MISD 2018: The 6th International Symposium on Mining Intelligence from Sensory Data Leuven, Belgium, November 5-8, 2018 |
Conference website | http://cs-conferences.acadiau.ca/euspn-18/workshops.html |
Submission link | https://easychair.org/conferences/?conf=misd2018 |
Submission deadline | July 30, 2018 |
The 6th International Symposium on Mining Intelligence from Sensory Data (MISD)
November 5-8, 2018
Leuven, Belgium
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MISD 2018 intends to provide a leading edge, scholarly forum for researchers, engineers, and students alike to share their state-of-the-art research and developmental work in the broad areas of Mining Intelligence from Sensory Data. MISD will be held in Leuven, Beligum (5-8 November 2018) in conjunction with the 9th International Conference on Emerging Ubiquitous Systems and Pervasive Networks (EUSPN 2018).
Important Dates
- Paper Submission Due: July 30, 2018
- Acceptance Notification: August 15, 2018
- Final Manuscript Due: September 8, 2018
Scope
This symposium aims to bring together researchers and practitioners working on different aspects of machine learning, data mining and sensor networks technologies in an effort to highlight the state-of-the-art and discuss the challenges and opportunities to explore new research directions.
MISD aims to bring together people from both academia and industry for original discussions and to prompt future directions in the development of new techniques and strategies for sensory data. The topics of interest include, but are not limited to:
- Applications and deployment experiences on mining sensory data
- Applications of data mining for senor networks in business, science, engineering, medicine, and other disciplines with particular attention to lessons learned.
- Data mining approaches to overcome sensor limitations such as available energy for transmission, computational power, memory, and communications bandwidth.
- Data mining approaches to overcome sensor limitations such as available energy for transmission, computational power, memory, and communications bandwidth.
- Data mining processes including data selection, sampling, cleaning, reduction, transformation, integration and aggregation, as well as model development, validation and deployment.
- Data processing, storage and management for WSN
- Detection, classification, and tracking of sensory information
- Distributed algorithms and reasoning of sensory data
- Distributed and collaborative signal processing for WSN
- Distributed Bayesian learning (belief networks, decision networks)
- Distributed clustering methods (distributed k-Means, dynamic neural networks)
- Distributed machine learning (neural networks, support vector machines, decisions trees and rules, genetic algorithms) in sensor networks
- Distributed Principal Component Analysis (PCA) and Independent Component Analysis (ICA)
- Distributed statistical regression methods in sensor networks.
- Efficient, scalable and distributed algorithms for large-scale DDM tasks such as classification, prediction, link analysis, time series analysis, clustering, and anomaly detection.
- Fault tolerance and identification in WSN
- Fundamental bounds and formulations of intelligence in WSN
- Incremental, exploratory and interactive mining.
- Location, time, and other network services for WSN
- Mining of data streams.
- Mining security violations and patterns for WSN
- Network health monitoring and management for WSN
- Network protocols for WSN
- Operating systems and runtime environments
- Power consumption characteristics of distributed data mining algorithms and developing data mining algorithms to minimize power consumption.
- Privacy sensitive data mining.
- Programming models and languages
- Sensor tasking, control, and actuation
- Simulation of WSN
- Software agents approaches.
- Theoretical foundations in data mining and sensor network; extensions of computational learning theory to sensor networks.
- Visual data mining for sensory data.
Paper Format
The submitted paper must be formatted according to the guidelines of Procedia Computer Science, MS Word Template, Elsevier.
Paper Length
Submitted technical papers must be no longer than 6 pages for full papers, including all figures, tables and references.
Paper Submission
Authors are requested to submit their papers electronically using the online conference management system in PDF format before the deadline.
The submission processes will be managed by easychair.org. If you have used this system before, you can use the same username and password. If this is your first time using EasyChair, you will need to register for an account by clicking “I have no EasyChair account” button. Upon completion of registration, you will get a notification email from the system and you are ready for submitting your paper. You can upload and re-upload the paper to the system by
Publication
All MISD 2018 accepted papers will be published by Elsevier Science in the open-access Procedia Computer Science series on-line. Procedia Computer Science is hosted by Elsevier on www.Elsevier.com and on Elsevier content platform ScienceDirect (www.sciencedirect.com), and will be freely available worldwide. All papers in Procedia will be indexed by Scopus (www.scopus.com) and by Thomson Reuters' Conference Proceeding Citation Index (http://thomsonreuters.com/conference-proceedings-citation-index/). All papers in Procedia will also be indexed by Scopus (www.scopus.com) and Engineering Village (Ei) (www.engineeringvillage.com). This includes EI Compendex (www.ei.org/compendex). Moreover, all accepted papers will be indexed in DBLP (http://dblp.uni-trier.de/). The papers will contain linked references, XML versions and citable DOI numbers. You will be able to provide a hyperlink to all delegates and direct your conference website visitors to your proceedings. Selected papers will be invited for publication, in the following special issues:
Organizing committee
Haroon Malik, Marshall University, USA
Elhadi Shakshuki, Acadia University, Canada
Publicity Chair
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Contact
Email to: malikh@marshall.edu