992 resultados para HETEROGENEOUS ENVIRONMENTS


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A web service is a collection of industry standards to enable reusability of services and interoperability of heterogeneous applications. The UMLS Knowledge Source (UMLSKS) Server provides remote access to the UMLSKS and related resources. We propose a Web Services Architecture that encapsulates UMLSKS-API and makes it available in distributed and heterogeneous environments. This is the first step towards intelligent and automatic UMLS services discovery and invocation by computer systems in distributed environments such as web.

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Most empirical and theoretical studies have shown that sex increases the rate of evolution, although evidence of sex constraining genomic and epigenetic variation and slowing down evolution also exists. Faster rates with sex have been attributed to new gene combinations, removal of deleterious mutations, and adaptation to heterogeneous environments. Slower rates with sex have been attributed to removal of major genetic rearrangements, the cost of finding a mate, vulnerability to predation, and exposure to sexually transmitted diseases. Whether sex speeds or slows evolution, the connection between reproductive mode, the evolutionary rate, and species diversity remains largely unexplored. Here we present a spatially explicit model of ecological and evolutionary dynamics based on DNA sequence change to study the connection between mutation, speciation, and the resulting biodiversity in sexual and asexual populations. We show that faster speciation can decrease the abundance of newly formed species and thus decrease long-term biodiversity. In this way, sex can reduce diversity relative to asexual populations, because it leads to a higher rate of production of new species, but with lower abundances. Our results show that reproductive mode and the mechanisms underlying it can alter the link between mutation, evolutionary rate, speciation and biodiversity and we suggest that a high rate of evolution may not be required to yield high biodiversity.

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1. Positive interactions among plants can increase species richness by relaxing environmental filters and providing more heterogeneous environments. However, it is not known if facilitation could affect coexistence through other mechanisms. Most studies on plant coexistence focus on negative frequency-dependent mechanisms (decreasing the abundance of common species); here, we test if facilitation can enhance coexistence by giving species an advantage when rare. 2. To test our hypothesis, we used a global data set from drylands and alpine environments and measured the intensity of facilitation (based on co-occurrences with nurse plants) for 48 species present in at least 4 different sites and with a range of abundances in the field. We compared these results with the degree of facilitation experienced by species which are globally rare or common (according to the IUCN Red List), and with a larger data base including over 1200 co-occurrences of target species with their nurses. 3. Facilitation was stronger for rare species (i.e. those having lower local abundances or considered endangered by the IUCN) than for common species, and strongly decreased with the abundance of the facilitated species. These results hold after accounting for the distance of each species from its ecological optimum (i.e. the degree of functional stress it experiences). 4. Synthesis. Our results highlight that nurse plants not only increase the number of species able to colonize a given site, but may also promote species coexistence by preventing the local extinction of rare species. Our findings illustrate the role that nurse plants play in conserving endangered species and link the relationship between facilitation and diversity with coexistence theory. As such, they provide further mechanistic understanding on how facilitation maintains plant diversity.

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Theoretical models predict lognormal species abundance distributions (SADs) in stable and productive environments, with log-series SADs in less stable, dispersal driven communities. We studied patterns of relative species abundances of perennial vascular plants in global dryland communities to: (i) assess the influence of climatic and soil characteristics on the observed SADs, (ii) infer how environmental variability influences relative abundances, and (iii) evaluate how colonisation dynamics and environmental filters shape abundance distributions. We fitted lognormal and log-series SADs to 91 sites containing at least 15 species of perennial vascular plants. The dependence of species relative abundances on soil and climate variables was assessed using general linear models. Irrespective of habitat type and latitude, the majority of the SADs (70.3%) were best described by a lognormal distribution. Lognormal SADs were associated with low annual precipitation, higher aridity, high soil carbon content, and higher variability of climate variables and soil nitrate. Our results do not corroborate models predicting the prevalence of log-series SADs in dryland communities. As lognormal SADs were particularly associated with sites with drier conditions and a higher environmental variability, we reject models linking lognormality to environmental stability and high productivity conditions. Instead our results point to the prevalence of lognormal SADs in heterogeneous environments, allowing for more evenly distributed plant communities, or in stressful ecosystems, which are generally shaped by strong habitat filters and limited colonisation. This suggests that drylands may be resilient to environmental changes because the many species with intermediate relative abundances could take over ecosystem functioning if the environment becomes suboptimal for dominant species.

