- Go to the Sessions
- Event Details
Welcome from the Chairs
You are cordially invited to participate in the 5th International Electronic Conference on Entropy and Its Applications. The conference aims to bring together researchers to present and discuss their recent contributions, without the need for travel. This e-conference is hosted on the MDPI Sciforum platform, which allows online presentation and discussion of participants’ work.
The concept of entropy is key in a broad range of research activities related to the understanding of (complex) dynamic systems, statistical mechanics, and information theory. Entropy also plays a crucial role in many practical applications. This conference aims to bring together researchers of different backgrounds—with a common interest in clarifying the role of entropy in their respective fields—to discuss ideas across different domains and expand their knowledge on the variety of possible applications of entropic methods.
The format of the conference is as follows. After abstract acceptance, the authors of oral contributions will submit a pre-recorded video presentation or series of narrated slides which will be accessible, online, during the entire conference and remain available after the e-conference. Alternatively, there is a track for posters, which will also be made available via the online platform.
In addition, authors are invited to submit a full description of their work (max. 8 pages), optionally along with a PowerPoint presentation and/or poster. Conference papers will be peer-reviewed and, upon acceptance, published in Proceedings. Paper submission is not a requirement for active conference participation.
Finally, authors may submit extended papers to be considered for publication in a Special Issue of Entropy, with a 20% discount on the APC. Entropy is an open-access publication journal of MDPI in the field of entropy and information theory.
Prof. Dr. Geert Verdoolaege
|Geert Verdoolaege (M.Sc. Theoretical Physics in 1999, Ph.D. Engineering Physics in 2006) is a researcher at the Laboratory for Plasma Physics of the Royal Military Academy (LPP-ERM/KMS) in Brussels, Belgium. His research activities include development of data analysis techniques using methods from probability theory, machine learning, and information geometry and application of these methods to nuclear fusion experiments and image processing. He also teaches a Master course on Continuum Mechanics at Ghent University in Belgium. He serves on the Editorial Board of the multidisciplinary journal Entropy and is a member of the scientific committees of several conferences (IAEA Technical Meeting on Fusion Data Processing, Validation and Analysis; International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering; Conference on Geometric Science of Information). In addition, he is a consulting expert in the International Tokamak Physics Activity (ITPA) Transport and Confinement Topical Group and member of the General Assembly of the European Fusion Education Network (FuseNet).
Conference Session Chairs
Prof. Dr. Philip Broadbridge
Prof. Dr. Hung T. Diep
Prof. Dr. Ercan Kuruoglu
Prof. Dr. Anne Humeau-Heurtier
Laboratoire Angevin de Recherche en Ingénierie des Systèmes (LARIS), University of Angers, Angers cedex, France
Prof. Dr. William B. Sherwin
Evolution & Ecology Research Centre, School of Biological Earth and Environmental Science, UNSW Sydney, Sydney, Australia
Dr. Remo Garattini
Professor José Miguel Mateos Roco
Universita’ Sapienza Roma, Roma, Italy
Prof. Dr. Troy Day
Prof. Dr. Luca Faes
University of Palermo, Palermo, Italy
Prof. Dr. Roberto Hornero
Universidad de Valladolid,
Professor Michael Nosonovsky
University of Wisconsin-Milwaukee, Milwaukee, WI, USA
Prof. Dr. Raúl Alcaraz Martínez
University of Castilla-La Mancha, Cuenca, Spain
Dr. Antonio M. Scarfone
Istituto dei Sistemi Complessi, Consiglio Nazionale delle Ricerche (ISC-CNR), Torino, Italy
Dr. Takuya Yamano
Kanagawa University, Kanagawa, Japan
Prof. Dr. Tapio Ala-Nissila
Aalto University, Aalto, Finland
Dr. Eun-jin Kim
University of Sheffield, Sheffield, UK
Dr Kim obtained her BSc in Physics from Yonsei University in Seoul, Korea, and PhD in Physics from the University of Chicago, USA. She held postdoctoral positions at the Universities of Leeds and Exeter in UK, High-Altitude Observatory in Boulder, USA and University of California, San Diego, USA. She is currently an Associate Professor at the University of Sheffield, UK. Dr Kim is interested in complexity, self-organisation and non-equilibrium processes, and has a unique track record in multidisciplinary research, with applications to astrophysical and laboratory fluids/plasmas and biosystems. In particular, Dr. Kim is keen on the information theory (information length) to model complexity and self-organisation in nonlinear dynamical systems, fluid/plasma turbulence, and biosystems. She is a holder of a Leverhulme Trust Research Fellowship. She published over 110 refereed journal papers (51 as first author)
non-equilibrium statistical mechanics; complex systems; information theory; self-organisation; fluid dynamics; magnetohydrodynamics (MHD); plasma physics; turbulence; solar/stellar physics; homeostasis in biosystems
Dr. Matteo Convertino
Hokkaido University, Hokkaido, Japan
Dr. Convertino is an Associate Professor in the Graduate School of Information Science and Technology at Hokkaido University, Sapporo (JP), where he is the PI of the Nexus Group. Dr. Convertino is also a faculty member of the Station for Big-Data & Cybersecurity (Environmental and Biomedical Data Science research) and in the Department of Information Engineering at Hokkaido University. Additionally he is also Adjunct Professor position at the Institute on the Environment and the Bioinformatics and Computational Biology program at the University of Minnesota. Dr. Convertino expertise is in biocomplexity focused on environmental dynamics (in particular ecohydrogeomorphological processes) and its nexus with population patterns at multiple scales of biological organization. Research is sought via process- & pattern-oriented theoretical and computational models based on information, network, and decision sciences. Models are applied to a variety of ecosystems for understanding their biological, ecological, and socio-technological function as well as for value-based ecosystem design.
