831 resultados para Multiport Network Model
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The transient and equilibrium properties of dynamics unfolding in complex systems can depend critically on specific topological features of the underlying interconnections. In this work, we investigate such a relationship with respect to the integrate-and-fire dynamics emanating from a source node and an extended network model that allows control of the small-world feature as well as the length of the long-range connections. A systematic approach to investigate the local and global correlations between structural and dynamical features of the networks was adopted that involved extensive simulations (one and a half million cases) so as to obtain two-dimensional correlation maps. Smooth, but diverse surfaces of correlation values were obtained in all cases. Regarding the global cases, it has been verified that the onset avalanche time (but not its intensity) can be accurately predicted from the structural features within specific regions of the map (i.e. networks with specific structural properties). The analysis at local level revealed that the dynamical features before the avalanches can also be accurately predicted from structural features. This is not possible for the dynamical features after the avalanches take place. This is so because the overall topology of the network predominates over the local topology around the source at the stationary state.
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Abstract Background A popular model for gene regulatory networks is the Boolean network model. In this paper, we propose an algorithm to perform an analysis of gene regulatory interactions using the Boolean network model and time-series data. Actually, the Boolean network is restricted in the sense that only a subset of all possible Boolean functions are considered. We explore some mathematical properties of the restricted Boolean networks in order to avoid the full search approach. The problem is modeled as a Constraint Satisfaction Problem (CSP) and CSP techniques are used to solve it. Results We applied the proposed algorithm in two data sets. First, we used an artificial dataset obtained from a model for the budding yeast cell cycle. The second data set is derived from experiments performed using HeLa cells. The results show that some interactions can be fully or, at least, partially determined under the Boolean model considered. Conclusions The algorithm proposed can be used as a first step for detection of gene/protein interactions. It is able to infer gene relationships from time-series data of gene expression, and this inference process can be aided by a priori knowledge available.
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The Ph.D. thesis describes the simulations of different microwave links from the transmitter to the receiver intermediate-frequency ports, by means of a rigorous circuit-level nonlinear analysis approach coupled with the electromagnetic characterization of the transmitter and receiver front ends. This includes a full electromagnetic computation of the radiated far field which is used to establish the connection between transmitter and receiver. Digitally modulated radio-frequency drive is treated by a modulation-oriented harmonic-balance method based on Krylov-subspace model-order reduction to allow the handling of large-size front ends. Different examples of links have been presented: an End-to-End link simulated by making use of an artificial neural network model; the latter allows a fast computation of the link itself when driven by long sequences of the order of millions of samples. In this way a meaningful evaluation of such link performance aspects as the bit error rate becomes possible at the circuit level. Subsequently, a work focused on the co-simulation an entire link including a realistic simulation of the radio channel has been presented. The channel has been characterized by means of a deterministic approach, such as Ray Tracing technique. Then, a 2x2 multiple-input multiple-output antenna link has been simulated; in this work near-field and far-field coupling between radiating elements, as well as the environment factors, has been rigorously taken into account. Finally, within the scope to simulate an entire ultra-wideband link, the transmitting side of an ultrawideband link has been designed, and an interesting Front-End co-design technique application has been setup.
