Collaborative Research: ATD: Theory and Algorithms for Discrete Curvatures on Network Data from Human Mobility and Monitoring

合作研究:ATD:人体移动和监测网络数据离散曲率的理论和算法

基本信息

  • 批准号:
    1737812
  • 负责人:
  • 金额:
    $ 10万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2017
  • 资助国家:
    美国
  • 起止时间:
    2017-08-15 至 2020-07-31
  • 项目状态:
    已结题

项目摘要

New developments in technologies of embedded systems, sensors, and wireless communications provide great potential to improve the safety and security of the physical and social environment we live in. These technologies can help identify and mitigate unfortunate accidents, emergency events, and malicious attacks. This project seeks to develop mathematical tools and algorithms based on discrete curvatures for the purpose of understanding and detecting community structures and anomalies in networks that can be of crucial value in many applications. The project considers high level mobility patterns, community structures, and anomalies as well as finer details such as who is where. The mathematical tools to be developed will be useful in other networks (for example, protein-protein interactions in biological networks). This project will investigate mathematical problems arising the analysis of real-time spatial and temporal human mobility data. The focus will be on the community detection problem on graphs by using discrete Ricci curvatures and discrete curvature flows on graphs. The problem is to extract stable groups in human mobility patterns, which will serve as the traffic norm for detecting abnormal patterns that can be tied to criminal or terroristic events. To detect these stable groups, or communities, the main observation is that community structures in a network resemble well known geometric phenomena such as thick-thin decompositions in Riemannian geometry. Inspired by Riemannian geometry and the success of Hamilton-Perelman's Ricci flow program, this work investigates how to use discrete curvatures and discrete curvature flows to detect community structure in a network. Preliminary investigations show that the proposed method has great potential and can detect communities with high accuracy. This potential prompts PIs to examine computationally feasible definitions of discrete Ricci curvatures on weighted networks. The important work of Ollivier on discrete Ricci curvature is the starting point of this investigation. The drawback of Ollivier's curvature is that it is computationally expensive -- almost impossible to compute the proposed discrete curvature flow on large networks containing more than a million nodes. As such, the main task in this work is to find computationally feasible Ricci curvatures where the discrete curvature flow can be computed in real time for large networks. The affirmative resolution of this work will be useful in pure mathematical research and computer science. The work will also develop software for practical use.
嵌入式系统、传感器和无线通信技术的新发展为改善我们所生活的物理和社会环境的安全性提供了巨大的潜力。这些技术可以帮助识别和减轻不幸的事故、紧急事件和恶意攻击。该项目旨在开发基于离散曲率的数学工具和算法,以理解和检测网络中的社区结构和异常,这在许多应用中具有至关重要的价值。该项目考虑了高层次的流动模式、社区结构和异常情况,以及更精细的细节,如谁在哪里。待开发的数学工具将在其他网络中有用(例如,生物网络中的蛋白质-蛋白质相互作用)。该项目将研究实时时空人类流动数据分析中出现的数学问题。重点讨论了离散Ricci曲率和离散曲率流在图上的群体检测问题。问题是如何从人类流动模式中提取出稳定的群体,这些群体将作为交通规范,用于检测可能与犯罪或恐怖事件有关的异常模式。为了检测这些稳定的群体或群落,主要观察是网络中的群落结构类似于黎曼几何中的厚薄分解等众所周知的几何现象。受黎曼几何和Hamilton-Perelman的Ricci流程序的成功启发,这项工作研究了如何使用离散曲率和离散曲率流来检测网络中的社区结构。初步研究表明,该方法具有很大的潜力,能够以较高的准确率检测出群落。这种可能性促使pi检查加权网络上离散里奇曲率的计算可行定义。奥利维尔关于离散里奇曲率的重要工作是这一研究的起点。奥利维尔曲率的缺点是计算成本很高——在包含超过一百万个节点的大型网络上计算所提出的离散曲率流几乎是不可能的。因此,本工作的主要任务是寻找计算上可行的Ricci曲率,其中可以实时计算大型网络的离散曲率流。这项工作的肯定解析将有助于纯数学研究和计算机科学。这项工作还将开发实际使用的软件。

