Advances in Intelligent Systems and Computing 290
Sigeru Omatu · Hugues Bersini
Juan M. Corchado · Sara Rodríguez
Paweł Pawlewski · Edgardo Bucciarelli Editors
Distributed Computing
and Artificial Intelligence,
11th International
Conference
Advances in Intelligent Systems and Computing
Volume 290
Series editor
Janusz Kacprzyk, Polish Academy of Sciences, Warsaw, Poland
e-mail: [email protected]
For further volumes:
http://www.springer.com/series/11156
About this Series
The series “Advances in Intelligent Systems and Computing” contains publications on theory,
applications, and design methods of Intelligent Systems and Intelligent Computing. Virtually all
disciplines such as engineering, natural sciences, computer and information science, ICT, economics, business, e-commerce, environment, healthcare, life science are covered. The list of topics spans all the areas of modern intelligent systems and computing.
The publications within “Advances in Intelligent Systems and Computing” are primarily
textbooks and proceedings of important conferences, symposia and congresses. They cover significant recent developments in the field, both of a foundational and applicable character. An
important characteristic feature of the series is the short publication time and world-wide distribution. This permits a rapid and broad dissemination of research results.
Advisory Board
Chairman
Nikhil R. Pal, Indian Statistical Institute, Kolkata, India
e-mail: [email protected]
Members
Rafael Bello, Universidad Central “Marta Abreu” de Las Villas, Santa Clara, Cuba
e-mail: [email protected]
Emilio S. Corchado, University of Salamanca, Salamanca, Spain
e-mail: [email protected]
Hani Hagras, University of Essex, Colchester, UK
e-mail: [email protected]
László T. Kóczy, Széchenyi István University, Győr, Hungary
e-mail: [email protected]
Vladik Kreinovich, University of Texas at El Paso, El Paso, USA
e-mail: [email protected]
Chin-Teng Lin, National Chiao Tung University, Hsinchu, Taiwan
e-mail: [email protected]
Jie Lu, University of Technology, Sydney, Australia
e-mail: [email protected]
Patricia Melin, Tijuana Institute of Technology, Tijuana, Mexico
e-mail: [email protected]
Nadia Nedjah, State University of Rio de Janeiro, Rio de Janeiro, Brazil
e-mail: [email protected]
Ngoc Thanh Nguyen, Wroclaw University of Technology, Wroclaw, Poland
e-mail: [email protected]
Jun Wang, The Chinese University of Hong Kong, Shatin, Hong Kong
e-mail: [email protected]
Sigeru Omatu · Hugues Bersini
Juan M. Corchado · Sara Rodríguez
Paweł Pawlewski · Edgardo Bucciarelli
Editors
Distributed Computing
and Artificial Intelligence,
11th International Conference
ABC
Editors
Sigeru Omatu
Faculty of Engineering
Osaka Institute of Technology
Osaka
Japan
Sara Rodríguez
Faculty of Science
Department of Computing Science
and Control
University of Salamanca
Salamanca
Spain
Hugues Bersini
Université Libre de Bruxelles
Brussels
Belgium
Juan M. Corchado
Faculty of Science
Department of Computing Science and
Control
University of Salamanca
Salamanca
Spain
ISSN 2194-5357
ISBN 978-3-319-07592-1
DOI 10.1007/978-3-319-07593-8
Paweł Pawlewski
Faculty of Engineering Management
Poznan University of Technology
Poznan
Poland
Edgardo Bucciarelli
Dep. PPEQS, Section of Economics and
Quantitative Methods
University of Chieti-Pescara
Pescara
Italy
ISSN 2194-5365 (electronic)
ISBN 978-3-319-07593-8 (eBook)
Springer Cham Heidelberg New York Dordrecht London
Library of Congress Control Number: 2014939945
c Springer International Publishing Switzerland 2014
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Preface
Artificial intelligence is changing our society. Its application in distributed environments, such as internet, electronic commerce, environment monitoring, mobile communications, wireless devices, distributed computing, to mention only a few, is continuously increasing, becoming an element of high added value with social and economic
potential, in industry, quality of life and research. These technologies are changing constantly as a result of the large research and technical effort being undertaken in both
universities and businesses.
