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arXiv 2020年

作者： Vescovi, Rafael Li, Hanyu Kinnison, Jeffery Keçeli, Murat Salim, Misha Kasthuri, Narayanan Uram, Thomas D. Ferrier, Nicola Leadership Computing Facility Argonne National Laboratory LemontIL United States Department of Neurobiology University of Chicago ChicagoIL United States Dept. of Computer Science and Engineering University of Notre Dame Notre DameIN United States Computational Science Division Argonne National Laboratory LemontIL United States Mathematics and Computer Science Division Argonne National Laboratory LemontIL United States

We present a fully modular and scalable software pipeline for processing electron microscope (EM) images of brain slices into 3D visualization of individual neurons and demonstrate an end-to-end segmentation of a large EM volume using a supercomputer. Our pipeline scales multiple packages used by the EM community with minimal changes to the original source codes. We tested each step of the pipeline individually, on a workstation, a cluster, and a supercomputer. Furthermore, we can compose workflows from these operations using a Balsam database that can be triggered during the data acquisition or with the use of different front ends and control the granularity of the pipeline execution. We describe the implementation of our pipeline and modifications required to integrate and scale up existing codes. The modular nature of our environment enables diverse research groups to contribute to the pipeline without disrupting the workflow, i.e. new individual codes can be easily integrated for each step on the pipeline. © 2020, CC-BY.

关键词： Pipelines

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Time threshold for classification between 2D-touch and 3D-touch based on user's 3D-touch input 8

Time threshold for classification between 2D-touch and 3D-to...

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2018 8th International Workshop on Computer science and engineering, WCSE 2018

作者： Park, JinHyuck Nam, ChoonSung Lee, JangYeol Seo, Young Hoon Shin, DongRyeol Dept. Electric and Electrical Computer Engineering SungKyunKwan University Suwon Korea Republic of Dept. Applied Data Science SungKyunKwan University Suwon Korea Republic of

ISBN: (纸本)9789811178610

As 3D-Touch technology has recently developed, 3D-Touch technology, which was applied only to the touch display of mobile devices, has been introduced to various devices. Although many researches have proposed applying the 3D-Touch technology to various devices, these researches have been confined only to apply 3D-Touch technology without considering 2D-Touch technology. Therefore, there is no clear criterion for distinguishing between 2D-Touch and 3D-Touch. In this paper, we suggest a time threshold for distinguishing between 2D-Touch and 3D-Touch on a display that supports 3D-Touch. © Proceedings of 2018 the 8th International Workshop on Computer science and engineering, WCSE 2018. All rights reserved.

关键词： Three dimensional displays

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Leveraging randomized compiling for the QITE algorithm

arXiv

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arXiv 2021年

作者： Ville, Jean-Loup Morvan, Alexis Hashim, Akel Naik, Ravi K. Lu, Marie Mitchell, Bradley Kreikebaum, John-Mark O’Brien, Kevin P. Wallman, Joel J. Hincks, Ian Emerson, Joseph Smith, Ethan Younis, Ed Iancu, Costin Santiago, David I. Siddiqi, Irfan Quantum Nanoelectronics Laboratory Dept. of Physics University of California at Berkeley BerkeleyCA94720 United States Computational Research Division Lawrence Berkeley National Lab BerkeleyCA94720 United States Materials Sciences Division Lawrence Berkeley National Lab BerkeleyCA94720 United States Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology CambridgeMA02139 United States Inst. for Quantum Computing Dept. of Applied Mathematics University of Waterloo WaterlooONN2L 3G1 Canada Quantum Benchmark Inc. KitchenerONN2H 5G5 Canada

The success of the current generation of Noisy Intermediate-Scale Quantum (NISQ) hardware shows that quantum hardware may be able to tackle complex problems even without error correction. One outstanding issue is that of coherent errors arising from the increased complexity of these devices. These errors can accumulate through a circuit, making their impact on algorithms hard to predict and mitigate. Iterative algorithms like Quantum Imaginary Time Evolution are susceptible to these errors. This article presents the combination of both noise tailoring using Randomized Compiling and error mitigation with a purification. We also show that Cycle Benchmarking gives an estimate of the reliability of the purification. We apply this method to the Quantum Imaginary Time Evolution of a Transverse Field Ising Model and report an energy estimation and a ground state infidelity both below 1%. Our methodology is general and can be used for other algorithms and platforms. We show how combining noise tailoring and error mitigation will push forward the performance of NISQ devices. © 2021, CC BY.

