838 resultados para network congestion control


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LOPES, Jose Soares Batista et al. Application of multivariable control using artificial neural networks in a debutanizer distillation column.In: INTERNATIONAL CONGRESS OF MECHANICAL ENGINEERING - COBEM, 19, 5-9 nov. 2007, Brasilia. Anais... Brasilia, 2007

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A multistate molecular dyad containing flavylium and viologen units was synthesized and the pH dependent thermodynamics of the network completely characterized by a variety of spectroscopic techniques such as NMR, UV-vis and stopped-flow. The flavylium cation is only stable at acidic pH values. Above pH ≈ 5 the hydration of the flavylium leads to the formation of the hemiketal followed by ring-opening tautomerization to give the cis-chalcone. Finally, this last species isomerizes to give the trans-chalcone. For the present system only the flavylium cation and the trans-chalcone species could be detected as being thermodynamically stable. The hemiketal and the cis-chalcone are kinetic intermediates with negligible concentrations at the equilibrium. All stable species of the network were found to form 1 : 1 and 2 : 1 host : guest complexes with cucurbit[7]uril (CB7) with association constants in the ranges 10(5)-10(8) M(-1) and 10(3)-10(4) M(-1), respectively. The 1 : 1 complexes were particularly interesting to devise pH responsive bistable pseudorotaxanes: at basic pH values (≈12) the flavylium cation interconverts into the deprotonated trans-chalcone in a few minutes and under these conditions the CB7 wheel was found to be located around the viologen unit. A decrease in pH to values around 1 regenerates the flavylium cation in seconds and the macrocycle is translocated to the middle of the axle. On the other hand, if the pH is decreased to 6, the deprotonated trans-chalcone is neutralized to give a metastable species that evolves to the thermodynamically stable flavylium cation in ca. 20 hours. By taking advantage of the pH-dependent kinetics of the trans-chalcone/flavylium interconversion, spatiotemporal control of the molecular organization in pseudorotaxane systems can be achieved.

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The recently developed network-wide real-time signal control strategy TUC has been implemented in three traffic networks with quite different traffic and control infrastructure characteristics: Chania, Greece (23 junctions); Southampton, UK (53 junctions); and Munich, Germany (25 junctions), where it has been compared to the respective resident real-time signal control strategies TASS, SCOOT and BALANCE. After a short outline of TUC, the paper describes the three application networks; the application, demonstration and evaluation conditions; as well as the comparative evaluation results. The main conclusions drawn from this high-effort inter-European undertaking is that TUC is an easy-to-implement, inter-operable, low-cost real-time signal control strategy whose performance, after very limited fine-tuning, proved to be better or, at least, similar to the ones achieved by long-standing strategies that were in most cases very well fine-tuned over the years in the specific networks.

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This paper describes how the recently developed network-wide real-time signal control strategy TUC has been implemented in three traffic networks with quite different traffic and control infrastructure characteristics: Chania, Greece (23 junctions); Southampton, U.K. (53 junctions); and Munich, Germany (25 junctions), where it has been compared to the respective resident real-time signal control strategies TASS, SCOOT and BALANCE. After a short outline of TUC, the paper describes the three application networks; the application, demonstration and evaluation conditions; as well as the comparative evaluation results. The main conclusions drawn from this high-effort inter-European undertaking is that TUC is an easy-to-implement, inter-operable, low-cost real-time signal control strategy whose performance, after limited fine-tuning, proved to be better or, at least, similar to the ones achieved by long-standing strategies that were in most cases very well fine-tuned over the years in the specific networks.

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This paper presents MOTION, a modular on-line model for urban traffic signal control. It consists of a network and a local level and builds on enhanced traffic state estimation. Special consideration is given to the prioritization of public transit. MOTION provides possibilities for the interaction with integrated urban management systems.

