*ACM Symposium on Applied Computing *
The 35th ACM/SIGAPP Symposium on Applied Computing in Brno, Czech Republic
March 30 – April 3, 2020
www.sigapp.org/sac/sac2020/
*Data Streams Track *
www.cs.waikato.ac.nz/~abifet/SAC2020/

*Call for Papers *
The rapid development in Big Data information science and technology in general and in growth complexity and volume of data in particular has introduced new challenges for the research community. Many sources produce data continuously. Examples include the Internet of Things (IoT), Smart Cities, Urban Computing, sensor networks, wireless networks, radio frequency identification, health-care devices and information systems, customer click streams, telephone records, multimedia data, scientific data, sets of retail chain transactions, etc. These sources are called data streams. A data stream is an ordered sequence of instances that can be read only once or a small number of times using limited computing and storage capabilities. These sources of data are characterized by being open-ended, flowing at high-speed, and generated by non stationary distributions.
*TOPICS OF INTEREST *
We are looking for original, unpublished work related to algorithms, methods and applications on big data streams and large scale machine learning. Topics include (but are not restricted) to:
* Real-Time Analytics
* Big Data Mining
* Data Stream Models
* Large Scale Machine Learning
* Languages for Stream Query
* Continuous Queries
* Clustering from Data Streams
* Decision Trees from Data Streams
* Association Rules from Data Streams
* Decision Rules from Data Streams
* Bayesian Networks from Data Streams
* Neural Networks for Data Streams
* Feature Selection from Data Streams
* Visualization Techniques for Data Streams
* Incremental on-line Learning Algorithms
* Single-Pass Algorithms
* Temporal, spatial, and spatio-temporal data mining
* Scalable Algorithms
* Real-Time and Real-World Applications using Stream data
* Distributed and Social Stream Mining
* Urban Computing, Smart Cities
* Internet of Things (IoT)
*IMPORTANT DATES (strict) *
1. Paper Submission: September 15, 2019
2. Author Notification: November 10, 2019
3. Camera‐ready copies: November 25, 2019

*PAPER SUBMISSION GUIDELINES *
Papers should be submitted in PDF. Authors are invited to submit original papers in all topics related to data streams. All papers should be submitted in ACM 2-column camera ready format for publication in the symposium proceedings. ACM SAC follows a double blind review process. Consequently, the author(s) name(s) and address(s) must NOT appear in the body of the submitted paper, and self-references should be in the third person. This is to facilitate double blind review required by ACM. All submitted papers must include the paper identification number provided by the eCMS system when the paper is first registered. The number must appear on the front page, above the title of the paper. Each submitted paper will be fully refereed and undergo a blind review process by at least three referees. The conference proceedings will be published by ACM. The maximum number of pages allowed for the final papers is 6 pages. There is a set of templates to support the required paper format for a number of document preparation systems at: www.acm.org/sigs/pubs/proceed/template.html
Important notice:
1. Please submit your contribution via SAC 2020 Webpage. 2. Paper registration is required, allowing the inclusion of the paper, poster, or SRC abstract in the conference proceedings. An author or a proxy attending SAC MUST present the paper. This is a requirement for including the work in the ACM/IEEE digital library. No-show of registered papers, posters, and SRC abstracts will result in excluding them from the ACM/IEEE digital library.
If you encounter any problems with your submission, please contact the Program Coordinator.

Carlos Ferreira
[http://www2.isep.ipp.pt/assinatura_email/EMAIL_ISEP.png]<www2.isep.ipp.pt/assinatura_email/> ISEP | Instituto Superior de Engenharia do Porto Rua Dr. António Bernardino de Almeida, 431 4249-015 Porto – PORTUGAL tel. +351 228 340 500 | fax +351 228 321 159 mail@isep.ipp.pt | www.isep.ipp.pt<www.isep.ipp.pt>

*ACM Symposium on Applied Computing *
The 35th ACM/SIGAPP Symposium on Applied Computing in Brno, Czech Republic
March 30 – April 3, 2020
www.sigapp.org/sac/sac2020/
*Data Streams Track *
www.cs.waikato.ac.nz/~abifet/SAC2020/

