929 resultados para 080101 Adaptive Agents and Intelligent Robotics
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The ecological theory of adaptive radiation predicts that the evolution of phenotypic diversity within species is generated by divergent natural selection arising from different environments and competition between species. Genetic connectivity among populations is likely also to have an important role in both the origin and maintenance of adaptive genetic diversity. Our goal was to evaluate the potential roles of genetic connectivity and natural selection in the maintenance of adaptive phenotypic differences among morphs of Arctic charr, Salvelinus alpinus, in Iceland. At a large spatial scale, we tested the predictive power of geographic structure and phenotypic variation for patterns of neutral genetic variation among populations throughout Iceland. At a smaller scale, we evaluated the genetic differentiation between two morphs in Lake Thingvallavatn relative to historically explicit, coalescent-based null models of the evolutionary history of these lineages. At the large spatial scale, populations are highly differentiated, but weakly structured, both geographically and with respect to patterns of phenotypic variation. At the intralacustrine scale, we observe modest genetic differentiation between two morphs, but this level of differentiation is nonetheless consistent with strong reproductive isolation throughout the Holocene. Rather than a result of the homogenizing effect of gene flow in a system at migration-drift equilibrium, the modest level of genetic differentiation could equally be a result of slow neutral divergence by drift in large populations. We conclude that contemporary and recent patterns of restricted gene flow have been highly conducive to the evolution and maintenance of adaptive genetic variation in Icelandic Arctic charr.
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Adaptive immunity in vertebrates can confer increased resistance against invading pathogens upon re-infection. But how specific parasite genotypes affect the transition from innate to adaptive immunity is poorly understood. Here, we investigated the effects of homologous and heterologous exposures of genetically distinct parasite lineages of the eye fluke Diplostomum pseudospathaceum on gene expression patterns of adaptive immunity in sticklebacks (Gasterosteus aculeatus). We showed that observable differences were largely attributable to final exposures and that there is no transcription pattern characteristic for a general response to repeated infections with D. pseudospathaceum. Final exposure did not unify expression patterns of heterologous pre-exposed fish. Interestingly, heterologous final exposures showed similarities between different treatment groups subjected to homologous pre-exposure. The observed pattern was supported by parasite infection rates and suggests that host immunization was optimized towards an adaptive immune response that favored effectiveness against parasite diversity over specificity.
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Although oceanwarming and acidification are recognized as two major anthropogenic perturbations of today's oceanswe know very little about how marine phytoplankton may respond via evolutionary change.We tested for adaptation to ocean warming in combination with ocean acidification in the globally important phytoplankton species Emiliania huxleyi. Temperature adaptation occurred independently of ocean acidifcation levels. Exponential growth rates were were up to 16% higher in populations adapted for one year to warming when assayed at their upper thermal tolerance limit. Particulate inorganic (PIC) and organic (POC) carbon production was restored to values under present-day ocean conditions, owing to adaptive evolution, and were 101% and 55% higher under combined warming and acidification, respectively, than in non-adapted controls. Cells also evolved to a smaller size while they recovered their initial PIC:POC ratio even under elevated CO2. The observed changes in coccolithophore growth, calcite and biomass production, cell size and elemental composition demonstrate the importance of evolutionary processes for phytoplankton performance in a future ocean. At the end of a 1-yr temperature selection phase, we conducted a reciprocal assay experiment in which temperature-adapted asexual populations were compared to the respective non-adapted control populations under high temperature, and vice versa (1. Assay Data, Dataset #835336). Mean exponential growth rates ? in treatments subjected to high temperature increased rapidly under all high temperature-CO2 treatment combinations during the temperature selection phase (2. time series, Dataset #835339).
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Coral reefs are globally threatened by climate change-related ocean warming and ocean acidification (OA). To date, slow-response mechanisms such as genetic adaptation have been considered the major determinant of coral reef persistence, with little consideration of rapid-response acclimatization mechanisms. These rapid mechanisms such as parental effects that can contribute to trans-generational acclimatization (e.g. epigenetics) have, however, been identified as important contributors to offspring response in other systems. We present the first evidence of parental effects in a cross-generational exposure to temperature and OA in reef-building corals. Here, we exposed adults to high (28.9°C, 805 µatm PCO2) or ambient (26.5°C, 417 µatm PCO2) temperature and OA treatments during the larval brooding period. Exposure to high treatment negatively affected adult performance, but their larvae exhibited size differences and metabolic acclimation when subsequently re-exposed, unlike larvae from parents exposed to ambient conditions. Understanding the innate capacity corals possess to respond to current and future climatic conditions is essential to reef protection and maintenance. Our results identify that parental effects may have an important role through (1) ameliorating the effects of stress through preconditioning and adaptive plasticity, and/or (2) amplifying the negative parental response through latent effects on future life stages. Whether the consequences of parental effects and the potential for trans-generational acclimatization are beneficial or maladaptive, our work identifies a critical need to expand currently proposed climate change outcomes for corals to further assess rapid response mechanisms that include non-genetic inheritance through parental contributions and classical epigenetic mechanisms.