关键词： Benchmarking

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Mechanics of mineralized collagen fibrils upon transient loads

arXiv

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arXiv 2020年

作者： Milazzo, Mario Jung, Gang Seob Danti, Serena Buehler, Markus J. Massachusetts Institute of Technology 77 Massachusetts Ave CambridgeMA02139 United States 56025 Italy Dept. of Civil and Industrial Engineering University of Pisa Largo L. Lazzarino 2 Pisa56122 Italy Center for Computational Science and Engineering Schwarzman College of Computing Massachusetts Institute of Technology 77 Massachusetts Ave CambridgeMA02139 United States

Collagen is a key structural protein in the human body, which undergoes mineralization during the formation of hard tissues. Earlier studies have described the mechanical behavior of bone at different scales highlighting material features across hierarchical structures. Here we present a study that aims to understand the mechanical properties of mineralized collagen fibrils upon tensile/compressive transient loads, investigating how the kinetic energy propagates and it is dissipated at the molecular scale, thus filling a gap of knowledge in this area. These specific features are the mechanisms that Nature has developed to passively dissipate stress and prevent structural failures. In addition to the mechanical properties of the mineralized fibrils, we observe distinct nanomechanical behaviors for the two regions (i.e., overlap and gap) of the Dperiod to highlight the effect of the mineralization. We notice decreasing trends for both wave speeds and Young’s moduli over input velocity with a marked strengthening effect in the gap region due to the accumulation of the hydroxyapatite. In contrast, the dissipative behavior is not affected by either loading conditions or the mineral percentage, showing a stronger damping effect upon faster inputs compatible to the bone behavior at the macroscale. Our results offers insights on the energy dissipative behavior of mineralized collagen composites to design and characterize bioinspired composites for replacement devices (e.g., prostheses for sound transmission or conduction) or optimized structures able to bear transient loads, e.g., impact, fatigue, in structural applications. Copyright © 2020, The Authors. All rights reserved.

关键词： Collagen

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Traffic Optimization Algorithms in Optical Networks For Real Time Traffic Analysis

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Optik 2022年

作者： Suresh Kumar. K Swati Vijay Shinde S. Venkata Lakshmi R.S. Sabeenian Koppisetti Durga Bhavani K.V.S.R. Murthy Department of Information Technology Saveetha Engineering College Tamil Nadu India Department of Computer Engineering Pimpri Chinchwad College of Engineering Pune India Dept. of Artificial Intelligence and Data Science Sri Krishna College of Engineering and Technology Coimbatore India Department of ECE Sona College of Technology Salem Department of Management Studies Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai India EEE Department & Dean (R&D) Aditya Group of Engineering Colleges

The rapid growth of metropolitan areas poses significant traffic control issues. Advanced telecommunication structures, such as the IoT (Internet of Things) technology, including wireless connections, produce enormous amounts of diverse traffic information. Conventional networking control approaches for tracking and information analysis confront certain obstacles and problems in specific systems, like reliability and efficient actual-time analysis of massive datasets. Furthermore, due to variables like gadget portability and connection diversity, the overall structure of internet activity, particularly in wireless networks, exhibits extremely complicated activity. The article aims to create a method for collecting high-quality, comprehensive information like transportation flowing strength, travel routes, and mean vehicle velocity. Simultaneously, information is gathered throughout the whole operational zone of junctions and neighboring highway segments under the city video security sensor perspective. More profound learning methods will be used within the communication domain for Networking Transport Management and Analytics (NTMA) activities such as traffic categorization and forecasting. The YOLOv3 artificial routing topology, as well as a SORT-accessible monitor, are used in our approach. Utilizing extended masking branches and improving its geometry of anchoring, overall essential efficiency in YOLO has been enhanced. We employed a technique of viewpoint conversion using parameters from actual pictures to global dimensions for computing overall vehicular velocities.

