11 research outputs found
Pattern Recognition
A wealth of advanced pattern recognition algorithms are emerging from the interdiscipline between technologies of effective visual features and the human-brain cognition process. Effective visual features are made possible through the rapid developments in appropriate sensor equipments, novel filter designs, and viable information processing architectures. While the understanding of human-brain cognition process broadens the way in which the computer can perform pattern recognition tasks. The present book is intended to collect representative researches around the globe focusing on low-level vision, filter design, features and image descriptors, data mining and analysis, and biologically inspired algorithms. The 27 chapters coved in this book disclose recent advances and new ideas in promoting the techniques, technology and applications of pattern recognition
Interdependent networks - topological percolation research and application in finance
This dissertation covers the two major parts of my Ph.D. research: i) developing a theoretical framework of complex networks and applying simulation and numerical methods to study the robustness of the network system, and ii) applying statistical physics concepts and methods to quantitatively analyze complex systems and applying the theoretical framework to study real-world systems.
In part I, we focus on developing theories of interdependent networks as well as building computer simulation models, which includes three parts: 1) We report on the effects of topology on failure propagation for a model system consisting of two interdependent networks. We find that the internal node correlations in each of the networks significantly changes the critical density of failures, which can trigger the total disruption of the two-network system. Specifically, we find that the assortativity within a single network decreases the robustness of the entire system. 2) We study the percolation behavior of two interdependent scale-free (SF) networks under random failure of 1-p fraction of nodes. We find that as the coupling strength q between the two networks reduces from 1 (fully coupled) to 0 (no coupling), there exist two critical coupling strengths q1 and q2 , which separate the behaviors of the giant component as a function of p into three different regions, and for q2 < q < q1 , we observe a hybrid order phase transition phenomenon. 3) We study the robustness of n interdependent networks with partially support-dependent relationship both analytically and numerically. We study a starlike network of n Erdos-Renyi (ER), SF networks and a looplike network of n ER networks, and we find for starlike networks, their phase transition regions change with n, but for looplike networks the phase regions change with average degree k .
In part II, we apply concepts and methods developed in statistical physics to study economic systems. We analyze stock market indices and foreign exchange daily returns for 60 countries over the period of 1999-2012. We build a multi-layer network model based on different correlation measures, and introduce a dynamic network model to simulate and analyze the initializing and spreading of financial crisis. Using different computational approaches and econometric tests, we find atypical behavior of the cross correlations and community formations in the financial networks that we study during the financial crisis of 2008. For example, the overall correlation of stock market increases during crisis while the correlation between stock market and foreign exchange market decreases. The dramatic increase in correlations between a specific nation and other nations may indicate that this nation could trigger a global financial crisis. Specifically, core countries that have higher correlations with other countries and larger Gross Domestic Product (GDP) values spread financial crisis quite effectively, yet some countries with small GDPs like Greece and Cyprus are also effective in propagating systemic risk and spreading global financial crisis
The 1991 3rd NASA Symposium on VLSI Design
Papers from the symposium are presented from the following sessions: (1) featured presentations 1; (2) very large scale integration (VLSI) circuit design; (3) VLSI architecture 1; (4) featured presentations 2; (5) neural networks; (6) VLSI architectures 2; (7) featured presentations 3; (8) verification 1; (9) analog design; (10) verification 2; (11) design innovations 1; (12) asynchronous design; and (13) design innovations 2
LIPIcs, Volume 251, ITCS 2023, Complete Volume
LIPIcs, Volume 251, ITCS 2023, Complete Volum
Fault tolerant and dynamic evolutionary optimization engines
Mimicking natural evolution to solve hard optimization problems has played an important
role in the artificial intelligence arena. Such techniques are broadly classified
as Evolutionary Algorithms (EAs) and have been investigated for around four decades
during which important contributions and advances have been made.
One main evolutionary technique which has been widely investigated is the Genetic
Algorithm (GA). GAs are stochastic search techniques that follow the Darwinian
principle of evolution. Their application in the solution of hard optimization problems
has been very successful. Indeed multi-dimensional problems presenting difficult search
spaces with characteristics such as multi-modality, epistasis, non regularity, deceptiveness,
etc., have all been effectively tackled by GAs.
In this research, a competitive form of GAs known as fine or cellular GAs (cGAs)
are investigated, because of their suitability for System on Chip (SoC) implementation
when tackling real-time problems. Cellular GAs have also attracted the attention
of researchers due to their high performance, ease of implementation and massive
parallelism. In addition, cGAs inherently possess a number of structural configuration
parameters which make them capable of sustaining diversity during evolution and
therefore of promoting an adequate balance between exploitative and explorative stages
of the search.