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Introducción: Determinar la eficacia de la administración preincisional de ropivacaína al 0,1 % intraperitoneal en el control del dolor abdominal y/o de hombro, durante la primera semana de la cirugía laparoscópica ginecológica benigna. Diseño: Ensayo clínico aleatorizado y doble ciego. Material y métodos: Se realizó un ensayo clínico aleatorizado y doble ciego donde participaron 64 pacientes ASA I-III sometidas a cirugía laparoscópica ginecológica por patología benigna. Tras la realización del neumoperitoneo, se administraron 100 ml de ropivacaína 0,1 % o suero fisiológico intraperitoneal, dependiendo del grupo al que pertenecieran. Las pacientes recibieron, además, AINE junto con una bomba de PCA con opción de morfina de rescate como analgesia multimodal asociada. Se evaluó el dolor abdominal y/o de hombro al despertar, en reposo y en movimiento, a los 5, 30, 60 y 120 minutos, así como a las 24 horas. Se registró el consumo de morfina en las primeras 24 horas y la incidencia de náuseas y/o vómitos postoperatorios. A la semana, mediante encuesta telefónica, se registró la presencia de dolor de hombro a partir de las 24 horas, así como de dolor abdominal persistente al 7º día. Resultados: No se observaron diferencias significativas en el ENV durante las primeras 24 horas. Tampoco se observaron diferencias en el consumo de morfina, en la incidencia de náuseas y/o vómitos o en el dolor de hombro. Se evidenciaron diferencias estadísticamente significativas en la incidencia de dolor abdominal persistente al 7º día (18,52 % en grupo tratamiento vs. 57,58 % en grupo control con p = 0,04). Conclusiones: La administración intraperitoneal preincisional de 100 ml de ropivacaína 0,1 % en comparación con la administración de suero fisiológico, en el contexto de una técnica anestésica y analgésica multimodal, no ha demostrado reducir el dolor postoperatorio, el consumo de opioides ni la incidencia de náuseas y vómitos postoperatorios en las primeras 24 horas. Tampoco ha demostrado reducción del dolor de hombro a partir del primer día tras cirugía laparoscópica ginecológica. El uso de ropivacaína al 0,1 % intraperitoneal preincisional presenta una disminución estadísticamente significativa en la incidencia de dolor abdominal persistente al séptimo día de postoperatorio.

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Travel demand models are important tools used in the analysis of transportation plans, projects, and policies. The modeling results are useful for transportation planners making transportation decisions and for policy makers developing transportation policies. Defining the level of detail (i.e., the number of roads) of the transport network in consistency with the travel demand model’s zone system is crucial to the accuracy of modeling results. However, travel demand modelers have not had tools to determine how much detail is needed in a transport network for a travel demand model. This dissertation seeks to fill this knowledge gap by (1) providing methodology to define an appropriate level of detail for a transport network in a given travel demand model; (2) implementing this methodology in a travel demand model in the Baltimore area; and (3) identifying how this methodology improves the modeling accuracy. All analyses identify the spatial resolution of the transport network has great impacts on the modeling results. For example, when compared to the observed traffic data, a very detailed network underestimates traffic congestion in the Baltimore area, while a network developed by this dissertation provides a more accurate modeling result of the traffic conditions. Through the evaluation of the impacts a new transportation project has on both networks, the differences in their analysis results point out the importance of having an appropriate level of network detail for making improved planning decisions. The results corroborate a suggested guideline concerning the development of a transport network in consistency with the travel demand model’s zone system. To conclude this dissertation, limitations are identified in data sources and methodology, based on which a plan of future studies is laid out.

