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Introduction

In real world a great majority of processes are time-dependant by nature. Therefore, methodologies of processing data and information in dynamic environments are widely studied. In particular, application areas like for instance in business, medicine, or smart cities are expanding rapidly such that the trend creates the challenge for research community to build newinfrastructure aimed at meeting the innovative requirements.

One of the fundamental goals in computational intelligence is to achieve the ability to effective computer-assisted learning from noisy, uncertain and incomplete data in order to adapt to constantly changing environments. Examples of such dynamic environments, which require some well-defined and verified methods and tools, include Internet of Things networks and realtime systems. Substantial changes, concept drift and some newly emerging trends in dynamic environments can have an impact on the increasing number of imprecise predictive methods, the rate of false alarms and consequently it may influence the systems performance and/or security.

The special session aims at presenting novel approaches to learning and adaptation to dynamic environments both from theoretical and practical application-oriented perspective. 
This Special Session is intended to provide a forum for researchers in this area to exchange new ideas. So that we encourage the research community to submit their work in progress, concept papers, position papers, case studies, reports, review papers to present innovative ideas that can provoke a discussion and provide a feedback to the session participants, initiate collaborations and stimulate some creative thinking about promising research trends.

Call for paper

Important date

2017-03-01
Draft paper submission deadline
2017-04-15
Draft paper acceptance notification

Submission Topics

List of topics:

  • Real-time systems

  • Concept drift identification

  • Methodologies/algorithms/techniques for learning in dynamic environments

  • Dynamic environment optimization algorithms 

  • Incremental e-learning, lifelong learning, cumulative learning

  • Mobile robots in a dynamic environment

  • Machine learning under concept drift and class imbalance

  • Change-detection and anomaly-detection algorithms

  • Dynamic cloud applications in PaaS (Platform as a Service) models

  • Decision support systems working in real-time

  • Predictive information-mining approaches

  • Dynamical nature of Web information search including Deep Web layers

  • Machine learning scenarios following parametric dataflow

  • Simultaneous machine translation systems

  • Streaming media

  • Geolocalization systems

  • RSS-based positioning

  • Real-Time traffic data services including emergency services

  • 5G communication in Smart cities

  • Remote sensing data processing

  • Instant messaging paradigms

  • Cognitive-inspired approaches to adaptation and learning

  • Internet of Things

  • Applications of change/anomaly detection, such as:

(a) adaptive/Intelligent systems

(b) fraud detection

(c) fault detection

(d) network-intrusion detection and security

(e) intelligent sensor networks

(f) statistical analysis of time series

(g) security challenges in the area of Internet of Things (IoT)

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Important Date
  • Conference Date

    Jul 03

    2017

    to

    Jul 05

    2017

  • Mar 01 2017

    Draft paper submission deadline

  • Apr 15 2017

    Draft Paper Acceptance Notification

  • Jul 05 2017

    Registration deadline

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Gdynia Maritime University
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