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1705.02758
Xiu-Shen Wei
Xiu-Shen Wei, Chen-Lin Zhang, Yao Li, Chen-Wei Xie, Jianxin Wu, Chunhua Shen, Zhi-Hua Zhou
Deep Descriptor Transforming for Image Co-Localization
Accepted by IJCAI 2017
null
null
null
cs.CV cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Reusable model design becomes desirable with the rapid expansion of machine learning applications. In this paper, we focus on the reusability of pre-trained deep convolutional models. Specifically, different from treating pre-trained models as feature extractors, we reveal more treasures beneath convolutional layers, i.e., the convolutional activations could act as a detector for the common object in the image co-localization problem. We propose a simple but effective method, named Deep Descriptor Transforming (DDT), for evaluating the correlations of descriptors and then obtaining the category-consistent regions, which can accurately locate the common object in a set of images. Empirical studies validate the effectiveness of the proposed DDT method. On benchmark image co-localization datasets, DDT consistently outperforms existing state-of-the-art methods by a large margin. Moreover, DDT also demonstrates good generalization ability for unseen categories and robustness for dealing with noisy data.
2017-05-30T00:00:00
no_new_dataset
false
0.710729
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.03033
Leonardo Mondaini
Leonardo Mondaini
Towards a Field Theoretical Stochastic Model for Description of Tumour Growth
To appear in J. Appl. Math. Phys., 8 pages
Journal of Applied Mathematics and Physics, 5 (2017) 1092-1098
10.4236/jamp.2017.55095
null
physics.bio-ph q-bio.TO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We develop a field theory-inspired stochastic model for description of tumour growth based on an analogy with an SI epidemic model, where the susceptible individuals (S) would represent the healthy cells and the infected ones (I), the cancer cells. From this model, we obtain a curve describing the tumour volume as a function of time, which can be compared to available experimental data.
2017-05-30T00:00:00
no_new_dataset
false
0.70776
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.03978
Markus Kowalewski
Markus Kowalewski, Kochise Bennett, Shaul Mukamel
Monitoring Nonadiabatic Avoided Crossing Dynamics in Molecules by Ultrafast X-Ray Diffraction
null
Struct. Dynam. 4, 054101 (2017)
10.1063/1.4984241
null
physics.chem-ph physics.atm-clus
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We examine time-resolved X-ray diffraction from molecules in the gas phase which undergo nonadiabatic avoided-crossing dynamics involving strongly coupled electrons and nuclei. Several contributions to the signal are identified, representing (in decreasing strength) elastic scattering, contributions of the electronic coherences created by nonadiabatic couplings in the avoided crossing regime, and inelastic scattering. The former probes the charge density and delivers direct information on the evolving molecular geometry. The latter two contributions are weaker and carry spatial information of the transition charge densities (off-diagonal elements of the charge-density operator). Simulations are presented for the nonadiabatic harpooning process in the excited states of sodium fluoride.
2017-05-30T00:00:00
no_new_dataset
false
0.710167
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.07679
Ana Carpio
Bjorn Birnir, Ana Carpio, Elena Cebrian, Perfecto Vidal
Dynamic energy budget approach to evaluate antibiotic effects on biofilms
to appear in Communications in Nonlinear Science and Numerical Simulation
Communications in Nonlinear Science and Numerical Simulation 54, 70-83, 2018
10.1016/j.cnsns.2017.05.016
null
physics.bio-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Quantifying the action of antibiotics on biofilms is essential to devise therapies against chronic infections. Biofilms are bacterial communities attached to moist surfaces, sheltered from external aggressions by a polymeric matrix. Coupling a dynamic energy budget based description of cell metabolism to surrounding concentration fields, we are able to approximate survival curves measured for different antibiotics. We reproduce numerically stratified distributions of cell types within the biofilm and introduce ways to incorporate different resistance mechanisms. Qualitative predictions follow that are in agreement with experimental observations, such as higher survival rates of cells close to the substratum when employing antibiotics targeting active cells or enhanced polymer production when antibiotics are administered. The current computational model enables validation and hypothesis testing when developing therapies.
2017-05-30T00:00:00
no_new_dataset
false
0.707023
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.08111
Benjamin Gutierrez Becker
Benjam\'in Guti\'errez and Lo\"ic Peter and Tassilo Klein and Christian Wachinger
A Multi-Armed Bandit to Smartly Select a Training Set from Big Medical Data
MICCAI 2017 Proceedings
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
With the availability of big medical image data, the selection of an adequate training set is becoming more important to address the heterogeneity of different datasets. Simply including all the data does not only incur high processing costs but can even harm the prediction. We formulate the smart and efficient selection of a training dataset from big medical image data as a multi-armed bandit problem, solved by Thompson sampling. Our method assumes that image features are not available at the time of the selection of the samples, and therefore relies only on meta information associated with the images. Our strategy simultaneously exploits data sources with high chances of yielding useful samples and explores new data regions. For our evaluation, we focus on the application of estimating the age from a brain MRI. Our results on 7,250 subjects from 10 datasets show that our approach leads to higher accuracy while only requiring a fraction of the training data.
2017-05-30T00:00:00
no_new_dataset
false
0.711637
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.08245
Vincent Huang
Vincent Huang, Tobias Ley, Martha Vlachou-Konchylaki, Wenfeng Hu
Enhanced Experience Replay Generation for Efficient Reinforcement Learning
null
null
null
null
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Applying deep reinforcement learning (RL) on real systems suffers from slow data sampling. We propose an enhanced generative adversarial network (EGAN) to initialize an RL agent in order to achieve faster learning. The EGAN utilizes the relation between states and actions to enhance the quality of data samples generated by a GAN. Pre-training the agent with the EGAN shows a steeper learning curve with a 20% improvement of training time in the beginning of learning, compared to no pre-training, and an improvement compared to training with GAN by about 5% with smaller variations. For real time systems with sparse and slow data sampling the EGAN could be used to speed up the early phases of the training process.
2017-05-30T00:00:00
no_new_dataset
false
0.709987
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.08499
Yonatan Geifman
Ran El-Yaniv, Yonatan Geifman, Yair Wiener
The Prediction Advantage: A Universally Meaningful Performance Measure for Classification and Regression
null
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We introduce the Prediction Advantage (PA), a novel performance measure for prediction functions under any loss function (e.g., classification or regression). The PA is defined as the performance advantage relative to the Bayesian risk restricted to knowing only the distribution of the labels. We derive the PA for well-known loss functions, including 0/1 loss, cross-entropy loss, absolute loss, and squared loss. In the latter case, the PA is identical to the well-known R-squared measure, widely used in statistics. The use of the PA ensures meaningful quantification of prediction performance, which is not guaranteed, for example, when dealing with noisy imbalanced classification problems. We argue that among several known alternative performance measures, PA is the best (and only) quantity ensuring meaningfulness for all noise and imbalance levels.
2017-05-30T00:00:00
no_new_dataset
false
0.711639
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.08921
Efr\'en Cruz Cort\'es
Efr\'en Cruz Cort\'es, Clayton Scott
Consistent Kernel Density Estimation with Non-Vanishing Bandwidth
17 pages, updated abstract
null
null
null
stat.ML cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Consistency of the kernel density estimator requires that the kernel bandwidth tends to zero as the sample size grows. In this paper we investigate the question of whether consistency is possible when the bandwidth is fixed, if we consider a more general class of weighted KDEs. To answer this question in the affirmative, we introduce the fixed-bandwidth KDE (fbKDE), obtained by solving a quadratic program, and prove that it consistently estimates any continuous square-integrable density. We also establish rates of convergence for the fbKDE with radial kernels and the box kernel under appropriate smoothness assumptions. Furthermore, in an experimental study we demonstrate that the fbKDE compares favorably to the standard KDE and the previously proposed variable bandwidth KDE.
2017-05-30T00:00:00
no_new_dataset
false
0.710974
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.08991
Shuang Liu
Shuang Liu, Olivier Bousquet, Kamalika Chaudhuri
Approximation and Convergence Properties of Generative Adversarial Learning
null
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Generative adversarial networks (GAN) approximate a target data distribution by jointly optimizing an objective function through a "two-player game" between a generator and a discriminator. Despite their empirical success, however, two very basic questions on how well they can approximate the target distribution remain unanswered. First, it is not known how restricting the discriminator family affects the approximation quality. Second, while a number of different objective functions have been proposed, we do not understand when convergence to the global minima of the objective function leads to convergence to the target distribution under various notions of distributional convergence. In this paper, we address these questions in a broad and unified setting by defining a notion of adversarial divergences that includes a number of recently proposed objective functions. We show that if the objective function is an adversarial divergence with some additional conditions, then using a restricted discriminator family has a moment-matching effect. Additionally, we show that for objective functions that are strict adversarial divergences, convergence in the objective function implies weak convergence, thus generalizing previous results.
2017-05-30T00:00:00
no_new_dataset
false
0.710458
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.09225
Fabrice Lemoult
Simon Yves, Romain Fleury, Thomas Berthelot, Mathias Fink, Fabrice Lemoult, Geoffroy Lerosey
Crystalline metamaterials for topological properties at subwavelength scales
null
null
10.1038/ncomms16023
null
physics.optics
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The exciting discovery of topological condensed matter systems has lately triggered a search for their photonic analogs, motivated by the possibility of robust backscattering-immune light transport. However, topological photonic phases have so far only been observed in photonic crystals and waveguide arrays, which are inherently physically wavelength scaled, hindering their application in compact subwavelength systems. In this letter, we tackle this problem by patterning the deep subwavelength resonant elements of metamaterials onto specific lattices, and create crystalline metamaterials that can develop complex nonlocal properties due to multiple scattering, despite their very subwavelength spatial scale that usually implies to disregard their structure. These spatially dispersive systems can support subwavelength topological phases, as we demonstrate at microwaves by direct field mapping. Our approach gives a straightforward tabletop platform for the study of photonic topological phases, and allows to envision applications benefiting the compactness of metamaterials and the amazing potential of topological insulators.
2017-05-30T00:00:00
no_new_dataset
false
0.712115
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.09388
Ning Wang
Ning C. Wang, Enrique A. Carrion, Maryann C. Tung, Eric Pop
Reducing Graphene Device Variability with Yttrium Sacrificial Layers
null
null
10.1063/1.4984090
null
physics.app-ph cond-mat.mes-hall cond-mat.mtrl-sci
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Graphene technology has made great strides since the material was isolated more than a decade ago. However, despite improvements in growth quality and numerous 'hero' devices, challenges of uniformity remain, restricting large-scale development of graphene-based technologies. Here we investigate and reduce the variability of graphene transistors by studying the effects of contact metals (with and without Ti layer), resist, and yttrium (Y) sacrificial layers during the fabrication of hundreds of devices. We find that with optical photolithography, residual resist and process contamination is unavoidable, ultimately limiting device performance and yield. However, using Y sacrificial layers to isolate the graphene from processing conditions improves the yield (from 73% to 97%), average device performance (three-fold increase of mobility, 58% lower contact resistance), and the device-to-device variability (standard deviation of Dirac voltage reduced by 20%). In contrast to other sacrificial layer techniques, removal of the Y sacrificial layer with HCl does not harm surrounding materials, simplifying large-scale graphene fabrication.
2017-05-30T00:00:00
no_new_dataset
false
0.712362
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.09658
David Bravo Bergu\~no
David Bravo-Bergu\~no, Riccardo Mereu, Robert Bruce Vogelaar, Fabio Inzoli
Fluid-dynamics in the Borexino Neutrino Detector: behavior of a pseudo-stably-stratified, near-equilibrium closed system under asymmetrical, changing boundary conditions
14 pages, 6 figures, 1 table
null
null
null
physics.ins-det hep-ex
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The strategy to install Borexino's Thermal Monitoring and Management System (BTMMS) successfully stabilized the thermal environment inside the Borexino neutrino observatory, which is understood to be a necessary step to improve and minimize radioactive background contamination inside the active volume of the detector, allowing for it to achieve better sensitivity in the regions of interest. Two-dimensional numerical simulations to achieve a proper understanding of Borexino's fluid-dynamics were developed and optimized for different regions and periods of interest, focusing on the most critical effects that were identified as influencing background concentrations. Literature experimental case studies were reproduced to benchmark the method and settings, and a Borexino-specific benchmark was constructed in order to validate the model's thermal transport. Finally, fully-convective models were implemented to understand general and specific fluid motions impacting the active detector volume.
2017-05-30T00:00:00
no_new_dataset
false
0.711001
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.09665
Cristian Danescu-Niculescu-Mizil
Justine Zhang and William L. Hamilton and Cristian Danescu-Niculescu-Mizil and Dan Jurafsky and Jure Leskovec
Community Identity and User Engagement in a Multi-Community Landscape
10 page, 3 figures, To appear in the Proceedings of the 11th International Conference On Web And Social Media, ICWSM 2017; this version has subtle differences with the proceedings version, including an introductory quote
null
null
null
cs.SI cs.CL cs.CY physics.soc-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A community's identity defines and shapes its internal dynamics. Our current understanding of this interplay is mostly limited to glimpses gathered from isolated studies of individual communities. In this work we provide a systematic exploration of the nature of this relation across a wide variety of online communities. To this end we introduce a quantitative, language-based typology reflecting two key aspects of a community's identity: how distinctive, and how temporally dynamic it is. By mapping almost 300 Reddit communities into the landscape induced by this typology, we reveal regularities in how patterns of user engagement vary with the characteristics of a community. Our results suggest that the way new and existing users engage with a community depends strongly and systematically on the nature of the collective identity it fosters, in ways that are highly consequential to community maintainers. For example, communities with distinctive and highly dynamic identities are more likely to retain their users. However, such niche communities also exhibit much larger acculturation gaps between existing users and newcomers, which potentially hinder the integration of the latter. More generally, our methodology reveals differences in how various social phenomena manifest across communities, and shows that structuring the multi-community landscape can lead to a better understanding of the systematic nature of this diversity.