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Ecological network analysis was applied in the Seine estuary ecosystem, northern France, integrating ecological data from the years 1996 to 2002. The Ecopath with Ecosim (EwE) approach was used to model the trophic flows in 6 spatial compartments leading to 6 distinct EwE models: the navigation channel and the two channel flanks in the estuary proper, and 3 marine habitats in the eastern Seine Bay. Each model included 12 consumer groups, 2 primary producers, and one detritus group. Ecological network analysis was performed, including a set of indices, keystoneness, and trophic spectrum analysis to describe the contribution of the 6 habitats to the Seine estuary ecosystem functioning. Results showed that the two habitats with a functioning most related to a stressed state were the northern and central navigation channels, where building works and constant maritime traffic are considered major anthropogenic stressors. The strong top-down control highlighted in the other 4 habitats was not present in the central channel, showing instead (i) a change in keystone roles in the ecosystem towards sediment-based, lower trophic levels, and (ii) a higher system omnivory. The southern channel evidenced the highest system activity (total system throughput), the higher trophic specialisation (low system omnivory), and the lowest indication of stress (low cycling and relative redundancy). Marine habitats showed higher fish biomass proportions and higher transfer efficiencies per trophic levels than the estuarine habitats, with a transition area between the two that presented intermediate ecosystem structure. The modelling of separate habitats permitted disclosing each one's response to the different pressures, based on their a priori knowledge. Network indices, although non-monotonously, responded to these differences and seem a promising operational tool to define the ecological status of transitional water ecosystems.

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The digital revolution of the 21st century contributed to stem the Internet of Things (IoT). Trillions of embedded devices using the Internet Protocol (IP), also called smart objects, will be an integral part of the Internet. In order to support such an extremely large address space, a new Internet Protocol, called Internet Protocol Version 6 (IPv6) is being adopted. The IPv6 over Low Power Wireless Personal Area Networks (6LoWPAN) has accelerated the integration of WSNs into the Internet. At the same time, the Constrained Application Protocol (CoAP) has made it possible to provide resource constrained devices with RESTful Web services functionalities. This work builds upon previous experience in street lighting networks, for which a proprietary protocol, devised by the Lighting Living Lab, was implemented and used for several years. The proprietary protocol runs on a broad range of lighting control boards. In order to support heterogeneous applications with more demanding communication requirements and to improve the application development process, it was decided to port the Contiki OS to the four channel LED driver (4LD) board from Globaltronic. This thesis describes the work done to adapt the Contiki OS to support the Microchip TM PIC24FJ128GA308 microprocessor and presents an IP based solution to integrate sensors and actuators in smart lighting applications. Besides detailing the system’s architecture and implementation, this thesis presents multiple results showing that the performance of CoAP based resource retrievals in constrained nodes is adequate for supporting networking services in street lighting networks.

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The function of a complex nervous system relies on an intricate interaction between neurons and glial cells. However, as glial cells are generally born distant from the place where they settle, molecular cues are important to direct their migration. Glial cell migration is important in both normal development and disease, thus current research in the laboratory has been focused on dissecting regulatory events underlying that crucial process. With this purpose, the Drosophila eye imaginal disc has been used as a model. In response to neuronal photoreceptor differentiation, glial cells migrate from the CNS into the eye disc where they act to correctly wrap axons. To ensure proper development, attractive and repulsive signals must coordinate glial cell migration. Importantly, one of these signals is Bnl, a Fibroblast Growth Factor (FGF) ligand expressed by retinal progenitor cells that was suggested to act as a non-autonomous negative regulator of excessive glial cell migration (overmigration) by binding and activating the Btl receptor expressed by glial cells. Through the experimental results described in chapter 3 we gained a detailed insight into the function of bnl in eye disc growth, photoreceptor development, and glia migration. Interestingly, we did not find a direct correlation between the defects on the ongoing photoreceptors and the glia overmigration phenotype; however, bnl knockdown caused apoptosis of eye progenitor cells what was strongly correlated with glia migration defects. Glia overmigration due to Bnl down-regulation in eye progenitor cells was rescued by inhibiting the pro-apoptotic genes or caspases activity, as well as, by depleting JNK or Dp53 function in retinal progenitor cells. Thus, we suggest a cross-talk between those developmental signals in the control of glia migration at a distance. Importantly, these results suggest that Bnl does not control glial migration in the eye disc exclusively through its ability to bind and activate its receptor Btl in glial cells. We also discuss possible biological roles for the glia overmigration in the bnl knockdown background. Previous results in the lab showed an interaction between dMyc, a master regulator of tissue growth, and Dpp, a Transforming Growth Factor-β important for retinal patterning and for accurate glia migration into the eye disc. Thus, we became interested in understanding putative relationships between Bnl and dMyc. In chapter 4, we show that they positively cooperate in order to ensure proper development of the eye disc. This work highlights the importance of the FGF signaling in eye disc development and reveals a signaling network where a range of extra- and intra-cellular signals cooperate to non-autonomously control glial cell migration. Therefore, such inter-relations could be important in other Drosophila cellular contexts, as well as in vertebrate tissue development.

