms that solve NNM problems. We present numerical results on
applying BLWS to Robust PCA and Matrix Completion problems. Experimental
results show that our BLWS technique usually accelerates its host algorithm by
at least two to three times.
| [{'version': 'v1', 'created': 'Thu, 2 Dec 2010 01:59:21 GMT'}, {'version': 'v2', 'created': 'Sun, 26 Dec 2010 07:39:11 GMT'}] | 2010-12-30 | [['Lin', 'Zhouchen', ''], ['Wei', 'Siming', '']] |
1908.02037 | Nusrah Hussain | Nusrah Hussain, Engin Erzin, T. Metin Sezgin, and Yucel Yemez | Batch Recurrent Q-Learning for Backchannel Generation Towards Engaging
Agents | 8 pages, 4 figures. arXiv admin note: substantial text overlap with
arXiv:1908.01618 | null | null | null | cs.AI cs.LG | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The ability to generate appropriate verbal and non-verbal backchannels by an
agent during human-robot interaction greatly enhances the interaction
experience. Backchannels are particularly important in applications like
tutoring and counseling, which require constant attention and engagement of the
user. We present here a method for training a robot for backchannel generation
during a human-robot interaction within the reinforcement learning (RL)
framework, with the goal of maintaining high engagement level. Since online
learning by interaction with a human is highly time-consuming and impractical,
we take advantage of the recorded human-to-human dataset and approach our
problem as a batch reinforcement learning problem. The dataset is utilized as a
batch data acquired by some behavior policy. We perform experiments with laughs
as a backchannel and train an agent with value-based techniques. In particular,
we demonstrate the effectiveness of recurrent layers in the approximate value
function for this problem, that boosts the performance in partially observable
environments. With off-policy policy evaluation, it is shown that the RL agents
are expected to produce more engagement than an agent trained from imitation
learning.
| [{'version': 'v1', 'created': 'Tue, 6 Aug 2019 09:25:51 GMT'}] | 2019-08-07 | [['Hussain', 'Nusrah', ''], ['Erzin', 'Engin', ''], ['Sezgin', 'T. Metin', ''], ['Yemez', 'Yucel', '']] |
1702.04154 | Eduardo Fabiano | S. \'Smiga, E. Fabiano, L. A. Constantin, F. Della Sala | Laplacian-dependent models of the kinetic energy density: Applications
in subsystem density functional theory with meta-generalized gradient
approximation functionals | 11 pages, 5 figures | J. Chem. Phys. 146, 064105 (2017) | 10.1063/1.4975092 | null | cond-mat.other physics.chem-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The development of semilocal models for the kinetic energy density (KED) is
an important topic in density functional theory (DFT). This is especially true
for subsystem DFT, where these models are necessary to construct the required
non-additive embedding contributions. In particular, these models can also be
efficiently employed to replace the exact KED in meta-Generalized Gradient
Approximation (meta-GGA) exchange-correlation functionals allowing to extend
the subsystem DFT applicability to the meta-GGA level of theory. Here, we
present a two-dimensional scan of semilocal KED models as linear functionals of
the reduced gradient and of the reduced Laplacian, for atoms and weakly-bound
molecular systems. We find that several models can perform well but in any case
the Laplacian contribution is extremely important to model the local features
of the KED. Indeed a simple model constructed as the sum of Thomas-Fermi KED
and 1/6 of the Laplacian of the density yields the best accuracy for atoms and
weakly-bound molecular systems. These KED models are tested within subsystem
DFT with various meta-GGA exchange-correlation functionals for non-bonded
systems, showing a good accuracy of the method.
| [{'version': 'v1', 'created': 'Tue, 14 Feb 2017 11:11:29 GMT'}] | 2017-02-15 | [['Śmiga', 'S.', ''], ['Fabiano', 'E.', ''], ['Constantin', 'L. A.', ''], ['Della Sala', 'F.', '']] |
2107.11163 | Mariliza Tzes | Mariliza Tzes, Yiannis Kantaros, George J. Pappas | Technical Report: Distributed Sampling-based Planning for Non-Myopic
Active Information Gathering | Accepted to IROS2021 | null | null | null | cs.RO | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | This paper addresses the problem of active information gathering for
multi-robot systems. Specifically, we consider scenarios where robots are
tasked with reducing uncertainty of dynamical hidden states evolving in complex
environments. The majority of existing information gathering approaches are
centralized and, therefore, they cannot be applied to distributed robot teams
where communication to a central user is not available. To address this
challenge, we propose a novel distributed sampling-based planning algorithm
that can significantly increase robot and target scalability while decreasing
computational cost. In our non-myopic approach, all robots build in parallel
local trees exploring the information space and their corresponding motion
space. As the robots construct their respective local trees, they communicate
with their neighbors to exchange and aggregate their local beliefs about the
hidden state through a distributed Kalman filter. We show that the proposed
algorithm is probabilistically complete and asymptotically optimal. We provide
extensive simulation results that demonstrate the scalability of the proposed
algorithm and that it can address large-scale, multi-robot information
gathering tasks, that are computationally challenging for centralized methods.
| [{'version': 'v1', 'created': 'Fri, 23 Jul 2021 12:13:51 GMT'}] | 2021-07-26 | [['Tzes', 'Mariliza', ''], ['Kantaros', 'Yiannis', ''], ['Pappas', 'George J.', '']] |
2107.06082 | James Wells | James D. Wells | Evaluation and Utility of Wilsonian Naturalness | 21 pages | null | null | null | hep-ph hep-th physics.hist-ph | http://creativecommons.org/licenses/by/4.0/ | We demonstrate that many Naturalness tests of particle theories discussed in
the literature can be reformulated as straightforward algorithmic finetuning
assessments in the matching of Wilsonian effective theories above and below
particle mass thresholds. Implications of this EFT formulation of Wilsonian
Naturalness are discussed for several theories, including the Standard Model,
heavy singlet scalar theory, supersymmetry, Grand Unified Theories, twin Higgs
theories, and theories of extra dimensions. We argue that the Wilsonian
Naturalness algorithm presented here constitutes an unambiguous, a priori, and
meaningful test that the Standard Model passes and which "the next good theory"
of particle physics is very likely to pass.
| [{'version': 'v1', 'created': 'Mon, 5 Jul 2021 18:02:02 GMT'}] | 2021-07-14 | [['Wells', 'James D.', '']] |
1803.11440 | Avi Mendelson | Ori Chalak, Cai Weiguang, Li Wei, Fang Lei, Zheng Libing, Wang
Jintang, Wu Zuguang, Gu Xiongli, Wang Haibin, Avi Mendelson | ScaleSimulator: A Fast and Cycle-Accurate Parallel Simulator for
Architectural Exploration | Was published in SIMUTools 2017
https://drive.google.com/file/d/0B-bj84Yl7TM4R0NJRC16dnUxX0U/view | null | null | null | cs.DC cs.AR cs.PF | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Design of next generation computer systems should be supported by simulation
infrastructure that must achieve a few contradictory goals such as fast
execution time, high accuracy, and enough flexibility to allow comparison
between large numbers of possible design points. Most existing architecture
level simulators are designed to be flexible and to execute the code in
parallel for greater efficiency, but at the cost of scarified accuracy. This
paper presents the ScaleSimulator simulation environment, which is based on a
new design methodology whose goal is to achieve near cycle accuracy while still
being flexible enough to simulate many different future system architectures
and efficient enough to run meaningful workloads. We achieve these goals by
making the parallelism a first-class citizen in our methodology. Thus, this
paper focuses mainly on the ScaleSimulator design points that enable better
parallel execution while maintaining the scalability and cycle accuracy of a
simulated architecture. The paper indicates that the new proposed
ScaleSimulator tool can (1) efficiently parallelize the execution of a
cycle-accurate architecture simulator, (2) efficiently simulate complex
architectures (e.g., out-of-order CPU pipeline, cache coherency protocol, and
network) and massive parallel systems, and (3) use meaningful workloads, such
as full simulation of OLTP benchmarks, to examine future architectural choices.