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The research activity carried out during the PhD course was focused on the development of mathematical models of some cognitive processes and their validation by means of data present in literature, with a double aim: i) to achieve a better interpretation and explanation of the great amount of data obtained on these processes from different methodologies (electrophysiological recordings on animals, neuropsychological, psychophysical and neuroimaging studies in humans), ii) to exploit model predictions and results to guide future research and experiments. In particular, the research activity has been focused on two different projects: 1) the first one concerns the development of neural oscillators networks, in order to investigate the mechanisms of synchronization of the neural oscillatory activity during cognitive processes, such as object recognition, memory, language, attention; 2) the second one concerns the mathematical modelling of multisensory integration processes (e.g. visual-acoustic), which occur in several cortical and subcortical regions (in particular in a subcortical structure named Superior Colliculus (SC)), and which are fundamental for orienting motor and attentive responses to external world stimuli. This activity has been realized in collaboration with the Center for Studies and Researches in Cognitive Neuroscience of the University of Bologna (in Cesena) and the Department of Neurobiology and Anatomy of the Wake Forest University School of Medicine (NC, USA). PART 1. Objects representation in a number of cognitive functions, like perception and recognition, foresees distribute processes in different cortical areas. One of the main neurophysiological question concerns how the correlation between these disparate areas is realized, in order to succeed in grouping together the characteristics of the same object (binding problem) and in maintaining segregated the properties belonging to different objects simultaneously present (segmentation problem). Different theories have been proposed to address these questions (Barlow, 1972). One of the most influential theory is the so called “assembly coding”, postulated by Singer (2003), according to which 1) an object is well described by a few fundamental properties, processing in different and distributed cortical areas; 2) the recognition of the object would be realized by means of the simultaneously activation of the cortical areas representing its different features; 3) groups of properties belonging to different objects would be kept separated in the time domain. In Chapter 1.1 and in Chapter 1.2 we present two neural network models for object recognition, based on the “assembly coding” hypothesis. These models are networks of Wilson-Cowan oscillators which exploit: i) two high-level “Gestalt Rules” (the similarity and previous knowledge rules), to realize the functional link between elements of different cortical areas representing properties of the same object (binding problem); 2) the synchronization of the neural oscillatory activity in the γ-band (30-100Hz), to segregate in time the representations of different objects simultaneously present (segmentation problem). These models are able to recognize and reconstruct multiple simultaneous external objects, even in difficult case (some wrong or lacking features, shared features, superimposed noise). In Chapter 1.3 the previous models are extended to realize a semantic memory, in which sensory-motor representations of objects are linked with words. To this aim, the network, previously developed, devoted to the representation of objects as a collection of sensory-motor features, is reciprocally linked with a second network devoted to the representation of words (lexical network) Synapses linking the two networks are trained via a time-dependent Hebbian rule, during a training period in which individual objects are presented together with the corresponding words. Simulation results demonstrate that, during the retrieval phase, the network can deal with the simultaneous presence of objects (from sensory-motor inputs) and words (from linguistic inputs), can correctly associate objects with words and segment objects even in the presence of incomplete information. Moreover, the network can realize some semantic links among words representing objects with some shared features. These results support the idea that semantic memory can be described as an integrated process, whose content is retrieved by the co-activation of different multimodal regions. In perspective, extended versions of this model may be used to test conceptual theories, and to provide a quantitative assessment of existing data (for instance concerning patients with neural deficits). PART 2. The ability of the brain to integrate information from different sensory channels is fundamental to perception of the external world (Stein et al, 1993). It is well documented that a number of extraprimary areas have neurons capable of such a task; one of the best known of these is the superior colliculus (SC). This midbrain structure receives auditory, visual and somatosensory inputs from different subcortical and cortical areas, and is involved in the control of orientation to external events (Wallace et al, 1993). SC neurons respond to each of these sensory inputs separately, but is also capable of integrating them (Stein et al, 1993) so that the response to the combined multisensory stimuli is greater than that to the individual component stimuli (enhancement). This enhancement is proportionately greater if the modality-specific paired stimuli are weaker (the principle of inverse effectiveness). Several studies have shown that the capability of SC neurons to engage in multisensory integration requires inputs from cortex; primarily the anterior ectosylvian sulcus (AES), but also the rostral lateral suprasylvian sulcus (rLS). If these cortical inputs are deactivated the response of SC neurons to cross-modal stimulation is no different from that evoked by the most effective of its individual component stimuli (Jiang et al 2001). This phenomenon can be better understood through mathematical models. The use of mathematical