993 resultados para Sistemi multi-agente, TuCSoN, ReSpecT, coordinazione semantica
Resumo:
El uso de aritmética de punto fijo es una opción de diseño muy extendida en sistemas con fuertes restricciones de área, consumo o rendimiento. Para producir implementaciones donde los costes se minimicen sin impactar negativamente en la precisión de los resultados debemos llevar a cabo una asignación cuidadosa de anchuras de palabra. Encontrar la combinación óptima de anchuras de palabra en coma fija para un sistema dado es un problema combinatorio NP-hard al que los diseñadores dedican entre el 25 y el 50 % del ciclo de diseño. Las plataformas hardware reconfigurables, como son las FPGAs, también se benefician de las ventajas que ofrece la aritmética de coma fija, ya que éstas compensan las frecuencias de reloj más bajas y el uso más ineficiente del hardware que hacen estas plataformas respecto a los ASICs. A medida que las FPGAs se popularizan para su uso en computación científica los diseños aumentan de tamaño y complejidad hasta llegar al punto en que no pueden ser manejados eficientemente por las técnicas actuales de modelado de señal y ruido de cuantificación y de optimización de anchura de palabra. En esta Tesis Doctoral exploramos distintos aspectos del problema de la cuantificación y presentamos nuevas metodologías para cada uno de ellos: Las técnicas basadas en extensiones de intervalos han permitido obtener modelos de propagación de señal y ruido de cuantificación muy precisos en sistemas con operaciones no lineales. Nosotros llevamos esta aproximación un paso más allá introduciendo elementos de Multi-Element Generalized Polynomial Chaos (ME-gPC) y combinándolos con una técnica moderna basada en Modified Affine Arithmetic (MAA) estadístico para así modelar sistemas que contienen estructuras de control de flujo. Nuestra metodología genera los distintos caminos de ejecución automáticamente, determina las regiones del dominio de entrada que ejercitarán cada uno de ellos y extrae los momentos estadísticos del sistema a partir de dichas soluciones parciales. Utilizamos esta técnica para estimar tanto el rango dinámico como el ruido de redondeo en sistemas con las ya mencionadas estructuras de control de flujo y mostramos la precisión de nuestra aproximación, que en determinados casos de uso con operadores no lineales llega a tener tan solo una desviación del 0.04% con respecto a los valores de referencia obtenidos mediante simulación. Un inconveniente conocido de las técnicas basadas en extensiones de intervalos es la explosión combinacional de términos a medida que el tamaño de los sistemas a estudiar crece, lo cual conlleva problemas de escalabilidad. Para afrontar este problema presen tamos una técnica de inyección de ruidos agrupados que hace grupos con las señales del sistema, introduce las fuentes de ruido para cada uno de los grupos por separado y finalmente combina los resultados de cada uno de ellos. De esta forma, el número de fuentes de ruido queda controlado en cada momento y, debido a ello, la explosión combinatoria se minimiza. También presentamos un algoritmo de particionado multi-vía destinado a minimizar la desviación de los resultados a causa de la pérdida de correlación entre términos de ruido con el objetivo de mantener los resultados tan precisos como sea posible. La presente Tesis Doctoral también aborda el desarrollo de metodologías de optimización de anchura de palabra basadas en simulaciones de Monte-Cario que se ejecuten en tiempos razonables. Para ello presentamos dos nuevas técnicas que exploran la reducción del tiempo de ejecución desde distintos ángulos: En primer lugar, el método interpolativo aplica un interpolador sencillo pero preciso para estimar la sensibilidad de cada señal, y que es usado después durante la etapa de optimización. En segundo lugar, el método incremental gira en torno al hecho de que, aunque es estrictamente necesario mantener un intervalo de confianza dado para los resultados finales de nuestra búsqueda, podemos emplear niveles de confianza más relajados, lo cual deriva en un menor número de pruebas por simulación, en las etapas iniciales de la búsqueda, cuando todavía estamos lejos de las soluciones optimizadas. Mediante estas dos aproximaciones demostramos que podemos acelerar el tiempo de ejecución de los algoritmos clásicos de búsqueda voraz en factores de hasta x240 para problemas de tamaño pequeño/mediano. Finalmente, este libro presenta HOPLITE, una infraestructura de cuantificación automatizada, flexible y modular que incluye la implementación de las técnicas anteriores y se proporciona de forma pública. Su objetivo es ofrecer a desabolladores e investigadores un entorno común para prototipar y verificar nuevas metodologías de cuantificación de forma sencilla. Describimos el flujo de trabajo, justificamos las decisiones de diseño tomadas, explicamos su API pública y hacemos una demostración paso a paso de su funcionamiento. Además mostramos, a través de un ejemplo sencillo, la forma en que conectar nuevas extensiones a la herramienta con las interfaces ya existentes para poder así expandir y mejorar las capacidades de HOPLITE. ABSTRACT Using fixed-point arithmetic is one of the most common design choices for systems where area, power or throughput are heavily constrained. In order to produce implementations where the cost is minimized without negatively impacting the accuracy of the results, a careful assignment of word-lengths is required. The problem of finding the optimal combination of fixed-point word-lengths for a given system is a combinatorial NP-hard problem to which developers devote between 25 and 50% of the design-cycle time. Reconfigurable hardware platforms such as FPGAs also benefit of the advantages of fixed-point arithmetic, as it compensates for the slower clock frequencies and less efficient area utilization of the hardware platform with respect to ASICs. As FPGAs become commonly used for scientific computation, designs constantly grow larger and more complex, up to the point where they cannot be handled efficiently by current signal and quantization noise modelling and word-length optimization methodologies. In this Ph.D. Thesis we explore different aspects of the quantization problem and we present new methodologies for each of them: The techniques based on extensions of intervals have allowed to obtain accurate models of the signal and quantization noise propagation in systems with non-linear operations. We take this approach a step further by introducing elements of MultiElement Generalized Polynomial Chaos (ME-gPC) and combining them with an stateof- the-art Statistical Modified Affine Arithmetic (MAA) based methodology in order to model systems that contain control-flow structures. Our methodology produces the different execution paths automatically, determines the regions of the input domain that will exercise them, and extracts the system statistical moments from the partial results. We use this technique to estimate both the dynamic range and the round-off noise in systems with the aforementioned control-flow structures. We show the good accuracy of our approach, which in some case studies with non-linear operators shows a 0.04 % deviation respect to the simulation-based reference values. A known drawback of the techniques based on extensions of intervals is the combinatorial explosion of terms as the size of the targeted systems grows, which leads to scalability problems. To address this issue we present a clustered noise injection technique that groups the signals in the system, introduces the noise terms in each group independently and then combines the results at the end. In this way, the number of noise sources in the system at a given time is controlled and, because of this, the combinato rial explosion is minimized. We also present a multi-way partitioning algorithm aimed at minimizing the deviation of the results due to the loss of correlation between noise terms, in order to keep the results as accurate as possible. This Ph.D. Thesis also covers the development of methodologies for word-length optimization based on Monte-Carlo simulations in reasonable times. We do so by presenting two novel techniques that explore the reduction of the execution times approaching the problem in two different ways: First, the interpolative method applies a simple but precise interpolator to estimate the sensitivity of each signal, which is later used to guide the optimization effort. Second, the incremental method revolves on the fact that, although we strictly need to guarantee a certain confidence level in the simulations for the final results of the optimization process, we can do it with more relaxed levels, which in turn implies using a considerably smaller amount of samples, in the initial stages of the process, when we are still far from the optimized solution. Through these two approaches we demonstrate that the execution time of classical greedy techniques can be accelerated by factors of up to ×240 for small/medium sized problems. Finally, this book introduces HOPLITE, an automated, flexible and modular framework for quantization that includes the implementation of the previous techniques and is provided for public access. The aim is to offer a common ground for developers and researches for prototyping and verifying new techniques for system modelling and word-length optimization easily. We describe its work flow, justifying the taken design decisions, explain its public API and we do a step-by-step demonstration of its execution. We also show, through an example, the way new extensions to the flow should be connected to the existing interfaces in order to expand and improve the capabilities of HOPLITE.
Resumo:
Current arrangements for multi-national company taxation in EU are plagued by severe conceptual and administrative problems, leading to high compliance costs, considerable uncertainty and ample room for abuse. Integration is amplifying these difficulties. There are two possible approaches in designing an efficient trans-border corporate tax system for the European Union. The first is to consolidate the EU-wide operations of MNEs, using an agreed common base as the reference variable, and then to apportion this total tax base using some presumptive indicators of activity in each tax jurisdiction – hence, implicitly, of the likely benefits stemming from each location. The apportionment formula should respect requisites of neutrality between productive factors and forms of corporate financing. A radically different approach is also available that offers considerable advantages in terms of efficiency, simplicity and decentralisation, including full administrative autonomy of national tax authorities. It entails abandoning corporate income as the relevant tax base and taxing at a moderate rate some agreed measure of business activity such as company value added, sales or employment. These are the variables usually considered in formula apportionment, but they would apply directly without having first to go through the complications of EU-wide consolidation based on a common-base definition. Reference to a broad base, with no exemptions or deductions, would allow to set low statutory rates.
Resumo:
Online geographic information systems provide the means to extract a subset of desired spatial information from a larger remote repository. Data retrieved representing real-world geographic phenomena are then manipulated to suit the specific needs of an end-user. Often this extraction requires the derivation of representations of objects specific to a particular resolution or scale from a single original stored version. Currently standard spatial data handling techniques cannot support the multi-resolution representation of such features in a database. In this paper a methodology to store and retrieve versions of spatial objects at, different resolutions with respect to scale using standard database primitives and SQL is presented. The technique involves heavy fragmentation of spatial features that allows dynamic simplification into scale-specific object representations customised to the display resolution of the end-user's device. Experimental results comparing the new approach to traditional R-Tree indexing and external object simplification reveal the former performs notably better for mobile and WWW applications where client-side resources are limited and retrieved data loads are kept relatively small.
Resumo:
La riduzione dei consumi di combustibili fossili e lo sviluppo di tecnologie per il risparmio energetico sono una questione di centrale importanza sia per l’industria che per la ricerca, a causa dei drastici effetti che le emissioni di inquinanti antropogenici stanno avendo sull’ambiente. Mentre un crescente numero di normative e regolamenti vengono emessi per far fronte a questi problemi, la necessità di sviluppare tecnologie a basse emissioni sta guidando la ricerca in numerosi settori industriali. Nonostante la realizzazione di fonti energetiche rinnovabili sia vista come la soluzione più promettente nel lungo periodo, un’efficace e completa integrazione di tali tecnologie risulta ad oggi impraticabile, a causa sia di vincoli tecnici che della vastità della quota di energia prodotta, attualmente soddisfatta da fonti fossili, che le tecnologie alternative dovrebbero andare a coprire. L’ottimizzazione della produzione e della gestione energetica d’altra parte, associata allo sviluppo di tecnologie per la riduzione dei consumi energetici, rappresenta una soluzione adeguata al problema, che può al contempo essere integrata all’interno di orizzonti temporali più brevi. L’obiettivo della presente tesi è quello di investigare, sviluppare ed applicare un insieme di strumenti numerici per ottimizzare la progettazione e la gestione di processi energetici che possa essere usato per ottenere una riduzione dei consumi di combustibile ed un’ottimizzazione dell’efficienza energetica. La metodologia sviluppata si appoggia su un approccio basato sulla modellazione numerica dei sistemi, che sfrutta le capacità predittive, derivanti da una rappresentazione matematica dei processi, per sviluppare delle strategie di ottimizzazione degli stessi, a fronte di condizioni di impiego realistiche. Nello sviluppo di queste procedure, particolare enfasi viene data alla necessità di derivare delle corrette strategie di gestione, che tengano conto delle dinamiche degli impianti analizzati, per poter ottenere le migliori prestazioni durante l’effettiva fase operativa. Durante lo sviluppo della tesi il problema dell’ottimizzazione energetica è stato affrontato in riferimento a tre diverse applicazioni tecnologiche. Nella prima di queste è stato considerato un impianto multi-fonte per la soddisfazione della domanda energetica di un edificio ad uso commerciale. Poiché tale sistema utilizza una serie di molteplici tecnologie per la produzione dell’energia termica ed elettrica richiesta dalle utenze, è necessario identificare la corretta strategia di ripartizione dei carichi, in grado di garantire la massima efficienza energetica dell’impianto. Basandosi su un modello semplificato dell’impianto, il problema è stato risolto applicando un algoritmo di Programmazione Dinamica deterministico, e i risultati ottenuti sono stati comparati con quelli derivanti dall’adozione di una più semplice strategia a regole, provando in tal modo i vantaggi connessi all’adozione di una strategia di controllo ottimale. Nella seconda applicazione è stata investigata la progettazione di una soluzione ibrida per il recupero energetico da uno scavatore idraulico. Poiché diversi layout tecnologici per implementare questa soluzione possono essere concepiti e l’introduzione di componenti aggiuntivi necessita di un corretto dimensionamento, è necessario lo sviluppo di una metodologia che permetta di valutare le massime prestazioni ottenibili da ognuna di tali soluzioni alternative. Il confronto fra i diversi layout è stato perciò condotto sulla base delle prestazioni energetiche del macchinario durante un ciclo di scavo standardizzato, stimate grazie all’ausilio di un dettagliato modello dell’impianto. Poiché l’aggiunta di dispositivi per il recupero energetico introduce gradi di libertà addizionali nel sistema, è stato inoltre necessario determinare la strategia di controllo ottimale dei medesimi, al fine di poter valutare le massime prestazioni ottenibili da ciascun layout. Tale problema è stato di nuovo risolto grazie all’ausilio di un algoritmo di Programmazione Dinamica, che sfrutta un modello semplificato del sistema, ideato per lo scopo. Una volta che le prestazioni ottimali per ogni soluzione progettuale sono state determinate, è stato possibile effettuare un equo confronto fra le diverse alternative. Nella terza ed ultima applicazione è stato analizzato un impianto a ciclo Rankine organico (ORC) per il recupero di cascami termici dai gas di scarico di autovetture. Nonostante gli impianti ORC siano potenzialmente in grado di produrre rilevanti incrementi nel risparmio di combustibile di un veicolo, è necessario per il loro corretto funzionamento lo sviluppo di complesse strategie di controllo, che siano in grado di far fronte alla variabilità della fonte di calore per il processo; inoltre, contemporaneamente alla massimizzazione dei risparmi di combustibile, il sistema deve essere mantenuto in condizioni di funzionamento sicure. Per far fronte al problema, un robusto ed efficace modello dell’impianto è stato realizzato, basandosi sulla Moving Boundary Methodology, per la simulazione delle dinamiche di cambio di fase del fluido organico e la stima delle prestazioni dell’impianto. Tale modello è stato in seguito utilizzato per progettare un controllore predittivo (MPC) in grado di stimare i parametri di controllo ottimali per la gestione del sistema durante il funzionamento transitorio. Per la soluzione del corrispondente problema di ottimizzazione dinamica non lineare, un algoritmo basato sulla Particle Swarm Optimization è stato sviluppato. I risultati ottenuti con l’adozione di tale controllore sono stati confrontati con quelli ottenibili da un classico controllore proporzionale integrale (PI), mostrando nuovamente i vantaggi, da un punto di vista energetico, derivanti dall’adozione di una strategia di controllo ottima.
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This paper explores the use of the optimization procedures in SAS/OR software with application to the contemporary logistics distribution network design using an integrated multiple criteria decision making approach. Unlike the traditional optimization techniques, the proposed approach, combining analytic hierarchy process (AHP) and goal programming (GP), considers both quantitative and qualitative factors. In the integrated approach, AHP is used to determine the relative importance weightings or priorities of alternative warehouses with respect to both deliverer oriented and customer oriented criteria. Then, a GP model incorporating the constraints of system, resource, and AHP priority is formulated to select the best set of warehouses without exceeding the limited available resources. To facilitate the use of integrated multiple criteria decision making approach by SAS users, an ORMCDM code was implemented in the SAS programming language. The SAS macro developed in this paper selects the chosen variables from a SAS data file and constructs sets of linear programming models based on the selected GP model. An example is given to illustrate how one could use the code to design the logistics distribution network.
Resumo:
Future high capacity optical links will have to make use of frequent signal regeneration to enable long distance transmission. In this respect, the role of all-optical signal processing becomes increasingly important because of its potential to mitigate signal impairments at low cost and power consumption. More substantial benefits are expected if regeneration is achieved simultaneously on a multiple signal band. Until recently, this had been achieved only for on-off keying modulation formats. However, as in future transmission links the information will be encoded also in the phase for enhancing the spectral efficiency, novel subsystem concepts will be needed for multichannel processing of such advanced signal formats. In this paper we show that phase sensitive amplifiers can be an ideal technology platform for developing such regenerators and we discuss our recent demonstration of the first multi-channel regenerator for phase encoded signals.
Resumo:
Projection of a high-dimensional dataset onto a two-dimensional space is a useful tool to visualise structures and relationships in the dataset. However, a single two-dimensional visualisation may not display all the intrinsic structure. Therefore, hierarchical/multi-level visualisation methods have been used to extract more detailed understanding of the data. Here we propose a multi-level Gaussian process latent variable model (MLGPLVM). MLGPLVM works by segmenting data (with e.g. K-means, Gaussian mixture model or interactive clustering) in the visualisation space and then fitting a visualisation model to each subset. To measure the quality of multi-level visualisation (with respect to parent and child models), metrics such as trustworthiness, continuity, mean relative rank errors, visualisation distance distortion and the negative log-likelihood per point are used. We evaluate the MLGPLVM approach on the ‘Oil Flow’ dataset and a dataset of protein electrostatic potentials for the ‘Major Histocompatibility Complex (MHC) class I’ of humans. In both cases, visual observation and the quantitative quality measures have shown better visualisation at lower levels.
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Digestate from the anaerobic digestion conversion process is widely used as a farm land fertiliser. This study proposes an alternative use as a source of energy. Dried digestate was pyrolysed and the resulting oil was blended with waste cooking oil and butanol (10, 20 and 30 vol.%). The physical and chemical properties of the pyrolysis oil blends were measured and compared with pure fossil diesel and waste cooking oil. The blends were tested in a multi-cylinder indirect injection compression ignition engine.Engine combustion, exhaust gas emissions and performance parameters were measured and compared with pure fossil diesel operation. The ASTM copper corrosion values for 20% and 30% pyrolysis blends were 2c, compared to 1b for fossil diesel. The kinematic viscosities of the blends at 40 C were 5–7 times higher than that of fossil diesel. Digested pyrolysis oil blends produced lower in-cylinder peak pressures than fossil diesel and waste cooking oil operation. The maximum heat release rates of the blends were approximately 8% higher than with fossil diesel. The ignition delay periods of the blends were higher; pyrolysis oil blends started to combust late and once combustion started burnt quicker than fossil diesel. The total burning duration of the 20% and 30% blends were decreased by 12% and 3% compared to fossil diesel. At full engine load, the brake thermal efficiencies of the blends were decreased by about 3–7% when compared to fossil diesel. The pyrolysis blends gave lower smoke levels; at full engine load, smoke level of the 20% blend was 44% lower than fossil diesel. In comparison to fossil diesel and at full load, the brake specific fuel consumption (wt.) of the 30% and 20% blends were approximately 32% and 15% higher. At full engine load, the CO emission of the 20% and 30% blends were decreased by 39% and 66% with respect to the fossil diesel. Blends CO2 emissions were similar to that of fossil diesel; at full engine load, 30% blend produced approximately 5% higher CO2 emission than fossil diesel. The study concludes that on the basis of short term engine experiment up to 30% blend of pyrolysis oil from digestate of arable crops can be used in a compression ignition engine.
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This research has been undertaken to determine how successful multi-organisational enterprise strategy is reliant on the correct type of Enterprise Resource Planning (ERP) information systems being used. However there appears to be a dearth of research as regards strategic alignment between ERP systems development and multi-organisational enterprise governance as guidelines and frameworks to assist practitioners in making decision for multi-organisational collaboration supported by different types of ERP systems are still missing from theoretical and empirical perspectives. This calls for this research which investigates ERP systems development and emerging practices in the management of multi-organisational enterprises (i.e. parts of companies working with parts of other companies to deliver complex product-service systems) and identify how different ERP systems fit into different multi-organisational enterprise structures, in order to achieve sustainable competitive success. An empirical inductive study was conducted using the Grounded Theory-based methodological approach based on successful manufacturing and service companies in the UK and China. This involved an initial pre-study literature review, data collection via 48 semi-structured interviews with 8 companies delivering complex products and services across organisational boundaries whilst adopting ERP systems to support their collaborative business strategies – 4 cases cover printing, semiconductor manufacturing, and parcel distribution industries in the UK and 4 cases cover crane manufacturing, concrete production, and banking industries in China in order to form a set of 29 tentative propositions that have been validated via a questionnaire receiving 116 responses from 16 companies. The research has resulted in the consolidation of the validated propositions into a novel concept referred to as the ‘Dynamic Enterprise Reference Grid for ERP’ (DERG-ERP) which draws from multiple theoretical perspectives. The core of the DERG-ERP concept is a contingency management framework which indicates that different multi-organisational enterprise paradigms and the supporting ERP information systems are not the result of different strategies, but are best considered part of a strategic continuum with the same overall business purpose of multi-organisational cooperation. At different times and circumstances in a partnership lifecycle firms may prefer particular multi-organisational enterprise structures and the use of different types of ERP systems to satisfy business requirements. Thus the DERG-ERP concept helps decision makers in selecting, managing and co-developing the most appropriate multi-organistional enterprise strategy and its corresponding ERP systems by drawing on core competence, expected competitiveness, and information systems strategic capabilities as the main contingency factors. Specifically, this research suggests that traditional ERP(I) systems are associated with Vertically Integrated Enterprise (VIE); whilst ERPIIsystems can be correlated to Extended Enterprise (EE) requirements and ERPIII systems can best support the operations of Virtual Enterprise (VE). The contribution of this thesis is threefold. Firstly, this work contributes to a gap in the extant literature about the best fit between ERP system types and multi-organisational enterprise structure types; and proposes a new contingency framework – the DERG-ERP, which can be used to explain how and why enterprise managers need to change and adapt their ERP information systems in response to changing business and operational requirements. Secondly, with respect to a priori theoretical models, the new DERG-ERP has furthered multi-organisational enterprise management thinking by incorporating information system strategy, rather than purely focusing on strategy, structural, and operational aspects of enterprise design and management. Simultaneously, the DERG-ERP makes theoretical contributions to the current IS Strategy Formulation Model which does not explicitly address multi-organisational enterprise governance. Thirdly, this research clarifies and emphasises the new concept and ideas of future ERP systems (referred to as ERPIII) that are inadequately covered in the extant literature. The novel DERG-ERP concept and its elements have also been applied to 8 empirical cases to serve as a practical guide for ERP vendors, information systems management, and operations managers hoping to grow and sustain their competitive advantage with respect to effective enterprise strategy, enterprise structures, and ERP systems use; referred to in this thesis as the “enterprisation of operations”.
