Program Book - Waseda University

Theory and Applications of

Models of Computation

15th

Annual Conference on

Kitakyushu International Conference Center,

Kokura Station, Kitakyushu (City), Japan

13-16 April 2019

In Association with Proceedings published by

Professor Junzo Watada Professor Emeritus

Waseda University, Japan Chair, Programme Committee

IPS Graduate School, Waseda University, 2-7 Hibikino,

Wakamatsu. Kitakyushu 808-0135 JAPAN

Mobile: +81-90-3464-4929 E-Mail : [email protected]

Professor T V Gopal CEG Campus,

Anna University, Chennai, India Co-Chair, Programme Committee

Department of Computer Science and Engineering

College of Engineering Anna University

Chennai - 600 025, INDIA Ph : (Off) 22351723 Extn. 3340

Mobile: +91 9840121302 E-Mail : [email protected];

[email protected]

Program Book

Organization

Steering Committee Manindra

Agrawal

Indian Institute of Technology,

Kanpur, India

Jin -Yi Cai University of Wisconsin, USA

John Hopcroft Cornell University, USA

Ansheng Li Beihang University, Beijing,

China

Zhiyong Liu Institute of Computing

Technology, Chinese Academy

of Sciences, China

Conference and Program Committee Chair Junzo Watada Waseda University, Japan

Program Committee Co-chair T. V. Gopal Anna University, Chennai, India

Finance Committee Chair Yoshiyuki

Matsumoto

Shimonoseki City University,

Japan

Registration Committee Chair Yoshiyuki

Yabuuchi


Japan

Registration Committee Co-Chair Hiroshi Sakai Kyushu Institute of Technology,

Japan

Program Committee Manindra

Agrawal


Kanpur, India

Klaus Ambos-

Spies

Heidelberg University, Germany

Abdel Monim

Artoli

King Saud University, Saudi

Arabia

Valentina Emilia

Balas

Aurel Vlaicu University of Arad,

Romania

Hans L.

Bodlaender

Utrecht University/Eindhoven

University of Technology, The

Netherlands

Anthony Bonato Ryerson University, Canada

Cristian S.

Calude

The University of Auckland,

New Zealand

Venkatesan

Chakaravarthy

IBM Research, India

Partha Pratim

Das


Kharagpur, India

Maya Dimitrova Institute of Robotics, Bulgarian

Academy of Sciences, Bulgaria

Antonio

Fernandez Anta

IMDEA Networks Institute,

Spain

Toshihiro Fujito Toyohashi University of

Technology, Japan

Wu Guohua Nanyang Technological

University

Kouichi Hirata Kyushu Institute of Technology,

Japan

John Hopcroft Cornell University, USA

Aaron D. Jaggard U.S. Naval Research Laboratory,

USA

Pushkar Joglekar Vishwakarma Institute of

Technology, Pune, India

Jan Kratochvil Charles University, Czech

Republic

Roman Kuznets TU Wien, Austria

Steffen Lempp University of Wisconsin-

Madison, USA

Angsheng Li

Zhiyong Liu

Beihang University

Institute of Computing

Technology, Chinese Academy

of Science, China

Johann

Makowsky

Technion Israel Institute of

Technology, Israel

Klaus Meer BTU Cottbus-Senftenberg,

Germany

Philippe Moser National University of Ireland,

Maynooth, Ireland

Masaaki

Nagahara

The University of Kitakyushu,

Japan

Pan Peng University of Sheffield,

Sheffield, UK

Jose Rolim University of Geneva,

Switzerland

Hiroshi Sakai

Yaroslav

Sergeyev

Kyushu Institute of Technology,

Japan University of Calabria,

Italy

Rudrapatna

Shyamasundar

Tata Institute of Fundamental

Research and Indian Institute of

Technology, Mumbai

Frank Stephan

Gopal Tadepalli

National University of Singapore,

Singapore Anna University, India

Junzo Watada Waseda University, Japan

Yoshiyuki

Yabuuchi


Japan

Thomas

Zeugmann

Hokkaido University, Japan

Naijun Zhan Institute of Software, Chinese

Academy of Sciences, China

Akshay, S. Liu, Jiang

B. Krishna

Kumar

Meadows, Catherine

Fujiwara, Hiroshi N. R., Aravind

Ishii, Toshimasa Phawade, Ramachandra

Jiao, Li R. S. Bhuvaneswaran

Kar, Purushottam Rao, Raghavendra

Kimura, Kei Siromoney, Arul

Kucera, Antonin Xue, Bai

In Association with:

