RECENT ADVANCES in APPLIED MATHEMATICS, MODELLING and SIMULATION

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2 RECENT ADVANCES in APPLIED MATHEMATICS, MODELLING and SIMULATION Proceedings of the 8th International Conference on Applied Mathematics, Simulation, Modelling (ASM '14) Florence, Italy November 22-24, 2014 Series: Mathematics and Computers in Science and Engineering Series 34 ISSN: ISBN:

3 RECENT ADVANCES in APPLIED MATHEMATICS, MODELLING and SIMULATION Proceedings of the 8th International Conference on Applied Mathematics, Simulation, Modelling (ASM '14) Florence, Italy November 22-24, 2014 Published by WSEAS Press Copyright 2014, by WSEAS Press All the copyright of the present book belongs to the World Scientific and Engineering Academy and Society Press. All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise, without the prior written permission of the Editor of World Scientific and Engineering Academy and Society Press. All papers of the present volume were peer reviewed by no less that two independent reviewers. Acceptance was granted when both reviewers' recommendations were positive. ISSN: ISBN:

4 RECENT ADVANCES in APPLIED MATHEMATICS, MODELLING and SIMULATION Proceedings of the 8th International Conference on Applied Mathematics, Simulation, Modelling (ASM '14) Florence, Italy November 22-24, 2014

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6 Editors: Prof. Nikos E. Mastorakis, Technical University of Sofia, Bulgaria Prof. Metin Demiralp, Istanbul Technical University, Turkey Prof. Nitis Mukhopadhyay, University of Connecticut, USA Prof. Francesco Mainardi, University of Bologna & INFN, Italy Committee Members-Reviewers: Elena Bautu Ankit Patel Claudio Guarnaccia Arion Felix Nikos Loukeris Takuya Yamano Petr Hajek Valeriy Perminov M. M. Noor Yu Zhang Sorinel Oprisan Hime Aguiar Valeriu Prepelita Satish Kumar Duraiswamy Mohamed Zahran Zengshi Chen Eleazar Jimenez Serrano Kevin Kam Fung Yuen Huashui Zhan Jiri Hrebicek Hongjun Liu Mahdi Faraji Hamed Ziaeipoor Guoxiang Liu Diego Pinto Roa Amjad Mahmood David Nicoleta Claudia-Georgeta Carstea Al Emran Ismail Snezhana Georgieva Gocheva-Ilieva Ahmed Zeeshan Ali Sadeghi Alina Adriana Minea Anton V. Doroshin Calin Ciufudean Carlos E. Formigoni Cleopatra Florentina Cuciumita Dana Anderson Daniela Cristiana Docan Dean Teneng Gabriel Frumusanu Gheorghe Mugurel Radulescu Gheorghe Badea Huashui Zhan Zhan Ibrahim Canak Ioana Adrian Jose Manuel Mesa Fernández Lungu Mihai Aureliu Majid Mohammed Ali Maria Dobritoiu Maria Wenisch Mehmet Emir Köksal Mihaela Neamtu Mihaiela Iliescu Muhammad Raheel Mohyuddin Naveen G. Ramunigari Nazir Ahmad Nicolae Ungureanu Noor Fadiya Mohd Noor Panagiotis Gioannis Petras Rupšys Roman Prokop Roots Larissa Rosli Abu Bakar Santhosh Kumar.B B Swapnadip De Tiberiu Socaciu Zaharia Sebastian Zahéra Mekkioui Zakaria Zubi

