咨询与建议

限定检索结果

文献类型

  • 382 篇 期刊文献
  • 116 篇 会议

馆藏范围

  • 498 篇 电子文献
  • 0 种 纸本馆藏

日期分布

学科分类号

  • 285 篇 理学
    • 139 篇 数学
    • 77 篇 物理学
    • 65 篇 统计学(可授理学、...
    • 64 篇 生物学
    • 33 篇 系统科学
    • 25 篇 化学
    • 15 篇 大气科学
  • 257 篇 工学
    • 101 篇 计算机科学与技术...
    • 68 篇 软件工程
    • 38 篇 生物工程
    • 36 篇 生物医学工程(可授...
    • 29 篇 控制科学与工程
    • 24 篇 材料科学与工程(可...
    • 24 篇 电气工程
    • 24 篇 信息与通信工程
    • 23 篇 动力工程及工程热...
    • 18 篇 电子科学与技术(可...
    • 18 篇 土木工程
    • 16 篇 化学工程与技术
    • 15 篇 光学工程
    • 14 篇 环境科学与工程(可...
    • 13 篇 力学(可授工学、理...
  • 68 篇 医学
    • 54 篇 临床医学
    • 33 篇 基础医学(可授医学...
    • 19 篇 药学(可授医学、理...
    • 14 篇 公共卫生与预防医...
  • 65 篇 管理学
    • 43 篇 管理科学与工程(可...
    • 21 篇 工商管理
  • 20 篇 法学
    • 18 篇 社会学
  • 18 篇 农学
  • 14 篇 经济学
    • 12 篇 应用经济学
  • 12 篇 教育学
  • 4 篇 文学
  • 3 篇 艺术学
  • 2 篇 军事学

主题

  • 9 篇 machine learning
  • 8 篇 statistics
  • 7 篇 predictive model...
  • 6 篇 deep learning
  • 5 篇 solitons
  • 4 篇 covid-19
  • 4 篇 electroencephalo...
  • 4 篇 cosmology
  • 4 篇 bioinformatics
  • 4 篇 engineering educ...
  • 4 篇 synchronization
  • 4 篇 forecasting
  • 4 篇 training
  • 3 篇 neurons
  • 3 篇 dynamical system...
  • 3 篇 modeling
  • 3 篇 noise measuremen...
  • 3 篇 neural networks
  • 3 篇 noise
  • 3 篇 monitoring

机构

  • 11 篇 health managemen...
  • 11 篇 department of ap...
  • 9 篇 health systems a...
  • 9 篇 julius centre fo...
  • 9 篇 department of in...
  • 9 篇 department of co...
  • 9 篇 department of in...
  • 9 篇 department of el...
  • 9 篇 department of in...
  • 8 篇 karachi pakistan
  • 8 篇 department of pu...
  • 8 篇 center of comple...
  • 7 篇 department of ph...
  • 7 篇 department of co...
  • 7 篇 university centr...
  • 7 篇 department of co...
  • 7 篇 hydrologic scien...
  • 6 篇 kavli institute ...
  • 6 篇 department of co...
  • 6 篇 physics division...

作者

  • 11 篇 carr lincoln d.
  • 11 篇 ombao hernando
  • 7 篇 schmidt michael ...
  • 7 篇 chu dinh-toi
  • 7 篇 abu-gharbieh ema...
  • 7 篇 benson david a.
  • 7 篇 jasra ajay
  • 6 篇 bärnighausen til...
  • 6 篇 whitehorn n.
  • 6 篇 everett w.
  • 6 篇 sievers c.
  • 6 篇 halverson n.w.
  • 6 篇 benson b.a.
  • 6 篇 smecher g.
  • 6 篇 padin s.
  • 6 篇 chattu vijay kum...
  • 6 篇 ruhl j.e.
  • 6 篇 bender a.n.
  • 6 篇 alahdab fares
  • 6 篇 schaffer k.k.