Dr. Pritam Chanda
Research Scientist in data science and machine learning, Corteva Agrisciences, Indianapolis, Indiana, USA
Pritam Chanda received his PhD in Computer Science from the State University of New York, Buffalo, NY in 2010 and MS in Computer Engineering from the University of Cincinnati, OH in 2005. He has held post-doctoral position at the department of Biomedical Engineering, Johns Hopkins University (2010-2013). Since 2013, he has joined Dow Agrosciences (subsidiary of Dow Chemical Company) as Research Scientist in Data mining and Machine Learning. Currently he is a senior member of the global Data Science group in Corteva Agriscience, a market shaping agricultural company with leading positions in seed technologies, crop protection and digital agriculture. His work focuses on machine learning and information theoretic methods and its applications in computational biology and multi-omics data sciences (genetics, genomics, proteomics, transcriptomics). His research also involves deep learning methods and their uses in biological and chemical sciences.
Dr. Eleonora Di Valentino
University of Manchester, Manchester, UK
Dr. Eleonora Di Valentino is a postdoctoral research associate at the University of Manchester. Her area of research is focused on cosmology, mainly on Cosmic Microwave Background anisotropies, and cosmological data analysis to constrain properties of the early and recent Universe and fundamental physics. A major goal of her research is to constrain neutrino physics and other light fundamental particles such as axions with cosmology, using different observables and methods that offer complementary informations. Moreover, she is investigating the main tensions present between the different cosmological probes and models, trying to understand if they can have a physical explanation, going beyond the standard LCDM cosmological model.
Prof. Dr. George Ruppeiner
New College of Florida, Sarasota, FL, USA
Dr. Ruppeiner is a Professor of Physics and Astronomy at New College of Florida ([email protected]). Dr. Ruppeiner received his Bachelor’s Degree in Physics at Louisiana State University in 1975, and his PhD in Experimental Low Temperature Physics at Duke University in 1980. In his PhD work, Dr. Ruppeiner developed a great appreciation for high quality experimental data, and for the need of theory to interpret such data. In his professional research, Dr. Ruppeiner has been mostly theoretical, focusing on what is nowadays called information geometry, in the area of thermodynamics. Specifically, Dr. Ruppeiner has investigated the thermodynamic Ricci curvature scalar R, and contributed to the case that this quantity provides essential information about the microscopic interactions in systems including fluids, magnets, and even black holes.
Dr. Shao-Lun Huang
Tsinghua-Berkeley Shenzhen Institute, Shenzhen, China
Shao-Lun Huang received the B.S. degree with honor in 2008 from the Department of Electronic Engineering, National Taiwan University, Taiwan, and the M.S. and Ph.D. degree in 2010 and 2013 from the Department of Electronic Engineering and Computer Sciences, Massachusetts Institute of Technology. From 2013 to 2016, he was working as a postdoctoral researcher jointly in the Department of Electrical Engineering at the National Taiwan University and the Department of Electrical Engineering and Computer Science at the Massachusetts Institute of Technology. Since 2016, he has joined Tsinghua-Berkeley Shenzhen Institute, where he is currently an assistant professor. His research interests include information theory, communication theory, machine learning, and social networks.