Preface

Theory and Applications of Models of Computation is a series of Annual Conferences

addressing all major areas in computer science; mathematics, especially logic; and physical

sciences, particularly with regard to computation and computability theory. The earlier

editions of these conferences were held at: TAMC 2004, Beijing; TAMC 2005, Kunming;

TAMC 2006, Beijing; TAMC 2007, Shanghai; TAMC 2008, Xi'an; TAMC 2009, Chang Sha;

TAMC 2010, Prague; TAMC 2011, Tokyo, Japan; TAMC 2012,Beijing, China; TAMC 2013,

Hong Kong, China., TAMC 2014, Chennai, India; TAMC 2015, Singapore; TAMC 2016 -

2017, Bern, Switzerland.

The 15th

Annual Conference TAMC 2019 was organized at Kitakyushu, Japan. The core

challenge is the complexity of describing problems in a logical formalism over finite

resources. Computational Models facilitate the discovery of the connections between the

computational complexity and the complexity of the problem formally specified.

The core team organizing TAMC 2019 was active over the past one year. The Call For Papers

attracted very good quality papers from 29 countries across the world. Professionals from 36

countries have been associated with TAMC 2019 as members of various committees, authors

and reviewers.

The Ministry for Human Resource Development, Government of India has decided to use

'Turnitin' software to curb "similarities" in Ph.D level publications. For practical use of this

policy, the following four color bands are being used in India.

1. Green: 1%to - 24% similarity index and means normal. or accepted

2. Yellow: 25-49% similarity index which is the second stage which means high

3. Orange (50-74% similarity index)

4. Red (75-100% similarity index)

Both iThenticate and Turnitin share the same underlying technology. The latter has a slant for

classroom work and hence less stringent. iThenticate is the last program in the series of

Turnitin programs. Leading academic institutions all over the world have adapted the

appropriate use of both these tools. Interpreting the results of "Similarity Check" software was

done with care and caution.

After the similarity check was completed 60 submissions went for reviews. Each submission

had two reviewers and there was spell of discussions. Finally 43 submissions were accepted

for inclusion in the proceedings and presentation during TAMC 2019. In addition, there are

six key – note addresses for professionals actively working in the areas related to TAMC

2019. Nearly 80% of the topics listed for TAMC series are covered in TAMC 2019.

TAMC 2019 was organized at the Kitakyushu International Conference Center which is the

core facility in the International Convention Zone, located in close proximity to the North Exit

of the JR Kokura Station. This innovative building, inspired by a ship’s bridge and choppy

waves, was designed by Isozaki Arata, one of Japan’s most world-renowned architects. The

wall facing the sea is made of glass, creating a wide open space that incorporates the maritime

scenery. The Main Hall and International Meeting Room are equipped with facilities for

simultaneous interpreting in 4 languages.

The conference team for TAMC 2019 thanks the key – note speakers, authors of the accepted

papers and all the members of various committees.

T.V.Gopal

Junzo Watada

PROGRAM SCHEDULE

13 April 2019

15:00-17:00 Registration

18:00-19:30 Warm Welcome

14 April 2019

8:00 Registration

9:00 Opening Ceremony

9:00-10:00 KEYNOTE Speech 1

Disruptive Innovation Based Schools – Are They Possible?

Maya Dimitrova (Institute of Systems Engineering and Robotics, Bulgarian Academy of

Sciences, Bulgaria)


Rough Set Approaches to Data Mining

Masahiro Inuiguchi (Graduate School of Engineering Science, Osaka University, Japan)

11:00-11:30 Coffee Break

11:30-13:00 Battery Scheduling Problem

Aakash Agrawal, Krunal Shah, Amit Kumar, and Ranveer Chandra

The Volume of a Crosspolytope Truncated by a Halfspace - Ei Ando and Shoichi Tsuchiya

Computable Isomorphisms of Distributive Lattices - Nikolay Bazhenov, Manat Mustafa,

and Mars Yamaleev

Minmax-Regret Evacuation Planning for Cycle Networks - Robert Benkoczi, Binay

Bhattacharya, Yuya Higashikawa, Tsunehiko Kameda, and Naoki Katoh

Planar Digraphs for Automatic Complexity - Achilles A. Beros, Bjørn Kjos-Hanssen, and

Daylan Kaui Yogi

13:00 – 14:30 Lunch Break

14:00 – 15:30 Approximation Algorithms for Graph Burning - Anthony Bonato and Shahin Kamali

Sublinear Decoding Schemes for Non-adaptive Group Testing with Inhibitors - Thach V.