2017-05-30T00:00:00
no_new_dataset
false
0.708077
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.09683
Bo Zhang
Bo Zhang, Jie Kong, Mudi Chen, Ke Qiao, Lorin S. Matthews, Truell W. Hyde
Dust cluster spin in complex (dusty) plasmas
7 pages, 7 figures, 2 tables
null
null
null
physics.plasm-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The spontaneous rotation of small dust clusters confined inside a cubical glass box in the sheath of a complex plasma was observed in experiment. Due to strong coupling between the dust particles, these clusters behave like a rigid-body where cluster rotation is contingent upon their configuration and symmetry. By evaluating the effects of distinct contributing forces, it is postulated that the rotation observed is driven by the net torque exerted on the cluster by the ion wake force. The configuration and symmetry of a cluster determines whether the net torque induced by the ion wake force is nonzero, in turn leading to cluster rotation. A COPTIC (Cartesian mesh, oblique boundary, particles and thermals in cell) simulation is employed to obtain the ion wake potential providing a theoretical model of cluster rotation which includes both the ion wake force and neutral drag and predicts rotation rates and direction in agreement with experimental results. These results are then used to diagnose the ion flow within the box.
2017-05-30T00:00:00
no_new_dataset
false
0.71236
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.09691
Vitoriano Ruas
Vitoriano Ruas
One-parameter tetrahedral mesh generation for spheroids
The description of the method studied in this work was first published in Portuguese in Revista Brasileira de Computa\c{c}\~ao, 4-3 (1985), 165-178. It was also published in Proc. Int. Conf. Numerical Grid Generation in CFD, Landshut, Germany, 1986, C. Taylor ed., Pineridge Press, Swansea, UK, p. 71-82, 1986. However method's implementation and assessment by the author took place only in 2017
null
null
null
cs.CG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper deals with a simple and straightforward procedure for automatic generation of finite-element or finite-volume meshes of spheroidal domains, consisting of tetrahedra. Besides the equation of the boundary, the generated meshes depend only on an integer parameter, whose value is associated with the degree of refinement. More specifically the procedure applies to the case where the boundary of a curved three-dimensional domain not so irregular can be expressed in spherical coordinates, with origin placed at a suitable location in its interior. An optimal numbering of mesh elements and nodes can be accomplished very easily. Several examples indicate that the generated meshes form a quasi-uniform family of partitions, as the corresponding value of the integer parameter increases, as long as the domain is not too distorted.
2017-05-30T00:00:00
no_new_dataset
false
0.710534
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.09694
Petar Petrov
Petar N. Petrov, Yoav Shechtman, W. E. Moerner
Measurement-based estimation of global pupil functions in 3D localization microscopy
14 pages, 4 figures. This paper was published in Optics Express and is made available as an electronic reprint with the permission of OSA. The paper can be found at the following URL on the OSA website: https://doi.org/10.1364/OE.25.007945
Optics Express, Vol. 25, Issue 7, pp. 7945-7959 (2017)
10.1364/OE.25.007945
null
physics.optics physics.ins-det
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We report the use of a phase retrieval procedure based on maximum likelihood estimation (MLE) to produce an improved, experimentally calibrated model of a point spread function (PSF) for use in three-dimensional (3D) localization microscopy experiments. The method estimates a global pupil phase function (which includes both the PSF and system aberrations) over the full axial range from a simple calibration scan. The pupil function is used to refine the PSF model and hence enable superior localizations from experimental data. To demonstrate the utility of the procedure, we apply it to experimental data acquired with a microscope employing a tetrapod PSF with a 6 micron axial range. The phase-retrieved model demonstrates significant improvements in both accuracy and precision of 3D localizations relative to the model based on scalar diffraction theory. The localization precision of the phase-retrieved model is shown to be near the limits imposed by estimation theory, and the reproducibility of the procedure is characterized and discussed. Code which performs the phase retrieval algorithm is provided.
2017-05-30T00:00:00
no_new_dataset
false
0.710606
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.09699
Geoffrey Hutchison
Xinfeng Quan and Geoffrey R. Hutchison
Single Molecule Ferroelectrics via Conformational Inversion: An Electronic Structure Investigation
22 pages, 7 figures plus supporting information (25 pages total)
null
null
null
physics.app-ph cond-mat.mtrl-sci
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Ferroelectric materials can switch their polarization in response to an applied electric field. In this work, ferroelectricity at the single molecule level is proposed and investigated using density functional theory (DFT) calculations. Several bowl-shaped molecules, both synthetically reported and hypothetically proposed, are shown to invert polarization in response to external applied electric fields. Such a polarization inversion relies on the conformational change of a single molecule, unlike its traditional counterparts of which ferroelectricity originates from the switch of an asymmetrical polar unit cell in inorganic crystals, or from the polar polymer chain rotation of ferroelectric polymers. We discuss both structural and functional group factors in determining the inversion electric field and the design rules for good single molecule ferroelectrics. A conceptual multistate ferroelectric model is discussed for single molecule ferroelectrics.
2017-05-30T00:00:00
no_new_dataset
false
0.712943
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.09701
Keith Smith
Peter Macko, Xiongzi Ge, John Haskins Jr., James Kelley, David Slik, Keith A. Smith, Maxim G. Smith
SMORE: A Cold Data Object Store for SMR Drives (Extended Version)
13 pages, 8 figures, full version of 6 page paper published at MSST 2017
null
null
null
cs.OS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Shingled magnetic recording (SMR) increases the capacity of magnetic hard drives, but it requires that each zone of a disk be written sequentially and erased in bulk. This makes SMR a good fit for workloads dominated by large data objects with limited churn. To explore this possibility, we have developed SMORE, an object storage system designed to reliably and efficiently store large, seldom-changing data objects on an array of host-managed or host-aware SMR disks. SMORE uses a log-structured approach to accommodate the constraint that all writes to an SMR drive must be sequential within large shingled zones. It stripes data across zones on separate disks, using erasure coding to protect against drive failure. A separate garbage collection thread reclaims space by migrating live data out of the emptiest zones so that they can be trimmed and reused. An index stored on flash and backed up to the SMR drives maps object identifiers to on-disk locations. SMORE interleaves log records with object data within SMR zones to enable index recovery after a system crash (or failure of the flash device) without any additional logging mechanism. SMORE achieves full disk bandwidth when ingesting data---with a variety of object sizes---and when reading large objects. Read performance declines for smaller object sizes where inter- object seek time dominates. With a worst-case pattern of random deletions, SMORE has a write amplification (not counting RAID parity) of less than 2.0 at 80% occupancy. By taking an index snapshot every two hours, SMORE recovers from crashes in less than a minute. More frequent snapshots allow faster recovery.
2017-05-30T00:00:00
no_new_dataset
false
0.698049
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.09710
Marcos Villagra
Marcos Villagra
A Block-Sensitivity Lower Bound for Quantum Testing Hamming Distance
Short note, 3 pages
null
null
null
cs.CC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The Gap-Hamming distance problem is the promise problem of deciding if the Hamming distance $h$ between two strings of length $n$ is greater than $a$ or less than $b$, where the gap $g=|a-b|\geq 1$ and $a$ and $b$ could depend on $n$. In this short note, we give a lower bound of $\Omega( \sqrt{n/g})$ on the quantum query complexity of computing the Gap-Hamming distance between two given strings of lenght $n$. The proof is a combinatorial argument based on block sensitivity and a reduction from a threshold function.
2017-05-30T00:00:00
no_new_dataset
false
0.706869
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.09711
Ulises Arturo P\'erez Ventura
Ulises P\'erez-Ventura and Leonid Fridman
Is It Reasonable to Substitute Discontinuous SMC by Continuous HOSMC?
7 pages, 5 figures
null
null
null
cs.SY
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Professor Utkin in his discussion paper proposed an example showing that the amplitude of chattering caused by the presence of parasitic dynamics in systems governed by First-Order Sliding-Mode Control (FOSMC) is lower than the obtained using Super-Twisting Algorithm (STA). This example served to motivate this research reconsidering the problem of comparison of chattering magnitude in systems governed by FOSMC that produces a discontinuous control signal and by STA that produces a continuous one, using Harmonic Balance (HB) methodology. With this aim the Averaged Power (AP) criteria for chattering measurements is revisited. The STA gains are redesigned to minimize amplitude or AP of oscillations predicted by HB. The comparison of the chattering produced by FOSMC and STA with redesigned gains is analyzed taking into account their amplitudes, frequencies and values of AP allowing to conclude that: (a) for any value of upperbound of disturbance and Actuator Time Constant (ATC) there exist a bounded disturbance for which the amplitude and AP of chattering produced by FOSMC is lower than the caused by STA; (b) if the upperbound of disturbance and upperbound of time-derivative disturbance are given, then for all sufficiently small values of ATC the amplitude of chattering and AP produced by STA will be smaller than the caused by FOSMC; (c) critical values of ATC are predicted by HB for which the parameters, amplitude of chattering and AP, produced by FOSMC and STA are the same. Also the frequency of self-exited oscillations caused by FOSMC is always grater than the produced by STA.
2017-05-30T00:00:00
no_new_dataset
false
0.7116
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.09713
You Chen
You Chen, Mayur B. Patel, Candace D. McNaughton, Bradley A. Malin
A Data-Driven Analysis of the Influence of Care Coordination on Trauma Outcome
25 pages, 1 figure, 2 tables
null
null
null
cs.CY
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
OBJECTIVE: To test the hypothesis that variation in care coordination is related to LOS. DESIGN We applied a spectral co-clustering methodology to simultaneously infer groups of patients and care coordination patterns, in the form of interaction networks of health care professionals, from electronic medical record (EMR) utilization data. The care coordination pattern for each patient group was represented by standard social network characteristics and its relationship with hospital LOS was assessed via a negative binomial regression with a 95% confidence interval. SETTING AND PATIENTS This study focuses on 5,588 adult patients hospitalized for trauma at the Vanderbilt University Medical Center. The EMRs were accessed by healthcare professionals from 179 operational areas during 158,467 operational actions. MAIN OUTCOME MEASURES: Hospital LOS for trauma inpatients, as an indicator of care coordination efficiency. RESULTS: Three general types of care coordination patterns were discovered, each of which was affiliated with a specific patient group. The first patient group exhibited the shortest hospital LOS and was managed by a care coordination pattern that involved the smallest number of operational areas (102 areas, as opposed to 125 and 138 for the other patient groups), but exhibited the largest number of collaborations between operational areas (e.g., an average of 27.1 connections per operational area compared to 22.5 and 23.3 for the other two groups). The hospital LOS for the second and third patient groups was 14 hours (P = 0.024) and 10 hours (P = 0.042) longer than the first patient group, respectively.
2017-05-30T00:00:00
no_new_dataset
false
0.71079
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.09724
Iroro Orife
Shane Walker, Morten Pedersen, Iroro Orife and Jason Flaks
Semi-Supervised Model Training for Unbounded Conversational Speech Recognition
null
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
For conversational large-vocabulary continuous speech recognition (LVCSR) tasks, up to about two thousand hours of audio is commonly used to train state of the art models. Collection of labeled conversational audio however, is prohibitively expensive, laborious and error-prone. Furthermore, academic corpora like Fisher English (2004) or Switchboard (1992) are inadequate to train models with sufficient accuracy in the unbounded space of conversational speech. These corpora are also timeworn due to dated acoustic telephony features and the rapid advancement of colloquial vocabulary and idiomatic speech over the last decades. Utilizing the colossal scale of our unlabeled telephony dataset, we propose a technique to construct a modern, high quality conversational speech training corpus on the order of hundreds of millions of utterances (or tens of thousands of hours) for both acoustic and language model training. We describe the data collection, selection and training, evaluating the results of our updated speech recognition system on a test corpus of 7K manually transcribed utterances. We show relative word error rate (WER) reductions of {35%, 19%} on {agent, caller} utterances over our seed model and 5% absolute WER improvements over IBM Watson STT on this conversational speech task.
2017-05-30T00:00:00
new_dataset
true
0.691153
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.09728
Wufeng Xue
Wufeng Xue, Ilanit Ben Nachum, Sachin Pandey, James Warrington, Stephanie Leung, and Shuo Li
Direct Estimation of Regional Wall Thicknesses via Residual Recurrent Neural Network
To appear as an oral paper in IPMI2017
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Accurate estimation of regional wall thicknesses (RWT) of left ventricular (LV) myocardium from cardiac MR sequences is of significant importance for identification and diagnosis of cardiac disease. Existing RWT estimation still relies on segmentation of LV myocardium, which requires strong prior information and user interaction. No work has been devoted into direct estimation of RWT from cardiac MR images due to the diverse shapes and structures for various subjects and cardiac diseases, as well as the complex regional deformation of LV myocardium during the systole and diastole phases of the cardiac cycle. In this paper, we present a newly proposed Residual Recurrent Neural Network (ResRNN) that fully leverages the spatial and temporal dynamics of LV myocardium to achieve accurate frame-wise RWT estimation. Our ResRNN comprises two paths: 1) a feed forward convolution neural network (CNN) for effective and robust CNN embedding learning of various cardiac images and preliminary estimation of RWT from each frame itself independently, and 2) a recurrent neural network (RNN) for further improving the estimation by modeling spatial and temporal dynamics of LV myocardium. For the RNN path, we design for cardiac sequences a Circle-RNN to eliminate the effect of null hidden input for the first time-step. Our ResRNN is capable of obtaining accurate estimation of cardiac RWT with Mean Absolute Error of 1.44mm (less than 1-pixel error) when validated on cardiac MR sequences of 145 subjects, evidencing its great potential in clinical cardiac function assessment.