| [{'version': 'v1', 'created': 'Fri, 9 Mar 2018 18:20:20 GMT'}] | 2018-04-02 | [['Chalak', 'Ori', ''], ['Weiguang', 'Cai', ''], ['Wei', 'Li', ''], ['Lei', 'Fang', ''], ['Libing', 'Zheng', ''], ['Jintang', 'Wang', ''], ['Zuguang', 'Wu', ''], ['Xiongli', 'Gu', ''], ['Haibin', 'Wang', ''], ['Mendelson', 'Avi', '']] |
1406.1906 | Jan Egger | Jan Egger | Refinement-Cut: User-Guided Segmentation Algorithm for Translational
Science | 6 figures, 50 references | Sci. Rep. 4, 5164, 2014 | null | null | cs.CV | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | In this contribution, a semi-automatic segmentation algorithm for (medical)
image analysis is presented. More precise, the approach belongs to the category
of interactive contouring algorithms, which provide real-time feedback of the
segmentation result. However, even with interactive real-time contouring
approaches there are always cases where the user cannot find a satisfying
segmentation, e.g. due to homogeneous appearances between the object and the
background, or noise inside the object. For these difficult cases the algorithm
still needs additional user support. However, this additional user support
should be intuitive and rapid integrated into the segmentation process, without
breaking the interactive real-time segmentation feedback. I propose a solution
where the user can support the algorithm by an easy and fast placement of one
or more seed points to guide the algorithm to a satisfying segmentation result
also in difficult cases. These additional seed(s) restrict(s) the calculation
of the segmentation for the algorithm, but at the same time, still enable to
continue with the interactive real-time feedback segmentation. For a practical
and genuine application in translational science, the approach has been tested
on medical data from the clinical routine in 2D and 3D.
| [{'version': 'v1', 'created': 'Sat, 7 Jun 2014 17:11:00 GMT'}] | 2014-06-10 | [['Egger', 'Jan', '']] |
2105.07552 | Kailai Xu | Kailai Xu, Eric Darve | Trust Region Method for Coupled Systems of PDE Solvers and Deep Neural
Networks | null | null | null | null | math.NA cs.NA | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Physics-informed machine learning and inverse modeling require the solution
of ill-conditioned non-convex optimization problems. First-order methods, such
as SGD and ADAM, and quasi-Newton methods, such as BFGS and L-BFGS, have been
applied with some success to optimization problems involving deep neural
networks in computational engineering inverse problems. However, empirical
evidence shows that convergence and accuracy for these methods remain a
challenge. Our study unveiled at least two intrinsic defects of these methods
when applied to coupled systems of partial differential equations (PDEs) and
deep neural networks (DNNs): (1) convergence is often slow with long plateaus
that make it difficult to determine whether the method has converged or not;
(2) quasi-Newton methods do not provide a sufficiently accurate approximation
of the Hessian matrix; this typically leads to early termination (one of the
stopping criteria of the optimizer is satisfied although the achieved error is
far from minimal). Based on these observations, we propose to use trust region
methods for optimizing coupled systems of PDEs and DNNs. Specifically, we
developed an algorithm for second-order physics constrained learning, an
efficient technique to calculate Hessian matrices based on computational
graphs. We show that trust region methods overcome many of the defects and
exhibit remarkable fast convergence and superior accuracy compared to ADAM,
BFGS, and L-BFGS.
| [{'version': 'v1', 'created': 'Mon, 17 May 2021 00:27:16 GMT'}] | 2021-05-18 | [['Xu', 'Kailai', ''], ['Darve', 'Eric', '']] |
2109.00471 | Ruiqi Zhao | Ruiqi Zhao, Tianyi Wu and Guodong Guo | Sparse to Dense Motion Transfer for Face Image Animation | Accepted by ICCV 2021 Advances in Image Manipulation Workshop | null | null | null | cs.CV | http://creativecommons.org/licenses/by-nc-nd/4.0/ | Face image animation from a single image has achieved remarkable progress.
However, it remains challenging when only sparse landmarks are available as the
driving signal. Given a source face image and a sequence of sparse face
landmarks, our goal is to generate a video of the face imitating the motion of
landmarks. We develop an efficient and effective method for motion transfer
from sparse landmarks to the face image. We then combine global and local
motion estimation in a unified model to faithfully transfer the motion. The
model can learn to segment the moving foreground from the background and
generate not only global motion, such as rotation and translation of the face,
but also subtle local motion such as the gaze change. We further improve face
landmark detection on videos. With temporally better aligned landmark sequences
for training, our method can generate temporally coherent videos with higher
visual quality. Experiments suggest we achieve results comparable to the
state-of-the-art image driven method on the same identity testing and better
results on cross identity testing.
| [{'version': 'v1', 'created': 'Wed, 1 Sep 2021 16:23:57 GMT'}, {'version': 'v2', 'created': 'Fri, 3 Sep 2021 04:05:08 GMT'}] | 2021-09-06 | [['Zhao', 'Ruiqi', ''], ['Wu', 'Tianyi', ''], ['Guo', 'Guodong', '']] |
astro-ph/0210185 | Jean-Luc Thiffeault | Edward A. Spiegel and Jean-Luc Thiffeault | Continuum Equations for Stellar Dynamics | 12 pages, 2 figures, RevTeX 4 style. To appear in Stellar
Astrophysical Fluid Dynamics: Proceedings of the Chateau de Mons meeting in
honour of Douglas Gough's 60th birthday (Cambridge University Press, 2003) | null | null | null | astro-ph physics.flu-dyn | null | The description of a stellar system as a continuous fluid represents a
convenient first approximation to stellar dynamics, and its derivation from the
kinetic theory is standard. The challenge lies in providing adequate closure
approximations for the higher-order moments of the phase-space density function
that appear in the fluid dynamical equations. Such closure approximations may
be found using representations of the phase-space density as embodied in the
kinetic theory. In the classic approach of Chapman and Enskog, one is led to
the Navier-Stokes equations, which are known to be inaccurate when the mean
free paths of particles are long, as they are in many stellar systems. To
improve on the fluid description, we derive here a modified closure relation
using a Fokker-Planck collision operator. To illustrate the nature of our
approximation, we apply it to the study of gravitational instability. The
instability proceeds in a qualitative manner as given by the Navier-Stokes
equations but, in our description, the damped modes are considerably closer to
marginality, especially at small scales.
| [{'version': 'v1', 'created': 'Tue, 8 Oct 2002 15:20:30 GMT'}] | 2007-05-23 | [['Spiegel', 'Edward A.', ''], ['Thiffeault', 'Jean-Luc', '']] |
1701.06431 | Oluwaseun Ajao | Oluwaseun Ajao, Anna Jurek, Aisling Gough, Ruth Hunter, Eimear
Barrett, Gary McKeown, Jun Hong and Frank Kee | Feasibility Study of Social Media for Public Health Behaviour Changes | Conference Paper presented by Oluwaseun Ajao 7th Int'l Conference on
Social Media & Society 2016, Goldsmiths University of London | null | null | null | cs.CY | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Social networking sites such as Twitter and Facebook have been shown to
function as effective social sensors that can "feel the pulse" of a community.
The aim of the current study is to test the feasibility of designing,
implementing and evaluating a bespoke social media-enabled intervention that
can be effective for sharing and changing knowledge, attitudes and behaviours
in meaningful ways to promote public health, specifically with regards to
prevention of skin cancer. We present the design and implementation details of
the campaign followed by summary findings and analysis.
| [{'version': 'v1', 'created': 'Fri, 13 Jan 2017 11:39:54 GMT'}] | 2017-01-24 | [['Ajao', 'Oluwaseun', ''], ['Jurek', 'Anna', ''], ['Gough', 'Aisling', ''], ['Hunter', 'Ruth', ''], ['Barrett', 'Eimear', ''], ['McKeown', 'Gary', ''], ['Hong', 'Jun', ''], ['Kee', 'Frank', '']] |
1812.11270 | Yu Meng | Yu Meng, Jiaming Shen, Chao Zhang, Jiawei Han | Weakly-Supervised Hierarchical Text Classification | AAAI 2019 | null | null | null | cs.CL cs.AI cs.LG | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Hierarchical text classification, which aims to classify text documents into
a given hierarchy, is an important task in many real-world applications.