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Managing large medical image collections is an increasingly demanding important issue in many hospitals and other medical settings. A huge amount of this information is daily generated, which requires robust and agile systems. In this paper we present a distributed multi-agent system capable of managing very large medical image datasets. In this approach, agents extract low-level information from images and store them in a data structure implemented in a relational database. The data structure can also store semantic information related to images and particular regions. A distinctive aspect of our work is that a single image can be divided so that the resultant sub-images can be stored and managed separately by different agents to improve performance in data accessing and processing. The system also offers the possibility of applying some region-based operations and filters on images, facilitating image classification. These operations can be performed directly on data structures in the database.
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This article presents the model and implementation of a multiagent fuzzy system (MAFS), to automate the search of solutions of incidents in telecommunications, expressed by the users in an imprecise way and, later, registered in a a knowledge base keeping their original vaguenesses and the relationships between the incidents considered as ancestors and descendants. The process of the fuzzy incidents, no matter their causes, is based on the application of a formula which transforms the intervals of the fuzzy incidents to a computational language and in the interaction between the different kinds of software agents and the humans. To search and suggest solutions of the incident originally stated, a search algorithm is used and illustrated with an example. The preliminary results obtained show the users' satisfaction, in a great percentage of the presented cases. The system is adaptive and allows to record new solutions for future users.
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Modern FPGAs with Dynamic and Partial Reconfiguration (DPR) feature allow the implementation of complex, yet flexible, hardware systems. Combining this flexibility with evolvable hardware techniques, real adaptive systems, able to reconfigure themselves according to environmental changes, can be envisaged. In this paper, a highly regular and modular architecture combined with a fast reconfiguration mechanism is proposed, allowing the introduction of dynamic and partial reconfiguration in the evolvable hardware loop. Results and use case show that, following this approach, evolvable processing IP Cores can be built, providing intensive data processing capabilities, improving data and delay overheads with respect to previous proposals. Results also show that, in the worst case (maximum mutation rate), average reconfiguration time is 5 times lower than evaluation time.
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In spite of the increasing presence of Semantic Web Facilities, only a limited amount of the available resources in the Internet provide a semantic access. Recent initiatives such as the emerging Linked Data Web are providing semantic access to available data by porting existing resources to the semantic web using different technologies, such as database-semantic mapping and scraping. Nevertheless, existing scraping solutions are based on ad-hoc solutions complemented with graphical interfaces for speeding up the scraper development. This article proposes a generic framework for web scraping based on semantic technologies. This framework is structured in three levels: scraping services, semantic scraping model and syntactic scraping. The first level provides an interface to generic applications or intelligent agents for gathering information from the web at a high level. The second level defines a semantic RDF model of the scraping process, in order to provide a declarative approach to the scraping task. Finally, the third level provides an implementation of the RDF scraping model for specific technologies. The work has been validated in a scenario that illustrates its application to mashup technologies
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Adaptive agents use feedback as a key strategy to cope with un- certainty and change in their environments. The information fed back from the sensorimotor loop into the control subsystem can be used to change four different elements of the controller: parameters associated to the control model, the control model itself, the functional organization of the agent and the functional realization of the agent. There are many change alternatives and hence the complexity of the agent’s space of potential configurations is daunting. The only viable alternative for space- and time-constrained agents —in practical, economical, evolutionary terms— is to achieve a reduction of the dimensionality of this configuration space. Emotions play a critical role in this reduction. The reduction is achieved by func- tionalization, interface minimization and by patterning, i.e. by selection among a predefined set of organizational configurations. This analysis lets us state how autonomy emerges from the integration of cognitive, emotional and autonomic systems in strict functional terms: autonomy is achieved by the closure of functional dependency. Emotion-based morphofunctional systems are able to exhibit complex adaptation patterns at a reduced cognitive cost. In this article we show a general model of how emotion supports functional adaptation and how the emotional biological systems operate following this theoretical model. We will also show how this model is also of applicability to the construction of a wide spectrum of artificial systems1.
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The objective of this paper is to design a path following control system for a car-like mobile robot using classical linear control techniques, so that it adapts on-line to varying conditions during the trajectory following task. The main advantages of the proposed control structure is that well known linear control theory can be applied in calculating the PID controllers to full control requirements, while at the same time it is exible to be applied in non-linear changing conditions of the path following task. For this purpose the Frenet frame kinematic model of the robot is linearised at a varying working point that is calculated as a function of the actual velocity, the path curvature and kinematic parameters of the robot, yielding a transfer function that varies during the trajectory. The proposed controller is formed by a combination of an adaptive PID and a feed-forward controller, which varies accordingly with the working conditions and compensates the non-linearity of the system. The good features and exibility of the proposed control structure have been demonstrated through realistic simulations that include both kinematics and dynamics of the car-like robot.