2017-05-30T00:00:00
no_new_dataset
false
0.70931
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.09748
Mohammad Mozaffari
Mohammad Mozaffari, Walid Saad, Mehdi Bennis, and Merouane Debbah
Optimal Transport Theory for Cell Association in UAV-Enabled Cellular Networks
Accepted in IEEE Communications Letters
null
null
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, a novel framework for delay-optimal cell association in unmanned aerial vehicle (UAV)-enabled cellular networks is proposed. In particular, to minimize the average network delay under any arbitrary spatial distribution of the ground users, the optimal cell partitions of UAVs and terrestrial base stations (BSs) are determined. To this end, using the powerful mathematical tools of optimal transport theory, the existence of the solution to the optimal cell association problem is proved and the solution space is completely characterized. The analytical and simulation results show that the proposed approach yields substantial improvements of the average network delay.
2017-05-30T00:00:00
no_new_dataset
false
0.710104
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.09751
Ying Chen
Ying Chen, Rongpeng Li, Zhifeng Zhao, and Honggang Zhang
On the Capacity of Fractal Wireless Networks With Direct Social Interactions
null
null
null
null
cs.IT math.IT
http://creativecommons.org/licenses/by-nc-sa/4.0/
The capacity of a fractal wireless network with direct social interactions is studied in this paper. Specifically, we mathematically formulate the self-similarity of a fractal wireless network by a power-law degree distribution $ P(k) $, and we capture the connection feature between two nodes with degree $ k_{1} $ and $ k_{2} $ by a joint probability distribution $ P(k_{1},k_{2}) $. It is proved that if the source node communicates with one of its direct contacts randomly, the maximum capacity is consistent with the classical result $ \Theta\left(\frac{1}{\sqrt{n\log n}}\right) $ achieved by Kumar \cite{Gupta2000The}. On the other hand, if the two nodes with distance $ d $ communicate according to the probability $ d^{-\beta} $, the maximum capacity can reach up to $ \Theta\left(\frac{1}{\log n}\right) $, which exhibits remarkable improvement compared with the well-known result in \cite{Gupta2000The}.
2017-05-30T00:00:00
no_new_dataset
false
0.711149
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.09755
Andrew Landgraf
Andrew J. Landgraf, Jeremy Bellay
word2vec Skip-Gram with Negative Sampling is a Weighted Logistic PCA
null
null
null
null
cs.CL stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We show that the skip-gram formulation of word2vec trained with negative sampling is equivalent to a weighted logistic PCA. This connection allows us to better understand the objective, compare it to other word embedding methods, and extend it to higher dimensional models.
2017-05-30T00:00:00
no_new_dataset
false
0.712612
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.09759
Chen Feng
Zhiding Yu, Chen Feng, Ming-Yu Liu, Srikumar Ramalingam
CASENet: Deep Category-Aware Semantic Edge Detection
Accepted to CVPR 2017
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Boundary and edge cues are highly beneficial in improving a wide variety of vision tasks such as semantic segmentation, object recognition, stereo, and object proposal generation. Recently, the problem of edge detection has been revisited and significant progress has been made with deep learning. While classical edge detection is a challenging binary problem in itself, the category-aware semantic edge detection by nature is an even more challenging multi-label problem. We model the problem such that each edge pixel can be associated with more than one class as they appear in contours or junctions belonging to two or more semantic classes. To this end, we propose a novel end-to-end deep semantic edge learning architecture based on ResNet and a new skip-layer architecture where category-wise edge activations at the top convolution layer share and are fused with the same set of bottom layer features. We then propose a multi-label loss function to supervise the fused activations. We show that our proposed architecture benefits this problem with better performance, and we outperform the current state-of-the-art semantic edge detection methods by a large margin on standard data sets such as SBD and Cityscapes.
2017-05-30T00:00:00
no_new_dataset
false
0.708631
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.09761
Mohammadhussein Rafieisakhaei
Dan Yu, Mohammadhussein Rafieisakhaei and Suman Chakravorty
Stochastic Feedback Control of Systems with Unknown Nonlinear Dynamics
7 pages, 7 figures, submitted to 56th IEEE Conference on Decision and Control (CDC), 2017
null
null
null
cs.SY cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper studies the stochastic optimal control problem for systems with unknown dynamics. First, an open-loop deterministic trajectory optimization problem is solved without knowing the explicit form of the dynamical system. Next, a Linear Quadratic Gaussian (LQG) controller is designed for the nominal trajectory-dependent linearized system, such that under a small noise assumption, the actual states remain close to the optimal trajectory. The trajectory-dependent linearized system is identified using input-output experimental data consisting of the impulse responses of the nominal system. A computational example is given to illustrate the performance of the proposed approach.
2017-05-30T00:00:00
no_new_dataset
false
0.70898
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.09765
Yue Wu Dr.
Yue Wu, Wael AbdAlmageed, Prem Natarajan
Deep Matching and Validation Network -- An End-to-End Solution to Constrained Image Splicing Localization and Detection
9 pages, 10 figures
null
null
null
cs.CV cs.CR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Image splicing is a very common image manipulation technique that is sometimes used for malicious purposes. A splicing detec- tion and localization algorithm usually takes an input image and produces a binary decision indicating whether the input image has been manipulated, and also a segmentation mask that corre- sponds to the spliced region. Most existing splicing detection and localization pipelines suffer from two main shortcomings: 1) they use handcrafted features that are not robust against subsequent processing (e.g., compression), and 2) each stage of the pipeline is usually optimized independently. In this paper we extend the formulation of the underlying splicing problem to consider two input images, a query image and a potential donor image. Here the task is to estimate the probability that the donor image has been used to splice the query image, and obtain the splicing masks for both the query and donor images. We introduce a novel deep convolutional neural network architecture, called Deep Matching and Validation Network (DMVN), which simultaneously localizes and detects image splicing. The proposed approach does not depend on handcrafted features and uses raw input images to create deep learned representations. Furthermore, the DMVN is end-to-end op- timized to produce the probability estimates and the segmentation masks. Our extensive experiments demonstrate that this approach outperforms state-of-the-art splicing detection methods by a large margin in terms of both AUC score and speed.
2017-05-30T00:00:00
no_new_dataset
false
0.711248
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.09766
Hazim Shakhatreh
Hazim Shakhatreh, Abdallah Khreishah, Jacob Chakareski, Haythem Bany Salameh, and Issa Khalil
On The Continuous Coverage Problem for a Swarm of UAVs
6 pages, 6 figures
null
10.1109/SARNOF.2016.7846742
null
cs.IT math.IT
http://creativecommons.org/licenses/by/4.0/
Unmanned aerial vehicles (UAVs) can be used to provide wireless network and remote surveillance coverage for disaster-affected areas. During such a situation, the UAVs need to return periodically to a charging station for recharging, due to their limited battery capacity. We study the problem of minimizing the number of UAVs required for a continuous coverage of a given area, given the recharging requirement. We prove that this problem is NP-complete. Due to its intractability, we study partitioning the coverage graph into cycles that start at the charging station. We first characterize the minimum number of UAVs to cover such a cycle based on the charging time, the traveling time, and the number of subareas to be covered by the cycle. Based on this analysis, we then develop an efficient algorithm, the cycles with limited energy algorithm. The straightforward method to continuously cover a given area is to split it into N subareas and cover it by N cycles using N additional UAVs. Our simulation results examine the importance of critical system parameters: the energy capacity of the UAVs, the number of subareas in the covered area, and the UAV charging and traveling times.We demonstrate that the cycles with limited energy algorithm requires 69%-94% fewer additional UAVs relative to the straightforward method, as the energy capacity of the UAVs is increased, and 67%-71% fewer additional UAVs, as the number of subareas is increased.
2017-05-30T00:00:00
no_new_dataset
false
0.711264
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.09769
Hazim Shakhatreh
Hazim Shakhatreh, Abdallah Khreishah, Ayoub Alsarhan, Issa Khalil, Ahmad Sawalmeh, and Noor Shamsiah Othman
Efficient 3D Placement of a UAV Using Particle Swarm Optimization
6 pages, 7 figures
null
10.1109/IACS.2017.7921981
null
cs.IT math.IT
http://creativecommons.org/licenses/by/4.0/
Unmanned aerial vehicles (UAVs) can be used as aerial wireless base stations when cellular networks go down. Prior studies on UAV-based wireless coverage typically consider an Air-to-Ground path loss model, which assumes that the users are outdoor and they are located on a 2D plane. In this paper, we propose using a single UAV to provide wireless coverage for indoor users inside a high-rise building under disaster situations (such as earthquakes or floods), when cellular networks are down. We assume that the locations of indoor users are uniformly distributed in each floor and we propose a particle swarm optimization algorithm to find an efficient 3D placement of a UAV that minimizes the total transmit power required to cover the indoor users.
2017-05-30T00:00:00
no_new_dataset
false
0.708753
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.09770
Hazim Shakhatreh
Hazim Shakhatreh, Abdallah Khreishah, and Bo Ji
Providing Wireless Coverage to High-rise Buildings Using UAVs
6 pages, 5 figures
null
null
null
cs.IT math.IT
http://creativecommons.org/licenses/by/4.0/
Unmanned aerial vehicles (UAVs) can be used as aerial wireless base stations when cellular networks go down. Prior studies on UAV-based wireless coverage typically consider an Air-to-Ground path loss model, which assumes that the users are outdoor and they are located on a 2D plane. In this paper, we propose using a single UAV to provide wireless coverage for indoor users inside a high-rise building under disaster situations (such as earthquakes or floods), when cellular networks are down. First, we present a realistic Outdoor-Indoor path loss model and describe the tradeoff introduced by this model. Then, we study the problem of efficient UAV placement, where the objective is to minimize the total transmit power required to cover the entire high-rise building. The formulated problem is non-convex and is generally difficult to solve. To that end, we consider two cases of practical interest and provide the efficient solutions to the formulated problem under these cases. In the first case, we aim to find the minimum transmit power such that an indoor user with the maximum path loss can be covered. In the second case, we assume that the locations of indoor users are symmetric across the dimensions of each floor.
2017-05-30T00:00:00
no_new_dataset
false
0.708972
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.09772
Hazim Shakhatreh
Hazim Shakhatreh and Abdallah Khreishah
Maximizing Indoor Wireless Coverage Using UAVs Equipped with Directional Antennas
19 pages, 17 figures
null
null
null
cs.IT math.IT
http://creativecommons.org/licenses/by/4.0/
Unmanned aerial vehicles (UAVs) can be used to provide wireless coverage during emergency cases where each UAV serves as an aerial wireless base station when the cellular network goes down. They can also be used to supplement the ground base station in order to provide better coverage and higher data rates for the users. In this paper, we aim to maximize the indoor wireless coverage using UAVs equipped with directional antennas. We study the case that the UAVs are using one channel, thus in order to maximize the total indoor wireless coverage, we avoid any overlapping in their coverage volumes. We present two methods to place the UAVs; providing wireless coverage from one building side and from two building sides. In the first method, we utilize circle packing theory to determine the 3-D locations of the UAVs in a way that the total coverage area is maximized. In the second method, we place the UAVs in front of two building sides and efficiently arrange the UAVs in alternating upsidedown arrangements. We show that the upside-down arrangements problem can be transformed from 3D to 2D and based on that we present an efficient algorithm to solve the problem. Our results show that the upside-down arrangements of UAVs, can improve the maximum total coverage by 100% compared to providing wireless coverage from one building side.
2017-05-30T00:00:00
no_new_dataset
false
0.711593
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.09785
Ankit Dhall
Ankit Dhall, Kunal Chelani, Vishnu Radhakrishnan, K.M. Krishna
LiDAR-Camera Calibration using 3D-3D Point correspondences
null
null
null
null
cs.RO cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
With the advent of autonomous vehicles, LiDAR and cameras have become an indispensable combination of sensors. They both provide rich and complementary data which can be used by various algorithms and machine learning to sense and make vital inferences about the surroundings. We propose a novel pipeline and experimental setup to find accurate rigid-body transformation for extrinsically calibrating a LiDAR and a camera. The pipeling uses 3D-3D point correspondences in LiDAR and camera frame and gives a closed form solution. We further show the accuracy of the estimate by fusing point clouds from two stereo cameras which align perfectly with the rotation and translation estimated by our method, confirming the accuracy of our method's estimates both mathematically and visually. Taking our idea of extrinsic LiDAR-camera calibration forward, we demonstrate how two cameras with no overlapping field-of-view can also be calibrated extrinsically using 3D point correspondences. The code has been made available as open-source software in the form of a ROS package, more information about which can be sought here: https://github.com/ankitdhall/lidar_camera_calibration .
2017-05-30T00:00:00
no_new_dataset
false
0.711518
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.09789
Rivera Mariano
Mariano Rivera (CIMAT)
Half-quadratic transportation problems
null
null
null
null
math.OC cs.DS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present a primal--dual memory efficient algorithm for solving a relaxed version of the general transportation problem. Our approach approximates the original cost function with a differentiable one that is solved as a sequence of weighted quadratic transportation problems. The new formulation allows us to solve differentiable, non-- convex transportation problems.
2017-05-30T00:00:00
no_new_dataset
false
0.707682
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.09796
Cristina Turcu
Valentin Vlad, Adrian Graur, Cristina Elena Turcu, Calin Ciufudean
Studiu de caz privind utilizarea modelelor IEC 61499 in controlul holonic de nivel inalt
7th International Conference on Microelectronics and Computer Science, Chisinau, Republic of Moldova, September 22-24, 2011
null
null
null
cs.SY
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper presents various solutions for applying the specifications of the IEC 61499 standard in order to modeling and implementing applications of holons control.
2017-05-30T00:00:00
no_new_dataset
false
0.705485
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.09800
Guy Uziel
Guy Uziel and Ran El-Yaniv
Growth-Optimal Portfolio Selection under CVaR Constraints
null
null
null
null
q-fin.MF cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Online portfolio selection research has so far focused mainly on minimizing regret defined in terms of wealth growth. Practical financial decision making, however, is deeply concerned with both wealth and risk. We consider online learning of portfolios of stocks whose prices are governed by arbitrary (unknown) stationary and ergodic processes, where the goal is to maximize wealth while keeping the conditional value at risk (CVaR) below a desired threshold. We characterize the asymptomatically optimal risk-adjusted performance and present an investment strategy whose portfolios are guaranteed to achieve the asymptotic optimal solution while fulfilling the desired risk constraint. We also numerically demonstrate and validate the viability of our method on standard datasets.