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La seguridad en redes informáticas es un área que ha sido ampliamente estudiada y objeto de una extensa investigación en los últimos años. Debido al continuo incremento en la complejidad y sofisticación de los ataques informáticos, el aumento de su velocidad de difusión, y la lentitud de reacción frente a las intrusiones existente en la actualidad, se hace patente la necesidad de mecanismos de detección y respuesta a intrusiones, que detecten y además sean capaces de bloquear el ataque, y mitiguen su impacto en la medida de lo posible. Los Sistemas de Detección de Intrusiones o IDSs son tecnologías bastante maduras cuyo objetivo es detectar cualquier comportamiento malicioso que ocurra en las redes. Estos sistemas han evolucionado rápidamente en los últimos años convirtiéndose en herramientas muy maduras basadas en diferentes paradigmas, que mejoran su capacidad de detección y le otorgan un alto nivel de fiabilidad. Por otra parte, un Sistema de Respuesta a Intrusiones (IRS) es un componente de seguridad que puede estar presente en la arquitectura de una red informática, capaz de reaccionar frente a los incidentes detectados por un Sistema de Detección de Intrusiones (IDS). Por desgracia, esta tecnología no ha evolucionado al mismo ritmo que los IDSs, y la reacción contra los ataques detectados es lenta y básica, y los sistemas presentan problemas para ejecutar respuestas de forma automática. Esta tesis doctoral trata de hacer frente al problema existente en la reacción automática frente a intrusiones, mediante el uso de ontologías, lenguajes formales de especificación de comportamiento y razonadores semánticos como base de la arquitectura del sistema de un sistema de respuesta automática frente a intrusiones o AIRS. El objetivo de la aproximación es aprovechar las ventajas de las ontologías en entornos heterogéneos, además de su capacidad para especificar comportamiento sobre los objetos que representan los elementos del dominio modelado. Esta capacidad para especificar comportamiento será de gran utilidad para que el AIRS infiera la respuesta óptima frente a una intrusión en el menor tiempo posible. Abstract Security in networks is an area that has been widely studied and has been the focus of extensive research over the past few years. The number of security events is increasing, and they are each time more sophisticated, and quickly spread, and slow reaction against intrusions, there is a need for intrusion detection and response systems to dynamically adapt so as to better detect and respond to attacks in order to mitigate them or reduce their impact. Intrusion Detection Systems (IDSs) are mature technologies whose aim is detecting malicious behavior in the networks. These systems have quickly evolved and there are now very mature tools based on different paradigms (statistic anomaly-based, signature-based and hybrids) with a high level of reliability. On the other hand, Intrusion Response System (IRS) is a security technology able to react against the intrusions detected by IDS. Unfortunately, the state of the art in IRSs is not as mature as with IDSs. The reaction against intrusions is slow and simple, and these systems have difficulty detecting intrusions in real time and triggering automated responses. This dissertation is to address the existing problem in automated reactions against intrusions using ontologies, formal behaviour languages and semantic reasoners as the basis of the architecture of an automated intrusion response systems or AIRS. The aim is to take advantage of ontologies in heterogeneous environments, in addition to its ability to specify behavior of objects representing the elements of the modeling domain. This ability to specify behavior will be useful for the AIRS in the inference process of the optimum response against an intrusion, as quickly as possible.