The fast technological development of Integrated Circuits (ICs) has allowed a considerable
increase in compactness and therefore in density. As a result, it is nowadays
possible to have millions of gates and transistor based circuits in very small silicon
areas. Operational complexity has also significantly increased and consequently other
setbacks have emerged, such as the presence of faults that commonly appear in the
form of single or multiple bit flips. Tough environmental or time dependent operating
conditions can trigger faults in registers and memory allocations due to induced radiation, electron migration and dielectric breakdown. These kinds of faults are known as
Single Event Effects (SEEs).
Research has shown that an effective way of dealing with SEEs consists of a combination
of hardware and software mitigation techniques to overcome faulty scenarios.
Permanent faults known as Single Hard Errors (SHEs) and temporary faults known
as Single Event Upsets (SEUs) are common SEEs. This thesis aims to investigate the
inherent abilities of cellular GAs to deal with SHEs and SEUs at algorithmic level. A
hard real-time application is targeted: calculating the attitude parameters for navigation
in vehicles using Global Positioning System (GPS) technology. Faulty critical
data, which can cause a system’s functionality to fail, are evaluated. The proposed
mitigation techniques show cGAs ability to deal with up to 40% stuck at zero and 30%
stuck at one faults in chromosomes bits and fitness score cells.
Due to the non-deterministic nature of GAs, dynamic on-the-fly algorithmic and
parametric configuration has also attracted the attention of researchers. In this respect,
the structural properties of cellular GAs provide a valuable attribute to influence their
selection pressure. This helps to maintain an adequate exploitation-exploration tradeoff,
either from a pure topological perspective or through genetic operations that also
make use of structural characteristics in cGAs. These properties, unique to cGAs, are
further investigated in this thesis through a set of middle to high difficulty benchmark
problems. Experimental results show that the proposed dynamic techniques enhance
the overall performance of cGAs in most benchmark problems.
Finally, being structurally attached, the dimensionality of cellular GAs is another
line of investigation. 1D and 2D structures have normally been used to test cGAs at
algorithm and implementation levels. Although 3D-cGAs are an immediate extension,
not enough attention has been paid to them, and so a comparative study on the dimensionality
of cGAs is carried out. Having shorter radii, 3D-cGAs present a faster
dissemination of solutions and have denser neighbourhoods. Empirical results reported
in this thesis show that 3D-cGAs achieve better efficiency when solving multi-modal
and epistatic problems. In future, the performance improvements of 3D-cGAs will
merge with the latest benefits that 3D integration technology has demonstrated, such
as reductions in routing length, in interconnection delays and in power consumption
New Fundamental Technologies in Data Mining
The progress of data mining technology and large public popularity establish a need for a comprehensive text on the subject. The series of books entitled by "Data Mining" address the need by presenting in-depth description of novel mining algorithms and many useful applications. In addition to understanding each section deeply, the two books present useful hints and strategies to solving problems in the following chapters. The contributing authors have highlighted many future research directions that will foster multi-disciplinary collaborations and hence will lead to significant development in the field of data mining
Anuário CientÃfico – 2011 Resumos de Artigos, Comunicações, Livros e Monografias de Mestrado
Há mais de uma década que o ISEL vem firmando a sua aposta na busca e na divulgação do conhecimento cientÃfico na área da Engenharia, assentes na inovação e no desenvolvimento de novas tecnologias, procurando que os resultados alcançados nos projetos de investigação tenham impacto na indústria e na vida dos cidadãos como forma de responder à s necessidades cada vez mais complexas e exigentes da sociedade no seu todo.
Nesta relação, o ISEL tem contribuÃdo para a evolução da produção e do conhecimento cientÃficos, assumindo, por vezes numa posição de vanguarda, ora em iniciativa própria ora em parceria com diversas instituições, quer de ensino quer do tecido empresarial.
Como forma de dar visibilidade ao trabalho desenvolvido pelos docentes (com afiliação ISEL) e alunos do ISEL, o Anuário CientÃfico tornou-se num meio de divulgação privilegiado, estando disponÃvel em acesso livre a toda a comunidade cientÃfica mas também a todos os cidadãos, podendo ser consultado em formato eletrónico no sÃtio institucional do ISEL, bem como no Repositório CientÃfico do Instituto PolÃtécnico de Lisboa.1
Fazendo uma análise comparativa em relação às publicações referentes a 2009 e a 2010, constata-se que o número de publicações duplicou em 2011
Anales del XIII Congreso Argentino de Ciencias de la Computación (CACIC)
Contenido:
Arquitecturas de computadoras
Sistemas embebidos
Arquitecturas orientadas a servicios (SOA)
Redes de comunicaciones
Redes heterogéneas
Redes de Avanzada
Redes inalámbricas
Redes móviles
Redes activas
Administración y monitoreo de redes y servicios
Calidad de Servicio (QoS, SLAs)
Seguridad informática y autenticación, privacidad
Infraestructura para firma digital y certificados digitales
Análisis y detección de vulnerabilidades
Sistemas operativos
Sistemas P2P
Middleware
Infraestructura para grid
Servicios de integración (Web Services o .Net)Red de Universidades con Carreras en Informática (RedUNCI