2017-05-30T00:00:00
no_new_dataset
false
0.705678
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.09808
Madhulika Mohanty
Madhulika Mohanty and Maya Ramanath
KlusTree: Clustering Answer Trees from Keyword Search on Graphs
16 pages, 2 Figures
null
null
null
cs.IR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Graph structured data on the web is now massive as well as diverse, ranging from social networks, web graphs to knowledge-bases. Effectively querying this graph structured data is non-trivial and has led to research in a variety of directions -- structured queries, keyword and natural language queries, automatic translation of these queries to structured queries, etc. We are concerned with a class of queries called relationship queries, which are usually expressed as a set of keywords (each keyword denoting a named entity). The results returned are a set of ranked trees, each of which denotes relationships among the various keywords. The result list could consist of hundreds of answers. The problem of keyword search on graphs has been explored for over a decade now, but an important aspect that is not as extensively studied is that of user experience. We propose KlusTree, which presents clustered results to the users instead of a list of all the results. In our approach, the result trees are represented using language models and are clustered using JS divergence as a distance measure. We compare KlusTree with the well-known approaches based on isomorphism and tree-edit distance based clustering. The user evaluations show that KlusTree outperforms the other two in providing better clustering, thereby enriching user experience, revealing interesting patterns and improving result interpretation by the user.
2017-05-30T00:00:00
no_new_dataset
false
0.709429
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.09816
Reza Borhani
Reza Borhani, Jeremy Watt, Aggelos Katsaggelos
Global hard thresholding algorithms for joint sparse image representation and denoising
null
null
null
null
cs.CV cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Sparse coding of images is traditionally done by cutting them into small patches and representing each patch individually over some dictionary given a pre-determined number of nonzero coefficients to use for each patch. In lack of a way to effectively distribute a total number (or global budget) of nonzero coefficients across all patches, current sparse recovery algorithms distribute the global budget equally across all patches despite the wide range of differences in structural complexity among them. In this work we propose a new framework for joint sparse representation and recovery of all image patches simultaneously. We also present two novel global hard thresholding algorithms, based on the notion of variable splitting, for solving the joint sparse model. Experimentation using both synthetic and real data shows effectiveness of the proposed framework for sparse image representation and denoising tasks. Additionally, time complexity analysis of the proposed algorithms indicate high scalability of both algorithms, making them favorable to use on large megapixel images.
2017-05-30T00:00:00
no_new_dataset
false
0.710577
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.09819
Nalin Asanka Gamagedara Arachchilage
B. B. Gupta, Nalin Asanka Gamagedara Arachchilage, Konstantinos E. Psannis
Defending against Phishing Attacks: Taxonomy of Methods, Current Issues and Future Directions
32, Telecommunication Systems, Springer, 2017
null
null
null
cs.CR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Internet technology is so pervasive today, for example, from online social networking to online banking, it has made people's lives more comfortable. Due the growth of Internet technology, security threats to systems and networks are relentlessly inventive. One such a serious threat is "phishing", in which, attackers attempt to steal the user's credentials using fake emails or websites or both. It is true that both industry and academia are working hard to develop solutions to combat against phishing threats. It is therefore very important that organisations to pay attention to end-user awareness in phishing threat prevention. Therefore, the aim of our paper is twofold. First, we will discuss the history of phishing attacks and the attackers' motivation in details. Then, we will provide taxonomy of various types of phishing attacks. Second, we will provide taxonomy of various solutions proposed in literature to protect users from phishing based on the attacks identified in our taxonomy. Moreover, we have also discussed impact of phishing attacks in Internet of Things (IoTs). We conclude our paper discussing various issues and challenges that still exist in the literature, which are important to fight against with phishing threats.
2017-05-30T00:00:00
no_new_dataset
false
0.709248
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.09823
George Kesidis
David J. Miller, Xinyi Hu, Zhicong Qiu, George Kesidis
Adversarial Learning: A Critical Review and Active Learning Study
null
null
null
null
cs.CR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This papers consists of two parts. The first is a critical review of prior art on adversarial learning, identifying some significant limitations of previous works. The second part is an experimental study considering adversarial active learning and an investigation of the efficacy of a mixed sample selection strategy for combating an adversary who attempts to disrupt the classifier learning.
2017-05-30T00:00:00
no_new_dataset
false
0.712362
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.09838
Cristina Turcu
Cristina Turcu, Cornel Turcu
Applying Artificial Intelligence and Internet Techniques in Rural Tourism Domain
Proceedings of the Fourth International Conference "Internet-Education-Science-2004", IES-2004, Baku-Vinnytsia-Veliko Turnovo, 2004, vol. 2, ISBN 966-641-104-0, pag. 583-586
null
null
null
cs.MA
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Society has become more dependent on automated intelligent systems, at the same time, these systems have become more and more complicated. Society's expectation regarding the capabilities and intelligence of such systems has also grown. We have become a more complicated society with more complicated problems. As the expectation of intelligent systems rises, we discover many more applications for artificial intelligence. Additionally, as the difficulty level and computational requirements of such problems rise, there is a need to distribute the problem solving. Although the field of multiagent systems (MAS) and distributed artificial intelligence (DAI) is relatively young, the importance and applicability of this technology for solving today's problems continue to grow. In multiagent systems, the main goal is to provide fruitful cooperation among agents in order to enrich the support given to all user activities. This paper deals with the development of a multiagent system aimed at solving the reservation problems encountered in rural tourism. Due to their benefits over the last few years, online travel agencies have become a very useful instrument in planning vacations. A MAS concept (which is based on the Internet exploitation) can improve this activity and provide clients with a new, rapid and efficient way of making accommodation arrangements.
2017-05-30T00:00:00
no_new_dataset
false
0.709107
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.09844
Mark Lewis
Mark Lewis, Fred Glover
Quadratic Unconstrained Binary Optimization Problem Preprocessing: Theory and Empirical Analysis
Benchmark problems used are available from the first author
null
null
null
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The Quadratic Unconstrained Binary Optimization problem (QUBO) has become a unifying model for representing a wide range of combinatorial optimization problems, and for linking a variety of disciplines that face these problems. A new class of quantum annealing computer that maps QUBO onto a physical qubit network structure with specific size and edge density restrictions is generating a growing interest in ways to transform the underlying QUBO structure into an equivalent graph having fewer nodes and edges. In this paper we present rules for reducing the size of the QUBO matrix by identifying variables whose value at optimality can be predetermined. We verify that the reductions improve both solution quality and time to solution and, in the case of metaheuristic methods where optimal solutions cannot be guaranteed, the quality of solutions obtained within reasonable time limits. We discuss the general QUBO structural characteristics that can take advantage of these reduction techniques and perform careful experimental design and analysis to identify and quantify the specific characteristics most affecting reduction. The rules make it possible to dramatically improve solution times on a new set of problems using both the exact Cplex solver and a tabu search metaheuristic.
2017-05-30T00:00:00
no_new_dataset
false
0.706998
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.09849
M. Ehsan Raoufat
M. Ehsan Raoufat, Kevin Tomsovic, Seddik M. Djouadi
Power System Supplementary Damping Controllers in the Presence of Saturation
Proceedings of Power and Energy Conference at Illinois (PECI), Champaign, IL, 2017
null
null
null
cs.SY
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper presents the analysis and a method to design supplementary damping controllers (SDCs) for synchronous generators considering the effects of saturation limits. Usually such saturations of control signals are imposed in order to enforce practical limitations such as component ratings. However, to guarantee the stability in the presence of saturation limits, the state trajectories must remain inside the domain of attraction (DA). In this paper, the domain of attraction of a single-machine infinite-bus (SMIB) power system with saturation nonlinearity is estimated and compared with the exact description of the null controllable region. Then, state-feedback controllers are designed to enlarge the DA. Our analysis shows that nonlinear effects of saturation should be considered to guarantee stability and satisfactory performance. Simulation results on a detailed nonlinear model of a synchronous generator indicate that the DA enlarges with the proposed controller. The results also indicate that Critical Clearing Time (CCT) and damping of the system with saturation can be improved by the proposed method.
2017-05-30T00:00:00
no_new_dataset
false
0.707827
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.09855
Cristina Turcu
Cristina Turcu. Cornel Turcu
RFID-based Solutions for Smarter Healthcare
International Workshop Fostering Innovation in Healthcare Services, 2012, Brasov, ISBN: 978-973-708-659-4
null
null
null
cs.CY
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper proposes the application of RFID technology in healthcare industry based on its increased functionality, high reliability, easy-to-use capabilities and low cost. After a brief presentation of RFID technologies and their applications, the paper describes an RFID-based system that can provide efficient facilities to allow essential information management for emergency care across hospital boundaries. This system performs RFID-based identification of the patients, querying and retrieving medical data from various existing healthcare information systems, as well as storing and giving the most clinically significant information to the clinicians. Also, the system allows identifying and tracking RFID- tagged objects in order to provide new quality services for the mobility of objects.
2017-05-30T00:00:00
no_new_dataset
false
0.711262
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.09858
Daniele Oriti
Daniele Oriti
No alternative to proliferation
15 pages; contribution to the volume "Why trust a theory?", edited by: R. Dardashti, R. Dawid, K. Thebault, to be published by Cambridge University Press
null
null
null
physics.hist-ph gr-qc hep-th
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We reflect on the nature, role and limits of non-empirical theory assessment in fundamental physics, focusing in particular on quantum gravity. We argue for the usefulness and, to some extent, necessity of non-empirical theory assessment, but also examine critically its dangers. We conclude that the principle of proliferation of theories is not only at the very root of theory assessment but all the more necessary when experimental tests are scarce, and also that, in the same situation, it represents the only medicine against the degeneration of scientific research programmes.
2017-05-30T00:00:00
no_new_dataset
false
0.712617
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.09859
Arti Yardi
Arti Yardi, Ruud Pellikaan
On shortened and punctured cyclic codes
null
null
null
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The problem of identifying whether the family of cyclic codes is asymptotically good or not is a long-standing open problem in the field of coding theory. It is known in the literature that some families of cyclic codes such as BCH codes and Reed-Solomon codes are asymptotically bad, however in general the answer to this question is not known. A recent result by Nelson and Van Zwam shows that, all linear codes can be obtained by a sequence of puncturing and/or shortening of a collection of asymptotically good codes~\cite{Nelson_2015}. In this paper, we prove that any linear code can be obtained by a sequence of puncturing and/or shortening of some cyclic code. Therefore the result that all codes can be obtained by shortening and/or puncturing cyclic codes leaves the possibility open that cyclic codes are asymptotically good.
2017-05-30T00:00:00
no_new_dataset
false
0.712733
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.09860
Edgar Sucar
Edgar Sucar, Jean-Bernard Hayet
Probabilistic Global Scale Estimation for MonoSLAM Based on Generic Object Detection
Int. Workshop on Visual Odometry, CVPR, (July 2017)
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper proposes a novel method to estimate the global scale of a 3D reconstructed model within a Kalman filtering-based monocular SLAM algorithm. Our Bayesian framework integrates height priors over the detected objects belonging to a set of broad predefined classes, based on recent advances in fast generic object detection. Each observation is produced on single frames, so that we do not need a data association process along video frames. This is because we associate the height priors with the image region sizes at image places where map features projections fall within the object detection regions. We present very promising results of this approach obtained on several experiments with different object classes.
2017-05-30T00:00:00
no_new_dataset
false
0.709295
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.09862
Zhenwen Dai
Zhenwen Dai, Mauricio A. \'Alvarez, Neil D. Lawrence
Efficient Modeling of Latent Information in Supervised Learning using Gaussian Processes
null
null
null
null
stat.ML cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Often in machine learning, data are collected as a combination of multiple conditions, e.g., the voice recordings of multiple persons, each labeled with an ID. How could we build a model that captures the latent information related to these conditions and generalize to a new one with few data? We present a new model called Latent Variable Multiple Output Gaussian Processes (LVMOGP) and that allows to jointly model multiple conditions for regression and generalize to a new condition with a few data points at test time. LVMOGP infers the posteriors of Gaussian processes together with a latent space representing the information about different conditions. We derive an efficient variational inference method for LVMOGP, of which the computational complexity is as low as sparse Gaussian processes. We show that LVMOGP significantly outperforms related Gaussian process methods on various tasks with both synthetic and real data.
2017-05-30T00:00:00
no_new_dataset
false
0.708877
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.09870
Cristina Turcu
Cristina Turcu, Remus Prodan, Tudor Cerlinca, Marius Cerlinca, Cornel Turcu, Valentin Popa, Alexandru Goloca
Integration of RFID Applications in a Web B2B Platform for Enterprise Supply Networks
Third International Conference on the Use of Modern Information and Communication Technologies, March 2008 Gent, Belgium, pp 419-428, ISBN 9 78908082, 2008
null
null
null
cs.CY
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
B2B applications focus on using the Internet and/or extranet to improve business-to-business partnerships and transform inter-organizational relationships. RFID is relatively low-cost data and wireless transmission technology that helps manufacturers to improve a number of business applications and processes. In this paper we present an RFID_B2B system that brings together the B2B and RFID advantages and which could be a viable solution for the potential problems created due to the globalization process. Using the developed system may help customers sharpen data accuracy, process supply chain transactions faster, and improve supply chain and inventory management.
2017-05-30T00:00:00
no_new_dataset
false
0.712324
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.09871
Cristina Turcu
Turcu Cristina Elena, Prodan Remus Catalin. Popa Valentin
An RFID Based Generalized Integrated System for the Identification and Traceability of Products and Subsets in Enterprises
The 2nd International Conference on the Use of Modern Information and Communication Technologies, ECUMICT, 30-31 March 2006, Ghent, Belgia, pg. 147-158, ISBN 9-08082-552-2, 2006
null
null
null
cs.CY
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
RFID tags are small electronic devices that can be used to identify objects and people. The present paper presents an RFID-based integrated system that has been developed to allow the identification and traceability of products and subsets in whatever activity field. Thus this system offers to the users the possibility to define their own information format to be stored in the transponder. The potential beneficiaries of this system are companies that activate in fields that lend themselves admirably to RFID technologies.
