Search results for "Network model"
showing 10 items of 69 documents
Energy Efficient Consensus Over Complex Networks
2015
The need to extract large amounts of information from the environment to have precise situation awareness and then react appropriately to certain events has led to the emergence of complex and heterogeneous sensor networks. In this context, where the sensor nodes are usually powered by batteries, the design of new methods to make inference processes efficient in terms of energy consumption is necessary. One of these processes, which is present in many distributed tasks performed by these complex networks, is the consensus process. This is the basis for certain tracking algorithms in monitoring and control applications. To improve the energy efficiency of this process, in this paper we propo…
Anatomical networks reveal the musculoskeletal modularity of the human head
2015
AbstractMosaic evolution is a key mechanism that promotes robustness and evolvability in living beings. For the human head, to have a modular organization would imply that each phenotypic module could grow and function semi-independently. Delimiting the boundaries of head modules and even assessing their existence, is essential to understand human evolution. Here we provide the first study of the human head using anatomical network analysis (AnNA), offering the most complete overview of the modularity of the head to date. Our analysis integrates the many biological dependences that tie hard and soft tissues together, arising as a consequence of development, growth, stresses and loads and mo…
Grist for Riedl's mill: A network model perspective on the integration and modularity of the human skull
2013
This research project was supported by Grant BFU2008‐00643 to D.R.G. from the Spanish Ministerio de Ciencia e Innovacion as well as project CGL2012‐37279 to M.B., from the Spanish Ministerio de Economia y Competitividad.
Study of elution behaviour with gradient voltage in CEC using methacrylate monolithic columns.
2010
A theoretical study on the retention behaviour and chromatographic performance of neutral solutes using a lauryl methacrylate-based monolithic column under voltage gradient mode in CEC was carried out. Through a flexible mathematical function based on a modified Gaussian model, the peak shape of compounds was firstly fitted under constant and gradient voltage. Using the peak shape parameters and retention time, the estimation of global chromatographic performance, efficiency and peak capacity under several voltage conditions was performed. The influence of voltage gradient on the separation efficiency is discussed and simple equations are presented to calculate retention and peak widths und…
Catalan Morphology and Low-level Patterns in a Network Model
2005
The fact that more specific or low-level morphological patterns may coexist with the most general or abstract ones is a characteristic insight of Cognitive Morphology. According to the bottom-up approach of the model, it is even to be expected that low-level patterns may have a more relevant role than the most inclusive and abstract ones. On the basis of the analysis of an aspect of Catalan inflection (velar verbs of the second conjugation) and one aspect of Catalan word-formation (complex words with the prefixoid radio-), we will show the advantages of incorporating to the model salient low-level patterns and the local paradigmatic relations in which they are based. info:eu-repo/semantics/…
Distributed intelligent management,of active networks
2003
This paper focuses on improving computer network management by the adoption of artificial intelligence techniques. A logical inference system has being devised to enable automated isolation, diagnosis, and even repair of network problems, thus enhancing the reliability, performance, and security of networks. We propose a distributed multi-agent architecture for network management, where a logical reasoner acts as an external managing entity capable of directing, coordinating, and stimulating actions in an active management architecture. The active networks technology represents the lower level layer which makes possible the deployment of code which implement teleo-reactive agents, distribut…
Analysis and simulation of creativity learning by means of artificial neural networks
2007
The paper presents a new neural network approach for analysis and simulation of creative behavior. The used concept of Dynamically Controlled Neural Gas (DyCoNG) entails a combination of Dynamically Controlled Network [Perl, J. (2004a). A neural network approach to movement pattern analysis. Human Movement Science,23, 605-620] and Growing Neural Gas (Fritzke, 1995) by quality neurons. A quality neuron reflects the rareness of a piece of information and therefore can measure the originality of a recorded activity that was assigned to the neuron during the network training. The DyCoNG approach was validated using data from a longitudinal field-based study. The creative behavior of 42 particip…
Interbank lending and the spread of bank failures: A network model of systemic risk
2012
We model a stylized banking system where banks are characterized by the amount of capital, cash reserves and their exposure to the interbank loan market as borrowers as well as lenders. A network of interbank lending is established that is used as a transmission mechanism for the failure of banks through the system. We trigger a potential banking crisis by exogenously failing a bank and investigate the spread of this failure within the banking system. We find the obvious result that the size of the bank initially failing is the dominant factor whether contagion occurs, but for the extent of its spread the characteristics of the network of interbank loans are most important. These results ha…
Dynamic Pattern Recognition in Sport by Means of Artificial Neural Networks
2008
Behavioural processes like those in sports, motor activities or rehabilitation are often the object of optimization methods. Such processes are often characterized by a complex structure. Measurements considering them may produce a huge amount of data. It is an interesting challenge not only to store these data, but also to transform them into useful information. Artificial Neural Networks turn out to be an appropriate tool to transform abstract numbers into informative patterns that help to understand complex behavioural phenomena. The contribution presents some basic ideas of neural network approaches and several examples of application. The aim is to give an impression of how neural meth…
Evidence against a glass transition in the 10-state short range Potts glass
2002
We present the results of Monte Carlo simulations of two different 10-state Potts glasses with random nearest neighbor interactions on a simple cubic lattice. In the first model the interactions come from a \pm J distribution and in the second model from a Gaussian one, and in both cases the first two moments of the distribution are chosen to be equal to J_0=-1 and Delta J=1. At low temperatures the spin autocorrelation function for the \pm J model relaxes in several steps whereas the one for the Gaussian model shows only one. In both systems the relaxation time increases like an Arrhenius law. Unlike the infinite range model, there are only very weak finite size effects and there is no evi…