models and neural networks can place the mass of data that has been accumulated about this phenomenon and its underlying circuitry into a coherent theoretical structure. In Chapter 2.1 a simple neural network model of this structure is presented; this model is able to reproduce a large number of SC behaviours like multisensory enhancement, multisensory and unisensory depression, inverse effectiveness. In Chapter 2.2 this model was improved by incorporating more neurophysiological knowledge about the neural circuitry underlying SC multisensory integration, in order to suggest possible physiological mechanisms through which it is effected. This endeavour was realized in collaboration with Professor B.E. Stein and Doctor B. Rowland during the 6 months-period spent at the Department of Neurobiology and Anatomy of the Wake Forest University School of Medicine (NC, USA), within the Marco Polo Project. The model includes four distinct unisensory areas that are devoted to a topological representation of external stimuli. Two of them represent subregions of the AES (i.e., FAES, an auditory area, and AEV, a visual area) and send descending inputs to the ipsilateral SC; the other two represent subcortical areas (one auditory and one visual) projecting ascending inputs to the same SC. Different competitive mechanisms, realized by means of population of interneurons, are used in the model to reproduce the different behaviour of SC neurons in conditions of cortical activation and deactivation. The model, with a single set of parameters, is able to mimic the behaviour of SC multisensory neurons in response to very different stimulus conditions (multisensory enhancement, inverse effectiveness, within- and cross-modal suppression of spatially disparate stimuli), with cortex functional and cortex deactivated, and with a particular type of membrane receptors (NMDA receptors) active or inhibited. All these results agree with the data reported in Jiang et al. (2001) and in Binns and Salt (1996). The model suggests that non-linearities in neural responses and synaptic (excitatory and inhibitory) connections can explain the fundamental aspects of multisensory integration, and provides a biologically plausible hypothesis about the underlying circuitry.
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The main aim of this thesis is strongly interdisciplinary: it involves and presumes a knowledge on Neurophysiology, to understand the mechanisms that undergo the studied phenomena, a knowledge and experience on Electronics, necessary during the hardware experimental set-up to acquire neuronal data, on Informatics and programming to write the code necessary to control the behaviours of the subjects during experiments and the visual presentation of stimuli. At last, neuronal and statistical models should be well known to help in interpreting data. The project started with an accurate bibliographic research: until now the mechanism of perception of heading (or direction of motion) are still poorly known. The main interest is to understand how the integration of visual information relative to our motion with eye position information happens. To investigate the cortical response to visual stimuli in motion and the integration with eye position, we decided to study an animal model, using Optic Flow expansion and contraction as visual stimuli. In the first chapter of the thesis, the basic aims of the research project are presented, together with the reasons why it’s interesting and important to study perception of motion. Moreover, this chapter describes the methods my research group thought to be more adequate to contribute to scientific community and underlines my personal contribute to the project. The second chapter presents an overview on useful knowledge to follow the main part of the thesis: it starts with a brief introduction on central nervous system, on cortical functions, then it presents more deeply associations areas, which are the main target of our study. Furthermore, it tries to explain why studies on animal models are necessary to understand mechanism at a cellular level, that could not be addressed on any other way. In the second part of the chapter, basics on electrophysiology and cellular communication are presented, together with traditional neuronal data analysis methods. The third chapter is intended to be a helpful resource for future works in the laboratory: it presents the hardware used for experimental sessions, how to control animal behaviour during the experiments by means of C routines and a software, and how to present visual stimuli on a screen. The forth chapter is the main core of the research project and the thesis. In the methods, experimental paradigms, visual stimuli and data analysis are presented. In the results, cellular response of area PEc to visual stimuli in motion combined with different eye positions are shown. In brief, this study led to the identification of different cellular behaviour in relation to focus of expansion (the direction of motion given by the optic flow pattern) and eye position. The originality and importance of the results are pointed out in the conclusions: this is the first study aimed to investigate perception of motion in this particular cortical area. In the last paragraph, a neuronal network model is presented: the aim is simulating cellular pre-saccadic and post-saccadic response of neuron in area PEc, during eye movement tasks. The same data presented in chapter four, are further analysed in chapter fifth. The analysis started from the observation of the neuronal responses during 1s time period in which the visual stimulation was the same. It was clear that cells activities showed oscillations in time, that had been neglected by the previous analysis based on mean firing frequency. Results distinguished two cellular behaviour by their response characteristics: some neurons showed oscillations that changed depending on eye and optic flow position, while others kept the same oscillations characteristics independent of the stimulus. The last chapter discusses the results of the research project, comments the originality and interdisciplinary of the study and proposes some future developments.