2017-05-30T00:00:00
no_new_dataset
false
0.711042
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.09872
Gerard Memmi P
Katarzyna Kapusta, Gerard Memmi, and Hassan Noura
An Efficient Keyless Fragmentation Algorithm for Data Protection
null
null
null
null
cs.CR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The family of Information Dispersal Algorithms is applied to distributed systems for secure and reliable storage and transmission. In comparison with perfect secret sharing it achieves a significantly smaller memory overhead and better performance, but provides only incremental confidentiality. Therefore, even if it is not possible to explicitly reconstruct data from less than the required amount of fragments, it is still possible to deduce some information about the nature of data by looking at preserved data patterns inside a fragment. The idea behind this paper is to provide a lightweight data fragmentation scheme, that would combine the space efficiency and simplicity that could be find in Information Dispersal Algorithms with a computational level of data confidentiality.
2017-05-30T00:00:00
no_new_dataset
false
0.709454
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.09879
Patrick Rodler
Patrick Rodler and Wolfgang Schmid and Konstantin Schekotihin
Inexpensive Cost-Optimized Measurement Proposal for Sequential Model-Based Diagnosis
null
null
null
null
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this work we present strategies for (optimal) measurement selection in model-based sequential diagnosis. In particular, assuming a set of leading diagnoses being given, we show how queries (sets of measurements) can be computed and optimized along two dimensions: expected number of queries and cost per query. By means of a suitable decoupling of two optimizations and a clever search space reduction the computations are done without any inference engine calls. For the full search space, we give a method requiring only a polynomial number of inferences and guaranteeing query properties existing methods cannot provide. Evaluation results using real-world problems indicate that the new method computes (virtually) optimal queries instantly independently of the size and complexity of the considered diagnosis problems.
2017-05-30T00:00:00
no_new_dataset
false
0.708178
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.09888
Peng Xu
Peng Xu, Qiyue Yin, Yongye Huang, Yi-Zhe Song, Zhanyu Ma, Liang Wang, Tao Xiang, W. Bastiaan Kleijn, Jun Guo
Cross-modal Subspace Learning for Fine-grained Sketch-based Image Retrieval
Accepted by Neurocomputing
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Sketch-based image retrieval (SBIR) is challenging due to the inherent domain-gap between sketch and photo. Compared with pixel-perfect depictions of photos, sketches are iconic renderings of the real world with highly abstract. Therefore, matching sketch and photo directly using low-level visual clues are unsufficient, since a common low-level subspace that traverses semantically across the two modalities is non-trivial to establish. Most existing SBIR studies do not directly tackle this cross-modal problem. This naturally motivates us to explore the effectiveness of cross-modal retrieval methods in SBIR, which have been applied in the image-text matching successfully. In this paper, we introduce and compare a series of state-of-the-art cross-modal subspace learning methods and benchmark them on two recently released fine-grained SBIR datasets. Through thorough examination of the experimental results, we have demonstrated that the subspace learning can effectively model the sketch-photo domain-gap. In addition we draw a few key insights to drive future research.
2017-05-30T00:00:00
no_new_dataset
false
0.707622
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.09890
David Zarrouk Prof.
Moshe P. Mann, Lior Damti, David Zarrouk
Minimally Actuated Serial Robot
null
null
null
null
cs.RO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we propose a novel type of serial robot with minimal actuation. The robot is a serial rigid structure consisting of multiple links connected by passive joints and of movable actuators. The novelty of this robot is that the actuators travel over the links to a given joint and adjust the relative angle between the two adjacent links. The joints passively preserve their angles until one of the actuators moves them again. This actuation can be applied to any serial robot with two or more links. This unique configuration enables the robot to undergo the same wide range of motions typically associated with hyper-redundant robots but with much fewer actuators. The robot is modular and its size and geometry can be easily changed. We describe the robot's mechanical design and kinematics in detail and demonstrate its capabilities for obstacle avoidance with some simulated examples. In addition, we show how an experimental robot fitted with a single mobile actuator can maneuver through a confined space to reach its target.
2017-05-30T00:00:00
no_new_dataset
false
0.71101
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.09892
Chunhua Shen
Bohan Zhuang, Qi Wu, Chunhua Shen, Ian Reid, Anton van den Hengel
Care about you: towards large-scale human-centric visual relationship detection
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Visual relationship detection aims to capture interactions between pairs of objects in images. Relationships between objects and humans represent a particularly important subset of this problem, with implications for challenges such as understanding human behaviour, and identifying affordances, amongst others. In addressing this problem we first construct a large-scale human-centric visual relationship detection dataset (HCVRD), which provides many more types of relationship annotation (nearly 10K categories) than the previous released datasets. This large label space better reflects the reality of human-object interactions, but gives rise to a long-tail distribution problem, which in turn demands a zero-shot approach to labels appearing only in the test set. This is the first time this issue has been addressed. We propose a webly-supervised approach to these problems and demonstrate that the proposed model provides a strong baseline on our HCVRD dataset.
2017-05-30T00:00:00
new_dataset
true
0.711419
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.09894
Brandon Victor
Brandon Victor, Zhen He, Stuart Morgan, Dino Miniutti
Continuous Video to Simple Signals for Swimming Stroke Detection with Convolutional Neural Networks
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In many sports, it is useful to analyse video of an athlete in competition for training purposes. In swimming, stroke rate is a common metric used by coaches; requiring a laborious labelling of each individual stroke. We show that using a Convolutional Neural Network (CNN) we can automatically detect discrete events in continuous video (in this case, swimming strokes). We create a CNN that learns a mapping from a window of frames to a point on a smooth 1D target signal, with peaks denoting the location of a stroke, evaluated as a sliding window. To our knowledge this process of training and utilizing a CNN has not been investigated before; either in sports or fundamental computer vision research. Most research has been focused on action recognition and using it to classify many clips in continuous video for action localisation. In this paper we demonstrate our process works well on the task of detecting swimming strokes in the wild. However, without modifying the model architecture or training method, the process is also shown to work equally well on detecting tennis strokes, implying that this is a general process. The outputs of our system are surprisingly smooth signals that predict an arbitrary event at least as accurately as humans (manually evaluated from a sample of negative results). A number of different architectures are evaluated, pertaining to slightly different problem formulations and signal targets.
2017-05-30T00:00:00
no_new_dataset
false
0.710933
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.09897
Mahendra K. Verma Prof.
Supriyo Paul and Mahendra K. Verma
Proper orthogonal decomposition vs. Fourier analysis for extraction of large-scale structures of thermal convection
In Proc. Advances in Computation, Modeling and Control of Transitional and Turbulent Flows Eds. T. K. Sengupta, S. Lele, K. R. Sreenivasan, and P. A. Davidson, p. 433, World Scientific (2016)
null
null
null
physics.flu-dyn nlin.PS physics.comp-ph
http://creativecommons.org/publicdomain/zero/1.0/
We performed a comparative study of extraction of large-scale flow structures in Rayleigh B\'enard convection using proper orthogonal decomposition (POD) and {\em Fourier analysis}. We show that the free-slip basis functions capture the flow profiles successfully for the no-slip boundary conditions. We observe that the large-scale POD modes capture a larger fraction of total energy than the Fourier modes. However, the Fourier modes capture the rarer flow structures like flow reversals better. The flow profiles of the dominant POD and Fourier modes are quite similar. Our results show that the Fourier analysis provides an attractive alternative to POD analysis for capturing large-scale flow structures.
2017-05-30T00:00:00
no_new_dataset
false
0.712825
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.09902
Nik Sultana
Nik Sultana, Salvator Galea, David Greaves, Marcin Wojcik, Noa Zilberman, Richard Clegg, Luo Mai, Richard Mortier, Peter Pietzuch, Jon Crowcroft, Andrew W Moore
Extending programs with debug-related features, with application to hardware development
null
null
null
null
cs.PL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The capacity and programmability of reconfigurable hardware such as FPGAs has improved steadily over the years, but they do not readily provide any mechanisms for monitoring or debugging running programs. Such mechanisms need to be written into the program itself. This is done using ad hoc methods and primitive tools when compared to CPU programming. This complicates the programming and debugging of reconfigurable hardware. We introduce Program-hosted Directability (PhD), the extension of programs to interpret direction commands at runtime to enable debugging, monitoring and profiling. Normally in hardware development such features are fixed at compile time. We present a language of directing commands, specify its semantics in terms of a simple controller that is embedded with programs, and implement a prototype for directing network programs running in hardware. We show that this approach affords significant flexibility with low impact on hardware utilisation and performance.
2017-05-30T00:00:00
no_new_dataset
false
0.708226
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.09906
Haichao Zhang
Haichao Zhang, Haonan Yu, and Wei Xu
Listen, Interact and Talk: Learning to Speak via Interaction
null
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
One of the long-term goals of artificial intelligence is to build an agent that can communicate intelligently with human in natural language. Most existing work on natural language learning relies heavily on training over a pre-collected dataset with annotated labels, leading to an agent that essentially captures the statistics of the fixed external training data. As the training data is essentially a static snapshot representation of the knowledge from the annotator, the agent trained this way is limited in adaptiveness and generalization of its behavior. Moreover, this is very different from the language learning process of humans, where language is acquired during communication by taking speaking action and learning from the consequences of speaking action in an interactive manner. This paper presents an interactive setting for grounded natural language learning, where an agent learns natural language by interacting with a teacher and learning from feedback, thus learning and improving language skills while taking part in the conversation. To achieve this goal, we propose a model which incorporates both imitation and reinforcement by leveraging jointly sentence and reward feedbacks from the teacher. Experiments are conducted to validate the effectiveness of the proposed approach.
2017-05-30T00:00:00
no_new_dataset
false
0.682593
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.09914
Fisher Yu
Fisher Yu, Vladlen Koltun, Thomas Funkhouser
Dilated Residual Networks
Published at the Conference on Computer Vision and Pattern Recognition (CVPR 2017)
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Convolutional networks for image classification progressively reduce resolution until the image is represented by tiny feature maps in which the spatial structure of the scene is no longer discernible. Such loss of spatial acuity can limit image classification accuracy and complicate the transfer of the model to downstream applications that require detailed scene understanding. These problems can be alleviated by dilation, which increases the resolution of output feature maps without reducing the receptive field of individual neurons. We show that dilated residual networks (DRNs) outperform their non-dilated counterparts in image classification without increasing the model's depth or complexity. We then study gridding artifacts introduced by dilation, develop an approach to removing these artifacts (`degridding'), and show that this further increases the performance of DRNs. In addition, we show that the accuracy advantage of DRNs is further magnified in downstream applications such as object localization and semantic segmentation.
2017-05-30T00:00:00
no_new_dataset
false
0.711101
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.09920
Ali Nassif
Mohammad Azzeh, Ali Bou Nassif
Analyzing the Relationship between Project Productivity and Environment Factors in the Use Case Points Method
Journal of Software: Evolution and Process, 2017
null
10.1002/smr.1882
null
cs.SE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Project productivity is a key factor for producing effort estimates from Use Case Points (UCP), especially when the historical dataset is absent. The first versions of UCP effort estimation models used a fixed number or very limited numbers of productivity ratios for all new projects. These approaches have not been well examined over a large number of projects so the validity of these studies was a matter for criticism. The newly available large software datasets allow us to perform further research on the usefulness of productivity for effort estimation of software development. Specifically, we studied the relationship between project productivity and UCP environmental factors, as they have a significant impact on the amount of productivity needed for a software project. Therefore, we designed four studies, using various classification and regression methods, to examine the usefulness of that relationship and its impact on UCP effort estimation. The results we obtained are encouraging and show potential improvement in effort estimation. Furthermore, the efficiency of that relationship is better over a dataset that comes from industry because of the quality of data collection. Our comment on the findings is that it is better to exclude environmental factors from calculating UCP and make them available only for computing productivity. The study also encourages project managers to understand how to better assess the environmental factors as they do have a significant impact on productivity
2017-05-30T00:00:00
no_new_dataset
false
0.707212
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.09922
Ole-Christoffer Granmo
Ole-Christoffer Granmo
Bayesian Unification of Gradient and Bandit-based Learning for Accelerated Global Optimisation
15th IEEE International Conference on Machine Learning and Applications (ICMLA 2016)
null
10.1109/ICMLA.2016.0044
null
cs.AI cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Bandit based optimisation has a remarkable advantage over gradient based approaches due to their global perspective, which eliminates the danger of getting stuck at local optima. However, for continuous optimisation problems or problems with a large number of actions, bandit based approaches can be hindered by slow learning. Gradient based approaches, on the other hand, navigate quickly in high-dimensional continuous spaces through local optimisation, following the gradient in fine grained steps. Yet, apart from being susceptible to local optima, these schemes are less suited for online learning due to their reliance on extensive trial-and-error before the optimum can be identified. In this paper, we propose a Bayesian approach that unifies the above two paradigms in one single framework, with the aim of combining their advantages. At the heart of our approach we find a stochastic linear approximation of the function to be optimised, where both the gradient and values of the function are explicitly captured. This allows us to learn from both noisy function and gradient observations, and predict these properties across the action space to support optimisation. We further propose an accompanying bandit driven exploration scheme that uses Bayesian credible bounds to trade off exploration against exploitation. Our empirical results demonstrate that by unifying bandit and gradient based learning, one obtains consistently improved performance across a wide spectrum of problem environments. Furthermore, even when gradient feedback is unavailable, the flexibility of our model, including gradient prediction, still allows us outperform competing approaches, although with a smaller margin. Due to the pervasiveness of bandit based optimisation, our scheme opens up for improved performance both in meta-optimisation and in applications where gradient related information is readily available.
