Conference Secretary at:
1st floor of Physics and Mathematics
School.
Section of Electronics & Computers.
Tel.: + 30 2310 998071


 

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Accepted Workshops and Special Sessions 

 

1. Workshop on Nonlinear Circuits and Systems

Over the last 60 years chaotic systems have been repeatedly proven to be a useful tool in modelling complex phenomena in physics and engineering, as well as an asset for applications related to encryption, like signal masking, secure communications, path planning, optimization and more. Moreover, chaotic phenomena have been reported to emerge in electrical and electronic circuits. Physicists and engineers thus design circuits to emulate chaotic systems, in order to physically verify their chaotic behavior, and also use them in the aforementioned applications. Thus, the aim of this workshop is to explore applications of chaotic systems and their circuits, as well as and their relevance to trending technologies.

Topics of interest include, but are not limited to the following:

 Continuous, fractional, and discrete time chaotic systems

 Chaotic circuits

 Applications related to communications and encryption

 Robotics

 Synchronization and control of chaotic systems

 Memristors and memristive systems

 Chaotic neural networks

 Modelling of chaotic phenomena with nonlinear circuits

 

Workshop Organizers

Dr. Christos Volos, Associate Professor

Laboratory of Nonlinear Systems - Circuits & Complexity (LaNSCom)

Department of Physics, Aristotle University of Thessaloniki

GR-54124 Thessaloniki, Greece

Tel.: +30 2310 998284 e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it., This email address is being protected from spambots. You need JavaScript enabled to view it.

URL: http://users.auth.gr/christov

 

Dr. Lazaros Moysis, Postdoctoral researcher

Laboratory of Nonlinear Systems - Circuits & Complexity (LaNSCom)

Department of Physics, Aristotle University of Thessaloniki

GR-54124 Thessaloniki, Greece Tel.: +30 2310 998284 e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it. https://www.researchgate.net/profile/Lazaros_Moysis

 

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2. Workshop on Emergent Memristive Devices, Circuits and Systems for Wave Computing

During recent years there is a growing concern regarding the future of CMOS technology, since its growth rate has begun to decline. Moreover, the future of silicon transistors seems to be uncertain, as the magnitude of the transistor reaches few nm and new, perhaps unresolved, problems arise, such as the very large production costs, the leakage of electrical power, the high energy consumption, the credibility of the devices and the approach of the physical limits of this technology. At the same time, the corresponding classical (von Neumman) computing systems are also plagued by the problems of memory wall and energy wall and, consequently, the search for new computing approaches is heavily investigated.

As an alternative, emergent nanoelectronic devices like the well-known memristor devices and its groundbreaking nanotechnologies, seem to be quite promising in these aspects. This special session will discuss the latest developments on memristors on the whole spectrum of scientific fields which will contribute to the establishment of their technologies for circuit and system design in the years to come, from material engineering, to device physics, to circuit design and architecture with special focus on wave computing. Emphasis will be given on the latest research achievements on the proposal of

-         - emergent memristor models,

-         - novel memcomputing paradigms,

-         - design methodologies, and circuit implementations of memristive wave computing structures,

-         - wave based electronic computational units,

-         - memristor Cellular Nonlinear Networks (mCNNs),

-         - crossbar arrays a d nanoelectronic circuits for Boolean and unconventional calculations,

-         - neuromorphic circuits, architectures and systems

-         - memristive deep learning acceleration units,

-         - spin wave computing circuits and systems,

-         - biochemical processes, devices, circuits and systems for conventional and unconventional computing.

 

AC  AKNOWLEDGMENT
This work has been supported by the Hellenic Foundation for Research and Innovation (H.F.R.I.) under the “First Call for H.F.R.I. Research Projects to support Faculty members and Researchers and the procurement of high-cost research equipment grant” (Project Number: 3830).

 

Workshop Organizers

Prof. Georgios Ch. Sirakoulis

Laboratory of Electronics,

Department of Electrical and Computer Engineering,

Democritus University of Thrace,

Xanthi, GREECE

 

Prof. Dimitrios Tsoukalas

Electronic Nanomaterials and Devices Group

Department of Physics,

National Technical University of Athens,

Athens, GREECE

 

Dr. Alon Ascoli,
Technische Universität Dresden
Faculty of Electrical and Computer Engineering
Institute of Circuits and Systems
Chair of Fundamentals of Electrical Engineering

Dresden, Germany

 

Prof. Ronald Tetzlaff,
Faculty of Electrical and Computer Engineering,
Institute of Circuits and Systems,
Chair of Fundamentals of Electrical Engineering,
Dresden, Germany

 

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3. Special Session on Wireless sensor system for leak detection and localization in pipelines

A large number of industrial and commercial applications rely on the utilization of pipeline networks. Pipelines can be used for several reasons, like the transportation of fluid products (e.g. oil, natural gas) among different cities or countries, the process of fluids in factories etc. They are also used for the construction of networks needed in urban areas, such as water and sewer networks.

