780 resultados para Bound Algorithm


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The Lanczos algorithm is appreciated in many situations due to its speed. and economy of storage. However, the advantage that the Lanczos basis vectors need not be kept is lost when the algorithm is used to compute the action of a matrix function on a vector. Either the basis vectors need to be kept, or the Lanczos process needs to be applied twice. In this study we describe an augmented Lanczos algorithm to compute a dot product relative to a function of a large sparse symmetric matrix, without keeping the basis vectors.

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This article presents Monte Carlo techniques for estimating network reliability. For highly reliable networks, techniques based on graph evolution models provide very good performance. However, they are known to have significant simulation cost. An existing hybrid scheme (based on partitioning the time space) is available to speed up the simulations; however, there are difficulties with optimizing the important parameter associated with this scheme. To overcome these difficulties, a new hybrid scheme (based on partitioning the edge set) is proposed in this article. The proposed scheme shows orders of magnitude improvement of performance over the existing techniques in certain classes of network. It also provides reliability bounds with little overhead.

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The volume of the primary (PCS) and secondary (SCS) circulatory system in the Atlantic cod Gadus morhua was determined using a modified dye dilution technique. Cod (N=10) were chronically cannulated in the second afferent branchial artery with PE-50 tubing. Evans Blue dye was bound to harvested fish plasma at a concentration of 1 mg dye ml(-1) plasma, and injected at a concentration of 1 mg kg(-1) body mass. Serial sampling from the cannula produced a dye dilution curve, which could be described by a double exponential decay equation. Curve analysis enabled the calculation of the primary circulatory and total distribution volume. The difference between these volumes is assumed to be the volume of the SCS. From the dilution curve, it was also possible to calculate flow rates between and within the systems. The results of these experiments suggest a plasma volume in the PCS of 3.42+/-0.89 ml 100 g(-1) body mass, and in the SCS of 1.68+/-0.35 ml 100 g(-1) body mass (mean +/- S.D.) or approximately 50% that of the PCS. Flow rates to the SCS were calculated as 2.7% of the resting cardiac output. There was an allometric relationship between body mass and blood volumes. Increasing condition factor showed a tendency towards smaller blood volumes of the PCS, expressed as percentage body mass, but this was not evident for the volume of the SCS.

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Three new peptidomimetics (1-3) have been developed with highly stable and conformationally constrained macrocyclic components that replace tripeptide segments of protease substrates. Each compound inhibits both HIV-1 protease and viral replication (HIV-I, HIV-2) at nanomolar concentrations without cytotoxicity to uninfected cells below 10 mu M. Their activities against HIV-1 protease (K-i 1.7 nM (1), 0.6 nM (2), 0.3 nM (3)) are 1-2 orders of magnitude greater than their antiviral potencies against HIV-1-infected primary peripheral blood mononuclear cells (IC50 45 nM (1), 56 nM (2), 95 nM (3)) or HIV-1-infected MT2 cells (IC50 90 nM (1), 60 nM (2)), suggesting suboptimal cellular uptake. However their antiviral potencies are similar to those of indinavir and amprenavir under identical conditions. There were significant differences in their capacities to inhibit the replication of HIV-1 and HIV-2 in infected MT2 cells, 1 being ineffective against HIV-2 while 2 was equally effective against both virus types. Evidence is presented that 1 and 2 inhibit cleavage of the HIV-1 structural protein precursor Pr55(gag) to p24 in virions derived from chronically infected cells, consistent with inhibition of the viral protease in cells. Crystal structures refined to 1.75 Angstrom (1) and 1.85 Angstrom (2) for two of the macrocyclic inhibitors bound to HIV-1 protease establish structural mimicry of the tripeptides that the cycles were designed to imitate. Structural comparisons between protease-bound macrocyclic inhibitors, VX478 (amprenavir), and L-735,524 (indinavir) show that their common acyclic components share the same space in the active site of the enzyme and make identical interactions with enzyme residues. This substrate-mimicking minimalist approach to drug design could have benefits in the context of viral resistance, since mutations which induce inhibitor resistance may also be those which prevent substrate processing.

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Bound and resonance states of HO2 have been calculated quantum mechanically by the Lanczos homogeneous filter diagonalization method [Zhang and Smith, Phys. Chem. Chem. Phys. 3, 2282 (2001); J. Chem. Phys. 115, 5751 (2001)] for nonzero total angular momentum J = 1,2,3. For lower bound states, agreement between the results in this paper and previous work is quite satisfactory; while for high lying bound states and resonances these are the first reported results. A helicity quantum number V assignment (within the helicity conserving approximation) is performed and the results indicate that for lower bound states it is possible to assign the V quantum numbers unambiguously, but for resonances it is impossible to assign the V helicity quantum numbers due to strong mixing. In fact, for the high-lying bound states, the mixing has already appeared. These results indicate that the helicity conserving approximation is not good for the resonance state calculations and exact quantum calculations are needed to accurately describe the reaction dynamics for HO2 system. Analysis of the resonance widths shows that most of the resonances are overlapping and the interferences between them lead to large fluctuations from one resonance to another. In accord with the conclusions from earlier J = 0 calculations, this indicates that the dissociation of HO2 is essentially irregular. (C) 2003 American Institute of Physics.