2017-05-30T00:00:00
no_new_dataset
false
0.709583
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.09930
Amikam Patron
Amikam Patron, Reuven Cohen, Daqing Li, Shlomo Havlin
Optimal cost for strengthening or destroying a given network
null
Physical Review E 95, 052305 (2017)
10.1103/PhysRevE.95.052305
null
physics.soc-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Strengthening or destroying a network is a very important issue in designing resilient networks or in planning attacks against networks including planning strategies to immunize a network against diseases, viruses etc.. Here we develop a method for strengthening or destroying a random network with a minimum cost. We assume a correlation between the cost required to strengthen or destroy a node and the degree of the node. Accordingly, we define a cost function c(k), which is the cost of strengthening or destroying a node with degree k. Using the degrees $k$ in a network and the cost function c(k), we develop a method for defining a list of priorities of degrees, and for choosing the right group of degrees to be strengthened or destroyed that minimizes the total price of strengthening or destroying the entire network. We find that the list of priorities of degrees is universal and independent of the network's degree distribution, for all kinds of random networks. The list of priorities is the same for both strengthening a network and for destroying a network with minimum cost. However, in spite of this similarity there is a difference between their p_c - the critical fraction of nodes that has to be functional, to guarantee the existence of a giant component in the network.
2017-05-30T00:00:00
no_new_dataset
false
0.711522
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.09935
Rajany K V
K.V. Rajany, Anupam Gupta, Alexander V. Panfilov, Rahul Pandit
The statistical properties of spiral- and scroll-wave turbulence in cardiac tissue
16 pages, 24 figures, One table
null
null
null
physics.bio-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Disorganized electrical activity in the heart leads to sudden cardiac death. To what extent can this electrical turbulence be viewed as classical fluid turbulence,which is an important central problem in modern physics? We investigate,for the first time,via extensive DNSs,the statistical properties of spiral-and scroll-wave turbulence in two- and three-dimensional excitable media by using approaches employed in studies of classical turbulence. We use the Panfilov and the Aliev-Panfilov mathematical models for cardiac tissue. We show that once electrical-wave turbulence has been initiated,there is a forward cascade,in which spirals or scrolls form,interact,and break to yield a turbulent state that is statistically steady and,far away from boundaries,is statistically homogeneous and isotropic. For the transmembrane potential $V$ and the slow recovery variable $g$,which define our models,we define $E_V(k)$ and $E_g(k)$,the electrical-wave analogs of the fluid energy spectrum $E(k)$ in fluid turbulence. We show that $E_V(k)$ and $E_g(k)$ are spread out over several decades in $k$. Thus spiral- and scroll-wave turbulence involves a wide range of spatial scales. $E_V(k)$ and $E_g(k)$ show approximate power laws,in some range of $k$, however,their exponents cannot be determined as accurately as their fluid-turbulence counterparts. The dimensionless ratio $L/\lambda$ is a convenient control parameter like the Reynolds number for fluid turbulence,where $L$ is the linear size of the domain and $\lambda$ the wavelength of a plane wave in the medium. By comparing several other statistical properties for spiral- and scroll-wave turbulence with their fluid-turbulence counterparts,we show that,although spiral- and scroll-wave turbulence have some statistical properties like those of fluid turbulence,overall these types of turbulence are special and differ in important ways from fluid turbulence.
2017-05-30T00:00:00
no_new_dataset
false
0.708814
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.09936
Raymond Veldhuis
Joep Peeters, Andreas Peter, Raymond N.J. Veldhuis
Fast and Accurate Likelihood Ratio Based Biometric Comparison in the Encrypted Domain
null
null
null
null
cs.CR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
As applications of biometric verification proliferate, users become more vulnerable to privacy infringement. Biometric data is very privacy sensitive as it may contain information as gender, ethnicity and health conditions which should not be shared with third parties during the verification process. Moreover, biometric data that has fallen into the wrong hands often leads to identity theft. Secure biometric verification schemes try to overcome such privacy threats. Unfortunately, existing secure solutions either introduce a heavy computational or communication overhead or have to accept a high loss in accuracy; both of which make them impractical in real-world settings. This paper presents a novel approach to secure biometric verification aiming at a practical trade-off between efficiency and accuracy, while guaranteeing full security against honest-but-curious adversaries. The system performs verification in the encrypted domain using elliptic curve based homomorphic ElGamal encryption for high efficiency. Classification is based on a log-likelihood ratio classifier which has proven to be very accurate. No private information is leaked during the verification process using a two-party secure protocol. Initial tests show highly accurate results that have been computed within milliseconds range.
2017-05-30T00:00:00
no_new_dataset
false
0.710392
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.09937
Leonid Yavits PhD
Leonid Yavits and Ran Ginosar
Sparse Matrix Multiplication on CAM Based Accelerator
null
null
null
null
cs.AR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Sparse matrix multiplication is an important component of linear algebra computations. In this paper, an architecture based on Content Addressable Memory (CAM) and Resistive Content Addressable Memory (ReCAM) is proposed for accelerating sparse matrix by sparse vector and matrix multiplication in CSR format. Using functional simulation, we show that the proposed ReCAM-based accelerator exhibits two orders of magnitude higher power efficiency as compared to existing sparse matrix-vector multiplication implementations.
2017-05-30T00:00:00
no_new_dataset
false
0.709212
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.09954
Bo Jiang
Chris Ding and Bo Jiang
L1-norm Error Function Robustness and Outlier Regularization
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In many real-world applications, data come with corruptions, large errors or outliers. One popular approach is to use L1-norm function. However, the robustness of L1-norm function is not well understood so far. In this paper, we present a new outlier regularization framework to understand and analyze the robustness of L1-norm function. There are two main features for the proposed outlier regularization. (1) A key property of outlier regularization is that how far an outlier lies away from its theoretically predicted value does not affect the final regularization and analysis results. (2) Another important feature of outlier regularization is that it has an equivalent continuous representation that closely relates to L1 function. This provides a new way to understand and analyze the robustness of L1 function. We apply our outlier regularization framework to PCA and propose an outlier regularized PCA (ORPCA) model. Comparing to the trace-normbased robust PCA, ORPCA has several benefits: (1) It does not suffer singular value suppression. (2) It can retain small high rank components which help retain fine details of data. (3) ORPCA can be computed more efficiently.
2017-05-30T00:00:00
no_new_dataset
false
0.710177
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.09959
Naoya Iwahara
Naoya Iwahara, Tohru Sato, Kazuyoshi Tanaka, Liviu F. Chibotaru
Mechanisms of localization in isotope-substituted dynamical Jahn-Teller systems
6 pages, 4 figures
Europhysics Letters 100, 43001 (2012)
10.1209/0295-5075/100/43001
null
physics.chem-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The mechanisms of localization of Jahn-Teller deformations and vibronic wavefunctions in isotope substituted dynamical Jahn-Teller systems are elucidated. It is found that the localization in the trough is of potential type in the case of strong vibronic coupling, while it becomes of kinetic type in the case of intermediate and weak coupling. It is shown that the vibronic levels in the linear $E\otimes e$-problem remain double degenerate upon arbitrary isotope substitution on the reasons similar to time reversal symmetry in which the role of spin is played by orbital pseudospin.
2017-05-30T00:00:00
no_new_dataset
false
0.712122
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.09975
Nazli Farajidavar
Nazli Farajidavar, Sefki Kolozali and Payam Barnaghi
A Deep Multi-View Learning Framework for City Event Extraction from Twitter Data Streams
null
null
null
null
cs.SI cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Cities have been a thriving place for citizens over the centuries due to their complex infrastructure. The emergence of the Cyber-Physical-Social Systems (CPSS) and context-aware technologies boost a growing interest in analysing, extracting and eventually understanding city events which subsequently can be utilised to leverage the citizen observations of their cities. In this paper, we investigate the feasibility of using Twitter textual streams for extracting city events. We propose a hierarchical multi-view deep learning approach to contextualise citizen observations of various city systems and services. Our goal has been to build a flexible architecture that can learn representations useful for tasks, thus avoiding excessive task-specific feature engineering. We apply our approach on a real-world dataset consisting of event reports and tweets of over four months from San Francisco Bay Area dataset and additional datasets collected from London. The results of our evaluations show that our proposed solution outperforms the existing models and can be used for extracting city related events with an averaged accuracy of 81% over all classes. To further evaluate the impact of our Twitter event extraction model, we have used two sources of authorised reports through collecting road traffic disruptions data from Transport for London API, and parsing the Time Out London website for sociocultural events. The analysis showed that 49.5% of the Twitter traffic comments are reported approximately five hours prior to the authorities official records. Moreover, we discovered that amongst the scheduled sociocultural event topics; tweets reporting transportation, cultural and social events are 31.75% more likely to influence the distribution of the Twitter comments than sport, weather and crime topics.
2017-05-30T00:00:00
no_new_dataset
false
0.698254
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.09985
Majid Bavand
Majid Bavand and Steven D. Blostein
User Selection and Widely Linear Multiuser Precoding for One-dimensional Signalling
null
null
null
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Massive deployment of low data rate Internet of things and ehealth devices prompts us to develop more practical precoding and user selection techniques that comply with these requirements. Moreover, it is known that when the data is real-valued and the observation is complex-valued, widely linear (WL) estimation can be employed in lieu of linear estimation to improve the performance. With these motivations, in this paper, we study the transmit precoding (beamforming) in multiuser multiple-input single-output communications systems assuming the transmit signal is one-dimensionally modulated and widely linear estimation is performed at the receivers. Closed-form solutions for widely linear maximum ratio transmission (MRT), WL zero-forcing (ZF), WL minimum mean square error (MMSE), and WL maximum signal to leakage and noise ratio (MSLNR) precoding are obtained. It is shown that widely linear processing can potentially double the number of simultaneous users compared to the linear processing of one-dimensionally modulated signals. Furthermore, to deal with the increasing number of communications devices a user selection algorithm compatible with widely linear processing of one-dimensionally modulated signals is proposed. The proposed user selection algorithm can double the number of simultaneously selected users compared to conventional user selection methods.
2017-05-30T00:00:00
no_new_dataset
false
0.710846
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.09987
Luciano Panek
Luciano Panek, Nayene Michele Pai\~ao Panek
Symmetry Group of Ordered Hamming Block Space
null
null
null
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Let $P = (\{1,2,\ldots,n,\leq)$ be a poset that is an union of disjoint chains of the same length and $V=\mathbb{F}_q^N$ be the space of $N$-tuples over the finite field $\mathbb{F}_q$. Let $V_i = \mathbb{F}_q^{k_i}$, $1 \leq i \leq n$, be a family of finite-dimensional linear spaces such that $k_1+k_2+\ldots +k_n = N$ and let $V = V_1 \oplus V_2 \oplus \ldots \oplus V_n$ endow with the poset block metric $d_{(P,\pi)}$ induced by the poset $P$ and the partition $\pi=(k_1,k_2,\ldots,k_n)$, encompassing both Niederreiter-Rosenbloom-Tsfasman metric and error-block metric. In this paper, we give a complete description of group of symmetries of the metric space $(V,d_{(P,\pi)})$, called the ordered Hammming block space. In particular, we reobtain the group of symmetries of the Niederreiter-Rosenbloom-Tsfasman space and obtain the group of symmetries of the error-block metric space.
2017-05-30T00:00:00
no_new_dataset
false
0.70454
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.09990
Smitha Milli
Smitha Milli, Dylan Hadfield-Menell, Anca Dragan, Stuart Russell
Should Robots be Obedient?
Accepted to IJCAI 2017
null
null
null
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Intuitively, obedience -- following the order that a human gives -- seems like a good property for a robot to have. But, we humans are not perfect and we may give orders that are not best aligned to our preferences. We show that when a human is not perfectly rational then a robot that tries to infer and act according to the human's underlying preferences can always perform better than a robot that simply follows the human's literal order. Thus, there is a tradeoff between the obedience of a robot and the value it can attain for its owner. We investigate how this tradeoff is impacted by the way the robot infers the human's preferences, showing that some methods err more on the side of obedience than others. We then analyze how performance degrades when the robot has a misspecified model of the features that the human cares about or the level of rationality of the human. Finally, we study how robots can start detecting such model misspecification. Overall, our work suggests that there might be a middle ground in which robots intelligently decide when to obey human orders, but err on the side of obedience.
2017-05-30T00:00:00
no_new_dataset
false
0.709184
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.09995
Nisansa De Silva
Nisansa de Silva, Danaja Maldeniya, Chamilka Wijeratne
Subject Specific Stream Classification Preprocessing Algorithm for Twitter Data Stream
6 pages
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Micro-blogging service Twitter is a lucrative source for data mining applications on global sentiment. But due to the omnifariousness of the subjects mentioned in each data item; it is inefficient to run a data mining algorithm on the raw data. This paper discusses an algorithm to accurately classify the entire stream in to a given number of mutually exclusive collectively exhaustive streams upon each of which the data mining algorithm can be run separately yielding more relevant results with a high efficiency.
2017-05-30T00:00:00
no_new_dataset
false
0.713956
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.10000
Deyu Meng
Hongwei Yong, Deyu Meng, Wangmeng Zuo, Lei Zhang
Robust Online Matrix Factorization for Dynamic Background Subtraction
14 pages, 13 figures
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We propose an effective online background subtraction method, which can be robustly applied to practical videos that have variations in both foreground and background. Different from previous methods which often model the foreground as Gaussian or Laplacian distributions, we model the foreground for each frame with a specific mixture of Gaussians (MoG) distribution, which is updated online frame by frame. Particularly, our MoG model in each frame is regularized by the learned foreground/background knowledge in previous frames. This makes our online MoG model highly robust, stable and adaptive to practical foreground and background variations. The proposed model can be formulated as a concise probabilistic MAP model, which can be readily solved by EM algorithm. We further embed an affine transformation operator into the proposed model, which can be automatically adjusted to fit a wide range of video background transformations and make the method more robust to camera movements. With using the sub-sampling technique, the proposed method can be accelerated to execute more than 250 frames per second on average, meeting the requirement of real-time background subtraction for practical video processing tasks. The superiority of the proposed method is substantiated by extensive experiments implemented on synthetic and real videos, as compared with state-of-the-art online and offline background subtraction methods.