关键词： Networking Traffic Management and Analytics (NTMA) real-time surveillance traffic management and database processing

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Mass supply from Io to Jupiter's magnetosphere

arXiv

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arXiv 2024年

作者： Roth, L. Blöcker, A. de Kleer, K. Goldstein, D. Lellouch, E. Saur, J. Schmidt, C. Strobel, D.F. Tao, C. Tsuchiya, F. Dols, V. Huybrighs, H. Mura, A. Szalay, J.R. Badman, S.V. de Pater, I. Dott, A.-C. Kagitani, M. Klaiber, L. Koga, R. McEwen, A. Milby, Z. Retherford, K.D. Schlegel, S. Thomas, N. Tseng, W.L. Vorburger, A. KTH Royal Institute of Technology Space and Plasma Physics Stockholm Sweden Department of Earth and Environmental Sciences Ludwig Maximilian University of Munich Munich Germany Division of Geological and Planetary Sciences California Institute of Technology PasadenaCA91125 United States Dept. Aerospace Engineering and Engineering Mechanics The University of Texas at Austin AustinTX United States Observatoire de Paris Meudon France Institute of Geophysics and Meteorology University of Cologne Cologne Germany Center for Space Physics Boston University BostonMA United States Departments of Earth & Planetary Science and Physics & Astronomy Johns Hopkins University BaltimoreMD21218 United States National Institute of Information and Communications Technology Koganei Japan Graduate School of Science Tohoku University Sendai Japan Institute for Space Astrophysics and Planetology National Institute for Astrophysics Italy School of Cosmic Physics DIAS Dunsink Observatory Dublin Institute for Advanced Studies Dublin15 Ireland Space and Planetary Science Center Khalifa University Abu Dhabi United Arab Emirates Department of Mathematics Khalifa University Abu Dhabi United Arab Emirates Roma Italy Department of Astrophysical Sciences Princeton University PrincetonNJ United States Department of Physics Lancaster University LancasterLA1 4YB United Kingdom Department of Astronomy Department of Earth & Planetary Science University of California BerkeleyCA94720 United States Physics Institute University of Bern Bern3012 Switzerland School of Data Science Nagoya University Aichi Nagoya464-8601 Japan Department of Planetary Sciences University of Arizona TucsonAZ United States Southwest Research Institute San AntonioTX United States University of Texas at San Antonio San AntonioTX United States Department of Earth Sciences National Taiwan Normal University Taiwan

Since the Voyager mission flybys in 1979, we have known the moon Io to be both volcanically active and the main source of plasma in the vast magnetosphere of Jupiter. Material lost from Io forms neutral clouds, the Io plasma torus and ultimately the extended plasma sheet. This material is supplied from Io’s upper atmosphere and atmospheric loss is likely driven by plasma-interaction effects with possible contributions from thermal escape and photochemistry-driven escape. Direct volcanic escape is negligible. The supply of material to maintain the plasma torus has been estimated from various methods at roughly one ton per second. Most of the time the magnetospheric plasma environment of Io is stable on timescales from days to months. Similarly, Io’s atmosphere was found to have a stable average density on the dayside, although it exhibits lateral (longitudinal and latitudinal) and temporal (both diurnal and seasonal) variations. There is potential positive feedback in the Io torus supply: collisions of torus plasma with atmospheric neutrals are probably a significant loss process, which increases with torus density. The stability of the torus environment may be maintained by limiting mechanisms of either torus supply from Io or the loss from the torus by centrifugal interchange in the middle magnetosphere. Various observations suggest that occasionally (roughly 1 to 2 detections per decade) the plasma torus undergoes major transient changes over a period of several weeks, apparently overcoming possible stabilizing mechanisms. Such events (as well as more frequent minor changes) are commonly explained by some kind of change in volcanic activity that triggers a chain of reactions which modify the plasma torus state via a net change in supply of new mass. However, it remains unknown what kind of volcanic event (if any) can trigger events in torus and magnetosphere, whether Io’s atmosphere undergoes a general change before or during such events, and what processes could

关键词： Magnetosphere

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Estimating Confidence for Deep Neural Networks through Density modeling

Estimating Confidence for Deep Neural Networks through Densi...

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International Conference on Signal Processing and Communications, SPCOM

作者： Akshayvarun Subramanya Suraj Srinivas R. Venkatesh Babu Dept. of Computational and Data Sciences Indian Institute of Science Bangalore

ISBN: (纸本)9781538638224

State-of-the-art Neural Networks can be easily fooled into providing incorrect high-confidence predictions for images with small amounts of adversarial noise. Does this expose a flaw with deep neural networks, or do we simply need a better way to estimate confidence? In this paper we consider the problem of accurately estimating predictive confidence. We formulate this problem as that of density modelling, and show how traditional methods such as softmax produce poor estimates. To address this issue, we propose a novel confidence measure based on density modelling approaches. We test these measures on images distorted by blur, JPEG compression, random noise and adversarial noise. Experiments show that our confidence measure consistently shows reduced confidence scores in the presence of such distortions - a property which softmax lacks.