Dr. Sebastian Deffner
Department of Physics, UMBC, Baltimore, MD, USA
Dr. Sebastian Deffner received his doctorate from the University of Augsburg in 2011 under the supervision of Eric Lutz. From 2011 to 2014 he was a Research Associate in the group of Chris Jarzynski at the University of Maryland, College Park and from 2011 to 2016 he was a Directorʼs Funded Postdoctoral Fellow with Wojciech H. Zurek at the Los Alamos National Laboratory. Since 2016 he has been on the faculty of the Department of Physics at the University of Maryland Baltimore County (UMBC), where he leads the quantum thermodynamics group. As a theoretical physicist, Dr. Deffner employs tools from statistical physics, open quantum dynamics, quantum information theory, quantum optics, quantum field theory, condensed matter theory, and optimal control theory to investigate the nonequilibrium properties of nanosystems operating far from thermal equilibrium.
Prof. Dr. Hung T. Diep
Université de Cergy-Pontoise, CNRS, Cergy-Pontoise Cedex, France
Prof. Dr. Andrea Murari
Consorzio RFX (CNR, ENEA, INFN, Universita’ di Padova, Acciaierie Venete SpA), Padova, Italy
List of Keynotes & Videos
Multispecies Emergence of Collective Behavior: Microbiome Connectome, Diversity and Services
Cosmology in Tension
Cosmology in Tension
Social Conflicts Studied by Statistical Physics Approach and Monte Carlo Simulations
Spin Waves and Skyrmions in Magneto-Ferroelectric Superlattices: Theory and Simulation
Quantum Thermodynamics: An Introduction to the Thermodynamics of Quantum Computers
Quantifying Total Correlations between Variables with Information Theoretic and Machine Learning Techniques
An Information-theoretic Approach to Unsupervised Feature Selection for High-Dimensional Data
List of accepted submissions (38)
|Id||Title||Authors||Presentation Video||Presentation Pdf|
A New Perspective on the Kauzmann Entropy Paradox: A Four-Dimensional Crystal/Glass Quantum Critical Point
Submitted: 18 Oct 2019
Abstract: Show Abstract
In this article, a new perspective on the Kauzmann point is presented. We model the solidifying liquid by a quaternion orientational order parameter and find that the Kauzmann point is analogous to a quantum critical point. The “ideal glass transition" that occurs at the Kauzmann temperature is the point at which the configurational entropy of an undercooled metastable liquid equals that of its crystalline counterpart. We identify this point as a first order quantum critical point. We suggest that this quantum critical point belongs to quaternion ordered systems that exist in four- and three-dimensions. This “Kauzmann quantum critical point” can be considered to be a higher-dimensional analogue to the superfluid-to-Mott insulator quantum phase transition which occurs in two- and one-dimensional complex ordered systems. Such quantum critical points are driven by tuning a non-thermal frustration parameter, and result due to characteristic softening of a ‘Higgs’ type mode that corresponds to amplitude fluctuations of the order parameter. The first-order nature of the finite temperature Kauzmann quantum critical point is seen as a consequence of the discrete change of the topology of the ground state manifold that applies to crystalline and non-crystalline solid states.
A Novel Improved Feature Extraction Technique for Ship-radiated Noise Based on Improved Intrinsic Time-scale Decomposition and Multiscale Dispersion Entropy
Submitted: 23 Oct 2019
Abstract: Show Abstract
Entropy feature analysis is an important tool for classification and identification of different types of ships. In order to improve the limitations of traditional feature extraction of shipradiation noise in complex marine environments, we proposed a novel feature extraction method for ship-radiated noise based on improved intrinsic time-scale decomposition (IITD) and multiscale dispersion entropy (MDE). The proposed feature extraction technique, named IITD-MDE. IITD as an improved algorithm has more reliable performance than instrinsic time-scale decomposition(ITD). Firstly, five types of ship-radiated noise signals are decomposed into a series of intrinsic scale component (ISCs) by IITD. Then, we select the ISC with main information through the correlation analysis, and calculate the MDE value as feature vector. Finally, input the feature vector into the support vector machine (SVM) classifier to analysis and get classification. The experimental results demonstrate that the recognition rate of the proposed technique reaches 86% of accuracy. Therefore, compare with the other feature extraction methods, the proposed method is able to classify the different types of ships effectively.