*Call for Papers *
The rapid development in Big Data information science and technology in general and in growth complexity and volume of data in particular has introduced new challenges for the research community. Many sources produce data continuously. Examples include the Internet of Things (IoT), Smart Cities, Urban Computing, sensor networks, wireless networks, radio frequency identification, health-care devices and information systems, customer click streams, telephone records, multimedia data, scientific data, sets of retail chain transactions, etc. These sources are called data streams. A data stream is an ordered sequence of instances that can be read only once or a small number of times using limited computing and storage capabilities. These sources of data are characterized by being open-ended, flowing at high-speed, and generated by non stationary distributions.
*TOPICS OF INTEREST *
We are looking for original, unpublished work related to algorithms, methods and applications on big data streams and large scale machine learning. Topics include (but are not restricted) to:
* Real-Time Analytics
* Big Data Mining
* Data Stream Models
* Large Scale Machine Learning
* Languages for Stream Query
* Continuous Queries
* Clustering from Data Streams
* Decision Trees from Data Streams
* Association Rules from Data Streams
* Decision Rules from Data Streams
* Bayesian Networks from Data Streams
* Neural Networks for Data Streams
* Feature Selection from Data Streams
* Visualization Techniques for Data Streams
* Incremental on-line Learning Algorithms
* Single-Pass Algorithms
* Temporal, spatial, and spatio-temporal data mining
* Scalable Algorithms
* Real-Time and Real-World Applications using Stream data
* Distributed and Social Stream Mining
* Urban Computing, Smart Cities
* Internet of Things (IoT)
*IMPORTANT DATES (strict) *
1. Paper Submission: September 15, 2019
2. Author Notification: November 10, 2019
3. Camera‐ready copies: November 25, 2019

*PAPER SUBMISSION GUIDELINES *
Papers should be submitted in PDF. Authors are invited to submit original papers in all topics related to data streams. All papers should be submitted in ACM 2-column camera ready format for publication in the symposium proceedings. ACM SAC follows a double blind review process. Consequently, the author(s) name(s) and address(s) must NOT appear in the body of the submitted paper, and self-references should be in the third person. This is to facilitate double blind review required by ACM. All submitted papers must include the paper identification number provided by the eCMS system when the paper is first registered. The number must appear on the front page, above the title of the paper. Each submitted paper will be fully refereed and undergo a blind review process by at least three referees. The conference proceedings will be published by ACM. The maximum number of pages allowed for the final papers is 6 pages. There is a set of templates to support the required paper format for a number of document preparation systems at: www.acm.org/sigs/pubs/proceed/template.html
Important notice:
1. Please submit your contribution via SAC 2020 Webpage. 2. Paper registration is required, allowing the inclusion of the paper, poster, or SRC abstract in the conference proceedings. An author or a proxy attending SAC MUST present the paper. This is a requirement for including the work in the ACM/IEEE digital library. No-show of registered papers, posters, and SRC abstracts will result in excluding them from the ACM/IEEE digital library.
If you encounter any problems with your submission, please contact the Program Coordinator.

Carlos Ferreira
[http://www2.isep.ipp.pt/assinatura_email/EMAIL_ISEP.png]<www2.isep.ipp.pt/assinatura_email/> ISEP | Instituto Superior de Engenharia do Porto Rua Dr. António Bernardino de Almeida, 431 4249-015 Porto – PORTUGAL tel. +351 228 340 500 | fax +351 228 321 159 mail@isep.ipp.pt | www.isep.ipp.pt<www.isep.ipp.pt>