Bui, Minoru Kuribayashi, Tetsuya Kojima, and Isao Echizen

Compacting and Grouping Mobile Agents on Dynamic Rings - Shantanu Das, Giuseppe Di

Luna, Linda Pagli, and Giuseppe Prencipe

Maximum Independent and Disjoint Coverage - Amit Kumar Dhar, Raghunath Reddy

Madireddy, Supantha Pandit and Jagpreet Singh

Algorithms for Closest and Farthest String Problems via Rank Distance - Liviu P. Dinu,

Bogdan C. Dumitru, and Alexandru Popa


16:00 – 17:30 Computable Analysis of Linear Rearrangement Optimization - Amin Farjudian

On the Power of Oritatami Cotranscriptional Folding with Unary Bead Sequence -

Szilárd Zsolt Fazekas, Kohei Maruyama, Reoto Morita and Shinnosuke Seki

Stochastic Programming for Energy Plant Operation - Tomoki Fukuba, Takayuki Shiina,

and Ken-ichi Tokoro

Compact I/O-Efficient Representation of Separable Graphs and Optimal Tree Layouts -

Tomáš Gavenčiak and Jakub Tětek

Unshuffling Permutations: Trivial Bijections and Compositions - Guillaume Fertin,

Samuele Giraudo, Sylvie Hamel and Stéphane Vialette


18:00 – 19:30 Continuous Team Semantics - Åsa Hirvonen, Juha Kontinen, and Arno Pauly

Exact Satisfiabitity with Jokers - Gordon Hoi, Sanjay Jain, Sibylle Schwarz, and Frank

Stephan

Theoretical Model of Computation and Algorithms for FPGA-Based Hardware

Accelerators - Martin Hora, Václav Končický, and Jakub Tětek

On the Complexity of and Algorithms for Min-Max Target Coverage On a Line

Boundary - by Peihuang Huang, Wenxing Zhu, and Longkun Guo

Online Travelling Salesman Problem on a Circle - Vinay A. Jawgal, V. N. Muralidhara, and

P. S. Srinivasan

15 April 2019

8:00 Registration


Approach to Machine Learning without Neural Networks

Akihiro Yamamoto (Gradudate Scool of Informatics, Kyoto University, Japan


Fuzzy Cognitive Maps in Modelling Real Life Problems

Laszlo T. Koczy (Budapest University of Technology and Economics and Szechenyi Istvan

University (Gyor), Hungary


11:30-13:30 Second-Order Linear-Time Computability with Applications to Computable Analysis -

Akitoshi Kawamura, Florian Steinberg, and Holger Thies

Consistency as a Branching Time Notion - Astrid Kiehn and Mohnish Pattathurajan

Finite Choice, Convex Choice and Sorting - Takayuki Kihara and Arno Pauly

The Number of Languages with Maximum State Complexity - Bjørn Kjos-Hanssen and Lei

Liu

Deterministic Coresets for Stochastic Matrices with Applications to Scalable Sparse

PageRank - Harry Lang, Cenk Baykal, Najib Abu Samra, Tony Tannous, Dan Feldman, and

Daniela Rus

GPU Based Horn-Schunck Method to Estimate Optical Flow and Occlusion - Vanel

Lazcano and Francisco Rivera

Robot Computing for Music Visualization - Pei-Chun Lin, David Mettrick, Patrick C. K.

Hung, and Farkhund Iqbal

Combinatorial Properties of Fibonacci Arrays - Manasi S. Kulkarni, Kalpana Mahalingam,

Sivasankar Mohankumar


14.30 Half Day Tour

Departure at the exit of the International Conference Hall at 14.30

18:30 Banquet "Marrygold Mojiko Geihinkan"

20:30 Bus Returning to Convention Center / Kokura Station

16 April 2019

8:00 Registration


Structural Information Theory and Its Applications

Angsheng Li State Key Laboratory of Software Development Environment, School of Computer

Science, Beihang University, China


Unconventional Proving Techniques in Cyber – Physical Systems

Dr. T V Gopal, Department of Computer Science and Engineering, College of Engineering

Anna University, India


11:30-13:00 Watson-Crick Jumping Finite Automata - Kalpana Mahalingam, Rama Raghavan, Ujjwal

Kumar Mishra

Dispersion of Mobile Robots: The Power of Randomness - Anisur Rahaman Molla and

William K. Moses Jr.