The 11th International Symposium on Distributed Computing and Artificial Intelligence 2014 (DCAI 2014) is a forum to present applications of innovative techniques
for solving complex problems in these areas. The exchange of ideas between scientists
and technicians from both the academic and industrial sector is essential to facilitate
the development of systems that can meet the ever-increasing demands of today’s society. The present edition brings together past experience, current work and promising
future trends associated with distributed computing, artificial intelligence and their application in order to provide efficient solutions to real problems. This conference is a
stimulating and productive forum where the scientific community can work towards
future cooperation in Distributed Computing and Artificial Intelligence areas.
Nowadays it is continuing to grow and prosper in its role as one of the premier conferences devoted to the quickly changing landscape of distributed computing, artificial
intelligence and the application of AI to distributed systems. This year’s technical program will present both high quality and diversity, with contributions in well-established
and evolving areas of research. Specifically, 75 papers were submitted from over 21
different countries (Algeria, Brazil, China, Croatia, Czech Republic, Denmark, France,
Germany, Ireland, Italy, Japan, Malaysia, Mexico, Poland, Portugal, Republic of Korea,
Spain, Taiwan, Tunisia, Ukraine, United Kingdom), representing a truly “wide area network” of research activity. The DCAI’14 technical program has selected 64 papers and,
as in past editions, it will be special issues in journals such as Neurocomputing, Journal of Artificial Intelligence (IJAI), the International Journal of Imaging and Robotics
(IJIR) and the International Journal of Interactive Multimedia and Artificial Intelligence
(IJIMAI). These special issues will cover extended versions of the most highly regarded
works. Moreover, DCAI’14 Special Sessions have been a very useful tool in order to
VI
Preface
complement the regular program with new or emerging topics of particular interest to
the participating community. Special Sessions that emphasize on multi-disciplinary and
transversal aspects, such as AI-driven methods for Multimodal Networks and Processes
Modeling and Multi-Agents Macroeconomics have been especially encouraged and welcome.
This symposium has been organized by the Bioinformatics, Intelligent System and
Educational Technology Research Group (http://bisite.usal.es/) of the University of
Salamanca. The present edition was held in Salamanca, Spain, from 4th to 6th June
2014.
We thank the sponsors (Indra, INSA - Ingeniería de Software Avanzado S.A., IBM,
JCyL, IEEE Systems Man and Cybernetics Society Spain, AEPIA Asociación Española
para la Inteligencia Artificial, APPIA Associação Portuguesa Para a Inteligência Artificial, CNRS Centre national de la recherche scientifique), the Ministerio de Economía
y Competitividad (Spain) with the project Sociedades Humano-Agente: Inmersión,
Adaptación y Simulación (TIN2012-36586-C03-03 - Project co-financed with FEDER
funds), and finally, the Local Organization members and the Program Committee members for their hard work, which was essential for the success of DCAI’14.
Salamanca
June 2014
Sigeru Omatu
Hugues Bersini
Juan M. Corchado
Sara Rodríguez
Paweł Pawlewski
Edgardo Bucciarelli (Eds.)
