954 resultados para Hamiltonian centers


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Port-Hamiltonian Systems (PHS) have a particular form that incorporates explicitly a function of the total energy in the system (energy function) and also other functions that describe structure of the system in terms of energy distribution. For PHS, the product of the input and output variables gives the rate of energy change. This type of systems have the property that under certain conditions on the energy function, the system is passive; and thus, stable. Therefore, if one can design a controller such that the closed-loop system retains - or takes - a PHS form, such closed-loop system will inherit the properties of passivity and stability. In this paper, the classical model of marine craft is put into a PHS form. It is shown that models used for positioning control do not have a PHS form due to a kinematic transformation, but a control design can be done such that the closed-loop system takes a PHS form. It is further shown how integral action can be added and how the PHS-form can be exploited to provide a procedure for control design that ensures passivity and thus stability.

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OBJECTIVES To describe protocol and interobserver agreements of an instrument to evaluate nutrition and physical activity environments at child care. METHODS Interobserver data were collected from 9 child care centers, through direct observation and document review (17 observer pairs). RESULTS Mean agreement between observer pairs was 87.26% and 79.29% for the observation and document review, respectively. Items with lower agreement were primarily staff behavior, counting across the day/week, and policy classifications. CONCLUSIONS Although some revisions are required, the interobserver agreement for the environment and policy assessment and observation (EPAO instrument) appears to be quite good for assessing the nutrition and physical activity environment of child care centers.

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Live migration of multiple Virtual Machines (VMs) has become an integral management activity in data centers for power saving, load balancing and system maintenance. While state-of-the-art live migration techniques focus on the improvement of migration performance of an independent single VM, only a little has been investigated to the case of live migration of multiple interacting VMs. Live migration is mostly influenced by the network bandwidth and arbitrarily migrating a VM which has data inter-dependencies with other VMs may increase the bandwidth consumption and adversely affect the performances of subsequent migrations. In this paper, we propose a Random Key Genetic Algorithm (RKGA) that efficiently schedules the migration of a given set of VMs accounting both inter-VM dependency and data center communication network. The experimental results show that the RKGA can schedule the migration of multiple VMs with significantly shorter total migration time and total downtime compared to a heuristic algorithm.

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In the past few years, there has been a steady increase in the attention, importance and focus of green initiatives related to data centers. While various energy aware measures have been developed for data centers, the requirement of improving the performance efficiency of application assignment at the same time has yet to be fulfilled. For instance, many energy aware measures applied to data centers maintain a trade-off between energy consumption and Quality of Service (QoS). To address this problem, this paper presents a novel concept of profiling to facilitate offline optimization for a deterministic application assignment to virtual machines. Then, a profile-based model is established for obtaining near-optimal allocations of applications to virtual machines with consideration of three major objectives: energy cost, CPU utilization efficiency and application completion time. From this model, a profile-based and scalable matching algorithm is developed to solve the profile-based model. The assignment efficiency of our algorithm is then compared with that of the Hungarian algorithm, which does not scale well though giving the optimal solution.

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This study focuses on designing a community environment education center (CEEC) for Chillingham, as a hub for community transition to sustainability, redressing social fragmentation, youth unemployment, a high eco-footprint and economic rural decline due to globalisation. The ecologically sustainable development framework was delivered by integrating environment education and community development through project-based experiential learning. The development of Chillingham Community Centre involved case study research and incorporated participatory design charrettes, transformative learning, eco-positive development and community-public-private partnerships. This process evolved from community strategic planning in a small rural village buffering world heritage rainforests impacted by a rapidly expanding urban conurbation on Australia’s east coast. This community space encompasses socio-environmental flows connecting people to each other and the ecoscape to grow natural capital, community cohesion and empower eco-governance. Modelling passive solar design, on-site renewable energy/water/nutrient cycling, community garden/market and environment education programs sowed the seeds for a green local economy, demonstrating community capacity to participate in transition to sustainability. A small rural community can demonstrate to other communities that a CEEC enables people to meet their socio-environmental and economic needs locally and sustainably. The ecologically sustainable solution is holistic, all settlements need to be richly biodiverse, locally specific and globally wise.

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This paper presents a trajectory-tracking control strategy for a class of mechanical systems in Hamiltonian form. The class is characterised by a simplectic interconnection arising from the use of generalised coordinates and full actuation. The tracking error dynamic is modelled as a port-Hamiltonian Systems (PHS). The control action is designed to take the error dynamics into a desired closed-loop PHS characterised by a constant mass matrix and a potential energy with a minimum at the origin. A transformation of the momentum and a feedback control is exploited to obtain a constant generalised mass matrix in closed loop. The stability of the close-loop system is shown using the close-loop Hamiltonian as a Lyapunov function. The paper also considers the addition of integral action to design a robust controller that ensures tracking in spite of disturbances. As a case study, the proposed control design methodology is applied to a fully actuated robotic manipulator.