语言

  • 476 篇 英文
  • 18 篇 其他
  • 2 篇 中文
检索条件"机构=Program in Engineering Statistics"
498 条 记 录,以下是221-230 订阅
排序:
scTenifoldXct: A semi-supervised method for predicting cell-cell interactions and mapping cellular communication graphs
收藏 引用
Cell systems 2023年 第4期14卷 302-311.e4页
作者: Yongjian Yang Guanxun Li Yan Zhong Qian Xu Yu-Te Lin Cristhian Roman-Vicharra Robert S Chapkin James J Cai Department of Electrical and Computer Engineering Texas A&M University College Station TX 77843 USA. Department of Statistics Texas A&M University College Station TX 77843 USA. Key Laboratory of Advanced Theory and Application in Statistics and Data Science-MOE School of Statistics East China Normal University 3663 North Zhongshan Road Shanghai 200062 China. Department of Veterinary Integrative Biosciences Texas A&M University College Station TX 77843 USA. Graduate Institute of Biomedical Electronics and Bioinformatics National Taiwan University Taipei Taiwan. Department of Nutrition and the Program in Integrative Nutrition & Complex Diseases Texas A&M University College Station TX 77843 USA. Electronic address: r-chapkin@tamu.edu. Department of Electrical and Computer Engineering Texas A&M University College Station TX 77843 USA Department of Veterinary Integrative Biosciences Texas A&M University College Station TX 77843 USA Interdisciplinary Program of Genetics Texas A&M University College Station TX 77843 USA. Electronic address: jcai@tamu.edu.
We present scTenifoldXct, a semi-supervised computational tool for detecting ligand-receptor (LR)-mediated cell-cell interactions and mapping cellular communication graphs. Our method is based on manifold alignment, u... 详细信息
来源: 评论
Two-dimensional Bose-Hubbard model for helium on graphene
arXiv
收藏 引用
arXiv 2021年
作者: Yu, Jiangyong Lauricella, Ethan Elsayed, Mohamed Shepherd, Kenneth Nichols, Nathan S. Lombardi, Todd Kim, Sang Wook Wexler, Carlos Vanegas, Juan M. Lakoba, Taras Kotov, Valeri N. Del Maestro, Adrian Department of Physics University of Vermont BurlingtonVT05405 United States Materials Science Program University of Vermont BurlingtonVT05405 United States Department of Physics and Astronomy University of Missouri ColumbiaMO65211 United States Department of Mathematics & Statistics University of Vermont BurlingtonVT05405 United States Department of Physics and Astronomy University of Tennessee KnoxvilleTN37996 United States Min H. Kao Department of Electrical Engineering and Computer Science University of Tennessee KnoxvilleTN37996 United States
An exciting development in the field of correlated systems is the possibility of realizing two-dimensional (2D) phases of quantum matter. For a systems of bosons, an example of strong correlations manifesting themselv... 详细信息
来源: 评论
Spiral wave dynamics in a neuronal network model
arXiv
收藏 引用
arXiv 2024年
作者: Souza, Diogo L.M. Borges, Fernando S. Gabrick, Enrique C. Bentivoglio, Lucas E. Protachevicz, Paulo R. dos Santos, Vagner Viana, Ricardo L. Caldas, Ibere L. Iarosz, Kelly C. Batista, Antonio M. Kurths, Jürgen Graduate Program in Sciences State University of Ponta Grossa PR Ponta Grossa84030-900 Brazil Department of Physiology and Pharmacology State University of New York Downstate Health Sciences University BrooklynNY United States Center for Mathematics Computation and Cognition Federal University of ABC SP São Bernardo do Campo09606-045 Brazil Department of Physics Humboldt University Berlin Newtonstraße 15 Berlin12489 Germany Potsdam Institute for Climate Impact Research Telegrafenberg A31 Potsdam14473 Germany Institute of Physics University of São Paulo SP São Paulo05508-090 Brazil Department of Physics Federal University of Paraná PR Curitiba81530-000 Brazil Exact and Natural Sciences and Engineering UNIFATEB University Center PR Telêmaco Borba84266-010 Brazil Department of Physics State University of Ponta Grossa PR Ponta Grossa84030-900 Brazil Department of Mathematics and Statistics State University of Ponta Grossa PR Ponta Grossa84030-900 Brazil