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La presente tesis doctoral contribuye al problema del diagnóstico autonómico de fallos en redes de telecomunicación. En las redes de telecomunicación actuales, las operadoras realizan tareas de diagnóstico de forma manual. Dichas operaciones deben ser llevadas a cabo por ingenieros altamente cualificados que cada vez tienen más dificultades a la hora de gestionar debidamente el crecimiento exponencial de la red tanto en tamaño, complejidad y heterogeneidad. Además, el advenimiento del Internet del Futuro hace que la demanda de sistemas que simplifiquen y automaticen la gestión de las redes de telecomunicación se haya incrementado en los últimos años. Para extraer el conocimiento necesario para desarrollar las soluciones propuestas y facilitar su adopción por los operadores de red, se propone una metodología de pruebas de aceptación para sistemas multi-agente enfocada en simplificar la comunicación entre los diferentes grupos de trabajo involucrados en todo proyecto de desarrollo software: clientes y desarrolladores. Para contribuir a la solución del problema del diagnóstico autonómico de fallos, se propone una arquitectura de agente capaz de diagnosticar fallos en redes de telecomunicación de manera autónoma. Dicha arquitectura extiende el modelo de agente Belief-Desire- Intention (BDI) con diferentes modelos de diagnóstico que gestionan las diferentes sub-tareas del proceso. La arquitectura propuesta combina diferentes técnicas de razonamiento para alcanzar su propósito gracias a un modelo estructural de la red, que usa razonamiento basado en ontologías, y un modelo causal de fallos, que usa razonamiento Bayesiano para gestionar debidamente la incertidumbre del proceso de diagnóstico. Para asegurar la adecuación de la arquitectura propuesta en situaciones de gran complejidad y heterogeneidad, se propone un marco de argumentación que permite diagnosticar a agentes que estén ejecutando en dominios federados. Para la aplicación de este marco en un sistema multi-agente, se propone un protocolo de coordinación en el que los agentes dialogan hasta alcanzar una conclusión para un caso de diagnóstico concreto. Como trabajos futuros, se consideran la extensión de la arquitectura para abordar otros problemas de gestión como el auto-descubrimiento o la auto-optimización, el uso de técnicas de reputación dentro del marco de argumentación para mejorar la extensibilidad del sistema de diagnóstico en entornos federados y la aplicación de las arquitecturas propuestas en las arquitecturas de red emergentes, como SDN, que ofrecen mayor capacidad de interacción con la red. ABSTRACT This PhD thesis contributes to the problem of autonomic fault diagnosis of telecommunication networks. Nowadays, in telecommunication networks, operators perform manual diagnosis tasks. Those operations must be carried out by high skilled network engineers which have increasing difficulties to properly manage the growing of those networks, both in size, complexity and heterogeneity. Moreover, the advent of the Future Internet makes the demand of solutions which simplifies and automates the telecommunication network management has been increased in recent years. To collect the domain knowledge required to developed the proposed solutions and to simplify its adoption by the operators, an agile testing methodology is defined for multiagent systems. This methodology is focused on the communication gap between the different work groups involved in any software development project, stakeholders and developers. To contribute to overcoming the problem of autonomic fault diagnosis, an agent architecture for fault diagnosis of telecommunication networks is defined. That architecture extends the Belief-Desire-Intention (BDI) agent model with different diagnostic models which handle the different subtasks of the process. The proposed architecture combines different reasoning techniques to achieve its objective using a structural model of the network, which uses ontology-based reasoning, and a causal model, which uses Bayesian reasoning to properly handle the uncertainty of the diagnosis process. To ensure the suitability of the proposed architecture in complex and heterogeneous environments, an argumentation framework is defined. This framework allows agents to perform fault diagnosis in federated domains. To apply this framework in a multi-agent system, a coordination protocol is defined. This protocol is used by agents to dialogue until a reliable conclusion for a specific diagnosis case is reached. Future work comprises the further extension of the agent architecture to approach other managements problems, such as self-discovery or self-optimisation; the application of reputation techniques in the argumentation framework to improve the extensibility of the diagnostic system in federated domains; and the application of the proposed agent architecture in emergent networking architectures, such as SDN, which offers new capabilities of control for the network.

