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A Novel Multi-Module Approach to Predict Crime Based on Multivariate Spatio-Temporal Data Using Attention and Sequential Fusion Model

Nowshin Tasnim, Iftekher Toufique Imam, M. M. A. Hashem
2022 IEEE Access  
In the second module, the Spatio-Temporal based Attention-LSTM, Stacked Bidirectional LSTM, and the result of feature-level fusion module are used to get the final prediction.  ...  The first module employs temporal-based Attention LSTM, Spatio-Temporal based Stacked Bidirectional LSTM, and Fusion model. The Fusion model leverages the prior two models' training data.  ...  [9] performed a Spatio-temporal Attention-based study to predict crime of top 4 categories. Their model cannot predict categories having a small amount of data.  ... 
doi:10.1109/access.2022.3171843 fatcat:z3zqbdo7rvbazbe2sycjpxazlq

Generative Adversarial Networks for Spatio-temporal Data: A Survey [article]

Nan Gao, Hao Xue, Wei Shao, Sichen Zhao, Kyle Kai Qin, Arian Prabowo, Mohammad Saiedur Rahaman, Flora D. Salim
2021 arXiv   pre-print
Recently, GAN-based techniques are shown to be promising for spatio-temporal-based applications such as trajectory prediction, events generation and time-series data imputation.  ...  While several reviews for GANs in computer vision have been presented, no one has considered addressing the practical applications and challenges relevant to spatio-temporal data.  ...  [73] developed a context-based generative model Crime-GAN to learn the spatio-temporal dynamics of the crime situation.  ... 
arXiv:2008.08903v3 fatcat:pbhxbfgw65bodksjdmwazwo4dq

Short-Term Prediction of Demand for Ride-Hailing Services: A Deep Learning Approach

Long Chen, Piyushimita Vonu Thakuriah, Konstantinos Ampountolas
2021 Journal of Big Data Analytics in Transportation  
To assess the performance and effectiveness of UberNet, we use 9 months of Uber pickup data in 2014 and 28 spatial and temporal features from New York City.  ...  demographics characteristics, as well as travel-to-work, built environment and social factors such as crime level, within a multivariate framework, that leads to operational and policy insights for multiple  ...  as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made.  ... 
doi:10.1007/s42421-021-00041-4 fatcat:s3kjmtekmfbaldbkqpidcu7s3i

Program

2019 2019 International Conference on Control, Automation and Information Sciences (ICCAIS)  
This paper proposes a novel multi-station signal association and fusion technique for multi-target based on sequential Bayesian algorithm that can associate multi-station's signal from different scanning-beams  ...  To this end, the map is modeled as a multi-object Poisson process and a recently developed approach, named Cauchy-Schwarz fusion (CSF), is adopted.  ...  to accurately estimate the number of people in the elevator cab; finally, a state identification approach in the case of two abnormal behavior occurring in cabs is developed through the ViBe and optical  ... 
doi:10.1109/iccais46528.2019.9074650 fatcat:f3libdixzvez3kaeyb5dubekrq

GeoAI for Large-Scale Image Analysis and Machine Vision: Recent Progress of Artificial Intelligence in Geography

Wenwen Li, Chia-Yu Hsu
2022 ISPRS International Journal of Geo-Information  
While different applications tend to use diverse types of data and models, we summarized six major strengths of GeoAI research, including (1) enablement of large-scale analytics; (2) automation; (3) high  ...  We organize this review of GeoAI research according to different kinds of image or structured data, including satellite and drone images, street views, and geo-scientific data, as well as their applications  ...  Acknowledgments: The authors sincerely appreciate Yingjie Hu and Song Gao for comments on an earlier version of the manuscript. Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/ijgi11070385 fatcat:yyzi46anyfcjrjuzcjfhbczo5y

2021 Index IEEE Transactions on Industrial Informatics Vol. 17

2021 IEEE Transactions on Industrial Informatics  
Departments and other items may also be covered if they have been judged to have archival value. The Author Index contains the primary entry for each item, listed under the first author's name.  ...  The primary entry includes the coauthors' names, the title of the paper or other item, and its location, specified by the publication abbreviation, year, month, and inclusive pagination.  ...  ., +, TII June 2021 4197-4205 Remaining Useful Life Prediction Using a Novel Feature-Attention-Based End-to-End Approach.  ... 
doi:10.1109/tii.2021.3138206 fatcat:ulsazxgmpfdmlivigjqgyl7zre

Bayesian binary quantile regression for the analysis of Bachelor-to-Master transition

Cristina Mollica, Lea Petrella
2016 Journal of Applied Statistics  
methods for Predictive and Exploratory Path modeling  ...  Specialized teams Currently the ERCIM WG has over 1150 members and the following specialized teams BM: Bayesian Methodology CODA: Complex data structures and Object Data Analysis CPEP: Component-based  ...  EO144 Room MAL G15 SPATIAL AND SPATIO-TEMPORAL PROCESSES AND THEIR APPLICATIONS Chair: Jooyoung Jeon EO0512: A constructive spatio-temporal approach to modeling spatial covariance Presenter: Ephraim Hanks  ... 
doi:10.1080/02664763.2016.1263835 fatcat:l5eyielgxrct7hq5ljqeej5ccy