Spiral waves are spatial-temporal patterns that can emerge in different systems as heart tissues, chemical oscillators, ecological networks and the brain. These waves have been identified in the neocortex of turtles, ... 详细信息
来源: 评论
Design and Application Data Collection for integrated evaluation and monitoring
收藏 引用
IOP Conference Series: Materials Science and engineering 2021年 第1期1088卷
作者: Muhammad Hidayatullah Agus Teguh Wahyudi Shinta Esabella Titi Andriani G Gunawan Faculty of Engineering Universitas Teknologi Sumbawa Indonesia. 84371 Office of Informatics and Statistics Communication Sumbawa Regency Indonesia. Physics Education Study Program Faculty of Teacher Training and Education Universitas Mataram Indonesia. 83125
The process of data collection of tax subjects and objects at the Regional Revenue Agency (BAPENDA) of Sumbawa Regency is still manual, where the subject and tax object data are still managed in the form of records on...
来源: 评论
DeePN2: A deep learning-based non-Newtonian hydrodynamic model
arXiv
收藏 引用
arXiv 2021年
作者: Fang, Lidong Ge, Pei Zhang, Lei Weinan, E. Lei, Huan Department of Computational Mathematics Science and Engineering Michigan State University MI48824 United States School of Mathematical Sciences Institute of Natural Sciences and MOE-LSC Shanghai Jiao Tong University 800 Dongchuan Road Shanghai200240 China Center for Machine Learning Research School of Mathematical Sciences Peking University Beijing100871 China AI for Science Institute Beijing100080 China Department of Mathematics and Program in Applied and Computational Mathematics Princeton University NJ08544 United States Department of Statistics and Probability Michigan State University MI48824 United States
A long standing problem in the modeling of non-Newtonian hydrodynamics of polymeric flows is the availability of reliable and interpretable hydrodynamic models that faithfully encode the underlying micro-scale polymer... 详细信息
来源: 评论
Classification of EEG-based brain connectivity networks in schizophrenia using a multi-domain connectome convolutional neural network
arXiv
收藏 引用
arXiv 2019年
作者: Phang, Chun-Ren Ting, Chee-Ming Noman, Fuad Ombao, Hernando School of Biomedical Engineering & Health Sciences Universiti Teknologi Malaysia Skudai Johor81310 Malaysia Statistics Program King Abdullah University of Science and Technology Thuwal23955 Saudi Arabia
Objective: We exploit altered patterns in brain functional connectivity as features for automatic discriminative analysis of neuropsychiatric patients. Deep learning methods have been introduced to functional network ... 详细信息
来源: 评论
Modeling the number of confirmed cases of COVID-19 in East Java using negative binomial regression based on least square spline estimator
收藏 引用
AIP Conference Proceedings 2024年 第1期3083卷
作者: Arip Ramadan Nur Chamidah I. Nyoman Budiantara Student of Doctoral Study Program of Mathematics and Natural Sciences Faculty of Science and Technology Airlangga University Surabaya 60115 Indonesia. Department of Information System School of Industrial and System Engineering Telkom University Surabaya 60231 Indonesia. Department of Mathematics Faculty of Science and Technology Airlangga University Surabaya 60115 Indonesia. Research Group of Statistical Modeling in Life Science Faculty of Science and Technology Airlangga University Surabaya 60115 Indonesia. Department of Statistics Faculty of Sciences and Data Analytics Sepuluh Nopember Institute of Technology Surabaya 60111 Indonesia.
The East Java Province has experienced a significant surge in number of confirmed cases of COVID-19. This study endeavors to investigate the potential correlation between weather conditions and the incidence of number...
来源: 评论
Which ads to show? Advertisement image assessment with auxiliary information via multi-step modality fusion
arXiv
收藏 引用
arXiv 2019年
作者: Park, Kyung-Wha Lee, JungHoon Kwon, Sunyoung Ha, Jung-Woo Kim, Kyung-Min Zhang, Byoung-Tak Interdisciplinary Program in Neuroscience Seoul National University Statistics and Actuarial Science Soongsil University Clova AI Research NAVER Corp Department of Computer Science and Engineering Seoul National University Surromind Robotics