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The objective of the Ph.D. thesis is to put the basis of an all-embracing link analysis procedure that may form a general reference scheme for the future state-of-the-art of RF/microwave link design: it is basically meant as a circuit-level simulation of an entire radio link, with – generally multiple – transmitting and receiving antennas examined by EM analysis. In this way the influence of mutual couplings on the frequency-dependent near-field and far-field performance of each element is fully accounted for. The set of transmitters is treated as a unique nonlinear system loaded by the multiport antenna, and is analyzed by nonlinear circuit techniques. In order to establish the connection between transmitters and receivers, the far-fields incident onto the receivers are evaluated by EM analysis and are combined by extending an available Ray Tracing technique to the link study. EM theory is used to describe the receiving array as a linear active multiport network. Link performances in terms of bit error rate (BER) are eventually verified a posteriori by a fast system-level algorithm. In order to validate the proposed approach, four heterogeneous application contexts are provided. A complete MIMO link design in a realistic propagation scenario is meant to constitute the reference case study. The second one regards the design, optimization and testing of various typologies of rectennas for power generation by common RF sources. Finally, the project and implementation of two typologies of radio identification tags, at X-band and V-band respectively. In all the cases the importance of an exhaustive nonlinear/electromagnetic co-simulation and co-design is demonstrated to be essential for any accurate system performance prediction.
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L’oggetto del lavoro si concentra sull’analisi in chiave giuridica del modello di cooperazione in rete tra le autorità nazionali degli Stati membri nel quadro dello Spazio LSG, allo scopo di valutarne il contributo, le prospettive e il potenziale. La trattazione si suddivide in due parti, precedute da una breve premessa teorica incentrata sull’analisi della nozione di rete e la sua valenza giuridica. La prima parte ricostruisce il percorso di maturazione della cooperazione in rete, dando risalto tanto ai fattori di ordine congiunturale quanto ai fattori giuridici e d’ordine strutturale che sono alla base del processo di retificazione dei settori giustizia e sicurezza. In particolare, vengono elaborati taluni rilievi critici, concernenti l’operatività degli strumenti giuridici che attuano il principio di mutuo riconoscimento e di quelli che danno applicazione al principio di disponibilità delle informazioni. Ciò allo scopo di evidenziare gli ostacoli che, di frequente, impediscono il buon esito delle procedure di cooperazione e di comprendere le potenzialità e le criticità derivanti dall’utilizzo della rete rispetto alla concreta applicazione di tali procedure. La seconda parte si focalizza sull’analisi delle principali reti attive in materia di giustizia e sicurezza, con particolare attenzione ai rispettivi meccanismi di funzionamento. La trattazione si suddivide in due distinte sezioni che si concentrano sulle a) reti che operano a supporto dell’applicazione delle procedure di assistenza giudiziaria e degli strumenti di mutuo riconoscimento e sulle b) reti che operano nel settore della cooperazione informativa e agevolano lo scambio di informazioni operative e tecniche nelle azioni di prevenzione e lotta alla criminalità - specialmente nel settore della protezione dell’economia lecita. La trattazione si conclude con la ricostruzione delle caratteristiche di un modello di rete europea e del ruolo che questo esercita rispetto all’esercizio delle competenze dell’Unione Europea in materia di giustizia e sicurezza.