Program

2021 2021 National Conference on Communications (NCC)  
The benefits of MLdriven techniques over traditional model-based approaches are twofold: First, ML methods are independent of the underlying stochastic model, and thus can operate efficiently in scenarios  ...  Furthermore, we introduce a new tractable, electromagnetic-compliant, and circuit-based communication model for RIS-assisted transmission and discuss its applications to the modeling and optimization of  ...  usefulness of the latter in predicting PM2.5 concentration. 10:50 Spatio-Temporal Prediction of Roadside PM2.5 Based on Sparse Mobile Sensing and Traffic Information 11:10 Early Prediction of Human  ... 
doi:10.1109/ncc52529.2021.9530194 fatcat:ahdw5ezvtrh4nb47l2qeos3dwq

Open challenges for data stream mining research

Georg Krempl, Myra Spiliopoulou, Jerzy Stefanowski, Indre Žliobaite, Dariusz Brzeziński, Eyke Hüllermeier, Mark Last, Vincent Lemaire, Tino Noack, Ammar Shaker, Sonja Sievi
2014 SIGKDD Explorations  
While predictive modeling for data streams and big data have received a lot of attention over the last decade, many research approaches are typically designed for well-behaved controlled problem settings  ...  Existing solutions are based on "best practices", i.e., the systems' decisions are knowledge-driven and/or data-driven.  ...  on the challenges in stream mining.  ... 
doi:10.1145/2674026.2674028 fatcat:y3bozzeohveibgxb5wmiwfcogm

Big Data Meet Cyber-Physical Systems: A Panoramic Survey [article]

Rachad Atat, Lingjia Liu, Jinsong Wu, Guangyu Li, Chunxuan Ye, Yang Yi
2018 arXiv   pre-print
Compared with other survey papers, this is the first panoramic survey on big data for CPS, where our objective is to provide a panoramic summary of different CPS aspects.  ...  Furthermore, CPS require cybersecurity to protect them against malicious attacks and unauthorized intrusion, which become a challenge with the enormous amount of data that is continuously being generated  ...  The paper [187] proposed distributed composite spatio-temporal index approach VegaIndexer for efficiently processing the large amount of spatio-temporal sensor data.  ... 
arXiv:1810.12399v1 fatcat:2diydpforraofhyhhkfs3fnjtu

Big Data Meet Cyber-Physical Systems: A Panoramic Survey

Rachad Atat, Lingjia Liu, Jinsong Wu, Guangyu Li, Chunxuan Ye, Yi Yang
2018 IEEE Access  
Compared with other survey papers, this is the first panoramic survey on big data for CPS, where our objective is to provide a panoramic summary of different CPS aspects.  ...  Furthermore, CPS requires cybersecurity to protect them against malicious attacks and unauthorized intrusion, which become a challenge with the enormous amount of data that are continuously being generated  ...  The paper [187] proposed distributed composite spatio-temporal index approach VegaIndexer for efficiently processing the large amount of spatio-temporal sensor data.  ... 
doi:10.1109/access.2018.2878681 fatcat:czfu37subng6bl3sgd3a243vn4

2020 Index IEEE Systems Journal Vol. 14

2020 IEEE Systems Journal  
., +, JSYST Dec. 2020 5284-5295 Advertising data processing A Hierarchical Attention Model for CTR Prediction Based on User Interest.  ...  ., +, JSYST March 2020 900-908 A Hierarchical Attention Model for CTR Prediction Based on User Interest.  ...  ., +, 2585 -2588 Energy-Efficient IoT-Fog-Cloud Architectural Paradigm for Real-Time Wildfire Prediction and Forecasting. 2003 -2011 Agent Pseudonymous Authentication-Based Conditional Privacy Preservation  ... 
doi:10.1109/jsyst.2021.3054547 fatcat:zf2aafvnfzbeje32qei5563myu

26th Annual Computational Neuroscience Meeting (CNS*2017): Part 2

Leonid L. Rubchinsky, Sungwoo Ahn, Wouter Klijn, Ben Cumming, Stuart Yates, Vasileios Karakasis, Alexander Peyser, Marmaduke Woodman, Sandra Diaz-Pier, James Deraeve, Eliana Vassena, William Alexander (+473 others)
2017 BMC Neuroscience  
Based on experimental data recorded from the entorhinal sequentially.  ...  3D using 3DBAR [3] and data and to predict new experimental findings.  ... 
doi:10.1186/s12868-017-0371-2 fatcat:jkqnv4rvfvaj5g44xm5snzdqzy

FIRST INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND DATA SCIENCE (ICAIDS-2022) [article]

Dr. Agusthiyar . R
2022 Zenodo  
on Artificial Intelligence and Data Science (ICAIDS-2022) in association with Object Automation Software Solutions Pvt ltd, IBM, OpenPower, Onstitute and X-Scale Solutions on 4th and 5th March 2022.  ...  I would like to congratulate the staff, the students of the Department of Computer Applications (BCA) and all the others directly and indirectly associated in organizing the First International Conference  ...  For training the model, we created a pipeline using the Pipeline module from sklearn. This module is used to carry out sequential transformation on data.  ... 
doi:10.5281/zenodo.7024997 fatcat:2v4vxqlfxbgn3dl43zr4y2d26y

Proceedings of the 11th International Workshop "Data analysis methods for software systems"

Jolita Bernatavičienė
2019 Vilnius University Proceedings  
The main goal of the workshop is to introduce the research undertaken at Lithuanian and foreign universities in the fields of data science and software engineering.  ...  DAMSS-2019 is the 11th international workshop on data analysis methods for software systems, organized in Druskininkai, Lithuania, at the end of the year. The same place and the same time every year.  ...  Based on data mining methods, various models are developed to address segmentation, risk assessment, behavioral templates and tax crime detection.  ... 
doi:10.15388/proceedings.2019.8 fatcat:hb3t35tmpnhlbkzbstyvxfrgyu
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