Recently, deep neural models are gaining increasing popularity for text
classification due to their expressive power and minimum requirement for
feature engineering. However, applying deep neural networks for hierarchical
text classification remains challenging, because they heavily rely on a large
amount of training data and meanwhile cannot easily determine appropriate
levels of documents in the hierarchical setting. In this paper, we propose a
weakly-supervised neural method for hierarchical text classification. Our
method does not require a large amount of training data but requires only
easy-to-provide weak supervision signals such as a few class-related documents
or keywords. Our method effectively leverages such weak supervision signals to
generate pseudo documents for model pre-training, and then performs
self-training on real unlabeled data to iteratively refine the model. During
the training process, our model features a hierarchical neural structure, which
mimics the given hierarchy and is capable of determining the proper levels for
documents with a blocking mechanism. Experiments on three datasets from
different domains demonstrate the efficacy of our method compared with a
comprehensive set of baselines.
| [{'version': 'v1', 'created': 'Sat, 29 Dec 2018 03:04:26 GMT'}] | 2019-01-01 | [['Meng', 'Yu', ''], ['Shen', 'Jiaming', ''], ['Zhang', 'Chao', ''], ['Han', 'Jiawei', '']] |
1404.0607 | Mostafizur Rahman | Mostafizur Rahman, Santosh Khasanvis, Jiajun Shi, Mingyu Li, and Csaba
Andras Moritz | Skybridge: 3-D Integrated Circuit Technology Alternative to CMOS | 53 Pages | null | null | null | cs.ET cs.AR | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Continuous scaling of CMOS has been the major catalyst in miniaturization of
integrated circuits (ICs) and crucial for global socio-economic progress.
However, scaling to sub-20nm technologies is proving to be challenging as
MOSFETs are reaching their fundamental limits and interconnection bottleneck is
dominating IC operational power and performance. Migrating to 3-D, as a way to
advance scaling, has eluded us due to inherent customization and manufacturing
requirements in CMOS that are incompatible with 3-D organization. Partial
attempts with die-die and layer-layer stacking have their own limitations. We
propose a 3-D IC fabric technology, Skybridge[TM], which offers paradigm shift
in technology scaling as well as design. We co-architect Skybridge's core
aspects, from device to circuit style, connectivity, thermal management, and
manufacturing pathway in a 3-D fabric-centric manner, building on a uniform 3-D
template. Our extensive bottom-up simulations, accounting for detailed material
system structures, manufacturing process, device, and circuit parasitics,
carried through for several designs including a designed microprocessor, reveal
a 30-60x density, 3.5x performance per watt benefits, and 10X reduction in
interconnect lengths vs. scaled 16-nm CMOS. Fabric-level heat extraction
features are shown to successfully manage IC thermal profiles in 3-D. Skybridge
can provide continuous scaling of integrated circuits beyond CMOS in the 21st
century.
| [{'version': 'v1', 'created': 'Wed, 2 Apr 2014 16:41:11 GMT'}] | 2014-04-03 | [['Rahman', 'Mostafizur', ''], ['Khasanvis', 'Santosh', ''], ['Shi', 'Jiajun', ''], ['Li', 'Mingyu', ''], ['Moritz', 'Csaba Andras', '']] |
1308.0905 | Ciaran Phelan | C.F. Phelan, T. Hennessy and Th. Busch | Shaping the evanescent field of optical nanofibers for cold atom
trapping | 9 pages, 5 figures | null | 10.1364/OE.21.027093 | null | physics.optics physics.atom-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | We investigate trapping geometries for cold, neutral atoms that can be
created in the evanescent field of a tapered optical fibre by combining the
fundamental mode with one of the next lowest possible modes, namely the HE21
mode. Counter propagating red-detuned HE21 modes are combined with a
blue-detuned HE11 fundamental mode to form a potential in the shape of four
intertwined spirals. By changing the polar- ization from circular to linear in
each of the two counter-propagating HE21 modes simultaneously the 4-helix
configuration can be transformed into a lattice configuration. The modification
to the 4-helix configuration due to unwanted excitation of the the T E01 and T
M01 modes is also discussed.
| [{'version': 'v1', 'created': 'Mon, 5 Aug 2013 08:52:49 GMT'}] | 2015-06-16 | [['Phelan', 'C. F.', ''], ['Hennessy', 'T.', ''], ['Busch', 'Th.', '']] |
1811.08070 | Omur Ozel | Omur Ozel and Bruno Sinopoli and Osman Yagan | Optimizing Robustness against Cascading Failures under Max-Load Targeted
Attack | null | null | null | null | physics.soc-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Motivated by reliability of networks in critical infrastructures, we consider
optimal robustness of a class of flow networks against a \textit{targeted}
attack, namely max-load targeted attack, that triggers cascading failures due
to removal of largest load carrying portion of lines. The setup involves a
network of $N$ lines with initial loads $L_1, \ldots, L_N$, drawn from
independent and identical uniform distribution, and free-spaces or redundancies
$S_1, \ldots, S_N$ to be allocated. In the failure propagation mechanism, a
line fails initially due to attack and later due to overloading. The load that
was carried at the moment of failing gets redistributed equally among all
remaining lines in the system. We analyze robustness of this network against
the max-load targeted attack that removes the largest load carrying
$p$-fraction of the lines from the system. The system designer allocates $S_i$
as a stochastic function of the load in each line. Assuming an average
available resource budget, we show that allocating all lines the free-spaces
equally among nodes is optimal under some regulatory assumptions. We provide
numerical results verifying that equal free-space allocation to all lines
perform optimally in more general targeted attack scenarios.
| [{'version': 'v1', 'created': 'Tue, 20 Nov 2018 04:30:23 GMT'}, {'version': 'v2', 'created': 'Wed, 27 Mar 2019 03:46:23 GMT'}] | 2019-03-28 | [['Ozel', 'Omur', ''], ['Sinopoli', 'Bruno', ''], ['Yagan', 'Osman', '']] |
2006.06093 | Akshay Bhardwaj | Akshay Bhardwaj, Yidu Lu, Selina Pan, Nadine Sarter and Brent
Gillespie | The Effects of Driver Coupling and Automation Impedance on Emergency
Steering Interventions | Accepted to the 2020 IEEE International Conference on Systems, Man,
and Cybernetics | 2020 IEEE International Conference on Systems, Man, and
Cybernetics (SMC), pp. 1738-1744. IEEE, 2020 | 10.1109/SMC42975.2020.9282961 | null | eess.SY cs.RO cs.SY | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Automatic emergency steering maneuvers can be used to avoid more obstacles
than emergency braking alone. While a steer-by-wire system can decouple the
driver who might act as a disturbance during the emergency steering maneuver,
the alternative in which the steering wheel remains coupled can enable the
driver to cover for automation faults and conform to regulations that require
the driver to retain control authority. In this paper we present results from a
driving simulator study with 48 participants in which we tested the performance
of three emergency steering intervention schemes. In the first scheme, the
driver was decoupled and the automation system had full control over the
vehicle. In the second and third schemes, the driver was coupled and the
automation system was either given a high impedance or a low impedance. Two
types of unexpected automation faults were also simulated. Results showed that
a high impedance automation system results in significantly fewer collisions
during intended steering interventions but significantly higher collisions
during automation faults when compared to a low impedance automation system.