An Information-theoretic Approach to Unsupervised Feature Selection for High-Dimensional Data
Submitted: 05 Nov 2019
Abstract: Show Abstract
In this talk, we propose an information theoretic approach to design the functional representations to extract the hidden common structure shared by a set of random variables. The main idea is to measure the common information between the random variables by the Watanabe's total correlation, and then find the hidden attributes of these random variables such that common information between these random variables is reduced the most given these hidden attributes. We show that these hidden attributes can be characterized by an exponential family specified by the eigen-decomposition of some pairwise joint distribution matrix. Then, we adopt the log-likelihood functions for estimating these hidden attributes as the desired functional representations of the random variables, and show that these functional representations are informative to describe the common structure. Moreover, we design both the multivariate alternative conditional expectation (MACE) algorithm to compute the proposed functional representations for discrete data, and a novel neural network training scheme for continuous or high-dimensional data. Finally, the performances of our algorithms are validated by numerical simulations in the MNIST digital recognition.
Comparative Examination of Nonequilibrium Thermodynamic Models of Thermodiffusion in Liquids
Submitted: 19 Oct 2019
Abstract: Show Abstract
We analyze existing models for material transport in non-isothermal non-electrolyte liquid mixtures that utilize non-equilibrium thermodynamics. Many different sets of equations for material have been derived that, while based on the same fundamental expression of entropy production, utilize different terms of the temperature- and concentration-induced gradients in the chemical potential to express the material flux. We reason that only by establishing a system of transport equations that satisfies the following three requirements can we obtain a valid thermodynamic model of thermodiffusion based on entropy production and understand the underlying physical mechanism: (1) maintenance of mechanical equilibrium in a closed steady-state system, expressed by a form of the Gibbs-Duhem equation that accounts for all the relevant gradients in concentration, temperature, and pressure and respective thermodynamic forces; (2) thermodiffusion (thermophoresis) is zero in pure unbounded liquids (i.e., in the absence of wall effects); (3) invariance in the derived concentrations of components in a mixture, regardless of which concentration or material flux is considered to be the dependent versus independent variable in an overdetermined system of material transport equations. The analysis shows that thermodiffusion in liquids is based on the entropic mechanism.
Computer Simulation of Magnetic Skyrmions
Submitted: 18 Oct 2019
Abstract: Show Abstract
We present results of numerical simulation of thermodynamics for array of Classical Heisenberg spins placed on 2D square lattice, which effectively represents the behaviour of single layer. Using Metropolis algorithm, we show the temperature behaviour of system with competing Heisenberg and Dzyaloshinskii-Moriya interaction (DMI) in contrast with classical Heisenberg system. We show the process of nucleating of skyrmion depending on the value of external magnetic field. We proposed the controlling method for movement of skyrmions.
Best Presentation at ECEA-5
authored by Hung T. Diep, Ildus F. Sharafullin
"Hung T. Diep is professor of physics at the University of Cergy-Pontoise in Paris area, France. He works on problems in statistical physics, condensed matter physics, and magnetism, focusing mainly on phase transitions and critical phenomena, on elementary excitations such as spin waves in frustrated spin systems, thin films and super-lattices. He uses various theoretical methods such as exact solutions in two dimensions and Green’s function methods, as well as sophisticated high-performance Monte Carlo simulation techniques. Recently, he is also interested in using statistical physics models to study social phenomena (sociophysics) and economic issues (econophysics). Please see his publications and his books at his personal website: http://diep.u-cergy.fr/indexnfl_en.html."
The Award will consist of 500 Swiss Francs and a certificate.
Terms and Conditions:
- Full paper must be submitted to ECEA-5
- Originality / Novelty of the paper
- Significance of Content
- Scientific Soundness
- Interest to the readers
- English language and style
Call for Papers
e-conferences, virtually anywhere
5th International Electronic Conference on Entropy and Its Applications
The Chairs and the Scientific Committee Members are pleased to announce the Call for Papers for the 5th International Electronic Conference on Entropy and Its Applications and to invite each researcher working in this exciting field to share his/her recent results with his/her colleagues around the world.
The conference will be organized into six Sessions, which reflect the interdisciplinary nature of entropy and its applications:
Session A: Thermodynamics and Statistical Physics
Session B: Information Theory, Probability, Statistics and Artificial Intelligence
Session C: Quantum Information and Quantum Computing
Session D: Complex Systems
Session E: Biological Systems
Session F: Astrophysics, Cosmology and Black Holes
We look forward to receiving contributions in response to this call and will be glad to provide any further information to interested parties. Questions may be addressed to the Entropy editorial office at [email protected] or [email protected].
Thank you in advance for your attendance of this conference and look forward to a stimulating exchange.
Abstract submission deadline: 13 September 2019 13 October 2019
Notification of acceptance: 30 September 2019 20 October 2019
Submission of full paper and/or poster/presentation deadline: 8 November 2019
Conference open: 18–30 November 2019
Instructions for Authors
- Scholars interested in participating with the conference can submit their abstract (about 200-250 words) online on this website until 13 September 2019 13 October 2019.