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A new hearing therapy based on direct acoustic cochlear stimulation was developed for the treatment of severe to profound mixed hearing loss. The device efficacy was validated in an initial clinical trial with four patients. This semi-implantable investigational device consists of an externally worn audio processor, a percutaneous connector, and an implantable microactuator. The actuator is placed in the mastoid bone, right behind the external auditory canal. It generates vibrations that are directly coupled to the inner ear fluids and that, therefore, bypass the external and the middle ear. The system is able to provide an equivalent sound pressure level of 125 dB over the frequency range between 125 and 8000 Hz. The hermetically sealed actuator is designed to provide maximal output power by keeping its dimensions small enough to enable implantation. A network model is used to simulate the dynamic characteristics of the actuator to adjust its transfer function to the characteristics of the middle ear. The geometry of the different actuator components is optimized using finite-element modeling.
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The concept of elementary vector is generalised to the case where the steady-state space of the metabolic network is not a flux cone but is a general polyhedron due to further inhomogeneous constraints on the flows through some of the reactions. On one hand, this allows to selectively enumerate elementary modes which satisfy certain optimality criteria and this can yield a large computational gain compared with full enumeration. On the other hand, in contrast to the single optimum found by executing a linear program, this enables a comprehensive description of the set of alternate optima often encountered in flux balance analysis. The concepts are illustrated on a metabolic network model of human cardiac mitochondria.
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An experimental setup was designed to visualize water percolation inside the porous transport layer, PTL, of proton exchange membrane, PEM, fuel cells and identify the relevant characterization parameters. In parallel with the observation of the water movement, the injection pressure (pressure required to transport water through the PTL) was measured. A new scaling for the drainage in porous media has been proposed based on the ratio between the input and the dissipated energies during percolation. A proportional dependency was obtained between the energy ratio and a non-dimensional time and this relationship is not dependent on the flow regime; stable displacement or capillary fingering. Experimental results show that for different PTL samples (from different manufacturers) the proportionality is different. The identification of this proportionality allows a unique characterization of PTLs with respect to water transport. This scaling has relevance in porous media flows ranging far beyond fuel cells. In parallel with the experimental analysis, a two-dimensional numerical model was developed in order to simulate the phenomena observed in the experiments. The stochastic nature of the pore size distribution, the role of the PTL wettability and morphology properties on the water transport were analyzed. The effect of a second porous layer placed between the porous transport layer and the catalyst layer called microporous layer, MPL, was also studied. It was found that the presence of the MPL significantly reduced the water content on the PTL by enhancing fingering formation. Moreover, the presence of small defects (cracks) within the MPL was shown to enhance water management. Finally, a corroboration of the numerical simulation was carried out. A threedimensional version of the network model was developed mimicking the experimental conditions. The morphology and wettability of the PTL are tuned to the experiment data by using the new energy scaling of drainage in porous media. Once the fit between numerical and experimental data is obtained, the computational PTL structure can be used in different types of simulations where the conditions are representative of the fuel cell operating conditions.
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This paper examines the adaptations of the writing system in Internet language in mainland China from a sociolinguistic perspective. A comparison is also made of the adaptations in mainland China with those that Su (2003) found in Taiwan. In Computer-Mediated Communication (CMC), writing systems are often adapted to compensate for their inherent inadequacies (such as difficulty in input). Su (2003) investigates the creative uses of the writing system on the electronic bulletin boards (BBS) of two college student organizations in Taipei, Taiwan, and identifies four popular and creative uses of the Chinese writing system: stylized English, stylized Taiwanese-accented Mandarin, stylized Taiwanese, and the recycling of a transliteration alphabet used in elementary education. According to Coupland (2001; cited in Su 2003), stylization is “the knowing deployment of culturally familiar styles and identities that are marked as deviating from those predictably associated with the current speaking context”. Within this framework and drawing on the data in previous publications on Internet language and online sources, this study identifies five types of adaptations in mainland China’s Internet language: stylized Mandarin (e.g., 漂漂 piāopiāo for 漂亮 ‘beautiful’), stylized dialect-accented Mandarin (e.g., 灰常 huīcháng for 非常 ‘very much’), stylized English (e.g., 伊妹儿 yīmèier for ‘email’), stylized initials (e.g., bt 变态 biàntài for ‘abnormal’; pk, short form for ‘player kill’), and stylized numbers (e.g., 9494 jiùshi jiùshi 就是就是 ‘that is it’). The Internet community is composed of highly mobile individuals and thus forms a weak-tie social network. According to Milroy and Milroy (1992), a social network with weak ties is often where language innovation takes place. Adaptations of the Chinese writing system in Internet language provide interesting evidence for the innovations within a weak-tie social network. Our comparison of adaptations in mainland China and Taiwan shows that, in maximizing the effectiveness and functionality of their communication, participants of Internet communication are confronted with different language resources and situations, including differences in Romanization systems, English proficiency level, and attitudes towards English usage. As argued by Milroy and Milroy (1992), a weak-tie social network model can bridge the social class and social network. In the Internet community, the degree of diversity of the stylized linguistic varieties indexes the virtual and/or social status of its participants: the more diversified one’s Internet language is, the higher is his/her virtual and/or social status.
