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Spatiotemporal Data Mining: A Survey [article]

Arun Sharma, Zhe Jiang, Shashi Shekhar
2022 arXiv   pre-print
Spatiotemporal data mining aims to discover interesting, useful but non-trivial patterns in big spatial and spatiotemporal data.  ...  This problem is challenging because of the high societal cost of spurious patterns and exorbitant computational cost. Recent surveys of spatiotemporal data mining need update due to rapid growth.  ...  ACKNOWLEDGMENTS We would like to thank Kim Koffolt and the members of the University of Minnesota Spatial Computing Research Group for their comments.  ... 
arXiv:2206.12753v1 fatcat:jwm4mcxi5na7jbmbciwlrtt554

Discovering spatiotemporal event sequences

Berkay Aydin, Rafal Angryk
2016 Proceedings of the 5th ACM SIGSPATIAL International Workshop on Mobile Geographic Information Systems - MobiGIS '16  
who contributed to my growth, both personally and professionally.  ...  Finally, I take this opportunity to thank all my good friends, especially Ezgi, Can, Feyyaz, Semih, Akif, Aytek, Evrim, Yasin, Oner, Fatih, and Deniz, who made my last five years more enjoyable.  ...  Rafal Angryk, for believing in me at first, staying behind me at difficult times, and guiding me with his expertise. I would also like to thank each of my committee members -Dr.  ... 
doi:10.1145/3004725.3004735 fatcat:3m7tehj3yjawdg2htdvuwn6guu

Detecting Multineuronal Temporal Patterns in Parallel Spike Trains

Kai S. Gansel, Wolf Singer
2012 Frontiers in Neuroinformatics  
We present a non-parametric and computationally efficient method that detects spatiotemporal firing patterns and pattern sequences in parallel spike trains and tests whether the observed numbers of repeating  ...  repeating spatiotemporal patterns and pattern sequences.  ...  Anton Sirota for helpful discussions on various statistical topics, and Raoul-Martin Memmesheimer for carrying out some of the computations.  ... 
doi:10.3389/fninf.2012.00018 pmid:22661942 pmcid:PMC3357495 fatcat:frbmsmufwjcohd3aydqmajy3by

Spatiotemporal event detection: a review

Manzhu Yu, Myra Bambacus, Guido Cervone, Keith Clarke, Daniel Duffy, Qunying Huang, Jing Li, Wenwen Li, Zhenlong Li, Qian Liu, Bernd Resch, Jingchao Yang (+1 others)
2020 International Journal of Digital Earth  
Spatiotemporal event detection serves as a gateway to enable a better understanding by detecting events that represent the abnormal status of relevant phenomena.  ...  The observations have provided an unprecedented opportunity to better understand and respond to the spatiotemporal dynamics of the environment, urban settings, health and disease propagation, business  ...  This community paper is one of a set of efforts to setup the foundation for future spatiotemporal studies/sciences. Yang, Yu and Bambacus initialized the concept for this paper.  ... 
doi:10.1080/17538947.2020.1738569 fatcat:urbuc2zii5bajjmmkzu6idyrg4

Acute and non-resolving inflammation associate with oxidative injury after human spinal cord injury

Tobias Zrzavy, Carmen Schwaiger, Isabella Wimmer, Thomas Berger, Jan Bauer, Oleg Butovsky, Jan M Schwab, Hans Lassmann, Romana Höftberger
2020 Brain  
Lymphocyte numbers were low and mainly consisted of CD8+ T cells.  ...  Only in a subpopulation of patients, CD138+/IgG+ plasma cells were detected, which could serve as candidate cellular sources for a developing humoral immunity.  ...  Acknowledgements We thank Marianne Leißer, Ulrike Ko ¨ck and Angela Kury for excellent technical assistance with immunohistological techniques.  ... 
doi:10.1093/brain/awaa360 pmid:33578421 pmcid:PMC7880675 fatcat:pwthaz3zhjhvnmkpqrnlsdkfiu

50 Years of Cetacean Strandings Reveal a Concerning Rise in Chilean Patagonia

Mario Alvarado-Rybak, Frederick Toro, Joaquín Escobar-Dodero, Amy C. Kinsley, Maximiliano A. Sepúlveda, Juan Capella, Claudio Azat, Galaxia Cortés-Hinojosa, Natalia Zimin-Veselkoff, Fernando O. Mardones
2020 Scientific Reports  
This paper aims to characterize CS patterns and describe their fine-scale spatiotemporal dynamics. We analysed spatial and spatiotemporal CS patterns in Chile from January 1968 to January 2020.  ...  of changes in climate conditions and of an increase in monitoring activities as primary drivers for such patterns, particularly important in Chilean Patagonia.  ...  Jhoann Canto from the National Natural History Museum and Mr. Jorge Gibbons from the University of Magallanes.  ... 
doi:10.1038/s41598-020-66484-x pmid:32528030 pmcid:PMC7290033 fatcat:l6b3guu7ojgp5icvc4j2i5ahoq

Dynamics of large-scale fMRI networks: Deconstruct brain activity to build better models of brain function

Fikret Işık Karahanoğlu, Dimitri Van De Ville
2017 Current Opinion in Biomedical Engineering  
build better models of brain function and dysfunction.  ...  In particular, the HMM framework has been applied for covariance states in terms of a sparse basis of co-activation patterns [53] .  ... 
doi:10.1016/j.cobme.2017.09.008 fatcat:oo4evu6w2jgtvbithzy3emlyny

