PMAMCM 2017:The 2017 International Conference on
Pure Mathematics, Applied Mathematics and Computational Methods

* Invited and Regular Papers will be published in various Indexed Journals (ISI, SCOPUS, EBSCO, DBLP, ACM, IET/INSPEC, Proquest, Copernicus etc...) based on quality and reviewers' recommendations or in our Books in Springer Verlag. Click here

* Authors will be informed about the title of the Journal before their registration. 

* Contact us by email: support@inase.org   Registration fees       Publication Ethics and Malpractice Statement     Deadlines
 (Previous Conference: PMAMCM 2016, Corfu Island, Greece, July 14-17, 2016)

PLENARY SPEAKERS:

Prof. Demetrios Kazakos, Professor of Mathematics, Texas Southern University, Houston, Texas, USA, e-mail: kazakosd@tsu.edu
Co-author: Nancy Griesinger
Title: "The Design of Resilient and Adaptive Communication Networks with Intrusion Detection, Using Statistical and Artifical Intelligence Methods"
Abstract: One important issue is addressed in this paper. It is the security of Communication and Computer Networks, in the context of software based "Cyber attacks". We discuss the use of fastest change detection methods to detect rapid changes of data resulting from Cyberattacks, and the use of Learning Artificial Intelligence tools and methodologies for the same goal. A major part of our work is to address, in a theoretical and systematic context, the issue of Intrusion Detection. Intrusion Detection Methods and Systems (IDMS) exist presently in commercially available systems, and such protection is vital for the normal operation of computer and communication networks, including military, federal, financial, enterprise and industrial networks. However, the existing commercially available network intrusion detection systems have a number of severe shortcomings. More importantly, the existing systems suffer from a tremendous false alarm rate (FAR), are not structured for scalability to an arbitrary number of nodes, they cannot operate well in large scale, very high speed networks, and they cannot detect new, unknown threats. Statistical Detection Theory , Pattern Recognition, Data Clustering and Artificial Intelligence Algorithms are used.



Prof. Michael Gr. Voskoglou, Professor Emeritus of Mathematical Sciences, School of Technological Applications, Graduate Technological Educational Institute of Western Greece, GREECE, e-mail: voskoglou@teiwest.gr
Title: "Use of Fuzzy Numbers for Assessing Human Skills"
Abstract: There used to be a tradition in science and engineering of turning to probability theory when one is faced with a problem in which uncertainty plays a significant role. This was justified when there were no alternative tools for dealing with the uncertainty. Today this is no longer the case. Fuzzy logic (FL), based on the fuzzy sets theory (Zadeh, 1965), provides a rich and meaningful addition to standard logic. The applications which may be generated from or adapted to FL are wide-ranging and provide the opportunity for modelling under conditions which are imprecisely defined, despite the concerns of classical logicians (Klir & Folger, 1988).
In particular, due to its property to characterize with multiple values the frequently appearing in our day to day life ambiguous situations, FL provides a variety of tools for assessment under fuzzy conditions. Such tools were used by the speaker several times in the past including the measurement of a system's uncertainty (Voskoglou, 2011, etc.), the Centre of Gravity (COG) defuzzification technique (Voskoglou, 2012, etc.) and its equivalent variations (Voskoglou, 2015, Subbotin & Voskoglou, 2016), etc.
Fuzzy Numbers (FNs) play an important role in fuzzy mathematics analogous to the role played by the ordinary numbers in crisp mathematics. In this lecture we shall apply a combination of the Triangular (TFNs) and Trapezoidal (TpFNs) FNs (Kauffman & Gupta, 1991) with the COG technique for assessing human skills. Our examples involve student and basket-ball player assessment. Our new fuzzy method is validated by comparing its outcomes with the corresponding outcomes of two traditional assessment methods of the bi-valued logic, the calculation of the mean values and of the Grade Point Average (GPA) index (Swinburne.edu.au, 2014).