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Esta tesis estudia la monitorización y gestión de la Calidad de Experiencia (QoE) en los servicios de distribución de vídeo sobre IP. Aborda el problema de cómo prevenir, detectar, medir y reaccionar a las degradaciones de la QoE desde la perspectiva de un proveedor de servicios: la solución debe ser escalable para una red IP extensa que entregue flujos individuales a miles de usuarios simultáneamente. La solución de monitorización propuesta se ha denominado QuEM(Qualitative Experience Monitoring, o Monitorización Cualitativa de la Experiencia). Se basa en la detección de las degradaciones de la calidad de servicio de red (pérdidas de paquetes, disminuciones abruptas del ancho de banda...) e inferir de cada una una descripción cualitativa de su efecto en la Calidad de Experiencia percibida (silencios, defectos en el vídeo...). Este análisis se apoya en la información de transporte y de la capa de abstracción de red de los flujos codificados, y permite caracterizar los defectos más relevantes que se observan en este tipo de servicios: congelaciones, efecto de “cuadros”, silencios, pérdida de calidad del vídeo, retardos e interrupciones en el servicio. Los resultados se han validado mediante pruebas de calidad subjetiva. La metodología usada en esas pruebas se ha desarrollado a su vez para imitar lo más posible las condiciones de visualización de un usuario de este tipo de servicios: los defectos que se evalúan se introducen de forma aleatoria en medio de una secuencia de vídeo continua. Se han propuesto también algunas aplicaciones basadas en la solución de monitorización: un sistema de protección desigual frente a errores que ofrece más protección a las partes del vídeo más sensibles a pérdidas, una solución para minimizar el impacto de la interrupción de la descarga de segmentos de Streaming Adaptativo sobre HTTP, y un sistema de cifrado selectivo que encripta únicamente las partes del vídeo más sensibles. También se ha presentado una solución de cambio rápido de canal, así como el análisis de la aplicabilidad de los resultados anteriores a un escenario de vídeo en 3D. ABSTRACT This thesis proposes a comprehensive approach to the monitoring and management of Quality of Experience (QoE) in multimedia delivery services over IP. It addresses the problem of preventing, detecting, measuring, and reacting to QoE degradations, under the constraints of a service provider: the solution must scale for a wide IP network delivering individual media streams to thousands of users. The solution proposed for the monitoring is called QuEM (Qualitative Experience Monitoring). It is based on the detection of degradations in the network Quality of Service (packet losses, bandwidth drops...) and the mapping of each degradation event to a qualitative description of its effect in the perceived Quality of Experience (audio mutes, video artifacts...). This mapping is based on the analysis of the transport and Network Abstraction Layer information of the coded stream, and allows a good characterization of the most relevant defects that exist in this kind of services: screen freezing, macroblocking, audio mutes, video quality drops, delay issues, and service outages. The results have been validated by subjective quality assessment tests. The methodology used for those test has also been designed to mimic as much as possible the conditions of a real user of those services: the impairments to evaluate are introduced randomly in the middle of a continuous video stream. Based on the monitoring solution, several applications have been proposed as well: an unequal error protection system which provides higher protection to the parts of the stream which are more critical for the QoE, a solution which applies the same principles to minimize the impact of incomplete segment downloads in HTTP Adaptive Streaming, and a selective scrambling algorithm which ciphers only the most sensitive parts of the media stream. A fast channel change application is also presented, as well as a discussion about how to apply the previous results and concepts in a 3D video scenario.
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We report conditions on a switching signal that guarantee that solutions of a switched linear systems converge asymptotically to zero. These conditions are apply to continuous, discrete-time and hybrid switched linear systems, both those having stable subsystems and mixtures of stable and unstable subsystems.
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The deployment of home-based smart health services requires effective and reliable systems for personal and environmental data management. ooperation between Home Area Networks (HAN) and Body Area Networks (BAN) can provide smart systems with ad hoc reasoning information to support health care. This paper details the implementation of an architecture that integrates BAN, HAN and intelligent agents to manage physiological and environmental data to proactively detect risk situations at the digital home. The system monitors dynamic situations and timely adjusts its behavior to detect user risks concerning to health. Thus, this work provides a reasoning framework to infer appropriate solutions in cases of health risk episodes. Proposed smart health monitoring approach integrates complex reasoning according to home environment, user profile and physiological parameters defined by a scalable ontology. As a result, health care demands can be detected to activate adequate internal mechanisms and report public health services for requested actions.