Table of contents

2021 IEEE transactions on intelligent transportation systems (Print)  
Marcenaro, and C. RegazzoniTowards Better Detection and Analysis of Massive Spatiotemporal Co-Occurrence Patterns .............................. ................................... Y. Wu, D. Weng, Z.  ...  Performance Measurement and Analysis Method for Software-Defined Networking of IoV ........................... .........................................................................................  ... 
doi:10.1109/tits.2021.3082816 fatcat:cpd5gpodqzaw5bafrfzpjni2sm

Designing Visual Analytics Methods for Massive Collections of Movement Data

Natalia Andrienko, Gennady Andrienko
2007 Cartographica  
This is the unspecified version of the paper. This version of the publication may differ from the final published version.  ...  Acknowledgement The study is a part of the EU-funded project Geographic Privacy-Aware Knowledge Discovery and Delivery (GeoPKDD), grant no. IST-6FP-014915. See http://  ...  , and co-occurrence of behavioural patterns.  ... 
doi:10.3138/carto.42.2.117 fatcat:f4fu6b27jnfijdfcaboz3scnqa

Brain-wide neural co-activations in resting human [article]

Lei Ding, Guofa Shou, Yoon-Hee Cha, John A. Sweeney, Han Yuan
2021 bioRxiv   pre-print
with the prominent spatial phenomena of global patterns and anti-state pairs of co-(de)activations.  ...  Using state-of-the-art signal processing techniques, we reconstructed cortical neural tomography from resting-state EEG and extracted component-based co-activation patterns (cCAPs).  ...  Acknowledgement We gratefully acknowledge the financial support from NSF RII Track-2 FEC 1539068 and NIH U54HD104461.  ... 
doi:10.1101/2021.12.03.471116 fatcat:bd6icdmmtjcivgcg3plphnjrhe

Scanning the Issue

Azim Eskandarian
2021 IEEE transactions on intelligent transportation systems (Print)  
Vehicle and pedestrian detection are one of the critical tasks in autonomous driving.  ...  This article presents a state-of-the-art review of different approaches for driver fatigue and stress detection and evaluation with the focus on various signals (biological, car, and video) and derived  ...  Towards Better Detection and Analysis of Massive Spatiotemporal Co-Occurrence Patterns Y. Wu, D. Weng, Z. Deng, J. Bao, M. Xu, Z. Wang, Y. Zheng, Z. Ding, and W.  ... 
doi:10.1109/tits.2021.3079675 fatcat:mtssvivuebcplifv6bw233jbkq

Representing Urban Functions through Zone Embedding with Human Mobility Patterns

Zijun Yao, Yanjie Fu, Bin Liu, Wangsu Hu, Hui Xiong
2018 Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence  
Specifically, we extract human mobility patterns from taxi trajectories, and use the co-occurrence of origin-destination zones to learn zone embeddings.  ...  To utilize the spatio-temporal characteristics of human mobility patterns, we incorporate mobility direction, departure/arrival time, destination attraction, and travel distance into the modeling of zone  ...  Acknowledgments This research was partially supported by IFLYTEK Co., Ltd. and the National Science Foundation (NSF) via the grant number IIS-1648664.  ... 
doi:10.24963/ijcai.2018/545 dblp:conf/ijcai/YaoFLHX18 fatcat:r5nk2yhouvdtjajzwbcmujyabi


Huy Pham, Cyrus Shahabi, Yan Liu
2013 Proceedings of the 2013 international conference on Management of data - SIGMOD '13  
We examine two independent ways: diversity and weighted frequency, through which co-occurrences contribute to social strength.  ...  analysis.  ...  to a location and detects the significance of each single co-occurrence to social strength.  ... 
doi:10.1145/2463676.2465301 dblp:conf/sigmod/PhamSL13 fatcat:apykdgwumbgordrtpvhuhfegxa

Big Data Reduction Methods: A Survey

Muhammad Habib ur Rehman, Chee Sun Liew, Assad Abbas, Prem Prakash Jayaraman, Teh Ying Wah, Samee U. Khan
2016 Data Science and Engineering  
patterns.  ...  Modern big data systems collect inherently complex data streams due to the volume, velocity, value, variety, variability, and veracity in the acquired data and consequently give rise to the 6Vs of big  ...  The alternate to causality analysis is the assessment of influence among different nodes and establishing the connection between them on the basis of their co-occurrence.  ... 
doi:10.1007/s41019-016-0022-0 fatcat:3ivz52kpz5dhratokm4uenuoc4

Integrating Spatiotemporal Epidemiology, Eco-Phylogenetics, and Distributional Ecology to Assess West Nile Disease Risk in Horses

John M. Humphreys, Angela M. Pelzel-McCluskey, Lee W. Cohnstaedt, Bethany L. McGregor, Kathryn A. Hanley, Amy R. Hudson, Katherine I. Young, Dannele Peck, Luis L. Rodriguez, Debra P. C. Peters
2021 Viruses  
Research describing the drivers of West Nile disease in horses is greatly needed to better anticipate the spatial and temporal extent of disease risk, improve disease surveillance, and alleviate future  ...  To help meet this need, we integrated techniques from spatiotemporal epidemiology, eco-phylogenetics, and distributional ecology to assess West Nile disease risk in horses throughout the contiguous US.  ...  The spatiotemporal transitions observed between areas of over-dispersion and clustering tracked seasonal bird migration patterns in the US.  ... 
doi:10.3390/v13091811 pmid:34578392 pmcid:PMC8473291 fatcat:hlmn3abkyngtxcuxmqhdgmkggm
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