项目成果

期刊论文数量(13)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
A Geometric Understanding of Deep Learning
对深度学习的几何理解
  • DOI:
    10.1016/j.eng.2019.09.010
  • 发表时间:
    2020-03-01
  • 期刊:
  • 影响因子:
    12.8
  • 作者:
    Lei, Na;An, Dongsheng;Gu, Xianfeng
  • 通讯作者:
    Gu, Xianfeng
Ae-OT: a New Generative Model based on Extended Semi-discrete Optimal transport
  • DOI:
  • 发表时间:
    2020-04
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Dongsheng An;Yang Guo;Na Lei;Zhongxuan Luo;S. Yau;X. Gu
  • 通讯作者:
    Dongsheng An;Yang Guo;Na Lei;Zhongxuan Luo;S. Yau;X. Gu
AE-OT-GAN: Training GANs from data specific latent distribution
  • DOI:
    10.1007/978-3-030-58574-7_33
  • 发表时间:
    2020-01
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Dongsheng An;Yang Guo;Min Zhang;Xin Qi;Na Lei;S. Yau;X. Gu
  • 通讯作者:
    Dongsheng An;Yang Guo;Min Zhang;Xin Qi;Na Lei;S. Yau;X. Gu
Modeling the Space of Point Landmark Constrained Diffeomorphisms
  • DOI:
    10.1007/978-3-030-58577-8_22
  • 发表时间:
    2020-08
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Chengfeng Wen;Yang Guo;X. Gu
  • 通讯作者:
    Chengfeng Wen;Yang Guo;X. Gu
Automatic and Robust Skull Registration Based on Discrete Uniformization
{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ monograph.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ sciAawards.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ conferencePapers.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ patent.updateTime }}

Jie Gao其他文献

Few-shot learning for short text classification
短文本分类的少样本学习
  • DOI:
    10.1007/s11042-018-5772-4
  • 发表时间:
    2018
  • 期刊:
  • 影响因子:
    3.6
  • 作者:
    Leiming Yan;Yuhui Zheng;Jie Gao
  • 通讯作者:
    Jie Gao
Mucin2 is Required for Probiotic Agents-Mediated Blocking Effects on Meningitic E. coli-Induced Pathogenicities.
Mucin2 是益生菌介导的对脑膜炎大肠杆菌诱导的致病性的阻断作用所必需的。
  • DOI:
    10.4014/jmb.1502.02010
  • 发表时间:
    2015-10
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Jingyi Yu;Xiaolong He;Puthiyakunnon S;Liang Peng;Yan Li;Li-Sha Wu;Wen Ling Peng;Ya Zhang;Jie Gao;Yao-Yuan Zhang;Swapna Boddu;Ming Long;Hong Cao;Sheng-He Huang
  • 通讯作者:
    Sheng-He Huang
The Existence of Homoclinic Solutions for Second Order Differential Equation
  • DOI:
    10.4028/www.scientific.net/amm.195-196.728
  • 发表时间:
    2012-08
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Jie Gao
  • 通讯作者:
    Jie Gao
Study on photodissociation and photoconversion characteristics of CS2 in O2/O3 environment using real-time conversion products obtained by UV-DOAS
利用UV-DOAS获得的实时转换产物研究CS2在O2/O3环境中的光解离和光转换特性
Nonylphenol ethoxylates biodegradation increases estrogenicity of textile wastewater in biological treatment systems
壬基酚聚氧乙烯醚生物降解增加生物处理系统中纺织废水的雌激素性
  • DOI:
  • 发表时间:
    2020
  • 期刊:
  • 影响因子:
    12.8
  • 作者:
    Xiwei He;Zhaodong Qi;Jie Gao;Kailong Huang;Mei Li;Dirk Springael;Xu-xiang Zhang
  • 通讯作者:
    Xu-xiang Zhang