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The increase in data center dependent services has made energy optimization of data centers one of the most exigent challenges in today's Information Age. The necessity of green and energy-efficient measures is very high for reducing carbon footprint and exorbitant energy costs. However, inefficient application management of data centers results in high energy consumption and low resource utilization efficiency. Unfortunately, in most cases, deploying an energy-efficient application management solution inevitably degrades the resource utilization efficiency of the data centers. To address this problem, a Penalty-based Genetic Algorithm (GA) is presented in this paper to solve a defined profile-based application assignment problem whilst maintaining a trade-off between the power consumption performance and resource utilization performance. Case studies show that the penalty-based GA is highly scalable and provides 16% to 32% better solutions than a greedy algorithm.

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In the past few years, the virtual machine (VM) placement problem has been studied intensively and many algorithms for the VM placement problem have been proposed. However, those proposed VM placement algorithms have not been widely used in today's cloud data centers as they do not consider the migration cost from current VM placement to the new optimal VM placement. As a result, the gain from optimizing VM placement may be less than the loss of the migration cost from current VM placement to the new VM placement. To address this issue, this paper presents a penalty-based genetic algorithm (GA) for the VM placement problem that considers the migration cost in addition to the energy-consumption of the new VM placement and the total inter-VM traffic flow in the new VM placement. The GA has been implemented and evaluated by experiments, and the experimental results show that the GA outperforms two well known algorithms for the VM placement problem.

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Although live VM migration has been intensively studied, the problem of live migration of multiple interdependent VMs has hardly been investigated. The most important problem in the live migration of multiple interdependent VMs is how to schedule VM migrations as the schedule will directly affect the total migration time and the total downtime of those VMs. Aiming at minimizing both the total migration time and the total downtime simultaneously, this paper presents a Strength Pareto Evolutionary Algorithm 2 (SPEA2) for the multi-VM migration scheduling problem. The SPEA2 has been evaluated by experiments, and the experimental results show that the SPEA2 can generate a set of VM migration schedules with a shorter total migration time and a shorter total downtime than an existing genetic algorithm, namely Random Key Genetic Algorithm (RKGA). This paper also studies the scalability of the SPEA2.

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Art museums are playing an important role is attracting cultural tourists to global cities and regions. Traditionally, art museums were primarily known for their didactic role. In a post-avant-garde era however museums are more focused on appealing to a broader clientele that want art to be novel and entertaining. Art museums have also come to play a greater role in gentrification projects and cultural precincts. This is because they are ideally suited for tourist-centric environments that offer a variety of immersive sensory experiences, and combine museums (often designed by star-architects), international hotels, restaurants, high-end shopping zones, and other leisure platforms. These "experiencescapes" include Port Maravilha urban waterfront development in Rio de Janiero, the Shanghai Bund, and the Broad project in Los Angeles. The Museum of Old and New Art in Hobart Australia is a boutique player in the global market for experiencescapes. It is smaller than many of its competitors and is situated in a remote part of the world, yet it has made an important contribution to Tasmania’s tourism industry.

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We propose a new scheme for the use of constraints in setting up classical, Hamiltonian, relativistic, interacting particle theories. We show that it possesses both Poincaré invariance and invariance of world lines. We discuss the transition to the physical phase space and the nonrelativistic limit.

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The problem of separability in recent models of classical relativistic interacting particles is examined. This physical requirement is shown to be more subtle than naive separability of all the constraints defining the system: it is adequate to be able to canonically transform the time-fixing constraints from an unseparated to a separated form when clusters emerge. Viewing separability in this way, and within a specific framework, we are led to a new no-interaction theorem which states the incompatibility of nontrivial interaction with relativistic invariance, separability, and invariant world lines for more than two particles.

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This paper reports on the liquid-helium-temperature (5 K) electron paramagnetic resonance (EPR) spectra of Cr3+ ions in the nanoparticles of SnO2 synthesized at 600 degrees C with concentrations of 0%, 0.1%, 0.5%, 1%, 1.5%, 2.0%, 2.5%, 3.0%, 5.0%, and 10%. Each spectrum may be simulated as overlap of spectra due to four magnetically inequivalent Cr3+ centers characterized by different values of the spin-Hamiltonian parameters. Three of these centers belong to Cr3+ ions in orthorhombic sites, situated near oxygen vacancies, characterized by very large zero-field splitting parameters D and E, presumably due to the presence of nanoparticles in the samples. The fourth EPR spectrum belongs to the Cr3+ ions situated at sites with tetragonal symmetry, substituting for the Sn4+ ion, characterized by a very small value of D. In addition, there appears a ferromagnetic resonance line due to oxygen defects for samples with Cr3+ concentrations of <= 2.5%. Further, in samples with Cr3+ concentrations of >2.5%, there appears an intense and wide EPR line due to the interactions among the Cr3+ ions in the clusters formed due to rather excessive doping; the intensity and width of this line increase with increasing concentration. The Cr3+ EPR spectra observed in these nanopowders very different from those in bulk SnO2 crystals.

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Accurate extrapolations for the ground state energy per site of the one - dimensional Kondo chain system is obtained from exact finite system calculations carried out employing a valence bond scheme. An analysis of the ground state wave function indicates that the localized spin is quenched for all nonzero values of the Kondo exchange constant in one dimension.

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A general analysis of symmetries and constraints for singular Lagrangian systems is given. It is shown that symmetry transformations can be expressed as canonical transformations in phase space, even for such systems. The relation of symmetries to generators, constraints, commutators, and Dirac brackets is clarified.