Building Resource Auto-scaler with Functional-Link Neural Network and Adaptive

Bacterial Foraging Optimization - Thieu Nguyen, Binh Minh Nguyen, and Giang Nguyen

On the Enumeration of Bicriteria Temporal Paths - Petra Mutzel and Lutz Oettershagen

An Output-Sensitive Algorithm for the Minimization of 2-Dimensional String Covers -

Alexandru Popa and Andrei Tanasescu


14:00 – 15:30 Introducing Fluctuation into Increasing Order of Symmetric Uncertainty for

Consistency-Based Feature Selection - Sho Shimamura and Kouichi Hirata

Card-Based Cryptography with Invisible Ink - Kazumasa Shinagawa

Read-Once Certification of Linear Infeasibility in UTVPI Constraints - K. Subramani and

Piotr Wojciechowski

Generalizations of Weighted Matroid Congestion Games: Pure Nash Equilibrium,

Sensitivity Analysis, and Discrete Convex Function - Kenjiro Takazawa

The Complexity of Synthesis for 43 Boolean Petri Net Types - Ronny Tredup and Christian

Rosenke


16:00 – 17:30 Space Lower Bounds for Graph Stream Problems - Paritosh Verma

Bounded Jump and the High/Low Hierarchy - Guohua Wu and Huishan Wu

Supportive Oracles for Parameterized Polynomial-Time Sub-Linear-Space Computations

in Relation to L, NL, and P - Tomoyuki Yamakami

Dynamic Average Value-at-Risk Allocation on Worst Scenarios in Asset Management -

Yuji Yoshida and Satoru Kumamoto

First-Order vs. Second-Order Encodings for LTLf -to-Automata Translation - Shufang

Zhu, Geguang Pu, and Moshe Y. Vardi

17:30 Closing Session

Keynote Speech

Maya Dimitrova Institute of Systems Engineering and

Robotics, Bulgarian Academy of Sciences

Bulgaria

Topic : Disruptive Innovation Based Schools – Are They Possible?

Abstract : In the school of the future each teacher or a team of teachers, instead of paper and pencil tools,

can have an array of tools - robotic scenarios, Virtual Reality based demonstrations and

intelligent lesson-enhancing advice systems - to design up-to-date attractive and entertaining

educational courses. Moreover, intelligent desks will be able to monitor gaze direction and

count blinks in order to define moments in the lesson when the attention of the student is

optimal. By knowing the attentional dynamics it is possible to modify the lesson to avoid

repetition, yet provide additional help for the unlearned material. The lessons will be deeply

individualized and adapted to the student learning difficulties, or talents, and will include even

less in number examination tests. In such a classroom no students will be delayed by the

others, or intimidated by being slower than the group. In such a scenario the social

communication between the children will be supported and will not be based on competition,

but on collaboration and mutual care.

The keynote speech will focus on the main ideas and results of the ongoing H2020-MSCA-

RISE-2017 project “CybSPEED: Cyber-physical systems for pedagogical rehabilitation in

special education”, involving researchers from Bulgaria, Greece, France, Spain, Japan, Chile

and Morocco, and the main lessons learned in the context of introducing disruptive innovation

in the school of the future.

The book “Cyber-physical systems for social applications” is oriented towards achieving these

aims by providing relevant theoretical frameworks and the latest empirical findings in the

areas of designing socially-oriented cyber-physical systems.

Biography : Maya Dimitrova received her higher education in psychology from St Petersburg, Russia, in

1885. She obtained her MSc in psychology (by research) (with distinction) from Warwick

University, UK, in 1995 and her PhD on Adaptive Human Computer Interface from Institute

of Control and Systems Research at BAS in 2002. She is currently Associate Professor at the

Institute of Robotics at BAS, working on humanoid robotics for learners with special needs.