Moreover, decoupling the driver did not seem to significantly influence the
time required to hand back control to the driver. When coupled, drivers were
able to cover for a faulty automation system and avoid obstacles to a certain
degree, though differences by condition were significant for only one type of
automation fault.
| [{'version': 'v1', 'created': 'Wed, 10 Jun 2020 22:30:28 GMT'}, {'version': 'v2', 'created': 'Tue, 15 Sep 2020 20:42:51 GMT'}] | 2021-04-29 | [['Bhardwaj', 'Akshay', ''], ['Lu', 'Yidu', ''], ['Pan', 'Selina', ''], ['Sarter', 'Nadine', ''], ['Gillespie', 'Brent', '']] |
2208.10241 | Haozheng Luo | Mengyang Liu, Haozheng Luo, Leonard Thong, Yinghao Li, Chao Zhang, Le
Song | SciAnnotate: A Tool for Integrating Weak Labeling Sources for Sequence
Labeling | null | null | null | null | cs.CL | http://creativecommons.org/licenses/by/4.0/ | Weak labeling is a popular weak supervision strategy for Named Entity
Recognition (NER) tasks, with the goal of reducing the necessity for
hand-crafted annotations. Although there are numerous remarkable annotation
tools for NER labeling, the subject of integrating weak labeling sources is
still unexplored. We introduce a web-based tool for text annotation called
SciAnnotate, which stands for scientific annotation tool. Compared to
frequently used text annotation tools, our annotation tool allows for the
development of weak labels in addition to providing a manual annotation
experience. Our tool provides users with multiple user-friendly interfaces for
creating weak labels. SciAnnotate additionally allows users to incorporate
their own language models and visualize the output of their model for
evaluation. In this study, we take multi-source weak label denoising as an
example, we utilized a Bertifying Conditional Hidden Markov Model to denoise
the weak label generated by our tool. We also evaluate our annotation tool
against the dataset provided by Mysore which contains 230 annotated materials
synthesis procedures. The results shows that a 53.7% reduction in annotation
time obtained AND a 1.6\% increase in recall using weak label denoising. Online
demo is available at https://sciannotate.azurewebsites.net/(demo account can be
found in README), but we don't host a model server with it, please check the
README in supplementary material for model server usage.
| [{'version': 'v1', 'created': 'Sun, 7 Aug 2022 19:18:13 GMT'}] | 2022-08-23 | [['Liu', 'Mengyang', ''], ['Luo', 'Haozheng', ''], ['Thong', 'Leonard', ''], ['Li', 'Yinghao', ''], ['Zhang', 'Chao', ''], ['Song', 'Le', '']] |
1502.04262 | Eduardo Izquierdo | Eduardo J. Izquierdo, Paul L. Williams, Randall D. Beer | Information flow through a model of the C. elegans klinotaxis circuit | null | PLoS ONE 10(10): e0140397. (2015) | 10.1371/journal.pone.0140397 | null | q-bio.NC cs.IT math.IT | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Understanding how information about external stimuli is transformed into
behavior is one of the central goals of neuroscience. Here we characterize the
information flow through a complete sensorimotor circuit: from stimulus, to
sensory neurons, to interneurons, to motor neurons, to muscles, to motion.
Specifically, we apply a recently developed framework for quantifying
information flow to a previously published ensemble of models of salt
klinotaxis in the nematode worm C. elegans. The models are grounded in the
neuroanatomy and currently known neurophysiology of the worm. The unknown model
parameters were optimized to reproduce the worm's behavior. Information flow
analysis reveals several key principles underlying how the models operate: (1)
Interneuron class AIY is responsible for integrating information about positive
and negative changes in concentration, and exhibits a strong left/right
information asymmetry. (2) Gap junctions play a crucial role in the transfer of
information responsible for the information symmetry observed in interneuron
class AIZ. (3) Neck motor neuron class SMB implements an information gating
mechanism that underlies the circuit's state-dependent response. (4) The neck
carries non-uniform distribution about changes in concentration. Thus, not all
directions of movement are equally informative. Each of these findings
corresponds to an experimental prediction that could be tested in the worm to
greatly refine our understanding of the neural circuit underlying klinotaxis.
Information flow analysis also allows us to explore how information flow
relates to underlying electrophysiology. Despite large variations in the neural
parameters of individual circuits, the overall information flow architecture
circuit is remarkably consistent across the ensemble, suggesting that
information flow analysis captures general principles of operation for the
klinotaxis circuit.
| [{'version': 'v1', 'created': 'Sun, 15 Feb 2015 00:19:58 GMT'}] | 2015-10-15 | [['Izquierdo', 'Eduardo J.', ''], ['Williams', 'Paul L.', ''], ['Beer', 'Randall D.', '']] |
astro-ph/0610954 | Daniele Fargion | D.Fargion, P.Oliva | Updated Z-Burst Neutrinos at Horizons | 6 Pages, 9 figures | Nucl.Phys.Proc.Suppl.165:116-121,2007 | 10.1016/j.nuclphysbps.2006.11.018 | null | astro-ph hep-ph physics.ao-ph | null | Recent homogeneous and isotropic maps of UHECR, suggest an isotropic cosmic
origin almost uncorrelated to nearby Local Universe prescribed by GZK (tens
Mpc) cut-off. Z-Burst model based on UHE neutrino resonant scattering on light
relic ones in nearby Hot neutrino Dark Halo, may overcome the absence of such a
local imprint and explain the recent correlation with BL Lac at distances of a
few hundred Mpc. Z-Burst multiple imprint, due to very possible lightest
non-degenerated neutrino masses, may inject energy and modulate UHECR ZeV edge
spectra. The Z-burst (and GZK) ultra high energy neutrinos (ZeV and EeV band)
may also shine, by UHE neutrinos mass state mixing, and rise in corresponding
UHE Tau neutrino flavor, whose charged current tau production and its decay in
flight, maybe the source of UHE showering on Earth. The Radius and the
atmosphere size of our planet constrains the tau maximal distance and energy to
make a shower. These terrestrial tau energies are near GZK energy limit. Higher
distances and energies are available in bigger planets; eventual solar
atmosphere horizons may amplify the UHE tau flight allowing tau showering at
ZeV energies offering a novel way to reveal the expected Z-Burst extreme
neutrino fluxes.
| [{'version': 'v1', 'created': 'Tue, 31 Oct 2006 18:39:09 GMT'}, {'version': 'v2', 'created': 'Mon, 6 Nov 2006 23:38:00 GMT'}] | 2008-11-26 | [['Fargion', 'D.', ''], ['Oliva', 'P.', '']] |
2108.00159 | Prakhar Agarwal | Vidhi Jain, Prakhar Agarwal, Shishir Patil, Katia Sycara | Learning Embeddings that Capture Spatial Semantics for Indoor Navigation | null | null | null | null | cs.RO cs.AI | http://creativecommons.org/licenses/by/4.0/ | Incorporating domain-specific priors in search and navigation tasks has shown
promising results in improving generalization and sample complexity over
end-to-end trained policies. In this work, we study how object embeddings that
capture spatial semantic priors can guide search and navigation tasks in a
structured environment. We know that humans can search for an object like a
book, or a plate in an unseen house, based on the spatial semantics of bigger
objects detected. For example, a book is likely to be on a bookshelf or a
table, whereas a plate is likely to be in a cupboard or dishwasher. We propose
a method to incorporate such spatial semantic awareness in robots by leveraging
pre-trained language models and multi-relational knowledge bases as object
embeddings. We demonstrate using these object embeddings to search a query
object in an unseen indoor environment. We measure the performance of these
embeddings in an indoor simulator (AI2Thor). We further evaluate different
pre-trained embedding onSuccess Rate(SR) and success weighted by Path
Length(SPL).