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8 Table of Contents Keynote Lecture 1: Most Recent Developments within Enhanced Multivariance Products Representation (EMPR) Perspective Metin Demiralp Plenary Lecture 1: Fractional Diffusive Waves Generated by Evolution Equations of Fractional Order Francesco Mainardi Plenary Lecture 2: On Fundamental Sequential Confidence Interval Estimation Problems Revisited Nitis Mukhopadhyay Plenary Lecture 3: On Maximum Likelihood Clustering via a Multimodal Probability Model 16 Miin-Shen Yang Plenary Lecture 4: Geometrical Numerical Techniques for the Approximation of Ecological Models Described by Nonlinear Differential Equations Fasma Diele The gamma-transform: A New Approach to the Study of a Discrete and Finite Random Variable Fabio Grandi Valuation of Discretely-Sampled Variance Swaps under Correlated Stochastic Volatility and Stochastic Interest Rates Teh Raihana Nazirah Roslan, Wenjun Zhang, Jiling Cao A Viscoelastic Model for Transient Waves in Fluid-Filled Elastic Tubes 35 Andrea Giusti, Francesco Mainardi Approximate Confidence Sets for Adaptive Generalised Linear Models 40 D. S. Coad Small Noise Asymptotic Expansion for the Infinite Dimensional Van der Pol Oscillator 43 Francesco Cordoni, Luca Di Persio On Investigation and Approximate Solution of One Nonlinear Partial Integro-Differential Equation with Source Term Temur Jangveladze, Zurab Kiguradze Low-Velocity Impact Response of Non-Linear Doubly Curved Shallow Shells with Rectangular Base under 2:1 Internal Resonance Y. A. Rossikhin, M. V. Shitikova, Muhammed Salih Khalid J. M ISBN:

9 A Simplified Method for Finding Confidence Intervals through Sequential Monte Carlo Simulation Ivair Ramos Silva 65 A Grunwald Letnikov Scheme for Fractional Operators of Havriliak Negami Type 70 Roberto Garrappa Local and Nonlocal Symmetries and Inverse Problems for Ordinary Differential Equations 77 Valentin Zaitsev, Lidiya Linchuk, Alexander Flegontov Mean Density of Random Closed Sets and their Estimation: Some Results and Applications 84 Elena Villa Linking Lamda-Boolean Theory and the Coppo-Dezani Type-Assignment System 91 Seref Mirasyedioglu General Conditional Information with an Aim 96 Doretta Vivona, Maria Divari Computation Eigenvalues and Eigenfunctions of Mixed BVP for Helmholtz Equation 101 Vitaliy Lukinov Asymptotic Behaviour for an Electromagnetic Differential System with a Memory Dissipative Boundary Condition Mauro Fabrizio Application of Computational Fluid Dynamics to Address Environmental and Buildings Design Challenges Neihad Hussen Al-Khalidy Mathematical Analysis of Glioblastoma Invasion in 3D 117 Akisato Kubo, Katsutaka Kimura Stochastic Models for Ordinal Panel Data with Individual and Time-Varying Latent Effects 123 Fulvia Pennoni, Giorgio Vittadini A Debt Behavior Model 127 Wenjun Zhang Computational Prediction of Binding Affinity between Psychotropic Drugs and Neural Cytoskeleton Elements R. Pizzi, T. Rutigliano, A. Ferrarotti, M. Pregnolato 132 Robustness of Normal-Based Multi-Stage Sequential Sampling Procedures 139 H. I. Hamdy, M. S. Son, A. S. Yousef Functional Nonparametric Classification of Random Surfaces 143 Javier Álvarez-Liébana, M. Dolores Ruiz-Medina ISBN:

10 Ecological Modelling for Next Generation Sequencing Data 153 C. Sala, S. Vitali, E. Giampieri, D. Remondini, I. F. Do Valle, G. Castellani Mathematical Modeling of Crown Forest Fires Spread With Firebreaks 157 Valeriy Perminov An Impulse-Based Algorithm for Dynamical Systems with Multiple Simultaneous Collisions 164 Razvan Andrei Oprea, Cornelia Stan Parametric Methods for Fault Analysis Applied to a Servomechanism Affected by Multiple Failures P. Maggiore, M. D. L. Dalla Vedova, L. Pace 171 Causality in Continuous Time and Applications 183 Ljiljana Petrovic, Dragana Valjarevic Corridor Size Variation in Spatially Explicit/implicit Models 188 Fasma Diele, Carmela Marangi, Stefania Ragni The Solution of Time Fractional Heat Equation With New Fractional Derivative Definition 195 Yücel Çenesiz, Ali Kurt Approximation in Variation for Nonlinear Mellin Integral Operators in Multidimensional Setting Laura Angeloni, Gianluca Vinti The Use of Analytic Hierarchy Process for the Life Extension Analysis of Air Defense Integrated Systems Vasile Şandru, Cristian-George Constantinescu, Mircea Boscoianu A Comparison of a Dynamic Compilation and Mathematic Parser Libraries in.net for Expression Evaluation Petr Čápek, Erik Král Convective Instability in a Horizontal Annular Porous Duct with Conducting Walls 219 Eugenia Rossi di Schio Study Concerning the Influence of the Engine Mounting System on the Vibration Transmissibility to the Truck Cab Cornelia Stan, Daniel Iozsa, Razvan Oprea 225 Modelling and Simulation in Environmental Data Analysis 229 Claudio Guarnaccia, Joseph Quartieri A Comparison of the Performance of a Composite Pattern and a Mathematic Expression Parser and Interpreter Erik Král, Petr Čápek 239 Equilibrium-Based Simulation of Lignocellulosic Biomass Pyrolysis via Aspen Plus 242 Alessandro Visconti, Michele Miccio, Dagmar Juchelková ISBN:

