12 December, 2016

Special Sessions

Special Sessions

Special Session Title Organizers More information
Soft Computing Methods in Manufacturing and Management Systems Damian Krenczyk

soco_imms@imms.home.pl

Silesian University of Technology

Bozena Skolud
Anna Burduk
Krzysztof Kalinowski
Wojciech Bozejko

 

Management of manufacturing systems involves development of detailed solutions related to decision making and problem solving processes. There are many important decisions to be taken and high complexity problems to solve (NP-hard), related to e.g. processes organization, planning and control of manufacturing systems. Special attention is paid to inexact solutions for which there is no known algorithm that can obtain an exact solution in polynomial time. The aim of this session is to present results of research related to management of production systems. Taking into account the complexity of problems related to production management, soft computing may deliver the most adequate answers.

Topics:

Application of soft computing methods and tools to problem solving in:

  • Manufacturing Systems Integration
  • Modelling and Design
  • Control and Supervision
  • Production Planning and Scheduling
  • Project Management
  • Supply Chain Management
  • Virtual Organisation
  • Data Mining and Data Recognition
  • Integration of Organisational and Technical Production Preparation
  • Production System Organization
  • Production Management
  • Computer Integrated Manufacturing
  • System Layout
  • Line Balancing
Modeling and Control Systems Optimization by Soft Computing (OMCS) Eloy Irigoyen Gordo – University of the Basque Country (Spain)

Email: eloy.irigoyen@ehu.eus

Matilde Santos Peñas – Complutense University of Madrid (Spain)

José Luis Calvo Rolle – University of A Coruña (Spain)

Nowadays, regardless any context, due to different reasons as climate change, aging population, and new engineering and industrial requirements, it is necessary to achieve some key challenges such as: minimize energy consumption and emissions to the atmosphere, improve the quality of life of humans, or reach industrial enhancement requests. People involved with industry and academic cannot be oblivious to these facts, because that will determine the future.

In this sense, the industry and some other fields like buildings management, assistive technologies, or real engineering applications play an important role into the different emerging techniques developed with the aim to achieve the previously cited objectives. Obviously, traditional techniques have met to the demands so far, but for future, new advanced improvements are needed.

This session provides an interesting opportunity to present and discuss the latest theoretical advances and real-world applications in Optimization, Modeling and Control Systems by means of Soft Computing models, including among others, the following topics:

  • Energy efficiency and optimization.
  • Control Techniques efficiency and optimization.
  • Traditional systems improvement.
  • Industrial control new techniques.
  • Modeling of complex systems.
  • Process optimization new techniques.
  • Fault Detection and Diagnosis.
  • Techniques to improve robustness against system failure.
  • Computational intelligence developments aimed to human beings.
  • Engineering and industrial soft computing applications.
Artificial Intelligence and Machine Learning applied to Health Sciences (MLHS) Francisco Javier de Cos

E-mail:  fjcos@uniovi.es ‐ University of Oviedo (Spain)

Alastair Basden University of Durham (UK)

Jose Luis Calvo Rolle – University of La Coruña (Spain)

Francisco Javier Moreno Arboleda – Universidad Nacional de Colombia (Colombia)

Juan Albino Mendez – University of La Laguna (Spain)

Fernando Sánchez Lasheras ‐ University of Oviedo (Spain)

Since the 1970s decade the use of Artificial Intelligence (AI) has become more and more popular in Health Sciences. The first applications of AI on Health Sciences consisted on Expert Systems. Machine Learning (ML) is an emerging scientific discipline and has applications in many areas including Health Sciences. The main use of ML in Health Sciences consist on the development of predictive models for disorder detection, especially for early diagnosis, based on data although there are other applications such as feature dimensionality reduction.

Nowadays, ML is the most popular component of many innovative software developments for Health Sciences, where large amounts of data are providing medical scientists, healthcare providers and drug makers with a treasure that can be used to derive insights. As ML techniques are applied to big data there is the potential for tremendous innovations in Health Sciences.

This session provides an interesting opportunity to present and discuss the latest theoretical advances and real‐world applications in Artificial Intelligence and Machine Learning applied to Health Sciences, including among others, the following topics:

  • Forecasting models.
  • Personal health virtual assistant.
  • Advanced analytics and research.
  • Healthcare bots.
  • Machine learning applications in genetics and genomics.
  • Monitoring support.
  • Detection of patients anomalous status.

CONDITIONS

Organisers of Special Sessions are responsible for:

  • Select a topic of interest to themselves and to conference delegates.
  • Obtain papers on this topic, normally a minimum of 5 for an invited session, but often more.
  • If there are sufficient papers, the session may become a workshop.
  • Manage the review process for these papers.
  • Provide suitable reviewers for the reviews of the papers.
  • Ensure the final versions of the papers are uploaded before the deadline.
  • Attend the conference and chair the session.

Researchers who would like to organise one or more Invited Sessions on topics falling within the scope of the conference are invited to submit a proposal for consideration. This should include:

  • Decide on the title and content of your session.
  • Publicise your session.
  • Obtain at least five papers from workers in the area.
  • Find two suitably qualified reviewers for one of the papers.
  • Manage the review process of the papers.
  • Ensure the editable wordprocessor versions of the papers are uploaded by the proper deadline and comply with conference template.

More detailed guidance notes will be made available if you accept the invitation. If you agree to accept this invitation we would be grateful if you email us (javier.alfonso@unileon.es) the following information:

  • Title of the session.
  • A paragraph describing the content of the session.
  • Surname of chair/co-chairs.
  • First name of chair/co-chairs.
  • Email address (please give only one).
  • Affiliation.
  • Postal address.
  • Telephone number.
  • Fax Number.
  • URL of web page describing session (if any).