| [{'version': 'v1', 'created': 'Sat, 31 Jul 2021 06:12:40 GMT'}] | 2021-08-03 | [['Jain', 'Vidhi', ''], ['Agarwal', 'Prakhar', ''], ['Patil', 'Shishir', ''], ['Sycara', 'Katia', '']] |
1309.3364 | Alexander V. Savin | Alexander V. Savin and Oleg V. Gendelman | Mechanical control of heat conductivity in microscopic models of
dielectrics | 10 pages, 16 figures | null | null | null | cond-mat.mes-hall physics.comp-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | We discuss a possibility to control a heat conductivity in simple
one-dimensional models of dielectrics by means of external mechanical loads. To
illustrate such possibilities we consider first a well-studied chain with
degenerate double-well potential of the interparticle interaction. Contrary to
previous studies, we consider varying length of the chain with fixed number of
particles. Number of possible energetically degenerate ground states strongly
depends on the overall length of the chain, or, in other terms, on average
length of the link between neighboring particles. These degenerate states
correspond to mechanical equilibrium, therefore one can say that the transition
between them mimics to some extent a process of plastic deformation. We
demonstrate that such modification of the chain length can lead to quite
profound (almost five-fold) reduction of the heat conduction coefficient. Even
more profound effect is revealed for a model with single-well non-convex
potential. It is demonstrated that in certain range of constant external
forcing this model becomes "effectively"\ double-well, and has a multitude of
possible states of equilibrium for the same value of the external load. Thus,
the heat conduction coefficient can be reduced by two orders of magnitude. We
suggest a mechanical model of a chain with periodic double-well potential,
which allows control over the heat conduction. The models considered may be
useful for description of heat transport in biological macromolecules and for
control of the heat transport in microsystems.
| [{'version': 'v1', 'created': 'Fri, 13 Sep 2013 05:21:07 GMT'}] | 2013-09-16 | [['Savin', 'Alexander V.', ''], ['Gendelman', 'Oleg V.', '']] |
2102.04370 | Van Kien Nguyen | Dinh D\~ung and Van Kien Nguyen | High-dimensional nonlinear approximation by parametric manifolds in
H\"older-Nikol'skii spaces of mixed smoothness | 25 pages | null | null | null | math.NA cs.NA math.FA | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | We study high-dimensional nonlinear approximation of functions in
H\"older-Nikol'skii spaces $H^\alpha_\infty(\mathbb{I}^d)$ on the unit cube
$\mathbb{I}^d:=[0,1]^d$ having mixed smoothness, by parametric manifolds. The
approximation error is measured in the $L_\infty$-norm. In this context, we
explicitly constructed methods of nonlinear approximation, and give
dimension-dependent estimates of the approximation error explicitly in
dimension $d$ and number $N$ measuring computation complexity of the parametric
manifold of approximants. For $d=2$, we derived a novel right asymptotic order
of noncontinuous manifold $N$-widths of the unit ball of
$H^\alpha_\infty(\mathbb{I}^2)$ in the space $L_\infty(\mathbb{I}^2)$. In
constructing approximation methods, the function decomposition by the tensor
product Faber series and special representations of its truncations on sparse
grids play a central role.
| [{'version': 'v1', 'created': 'Mon, 8 Feb 2021 17:23:36 GMT'}] | 2021-02-09 | [['Dũng', 'Dinh', ''], ['Nguyen', 'Van Kien', '']] |
1903.04199 | G. S. Bisnovatyi-Kogan | V.S. Belyaev, G.S. Bisnovatyi-Kogan, A.I. Gromov, B.V. Zagreev, A.V.
Lobanov, A.P. Matafonov, S.G. Moiseenko, O.D. Toropina | Numerical Simulations of Magnetized Astrophysical Jets and Comparison
with Laboratory Laser Experiments | 21 pages, 19 figures, published in Astronomy reports 62, 162-188,
2018 | null | 10.1134/S1063772918030034 | null | astro-ph.HE physics.plasm-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The results of MHD numerical simulations of the formation and development of
magnetized jets are presented. Similarity criteria for comparisons of the
results of laboratory laser experiments and numerical simulations of
astrophysical jets are discussed. The results of laboratory simulations of jets
generated in experiments at the Neodim laser installation are presented.
| [{'version': 'v1', 'created': 'Mon, 11 Mar 2019 10:26:20 GMT'}] | 2019-03-20 | [['Belyaev', 'V. S.', ''], ['Bisnovatyi-Kogan', 'G. S.', ''], ['Gromov', 'A. I.', ''], ['Zagreev', 'B. V.', ''], ['Lobanov', 'A. V.', ''], ['Matafonov', 'A. P.', ''], ['Moiseenko', 'S. G.', ''], ['Toropina', 'O. D.', '']] |
2210.07105 | Vladislav Kurenkov | Denis Tarasov, Alexander Nikulin, Dmitry Akimov, Vladislav Kurenkov,
Sergey Kolesnikov | CORL: Research-oriented Deep Offline Reinforcement Learning Library | Accepted at 3rd Offline Reinforcement Learning Workshop at Neural
Information Processing Systems, 2022 | null | null | null | cs.LG cs.AI | http://creativecommons.org/licenses/by/4.0/ | CORL is an open-source library that provides single-file implementations of
Deep Offline Reinforcement Learning algorithms. It emphasizes a simple
developing experience with a straightforward codebase and a modern analysis
tracking tool. In CORL, we isolate methods implementation into distinct single
files, making performance-relevant details easier to recognise. Additionally,
an experiment tracking feature is available to help log metrics,
hyperparameters, dependencies, and more to the cloud. Finally, we have ensured
the reliability of the implementations by benchmarking a commonly employed D4RL
benchmark. The source code can be found at https://github.com/tinkoff-ai/CORL
| [{'version': 'v1', 'created': 'Thu, 13 Oct 2022 15:40:11 GMT'}, {'version': 'v2', 'created': 'Sun, 20 Nov 2022 22:34:33 GMT'}] | 2022-11-22 | [['Tarasov', 'Denis', ''], ['Nikulin', 'Alexander', ''], ['Akimov', 'Dmitry', ''], ['Kurenkov', 'Vladislav', ''], ['Kolesnikov', 'Sergey', '']] |
2209.06054 | Qihao Liang Mr. | Zihao Wang, Qihao Liang, Kejun Zhang, Yuxing Wang, Chen Zhang, Pengfei
Yu, Yongsheng Feng, Wenbo Liu, Yikai Wang, Yuntai Bao, Yiheng Yang | SongDriver: Real-time Music Accompaniment Generation without Logical
Latency nor Exposure Bias | *Both Zihao Wang and Qihao Liang contribute equally to the paper and
share the co-first authorship. This paper has been accepted by ACM Multimedia
2022, oral session, full paper (main track) | null | 10.1145/3503161.3548368 | null | cs.SD cs.LG cs.MM eess.AS | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Real-time music accompaniment generation has a wide range of applications in
the music industry, such as music education and live performances. However,
automatic real-time music accompaniment generation is still understudied and
often faces a trade-off between logical latency and exposure bias. In this
paper, we propose SongDriver, a real-time music accompaniment generation system
without logical latency nor exposure bias. Specifically, SongDriver divides one
accompaniment generation task into two phases: 1) The arrangement phase, where
a Transformer model first arranges chords for input melodies in real-time, and
caches the chords for the next phase instead of playing them out. 2) The
prediction phase, where a CRF model generates playable multi-track
accompaniments for the coming melodies based on previously cached chords. With
this two-phase strategy, SongDriver directly generates the accompaniment for
the upcoming melody, achieving zero logical latency. Furthermore, when
predicting chords for a timestep, SongDriver refers to the cached chords from
the first phase rather than its previous predictions, which avoids the exposure
bias problem. Since the input length is often constrained under real-time
conditions, another potential problem is the loss of long-term sequential
information. To make up for this disadvantage, we extract four musical features
from a long-term music piece before the current time step as global
information. In the experiment, we train SongDriver on some open-source
datasets and an original \`aiSong Dataset built from Chinese-style modern pop
music scores. The results show that SongDriver outperforms existing SOTA
(state-of-the-art) models on both objective and subjective metrics, meanwhile
significantly reducing the physical latency.
| [{'version': 'v1', 'created': 'Tue, 13 Sep 2022 15:05:27 GMT'}, {'version': 'v2', 'created': 'Thu, 13 Oct 2022 10:03:49 GMT'}] | 2022-10-14 | [['Wang', 'Zihao', ''], ['Liang', 'Qihao', ''], ['Zhang', 'Kejun', ''], ['Wang', 'Yuxing', ''], ['Zhang', 'Chen', ''], ['Yu', 'Pengfei', ''], ['Feng', 'Yongsheng', ''], ['Liu', 'Wenbo', ''], ['Wang', 'Yikai', ''], ['Bao', 'Yuntai', ''], ['Yang', 'Yiheng', '']] |
1909.00430 | Matan Ben Noach | Matan Ben Noach and Yoav Goldberg | Transfer Learning Between Related Tasks Using Expected Label Proportions | EMNLP 2019 | 2019 Conference on Empirical Methods in Natural Language
Processing and 9th International Joint Conference on Natural Language
Processing | null | null | cs.LG cs.CL cs.IR stat.ML | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Deep learning systems thrive on abundance of labeled training data but such
data is not always available, calling for alternative methods of supervision.