The transportation of fluids for the aforementioned reasons by using pipeline networks is, in general, a safe procedure. However, there is a serious problem that occasionally impedes the normal and secure operation of such networks, which is no other than the appearance of leakages. Leaks can occur in a pipeline for a variety of reasons and can lead to product loss, environmental pollution or even hazardous accidents. Over the years many leak localization techniques referred in the literature have been developed and applied to pipeline networks. These techniques may vary on the working principle, the number and type of the required sensors, the implementation cost, the power consumption etc.

As far as the physical background is concerned, a very interesting category of leak localization techniques is the one that relies on the acoustic phenomena occurring in a pipeline when a leak is present. The appearance of a leak in a pipeline results in the creation of vibro-acoustic waves that propagate along both directions of the pipe and carry the information needed for the leak point to be identified.

In this Special Session appropriate methods, based on acoustic signals, for leak detection and localization in metallic pipelines as well as a wireless sensor system for the implementation of these methods will be presented. This research effort has been produced in the context of the ESTHISIS project – Smart sensor system for leakage detection in pipes carrying oil products in noisy environment.

ACKNOWLEDGMENT

This research has been cofinanced by the European Regional Development Fund of the European Union and Greek national funds through the Operational Program Competitiveness, Entrepreneurship and Innovation, under the call RESEARCH – CREATE – INNOVATE (project code: T1EDK-00791).

 

Special Session Organizers

Prof. Spiros Nikolaidis

Aristotle University of Thessaloniki, Greece

 

Prof. Georgios-Othon Glentis

University of Peloponnese, Greece

 

Dr. Christos Spandonidis

PRISMA Electronics S.A., Greece

 

4. Special Session on Machine Learning Applications in Communications and Electronics

Machine learning (ML), artificial intelligence (AI) and its learning, adaption paradigms are providing an effective solution in engineering applications. ML can adapt to new conditions and to detect and estimate patterns. Machine learning (ML) has gained recent and well-deserved attention in many fields of engineering and science mostly due to the development of high-performance graphical-processing units (GPU) as well as development of deep neural networks (DNN) based algorithms. Several leading technology companies are heavily investing in AI/ML and academia is following suit to develop more powerful algorithms that utilize the new hardware. In addition to these new developments, practitioners have found new ways to utilize the many existing machine learning algorithms in their respective domains. The fields of wireless communications, electromagnetics (EM), antennas and electronics also benefit in a variety of ways from application of machine learning, deep learning and artificial intelligence. Several applications of ML to communications and electronics already exist. These, among others, evolutionary algorithms (EAs), Decision Trees, Random Forests, Support Vector Machines, Nearest Neighbors, Extreme Learning Machines, Gaussian Processes, Artificial Neural Networks (ANNs), Ensemble learning methods, and Deep Learning Networks (DNNs). The use of all of the above has an increasing impact to key enabling technologies for wireless communications, antenna design, propagation modeling and electronics. Additionally, hybrid combinations of ML techniques and other methods are also emerging. The aim of this special session is to use the ML computing paradigm to bring more awareness on applicability to the communications and electronics domain.

Potential topics include but are not limited to the following:

  • Machine learning techniques for wireless communications
  • Machine learning techniques for propagation modeling
  • Machine learning techniques for antenna design
  • Machine learning techniques for other EM problems
  • Machine learning techniques for 5G Networks and beyond
  • Machine learning techniques for VLSI design
  • Machine Learning techniques for signal processing
  • Machine Learning techniques for leakage detection problems
  • Machine Learning techniques for wired and wireless network
  • ML techniques for biomedical applications and wireless monitoring
  • Surrogate models for antenna design problems
  • Other innovative ML techniques

Special session organizers

Prof. Sotirios Goudos,

ELEDIA@AUTH, Department of Physics

Aristotle University of Thessaloniki, Greece

Prof. Marco Salucci,

ELEDIA@UniTN - DISI

University of Trento, Italy

Prof. Panagiotis Sarigiannidis,

Department of Electrical & Computer Engineering

University of Western Macedonia, Greece

Prof. Shaohua Wan,

School of Information and Safety Engineering,

Zhongnan University of Economics and Law, China