Prof. Adela Ionescu, Department of Applied Mathematics, University of Craiova, Romania, e-mail: adelajaneta@yahoo.com
Title: "On a Linearization Method for the Dynamical Systems Associated to Excitable Media Models"
Abstract: The mixing flow methods and techniques recently developed a significant relation between turbulence and chaos, in an area with far from complete solving problems: the flow kinematics. In the present paper there are presented recent results concerning the behavior of the mixing flow dynamical system. Both computational and analytical standpoint are taken into account. From computational standpoint, the challenge is great, as the simulation parameters involve strong nonlinearities for the models, both in 2D and 3D case. Therefore this dynamical system can be considered in the category of the so-called "far from equilibrium systems", widespread between the models of excitable media. From analytical standpoint, the feedback linearisation of this dynamical system issue special interpretations. This technique contains two fundamental nonlinear controller design techniques: input-output linearization and state-space linearization. The approach is usually referred as input-output linearization or feedback linearization and is based on concepts from nonlinear systems theory. The resulting controller includes the inverse of the dynamic model of the process, providing that such an inverse exists. The results will be used for further analysis of 3D mixing flow dynamical system.



Prof. Benabdellah Yagoubi, Department of Electrical Engineering University of Mostaganem, Algeria, e-mail: yagoubibenabdellah@yahoo.com
Title: "The Inverse of the Belonging Individual Probability and the Discrete Wavelet as a Hybrid Technique for Anomalous Detection and Identification"
Abstract: Anomalous detection as well as their identification is a vital domain in control that has been approached by many researchers using various methods such as stochastic techniques, neural networks based-method, and so on... The anomalous can be anything that may deviate from its normal behavior; a fault in machine, a sign of a disease such as a tumor, a heart problem and so on. However, most of the processes representing a normal real behavior are random in practice and thus the peaks representing eventual anomalous may be smeared in the normal process and hence their detection and identification become a difficult task. Various techniques for anomalous detection and diagnosis are being used in many engineering applications. Despite the good results provided by these techniques, there is, however, still more work to do to improve the anomalous detection and identification. We will discuss, therefore in this speech, a hybrid technique based on the inverse of the belonging individual probability (IBIP) and the discrete wavelet (DWT) for anomalous detection and identification. We will try to show, furthermore, in this lecture that this hybrid technique has a great potential to enhance detection and identification of anomalous.



Prof. Adam Ding, Department of Mathematics, Northeastern University, Boston, USA, e-mail: adamding@gmail.com
Title: "Robust Copula Dependence Measure and Equitability"
Abstract: Dependence measure plays an important role in filter-based feature selection. To correctly identify important features with complex relationship in large data sets, we like the measure to be equitable (Reshef et al. Science, 2011): treating all types of functional relationships, linear and nonlinear, equally. We provides a theoretical treatment of equitability, including the self-equitability definition (Kinney and Atwal, PNAS 2014) and a new robust-equitablity definition. The robust copula dependence (RCD) measure based on $L_1$-distance of copula density is shown to be equitable under all equitability definitions. We provide theoretical justification that RCD can be fundamentally easier to estimate than mutual information (MI), the recommended self-equitable measure in Kinney and Atwal. Numerical examples, on synthetic data sets and real data sets illustrate the effect of equitability in feature ranking and selection. Particuarly, selection based on RCD can be more robust to varying sample size than selection through MI and other measures.



Prof. Bijoy Kumar Ghosh, Dick and Martha Brooks Regent Professor of Mathematics and Statistics, Director, Center for Bio Cybernetics and Intelligent Systems, Texas Tech University, Lubbock, USA, e-mail: bijoy.ghosh@ttu.edu
Title: "Iterative Learning Control Problems from Rehabilitation Engineering"
Abstract: The purpose of this talk is to introduce Iterative Learning Control (ILC) Problems and show how these problems can be applied to patients with movement disorders, perhaps resulting from stroke. Stroke affects motor control and typically the command signals from the brain is affected. As a result the affected person is not able to move their arm along a desired trajectory. To remedy this impairment, electrical stimulus is directly applied to the hand muscles to augment the control signals from the brain. In this talk, we show how the additional control stimulus can be learnt iteratively, based on error between the desired and actual trajectories of the motion. A general theory for the ILCs are introduced for Multi Input Multi Output dynamical systems in discrete time. Convergence of the learning scheme has been discussed using Luenberger Observers, Kalman Filters and Parameter Identification based Projection Algorithms.