IoTStream 2019:IoTStream for Data Driven Predictive Maintenance ECML-PKDD 2019 Würzburg, Germany, September 16-20, 2019
Conference website abifet.wixsite.com/iotstream2019 <abifet.wixsite.com/iotstream2019> Submission link easychair.org/conferences/?conf=iotstream2019 <easychair.org/conferences/?conf=iotstream2019> Abstract registration deadline June 7, 2019 Submission deadline June 7, 2019
Topics: predictive maintenance <easychair.org/cfp/topic.cgi?a=21955490;tid=24891> fault detection <easychair.org/cfp/topic.cgi?tid=2906;a=21955490> internet of things <easychair.org/cfp/topic.cgi?tid=200145;a=21955490> data streams <easychair.org/cfp/topic.cgi?tid=6455;a=21955490>
Maintenance is a critical issue in the industrial context for the prevention of high costs or injures. The emerging technologies of Industry 4.0 empowered data production and exchange which lead to new concepts and methodologies exploitation for maintenance. Intensive research effort in data driven Predictive Maintenance (PdM) has been producing encouraged outcomes. Therefore, the main objective of this workshop is to raise awareness of research trends and promote interdisciplinary discussion in this field.
Submission Guidelines
Regular and short papers presenting work completed or in progress are invited. Regular papers should not exceed 12 pages, while short papers are maximum 6 pages. Papers must be written in English and are to be submitted in PDF format online via the Easychair submission interface:
easychair.org/conferences/?conf=iotstream2019 <easychair.org/conferences/?conf=iotstream2019>
Each submission will be evaluated on the basis of relevance, significance of contribution, quality of presentation and technical quality by at least two members of the program committee.
List of Topics
*
This workshop solicits contributions including but not limited to the following topics:
*
Fault Detection and Diagnosis (FDD)
*
Fault Isolation and Identification
*
Estimation of Remaining Useful Life of Components, Machines, ….
*
Forecasting of Product and Process Quality
*
Early Failure and Anomaly Detection and Analysis
*
Automatic Process Optimization
*
Self-healing and Self-correction
*
Incremental, evolving (data-driven and hybrid) models for FDD and anomaly detection
*
Self-adaptive time-series based models for prognostics and forecasting
*
Adaptive signal processing techniques for FDD and forecasting
*
Concept Drift issues in dynamic predictive maintenance systems
*
Active learning and Design of Experiment (DoE) aspects in dynamic predictive maintenance
*
Systems Fault tolerant control
*
Decision Support Systems for Predictive Maintenance
*
Data visualization for Prescriptive Maintenance
*
Real world applications such as:
*
Manufacturing systems
*
Production Processes and Factories of the Future (FoF)
*
Wind turbines (offshore/onshore/floating)
*
Smart management of energy demand/response
*
Energy and power systems and networks
*
Transport systems
*
Power generation and distribution systems
*
Intrusion detection and cyber security
*
Internet of Things,
*
Next Generation Airspace Applications, etc.
*
Big Data challenges in energy transition and digital transition
*
Solar plant monitoring and management
*
Active demand response
*
Distributed renewable energy management and integration into smart grids
*
Smart cities
Committees
Program Committee
*
Carlos Ferreira, LIAAD INESC Porto LA, ISEP, Portugal
*
Edwin Lughofer, Johannes Kepler University of Linz, Austria
*
Sylvie Charbonnier, Université Joseph Fourier-Grenoble, France
*
Bruno Sielly Jales Costa, IFRN, Natal, Brazil
*
Fernando Gomide, University of Campinas, Brazil
*
José A. Iglesias, Universidad Carlos III de Madrid, Spain
*
Anthony Fleury, Mines-Douai, Institut Mines-Télécom, France
*
Teng Teck Hou, Nanyang Technological University, Singapore
*
Plamen Angelov, Lancaster University, UK
*
Igor Skrjanc, University of Ljubljana, Slovenia
*
Indre Zliobaite, Aalto University, Austria
*
Elaine Faria, Univ. Uberlandia, Brazil
*
Mykola Pechenizkiy, TU Eindonvhen, Netherlands
*
Raquel Sebastião, Univ. Aveiro, Portugal
Organizing committee
* Rita P. Ribeiro, INESC TEC, Portugal *
Sepideh Pashami, Halmstad University
*
Albert Bifet, Telecom-ParisTech; Paris, France
* João Gama, INESC TEC, Portugal
Publication
All accepted papers will be included in the workshop proceedings and will be publically available on the conference web site. At least one author of each accepted paper is required to attend the workshop to present.
Venue
The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases will take place in Würzburg, Germany, from the *16th to the 20th of September 2019*.
Contact
All questions about submissions should be emailed to one of the Chairs

Carlos Ferreira
[http://www2.isep.ipp.pt/assinatura_email/EMAIL_ISEP.png]<www2.isep.ipp.pt/assinatura_email/> ISEP | Instituto Superior de Engenharia do Porto Rua Dr. António Bernardino de Almeida, 431 4249-015 Porto – PORTUGAL tel. +351 228 340 500 | fax +351 228 321 159 mail@isep.ipp.pt | www.isep.ipp.pt<www.isep.ipp.pt>