2017-05-30T00:00:00
no_new_dataset
false
0.711052
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.10004
Zuo-Bing Wu
Zuo-Bing Wu
Terminal thermocapillary migration of a droplet at small Reynolds numbers and large Marangoni numbers
null
Acta Mechanica Vol. 228(6), pp. 2347-2361, 2017
10.1007/s00707-017-1833-4
null
physics.flu-dyn
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, the overall steady-state momentum and energy balances in the thermocapillary migration of a droplet at small Reynolds numbers and large Marangoni numbers are investigated to confirm the quasi-steady state assumption of the system. The droplet is assumed to have a slight axisymmetric deformation from a sphere shape. It is shown that under the quasi-steady state assumption, the total momentum of the thermocapillary droplet migration system at small Reynolds numbers is conservative. The general solution of the steady momentum equations can be determined with its parameters depending on the temperature fields. However, a nonconservative integral thermal flux across the interface for the steady thermocapillary migration of the droplet at small Reynolds numbers and large Marangoni numbers is identified. The nonconservative integral thermal flux indicates that no solutions of the temperature fields exist for the steady energy equations. The terminal thermocapillary migration of the droplet at small Reynolds numbers and large Marangoni numbers cannot reach a steady state and is thus in an unsteady process.
2017-05-30T00:00:00
no_new_dataset
false
0.713398
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.10006
Zuo-Bing Wu
Zuo-Bing Wu
Terminal states of thermocapillary migration of a planar droplet at moderate and large Marangoni numbers
8 pages, 6 figures
International Journal of Heat and Mass Transfer, Vol. 105, pp. 704-711 (2017)
null
null
physics.flu-dyn
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, thermocapillary migration of a planar droplet at moderate and large Marangoni numbers is investigated analytically and numerically. By using the dimension-analysis method, the thermal diffusion time scale is determined as the controlling one of the thermocapillary droplet migration system. During this time, the whole thermocapillary migration process is fully developed. By using the front-tracking method, the steady/unsteady states as the terminal ones at moderate/large Marangoni numbers are captured in a longer time scale than the thermal diffusion time scale. In the terminal states, the instantaneous velocity fields in the unsteady migration process at large Marangoni numbers have the forms of the steady ones at moderate Marangoni numbers. However, in view of the former instantaneous temperature fields, the surface tension of the top surface of the droplet gradually becomes the main component of the driving force on the droplet after the inflection point appears. It is different from that the surface tension of the bottom surface of the droplet is the main component of the driving force on the droplet for the latter ones. The physical mechanism of thermocapillary droplet migration can be described as the significance of the thermal convection around the droplet is higher than/just as the thermal conduction across the droplet at large/moderate Marangoni numbers.
2017-05-30T00:00:00
no_new_dataset
false
0.713528
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.10030
Hu Xu
Hu Xu, Lei Shu, Philip S. Yu
Supervised Complementary Entity Recognition with Augmented Key-value Pairs of Knowledge
null
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Extracting opinion targets is an important task in sentiment analysis on product reviews and complementary entities (products) are one important type of opinion targets that may work together with the reviewed product. In this paper, we address the problem of Complementary Entity Recognition (CER) as a supervised sequence labeling with the capability of expanding domain knowledge as key-value pairs from unlabeled reviews, by automatically learning and enhancing knowledge-based features. We use Conditional Random Field (CRF) as the base learner and augment CRF with knowledge-based features (called the Knowledge-based CRF or KCRF for short). We conduct experiments to show that KCRF effectively improves the performance of supervised CER task.
2017-05-30T00:00:00
no_new_dataset
false
0.70903
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.10032
Maria Spichkova
Nasser Alzahrani, Maria Spichkova, Jan Olaf Blech
From Temporal Models to Property-Based Testing
Preprint. Accepted to the 12th International Conference on Evaluation of Novel Approaches to Software Engineering (ENASE 2017). Final version published by SCITEPRESS, http://www.scitepress.org
null
null
null
cs.SE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper presents a framework to apply property-based testing (PBT) on top of temporal formal models. The aim of this work is to help software engineers to understand temporal models that are presented formally and to make use of the advantages of formal methods: the core time-based constructs of a formal method are schematically translated to the BeSpaceD extension of the Scala programming language. This allows us to have an executable Scala code that corresponds to the formal model, as well as to perform PBT of the models functionality. To model temporal properties of the systems, in the current work we focus on two formal languages, TLA+ and FocusST.
2017-05-30T00:00:00
no_new_dataset
false
0.707974
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.10033
Chao Qin
Chao Qin, Diego Klabjan, and Daniel Russo
Improving the Expected Improvement Algorithm
Submitted to NIPS 2017
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The expected improvement (EI) algorithm is a popular strategy for information collection in optimization under uncertainty. The algorithm is widely known to be too greedy, but nevertheless enjoys wide use due to its simplicity and ability to handle uncertainty and noise in a coherent decision theoretic framework. To provide rigorous insight into EI, we study its properties in a simple setting of Bayesian optimization where the domain consists of a finite grid of points. This is the so-called best-arm identification problem, where the goal is to allocate measurement effort wisely to confidently identify the best arm using a small number of measurements. In this framework, one can show formally that EI is far from optimal. To overcome this shortcoming, we introduce a simple modification of the expected improvement algorithm. Surprisingly, this simple change results in an algorithm that is asymptotically optimal for Gaussian best-arm identification problems, and provably outperforms standard EI by an order of magnitude.
2017-05-30T00:00:00
no_new_dataset
false
0.708007
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.10034
Xiaopeng Zhang
Xiaopeng Zhang, Hongkai Xiong, Weiyao Lin, Qi Tian
Ensemble of Part Detectors for Simultaneous Classification and Localization
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Part-based representation has been proven to be effective for a variety of visual applications. However, automatic discovery of discriminative parts without object/part-level annotations is challenging. This paper proposes a discriminative mid-level representation paradigm based on the responses of a collection of part detectors, which only requires the image-level labels. Towards this goal, we first develop a detector-based spectral clustering method to mine the representative and discriminative mid-level patterns for detector initialization. The advantage of the proposed pattern mining technology is that the distance metric based on detectors only focuses on discriminative details, and a set of such grouped detectors offer an effective way for consistent pattern mining. Relying on the discovered patterns, we further formulate the detector learning process as a confidence-loss sparse Multiple Instance Learning (cls-MIL) task, which considers the diversity of the positive samples, while avoid drifting away the well localized ones by assigning a confidence value to each positive sample. The responses of the learned detectors can form an effective mid-level image representation for both image classification and object localization. Experiments conducted on benchmark datasets demonstrate the superiority of our method over existing approaches.
2017-05-30T00:00:00
no_new_dataset
false
0.709938
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.10038
David Moss
Fangxin Li, Stuart D. Jackson, Christian Grillet, Eric Magi, Darren Hudson, Steven J. Madden, Yashodhan Moghe, Christopher OBrien, Andrew Read, Steven G. Duvall, Peter Atanackovic, Benjamin J. Eggleton, and David J. Moss
High quality waveguides for the mid-infrared wavelength range in a silicon-on-sapphire platform
9 pages, 6 figures, 18 references
Optics Express Volume 19 Issue 16 Pages 15212-15220 (2011)
10.1364/OE.19.015212
null
physics.app-ph physics.optics
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We report record low loss silicon-on-sapphire nanowires for applications to mid infrared optics. We achieve propagation losses as low as 0.8dB/cm at 1550nm, 1.1 to 1.4dB/cm at 2080nm and < 2dB/cm at = 5.18 microns.
2017-05-30T00:00:00
no_new_dataset
false
0.709752
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.10050
Adnan Rashid
Adnan Rashid and Osman Hasan
Formalization of Transform Methods using HOL Light
15 Pages, CICM 2017
null
null
null
cs.LO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Transform methods, like Laplace and Fourier, are frequently used for analyzing the dynamical behaviour of engineering and physical systems, based on their transfer function, and frequency response or the solutions of their corresponding differential equations. In this paper, we present an ongoing project, which focuses on the higher-order logic formalization of transform methods using HOL Light theorem prover. In particular, we present the motivation of the formalization, which is followed by the related work. Next, we present the task completed so far while highlighting some of the challenges faced during the formalization. Finally, we present a roadmap to achieve our objectives, the current status and the future goals for this project.
2017-05-30T00:00:00
no_new_dataset
false
0.710378
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.10051
Jittat Fakcharoenphol
Adisak Supeesun (Kasetsart University, Bangkok, Thailand) and Jittat Fakcharoenphol (Kasetsart University, Bangkok, Thailand)
Learning Network Structures from Contagion
null
Information Processing Letters, Volume 121, May 2017, Pages 11-16
10.1016/j.ipl.2017.01.005
null
cs.LG cs.SI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In 2014, Amin, Heidari, and Kearns proved that tree networks can be learned by observing only the infected set of vertices of the contagion process under the independent cascade model, in both the active and passive query models. They also showed empirically that simple extensions of their algorithms work on sparse networks. In this work, we focus on the active model. We prove that a simple modification of Amin et al.'s algorithm works on more general classes of networks, namely (i) networks with large girth and low path growth rate, and (ii) networks with bounded degree. This also provides partial theoretical explanation for Amin et al.'s experiments on sparse networks.
2017-05-30T00:00:00
no_new_dataset
false
0.712071
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.10060
Juan Jos\'e Murillo Fuentes
Francisco J. Simois, Juan J. Murillo-Fuentes
On the Power Spectral Density Applied to the Analysis of Old Canvases
null
null
null
null
cs.CV math.SP
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A routine task for art historians is painting diagnostics, such as dating or attribution. Signal processing of the X-ray image of a canvas provides useful information about its fabric. However, previous methods may fail when very old and deteriorated artworks or simply canvases of small size are studied. We present a new framework to analyze and further characterize the paintings from their radiographs. First, we start from a general analysis of lattices and provide new unifying results about the theoretical spectra of weaves. Then, we use these results to infer the main structure of the fabric, like the type of weave and the thread densities. We propose a practical estimation of these theoretical results from paintings with the averaged power spectral density (PSD), which provides a more robust tool. Furthermore, we found that the PSD provides a fingerprint that characterizes the whole canvas. We search and discuss some distinctive features we may find in that fingerprint. We apply these results to several masterpieces of the 17th and 18th centuries from the Museo Nacional del Prado to show that this approach yields accurate results in thread counting and is very useful for paintings comparison, even in situations where previous methods fail.
2017-05-30T00:00:00
no_new_dataset
false
0.710275
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.10074
Gunter Scharf
Gunter Scharf and Lam Dang
The hyperbolic heat transfer equation and the ablation problem: Theory and experiment
7 pages, no figure
null
null
null
physics.med-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We study the ablation problem for the hyperbolic heat equation in an axisymmetrical geometry which can be conveniently realized in the lab. We determine an analytic solution which shows the approach to steady state. The thermal relaxation time $\tau$ is best obtained from the small time behavior. The measurements give a surprisingly large $\tau$ of about 7 minutes for 0.5 % NaCl in water. This shows that the hyperbolic equation must certainly be used instead of the parabolic heat equation in the ablation problem of electrocardiology.
2017-05-30T00:00:00
no_new_dataset
false
0.71201
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.10091
{\O}yvind Ytrehus
\'Angela Barbero and {\O}yvind Ytrehus
Rate $(n-1)/n$ Systematic MDS Convolutional Codes over $GF(2^m)$
null
null
null
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A systematic convolutional encoder of rate $(n-1)/n$ and maximum degree $D$ generates a code of free distance at most ${\cal D} = D+2$ and, at best, a column distance profile (CDP) of $[2,3,\ldots,{\cal D}]$. A code is \emph{Maximum Distance Separable} (MDS) if it possesses this CDP. Applied on a communication channel over which packets are transmitted sequentially and which loses (erases) packets randomly, such a code allows the recovery from any pattern of $j$ erasures in the first $j$ $n$-packet blocks for $j<{\cal D}$, with a delay of at most $j$ blocks counting from the first erasure. This paper addresses the problem of finding the largest ${\cal D}$ for which a systematic rate $(n-1)/n$ code over $GF(2^m)$ exists, for given $n$ and $m$. In particular, constructions for rates $(2^m-1)/2^m$ and $(2^{m-1}-1)/2^{m-1}$ are presented which provide optimum values of ${\cal D}$ equal to 3 and 4, respectively. A search algorithm is also developed, which produces new codes for ${\cal D}$ for field sizes $2^m \leq 2^{14}$. Using a complete search version of the algorithm, the maximum value of ${\cal D}$, and codes that achieve it, are determined for all code rates $\geq 1/2$ and every field size $GF(2^m)$ for $m\leq 5$ (and for some rates for $m=6$).
2017-05-30T00:00:00
no_new_dataset
false
0.709067
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.10092
Mingming Li
Mingming Li, Rui Jiang, Shuzhi Sam Ge, Tong Heng Lee
Role Playing Learning for Socially Concomitant Mobile Robot Navigation
null
null
null
null
cs.RO cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we present the Role Playing Learning (RPL) scheme for a mobile robot to navigate socially with its human companion in populated environments. Neural networks (NN) are constructed to parameterize a stochastic policy that directly maps sensory data collected by the robot to its velocity outputs, while respecting a set of social norms. An efficient simulative learning environment is built with maps and pedestrians trajectories collected from a number of real-world crowd data sets. In each learning iteration, a robot equipped with the NN policy is created virtually in the learning environment to play itself as a companied pedestrian and navigate towards a goal in a socially concomitant manner. Thus, we call this process Role Playing Learning, which is formulated under a reinforcement learning (RL) framework. The NN policy is optimized end-to-end using Trust Region Policy Optimization (TRPO), with consideration of the imperfectness of robot's sensor measurements. Simulative and experimental results are provided to demonstrate the efficacy and superiority of our method.