Jie Gao的其他文献

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

{{ truncateString('Jie Gao', 18)}}的其他基金

CRCNS Research Proposal: Modeling Human Brain Development as a Dynamic Multi-Scale Network Optimization Process
CRCNS 研究提案:将人脑发育建模为动态多尺度网络优化过程
  • 批准号:
    2207440
  • 财政年份:
    2022
  • 资助金额:
    $ 10万
  • 项目类别:
    Continuing Grant
Collaborative Research: AF: Small: Promoting Social Learning Amid Interference in the Age of Social Media
合作研究:AF:小:在社交媒体时代的干扰下促进社交学习
  • 批准号:
    2208663
  • 财政年份:
    2022
  • 资助金额:
    $ 10万
  • 项目类别:
    Standard Grant
Collaborative Research: Infrared Chiral Metasurface Enhanced Vibrational Circular Dichroism Biomolecule Sensing
合作研究:红外手性超表面增强振动圆二色性生物分子传感
  • 批准号:
    2230069
  • 财政年份:
    2022
  • 资助金额:
    $ 10万
  • 项目类别:
    Standard Grant
Collaborative Research: 2D ferroelectric nonlinear metasurface holograms
合作研究:二维铁电非线性超表面全息图
  • 批准号:
    2226875
  • 财政年份:
    2022
  • 资助金额:
    $ 10万
  • 项目类别:
    Standard Grant
Collaborative Research: PPoSS: LARGE: Principles and Infrastructure of Extreme Scale Edge Learning for Computational Screening and Surveillance for Health Care
合作研究:PPoSS:大型:用于医疗保健计算筛查和监视的超大规模边缘学习的原理和基础设施
  • 批准号:
    2118953
  • 财政年份:
    2021
  • 资助金额:
    $ 10万
  • 项目类别:
    Continuing Grant
CAREER: Flat Singular Optics: Generation and Detection of Optical Vortex Beams with Plasmonic Metasurfaces in Linear and Nonlinear Regimes
职业:平面奇异光学:在线性和非线性体系中使用等离激元超表面生成和检测光学涡旋光束
  • 批准号:
    2204163
  • 财政年份:
    2021
  • 资助金额:
    $ 10万
  • 项目类别:
    Standard Grant
Collaborative Research: From Brains to Society: Neural Underpinnings of Collective Behaviors Via Massive Data and Experiments
合作研究:从大脑到社会:通过大量数据和实验研究集体行为的神经基础
  • 批准号:
    2126582
  • 财政年份:
    2021
  • 资助金额:
    $ 10万
  • 项目类别:
    Continuing Grant
Collaborative Research: From Brains to Society: Neural Underpinnings of Collective Behaviors Via Massive Data and Experiments
合作研究:从大脑到社会:通过大量数据和实验研究集体行为的神经基础
  • 批准号:
    1939459
  • 财政年份:
    2019
  • 资助金额:
    $ 10万
  • 项目类别:
    Continuing Grant
CAREER: Flat Singular Optics: Generation and Detection of Optical Vortex Beams with Plasmonic Metasurfaces in Linear and Nonlinear Regimes
职业:平面奇异光学:在线性和非线性体系中使用等离激元超表面生成和检测光学涡旋光束
  • 批准号:
    1653032
  • 财政年份:
    2017
  • 资助金额:
    $ 10万
  • 项目类别:
    Standard Grant
NeTS: Small: Geometric and Topological Analysis on Trajectory Sensing: Collection, Classification and Anonymization
NeTS:小型:轨迹感知的几何和拓扑分析:收集、分类和匿名化
  • 批准号:
    1618391
  • 财政年份:
    2016
  • 资助金额:
    $ 10万
  • 项目类别:
    Standard Grant