Since 2017 she engaged with an EU funded project CybSPEED on “Cyber-physical systems

for pedagogical rehabilitation in special education

Keynote Speech

Masahiro Inuiguchi Graduate School of Engineering Science

Osaka University

Japan

Topic : Rough Set Approaches to Data Mining

Abstract : Rough set theory provides useful tools for reasoning from data. Attribute reduction and rule

induction are well developed techniques based on rough set theory. They are applied to various

fields including data analysis, signal processing, knowledge discovery, machine learning,

artificial intelligence, medical informatics, decision analysis, granular computing, Kansei

engineering, and so forth. In the approach, the lower approximation (a set of objects whose

classification is consistent in all given data) and upper approximation (a set of possible

members in view of given data) are calculated for each decision class.

In this talk, we introduce rough set approaches to data analysis. After describing fundamentals

of the classical rough sets, several methods for attribute reduction and minimal length rule

induction are introduced. Then generalization and extension of rough set approaches are

shown. First, we describe relation-based generalizations of rough sets and data analysis based

on them. In these approaches, the indiscernibility relation which is an equivalence relation in

the classical rough sets is generalized to any relation. General approaches from two different

viewpoints are described. Two special cases, i.e., rough set approaches under dominance

relation and missing values, demonstrate the usefulness of the approaches. Second, we extend

the classical rough set approaches to the analysis of imprecise decisions. By considering the

imprecise decisions, we show that a hierarchy of attribute reduction and a different aspect of

attribute importance can be analyzed. Moreover, we demonstrate that a set of imprecise

decision rules works better than a set of precise decision rules. This property is applied to a

privacy protection in data publication. Throughout this talk, we show the ideas of rough set

approaches potentially applicable to various fields involving data analysis.

Biography : Masahiro Inuiguchi received B.E., M.E. and D.E. degrees in industrial engineering at Osaka

Prefecture University, in 1985, 1987 and 1991. He worked as a Research Associate at Osaka

Prefecture University (1987-1992), Associate Professor at Hiroshima University (1992-1997),

Associate Professor at Osaka University (1997-2003). At present, he is a Full Professor at

Osaka University. His interests include possibility theory, fuzzy programming, rough sets and

multiple criteria decision analysis with interval models. He works as area editor of Fuzzy Sets

and Systems (FSS), Fuzzy Optimization and Decision Making (FODM), and Journal of

Multiple Criteria Decision Analysis (MCDA), as the associate editor of ITOR and 4OR, and

members of editorial boards of several other Journals including EJOR.

Keynote Speech

Akihiro Yamamoto Gradudate Scool of Informatics

Kyoto University

Japan

Topic : Approach to Machine Learning without Neural Networks

Abstract : Because of the great success of deep learning, many imagine that machine learning should be

implemented with neural networks well-structured for data which they would like to analyze.

Going back to the original meaning of machine learning, we should be allowed construct

learning mechanism without neural networks. In particular neural networks are suited for real

valued vector data, but are not always for discrete structured data. Discrete structured data,

such as character sequences, trees, and graphs, have mathematical theories and algorithms

particular to each, and learning algorithms treating such data should be designed based on the

theories and algorithms.

In this talk we would introduce recent results on learning from discrete structured data. The

first type of data are trees. In order to apply the idea of principle component analysis to tree

data, we investigate fast computation methods for computing distances between trees by using

integer programming technique. Second we report a result on learning logical formulae in

first order logic, which has been called inductive logic programming. Recent developments of

computing Boolean functions could be applied for various types of secrete data, and logical

formulae should be of such types. We show how binary decision diagrams should be applied

to inductive logic programming.

Biography : Akihiro Yamamoto received the B.S. degree from Kyoto University in 1985, and the M.S. and

Dr.Sci. degrees from Kyushu University in 1987 and 1990 respectively. From 1990 to 2003 he

was an associate professor at Hokkaido University. He was also a researcher of PREST at

JST, and a visiting researcher at Oxford University and Technische Hochschule Darmstadt.

Since October 2003 he has been a professor of Graduate School of Informatics, Kyoto

University. From April 2015 to March 2018 he was the dean of the school. Since April 2018

he has also held the position of the director of Center for Innovative Research and Education

in Data Science.

His research interest Includes foundations of Machine Learning and Data Mining, in

particular, with theory of computation, mathematical logic, and computational algebra.