One such method is expectation regularization (XR) (Mann and McCallum, 2007),
where models are trained based on expected label proportions. We propose a
novel application of the XR framework for transfer learning between related
tasks, where knowing the labels of task A provides an estimation of the label
proportion of task B. We then use a model trained for A to label a large
corpus, and use this corpus with an XR loss to train a model for task B. To
make the XR framework applicable to large-scale deep-learning setups, we
propose a stochastic batched approximation procedure. We demonstrate the
approach on the task of Aspect-based Sentiment classification, where we
effectively use a sentence-level sentiment predictor to train accurate
aspect-based predictor. The method improves upon fully supervised neural system
trained on aspect-level data, and is also cumulative with LM-based pretraining,
as we demonstrate by improving a BERT-based Aspect-based Sentiment model.
| [{'version': 'v1', 'created': 'Sun, 1 Sep 2019 17:11:35 GMT'}] | 2019-09-15 | [['Noach', 'Matan Ben', ''], ['Goldberg', 'Yoav', '']] |
1907.00450 | Erfan Pakdamanian | Ben Benzaman, Erfan Pakdamanian | Discrete Event Simulation of Driver's Routing Behavior Rule at a Road
Intersection | null | null | null | null | eess.SY cs.SY | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Several factors influence traffic congestion and overall traffic dynamics.
Simulation modeling has been utilized to understand the traffic performance
parameters during traffic congestions. This paper focuses on driver behavior of
route selection by differentiating three distinguishable decisions, which are
shortest distance routing, shortest time routing and less crowded road routing.
This research generated 864 different scenarios to capture various traffic
dynamics under collective driving behavior of route selection. Factors such as
vehicle arrival rate, behaviors at system boundary and traffic light phasing
were considered. The simulation results revealed that shortest time routing
scenario offered the best solution considering all forms of interactions among
the factors. Overall, this routing behavior reduces traffic wait time and total
time (by 69.5% and 65.72%) compared to shortest distance routing.
| [{'version': 'v1', 'created': 'Sun, 30 Jun 2019 20:18:41 GMT'}, {'version': 'v2', 'created': 'Mon, 15 Jul 2019 23:29:42 GMT'}] | 2019-07-17 | [['Benzaman', 'Ben', ''], ['Pakdamanian', 'Erfan', '']] |
1606.07953 | Abhyuday Jagannatha | Abhyuday Jagannatha, Hong Yu | Bidirectional Recurrent Neural Networks for Medical Event Detection in
Electronic Health Records | In proceedings of NAACL HLT 2016 | null | null | null | cs.CL cs.LG cs.NE | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Sequence labeling for extraction of medical events and their attributes from
unstructured text in Electronic Health Record (EHR) notes is a key step towards
semantic understanding of EHRs. It has important applications in health
informatics including pharmacovigilance and drug surveillance. The state of the
art supervised machine learning models in this domain are based on Conditional
Random Fields (CRFs) with features calculated from fixed context windows. In
this application, we explored various recurrent neural network frameworks and
show that they significantly outperformed the CRF models.
| [{'version': 'v1', 'created': 'Sat, 25 Jun 2016 19:46:28 GMT'}, {'version': 'v2', 'created': 'Tue, 12 Jul 2016 17:10:38 GMT'}] | 2016-07-13 | [['Jagannatha', 'Abhyuday', ''], ['Yu', 'Hong', '']] |
2012.11059 | Marco Moriconi | Nivaldo A. Lemos, Marco Moriconi | On the consistency of the Lagrange multiplier method in classical
mechanics | 17 pages, To appear in Am. J. Phys | null | 10.1119/10.0004135 | null | physics.class-ph | http://creativecommons.org/licenses/by/4.0/ | Problems involving rolling without slipping or no sideways skidding, to name
a few, introduce velocity-dependent constraints that can be efficiently treated
by the method of Lagrange multipliers in the Lagrangian formulation of the
classical equations of motion. In doing so one finds, as a bonus, the
constraint forces, which must be independent of the solution of the equations
of motion, and can only depend on the generalized coordinates and velocities,
as well as time. In this paper we establish the conditions the Lagrangian
should obey that guarantee that the constraint forces can be obtained
consistently.
| [{'version': 'v1', 'created': 'Mon, 21 Dec 2020 00:20:05 GMT'}, {'version': 'v2', 'created': 'Thu, 8 Apr 2021 20:38:22 GMT'}] | 2021-08-11 | [['Lemos', 'Nivaldo A.', ''], ['Moriconi', 'Marco', '']] |
2008.07961 | Ye Zhu | Ye Zhu, Yan Yan, and Oleg Komogortsev | Hierarchical HMM for Eye Movement Classification | ECCV2020 Workshop, OpenEyes: Eye Gaze in AR, VR, and in the Wild | null | null | null | cs.CV | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | In this work, we tackle the problem of ternary eye movement classification,
which aims to separate fixations, saccades and smooth pursuits from the raw eye
positional data. The efficient classification of these different types of eye
movements helps to better analyze and utilize the eye tracking data. Different
from the existing methods that detect eye movement by several pre-defined
threshold values, we propose a hierarchical Hidden Markov Model (HMM)
statistical algorithm for detecting fixations, saccades and smooth pursuits.
The proposed algorithm leverages different features from the recorded raw eye
tracking data with a hierarchical classification strategy, separating one type
of eye movement each time. Experimental results demonstrate the effectiveness
and robustness of the proposed method by achieving competitive or better
performance compared to the state-of-the-art methods.
| [{'version': 'v1', 'created': 'Tue, 18 Aug 2020 14:47:23 GMT'}] | 2020-08-19 | [['Zhu', 'Ye', ''], ['Yan', 'Yan', ''], ['Komogortsev', 'Oleg', '']] |
1911.05240 | Tuyen Tran | Tuyen Tran, Aidan Hamilton, Maricela Best McKay, Benjamin Quiring, and
Panayot S. Vassilevski | DNN Approximation of Nonlinear Finite Element Equations | null | null | null | null | math.NA cs.NA | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | We investigate the potential of applying (D)NN ((deep) neural networks) for
approximating nonlinear mappings arising in the finite element discretization
of nonlinear PDEs (partial differential equations). As an application, we apply
the trained DNN to replace the coarse nonlinear operator thus avoiding the need
to visit the fine level discretization in order to evaluate the actions of the
true coarse nonlinear operator. The feasibility of the studied approach is
demonstrated in a two-level FAS (full approximation scheme) used to solve a
nonlinear diffusion-reaction PDE.
| [{'version': 'v1', 'created': 'Wed, 13 Nov 2019 01:50:45 GMT'}] | 2019-11-14 | [['Tran', 'Tuyen', ''], ['Hamilton', 'Aidan', ''], ['McKay', 'Maricela Best', ''], ['Quiring', 'Benjamin', ''], ['Vassilevski', 'Panayot S.', '']] |
1804.03943 | Yong Man Ro | Heoun-taek Lim, Hak Gu Kim, Yong Man Ro | VR IQA NET: Deep Virtual Reality Image Quality Assessment using
Adversarial Learning | To appear at IEEE ICASSP 2018 | null | null | null | cs.CV | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | In this paper, we propose a novel virtual reality image quality assessment
(VR IQA) with adversarial learning for omnidirectional images. To take into
account the characteristics of the omnidirectional image, we devise deep
networks including novel quality score predictor and human perception guider.