Organization
General Chairs
José M. Molina
James Llinas
Andre Ponce de Leon F. de
Carvalho
Ajith Abraham
Universidad Carlos III de Madrid, Spain
State University of New York, USA
University of Sao Paulo at Sao Carlos, Brazil
Norwegian University of Science and
Technology
Honorary Chairman
Masataka Inoue
President of Osaka Institute of Technology,
Japan
Scientific Committee
Sigeru Omatu (Chairman)
Hugues Bersini (Co-Chairman)
Adriana Giret
Alberto Fernández
Álvaro Herrero
Ana Carolina Lorena
Ângelo Costa
Antonio Moreno
Antonio Manuel de Jesús
Pereira
Araceli Sanchís
B. Cristina Pelayo
García-Bustelo
Bianca Innocenti
Bogdan Gabrys
Osaka Institute of Technology, Japan
Université Libre de Bruxelles, Belgium
Politechnich University of Valencia, Spain
University Rey Juan Carlos, Spain
University of Burgos, Spain
Federal University of ABC, Brazil
University of Minho, Portugal
University Rovira y Virgili, Spain
Leiria Polytechnic Institute, Portugal
University Carlos III of Madrid, Spain
University of Oviedo, Spain
University of Girona, Spain
Bournemouth University, UK
VIII
Organization
Bruno Baruque
Carina González
Carlos Carrascosa
Carmen Benavides
Daniel Glez-Peña
David Griol Barres
Davide Carneiro
Dídac Busquets
Dongshik Kang
Eladio Sanz
Eleni Mangina
Emilio Corchado
Eugenio Aguirre
Eugénio Oliveira
Evelio J. González
Faraón Llorens Largo
Fernando Díaz
Fidel Aznar Gregori
Florentino Fdez-Riverola
Francisco Pujol López
Fumiaki Takeda
Germán Gutiérrez
Grzegorz Bocewicz
Helder Coelho
Gustavo Santos
Ivan López Arévalo
Jamal Dargham
Javier Carbó
Javier Martínez Elicegui
Jesús García Herrero
Joao Gama
Johan Lilius
José R. Villar
Juan A. Botía
Juan Pavón
José M. Molina
José R. Méndez
José V. Álvarez-Bravo
Joseph Giampapa
Juan Manuel Cueva Lovelle
Juan Gómez Romero
Kazutoshi Fujikawa
University of Burgos, Spain
University of La Laguna, Spain
Politechnich University of Valencia, Spain
University of Leon, Spain
University of Vigo, Spain
University Carlos III of Madrid, Spain
University of Minho, Portugal
University of Girona, Spain
Ryukyu University, Japan
Unversity of Salamanca, Spain
University College Dublin, Ireland
University of Burgos, Spain
University of Granada, Spain
University of Porto, Portugal
University of La Laguna, Spain
University of Alicante, Spain
Univesity of Valladolid, Spain
University of Alicante, Spain
University of de Vigo, Spain
Polytechnic University of Alicante, Spain
Kochi Institute of Technology, Japan
University Carlos III, Spain
Koszalin University of technology, Poland
University of Lisbon, Portugal
University of Salamanca, Spain
Lab. of Information T. Cinvestav, Mexico
University of Malaysia, Saba, Malaysia
University Carlos III of Madrid, Spain
Telefónica I+D, Spain
University Carlos III of Madrid, Spain
University of Porto, Portugal
Åbo Akademi University, Finland
University of Oviedo, Spain
University of Murcia, Spain
Complutense University of Madrid, Spain
University Carlos III of Madrid, Spain
University of Vigo, Spain
University of Valladolid, Spain
Carnegie Mellon, USA
University of Oviedo, Spain
University Carlos III of Madrid, Spain
Nara Institute of Science and Technology,
Japan
Organization
Lourdes Borrajo
Luis Alonso
Luis Correia
Luis F. Castillo
Luís Lima
Manuel González-Bedia
Manuel Pegalajar Cuéllar
Manuel Resinas
Marcilio Souto
Margarida Cardoso
Maria del Mar Pujol López
Masanori Akiyoshi
Masaru Teranishi
Michifumi Yoshioka
Miguel Delgado
Miguel Ángel Patricio
Miguel Rebollo
Miguel A. Vega-Rodriguez
Mohd Saberi Mohamad
Michael Zaki
Noki Mori
Norihisa Komoda
Paulo Novais
Pawel Pawlewski
Peter Fobrig
Ichiro Satoh
Rafael Corchuelo
Ramón Rizo
René Leistikow
Ricardo Campello
Ricardo Costa
Rubén Fuentes
Rui Camacho
Sebastian Ahrndt
Sebastian Bader
Seiichi Ozawa
Seiji Ito
Seyedsaeid Mirkamali
Shanmugasundaram Hariharan
Silvana Aciar
University of Vigo, Spain
University of Salamanca, Spain
University of Libon, Portugal
Autonomous University of Manizales, Colombia
Polytechnic of Porto, Portugal
University of Zaragoza, Spain
University of Granada, Spain
University of Sevilla, Spain
