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liesvarastranta

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arxiv_cs_category

like 3

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

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

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

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

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

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

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

physics.optics

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

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

IEEE Journal of Biomedical and Health Informatics, vol. 27, no. 2, pp. 1036-1047, Feb. 2023

10.1109/JBHI.2022.3225425

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

physics.gen-ph

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

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

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: {xuequan.lu@deakin.edu.au})

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

physics.acc-ph math-ph math.MP nlin.PS physics.comp-ph

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

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

10.1364/AO.55.005449

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

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

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

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

Physical Review Letters 126, 147401 (2021)

10.1103/PhysRevLett.126.147401

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

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

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

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

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

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

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

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)

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

10.1103/PhysRevE.75.051125

physics.data-an physics.bio-ph

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

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

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)

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

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

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

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

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

physics.plasm-ph physics.acc-ph

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

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

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

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

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

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

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

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

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

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

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

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

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

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)

astro-ph physics.flu-dyn

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

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

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

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

10.1364/OE.21.027093

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

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

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

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

PLoS ONE 10(10): e0140397. (2015)

10.1371/journal.pone.0140397

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

astro-ph hep-ph physics.ao-ph

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

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

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

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

10.1134/S1063772918030034

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

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)

10.1145/3503161.3548368

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

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

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

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

10.1119/10.0004135

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

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

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

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

Phys. Rev. A 106, 063319(2022)

10.1103/PhysRevA.106.063319

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

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

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

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

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

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

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

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

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

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', '']]