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A Combined Genetic Algorithm and Method of Moments design methods is presented for the design of unusual near-field antennas for use in Magnetic Resonance Imaging systems. The method is successfully applied to the design of an asymmetric coil structure for use at 190MHz and demonstrates excellent radiofrequency field homogeneity.

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Many organisations need to extract useful information from huge amounts of movement data. One example is found in maritime transportation, where the automated identification of a diverse range of traffic routes is a key management issue for improving the maintenance of ports and ocean routes, and accelerating ship traffic. This paper addresses, in a first stage, the research challenge of developing an approach for the automated identification of traffic routes based on clustering motion vectors rather than reconstructed trajectories. The immediate benefit of the proposed approach is to avoid the reconstruction of trajectories in terms of their geometric shape of the path, their position in space, their life span, and changes of speed, direction and other attributes over time. For clustering the moving objects, an adapted version of the Shared Nearest Neighbour algorithm is used. The motion vectors, with a position and a direction, are analysed in order to identify clusters of vectors that are moving towards the same direction. These clusters represent traffic routes and the preliminary results have shown to be promising for the automated identification of traffic routes with different shapes and densities, as well as for handling noise data.

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Quantitative analysis of cine cardiac magnetic resonance (CMR) images for the assessment of global left ventricular morphology and function remains a routine task in clinical cardiology practice. To date, this process requires user interaction and therefore prolongs the examination (i.e. cost) and introduces observer variability. In this study, we sought to validate the feasibility, accuracy, and time efficiency of a novel framework for automatic quantification of left ventricular global function in a clinical setting.

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5th. European Congress on Computational Methods in Applied Sciences and Engineering (ECCOMAS 2008) 8th. World Congress on Computational Mechanics (WCCM8)

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This paper presents an algorithm to efficiently generate the state-space of systems specified using the IOPT Petri-net modeling formalism. IOPT nets are a non-autonomous Petri-net class, based on Place-Transition nets with an extended set of features designed to allow the rapid prototyping and synthesis of system controllers through an existing hardware-software co-design framework. To obtain coherent and deterministic operation, IOPT nets use a maximal-step execution semantics where, in a single execution step, all enabled transitions will fire simultaneously. This fact increases the resulting state-space complexity and can cause an arc "explosion" effect. Real-world applications, with several million states, will reach a higher order of magnitude number of arcs, leading to the need for high performance state-space generator algorithms. The proposed algorithm applies a compilation approach to read a PNML file containing one IOPT model and automatically generate an optimized C program to calculate the corresponding state-space.

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In recent years the use of several new resources in power systems, such as distributed generation, demand response and more recently electric vehicles, has significantly increased. Power systems aim at lowering operational costs, requiring an adequate energy resources management. In this context, load consumption management plays an important role, being necessary to use optimization strategies to adjust the consumption to the supply profile. These optimization strategies can be integrated in demand response programs. The control of the energy consumption of an intelligent house has the objective of optimizing the load consumption. This paper presents a genetic algorithm approach to manage the consumption of a residential house making use of a SCADA system developed by the authors. Consumption management is done reducing or curtailing loads to keep the power consumption in, or below, a specified energy consumption limit. This limit is determined according to the consumer strategy and taking into account the renewable based micro generation, energy price, supplier solicitations, and consumers’ preferences. The proposed approach is compared with a mixed integer non-linear approach.

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To maintain a power system within operation limits, a level ahead planning it is necessary to apply competitive techniques to solve the optimal power flow (OPF). OPF is a non-linear and a large combinatorial problem. The Ant Colony Search (ACS) optimization algorithm is inspired by the organized natural movement of real ants and has been successfully applied to different large combinatorial optimization problems. This paper presents an implementation of Ant Colony optimization to solve the OPF in an economic dispatch context. The proposed methodology has been developed to be used for maintenance and repairing planning with 48 to 24 hours antecipation. The main advantage of this method is its low execution time that allows the use of OPF when a large set of scenarios has to be analyzed. The paper includes a case study using the IEEE 30 bus network. The results are compared with other well-known methodologies presented in the literature.

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This paper presents a Unit Commitment model with reactive power compensation that has been solved by Genetic Algorithm (GA) optimization techniques. The GA has been developed a computational tools programmed/coded in MATLAB. The main objective is to find the best generations scheduling whose active power losses are minimal and the reactive power to be compensated, subjected to the power system technical constraints. Those are: full AC power flow equations, active and reactive power generation constraints. All constraints that have been represented in the objective function are weighted with a penalty factors. The IEEE 14-bus system has been used as test case to demonstrate the effectiveness of the proposed algorithm. Results and conclusions are dully drawn.

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Electricity market players operating in a liberalized environment requires access to an adequate decision support tool, allowing them to consider all the business opportunities and take strategic decisions. Ancillary services represent a good negotiation opportunity that must be considered by market players. For this, decision support tools must include ancillary market simulation. This paper proposes two different methods (Linear Programming and Genetic Algorithm approaches) for ancillary services dispatch. The methodologies are implemented in MASCEM, a multi-agent based electricity market simulator. A test case concerning the dispatch of Regulation Down, Regulation Up, Spinning Reserve and Non-Spinning Reserve services is included in this paper.