Federal University of Rio Grande do Norte,
Brazil
ISCTE, Portugal
University of Alicante, Spain
Osaka University, Japan
Hiroshima Institute of Technology, Japan
Osaka Prefecture University, Japan
University of Granada, Spain
University Carlos III of Madrid, Spain
University of Vigo, Spain
University of Extremadura, Spain
University of Technology Malaysia, Malaysia
University Rostok, Germany
Osaka Prefecture University, Japan
Osaka University, Japan
Polytechnic University of Minho, Portugal
Poznan University of Technology, Poland
University Rostok, Germany
National Institute of Informatics, Japan
Catholic University of Sevilla, Spain
University of Alicante, Spain
University Rostok, Germany
University of Sao Paulo, Brazil
Polytechnic of Porto, Portugal
Complutense University of Madrid, Spain
University of Porto, Portugal
Technische Universität Berlin, Germany
University of Rostock, Germany
Kobe University, Japan
Hiroshima Institute of Technology, Japan
University of Mysore, India
B.S.Abdur Rahman University Vandalur, India
University of Girona, Spain
IX
X
Organization
Xinyu Que
Shiro Tamaki
Sofya V. Zhukova
Toru Yamamoto
Vicente Botti
Vicente Julián
Victor J. Sosa-Sosa
Viet-Hoang VU
Waldo Fajardo
Worawan Diaz Carballo
Yi Fang
Yusuke Nojima
Yutaka Maeda
Zbigniew Pasek
IBM Research, USA
University of the Ryukyus, Japan
St. Petersburg State University, Russia
Hiroshima University, Japan
Politechnich University of Valencia, Spain
Politechnich University of Valencia, Spain
Laboratory of Information
Technology - Cinvestav, México
Hanoi University of Technology, Vietnam
University of Granada, Spain
Thammasat University, Thailand
Purdue University, USA
Osaka Prefecture University, Japan
Kansai University, Japan
IMSE/University of Windsor, Canada
AI–Driven Methods for Multimodal Networks and Processes
Modeling Special Session Committee
Grzegorz Bocewicz (Chairman)
PawełPawlewski (Chairman)
Irena Bach-Dábrowska
(Co-Chairman)
Izabela E. Nielse
(Co-Chairman)
Peter Nielsen (Co-Chairman)
Robert Wójcik (Co-Chairman)
Zbigniew Banaszak
(Co-Chairman)
Koszalin University of Technology, Poland
Poznan University of Technology, Poland
Gdańsk University of Technology, Poland
Aalborg University, Denmark
Aalborg University, Denmark
Wrocław University of Technology, Poland
Warsaw University of Technology, Poland
Multi-Agents Macroeconomics Special Session Committee
Edgardo Bucciarelli
(Chairman)
Gianfranco Giulioni
(Chairman)
Alan Kirman
Anwar Shaikh
Barry Cooper
Enrico Rubaltelli
University of Chieti-Pescara, Italy
University of Chieti-Pescara, Italy
Aix-Marseille Université, France
The New School for Social Research, New York,
United States
University of Leeds, United Kingdom
University of Padua, Italy
Organization
Felix Freitag
José Carlos R. Alcantud
Katsunori Yamada
Leandro Navarro
Nicola Mattoscio
Shu-Heng Chen
Stefano Zambelli
Universitat Politècnica de Catalunya, Spain
University of Salamanca, Spain
Osaka University, Japan
Universitat Politècnica de Catalunya, Spain
University of Chieti-Pescara, Italy
National Chengchi University, Taipei, Taiwan
University of Trento, Italy
Organizing Committee
Juan M. Corchado (Chairman)
Sara Rodríguez (Co-Chairman)
Juan F. De Paz (Co-Chairman)
Javier Bajo
Fernando de la Prieta Pintado
Davinia Carolina Zato
Domínguez
Gabriel Villarrubia González
Antonio Juan Sánchez Martín
Dante I. Tapia
Emilio S. Corchado
Belén Pérez Lancho
Angélica González Arrieta
Vivian F. López
Ana de Luis
Ana B. Gil
University of Salamanca, Spain
University of Salamanca, Spain
University of Salamanca, Spain
Polytechnic University of Madrid, Spain
University of Salamanca, Spain
University of Salamanca, Spain
University of Salamanca, Spain
University of Salamanca, Spain
University of Salamanca, Spain
University of Salamanca, Spain
University of Salamanca, Spain
University of Salamanca, Spain
University of Salamanca, Spain
University of Salamanca, Spain
University of Salamanca, Spain
XI
Contents
AI-Driven Methods for Multimodal Networks and
Processes Modeling
Reachability Modeling for Multimodal Networks Prototyping . . . . . . . . . . . .