Prof. Peter Stavroulakis, Technical University of Crete, Crete, Greece, e-mail: pete_tsi@yahoo.gr
Title: "Survivability Quantification Of Wireless Critical Network Systems "
Abstract: The problem of survivability of critical networks systems has been around for a long time. Due to the fact that as a concept survivability consists of various components such as reliability, availability, fault tolerance and security and each one of them could be of major importance and satisfy the requirements of a specific problem, as a whole Survivability did not receive the attention it deserves as far as it concerns its quantification. This keynote speech , for the first time, will attempt to deal effectively with the problem of quantification of Survivability by breaking the critical network system under consideration to a seven layer model and then investigate quantitatively which component of survivability applies to each layer in order to establish an overall quantifiable survivability metric.

• Prof. Stefan Siegmund, Technische Universitaet Dresden, Germany
• Prof. Zoran Bojkovic, Univ. of Belgrade, Serbia
• Prof. Imre Rudas, Obuda University, Budapest, Hungary

• Prof. Ferhan M. Atici, Western KentuckyUniversity, Bowling Green, KY 42101, USA
• Prof. Ravi P. Agarwal, Texas A&M University - Kingsville, Kingsville, TX, USA
• Prof. Martin Bohner, Missouri University of Science and Technology, Rolla, Missouri, USA
• Prof. Dashan Fan, University of Wisconsin-Milwaukee, Milwaukee, WI, USA
• Prof. Paolo Marcellini. University of Firenze, Firenze, Italy
• Prof. Xiaodong Yan, University of Connecticut, Connecticut, USA
• Prof. Ming Mei, McGill University, Montreal, Quebec, Canada
• Prof. Enrique Llorens, University of Valencia, Valencia, Spain
• Prof. Yuriy V. Rogovchenko, University of Agder, Kristiansand, Norway
• Prof. Yong Hong Wu, Curtin University of Technology, Perth, WA, Australia
• Prof. Angelo Favini, University of Bologna, Bologna, Italy
• Prof. Andrew Pickering, Universidad Rey Juan Carlos, Mostoles, Madrid, Spain
• Prof. Guozhen Lu, Wayne state university, Detroit, MI 48202, USA
• Prof. Gerd Teschke, Hochschule Neubrandenburg - University of Applied Sciences, Germany
• Prof. Michel Chipot, University of Zurich, Switzerland
• Prof. Juan Carlos Cortes Lopez, Universidad Politecnica de Valencia, Spain
• Prof. Julian Lopez-Gomez, Universitad Complutense de Madrid, Madrid, Spain
• Prof. Jozef Banas, Rzeszow University of Technology, Rzeszow, Poland
• Prof. Ivan G. Avramidi, New Mexico Tech, Socorro, New Mexico, USA
• Prof. Kevin R. Payne, Universita' degli Studi di Milano, Milan, Italy
• Prof. Juan Pablo Rincon-Zapatero, Universidad Carlos III De Madrid, Madrid, Spain
• Prof. Valery Y. Glizer, ORT Braude College, Karmiel, Israel
• Prof. Norio Yoshida, University of Toyama, Toyama, Japan
• Prof. Feliz Minhos, Universidade de Evora, Evora, Portugal
• Prof. Mihai Mihailescu, University of Craiova, Craiova, Romania
• Prof. Lucas Jodar, Universitat Politecnica de Valencia, Valencia, Spain
• Prof. Dumitru Baleanu, Cankaya University, Ankara, Turkey
• Prof. Jianming Zhan, Hubei University for Nationalities, Enshi, Hubei Province, China
• Prof. Zhenya Yan, Institute of Systems Science, AMSS, Chinese Academy of Sciences, Beijing, China
• Prof. Nasser-Eddine Mohamed Ali Tatar, King Fahd University of Petroleum and Mineral, Dhahran, Saudi Arabia
• Prof. Jianqing Chen, Fujian Normal University, Cangshan, Fuzhou, Fujian, China
• Prof. Josef Diblik, Brno University of Technology, Brno, Czech Republic
• Prof. Stanislaw Migorski, Jagiellonian University in Krakow, Krakow, Poland
• Prof. Qing-Wen Wang, Shanghai University, Shanghai, China
• Prof. Luis Castro, University of Aveiro, Aveiro, Portugal
• Prof. Alberto Fiorenza, Universita' di Napoli "Federico II", Napoli (Naples), Italy
• Prof. Patricia J. Y. Wong, Nanyang Technological University, Singapore
• Prof. Salvatore A. Marano, Universita degli Studi di Catania, Catania, Italy
• Prof. Sung Guen Kim, Kyungpook National University, Daegu, South Korea
• Prof. Maria Alessandra Ragusa, Universita di Catania, Catania, Italy
• Prof. Gerassimos Barbatis, University of Athens, Athens, Greece
• Prof. Jinde Cao, Distinguished Prof., Southeast University, Nanjing 210096, China
• Prof. Kailash C. Patidar, University of the Western Cape, 7535 Bellville, South Africa
• Prof. Mitsuharu Otani, Waseda University, Japan
• Prof. Luigi Rodino, University of Torino, Torino, Italy
• Prof. Carlos Lizama, Universidad de Santiago de Chile, Santiago, Chile
• Prof. Jinhu Lu, Chinese Academy of Sciences, Beijing, China
• Prof. Narcisa C. Apreutesei, Technical University of Iasi, Iasi, Romania
• Prof. Sining Zheng, Dalian University of Technology, Dalian, China
• Prof. Daoyi Xu, Sichuan University, Chengdu, China
• Prof. Zili Wu, Xi'an Jiaotong-Liverpool University, Suzhou, Jiangsu, China
• Prof. Wei-Shih Du, National Kaohsiung Normal University, Kaohsiung City, Taiwan
• Prof. Khalil Ezzinbi, Universite Cadi Ayyad, Marrakesh, Morocco
• Prof. Youyu Wang, Tianjin University of Finance and Economics, Tianjin, China
• Prof. Satit Saejung, Khon Kaen University, Thailand
• Prof. Chun-Gang Zhu, Dalian University of Technology, Dalian, China
• Prof. Mohamed Kamal Aouf, Mansoura University, Mansoura City, Egypt
• Prof. Yansheng Liu, Shandong Normal University, Jinan, Shandong, China
• Prof. Naseer Shahzad, King Abdulaziz University, Jeddah, Saudi Arabia
• Prof. Janusz Brzdek, Pedagogical University of Cracow, Poland
• Prof. Mohammad T. Darvishi, Razi University, Kermanshah, Iran
• Prof. Ahmed El-Sayed, Alexandria University, Alexandria, Egypt
  