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Jerne's idiotypic network theory postulates that the immune response involves inter-antibody stimulation and suppression as well as matching to antigens. The theory has proved the most popular Artificial Immune System (AIS) model for incorporation into behavior-based robotics but guidelines for implementing idiotypic selection are scarce. Furthermore, the direct effects of employing the technique have not been demonstrated in the form of a comparison with non-idiotypic systems. This paper aims to address these issues. A method for integrating an idiotypic AIS network with a Reinforcement Learning based control system (RL) is described and the mechanisms underlying antibody stimulation and suppression are explained in detail. Some hypotheses that account for the network advantage are put forward and tested using three systems with increasing idiotypic complexity. The basic RL, a simplified hybrid AIS-RL that implements idiotypic selection independently of derived concentration levels and a full hybrid AIS-RL scheme are examined. The test bed takes the form of a simulated Pioneer robot that is required to navigate through maze worlds detecting and tracking door markers.

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Jerne's idiotypic network theory postulates that the immune response involves inter-antibody stimulation and suppression as well as matching to antigens. The theory has proved the most popular Artificial Immune System (AIS) model for incorporation into behavior-based robotics but guidelines for implementing idiotypic selection are scarce. Furthermore, the direct effects of employing the technique have not been demonstrated in the form of a comparison with non-idiotypic systems. This paper aims to address these issues. A method for integrating an idiotypic AIS network with a Reinforcement Learning based control system (RL) is described and the mechanisms underlying antibody stimulation and suppression are explained in detail. Some hypotheses that account for the network advantage are put forward and tested using three systems with increasing idiotypic complexity. The basic RL, a simplified hybrid AIS-RL that implements idiotypic selection independently of derived concentration levels and a full hybrid AIS-RL scheme are examined. The test bed takes the form of a simulated Pioneer robot that is required to navigate through maze worlds detecting and tracking door markers.

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El presente trabajo empleó herramientas de hardware y software de licencia libre para el establecimiento de una estación base celular (BTS) de bajo costo y fácil implementación. Partiendo de conceptos técnicos que facilitan la instalación del sistema OpenBTS y empleando el hardware USRP N210 (Universal Software Radio Peripheral) permitieron desplegar una red análoga al estándar de telefonía móvil (GSM). Usando los teléfonos móviles como extensiones SIP (Session Initiation Protocol) desde Asterisk, logrando ejecutar llamadas entre los terminales, mensajes de texto (SMS), llamadas desde un terminal OpenBTS hacia otra operadora móvil, entre otros servicios.

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The majority of research work carried out in the field of Operations-Research uses methods and algorithms to optimize the pick-up and delivery problem. Most studies aim to solve the vehicle routing problem, to accommodate optimum delivery orders, vehicles etc. This paper focuses on green logistics approach, where existing Public Transport infrastructure capability of a city is used for the delivery of small and medium sized packaged goods thus, helping improve the situation of urban congestion and greenhouse gas emissions reduction. It carried out a study to investigate the feasibility of the proposed multi-agent based simulation model, for efficiency of cost, time and energy consumption. Multimodal Dijkstra Shortest Path algorithm and Nested Monte Carlo Search have been employed for a two-phase algorithmic approach used for generation of time based cost matrix. The quality of the tour is dependent on the efficiency of the search algorithm implemented for plan generation and route planning. The results reveal a definite advantage of using Public Transportation over existing delivery approaches in terms of energy efficiency.