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Information technologies (IT) currently represent 2% of CO2 emissions. In recent years, a wide variety of IT solutions have been proposed, focused on increasing the energy efficiency of network data centers. Monitoring is one of the fundamental pillars of these systems, providing the information necessary for adequate decision making. However, today’s monitoring systems (MSs) are partial, specific and highly coupled solutions. This study proposes a model for monitoring data centers that serves as a basis for energy saving systems, offered as a value-added service embedded in a device with low cost and power consumption. The proposal is general in nature, comprehensive, scalable and focused on heterogeneous environments, and it allows quick adaptation to the needs of changing and dynamic environments. Further, a prototype of the system has been implemented in several devices, which has allowed validation of the proposal in addition to identification of the minimum hardware profile required to support the model.

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Next generation networks are characterized by ever increasing complexity, intelligence, heterogeneous technologies and increasing user expectations. Telecommunication networks in particular have become truly global, consisting of a variety of national and regional networks, both wired and wireless. Consequently, the management of telecommunication networks is becoming increasingly complex. In addition, network security and reliability requirements require additional overheads which increase the size of the data records. This in turn causes acute network traffic congestions. There is no single network management methodology to control the various requirements of today's networks, and provides a good level of Quality of Service (QoS), and network security. Therefore, an integrated approach is needed in which a combination of methodologies can provide solutions and answers to network events (which cause severe congestions and compromise the quality of service and security). The proposed solution focused on a systematic approach to design a network management system based upon the recent advances in the mobile agent technologies. This solution has provided a new traffic management system for telecommunication networks that is capable of (1) reducing the network traffic load (thus reducing traffic congestion), (2) overcoming existing network latency, (3) adapting dynamically to the traffic load of the system, (4) operating in heterogeneous environments with improved security, and (5) having robust and fault tolerance behavior. This solution has solved several key challenges in the development of network management for telecommunication networks using mobile agents. We have designed several types of agents, whose interactions will allow performing some complex management actions, and integrating them. Our solution is decentralized to eliminate excessive bandwidth usage and at the same time has extended the capabilities of the Simple Network Management Protocol (SNMP). Our solution is fully compatible with the existing standards.

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Two-photon initiated photo-isomerization of an azobenzene moiety adsorbed on silver nanoparticles (Ag NPs) is demonstrated. The azobenzene is linked to a materials-binding peptide that brings it into intimate contact with the Ag NP surface, producing a dramatic enhancement of its two-photon absorbance. An integrated modeling approach, combining advanced conformational sampling with Quantum Mechanics/Capacitance Molecular Mechanics and response theory, shows that charge transfer and image charges in the Ag NP generate local fields that enhance two-photon absorption of the cis isomer, but not the trans isomer, of adsorbed molecules. Moreover, dramatic local field enhancement is expected near the localized surface plasmon resonance (LSPR) wavelength, and the LSPR band of the Ag NPs overlaps the azobenzene absorbance that triggers cis to trans switching. As a result, the Ag NPs enable two-photon initiated cis to trans isomerization, but not trans to cis isomerization. Confocal anti-Stokes fluorescence imaging shows that this effect is not due to local heating, while the quadratic dependence of switching rate on laser intensity is consistent with a two-photon process. Highly localized two-photon initiated switching could allow local manipulation near the focal point of a laser within a 3D nanoparticle assembly, which cannot be achieved using linear optical processes.