  B) Program Committee for APPLIED MATHEMATICS AND COMPUTATIONAL METHODS
• Prof. Martin Bohner, Missouri University of Science and Technology, Rolla, Missouri, USA
• Prof. Martin Schechter, University of California, Irvine, USA
• Prof. Ivan G. Avramidi, New Mexico Tech, Socorro, New Mexico, USA
• Prof. Michel Chipot, University of Zurich, Zurich, Switzerland
• Prof. Xiaodong Yan, University of Connecticut, Connecticut USA
• Prof. Ravi P. Agarwal, Texas A&M University - Kingsville, Kingsville, TX, USA
• Prof. Yushun Wang, Nanjing Normal university, Nanjing, China
• Prof. Patricia J. Y. Wong, Nanyang Technological University, Singapore
• Prof. Andrei Korobeinikov, Centre de Recerca Matematica, Barcelona, Spain
• Prof. Jim Zhu, Western Michigan University, Kalamazoo, MI, USA
• Prof. Ferhan M. Atici, Department of Mathematics, Western Kentucky University, USA
• Prof. Gerd Teschke, Institute for Computational Mathematics in Science and Technology, Neubrandenburg, Berlin-Dahlem, Germany
• Prof. Meirong Zhang, Tsinghua University, Beijing, China
• Prof. Lucio Boccardo, Universita degli Studi di Roma "La Sapienza", Roma, Italy
• Prof. Shanhe Wu, Longyan University, Longyan, Fujian, China
• Prof. Natig M. Atakishiyev, National Autonomous University of Mexico, Mexico
• Prof. Jianming Zhan, Hubei University for Nationalities, Enshi, Hubei Province, China
• Prof. Narcisa C. Apreutesei, Technical University of Iasi, Iasi, Romania
• Prof. Chun-Gang Zhu, Dalian University of Technology, Dalian, China
• Prof. Abdelghani Bellouquid, University Cadi Ayyad, Morocco
• Prof. Jinde Cao, Southeast University/ King Abdulaziz University, China
• Prof. Josef Diblik, Brno University of Technology, Brno, Czech Republic
• Prof. Jianqing Chen, Fujian Normal University, Fuzhou, Fujian, China
• Prof. Naseer Shahzad, King Abdulaziz University, Jeddah, Saudi Arabia
• Prof. Sining Zheng, Dalian University of Technology, Dalian, China
• Prof. Leszek Gasinski, Uniwersytet Jagielloński, Krakowie, Poland
• Prof. Satit Saejung, Khon Kaen University, Muang District, Khon Kaen, Thailand
• Prof. Juan J. Trujillo, Universidad de La Laguna, La Laguna, Tenerife, Spain
• Prof. Tiecheng Xia, Department of Mathematics, Shanghai University, China
• Prof. Stevo Stevic, Mathematical Institute Serbian Academy of Sciences and Arts, Beogrand, Serbia
• Prof. Lucas Jodar, Universitat Politecnica de Valencia, Valencia, Spain
• Prof. Noemi Wolanski, Universidad de Buenos Aires, Buenos Aires, Argentina
• Prof. Zhenya Yan, Chinese Academy of Sciences, Beijing, China
• Prof. Juan Carlos Cortes Lopez, Universidad Politecnica de Valencia, Spain
• Prof. Wei-Shih Du, National Kaohsiung Normal University, Kaohsiung City, Taiwan
• Prof. Kailash C. Patidar, University of the Western Cape, Cape Town, South Africa
• Prof. Hossein Jafari, University of Mazandaran, Babolsar, Iran
• Prof. Abdel-Maksoud A Soliman, Suez Canal University, Egypt
• Prof. Janusz Brzdek, Pedagogical University of Cracow, Cracow, Poland
• Dr. Fasma Diele, Italian National Research Council (C.N.R.), Bari, Italy.