Assessing aesthetic preference is a fundamental task related to human cognition. It can also contribute to various practical applications such as image creation for online advertisements. Despite crucial influences of... 详细信息
来源: 评论
Artificial intelligence for modelling infectious disease epidemics
收藏 引用
Nature 2025年 第8051期638卷 623-635页
作者: Kraemer, Moritz U. G. Tsui, Joseph L.-H. Chang, Serina Y. Lytras, Spyros Khurana, Mark P. Vanderslott, Samantha Bajaj, Sumali Scheidwasser, Neil Curran-Sebastian, Jacob Liam Semenova, Elizaveta Zhang, Mengyan Unwin, H. Juliette T. Watson, Oliver J. Mills, Cathal Dasgupta, Abhishek Ferretti, Luca Scarpino, Samuel V. Koua, Etien Morgan, Oliver Tegally, Houriiyah Paquet, Ulrich Moutsianas, Loukas Fraser, Christophe Ferguson, Neil M. Topol, Eric J. Duchêne, David A. Stadler, Tanja Kingori, Patricia Parker, Michael J. Dominici, Francesca Shadbolt, Nigel Suchard, Marc A. Ratmann, Oliver Flaxman, Seth Holmes, Edward C. Gomez-Rodriguez, Manuel Schölkopf, Bernhard Donnelly, Christl A. Pybus, Oliver G. Cauchemez, Simon Bhatt, Samir Pandemic Sciences Institute University of Oxford Oxford United Kingdom Department of Biology University of Oxford Oxford United Kingdom Department of Electrical Engineering and Computer Science University of California Berkeley Berkeley CA United States UCSF UC Berkeley Joint Program in Computational Precision Health Berkeley CA United States Division of Systems Virology Department of Microbiology and Immunology The Institute of Medical Science The University of Tokyo Tokyo Japan Section of Epidemiology Department of Public Health University of Copenhagen Copenhagen Denmark Oxford Vaccine Group University of Oxford and NIHR Oxford Biomedical Research Centre Oxford United Kingdom Department of Epidemiology and Biostatistics Imperial College London London United Kingdom Department of Computer Science University of Oxford Oxford United Kingdom School of Mathematics University of Bristol Bristol United Kingdom MRC Centre for Global Infectious Disease Analysis School of Public Health Imperial College London London United Kingdom Department of Statistics University of Oxford Oxford United Kingdom Doctoral Training Centre University of Oxford Oxford United Kingdom Institute for Experiential AI Northeastern University MA Boston Thailand Santa Fe Institute Santa Fe NM United States World Health Organization Regional Office for Africa Brazzaville Congo WHO Hub for Pandemic and Epidemic Intelligence Health Emergencies Programme World Health Organization Berlin Germany Centre for Epidemic Response and Innovation (CERI) School for Data Science and Computational Thinking Stellenbosch University Stellenbosch South Africa African Institute for Mathematical Sciences (AIMS) South Africa Muizenberg Cape Town South Africa Genomics England London United Kingdom Scripps Research La Jolla CA United States Department of Biosystems Science and Engineering ETH Zürich Basel Switzerland Swiss Institute of Bioinformatics Lausanne Switzerland The Ethox Centre Nuffield
Infectious disease threats to individual and public health are numerous, varied and frequently unexpected. Artificial intelligence (AI) and related technologies, which are already supporting human decision making in e...
来源: 评论
Inferring a network from dynamical signals at its nodes
arXiv
收藏 引用
arXiv 2020年
作者: Weistuch, Corey Agozzino, Luca Mujica-Parodi, Lilianne R. Dill, Ken Laufer Center for Physical and Quantitative Biology Stony Brook University Department of Applied Mathematics and Statistics Stony Brook University Department of Physics and Astronomy Stony Brook University Department of Biomedical Engineering Stony Brook University Program in Neuroscience Stony Brook University Athinoula A. Martinos Center for Biomedical Imaging Massachusetts General Hospital Harvard Medical School Department of Chemistry Stony Brook University
We give an approximate solution to the difficult inverse problem of inferring the topology of an unknown network from given time-dependent signals at the nodes. For example, we measure signals from individual neurons ... 详细信息
来源: 评论