IDENTIFYING DATA 2016_17
Subject (*) COMPLEX NETWORKS Code 17685208
Study programme
Computer Security Engineering and Artificial Intelligence (2016)
 Cycle 2nd
Descriptors Credits Type Year Period
3 Optional 2Q
Language
Anglès
Department Computer Engineering and Mathematics
Coordinator
GÓMEZ JIMÉNEZ, SERGIO
 E-mail alexandre.arenas@urv.cat
sergio.gomez@urv.cat
manlio.dedomenico@urv.cat
Lecturers
ARENAS MORENO, ALEJANDRO
GÓMEZ JIMÉNEZ, SERGIO
DE DOMENICO ., MANLIO
Web
General description and relevant information This course covers the study of the main concepts and algorithms for the analysis of complex networks, the models that summarize their most relevant properties, and the dynamics which take place on top of them. First, we show the presence of complex networks in all kinds of fields (biology, ecology, social sciences, economy, linguistics, etc.) and we analyze their most recurrent and important properties, such as the power law degree distributions, the transitivity, the small world property and the assortativity. We will take special attention to the mesoscopic structure of complex networks, reviewing the main algorithms for the detection of their community structure. We will also study the main models of random complex networks, which allow the understanding of the appearance of their distinctive structural properties. Finally, we will describe some of the dynamics on complex networks, such as synchronization and epidemics spreading.

Competences
Type A Code Competences Specific
 A1 Integrate the fundamental technology, applications, services and systems of Computer Security and Artificial Intelligence,in a broader, multidisciplinary context.
 A7 Understand and apply advanced knowledge of high performance computing and numerical or computational problems related to artificial intelligence neural networks and evolutionary systems methods.
 G2 Perform mathematical modelling, calculation and simulation in company technology and engineering centres, particularly in tasks of research, development and innovation in the areas of Computer Security and Artificial Intelligence
Type B Code Competences Transversal
  CT1 Gestionar i comunicar informació complexa, de temes diversos, amb naturalitat, en llengua estrangera.
 CT2 Formular valoracions a partir de la gestió i ús eficient de la informació.
 CT3 Resoldre problemes complexes de manera crítica, creativa i innovadora en contextos multidisciplinars.
 CT5 Comunicar idees complexes de manera efectiva a tot tipus d’audiències.
Type C Code Competences Nuclear

Learning outcomes
Type A Code Learning outcomes
 A1 Analitza els problemes i les seves causes des d'un enfocament global i de mitjà i llarg termini.
 A7 Coneix les principals característiques de la teoria de xarxes complexes.
Coneix i sap les propietats estructurals de les xarxes complexes.
Sap implementar models de xarxes complexes.
Sap utilitzar els mètodes de detecció de comunitats en xarxes.
Sap resoldre problemes dinàmics en xarxes complexes.
Es familiaritza amb la recerca, comprensió i utilització d'articles d'investigació en llengua estrangera.
 G2 Aplica les tècniques apreses en contextos concrets.
Type B Code Learning outcomes
  CT1 Gestionar i comunicar informació complexa, de temes diversos, amb naturalitat, en llengua estrangera.
 CT2 Formular valoracions a partir de la gestió i ús eficient de la informació.
 CT3 Resoldre problemes complexes de manera crítica, creativa i innovadora en contextos multidisciplinars.
 CT5 Comunicar idees complexes de manera efectiva a tot tipus d’audiències.
Type C Code Learning outcomes

Contents
Topic Sub-topic
Structural properties of complex networks
 Introduction to complex networks
Real networks examples
Classification of networks
Metrics on networks
Models of complex networks Erdos-Renyi model
Barabasi-Albert preferential attachment
Configuration model
Watts-Strogatz small-world model
Mesoscopic description of complex networks Community structure in complex networks
Community detection algorithms
Multiple resolution of community structure in networks
Dynamics on networks Synchronization in complex networks
Epidemic spreading in complex networks
Other dynamics: percolation, evolutionary games, diffusion, etc.

Planning
Methodologies  ::  Tests
  Competences (*) Class hours
 Hours outside the classroom
 (**) Total hours
Introductory activities
1 0 1
Lecture
A7
CT2
 17 13 30
Practicals using information and communication technologies (ICTs) in computer rooms
A7
G2
 8 12 20
ICT practicals
A1
A7
G2
CT1
CT2
CT3
CT5
 2 20 22
Personal tuition
2 0 2
 
 
(*) On e-learning, hours of virtual attendance of the teacher.
(**) The information in the planning table is for guidance only and does not take into account the heterogeneity of the students.

Methodologies
Methodologies
  Description
Introductory activities Introduction to the course and its contents
Lecture Contents exposition and materials availability in electronic form
Practicals using information and communication technologies (ICTs) in computer rooms Tools for the developent of solutions and the practical resolution of problems
ICT practicals Practical exercises to attain experience and consolidate the theoretical knowledge
Personal tuition Personal tuitition, both in person or through telematic means

Personalized attention
Description
Soving doubts about the contents and practical exercises. Both in person or by email.

Assessment
Methodologies Competences Description Weight        
ICT practicals
A1
A7
G2
CT1
CT2
CT3
CT5
 Evaluation of practical exercises. 100%
Others  
 
Other comments and second exam session

Sources of information

Basic Newman, M.E.J., Networks: An Introduction, Oxford University Press, 2010

Articles in scientific journals:

- M.E.J. Newman: The Structure and Function of Complex Networks, SIAM Review 45 (2003) 167–256
- S. Boccaletti, V. Latora, Y. Moreno, M. Chavez, D.-U. Hwang: Complex networks: Structure and dynamics, Physics Reports 424 (2006) 175–308
- S. Fortunato: Community detection in graphs, Physics Reports 486 (2010) 75-174
Complementary

Recommendations
(*)The teaching guide is the document in which the URV publishes the information about all its courses. It is a public document and cannot be modified. Only in exceptional cases can it be revised by the competent agent or duly revised so that it is in line with current legislation.