- The Conference Committee will pre-evaluate, based on the submitted abstract, whether a contribution from the authors of the abstract will be welcome for the 5th International Electronic Conference on Entropy and Its Applications. All authors will be notified by 30 September 2019 20 October 2019 about the acceptance of their abstract.
- If the abstract is accepted for this conference, the author will be invited to prepare a full description of their work (max. 8 pages), optionally along with a PowerPoint presentation /poster, until the submission deadline of 8 November 2019.
- The conference proceedings papers and presentations will be available on https://sciforum.net/conference/ecea-5 for discussion during the time of the conference 18 November–30 November 2019.
- Accepted papers will be published in the Journal Proceedings. After the conference, the authors are recommended to submit an extended version of the proceeding papers to the Entropy Special issue with 20% discount of the APC charges.
Manuscripts should be prepared in MS Word or any other word processor and should be converted to the PDF format before submission. The publication format will be PDF. The manuscript should count at least 3 pages (including figures, tables and references).
Authors are encouraged to prepare a presentation in PowerPoint or similar software, to be displayed online along with the Manuscript. Slides, if available, will be displayed directly in the website using Sciforum.net's proprietary slides viewer. Slides can be prepared in exactly the same way as for any traditional conference where research results can be presented. Slides should be converted to the PDF format before submission so that our process can easily and automatically convert them for online displaying.
Authors are also encouraged to submit video presentations. If you are interested in submitting, please contact the conference organizer ([email protected]) to get to know more about the procedure.
Tips for authors: If you would like to prepare a video (15-20 minutes) based on your PPT presentation, you may use the "record slide" function in the PowerPoint. After recording, you can save the file as type: MPEG-4 Viedo (*.mp4).
It is the authors' responsibility to identify and declare any personal circumstances or interests that may be perceived as inappropriately influencing the representation or interpretation of clinical research. If there is no conflict, please state here "The authors declare no conflict of interest." This should be conveyed in a separate "Conflict of Interest" statement preceding the "Acknowledgments" and "References" sections at the end of the manuscript. Financial support for the study must be fully disclosed under "Acknowledgments" section. It is the authors' responsibility to identify and declare any personal circumstances or interests that may be perceived as inappropriately influencing the representation or interpretation of clinical research.
MDPI AG, the publisher of the Sciforum.net platform, is an open access publisher. We believe that authors should retain the copyright to their scholarly works. Hence, by submitting a Communication paper to this conference, you retain the copyright of your paper, but you grant MDPI AG the non-exclusive right to publish this paper online on the Sciforum.net platform. This means you can easily submit your paper to any scientific journal at a later stage and transfer the copyright to its publisher (if required by that publisher).
A. Thermodynamics and Statistical Physics
- classical thermodynamics
- chemical thermodynamics
- equilibrium thermodynamics
- non-equilibrium thermodynamics
- equilibrium statistical mechanics
- non-equilibrium statistical mechanics
- stochastic thermodynamics
- fluid mechanics
- numerical simulations in thermodynamics and statistical physics
Prof. Dr. Philip Broadbridge, La Trobe University, Melbourne, Australia
Prof. Dr. Hung T. Diep, University of Cergy-Pontoise, Cergy-Pontoise cedex, France
B. Information Theory, Probability, Statistics, and Artificial Intelligence
- Bayesian inference
- statistical inference
- information entropy
- information divergences
- information geometry
- pattern recognition
- machine learning
- deep learning
- natural language processing
- channel capacity
- source coding
- channel coding
- signal processing
Prof. Dr. Ercan Kuruoglu, Italian National Council of Research, Pisa, Italy
Prof. Dr. Geert Verdoolaege, Ghent University, Ghent, Belgium
C. Quantum Information and Quantum Computing
- quantum computing
- quantum simulation
- quantum communication
- quantum sensors
- quantum metrology
- quantum software
- fundamental aspects of quantum information
Prof. Dr. Göran Wendin, Chalmers University of Technology, Gothenburg, Sweden
D. Complex Systems
- information theory
- entropy measure
- coarse-graining procedure
- nonlinear analysis
Dr. Anne Humeau-Heurtier, University of Angers, Angers, France
E. Biological Systems
- information, entropy, mutation, epigenetics, recombination, speciation
- transmission, inheritance, transcription, translation, reproduction, learning, adaptation, natural selection, sexual selection, behaviour
- movement of molecules, dispersal of gametes or seeds or individuals
Prof. Dr. William B. Sherwin, UNSW Sydney, Sydney, Australia