11 Analytical Solution for Evaporating Sessile Drops on Solid Substrates 252 Stanislav Z. Dunin, Oleg V. Nagornov, Nikolay V. Starostin, Vladimir P. Trifonenkov Sampling Kantorovich Operators and their Applications to Approximation Problems and to Digital Image Processing Danilo Costarelli, Gianluca Vinti 256 Optimisation of Factory Floor Layout in a Complex Manufacturing Process 261 Tadej Kanduč, Blaž Rodič Energetic Considerations on the Effects of Inelastic Stiffness on Nonlinear Seismic Response 270 Rita Greco Simulations of Absorption and Emission Spectra for LH4 Ring - Full Hamiltonian Model 286 Pavel Herman, David Zapletal, Jan Slegr 3D Expression Recognition using Geometrical Surface Properties 295 Krasimir Tonchev, Strahil Sokolov A Contravariant Formulation of Non-Linear Shallow Water Equations 299 Giovanni Cannata, Francesco Lasaponara, Francesco Gallerano The Intelligent Identification Technique with Associative Search for Large-Scale Industrial Facilities Nataliya N. Bakhtadze, Evgeny M. Maximov, Vladimir A. Lototsky 307 Estimation Accuracy of an Inequality Index 318 Bhargab Chattopadhyay, Shyamal K. De The Cell Method as a Case of Bialgebra 322 Elena Ferretti Design of Intelligent Knowledge Engine for Decision Support Systems in Agriculture 332 František Kožíšek, Petr Hanzlík Finite Velocity Planar Random Motions Driven by Inhomogeneous Fractional Poisson Distributions Roberto Garra, Enzo Orsingher 337 An Indicator of an Individual s Professional Quality 342 Amelia Bucur Molecular Cooperation to Reinforce Immune Response during Carcinoma: A Structural Bioinformatics Analysis R. Pizzi, T. Rutigliano, P. Guadalupi, M. Pregnolato 346 Multi-Observer for Uncertain Output Nonlinear Systems 354 Hassene Bedoui, Kamel Ben Othman ISBN:

12 Understanding the Diffusion of a Mobile Application for Supply Chain Management: A System Dynamics Approach Anna Corinna Cagliano, Alberto De Marco, Carlo Rafele The Jet-To-Channel Reynolds Number Ratio Effect on the Flow Around a Wall-Mounted Cube Cooled Simultaneously by a Jet in a Crossflow Nemdili Saleha, Nemdili Fadela, Azzi Abbes An Alternating Least Squares Algorithm with Application to Image Processing 379 Lorenzo Piazzo Computational Information Conservation Theory: An Introduction 385 Rodolfo A. Fiorini Generating Random Samples from the Generalized Pareto Mixture Model 395 Mustafa Çavuş, Ahmet Sezer, Berna Yazici Incentive Design and Manager Performances: An ABM Approach 401 Concetta Sorropago Performance of the Simulation Method with Gumbel Distribution 411 Mustafa Çavuş, Özer Özdemir Authors Index 418 ISBN:

13 Keynote Lecture 1 Most Recent Developments within Enhanced Multivariance Products Representation (EMPR) Perspective Professor Metin Demiralp Istanbul Technical University Informatics Institute TURKEY metin.demiralp@gmail.com Abstract: A few years ago, Metin Demiralp has constructed an extension to High Dimensional Model Representation (HDMR) by inserting certain given univariate functions, support functions, to the formulation. This extension has been called Enhanced Multivariance Products Representation (EMPR) because of the additive terms with unique common multivariance same as the number of the target function s independent variables. After this construction, during the time period, from then until now, he and his group (Group for Science and Methods of Computing in Istanbul Tehcnical University Informatics Institute) members performed various applications and created new developments. EMPR preserves the orthogonal geometry of HDMR. It also uses the product type overall weight functions which are composed of univariate factors, each of which depends on a different independent variable argument of the target function; even though quite recently nonproduct type overall weights are succesfully introduced to the formulation of HDMR. Beyond these preservations, the basic extension is to multiply each HDMR component with certain univariate support functions such that the resulting form of the component becomes dependent of all independent variables of target function. The support functions are given entities and, depending on how they are defined, the EMPR truncations show different level of approximation qualities. Hence, the support function selection is perhaps the most important component of EMPR. EMPR has born from the image processing via HDMR upon noticing its certain in sufficiencies within technicalities. The bivariate HDMR has been used therein and soon it has been noticed that the all of the three different type HDMR truncations were giving almost nothing and the bivariate remainder term was involving overdominating pixel information about the target image with slightly depending on which kind of weight has been used. This motivated us to change, or truely speaking, extend HDMR philosophy by importing support functions. The result has been really more acceptable when the dimensionality grows. Even though there has been a noticable quality increase even in the case of bivariance, bivariate EMPR has appeared to be quite limited and urged us to seek more than one sets of support functions to extend HDMR. The result has been quite succesfull and TMEMPR (Tridiagonal Matrix EMPR) for discrete set domains and TKEMPR (Tridiagonal Kernel EMPR) for continuous functions which can be considered as the kernel of an appropriate univariate integral operator have born after these efforts. The presentation focuses on these and some related issues in somehow chronological order. Brief Biography of the Speaker: Metin Demiralp was born in Türkiye (Turkey) on 4 May His education from elementary school to university was entirely in Turkey. He got his BS, MS degrees and PhD from the same institution, Istanbul Technical University. He was originally chemical engineer, however, through theoretical chemistry, applied mathematics, and computational science years he was mostly working on methodology for computational sciences and he is continuing to do so. He has a group (Group for Science and Methods of Computing) in Informatics Institute of Istanbul Technical University (he is the founder of this institute). He collaborated with the Prof. Herschel A. Rabitz s group at Princeton University (NJ, USA) at summer and winter semester breaks during the period after his 14 month long postdoctoral visit to the same group in He was also (and still is) in collaboration with a neuroscience group at the Psychology Department in the University of Michigan at Ann Arbour in last three years (with certain publications in journals and proceedings). Metin Demiralp has more than 100 papers in well known and prestigious scientific journals, and, more than 230 contributions together with various keynote, plenary, and, tutorial talks to the proceedings of various international conferences. He gave many invited talks in various prestigious scientific meetings and academic institutions. He has a good scientific reputation in his country and he was one of the principal members of Turkish Academy of Sciences since He has resigned on June 2012 because of the governmental decree changing the structure of the ISBN:

14 academy and putting politicial influence possibility by bringing a member assignation system. Metin Demiralp is also a member of European Mathematical Society. He has also two important awards of turkish scientific establishments. The important recent foci in research areas of Metin Demiralp can be roughly listed as follows: Probabilistic Evolution Method in Explicit ODE Solutions and in Quantum and Liouville Mechanics, Fluctuation Expansions in Matrix Representations, High Dimensional Model Representations, Space Extension Methods, Data Processing via Multivariate Analytical Tools, Multivariate Numerical Integration via New Efficient Approaches, Matrix Decompositions, Multiway Array Decompositions, Enhanced Multivariate Product Representations, Quantum Optimal Control. ISBN:

15 Plenary Lecture 1 Fractional Diffusive Waves Generated by Evolution Equations of Fractional Order Professor Francesco Mainardi Department of Physics University of Bologna & INFN Italy francesco.mainardi@bo.infn.it Abstract: In this lecture we discuss some properties of the Cauchy and signaling problems for the one-dimensional time-fractional diffusion-wave equation with the time fractional derivative of order beta (1< beta <2). In particular, their response to a localized disturbance of the initial data is studied. It is known that whereas the diffusion equation describes a process where the disturbance spreads infinitely fast, the propagation velocity of the disturbance is a constant for the wave equation. We show that the time-fractional diffusion-wave equation interpolates between these two different responses in the sense that the propagation velocities of the maximum points, centers of gravity, and medians of the fundamental solutions to both the Cauchy and the signaling problems are allfinite. On the other hand, the disturbance spreads infinitely fast and the time-fractional diffusion-wave equation is non-relativistic like the classical diffusion equation. Furthermore, the maximum locations, the centers of gravity, and the medians of the fundamental solution to the Cauchy and signaling problems and their propagation velocities are described analytically and calculated numerically. The obtained results for the Cauchy and the signalling problems are interpreted and compared to each other. Brief Biography of the Speaker: Presently Francesco MAINARDI is retired professor of Mathematical Physics from the University of Bologna where has taught this course since 40 years. His fields of research concern several topics of applied mathematics, including diffusion and wave problems, asymptotic methods, integral transforms, special functions, fractional calculus and non-gaussian stochastic processes. At present his H-index is > 40 For a full biography, list of references on author's papers and books see: Home Page: and ISBN:

16 Plenary Lecture 2 On Fundamental Sequential Confidence Interval Estimation Problems Revisited Professor Nitis Mukhopadhyay Department of Statistics University of Connecticut Storrs, CT USA nitis.mukhopadhyay@uconn.edu Abstract: The literature on fundamental sequential confidence interval estimation problems had major breakthroughs with significant richness after the appearance of pioneering contributions of Dantzig (1940, Annals of Mathematical Statistics), Stein (1945, Annals of Mathematical Statistics), Anscombe (1952, Proceedings of Cambridge Philosophical Society), and Chow and Robbins (1965, Annals of Mathematical Statistics). This area was elegantly synthesized along with new directions for research by Ghosh and Mukhopadhyay (1976, Sankhya, Series B). The literature has since grown tremendously in many directions with incorporation of operationally convenient multistage and computer-intensive sampling methods having first-, and often second-order, asymptotic properties. One will find many important directions from the texts of Mukhopadhyay and Solanky (Multistage Selection and Ranking Procedures, 1994, Dekker), Ghosh, Mukhopadhyay, and Sen (Sequential Estimation, 1997, Wiley), Mukhopadhyay, Datta, and Chattopadhyay (Applied Sequential Methodologies, 2004, Dekker), Mukhopadhyay and de Silva (Sequential Methods and Their Applications, 2009, CRC Press), and others. In this plenary lecture, I will begin by summarizing the original contributions of Dantzig, Stein, Anscombe, and Chow and Robbins. Then, I will move to emphasize a clear roadmap linking some of the major methodological and theoretical developments from past 40 years. Real applications will be highlighted when appropriate. Brief Biography of the Speaker: Professor Nitis Mukhopadhyay received his PhD degree awarded by the Indian Statistical Institute-Calcutta based on a dissertation dated He has been a full professor in the Department of Statistics at the University of Connecticut-Storrs, USA since He served as the Head of this department during He has made prolific contributions in many areas including statistical inference -parametric and nonparametric, multiple comparisons, clinical trials, applied probability, and applications. Professor Mukhopadhyay is especially revered for path-breaking contributions in sequential analysis as well as selection and ranking. His honors include elected Fellows of the Institute of Mathematical Statistics (2002), the American Statistical Association (2003), the American Association for the Advancement of Science (2012), elected Ordinary Member of the International Statistical Institute (2007), elected Member of the Connecticut Academy of Arts and Sciences (2014), and the Abraham Wald Prize in Sequential Analysis (2008). He is the Editor-in-Chief for the premier journal, Sequential Analysis, and serves as an Associate Editor for a number of leading international journals. Professor Mukhopadhyay is the author or co-author of 6 books, 14 book chapters, more than 215 research papers, and editor or co-editor of 6 special volumes. He has supervised 22 PhD students as their major adviser. For more details, one may visit the website: ISBN:

17 Plenary Lecture 3 On Maximum Likelihood Clustering via a Multimodal Probability Model Professor Miin-Shen Yang Department of Applied Mathematics Chung Yuan Christian University Chung-Li 32023, Taiwan msyang@math.cycu.edu.tw Abstract: Clustering is a method for finding structure in a data set. Clustering methods can be generally categorized as either having a (probability) model-based approach or a nonparametric approach. For a model-based approach, there are two ways to use a probability model for clustering. One is based on the expectation & maximization (EM), and the other is based on the classification maximum likelihood (CML). For a nonparametric approach, clustering methods are generally based on an objective function of similarity or dissimilarity measures, and partitional methods are popularly used, such as k-means and fuzzy c-means, etc. In this lecture, we first consider the maximum likelihood (ML) estimation for the proposed multimodal probability model (MPM) to establish an ML clustering approach. According to the ML clustering, the relationships between most clustering algorithms and the MPM are established. We find that the MPM is actually a good basic probability model for most clustering methods. This ML clustering approach can lead to most clustering algorithms, such as EM, CML, k-means, fuzzy c-means, possibilistic c-means, mean shift, and latent class methods. We then construct two ML clustering frameworks based on the MPM for developing new clustering algorithms. One framework can develop penalized-type clustering algorithms. Another framework induces entropy-type clustering algorithms, especially with sample-weighted clustering. Several numerical and real data sets are made for comparisons. These experimental results show that these new constructions based on the ML clustering can produce useful and effective clustering algorithms. Brief Biography of the Speaker: Prof. Miin-Shen Yang received the BS degree in mathematics from the Chung Yuan Christian University, Chung-Li, Taiwan, in 1977, the MS degree in applied mathematics from the National Chiao-Tung University, Hsinchu, Taiwan, in 1980, and the PhD degree in statistics from the University of South Carolina, Columbia, USA, in In 1989, he joined the faculty of the Department of Mathematics in the Chung Yuan Christian University (CYCU) as an Associate Professor, where, since 1994, he has been a Professor. From 1997 to 1998, he was a Visiting Professor with the Department of Industrial Engineering, University of Washington, Seattle. During , he was the Chairman of the Department of Applied Mathematics in CYCU and now, he is the Director of Chaplain s Office in CYCU. His research interests include applications of statistics, fuzzy clustering, neural fuzzy systems, pattern recognition and machine learning. Dr. Yang was an Associate Editor of the IEEE Transactions on Fuzzy Systems ( ), and is an Associate Editor of the Applied Computational Intelligence & Soft Computing and Editor-in-Chief of Advances in Computational Research. He was awarded with 2008 Outstanding Associate Editor of IEEE Transactions on Fuzzy Systems, IEEE; 2009 Outstanding Research Professor of Chung Yuan Christian University; 2010 Top Cited Article Award , Pattern Recognition Letters; 2012 Distinguished Professor of Chung Yuan Christian University; 2014 overseas academic scholar for The 111 Plan of China. ISBN:

18 Plenary Lecture 4 Geometrical Numerical Techniques for the Approximation of Ecological Models Described by Nonlinear Differential Equations Dr. Fasma Diele IAC-CNR researcher via Amendola 122/D Bari, Italy f.diele@ba.iac.cnr.it Abstract: A major neglected weakness of many current (non trivial) ecological models is the numerical method used to solve the governing systems of differential equations (DEs). Indeed, the discrete dynamics of the approximations of DEs may provide spurious numerical behaviour. This indicates that many problems widely believed to be endemic to the models, are frequently merely artifacts of their numerical implementation. The approach represented by the geometric numerical integration, by preserving qualitative properties of the solution, leads to improved long-time numerical behaviour. Therefore geometric integration methods should be used for preserving one or more of the properties (positivity of the phase space, Poisson structure, invariants) that characterize the continuous ecological models. The effectiveness of this approach will be shown with some examples of population dynamics. Brief Biography of the Speaker: Dr. Fasma Diele (female), Master degree in Mathematics, researcher at Istituto per Applicazioni del Calcolo "M.Picone" of the Consiglio Nazionale delle Ricerche (CNR) since 1998, she is the Head of the IAC Research Unit located in Bari. She is author of several papers in numerical analysis and scientific computing. She was referee for Italian University and Research Ministry (MIUR) in the area of Numerical Analysis. She was referee for Proposals in Mathematics of the National Research Fund for Scientific & Technological Development (FONDECYT), Chile. She is reviewer for several mathematics journals such as SIMAX, SINUM, SISC. She is member of the editorial board of Journal of Computer Science and Abstract and Applied Analysis. Her area of expertise is the field of Geometric Numerical Integration of non linear differential equations: methods for preserving invariants, energy-preserving methods, symplectic partitioned Runge-Kutta methods, splitting and composition methods. She was research leader of RSTL id.332 project (funded by CNR), "Numerical algorithms for differential equations with specific qualitative properties". She participated to the FP7-SPACE project BIO_SOS developing her research activity on symplectic methods for simulating population and metapopulation dynamics in fragmented habitat. ISBN:

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20 Authors Index Abbes, A. 370 Grandi, F. 19 Pregnolato, M. 132, 346 Al-Khalidy, N. H. 109 Greco, R. 270 Quartieri, J. 229 Álvarez-Liébana, J. 143 Guadalupi, P. 346 Rafele, C. 360 Angeloni, L. 199 Guarnaccia, C. 229 Ragni, S. 188 Bakhtadze, N. N. 307 Hamdy, H. I. 139 Remondini, D. 153 Bedoui, H. 354 Hanzlík, P. 332 Rodič, B. 261 Boscoianu, M. 204 Herman, P. 286 Roslan, T. R. N. 27 Bucur, A. 342 Iozsa, D. 225 Rossikhin, Y. A. 56 Cagliano, A. C. 360 Jangveladze, T. 50 Ruiz-Medina, M. D. 143 Cannata, G. 299 Juchelková, D. 242 Rutigliano, T. 132, 346 Cao, J. 27 Kanduč, T. 261 Sala, C. 153 Čápek, P. 212, 239 Khalid, J. M. M. S. 56 Saleha, N. 370 Castellani, G. 153 Kiguradze, Z. 50 Şandru, V. 204 Çavuş, M. 395, 411 Kimura, K. 117 Sezer, A. 395 Çenesiz, Y. 195 Kožíšek, F. 332 Shitikova, M. V. 56 Chattopadhyay, B. 318 Král, E. 212, 239 Silva, I. R. 65 Coad, D. S. 40 Kubo, A. 117 Slegr, J. 286 Constantinescu, C.-G. 204 Kurt, A. 195 Sokolov, S. 295 Cordoni, F. 43 Lasaponara, F. 299 Son, M. S. 139 Costarelli, D. 256 Linchuk, L. 77 Sorropago, C. 401 De Marco, A. 360 Lototsky, V. A. 307 Stan, C. 164, 225 De, S. K. 318 Lukinov, V. 101 Starostin, N. V. 252 Di Persio, L. 43 Maggiore, P. 171 Tonchev, K. 295 Di Schio, E. R. 219 Mainardi, F. 35 Trifonenkov, V. P. 252 Diele, F. 188 Marangi, C. 188 Valjarevic, D. 183 Divari, M. 96 Maximov, E. M. 307 Vedova, M. D. L. D. 171 Do Valle, I. F. 153 Miccio, M. 242 Villa, E. 84 Dunin, S. Z. 252 Mirasyedioglu, S. 91 Vinti, G. 199, 256 Fabrizio, M. 105 Nagornov, O. V. 252 Visconti, A. 242 Fadela, N. 370 Oprea, R. A. 164, 225 Vitali, S. 153 Ferrarotti, A. 132 Orsingher, E. 337 Vittadini, G. 123 Ferretti, E. 322 Othman, K. B. 354 Vivona, D. 96 Fiorini, R. A. 385 Özdemir, O. 411 Yazici, B. 395 Flegontov, A. 77 Pace, L. 171 Yousef, A. S. 139 Gallerano, F. 299 Pennoni, F. 123 Zaitsev, V. 77 Garra, R. 337 Perminov, V. 157 Zapletal, D. 286 Garrappa, R. 70 Petrovic, L. 183 Zhang, W. 27, 127 Giampieri, E. 153 Piazzo, L. 379 Giusti, A. 35 Pizzi, R. 132, 346 ISBN: