837 resultados para Adaptive intelligent system


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We present a system for dynamic network resource configuration in environments with bandwidth reservation and path restoration mechanisms. Our focus is on the dynamic bandwidth management results, although the main goal of the system is the integration of the different mechanisms that manage the reserved paths (bandwidth, restoration, and spare capacity planning). The objective is to avoid conflicts between these mechanisms. The system is able to dynamically manage a logical network such as a virtual path network in ATM or a label switch path network in MPLS. This system has been designed to be modular in the sense that in can be activated or deactivated, and it can be applied only in a sub-network. The system design and implementation is based on a multi-agent system (MAS). We also included details of its architecture and implementation

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To coordinate ambulances for emergency medical services, a multiagent system uses an auction mechanism based on trust. Results of tests using real data show that this system can efficiently assign ambulances to patients, thereby reducing transportation time. Emergency transportation on specialized vehicles is needed when a person's health is in risk of irreparable damage. A patient can't benefit from sophisticated medical treatments and technologies if she or he isn't placed in a proper healthcare center with the appropriate medical team. For example, strokes are neurological emergencies involving a limited amount of time in which treatment measures are effective

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Identifying the genetic changes driving adaptive variation in natural populations is key to understanding the origins of biodiversity. The mosaic of mimetic wing patterns in Heliconius butterflies makes an excellent system for exploring adaptive variation using next-generation sequencing. In this study, we use a combination of techniques to annotate the genomic interval modulating red color pattern variation, identify a narrow region responsible for adaptive divergence and convergence in Heliconius wing color patterns, and explore the evolutionary history of these adaptive alleles. We use whole genome resequencing from four hybrid zones between divergent color pattern races of Heliconius erato and two hybrid zones of the co-mimic Heliconius melpomene to examine genetic variation across 2.2 Mb of a partial reference sequence. In the intergenic region near optix, the gene previously shown to be responsible for the complex red pattern variation in Heliconius, population genetic analyses identify a shared 65-kb region of divergence that includes several sites perfectly associated with phenotype within each species. This region likely contains multiple cis-regulatory elements that control discrete expression domains of optix. The parallel signatures of genetic differentiation in H. erato and H. melpomene support a shared genetic architecture between the two distantly related co-mimics; however, phylogenetic analysis suggests mimetic patterns in each species evolved independently. Using a combination of next-generation sequencing analyses, we have refined our understanding of the genetic architecture of wing pattern variation in Heliconius and gained important insights into the evolution of novel adaptive phenotypes in natural populations.

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El sistema de fangs activats és el tractament biològic més àmpliament utilitzat arreu del món per la depuració d'aigües residuals. El seu funcionament depèn de la correcta operació tant del reactor biològic com del decantador secundari. Quan la fase de sedimentació no es realitza correctament, la biomassa no decantada s'escapa amb l'efluent causant un impacte sobre el medi receptor. Els problemes de separació de sòlids, són actualment una de les principals causes d'ineficiència en l'operació dels sistemes de fangs activats arreu del món. Inclouen: bulking filamentós, bulking viscós, escumes biològiques, creixement dispers, flòcul pin-point i desnitrificació incontrolada. L'origen dels problemes de separació generalment es troba en un desequilibri entre les principals comunitats de microorganismes implicades en la sedimentació de la biomassa: els bacteris formadors de flòcul i els bacteris filamentosos. Degut a aquest origen microbiològic, la seva identificació i control no és una tasca fàcil pels caps de planta. Els Sistemes de Suport a la Presa de Decisions basats en el coneixement (KBDSS) són un grup d'eines informàtiques caracteritzades per la seva capacitat de representar coneixement heurístic i tractar grans quantitats de dades. L'objectiu de la present tesi és el desenvolupament i validació d'un KBDSS específicament dissenyat per donar suport als caps de planta en el control dels problemes de separació de sòlids d'orígen microbiològic en els sistemes de fangs activats. Per aconseguir aquest objectiu principal, el KBDSS ha de presentar les següents característiques: (1) la implementació del sistema ha de ser viable i realista per garantir el seu correcte funcionament; (2) el raonament del sistema ha de ser dinàmic i evolutiu per adaptar-se a les necessitats del domini al qual es vol aplicar i (3) el raonament del sistema ha de ser intel·ligent. En primer lloc, a fi de garantir la viabilitat del sistema, s'ha realitzat un estudi a petita escala (Catalunya) que ha permès determinar tant les variables més utilitzades per a la diagnosi i monitorització dels problemes i els mètodes de control més viables, com la detecció de les principals limitacions que el sistema hauria de resoldre. Els resultats d'anteriors aplicacions han demostrat que la principal limitació en el desenvolupament de KBDSSs és l'estructura de la base de coneixement (KB), on es representa tot el coneixement adquirit sobre el domini, juntament amb els processos de raonament a seguir. En el nostre cas, tenint en compte la dinàmica del domini, aquestes limitacions es podrien veure incrementades si aquest disseny no fos òptim. En aquest sentit, s'ha proposat el Domino Model com a eina per dissenyar conceptualment el sistema. Finalment, segons el darrer objectiu referent al seguiment d'un raonament intel·ligent, l'ús d'un Sistema Expert (basat en coneixement expert) i l'ús d'un Sistema de Raonament Basat en Casos (basat en l'experiència) han estat integrats com els principals sistemes intel·ligents encarregats de dur a terme el raonament del KBDSS. Als capítols 5 i 6 respectivament, es presenten el desenvolupament del Sistema Expert dinàmic (ES) i del Sistema de Raonament Basat en Casos temporal, anomenat Sistema de Raonament Basat en Episodis (EBRS). A continuació, al capítol 7, es presenten detalls de la implementació del sistema global (KBDSS) en l'entorn G2. Seguidament, al capítol 8, es mostren els resultats obtinguts durant els 11 mesos de validació del sistema, on aspectes com la precisió, capacitat i utilitat del sistema han estat validats tant experimentalment (prèviament a la implementació) com a partir de la seva implementació real a l'EDAR de Girona. Finalment, al capítol 9 s'enumeren les principals conclusions derivades de la present tesi.

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La present tesi pretén recollir l'experiència viscuda en desenvolupar un sistema supervisor intel·ligent per a la millora de la gestió de plantes depuradores d'aigües residuals., implementar-lo en planta real (EDAR Granollers) i avaluar-ne el funcionament dia a dia amb situacions típiques de la planta. Aquest sistema supervisor combina i integra eines de control clàssic de les plantes depuradores (controlador automàtic del nivell d'oxigen dissolt al reactor biològic, ús de models descriptius del procés...) amb l'aplicació d'eines del camp de la intel·ligència artificial (sistemes basats en el coneixement, concretament sistemes experts i sistemes basats en casos, i xarxes neuronals). Aquest document s'estructura en 9 capítols diferents. Hi ha una primera part introductòria on es fa una revisió de l'estat actual del control de les EDARs i s'explica el perquè de la complexitat de la gestió d'aquests processos (capítol 1). Aquest capítol introductori juntament amb el capítol 2, on es pretén explicar els antecedents d'aquesta tesi, serveixen per establir els objectius d'aquest treball (capítol 3). A continuació, el capítol 4 descriu les peculiaritats i especificitats de la planta que s'ha escollit per implementar el sistema supervisor. Els capítols 5 i 6 del present document exposen el treball fet per a desenvolupar el sistema basat en regles o sistema expert (capítol 6) i el sistema basat en casos (capítol 7). El capítol 8 descriu la integració d'aquestes dues eines de raonament en una arquitectura multi nivell distribuïda. Finalment, hi ha una darrer capítol que correspon a la avaluació (verificació i validació), en primer lloc, de cadascuna de les eines per separat i, posteriorment, del sistema global en front de situacions reals que es donin a la depuradora

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En esta tesis se propone el uso de agentes inteligentes en entornos de aprendizaje en línea con el fin de mejorar la asistencia y motivación del estudiante a través de contenidos personalizados que tienen en cuenta el estilo de aprendizaje del estudiante y su nivel de conocimiento. Los agentes propuestos se desempeñan como asistentes personales que ayudan al estudiante a llevar a cabo las actividades de aprendizaje midiendo su progreso y motivación. El entorno de agentes se construye a través de una arquitectura multiagente llamada MASPLANG diseñada para dar soporte adaptativo (presentación y navegación adaptativa) a un sistema hipermedia educativo desarrollado en la Universitat de Girona para impartir educación virtual a través del web. Un aspecto importante de esta propuesta es la habilidad de construir un modelo de estudiante híbrido que comienza con un modelo estereotípico del estudiante basado en estilos de aprendizaje y se modifica gradualmente a medida que el estudiante interactúa con el sistema (gustos subjetivos). Dentro del contexto de esta tesis, el aprendizaje se define como el proceso interno que, bajo factores de cambio resulta en la adquisición de la representación interna de un conocimiento o de una actitud. Este proceso interno no se puede medir directamente sino a través de demostraciones observables externas que constituyen el comportamiento relacionado con el objeto de conocimiento. Finalmente, este cambio es el resultado de la experiencia o entrenamiento y tiene una durabilidad que depende de factores como la motivación y el compromiso. El MASPLANG está compuesto por dos niveles de agentes: los intermediarios llamados IA (agentes de información) que están en el nivel inferior y los de Interfaz llamados PDA (agentes asistentes) que están en el nivel superior. Los agentes asistentes atienden a los estudiantes cuando trabajan con el material didáctico de un curso o una lección de aprendizaje. Esta asistencia consiste en la recolección y análisis de las acciones de los estudiantes para ofrecer contenidos personalizados y en la motivación del estudiante durante el aprendizaje mediante el ofrecimiento de contenidos de retroalimentación, ejercicios adaptados al nivel de conocimiento y mensajes, a través de interfaces de usuario animadas y atractivas. Los agentes de información se encargan del mantenimiento de los modelos pedagógico y del dominio y son los que están en completa interacción con las bases de datos del sistema (compendio de actividades del estudiante y modelo del dominio). El escenario de funcionamiento del MASPLANG está definido por el tipo de usuarios y el tipo de contenidos que ofrece. Como su entorno es un sistema hipermedia educativo, los usuarios se clasifican en profesores quienes definen y preparan los contenidos para el aprendizaje adaptativo, y los estudiantes quienes llevan a cabo las actividades de aprendizaje de forma personalizada. El perfil de aprendizaje inicial del estudiante se captura a través de la evaluación del cuestionario ILS (herramienta de diagnóstico del modelo FSLSM de estilos de aprendizaje adoptado para este estudio) que se asigna al estudiante en su primera interacción con el sistema. Este cuestionario consiste en un conjunto de preguntas de naturaleza sicológica cuyo objetivo es determinar los deseos, hábitos y reacciones del estudiante que orientarán la personalización de los contenidos y del entorno de aprendizaje. El modelo del estudiante se construye entonces teniendo en cuenta este perfil de aprendizaje y el nivel de conocimiento obtenido mediante el análisis de las acciones del estudiante en el entorno.

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In domain of intelligent buildings, saving energy in buildings and increasing preferences of occupants are two important factors. These factors are the important keys for evaluating the performance of work environment. In recent years, many researchers combine these areas to create the system that can change from original to the modern work environment called intelligent work environment. Due to advance of agent technology, it has received increasing attention in the area of intelligent pervasive environments. In this paper, we review several issues in intelligent buildings, with respect to the implementation of control system for intelligent buildings via multi-agent systems. Furthermore, we present the MASBO (Multi-Agent System for Building cOntrol) that has been implemented for controlling the building facilities to reach the balancing between energy efficiency and occupant’s comfort. In addition to enhance the MASBO system, the collaboration through negotiation among agents is presented.

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Although climate models have been improving in accuracy and efficiency over the past few decades, it now seems that these incremental improvements may be slowing. As tera/petascale computing becomes massively parallel, our legacy codes are less suitable, and even with the increased resolution that we are now beginning to use, these models cannot represent the multiscale nature of the climate system. This paper argues that it may be time to reconsider the use of adaptive mesh refinement for weather and climate forecasting in order to achieve good scaling and representation of the wide range of spatial scales in the atmosphere and ocean. Furthermore, the challenge of introducing living organisms and human responses into climate system models is only just beginning to be tackled. We do not yet have a clear framework in which to approach the problem, but it is likely to cover such a huge number of different scales and processes that radically different methods may have to be considered. The challenges of multiscale modelling and petascale computing provide an opportunity to consider a fresh approach to numerical modelling of the climate (or Earth) system, which takes advantage of the computational fluid dynamics developments in other fields and brings new perspectives on how to incorporate Earth system processes. This paper reviews some of the current issues in climate (and, by implication, Earth) system modelling, and asks the question whether a new generation of models is needed to tackle these problems.

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In this article, we examine the case of a system that cooperates with a “direct” user to plan an activity that some “indirect” user, not interacting with the system, should perform. The specific application we consider is the prescription of drugs. In this case, the direct user is the prescriber and the indirect user is the person who is responsible for performing the therapy. Relevant characteristics of the two users are represented in two user models. Explanation strategies are represented in planning operators whose preconditions encode the cognitive state of the indirect user; this allows tailoring the message to the indirect user's characteristics. Expansion of optional subgoals and selection among candidate operators is made by applying decision criteria represented as metarules, that negotiate between direct and indirect users' views also taking into account the context where explanation is provided. After the message has been generated, the direct user may ask to add or remove some items, or change the message style. The system defends the indirect user's needs as far as possible by mentioning the rationale behind the generated message. If needed, the plan is repaired and the direct user model is revised accordingly, so that the system learns progressively to generate messages suited to the preferences of people with whom it interacts.

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This paper focuses on improving computer network management by the adoption of artificial intelligence techniques. A logical inference system has being devised to enable automated isolation, diagnosis, and even repair of network problems, thus enhancing the reliability, performance, and security of networks. We propose a distributed multi-agent architecture for network management, where a logical reasoner acts as an external managing entity capable of directing, coordinating, and stimulating actions in an active management architecture. The active networks technology represents the lower level layer which makes possible the deployment of code which implement teleo-reactive agents, distributed across the whole network. We adopt the Situation Calculus to define a network model and the Reactive Golog language to implement the logical reasoner. An active network management architecture is used by the reasoner to inject and execute operational tasks in the network. The integrated system collects the advantages coming from logical reasoning and network programmability, and provides a powerful system capable of performing high-level management tasks in order to deal with network fault.