The proposed quality score predictor automatically predicts the quality score
of distorted image using the latent spatial and position feature. The proposed
human perception guider criticizes the predicted quality score of the predictor
with the human perceptual score using adversarial learning. For evaluation, we
conducted extensive subjective experiments with omnidirectional image dataset.
Experimental results show that the proposed VR IQA metric outperforms the 2-D
IQA and the state-of-the-arts VR IQA.
| [{'version': 'v1', 'created': 'Wed, 11 Apr 2018 11:45:56 GMT'}] | 2018-04-12 | [['Lim', 'Heoun-taek', ''], ['Kim', 'Hak Gu', ''], ['Ro', 'Yong Man', '']] |
2209.10366 | Yunhui He | Yunhui He, Zhengyang Bai, Yuechun Jiao, Jianming Zhao, and Weibin Li | Superradiance-induced multistability in driven Rydberg lattice gases | null | Phys. Rev. A 106, 063319(2022) | 10.1103/PhysRevA.106.063319 | null | quant-ph physics.atom-ph | http://creativecommons.org/licenses/by/4.0/ | We study steady state phases of a one-dimensional array of Rydberg atoms
coupled by a microwave (MW) field where the higher energy Rydberg state decays
to the lower energy one via single-body and collective (superradiant) decay.
Using mean-field approaches, we examine the interplay among the MW coupling,
intra-state van der Waals (vdW) interaction, and single-body and collective
dissipation between Rydberg states. A linear stability analysis reveals that a
series of phases, including uniform, antiferromagnetic, oscillatory, and
bistable and multistable phases can be obtained. Without the vdW interaction,
only uniform phases are found. In the presence of the vdW interaction,
multistable solutions are enhanced when increasing the strength of the
superradiant decay rate. Our numerical simulations show that the bistable and
multistable phases are stabilized by superradiance in a long chain. The
critical point between the uniform and multistable phases and its scaling with
the atom number is obtained. Through numerically solving the master equation of
a finite chain, we show that the mean-field multistable phase could be
characterized by expectation values of Rydberg populations and two-body
correlations between Rydberg atoms in different sites.
| [{'version': 'v1', 'created': 'Wed, 21 Sep 2022 14:01:08 GMT'}, {'version': 'v2', 'created': 'Fri, 6 Jan 2023 02:58:10 GMT'}] | 2023-01-09 | [['He', 'Yunhui', ''], ['Bai', 'Zhengyang', ''], ['Jiao', 'Yuechun', ''], ['Zhao', 'Jianming', ''], ['Li', 'Weibin', '']] |
2010.11868 | Raphael Luiz Vicente Fortulan | Raphael L. V. Fortulan and Lu\'is F. C. Alberto | Parameter Reduction in Probabilistic Critical Time Evaluation Using
Sensitivity Analysis and PCA | 5 pages | null | null | null | eess.SY cs.SY | http://creativecommons.org/licenses/by-nc-sa/4.0/ | In this paper, we discuss a method to find the most influential power system
parameters to the probabilistic transient stability assessment
problem---finding the probability distribution of the critical clearing time.
We perform the parameter selection by employing a sensitivity analysis combined
with a principal component analysis. First, we determine the sensitivity of the
machine angles with respect to all system parameters. Second, we employ the
principal component analysis algorithm to identify the most influential
parameters in the transient stability problem. By identifying such parameters,
we can reduce the number of uncertain parameters to only the influential ones
in the probabilistic assessment of transient stability, providing a significant
speed-up in the probabilistic analysis of large power systems. The proposed
algorithm was tested in the IEEE 14 bus systems and the results obtained show
that our method can effectively find the most influential parameters.
| [{'version': 'v1', 'created': 'Thu, 22 Oct 2020 17:01:29 GMT'}] | 2020-10-23 | [['Fortulan', 'Raphael L. V.', ''], ['Alberto', 'Luís F. C.', '']] |
1904.07087 | Rui Wang | Rui Wang, Stephen M. Pizer, Jan-Michael Frahm | Recurrent Neural Network for (Un-)supervised Learning of Monocular
VideoVisual Odometry and Depth | null | null | null | null | cs.CV | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Deep learning-based, single-view depth estimation methods have recently shown
highly promising results. However, such methods ignore one of the most
important features for determining depth in the human vision system, which is
motion. We propose a learning-based, multi-view dense depth map and odometry
estimation method that uses Recurrent Neural Networks (RNN) and trains
utilizing multi-view image reprojection and forward-backward flow-consistency
losses. Our model can be trained in a supervised or even unsupervised mode. It
is designed for depth and visual odometry estimation from video where the input
frames are temporally correlated. However, it also generalizes to single-view
depth estimation. Our method produces superior results to the state-of-the-art
approaches for single-view and multi-view learning-based depth estimation on
the KITTI driving dataset.
| [{'version': 'v1', 'created': 'Mon, 15 Apr 2019 14:48:43 GMT'}] | 2019-04-16 | [['Wang', 'Rui', ''], ['Pizer', 'Stephen M.', ''], ['Frahm', 'Jan-Michael', '']] |
1101.0662 | Gennady Naumenko | G.A. Naumenko, L.G. Sukhikh, Yu.A. Popov, M.V. Shevelev | Investigation of the longitudinal component of an electron
electromagnetic field under condition of the shadowing effect | This article is submitted for Proceedings of 4th International
Conference "Charged and Neutral Particles Channeling Phenomena", October 3 -
8, 2010, Ferrara (FE), Italy | null | null | null | physics.acc-ph physics.class-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | In this paper we present the method and experimental results of the
investigation of a longitudinal component of relativistic electron
electromagnetic field in the shadow area of a transversal component. We show
experimentally, that in a region, comparable with the formation length area no
shadowing effect of the longitudinal component of relativistic electron
electromagnetic field appears. This is important for understanding of
possibility of the shadowing effect in Smith-Purcell radiation and some other
radiation types.
| [{'version': 'v1', 'created': 'Tue, 4 Jan 2011 06:52:42 GMT'}] | 2011-01-05 | [['Naumenko', 'G. A.', ''], ['Sukhikh', 'L. G.', ''], ['Popov', 'Yu. A.', ''], ['Shevelev', 'M. V.', '']] |
1802.03239 | Avi Rosenfeld | Avi Rosenfeld and Ron Illuz and Dovid Gottesman and Mark Last | Using Discretization for Extending the Set of Predictive Features | 14 pages | EURASIP Journal on Advances in Signal Processing 2018:7 | 10.1186/s13634-018-0528-x | null | cs.LG cs.AI stat.ML | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | To date, attribute discretization is typically performed by replacing the
original set of continuous features with a transposed set of discrete ones.
This paper provides support for a new idea that discretized features should
often be used in addition to existing features and as such, datasets should be
extended, and not replaced, by discretization. We also claim that
discretization algorithms should be developed with the explicit purpose of
enriching a non-discretized dataset with discretized values. We present such an
algorithm, D-MIAT, a supervised algorithm that discretizes data based on
Minority Interesting Attribute Thresholds. D-MIAT only generates new features
when strong indications exist for one of the target values needing to be
learned and thus is intended to be used in addition to the original data. We
present extensive empirical results demonstrating the success of using D-MIAT
on $ 28 $ benchmark datasets. We also demonstrate that $ 10 $ other
discretization algorithms can also be used to generate features that yield
improved performance when used in combination with the original non-discretized
data. Our results show that the best predictive performance is attained using a
combination of the original dataset with added features from a "standard"
supervised discretization algorithm and D-MIAT.