Grzegorz Bocewicz, Robert Wójcik, Zbigniew Banaszak
1
Hybrid Solution Framework for Supply Chain Problems . . . . . . . . . . . . . . . .
Paweł Sitek, Jarosław Wikarek
11
Scheduling of Mobile Robots with Preemptive Tasks . . . . . . . . . . . . . . . . . . . .
Izabela Nielsen, Quang-Vinh Dang, Peter Nielsen, Pawel Pawlewski
19
Multimodal Processes Approach to Supply Chain Modeling . . . . . . . . . . . . . .
Patrycja Hoffa, Pawel Pawlewski, Izabela Nielsen
29
Multimodal Perspective on Ontologies Combining Problem in Production
Management Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Przemysław Różewski, Justyna Bednarz
39
Multi-Agents Macroeconomics
Behavioral Macroeconomics and Agent-Based Macroeconomics . . . . . . . . . .
Shu-Heng Chen, Umberto Gostoli
47
Heterogeneous Households: Monopolistic Capitalists, Entrepreneurs and
Employees . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Jonathan Swarbrick
55
When Can Cognitive Agents Be Modeled Analytically versus
Computationally? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Leigh Caldwell
63
XIV
Contents
Designing a Homo Psychologicus More Psychologicus: Empirical
Results on Value Perception in Support to a New Theoretical
Organizational-Economic Agent Based Model . . . . . . . . . . . . . . . . . . . . . . . . .
Andrea Ceschi, Enrico Rubaltelli, Riccardo Sartori
Differences between Entrepreneurs and Managers in Large
Organizations: An Implementation of a Theoretical Multi-Agent Model
on Overconfidence Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Riccardo Sartori, Andrea Ceschi, Andrea Scalco
The Empirical Microstructure of Agent-Based Models:
Recent Trends in the Interplay between ACE and Experimental
Economics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Paola D’Orazio, Marcello Silvestri
71
79
85
Households Debt Behavior and Financial Instability: Towards an
Agent-Based Model with Experimentally Estimated Behavioral Rules . . . . .
Paola D’Orazio
91
Firm Size Distribution in Oblivious Equilibrium Model
with Quality Ladder . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Tetsushi Murao
99
Modeling Uncertainty in Banking Networks . . . . . . . . . . . . . . . . . . . . . . . . . . . 107
Stojan Davidovic, Mirta Galesic, Konstantinos Katsikopoulos,
Nimalan Arinaminpathy
Artificial Intelligence Applications
Changing the Hidden Rules - An Excel Template for Discussing Soccer’s
Competitive Balance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115
Joaquim Teixeira, Nuno Santos, Paulo Mourao
Insider Trading, Earnings and Stock Based Compensation:
A View to Speculation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123
Esther B. Del Brio, Ilidio Lopes-e-Silva, Javier Perote
Service-Oriented Architectures: From Design to Production Exploiting
Workflow Patterns . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131
Maurizio Gabbrielli, Saverio Giallorenzo, Fabrizio Montesi
Reinforcement Learning Based on the Bayesian Theorem for Electricity
Markets Decision Support . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 141
Tiago M. Sousa, Tiago Pinto, Isabel Praça, Zita Vale, Hugo Morais
Distributed and Guided Genetic Algorithm for Humanitarian Relief
Planning in Disaster Case . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 149
Fethi Mguis, Kamel Zidi, Khaled Ghedira, Pierre Borne
Contents
XV
FleSe: A Tool for Posing Flexible and Expressive (Fuzzy) Queries to a
Regular Database . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 157
Víctor Pablos-Ceruelo, Susana Muñoz-Hernández
Software Fault Prediction Based on Improved Fuzzy
Clustering . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 165
Golnoosh Abaei, Ali Selamat
Facial Authentication before and after Applying the Smowl Tool
in Moodle . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 173
Francisco D. Guillén-Gámez, Iván García-Magariño
SOA Modeling Based on MDA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 181
Haeng-Kon Kim, Tai-Hoonn Kim
Intelligent Lighting Control System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 195
Elena García, Sara Rodríguez, Juan F. De Paz, Javier Bajo
Multi-Agent Systems
Norm’s Benefit Awareness in Open Normative Multi-agent Communities:
A Conceptual Framework . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 209
Al-Mutazbellah Khamees Itaiwi, Mohd Sharifuddin Ahmad,