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Neuropathic pain caused by peripheral nerve injury is a debilitating neurological condition of high clinical relevance. On the cellular level, the elevated pain sensitivity is induced by plasticity of neuronal function along the pain pathway. Changes in cortical areas involved in pain processing contribute to the development of neuropathic pain. Yet, it remains elusive which plasticity mechanisms occur in cortical circuits. We investigated the properties of neural networks in the anterior cingulate cortex (ACC), a brain region mediating affective responses to noxious stimuli. We performed multiple whole-cell recordings from neurons in layer 5 (L5) of the ACC of adult mice after chronic constriction injury of the sciatic nerve of the left hindpaw and observed a striking loss of connections between excitatory and inhibitory neurons in both directions. In contrast, no significant changes in synaptic efficacy in the remaining connected pairs were found. These changes were reflected on the network level by a decrease in the mEPSC and mIPSC frequency. Additionally, nerve injury resulted in a potentiation of the intrinsic excitability of pyramidal neurons, whereas the cellular properties of interneurons were unchanged. Our set of experimental parameters allowed constructing a neuronal network model of L5 in the ACC, revealing that the modification of inhibitory connectivity had the most profound effect on increased network activity. Thus, our combined experimental and modeling approach suggests that cortical disinhibition is a fundamental pathological modification associated with peripheral nerve damage. These changes at the cortical network level might therefore contribute to the neuropathic pain condition.
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I developed a new model for estimating annual production-to-biomass ratio P/B and production P of macrobenthic populations in marine and freshwater habitats. Self-learning artificial neural networks (ANN) were used to model the relationships between P/B and twenty easy-to-measure abiotic and biotic parameters in 1252 data sets of population production. Based on log-transformed data, the final predictive model estimates log(P/B) with reasonable accuracy and precision (r2 = 0.801; residual mean square RMS = 0.083). Body mass and water temperature contributed most to the explanatory power of the model. However, as with all least squares models using nonlinearly transformed data, back-transformation to natural scale introduces a bias in the model predictions, i.e., an underestimation of P/B (and P). When estimating production of assemblages of populations by adding up population estimates, accuracy decreases but precision increases with the number of populations in the assemblage.