Keynote Speech

Laszlo T. Koczy Budapest University of Technology and Economics

1111 Budapest,

Műegyetem rkp. 3.

and

Szechenyi Istvan University (Gyor)

H-9026 Győr, Egyetem tér 1., Hungary

Topic : Fuzzy Cognitive Maps in Modelling Real Life Problems

Abstract : Fuzzy Cognitive Maps (FCM) are a set of tools merging the properties of Artificial Neural

Networks (NN) and fuzzy systems. They are bipolar directed fuzzy graphs that consist of

Concepts (nodes) assigned fuzzy membership degrees expressing the intensity or level of the

property associated with the given concept; and of directed influence values (edges) which

have a sign (expressing whether the influence is positive or negative) and a fuzzy membership

degree of the intensity of the influence. E.g., if C1 and C2 are two concepts, µ1 is the degree of

C1 and µ2 of C2, the directed edges e12 and e21 have ± µ12 and ± µ21, respectively, denoting that

C1 influences C2 either in the positive sense (increasing its level) with + µ12, or in the negative

sense (decreasing C2) with - µ12. FCMs are suitable to model multicomponent systems with

multiple mutual influences, such as, e.g. a management system. Because of the NN-type

behaviour of FCMs, they may be used for simulating a system that changes in time, and

possibly converges to a steady state (called fixed point attractor). It is interesting to fit the

FCM to a series of historical data and calculate the expected development of the system in the

future – a way for time series prediction. Such fitting may happen by various machine

learnning techniques, such as evolutionary and memetic algorithms, among others. In this case

the FCM model will be determined by theis fitting, including all membership degrees at the

concepts and at the edges. On the other hand, often experts determine these values

(approximately) in advance, and thus the FCM model is ready for prediction - starting from a

known initial state.

In our past reserch we found real life applications (such as waste management, bank

management, etc.) where one or both of the starting data were available. Especially interesting

is the case when experts determine the membership degrees and then the FCM is matched to

the historical data. In some case we found contradiction in the contents and this fact started a

deeper methodological research about how to fit the proper FCM to a given problem, and how

to transform the size and complexity of such models, so that theyt reemain intuitive, and

tyransparent, while the fineness and precision of the model is satisfactory from the point of

view of the application field.

This talk will give some formal definitions in connection with FCMs, and then show the

iterative (NN-like) behaviour. The next question to be discussed will be the existence and

number of fixed point attractors (sustainable state of the system to be modelled), a topic that

has not yet been satisfactorily clarified in the literature. In this respect we have presented some

entirely new results in the form of mathematical statements.

In the next a novel extension, the Fuzzy Grey Cognitive Map will be introduced, and it will be

shown that they are more adequate in modelling real life systems, as human experts often

hesitate in giving concrete degrees, and subjectivity and uncertainty of the experts prevent any

clear and deterministic membership values at the concepts and edges. The next real application

motivated extension is the application of fuzzy numbers for determining the memberships.

Some results about the existense and uniqueness of a fixed point attractor are also stated here.

The other main stream of the research reported here focuses on the transformation of FCMs (as

far in the classic sense), especially by reducing the size of the model, namely, the number of

concepts, which of course also results in the drastic reduction of the number of edges in the

new model. A novel reduction technique, based on a very special FCM compatible metrics (a

distance measure between two concepts where all the influence degrees to other concepts and

the way around are known and compared) is proposed, illustrated by a real life problem, where

the obvious contradiction between the expert assessment and the historical data points towrds

the necessity of the refinement of the mmodel, and then, towards a transformation that leads to

the emerging of new concepts that have to be interpreted in the context of the application

problem. An extensive simulation, applying a large number of real life and randomly generated

examples for large size FCMs and respective reductions allows the discussion of to what

extent such a transformation preserves the properties of the original FCM, with a special stress

on the existence, number and parameters of the fixed points.

The last topic of the talk is about the sensitivity of the FCMs, where it may be assumed that

expert assessments are subjective and uncertain, and the uncertainty or error in the

membership values may cause instability, even, a total change of behaviour of the FCM. One

more real life example will be presented and evaluated.

Some future directions of further related research goals will be proposed at the end of the talk.