Moamin A. Mahmoud, Alicia Y.C. Tang
The Geranium System: Multimodal Conversational Agents
for E-learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 219
David Griol, José Manuel Molina, Araceli Sanchis de Miguel
DiSEN-AlocaHR: A Multi-Agent Mechanism for Human Resources
Allocation in a Distributed Software Development Environment . . . . . . . . . . 227
Lucas O. Teixeira, Elisa H.M. Huzita
Multi-Agent Web Recommendations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 235
Joaquim Neto, A. Jorge Morais
Designing Strategies for Improving the Performance of Groups in
Collective Environments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 243
L.F. Castillo, M.G. Bedia, C. Lopez, F.J. Seron, G. Isaza
Multiagent Application in Mobile Environments to Data Collection in
Park Zones . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 251
María Navarro, Fernando de la Prieta, Gabriel Villarrubia,
Mohd Saberi Mohamad
Organizational Architectures for Large-Scale Multi-Agent Systems’
Development: An Initial Ontology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 261
Markus Schatten
XVI
Contents
Distributed, Grid, Cloud and Mobile Computing
Exploring the Role of Macroeconomic Mechanisms in Voluntary
Resource Provisioning in Community Network Clouds . . . . . . . . . . . . . . . . . . 269
Amin M. Khan, Felix Freitag
Performance and Results of the Triple Buffering Built-In in a Raspberry
PI to Optimize the Distribution of Information from a Smart Sensor . . . . . . . 279
Jose-Luis Jimenez-Garcia, Jose-Luis Poza-Luján,
Juan-Luis Posadas-Yagüe, David Baselga-Masia,
José-Enrique Simó-Ten
Mobile Access to Sensor Network: A Use Case on Wildfire Monitoring . . . . . 287
Sergio Trilles, Óscar Belmonte, Joaquín Huerta
Building Scalable View Module of Object-Oriented Database . . . . . . . . . . . . . 295
Haeng-Kon Kim, Hyun Yeo
Bioinformatics, Biomedical Systems, E-health
E-Nose System by Using Neural Networks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 311
Sigeru Omatu, Mitsuak Yano
Modelling an Orientation System Based on Speculative Computation . . . . . . 319
João Ramos, Ken Satoh, Paulo Novais, José Neves
Stable Learning for Neural Network Tomography by Using Back
Projected Image . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 327
Masaru Teranishi, Keita Oka, Masahiro Aramoto
Security Considerations for Patient Telemonitoring Schemes through
Wireless Networks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 335
V. Morales, D. Cortés, N. Gordillo, A. De la Torre, D. Azpetia
Development of an Ontology for Supporting Diagnosis in Psychiatry . . . . . . 343
Cátia Silva, Goreti Marreiros, Nuno Silva
Augmented Reality Sign Language Teaching Model for Deaf Children . . . . . 351
Jorge Jonathan Cadeñanes Garnica, María Angélica González Arrieta
A Multi-agent Simulation: The Case of Physical Activity and Childhood
Obesity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 359
Rabia Aziza, Amel Borgi, Hayfa Zgaya, Benjamin Guinhouya
The Absorptive Capacity-Based View of Training: Enhancing
Organizational Performance. An Exploratory Study in Spanish Family
Businesses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 369
Felipe Hernández Perlines, María Yolanda Salinero Martín,
Benito Yáñez Araque
Contents
XVII
Data Mining, Information Extraction, Semantic,
Knowledge Representation
LIWC-Based Sentiment Analysis in Spanish Product Reviews . . . . . . . . . . . . 379
Estanislao López-López, María del Pilar Salas-Zárate,
Ángela Almela, Miguel Ángel Rodríguez-García, Rafael Valencia-García,
Giner Alor-Hernández
Data Extraction Tool to Analyse, Transform and Store Real Data from
Electricity Markets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 387
Ivo F. Pereira, Tiago M. Sousa, Isabel Praça, Ana Freitas,
Tiago Pinto, Zita Vale, Hugo Morais
Are There Semantic Primes in Formal Languages? . . . . . . . . . . . . . . . . . . . . . 397
Johannes Fähndrich, Sebastian Ahrndt, Sahin Albayrak
The Age of Confidentiality: A Review of the Security in Social Networks
and Internet . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 407
Antonio Juan Sánchez, Yves Demazeau
Extracting Sentences Describing Biomolecular Events from the
Biomedical Literature . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 417
Tiago Nunes, Sérgio Matos, José Luís Oliveira