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Nowadays, communication environments are already characterized by a myriad of competing and complementary technologies that aim to provide an ubiquitous connectivity service. Next Generation Networks need to hide this heterogeneity by providing a new abstraction level, while simultaneously be aware of the underlying technologies to deliver richer service experiences to the end-user. Moreover, the increasing interest for group-based multimedia services followed by their ever growing resource demands and network dynamics, has been boosting the research towards more scalable and exible network control approaches. The work developed in this Thesis enables such abstraction and exploits the prevailing heterogeneity in favor of a context-aware network management and adaptation. In this scope, we introduce a novel hierarchical control framework with self-management capabilities that enables the concept of Abstract Multiparty Trees (AMTs) to ease the control of multiparty content distribution throughout heterogeneous networks. A thorough evaluation of the proposed multiparty transport control framework was performed in the scope of this Thesis, assessing its bene ts in terms of network selection, delivery tree recon guration and resource savings. Moreover, we developed an analytical study to highlight the scalability of the AMT concept as well as its exibility in large scale networks and group sizes. To prove the feasibility and easy deployment characteristic of the proposed control framework, we implemented a proof-of-concept demonstrator that comprehends the main control procedures conceptually introduced. Its outcomes highlight a good performance of the multiparty content distribution tree control, including its local and global recon guration. In order to endow the AMT concept with the ability to guarantee the best service experience by the end-user, we integrate in the control framework two additional QoE enhancement approaches. The rst employs the concept of Network Coding to improve the robustness of the multiparty content delivery, aiming at mitigating the impact of possible packet losses in the end-user service perception. The second approach relies on a machine learning scheme to autonomously determine at each node the expected QoE towards a certain destination. This knowledge is then used by di erent QoE-aware network management schemes that, jointly, maximize the overall users' QoE. The performance and scalability of the control procedures developed, aided by the context and QoE-aware mechanisms, show the advantages of the AMT concept and the proposed hierarchical control strategy for the multiparty content distribution with enhanced service experience. Moreover we also prove the feasibility of the solution in a practical environment, and provide future research directions that bene t the evolved control framework and make it commercially feasible.

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The scarcity and diversity of resources among the devices of heterogeneous computing environments may affect their ability to perform services with specific Quality of Service constraints, particularly in dynamic distributed environments where the characteristics of the computational load cannot always be predicted in advance. Our work addresses this problem by allowing resource constrained devices to cooperate with more powerful neighbour nodes, opportunistically taking advantage of global distributed resources and processing power. Rather than assuming that the dynamic configuration of this cooperative service executes until it computes its optimal output, the paper proposes an anytime approach that has the ability to tradeoff deliberation time for the quality of the solution. Extensive simulations demonstrate that the proposed anytime algorithms are able to quickly find a good initial solution and effectively optimise the rate at which the quality of the current solution improves at each iteration, with an overhead that can be considered negligible.

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Context awareness, dynamic reconfiguration at runtime and heterogeneity are key characteristics of future distributed systems, particularly in ubiquitous and mobile computing scenarios. The main contributions of this dissertation are theoretical as well as architectural concepts facilitating information exchange and fusion in heterogeneous and dynamic distributed environments. Our main focus is on bridging the heterogeneity issues and, at the same time, considering uncertain, imprecise and unreliable sensor information in information fusion and reasoning approaches. A domain ontology is used to establish a common vocabulary for the exchanged information. We thereby explicitly support different representations for the same kind of information and provide Inter-Representation Operations that convert between them. Special account is taken of the conversion of associated meta-data that express uncertainty and impreciseness. The Unscented Transformation, for example, is applied to propagate Gaussian normal distributions across highly non-linear Inter-Representation Operations. Uncertain sensor information is fused using the Dempster-Shafer Theory of Evidence as it allows explicit modelling of partial and complete ignorance. We also show how to incorporate the Dempster-Shafer Theory of Evidence into probabilistic reasoning schemes such as Hidden Markov Models in order to be able to consider the uncertainty of sensor information when deriving high-level information from low-level data. For all these concepts we provide architectural support as a guideline for developers of innovative information exchange and fusion infrastructures that are particularly targeted at heterogeneous dynamic environments. Two case studies serve as proof of concept. The first case study focuses on heterogeneous autonomous robots that have to spontaneously form a cooperative team in order to achieve a common goal. The second case study is concerned with an approach for user activity recognition which serves as baseline for a context-aware adaptive application. Both case studies demonstrate the viability and strengths of the proposed solution and emphasize that the Dempster-Shafer Theory of Evidence should be preferred to pure probability theory in applications involving non-linear Inter-Representation Operations.