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Market mechanisms are a means by which resources in contention can be allocated between contending parties, both in human economies and those populated by software agents. Designing such mechanisms has traditionally been carried out by hand, and more recently by automation. Assessing these mechanisms typically involves them being evaluated with respect to multiple conflicting objectives, which can often be nonlinear, noisy, and expensive to compute. For typical performance objectives, it is known that designed mechanisms often fall short on being optimal across all objectives simultaneously. However, in all previous automated approaches, either only a single objective is considered, or else the multiple performance objectives are combined into a single objective. In this paper we do not aggregate objectives, instead considering a direct, novel application of multi-objective evolutionary algorithms (MOEAs) to the problem of automated mechanism design. This allows the automatic discovery of trade-offs that such objectives impose on mechanisms. We pose the problem of mechanism design, specifically for the class of linear redistribution mechanisms, as a naturally existing multi-objective optimisation problem. We apply a modified version of NSGA-II in order to design mechanisms within this class, given economically relevant objectives such as welfare and fairness. This application of NSGA-II exposes tradeoffs between objectives, revealing relationships between them that were otherwise unknown for this mechanism class. The understanding of the trade-off gained from the application of MOEAs can thus help practitioners with an insightful application of discovered mechanisms in their respective real/artificial markets.
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In this paper is proposed a model for researching the capability to influence, by selected methods’ groups of compression, to the co-efficient of information security of selected objects’ groups, exposed to selected attacks’ groups. With the help of methods for multi-criteria evaluation are chosen the methods’ groups with the lowest risk with respect to the information security. Recommendations for future investigations are proposed.
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Future high capacity optical links will have to make use of frequent signal regeneration to enable long distance transmission. In this respect, the role of all-optical signal processing becomes increasingly important because of its potential to mitigate signal impairments at low cost and power consumption. More substantial benefits are expected if regeneration is achieved simultaneously on a multiple signal band. Until recently, this had been achieved only for on-off keying modulation formats. However, as in future transmission links the information will be encoded also in the phase for enhancing the spectral efficiency, novel subsystem concepts will be needed for multichannel processing of such advanced signal formats. In this paper we show that phase sensitive amplifiers can be an ideal technology platform for developing such regenerators and we discuss our recent demonstration of the first multi-channel regenerator for phase encoded signals.
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This study was conducted to determine the effects of the Changing Lives Program intervention on troubled adolescents' feelings of personal expressiveness, believed to be one domain of positive identity development. Forty-three intervention and twenty nonintervention comparison control participants were given a battery of pre-, post-, and follow-up assessments including the Personally Expressive Questionnaire (Waterman, 1995), which was used to derive participants' feelings of personal expressiveness scores. Using Repeated Measures Analysis of Multivariate Analysis (RMANOVA), a significant four-way interaction of Time X Condition X Gender X Ethnicity was found relative to the Control, Roy's Ɵ = .166, F(2,47) = 3.899, p < .027 indicating that intervention participants' feelings of personal expressiveness did increase significantly relative to the control group. Furthermore, the results suggest differential outcomes based on ethnicity, suggesting the need for future study with respect to specificity of effects and mechanisms of identity formation in differing ethnic subgroups.
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L'obiettivo del kinodynamic motion planning è quello di determinare una sequenza di input di controllo per guidare un agente da uno stato iniziale ad uno finale, rispettando la dinamica del corpo e i vincoli fisici. In questa tesi sono presentate diverse versioni di algoritmi basati su Rapidly-exploring Random Tree in grado di risolvere questo tipo di problema. In particolare è preso in considerazione il caso di un sistema non lineare con vincoli non olonomici, rappresentativo del rover in dotazione al progetto europeo SHERPA. La qualità degli approcci proposti è inoltre provata con alcuni test di navigazione, in ambiente simulato, confrontando gli algoritmi proposti con alcuni presi nella letteratura di riferimento.
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The present paper describes a system for the construction of visual maps ("mosaics") and motion estimation for a set of AUVs (Autonomous Underwater Vehicles). Robots are equipped with down-looking camera which is used to estimate their motion with respect to the seafloor and built an online mosaic. As the mosaic increases in size, a systematic bias is introduced in its alignment, resulting in an erroneous output. The theoretical concepts associated with the use of an Augmented State Kalman Filter (ASKF) were applied to optimally estimate both visual map and the fleet position.