TKG: A Graph-Based Approach to Extract Keywords from Tweets . . . . . . . 425
Willyan Daniel Abilhoa, Leandro Nunes de Castro
Image Processing, Tracking, Robotic, Control and
Industrial Systems
Outdoor Robotic Companion Based on a Google AndroidTM Smartphone
and GPS Guidance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 433
Eduard Clotet, Dani Martínez, Javier Moreno, Marcel Tresanchez,
Tomàs Pallejà, Davinia Font, Mercè Teixidó, Jordi Palacín
A Threshold Scheme for 3D Objects Based on Cellular Automata . . . . . . . . . 441
Angel Martín del Rey
Generation Method of the Trigger Signal for the Automatic Capture
System to the Harmful Animals with Intelligent Image Processing . . . . . . . . . 449
Fumiaki Takeda
2-Scene Comic Creating System Based on the Distribution of Picture
State Transition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 459
Miki Ueno, Naoki Mori, Keinosuke Matsumoto
A Brief Approach to the Ear Recognition Process . . . . . . . . . . . . . . . . . . . . . . . 469
Pedro Luis Galdámez, María Angélica González Arrieta,
Miguel Ramón Ramón
XVIII
Contents
Integration of Mobile Robot Navigation on a Control Kernel Middleware
Based System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 477
Eduardo Munera Sánchez, Manuel Muñoz Alcobendas,
Juan Luis Posadas Yagüe, Jose-Luis Poza-Luján,
J. Francisco Blanes Noguera
Shared Map Convolutional Neural Networks for Real-Time Mobile
Image Recognition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 485
William Raveane, María Angélica González Arrieta
New Algorithms
Using Multi-Objective Optimization to Design Parameters in
Electro-Discharge Machining by Wire . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 493
Alberto Ochoa, Lourdes Margain, Julio Arreola, Guadalupe Gutiérrez,
Geovani García, Fernando Maldonado
Learning Bayesian Networks Using Probability Vectors . . . . . . . . . . . . . . . . . 503
Sho Fukuda, Takuya Yoshihiro
A Constraint Programming Approach to the Zahn’s Decision Problem . . . . . 511
Mhamdi Amel, Naanaa Wady
Multi-agent Model Based on Tabu Search for the Permutation Flow Shop
Scheduling Problem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 519
Hafewa Bargaoui, Olfa Belkahla Driss
Neural-Based Method of Measuring Exchange-Rate Impact on
International Companies’ Revenue . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 529
Svitlana Galeshchuk
Parallel Batch Pattern Training Algorithm for MLP with Two Hidden
Layers on Many-Core System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 537
Volodymyr Turchenko
A Bee-Inspired Data Clustering Approach to Design RBF Neural
Network Classifiers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 545
Dávila Patrícia Ferreira Cruz, Renato Dourado Maia,
Leandro Augusto da Silva, Leandro Nunes de Castro
An Item Influence-Centric Algorithm for Recommender Systems . . . . . . . . . 553
Na Chang, Mhd Irvan, Takao Terano
Author Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 561
Reachability Modeling for Multimodal Networks
Prototyping
Grzegorz Bocewicz1, Robert Wójcik2, and Zbigniew Banaszak3
1
Department of Electronics and Computer Science, Koszalin University of Technology,
Sniadeckich 2, 75-453 Koszalin, Poland
[email protected]
2
Institute of Computer Engineering, Control and Robotics,
Wrocław University of Technology, Wroclaw, Poland
[email protected]
3
Department of Business Informatics, Warsaw University of Technology,
Narbutta 85, 02-524 Warsaw, Poland
[email protected]
Abstract. A declarative model aimed at reachability-driven refinement of the
multimodal networks (MNs) cyclic steady state space is proposed. The concept
of multimodal processes executed in goods/passengers transportation or data
transmission networks where several closed loop structure subnetworks interact
each other via distinguished subsets of common shared hubs as to provide a
variety of demand-responsive goods or data transportation/handling services is
employed. Multimodal processes throughput depends on their cycle time that is
on cycle time reachable in considered MN. Therefore, searching for the MN’s
cyclic steady state behavior the following question is considered: Is the cyclic
steady state space reachable in the given network structure? The declarative
approach employed makes it possible to evaluate the reachability of cyclic
behaviors on a scale that reflects real practice.