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Robots are ever increasing in a variety of different workplaces providing an array of benefits such alternative solutions to traditional human labor. While developing fully autonomous robots is the ultimate goal in many robotic applications the reality is that there still exist many situationswere robots require some level of teleoperation in order to achieve assigned goals especially when deployed in non-deterministic environments. For instance teleoperation is commonly used in areas such as search and rescue, bomb disposal and exploration of inaccessible or harsh terrain. This is due to a range of factors such as the lack of ability for robots to quickly and reliably navigate unknown environments or provide high-level decision making especially intime critical tasks. To provide an adequate solution for such situations human-in-the-loop control is required. When developing human-in-the-loop control it is important to take advantage of the complimentary skill-sets that both humans and robots share. For example robots can performrapid calculations, provide accurate measurements through hardware such as sensors and store large amounts of data while humans provide experience, intuition, risk management and complex decision making capabilities. Shared autonomy is the concept of building robotic systems that take advantage of these complementary skills-sets to provide a robust an efficient robotic solution. While the requirement of human-in-the-loop control exists Human Machine Interaction (HMI) remains an important research topic especially the area of User Interface (UI) design.In order to provide operators with an effective teleoperation system it is important that the interface is intuitive and dynamic while also achieving a high level of immersion. Recent advancements in virtual and augmented reality hardware is giving rise to innovative HMI systems. Interactive hardware such as Microsoft Kinect, leap motion, Oculus Rift, Samsung Gear VR and even CAVE Automatic Virtual Environments [1] are providing vast improvements over traditional user interface designs such as the experimental web browser JanusVR [2]. This combined with the introduction of standardized robot frameworks such as ROS and Webots [3] that now support a large number of different robots provides an opportunity to develop a universal UI for teleoperation control to improve operator efficiency while reducing teleoperation training.This research introduces the concept of a dynamic virtual workspace for teleoperation of heterogeneous robots in non-deterministic environments that require human-in-the-loop control. The system first identifies the connected robots through the use kinematic information then determines its network capabilities such as latency and bandwidth. Given the robot type and network capabilities the system can then provide the operator with available teleoperation modes such as pick and place control or waypoint navigation while also allowing them to manipulate the virtual workspace layout to provide information from onboard camera’s or sensors.

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This paper presents the findings of an investigation into the rate-limiting mechanism for the heterogeneous burning in oxygen under normal gravity and microgravity of cylindrical iron rods. The original objective of the work was to determine why the observed melting rate for burning 3.2-mm diameter iron rods is significantly higher in microgravity than in normal gravity. This work, however, also provided fundamental insight into the rate-limiting mechanism for heterogeneous burning. The paper includes a summary of normal-gravity and microgravity experimental results, heat transfer analysis and post-test microanalysis of quenched samples. These results are then used to show that heat transfer across the solid/liquid interface is the rate-limiting mechanism for melting and burning, limited by the interfacial surface area between the molten drop and solid rod. In normal gravity, the work improves the understanding of trends reported during standard flammability testing for metallic materials, such as variations in melting rates between test specimens with the same cross-sectional area but different crosssectional shape. The work also provides insight into the effects of configuration and orientation, leading to an improved application of standard test results in the design of oxygen system components. For microgravity applications, the work enables the development of improved methods for lower cost metallic material flammability testing programs. In these ways, the work provides fundamental insight into the heterogeneous burning process and contributes to improved fire safety for oxygen systems in applications involving both normal-gravity and microgravity environments.

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The interest in utilising multiple heterogeneous Unmanned Aerial Vehicles (UAVs) in close proximity is growing rapidly. As such, many challenges are presented in the effective coordination and management of these UAVs; converting the current n-to-1 paradigm (n operators operating a single UAV) to the 1-to-n paradigm (one operator managing n UAVs). This paper introduces an Information Abstraction methodology used to produce the functional capability framework initially proposed by Chen et al. and its Level Of Detail (LOD) indexing scale. This framework was validated through comparing the operator workload and Situation Awareness (SA) of three experiment scenarios involving multiple autonomously heterogeneous UAVs. The first scenario was set in a high LOD configuration with highly abstracted UAV functional information; the second scenario was set in a mixed LOD configuration; and the final scenario was set in a low LOD configuration with maximal UAV functional information. Results show that there is a significant statistical decrease in operator workload when a UAV’s functional information is displayed at its physical form (low LOD - maximal information) when comparing to the mixed LOD configuration.