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Las limitaciones de las tecnologías de red actuales, identificadas en la Agencia de Proyectos de Investigación Avanzados para la Defensa (DARPA) durante 1995, han originado recientemente una propuesta de modelo de red denominado Redes Activas. En este modelo, los nodos proporcionan un entorno de ejecución sobre el que se ejecuta el código asociado a cada paquete. El objetivo es disponer de una tecnología de red que permita que nuevos servicios de red sean desarrollados e instalados rápidamente sin modificar los nodos de la red. Un servicio de red que se puede beneficiar de esta tecnología es la transmisión de datos en multipunto con diferentes grados fiabilidad. Las propuestas actuales de servicios de multipunto fiable proporcionan una solución específica para cada clase de aplicaciones, y los protocolos existentes extremo a extremo sufren de limitaciones técnicas relacionadas con una fiabilidad limitada, y con la ausencia de mecanismos de control de congestión efectivos. Esta tesis realiza propuestas originales conducentes a solucionar parte de las limitaciones actuales en el ámbito de Redes Activas y multipunto fiable con control de congestión. En primer lugar, se especificará un servicio genérico de multipunto fiable que, basándose en los requisitos de una serie de aplicaciones consideradas relevantes, proporcione diferentes clases de sesiones y grados de fiabilidad. Partiendo de la definición del servicio genérico especificado, se diseñará un protocolo de comunicaciones sobre la tecnología de Redes Activas que proporcione dicho servicio. El protocolo diseñado estará dotado de un mecanismo de control de congestión para que la fuente ajuste dinámicamente el tráfico inyectado a las condiciones de carga de la red. En esta tesis se pretende también profundizar en el estudio y análisis de la tecnología de Redes Activas, experimentando con dicha tecnología para proporcionar una realimentación a sus diseñadores. Dicha experimentación se realizará en tres ámbitos: el de los servicios y protocolos que puede soportar, el del modelo y arquitectura de las Redes Activas y el de las plataformas de ejecución disponibles. Como aportación adicional de este trabajo, se validarán los objetivos anteriores mediante una implementación piloto de las entidades de protocolo y de su interfaz de servicio sobre uno de los entornos de ejecución disponibles. Abstract The limitations of current networking technologies identified in the Defense Advance Research Projects Agency (DARPA) along 1995 have led to a recent proposal of a new network model called Active Networks. In this model, the nodes provide an execution environment over which the code used to process each packet is executed. The objective is a network technology that allows the fast design and deployment of new network services without requiring the modification of the network nodes. One network service that could benefit from this technology is the transmission of multicast data with different types of loss tolerance. The current proposals for reliable multicast services provide specific solutions for each application class, and existing end-to-end protocols suffer from technical drawbacks related to limited reliability and lack of an effective congestion control mechanism. This thesis contains original proposals that aim to solve part of the current drawbacks in the scope of Active Networks and reliable multicast with congestion control. Firstly, a generic reliable multicast network service will be specified. This service will be designed from the requirements of a relevant set of applications, and will provide different session classes and different types of reliability. Then, a network protocol based on Active Network technology will be designed such that it provides the specified network service. This protocol will incorporate a congestion control mechanism capable of performing an automatic adjustment of the traffic injected by the source to the available network capacity. This thesis will also contribute to a deeper study and analysis of Active Network technology, by experimenting with the technology in order to provide feedback to its designers. This experimentation will be done attending to three different scopes: support of Active Network for services and protocols, Active Network model and architecture, and currently available Active Network execution environments. As an additional contribution of this work, the previous objectives will be validated through a prototype implementation of the protocol entities and the service interface based on one of the current execution environments.
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The Self-OrganizingMap (SOM) is a neural network model that performs an ordered projection of a high dimensional input space in a low-dimensional topological structure. The process in which such mapping is formed is defined by the SOM algorithm, which is a competitive, unsupervised and nonparametric method, since it does not make any assumption about the input data distribution. The feature maps provided by this algorithm have been successfully applied for vector quantization, clustering and high dimensional data visualization processes. However, the initialization of the network topology and the selection of the SOM training parameters are two difficult tasks caused by the unknown distribution of the input signals. A misconfiguration of these parameters can generate a feature map of low-quality, so it is necessary to have some measure of the degree of adaptation of the SOM network to the input data model. The topologypreservation is the most common concept used to implement this measure. Several qualitative and quantitative methods have been proposed for measuring the degree of SOM topologypreservation, particularly using Kohonen's model. In this work, two methods for measuring the topologypreservation of the Growing Cell Structures (GCSs) model are proposed: the topographic function and the topology preserving map