Biography : Laszlo T. Koczy received the M.Sc., M.Phil. and Ph.D. degrees from the Technical University

of Budapest (BME) in 1975, 1976 and 1977, respectively; and the D.Sc. degree from the

Hungarian Academy of Science in 1998. He spent his career at BME until 2001, and from

2002 at Szechenyi Istvan University (Gyor, SZE). He has been from 2002 to 2011 Dean of

Engineering, and from 2013 to current, President of the University Research Council and of

the University Ph.D. Council. From 2012 he has been a member of the Hungarian

Accreditation Committee (for higher education), appointed by the Prime Minister, and elected

Chair of the Engineering and Computer Science sub-committee, Acting Chair of the Professors

and Ph.D. sub-committee, and has been a member of the National Doctoral Council since

2012.

He has been a visiting professor in Australia (ANU, UNSW, Murdoch and Deakin), in Japan

(TIT, being LIFE Endowed Fuzzy Theory Chair Professor), in Korea (POSTECH), Austria (J.

Kepler U.), Italy (U. of Trento), and Poland (AGH University) etc.

His research interests are Intelligent Modeling and algorithms with multidisciplinary

applications including management and logistics. He has published over 620 articles, most of

those being refereed papers, and several text books on the subject. He has over to 2727

independent citations (mtmt.hu) and his Hirsch-index is 37 by Google Scholar (based on

~5626 citations there).

His main results are: he did introduce the concept of rule interpolation in sparse fuzzy models,

and hierarchical interpolative fuzzy systems, fuzzy Hough transform, and also fuzzy signatures

and fuzzy situational maps, further fuzzy signature state machines among others. He also

proposed a family of memetic algorithms (Bacterial Memetic Algorithm, Discrete Bacterial

Memetic Algorithm) which, among others, provides the best solutions to the Traveling

Salesman Problems and Traveling Repairman Problems. His research interests include

applications of CI for management, transportation and logistics, control and decision support

information retrieval, etc.

He was a Lead Guest Editor at Complexity. He was an Associate Editor of IEEE TFS for

several periods, and is now AE of Fuzzy Sets and Systems, Int. Journal of Fuzzy Systems,

Journal of Advanced Computational Intelligence, Int. J. of Fuzzy Systems, Soft Computing,

etc. He is a Fellow of International Fuzzy Systems Association, of International Society of

Management Engineers and of the Hungarian Academy of Engineering. He was the founding

President and is now the Life Honorary President of the Hungarian Fuzzy Association, was

President, etc. of IFSA, AdCom member of IEEE CIS, and of IEEE Systems Council, etc.

He is a member of the St. Stephan Academy of Science (2016), and of the Polish Academy of

Science (2017)

Keynote Speech

Angsheng Li State Key Laboratory of Software Development Environment,

School of Computer Science, Beihang University,

100083 Beijing, P.R. China

Topic : Structural Information Theory and Its Applications

Abstract : Shannon 1948 defined the metric of the entropy of a probability distribution or a random

variable. The Shannon's theory answers two fundamental questions in communication theory,

the ultimate data compression (entropy) and the ultimate transmission rate of communication

(the channel capacity defined by using mutual information). Shannon's theory started the

classical information theory, providing the principle for us to understand the notion of

information in the current science. The current Computer Science has become very much

different from that in the last century in that, computer plays an important role in almost every

aspect of our life and our world, instead of simply "computing".

The current computer has changed its role from "computing of functions " to "information

processing" in a wider range of the universe such as massive graphs, and structured or

unstructured noisy data. The classic information theory, studying the principles of the simple

objects of random variables (which are actually functions), is apparently insufficient to support

the "information processing" of the current computer science, due to the fact that the universe

of computer information processing is much larger than that of the Shannon information

theory.

A grand challenge is hence: Is there a theory that supports the information processing of the

current computer? The key to this question is to define the information that is embedded in a

system such that the information of the system distinguishes the laws from the noises of the

system.

Recently, we proposed the notion of encoding tree of graphs and the notion of structural

entropy, and established the fundamental theory of the structural information.

Angsheng Li is a Professor of Beihang University, School of Computer Science from 2018,

July. He was research professor of Institute of Software, Chinese Academy of Sciences from

1999 to 2018, July. He was born in 1964. He got bachelor in Mathematics in Yunnan Normal

University in 1984, and ph D in 1993 in Institute of Software, Chinese Academy of Sciences.