相似国自然基金

Research on Quantum Field Theory without a Lagrangian Description
  • 批准号:
    24ZR1403900
  • 批准年份:
    2024
  • 资助金额:
    0.0 万元
  • 项目类别:
    省市级项目
Cell Research
  • 批准号:
    31224802
  • 批准年份:
    2012
  • 资助金额:
    24.0 万元
  • 项目类别:
    专项基金项目
Cell Research
  • 批准号:
    31024804
  • 批准年份:
    2010
  • 资助金额:
    24.0 万元
  • 项目类别:
    专项基金项目
Cell Research (细胞研究)
  • 批准号:
    30824808
  • 批准年份:
    2008
  • 资助金额:
    24.0 万元
  • 项目类别:
    专项基金项目
Research on the Rapid Growth Mechanism of KDP Crystal
  • 批准号:
    10774081
  • 批准年份:
    2007
  • 资助金额:
    45.0 万元
  • 项目类别:
    面上项目

相似海外基金

Collaborative Research: ATD: Fast Algorithms and Novel Continuous-depth Graph Neural Networks for Threat Detection
合作研究:ATD:用于威胁检测的快速算法和新颖的连续深度图神经网络
  • 批准号:
    2219956
  • 财政年份:
    2023
  • 资助金额:
    $ 10万
  • 项目类别:
    Standard Grant
Collaborative Research: ATD: a-DMIT: a novel Distributed, MultI-channel, Topology-aware online monitoring framework of massive spatiotemporal data
合作研究:ATD:a-DMIT:一种新颖的分布式、多通道、拓扑感知的海量时空数据在线监测框架
  • 批准号:
    2220495
  • 财政年份:
    2023
  • 资助金额:
    $ 10万
  • 项目类别:
    Standard Grant
Collaborative Research: ATD: Rapid Structure Recovery and Outlier Detection in Multidimensional Data
合作研究:ATD:多维数据中的快速结构恢复和异常值检测
  • 批准号:
    2319370
  • 财政年份:
    2023
  • 资助金额:
    $ 10万
  • 项目类别:
    Standard Grant
Collaborative Research: ATD: Geospatial Modeling and Risk Mitigation for Human Movement Dynamics under Hurricane Threats
合作研究:ATD:飓风威胁下人类运动动力学的地理空间建​​模和风险缓解
  • 批准号:
    2319552
  • 财政年份:
    2023
  • 资助金额:
    $ 10万
  • 项目类别:
    Standard Grant
Collaborative Research: ATD: Fast Algorithms and Novel Continuous-depth Graph Neural Networks for Threat Detection
合作研究:ATD:用于威胁检测的快速算法和新颖的连续深度图神经网络
  • 批准号:
    2219904
  • 财政年份:
    2023
  • 资助金额:
    $ 10万
  • 项目类别:
    Standard Grant
Collaborative Research: ATD: Rapid Structure Recovery and Outlier Detection in Multidimensional Data
合作研究:ATD:多维数据中的快速结构恢复和异常值检测
  • 批准号:
    2319371
  • 财政年份:
    2023
  • 资助金额:
    $ 10万
  • 项目类别:
    Standard Grant
Collaborative Research: ATD: Rapid Structure Recovery and Outlier Detection in Multidimensional Data
合作研究:ATD:多维数据中的快速结构恢复和异常值检测
  • 批准号:
    2319372
  • 财政年份:
    2023
  • 资助金额:
    $ 10万
  • 项目类别:
    Standard Grant
Collaborative Research: ATD: Geospatial Modeling and Risk Mitigation for Human Movement Dynamics under Hurricane Threats
合作研究:ATD:飓风威胁下人类运动动力学的地理空间建​​模和风险缓解
  • 批准号:
    2319551
  • 财政年份:
    2023
  • 资助金额:
    $ 10万
  • 项目类别:
    Standard Grant
ATD: Collaborative Research: A Geostatistical Framework for Spatiotemporal Extremes
ATD:协作研究:时空极值的地统计框架
  • 批准号:
    2220523
  • 财政年份:
    2023
  • 资助金额:
    $ 10万
  • 项目类别:
    Standard Grant
ATD: Collaborative Research: A Geostatistical Framework for Spatiotemporal Extremes
ATD:协作研究:时空极值的地统计框架
  • 批准号:
    2220529
  • 财政年份:
    2023
  • 资助金额:
    $ 10万
  • 项目类别:
    Standard Grant
{{ showInfoDetail.title }}

作者:{{ showInfoDetail.author }}

知道了