Keywords: multimodal network, initial states reduction-free method, cyclic
scheduling, constraint programming.
1
Introduction
Multimodal route planning that aims to find an optimal route between the source and
the target of a trip while utilizing several transportation modes including different
passenger/cargo transportation systems, e.g. ship, airline, AGV systems, train and
subway networks, are of significant importance [1, 2, 3, 6]. Multimodal processes
(MP) executed in the multimodal networks (MN), depending on the networks’ nature
can be seen either as passengers and/or goods flow transferred between different
modes to reach their destination [3] or as stream of packets transferred between the
source and destination nodes.
MPs planning problems, i.e. taking into account MPs routing and scheduling can
be found in different application domains (such as manufacturing, intercity fright
transportation, multimodal passenger transport network combining several unimodal
S. Omatu et al. (eds.), Distributed Computing and Artificial Intelligence,
11th International Conference, Advances in Intelligent Systems and Computing 290,
DOI: 10.1007/978-3-319-07593-8_1, © Springer International Publishing Switzerland 2014
1
2
G. Bocewicz, R. Wójcik, and Z. Banaszak
networks as well as distance learning environment and data and supply media flows,
e.g., cloud computing, oil pipeline, computer networks) [1, 3, 6, 8].
The local transportation/transmission processes serviced by different modes, while
executed along unimodal networks (lines, channels), are usually cyclic. Hence, MPs
supported by them also have the periodic character. That means that the periodicity of
MPs depends on periodicity of unimodal (local) processes executed in MN. Of
course, the MN throughput is maximized by the minimization of its cycle time.
Apart from such typically used, above mentioned, large scale networks let us focus
on smaller scale objects responsible for MP synchronization. In computer networks
such a role plays a router [8]. Assuming the given packet routings linking assumed
source-destination nodes have to be dedicated, e.g. for emergency cases. Since the
routings should be deadlock-free while of guaranteed capacity the capability of
routers employed play of primary role. In this context the paper discusses the
importance of transmission channels structure in assuring routers robustness. In other
words, a router’s channels structure design, enabling assumed output of packet
routings seen as MPs, is of our main interest.
The declarative models employing the constraint programming techniques
implemented in modern platforms such as OzMozart, ILOG, [2, 3] seems to be well
suited to cope with MPs planning problems. The existing approach to the concurrently
flowing cyclic processes scheduling problem is based upon the simulation models,
e.g. the Petri nets [13], the algebraic models [14] upon the (max,+) algebra or the
artificial intelligent methods [7, 15-17]. The constraints programming driven models
of multimodal networks composed of a set of local cyclic processes have been studied
in [2]. Therefore, this work can be seen as a continuation of our former investigations
conducted in [2, 3]. In that context, our paper provides contribution to reachability
modeling of multimodal networks as well as to multimodal processes prototyping.
Section 2 provides a description of a multimodal network while modeling its
structural and behavioral features. In Section 3 we formulate the problem of cyclic
states space generation for the given MN structure. The method of solving this
problem is shown in Section 4. Then, Sections 5 and 6 describe the conducted
experiments and provide conclusions resulting from them.
2
Modelling of Multimodal Networks
2.1
Structure
Fig. 1 shows an example of a four-port router for Video on Demand [7] where four
and ) support two MP servicing a
local packets transmission processes ( , ,
computer network dedicated routings. MP are transmitted along two routings:
distinguished by blue –
and red –
, lines. MP of this kind can be modeled
as the SCMCP shown in Fig. 1b). The class SCMCP is assumed to include two types
of processes:
,
,
,
), whose
• local processes (representing modes of transport –
operations are cyclically repeated along the set routes (sequences of successively
used resources). For the system from Fig. 1b), the routes of local processes are
defined as follows:
= ( , , ),
= ( , , ),
= ( , , ),
= ( , , ),