2017-05-30T00:00:00
no_new_dataset
false
0.710644
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.10093
Ali Nassif
Cuauht\'emoc L\'opez-Mart\'in, Ali Bou Nassif, Alain Abran
A training process for improving the quality of software projects developed by a practitioner
null
null
10.1016/j.jss.2017.05.050
null
cs.SE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Background: The quality of a software product depends on the quality of the software process followed in developing the product. Therefore, many higher education institutions (HEI) and software organizations have implemented software process improvement (SPI) training courses to improve the software quality. Objective: Because the duration of a course is a concern for HEI and software organizations, we investigate whether the quality of software projects will be improved by reorganizing the activities of the ten assignments of the original personal software process (PSP) course into a modified PSP having fewer assignments (i.e., seven assignments). Method: The assignments were developed by following a modified PSP with fewer assignments but including the phases, forms, standards, and logs suggested in the original PSP. The measurement of the quality of the software assignments was based on defect density. Results: When the activities in the original PSP were reordered into fewer assignments, as practitioners progress through the PSP training, the defect density improved with statistical significance. Conclusions: Our modified PSP could be applied in academy and industrial environments which are concerned in the sense of reducing the PSP training time
2017-05-30T00:00:00
no_new_dataset
false
0.712033
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.10097
Aaron Bernstein
Aaron Bernstein
Deterministic Partially Dynamic Single Source Shortest Paths in Weighted Graphs
null
null
null
null
cs.DS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper we consider the decremental single-source shortest paths (SSSP) problem, where given a graph $G$ and a source node $s$ the goal is to maintain shortest distances between $s$ and all other nodes in $G$ under a sequence of online adversarial edge deletions. In their seminal work, Even and Shiloach [JACM 1981] presented an exact solution to the problem in unweighted graphs with only $O(mn)$ total update time over all edge deletions. Their classic algorithm was the state of the art for the decremental SSSP problem for three decades, even when approximate shortest paths are allowed. A series of results showed how to improve upon $O(mn)$ if approximation is allowed, culminating in a recent breakthrough of Henzinger, Krinninger and Nanongkai [FOCS 14], who presented a $(1+\epsilon)$-approximate algorithm for undirected weighted graphs whose total update time is near linear: $O(m^{1+o(1)}\log(W))$, where $W$ is the ratio of the heaviest to the lightest edge weight in the graph. In this paper they posed as a major open problem the question of derandomizing their result. Until very recently, all known improvements over the Even-Shiloach algorithm were randomized and required the assumption of a non-adaptive adversary. In STOC 2016, Bernstein and Chechik showed the first \emph{deterministic} algorithm to go beyond $O(mn)$ total update time: the algorithm is also $(1+\epsilon)$-approximate, and has total update time $\tilde{O}(n^2)$. In SODA 2017, the same authors presented an algorithm with total update time $\tilde{O}(mn^{3/4})$. However, both algorithms are restricted to undirected, unweighted graphs. We present the \emph{first} deterministic algorithm for \emph{weighted} undirected graphs to go beyond the $O(mn)$ bound. The total update time is $\tilde{O}(n^2 \log(W))$.
2017-05-30T00:00:00
no_new_dataset
false
0.708371
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.10104
Tigran Tonoyan
Magnus M. Halldorsson and Tigran Tonoyan
Universal Framework for Wireless Scheduling Problems
18 pages, 1 figure. Appeared in Proc. ICALP 2017
null
null
null
cs.NI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
An overarching issue in resource management of wireless networks is assessing their capacity: How much communication can be achieved in a network, utilizing all the tools available: power control, scheduling, routing, channel assignment and rate adjustment? We propose the first framework for approximation algorithms in the physical model that addresses these questions in full, including rate control. The approximations obtained are doubly logarithmic in the link length and rate diversity. Where previous bounds are known, this gives an exponential improvement. A key contribution is showing that the complex interference relationship of the physical model can be simplified into a novel type of amenable conflict graphs, at a small cost. We also show that the approximation obtained is provably the best possible for any conflict graph formulation.
2017-05-30T00:00:00
no_new_dataset
false
0.710037
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.10115
Jean Christoph Jung
Jean Christoph Jung, Carsten Lutz, Mauricio Martel, Thomas Schneider, Frank Wolter
Conservative Extensions in Guarded and Two-Variable Fragments
Full version of paper accepted at ICALP 2017
null
null
null
cs.LO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We investigate the decidability and computational complexity of (deductive) conservative extensions in fragments of first-order logic (FO), with a focus on the two-variable fragment FO$^2$ and the guarded fragment GF. We prove that conservative extensions are undecidable in any FO fragment that contains FO$^2$ or GF (even the three-variable fragment thereof), and that they are decidable and 2\ExpTime-complete in the intersection GF$^2$ of FO$^2$ and GF.
2017-05-30T00:00:00
no_new_dataset
false
0.706279
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.10116
Dominik Peters
Haris Aziz, Florian Brandl, Felix Brandt, Paul Harrenstein, Martin Olsen, Dominik Peters
Fractional Hedonic Games
25 pages. Journal version following papers at AAMAS-2014 and AAMAS-2015. Includes new NP^NP-hardness result
null
null
null
cs.GT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The work we present in this paper initiated the formal study of fractional hedonic games, coalition formation games in which the utility of a player is the average value he ascribes to the members of his coalition. Among other settings, this covers situations in which players only distinguish between friends and non-friends and desire to be in a coalition in which the fraction of friends is maximal. Fractional hedonic games thus not only constitute a natural class of succinctly representable coalition formation games, but also provide an interesting framework for network clustering. We propose a number of conditions under which the core of fractional hedonic games is non-empty and provide algorithms for computing a core stable outcome. By contrast, we show that the core may be empty in other cases, and that it is computationally hard in general to decide non-emptiness of the core.
2017-05-30T00:00:00
no_new_dataset
false
0.712424
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.10120
Vijay Kumar
Vijay Kumar, Anoop Namboodiri, Manohar Paluri, C V Jawahar
Pose-Aware Person Recognition
To appear in CVPR 2017
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Person recognition methods that use multiple body regions have shown significant improvements over traditional face-based recognition. One of the primary challenges in full-body person recognition is the extreme variation in pose and view point. In this work, (i) we present an approach that tackles pose variations utilizing multiple models that are trained on specific poses, and combined using pose-aware weights during testing. (ii) For learning a person representation, we propose a network that jointly optimizes a single loss over multiple body regions. (iii) Finally, we introduce new benchmarks to evaluate person recognition in diverse scenarios and show significant improvements over previously proposed approaches on all the benchmarks including the photo album setting of PIPA.
2017-05-30T00:00:00
no_new_dataset
false
0.704629
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.10124
Abdelmalik Moujahid
Abdelmalik Moujahid, Alicia D'Anjou, Manuel Gra\~na
Energy demands of diverse spiking cells from the neocortex, hippocampus, and thalamus
null
Frontiers in Computational Neuroscience, Volume 8, Pages 41, 2014
10.3389/fncom.2014.00041
null
math.DS physics.bio-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
It has long been known that neurons in the brain are not physiologically homogeneous. In response to current stimulus, they can fire several distinct patterns of action potentials that are associated with different physiological classes ranging from regular-spiking cells, fast-spiking cells, intrinsically bursting cells, and low-threshold cells. In this work we show that the high degree of variability in firing characteristics of action potentials among these cells is accompanied with a significant variability in the energy demands required to restore the concentration gradients after an action potential. The values of the metabolic energy were calculated for a wide range of cell temperatures and stimulus intensities following two different approaches. The first one is based on the amount of Na+ load crossing the membrane during a single action potential, while the second one focuses on the electrochemical energy functions deduced from the dynamics of the computational neuron models. The results show that the thalamocortical relay neuron is the most energy-efficient cell consuming between 7 and 18 nJ/cm2 for each spike generated, while both the regular and fast spiking cells from somatosensory cortex and the intrinsically-bursting cell from a cat visual cortex are the least energy-efficient, and can consume up to 100 nJ/cm2 per spike. The lowest values of these energy demands were achieved at higher temperatures and high external stimuli.
2017-05-30T00:00:00
no_new_dataset
false
0.710968
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.10125
Kohji Tsumura
Kohji Tsumura
Verification of the anecdote about Edwin Hubble and the Nobel Prize
4 pages, 1 figure, Proceedings of the Sixth Symposium on History of Astronomy (March 17 - 18, 2017, Japan)
null
null
null
physics.hist-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Edwin Powel Hubble is regarded as one of the most important astronomers of 20th century. In despite of his great contributions to the field of astronomy, he never received the Nobel Prize because astronomy was not considered as the field of the Nobel Prize in Physics at that era. There is an anecdote about the relation between Hubble and the Nobel Prize. According to this anecdote, the Nobel Committee decided to award the Nobel Prize in Physics in 1953 to Hubble as the first Nobel laureate as an astronomer (Christianson 1995). However, Hubble was died just before its announcement, and the Nobel prize is not awarded posthumously. Documents of the Nobel selection committee are open after 50 years, thus this anecdote can be verified. I confirmed that the Nobel selection committee endorsed Frederik Zernike as the Nobel laureate in Physics in 1953 on September 15th, 1953, which is 13 days before the Hubble's death in September 28th, 1953. I also confirmed that Hubble and Henry Norris Russell were nominated but they are not endorsed because the Committee concluded their astronomical works were not appropriate for the Nobel Prize in Physics.
2017-05-30T00:00:00
no_new_dataset
false
0.711569
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.10130
Murtadha AL-Sharuee
Murtadha Talib AL-Sharuee, Fei Liu, Mahardhika Pratama
An Automatic Contextual Analysis and Clustering Classifiers Ensemble approach to Sentiment Analysis
This article is submitted to a journal
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Products reviews are one of the major resources to determine the public sentiment. The existing literature on reviews sentiment analysis mainly utilizes supervised paradigm, which needs labeled data to be trained on and suffers from domain-dependency. This article addresses these issues by describes a completely automatic approach for sentiment analysis based on unsupervised ensemble learning. The method consists of two phases. The first phase is contextual analysis, which has five processes, namely (1) data preparation; (2) spelling correction; (3) intensifier handling; (4) negation handling and (5) contrast handling. The second phase comprises the unsupervised learning approach, which is an ensemble of clustering classifiers using a majority voting mechanism with different weight schemes. The base classifier of the ensemble method is a modified k-means algorithm. The base classifier is modified by extracting initial centroids from the feature set via using SentWordNet (SWN). We also introduce new sentiment analysis problems of Australian airlines and home builders which offer potential benchmark problems in the sentiment analysis field. Our experiments on datasets from different domains show that contextual analysis and the ensemble phases improve the clustering performance in term of accuracy, stability and generalization ability.
2017-05-30T00:00:00
no_new_dataset
false
0.710173
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.10143
Javier Ros
Javier Ros, Xabier Iriarte, Aitor Plaza, Vicente Mata
Simplification of multibody models by parameter reduction
24 pages, 14 figures
null
null
null
cs.RO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Model selection methods are used in different scientific contexts to represent a characteristic data set in terms of a reduced number of parameters. Apparently, these methods have not found their way into the literature on multibody systems dynamics. Multibody models can be considered parametric models in terms of their dynamic parameters, and model selection techniques can then be used to express these models in terms of a reduced number of parameters. These parameter-reduced models are expected to have a smaller computational complexity than the original one and still preserve the desired level of accuracy. They are also known to be good candidates for parameter estimation purposes. In this work, simulations of the actual model are used to define a data set that is representative of the system's standard working conditions. A parameter-reduced model is chosen and its parameter values estimated so that they minimize the prediction error on these data. To that end, model selection heuristics and normalized error measures are proposed. Using this methodology, two multibody systems with very different characteristic mobility are analyzed. Highly considerable reductions in the number of parameters and computational cost are obtained without compromising the accuracy of the reduced model too much. As an additional result, a generalization of the base parameter concept to the context of parameter-reduced models is proposed.
2017-05-30T00:00:00
no_new_dataset
false
0.709432
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.10146
Judith B\"utepage
Judith B\"utepage, Danica Kragic
Human-Robot Collaboration: From Psychology to Social Robotics
null
null
null
null
cs.RO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
With the advances in robotic technology, research in human-robot collaboration (HRC) has gained in importance. For robots to interact with humans autonomously they need active decision making that takes human partners into account. However, state-of-the-art research in HRC does often assume a leader-follower division, in which one agent leads the interaction. We believe that this is caused by the lack of a reliable representation of the human and the environment to allow autonomous decision making. This problem can be overcome by an embodied approach to HRC which is inspired by psychological studies of human-human interaction (HHI). In this survey, we review neuroscientific and psychological findings of the sensorimotor patterns that govern HHI and view them in a robotics context. Additionally, we study the advances made by the robotic community into the direction of embodied HRC. We focus on the mechanisms that are required for active, physical human-robot collaboration. Finally, we discuss the similarities and differences in the two fields of study which pinpoint directions of future research.
2017-05-30T00:00:00
no_new_dataset
false
0.710779
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1705.10152
Benjamin Kutschan
Benjamin Kutschan
Tangent Cones to TT Varieties
null
null
null
null
math.OC cs.LG math.AG math.NA
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
As already done for the matrix case for example in [Joe Harris, Algebraic Geometry - A first course, p.256] we give a parametrization of the Bouligand tangent cone of the variety of tensors of bounded TT rank. We discuss how the proof generalizes to any binary hierarchical format. The parametrization can be rewritten as an orthogonal sum of TT tensors. Its retraction onto the variety is particularly easy to compose. We also give an implicit description of the tangent cone as the solution of a system of polynomial equations.
2017-05-30T00:00:00
no_new_dataset
false
0.707675
2026-01-25T00:43:33.318544
davanstrien/ModernBERT-base-is-new-arxiv-dataset