关键词： Distortion measurement Neural networks Noise measurement Distortion Uncertainty computational modeling Estimation

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Multi-task learning based survival analysis for predicting Alzheimer's disease progression with multi-source block-wise missing data

Multi-task learning based survival analysis for predicting A...

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2018 SIAM International Conference on data Mining, SDM 2018

作者： Li, Yan Yang, Tao Zhou, Jiayu Ye, Jieping Dept. of Computational Medicine and Bioinformatics University of Michigan Ann ArborMI United States Dept. of Computer Science Arizona State University TempeAZ United States Dept. of Computer Science and Engineering Michigan State University East LansingMI United States

There are many major diseases that remain incurable, e.g., cancer and Alzheimer's disease (AD). Hence, the preven-tion for these diseases has more impact than diagnosis and treatment. Survival analysis aims at predicting the time of occurrence of specific events of interest. It can be used to identify patients of high risk, which helps healthcare system to effectively allocate limited medical resources. In many real-world applications, such as healthcare analysis, a lot of datasets are collected from multiple data sources and ex-hibit a block-wise missing pattern, i.e., each patient takes different types of tests and receives various treatments, and each test/treatment associates with a corresponding set of features. However, all the existing survival analysis methods are designed for fully observed datasets and may not be di-rectly applied when such block-wise missing presented. The proposed work in this paper aims at addressing aforemen-tioned research challenges. Specifically, we employ a par-tition method that decomposes the multi-source block-wise missing data into the multiple completed sub-matrix;thus, transforms the original problem into a series of related multi-source survival analysis problems. To deal with these prob-lems, we propose a two-layer multi-task learning model that achieves both feature-level and source-level analysis, and the proposed model is able to take advantage of the structure in-formation in the block-wise missing pattern. We apply the proposed method in a real-world AD dataset to study the stage conversion of AD patients. Our experimental results show that the proposed method outperforms the other state-of-the-art methods. © 2018 by SIAM.

关键词： data mining

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Toward finding latent cities with non-negative matrix factorization

Toward finding latent cities with non-negative matrix factor...

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2018 Joint ACM IUI Workshops, ACMIUI-WS 2018

作者： Graells-Garrido, Eduardo Caro, DIego Parra, Denis Data Science Institute Universidad Del Desarrollo Telefonica RandD Santiago Chile Dept. of Computer Science Faculty of Engineering Pontificia Universidad Catolica Santiago Chile

In the last decade, digital footprints have been used to cluster population activity into functional areas of cities. However, a key aspect has been overlooked: we experience our cities not only by performing activities at specific destinations, but also by moving from one place to another. In this paper, we propose to analyze and cluster the city based on how people move through it. Particularly, we introduce Mobilicities, automatically generated travel patterns inferred from mobile phone network data using NMF, a matrix factorization model. We evaluate our method in a large city and we find that mobilicities reveal latent but at the same time interpretable mobility structures of the city. Our results provide evidence on how clustering and visualization of aggregated phone logs could be used in planning systems to interactively analyze city structure and population activity. © 2018 Copyright for the individual papers remains with the authors.

关键词： Non-negative matrix factorization

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Learning Representations with Strong Supervision for Image Search

Learning Representations with Strong Supervision for Image S...

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International Conference on Signal Processing and Communications, SPCOM

作者： Konda Reddy Mopuri Vishal B. Athreya R. Venkatesh Babu Dept. of Computational and Data Sciences Indian Institute of Science Bangalore India

ISBN: (纸本)9781538638224

Deep learning exploits large volumes of labeled data to learn powerful models. When the target dataset is small, it is a common practice to perform transfer learning using pretrained models to learn new task specific representations. However, pretrained CNNs for image recognition are provided with limited information about the image during training, which is label alone. Tasks such as scene retrieval suffer from features learned from this weak supervision and require stronger supervision to better understand the contents of the image. In this paper, we exploit the features learned from caption generating models to learn novel task specific image representations. In particular, we consider the state-of-the-art captioning system Show and Tell [1] and the dense region description model DenseCap [2]. We demonstrate that, owing to richer supervision provided during the process of training, the features learned by the captioning system perform better than those of CNNs. Further, we train a siamese network with a modified pair-wise loss to fuse the features learned by [1] and [2] and learn image representations suitable for retrieval. Experiments show that the proposed fusion exploits the complementary nature of the individual features and yields state-of-the art retrieval results on benchmark datasets.

关键词： Task analysis Training Image representation Visualization computational modeling Image retrieval Dogs

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