PURE MATHEMATICS: Analysis, Nonlinear Analysis, Algebra, Topology, Algebraic Topology, Lie Groups and Lie Algebras, C* Algebras, Functional Analysis, Geometry, Differential Geometry, Algebraic Geometry, Complex Analysis, Set Theory, Operators' Theory, Ordinary Differential Equations And Chaos, Partial Differential Equations, Inverse Problems, Banach Spaces, Convex Analysis, Ergodic Theory, Ergodic Theory and Symbolic Dynamics, Graph Theory, Manifolds, Modern Group Theory, Rings & Modules & Representations, Fields and Galois Theory, Algebraic K-Theory, Commutative Algebra, Harmonic Analysis, Measure Theory, Dynamical Systems, Topological Algebras, Mathematical Logic, Algebraic Number Theory, Analytic Number Theory, Probability & Statistics, Combinatorics, Combinatorics and Discrete Geometry, Module and Representation Theory, Non-Smooth Analysis, Mathematical Physics, Theoretical Topics in Numerical Analysis, Optimization and Variational Analysis, Theoretical Game Theory, Theoretical Fluid Dynamics, Theoretical Foundations of Control, Algorithms and Complexity, Others

APPLIED MATHEMATICS AND COMPUTATIONAL METHODS: Mathematical Logic, Probability, Statistics, Combinatorics, Discrete Mathematics, Numerical Analysis, Computational sciences, Applied Functional Analysis, Differential Geometry, Systems Theory, Computational Geometry, Control Theory, Numerical ODEs, Numerical PDEs, Scientific Computing and Algorithms, Stochastic Differential Equations, Approximation Theory, Numerical Linear Algebra, Numerical Integral Equations, Error Analysis and Interval Analysis, Difference Equations and Recurrence Relations, Algorithms & Computational Complexity, Computational Intelligence, Artificial Intelligence, Dynamical Systems, Computational Physics, Computational Statistics, Computational Chemistry, Computational Engineering, Mathematical Biology, Mathematical Medicine, Mathematics in Fluid mechanics, Mathematics in Heat and Mass Transfer, Theoretical Mechanics, Optimization and Operational Research, Others