| [{'version': 'v1', 'created': 'Fri, 9 Feb 2018 13:00:44 GMT'}] | 2018-02-12 | [['Rosenfeld', 'Avi', ''], ['Illuz', 'Ron', ''], ['Gottesman', 'Dovid', ''], ['Last', 'Mark', '']] |
2303.04060 | Shenghong Ju | Yongchao Rao, C. Y. Zhao, Lei Shen, Shenghong Ju | Large modulation of thermal transport in 2D semimetal triphosphides by
doping-induced electron-phonon coupling | null | null | null | null | cond-mat.mtrl-sci cond-mat.mes-hall physics.app-ph physics.comp-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Recent studies demonstrate that novel 2D triphosphides semiconductors possess
high carrier mobility and promising thermoelectric performance, while the
carrier transport behaviors in 2D semimetal triphosphides have never been
elucidated before. Herein, using the first-principles calculations and
Boltzmann transport theory, we reveal that the electron-phonon coupling can be
significant and thus greatly inhibits the electron and phonon transport in
electron-doped BP3 and CP3. The intrinsic heat transport capacity of flexural
acoustic phonon modes in the wrinkle structure is largely suppressed arising
from the strong out-of-plane phonon scatterings, leading to the low phonon
thermal conductivity of 1.36 and 5.33 W/(mK) for BP3 and CP3 at room
temperature, and at high doping level, the enhanced scattering from electron
diminishes the phonon thermal conductivity by 71% and 54% for BP3 and CP3,
respectively. Instead, electron thermal conductivity shows nonmonotonic
variations with the increase of doping concentration, stemming from the
competition between electron-phonon scattering rates and electron group
velocity. It is worth noting that the heavy-doping effect induced strong
scattering from phonon largely suppresses the electron transport and reduces
electron thermal conductivity to the magnitude of phonon thermal conductivity.
This work sheds light on the electron and phonon transport properties in
semimetal triphosphides monolayer and provides an efficient avenue for the
modulation of carrier transport by doping-induced electron-phonon coupling
effect.
| [{'version': 'v1', 'created': 'Tue, 7 Mar 2023 17:09:07 GMT'}] | 2023-03-08 | [['Rao', 'Yongchao', ''], ['Zhao', 'C. Y.', ''], ['Shen', 'Lei', ''], ['Ju', 'Shenghong', '']] |
1611.05961 | Vinayaka Yaji | Vinayaka Yaji and Shalabh Bhatnagar | Stochastic Recursive Inclusions in two timescales with non-additive
iterate dependent Markov noise | null | null | null | null | cs.SY | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | In this paper we study the asymptotic behavior of a stochastic approximation
scheme on two timescales with set-valued drift functions and in the presence of
non-additive iterate-dependent Markov noise. It is shown that the recursion on
each timescale tracks the flow of a differential inclusion obtained by
averaging the set-valued drift function in the recursion with respect to a set
of measures which take into account both the averaging with respect to the
stationary distributions of the Markov noise terms and the interdependence
between the two recursions on different timescales. The framework studied in
this paper builds on the works of \it{A. Ramaswamy et al. }\rm by allowing for
the presence of non-additive iterate-dependent Markov noise. As an application,
we consider the problem of computing the optimum in a constrained convex
optimization problem where the objective function and the constraints are
averaged with respect to the stationary distribution of an underlying Markov
chain. Further the proposed scheme neither requires the differentiability of
the objective function nor the knowledge of the averaging measure.
| [{'version': 'v1', 'created': 'Fri, 18 Nov 2016 03:20:56 GMT'}] | 2016-11-21 | [['Yaji', 'Vinayaka', ''], ['Bhatnagar', 'Shalabh', '']] |
1711.04249 | Lianwen Jin | Sheng Zhang, Yuliang Liu, Lianwen Jin, Canjie Luo | Feature Enhancement Network: A Refined Scene Text Detector | 8 pages, 5 figures, 2 tables. This paper is accepted to appear in
AAAI 2018 | null | null | null | cs.CV | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | In this paper, we propose a refined scene text detector with a \textit{novel}
Feature Enhancement Network (FEN) for Region Proposal and Text Detection
Refinement. Retrospectively, both region proposal with \textit{only} $3\times
3$ sliding-window feature and text detection refinement with \textit{single
scale} high level feature are insufficient, especially for smaller scene text.
Therefore, we design a new FEN network with \textit{task-specific},
\textit{low} and \textit{high} level semantic features fusion to improve the
performance of text detection. Besides, since \textit{unitary}
position-sensitive RoI pooling in general object detection is unreasonable for
variable text regions, an \textit{adaptively weighted} position-sensitive RoI
pooling layer is devised for further enhancing the detecting accuracy. To
tackle the \textit{sample-imbalance} problem during the refinement stage, we
also propose an effective \textit{positives mining} strategy for efficiently
training our network. Experiments on ICDAR 2011 and 2013 robust text detection
benchmarks demonstrate that our method can achieve state-of-the-art results,
outperforming all reported methods in terms of F-measure.
| [{'version': 'v1', 'created': 'Sun, 12 Nov 2017 08:12:54 GMT'}] | 2017-11-15 | [['Zhang', 'Sheng', ''], ['Liu', 'Yuliang', ''], ['Jin', 'Lianwen', ''], ['Luo', 'Canjie', '']] |
0809.5195 | Yong Zhang | Yong Zhang, Chul Koo Kim, Kong-Ju-Bock Lee and Youngah Park | A Brownian Energy Depot Model of the Basilar Membrane Oscillation with a
Braking Mechanism | 8 pages, 5 figures | null | null | null | physics.bio-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | High auditory sensitivity, sharp frequency selectivity, and otoacoustic
emissions are signatures of active amplification of the cochlea. The human ear
can also detect very large amplitude sound without being damaged as long as the
exposed time is not too long. The outer hair cells are believed as the best
candidate for the active force generator of the mammalian cochlea. In this
paper, we propose a new model for the basilar membrane oscillation which
successfully describes both the active and the protective mechanisms by
employing an energy depot concept and a critical velocity of the basilar
membrane. One of the main results is that thermal noise in the absence of
external stimulation can be amplified leading to the spontaneous basilar
membrane oscillation. The compressive response of the basilar membrane at the
characteristic frequency and the dynamic response to the stimulation are
consistent with the experimental results as expected. Our model also shows the
nonlinear distortion of the response of the basilar membrane.
| [{'version': 'v1', 'created': 'Tue, 30 Sep 2008 13:18:23 GMT'}] | 2008-10-01 | [['Zhang', 'Yong', ''], ['Kim', 'Chul Koo', ''], ['Lee', 'Kong-Ju-Bock', ''], ['Park', 'Youngah', '']] |
1502.07631 | Kacper Kornet | Kacper Kornet and Alban Potherat | The decay of wall-bounded MHD turbulence at low Rm | submitted to JFM | null | null | null | physics.flu-dyn | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | We present Direct Numerical Simulations of decaying Magnetohydrodynamic (MHD)
turbulence at low magnetic Reynolds number. The domain considered is bounded by
periodic boundary conditions in the two directions perpendicular to the
magnetic field and by two plane Hartmann walls in the third direction. High
magnetic fields (Hartmann number of up to 896) are considered thanks to a
numerical method based on a spectral code using the eigenvectors of the
dissipation operator. It is found that the decay proceeds through two phases:
first, energy and integral lengthscales vary rapidly during a
two-dimensionalisation phase extending over about one Hartmann friction time.
During this phase, the evolution of the former appears significantly more
impeded by the presence of walls than that of the latter. Once the large scales
are close to quasi-two dimensional, the decay results from the competition of a
two-dimensional dynamics driven by dissipation in the Hartmann boundary layers
and the three-dimensional dynamics of smaller scales. In the later stages of
the decay, three-dimensionality subsists under the form of barrel-shaped
structures. A purely quasi-two dimensional decay dominated by friction in the
Hartmann layers is not reached, because of residual dissipation in the bulk.
However, this dissipation is not generated by the three-dimensionality that
subsists, but by residual viscous friction due to horizontal velocity
gradients. Also, the energy in the velocity component aligned with the magnetic
field is found to be strongly suppressed, as is transport in this direction.
This results reproduces the experimental findings of Kolesnikov & Tsinober
(1974).
| [{'version': 'v1', 'created': 'Thu, 26 Feb 2015 16:50:44 GMT'}, {'version': 'v2', 'created': 'Wed, 18 Mar 2015 17:33:58 GMT'}] | 2015-03-19 | [['Kornet', 'Kacper', ''], ['Potherat', 'Alban', '']] |