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Purpose – The purpose of this paper is to investigate the concepts of intelligent buildings (IBs), and the opportunities offered by the application of computer-aided facilities management (CAFM) systems. Design/methodology/approach – In this paper definitions of IBs are investigated, particularly definitions that are embracing open standards for effective operational change, using a questionnaire survey. The survey further investigated the extension of CAFM to IBs concepts and the opportunities that such integrated systems will provide to facilities management (FM) professionals. Findings – The results showed variation in the understanding of the concept of IBs and the application of CAFM. The survey showed that 46 per cent of respondents use a CAFM system with a majority agreeing on the potential of CAFM in delivery of effective facilities. Research limitations/implications – The questionnaire survey results are limited to the views of the respondents within the context of FM in the UK. Practical implications – Following on the many definitions of an IB does not necessarily lead to technologies of equipment that conform to an open standard. This open standard and documentation of systems produced by vendors is the key to integrating CAFM with other building management systems (BMS) and further harnessing the application of CAFM for IBs. Originality/value – The paper gives experience-based suggestions for both demand and supply sides of the service procurement to gain the feasible benefits and avoid the currently hindering obstacles, as the paper provides insight to the current and future tools for the mobile aspects of FM. The findings are relevant for service providers and operators as well.

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It is argued that the truth status of emergent properties of complex adaptive systems models should be based on an epistemology of proof by constructive verification and therefore on the ontological axioms of a non-realist logical system such as constructivism or intuitionism. ‘Emergent’ properties of complex adaptive systems (CAS) models create particular epistemological and ontological challenges. These challenges bear directly on current debates in the philosophy of mathematics and in theoretical computer science. CAS research, with its emphasis on computer simulation, is heavily reliant on models which explore the entailments of Formal Axiomatic Systems (FAS). The incompleteness results of Gödel, the incomputability results of Turing, and the Algorithmic Information Theory results of Chaitin, undermine a realist (platonic) truth model of emergent properties. These same findings support the hegemony of epistemology over ontology and point to alternative truth models such as intuitionism, constructivism and quasi-empiricism.

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Uncertainty contributes a major part in the accuracy of a decision-making process while its inconsistency is always difficult to be solved by existing decision-making tools. Entropy has been proved to be useful to evaluate the inconsistency of uncertainty among different respondents. The study demonstrates an entropy-based financial decision support system called e-FDSS. This integrated system provides decision support to evaluate attributes (funding options and multiple risks) available in projects. Fuzzy logic theory is included in the system to deal with the qualitative aspect of these options and risks. An adaptive genetic algorithm (AGA) is also employed to solve the decision algorithm in the system in order to provide optimal and consistent rates to these attributes. Seven simplified and parallel projects from a Hong Kong construction small and medium enterprise (SME) were assessed to evaluate the system. The result shows that the system calculates risk adjusted discount rates (RADR) of projects in an objective way. These rates discount project cash flow impartially. Inconsistency of uncertainty is also successfully evaluated by the use of the entropy method. Finally, the system identifies the favourable funding options that are managed by a scheme called SME Loan Guarantee Scheme (SGS). Based on these results, resource allocation could then be optimized and the best time to start a new project could also be identified throughout the overall project life cycle.

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This article presents a prototype model based on a wireless sensor actuator network (WSAN) aimed at optimizing both energy consumption of environmental systems and well-being of occupants in buildings. The model is a system consisting of the following components: a wireless sensor network, `sense diaries', environmental systems such as heating, ventilation and air-conditioning systems, and a central computer. A multi-agent system (MAS) is used to derive and act on the preferences of the occupants. Each occupant is represented by a personal agent in the MAS. The sense diary is a new device designed to elicit feedback from occupants about their satisfaction with the environment. The roles of the components are: the WSAN collects data about physical parameters such as temperature and humidity from an indoor environment; the central computer processes the collected data; the sense diaries leverage trade-offs between energy consumption and well-being, in conjunction with the agent system; and the environmental systems control the indoor environment.

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The content of this paper is a snapshot of a current project looking at producing a real-time sensor-based building assessment tool, and a system that personalises workspaces using multi-agent technology. Both systems derive physical environment information from a wireless sensor network that allows clients to subscribe to real-time sensed data. The principal ideologies behind this project are energy efficiency and well-being of occupants; in the context of leveraging the current state-of-the-art in agent technology, wireless sensor networks and building assessment systems to enable the optimisation and assessment of buildings. Participants of this project are from both industry (construction and research) and academia.