He had been working for the Institute of Software, Chinese Academy of Sciences from 1993 to

2018, July after he finished his ph D. From 1998 to 2002, he was a visitor and research fellow

in the University of Leeds, UK, working with Professor Barry Cooper in Computability

Theory. In 2003, he was awarded the Distinguished Young Investigator award of the National

Natural Science Foundation of China. In 2008, he was selected by the Hundred Talent

Program of Chinese Academy of Sciences. From 2008 to 2009, he was a visiting scientist in

Computer Science Department, Cornell University, US, working with Professor Juris

Hartmanis (the founder of Computational Complexity Theory). His research areas include

Computability Theory, Computational Theory, Network Theory and Information Science. His

current interests focus on massive graph algorithms, information theory, and information

theoretical foundation of artificial intelligence.

Keynote Speech

Dr. T V Gopal Professor

Department of Computer Science and Engineering

College of Engineering

Anna University

Chennai - 600 025, INDIA

Topic : Unconventional Proving Techniques in Cyber – Physical

Systems

Abstract : Cyber - Physical Systems [CPS] are “Engineered systems that are built from, and depend

upon, the seamless integration of computational algorithms and physical components”. CPS

have the potential to provide much richer functionality - including efficiency, flexibility,

autonomy, and reliability – than systems that are loosely coupled, discrete, or manually

operated. CPS also can create vulnerability related to protection, security and reliability. This

can result in a chaotic collapse around the many new complex and powerful technological

systems we rely on. The very complexity and interconnectedness of such CPS warrants

unconventional proofing to unravel. Moreover, CPS is diffused across the social fabric. The

sociology of mathematics is quite elusive for the construction of formal proofing in CPS.

The gap between rigorous argument and formal proof in the sense of mathematical logic is one

that will close in CPS.

The frightening possibility is that the question of what is a proof may reach the law courts.

What does it mean when mainstream explanations of our physical reality are based on what

even scientists cannot comprehend? The generic characteristics of CPS are:

Self-organization

Interdependence

Feedback

Far from equilibrium

Exploration of the space of possibilities

History and path dependence

Creation of new order

Cyber risk is an increasing concern in the complex, connected world of CPS. The complexity

of the ecosystem, the connectivity of devices and the criticality of devices and services all

increase risk, and the necessary formal proofs are elusive to take an effective action. „Fake

People” is the Case Study presented in this address to illustrate unconventional proofing in

Humane Security Engineering of CPS.

References:

1. Gopal T V, "The Physics of Evolving Complex Software Systems", International

Journal of Engineering Issues [IJEI], Vol. 2015, no. 1, pp. 33-39.

2. Gopal T V, "Modeling Cyber - Physical Systems for Engineering Complex

Software",, International Journal of Engineering Issues [IJEI], Vol. 2015, no. 2, pp.

73-78.

3. Gopal T V,"Engineering Software Behavior in Cyber – Physical Systems",

International Journal of Engineering Issues [IJEI], Vol. 2016, no. 1, pp. 44-52.

4. Gopal T V, "Engineering Logic for Cyber – Physical Systems", International Journal

of Engineering Issues, Vol. 2016, no. 3,pp. 112-120.

5. Gopal T.V. „Beautiful code – circularity and anti-foundation axiom‟, Int. J.

Computational Systems Engineering, Vol. 2, No. 3, 2016, pp.148–154.

6. Gopal T V, “Communicating and Negotiating Proof Events in the Cyber – Physical

Systems”, International Journal of Advanced Research in Computer Science and

Software Engineering, Volume 7, Issue 3, March 2017, pp 236-242.

7. Gopal T. V, Cyber-Physical Systems and Humane Security Engineering, Journal of

Network and Information Security, Vol. 6, No. 2, December 2018, pp 24-31

8. Reuben Hersh (Editor), “18 Unconventional Essays on the Nature of Mathematics,

Springer; 2006.

Biography : Dr. T V Gopal is presently teaching Computer Science and Engineering at the CEG Campus,

Anna University. One of his research areas includes "Science and Spirituality". Dr. T V Gopal

has published around 75 Research Papers. He has written four books and Co-Edited Seven

Conference Proceedings. He is actively associated with many professional societies such as

CSI, IEEE and ACM India Council. He is an Expert Member of the Editorial Advisory Board

of the International Journal of Information Ethics. For further details, please visit:

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