787 resultados para Multiple routes planning
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Multiple-time signatures are digital signature schemes where the signer is able to sign a predetermined number of messages. They are interesting cryptographic primitives because they allow to solve many important cryptographic problems, and at the same time offer substantial efficiency advantage over ordinary digital signature schemes like RSA. Multiple-time signature schemes have found numerous applications, in ordinary, on-line/off-line, forward-secure signatures, and multicast/stream authentication. We propose a multiple-time signature scheme with very efficient signing and verifying. Our construction is based on a combination of one-way functions and cover-free families, and it is secure against the adaptive chosen-message attack.
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A new wave energy flow (WEF) map concept was proposed in this work. Based on it, an improved technique incorporating the laser scanning method and Betti’s reciprocal theorem was developed to evaluate the shape and size of damage as well as to realize visualization of wave propagation. In this technique, a simple signal processing algorithm was proposed to construct the WEF map when waves propagate through an inspection region, and multiple lead zirconate titanate (PZT) sensors were employed to improve inspection reliability. Various damages in aluminum and carbon fiber reinforced plastic laminated plates were experimentally and numerically evaluated to validate this technique. The results show that it can effectively evaluate the shape and size of damage from wave field variations around the damage in the WEF map.
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Spatially-explicit modelling of grassland classes is important to site-specific planning for improving grassland and environmental management over large areas. In this study, a climate-based grassland classification model, the Comprehensive and Sequential Classification System (CSCS) was integrated with spatially interpolated climate data to classify grassland in Gansu province, China. The study area is characterized by complex topographic features imposed by plateaus, high mountains, basins and deserts. To improve the quality of the interpolated climate data and the quality of the spatial classification over this complex topography, three linear regression methods, namely an analytic method based on multiple regression and residues (AMMRR), a modification of the AMMRR method through adding the effect of slope and aspect to the interpolation analysis (M-AMMRR) and a method which replaces the IDW approach for residue interpolation in M-AMMRR with an ordinary kriging approach (I-AMMRR), for interpolating climate variables were evaluated. The interpolation outcomes from the best interpolation method were then used in the CSCS model to classify the grassland in the study area. Climate variables interpolated included the annual cumulative temperature and annual total precipitation. The results indicated that the AMMRR and M-AMMRR methods generated acceptable climate surfaces but the best model fit and cross validation result were achieved by the I-AMMRR method. Twenty-six grassland classes were classified for the study area. The four grassland vegetation classes that covered more than half of the total study area were "cool temperate-arid temperate zonal semi-desert", "cool temperate-humid forest steppe and deciduous broad-leaved forest", "temperate-extra-arid temperate zonal desert", and "frigid per-humid rain tundra and alpine meadow". The vegetation classification map generated in this study provides spatial information on the locations and extents of the different grassland classes. This information can be used to facilitate government agencies' decision-making in land-use planning and environmental management, and for vegetation and biodiversity conservation. The information can also be used to assist land managers in the estimation of safe carrying capacities which will help to prevent overgrazing and land degradation.
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A variety of sustainable development research efforts and related activities are attempting to reconcile the issues of conserving our natural resources without limiting economic motivation while also improving our social equity and quality of life. Land use/land cover change, occurring on a global scale, is an aggregate of local land use decisions and profoundly impacts our environment. It is therefore the local decision making process that should be the eventual target of many of the ongoing data collection and research efforts which strive toward supporting a sustainable future. Satellite imagery data is a primary source of data upon which to build a core data set for use by researchers in analyzing this global change. A process is necessary to link global change research, utilizing satellite imagery, to the local land use decision making process. One example of this is the NASA-sponsored Regional Data Center (RDC) prototype. The RDC approach is an attempt to integrate science and technology at the community level. The anticipated result of this complex interaction between research and the decision making communities will be realized in the form of long-term benefits to the public.
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Objectives Given increasing trends of obesity being noted from early in life and that active lifestyles track across time, it is important that children at a very young age be active to combat a foundation of unhealthy behaviours forming. This study investigated, within a theory of planned behaviour (TPB) framework, factors which influence mothers’ decisions about their child’s 1) adequate physical activity (PA) and 2) limited screen time behaviours. Methods Mothers (N = 162) completed a main questionnaire, via on-line or paper-based administration, which comprised standard TPB items in addition to measures of planning and background demographic variables. One week later, consenting mothers completed a follow-up telephone questionnaire which assessed the decisions they had made regarding their child’s PA and screen time behaviours during the previous week. Results Hierarchical multiple regression analyses revealed support for the predictive model, explaining an overall 73% and 78% of the variance in mothers’ intention and 38% and 53% of the variance in mothers’ decisions to ensure their child engages in adequate PA and limited screen time, respectively. Attitude and subjective norms predicted intention in both target behaviours, as did intentions with behaviour. Contrary to predictions, perceived behavioural control (PBC) in PA behaviour and planning in screen time behaviour were not significant predictors of intention, neither was PBC a predictor of either behaviour. Conclusions The findings illustrate the various roles that psycho-social factors play in mothers’ decisions to ensure their child engages in active lifestyle behaviours which can help to inform future intervention programs aimed at combating very young children’s inactivity.
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Given the increased importance of adaptation debates in global climate negotiations, pressure to achieve biodiversity, food and water security through managed landscape-scale adaptation will likely increase across the globe over the coming decade. In parallel, emerging market-based, terrestrial greenhouse gas abatement programs present a real opportunity to secure such adaptation to climate change through enhanced landscape resilience. Australia has an opportunity to take advantage of such programs through regional planning aspects of its governance arrangements for NRM. This paper explores necessary reforms to Australia's regional NRM planning systems to ensure that they will be better able to direct the nation's emerging GGA programs to secure enhanced landscape adaptation. © 2013 Planning Institute Australia.
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A multi-secret sharing scheme allows several secrets to be shared amongst a group of participants. In 2005, Shao and Cao developed a verifiable multi-secret sharing scheme where each participant’s share can be used several times which reduces the number of interactions between the dealer and the group members. In addition some secrets may require a higher security level than others involving the need for different threshold values. Recently Chan and Chang designed such a scheme but their construction only allows a single secret to be shared per threshold value. In this article we combine the previous two approaches to design a multiple time verifiable multi-secret sharing scheme where several secrets can be shared for each threshold value. Since the running time is an important factor for practical applications, we will provide a complexity comparison of our combined approach with respect to the previous schemes.
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Planning techniques for large scale earthworks have been considered in this article. To improve these activities a “block theoretic” approach was developed that provides an integrated solution consisting of an allocation of cuts to fills and a sequence of cuts and fills over time. It considers the constantly changing terrain by computing haulage routes dynamically. Consequently more realistic haulage costs are used in the decision making process. A digraph is utilised to describe the terrain surface which has been partitioned into uniform grids. It reflects the true state of the terrain, and is altered after each cut and fill. A shortest path algorithm is successively applied to calculate the cost of each haul, and these costs are summed over the entire sequence, to provide a total cost of haulage. To solve this integrated optimisation problem a variety of solution techniques were applied, including constructive algorithms, meta-heuristics and parallel programming. The extensive numerical investigations have successfully shown the applicability of our approach to real sized earthwork problems.
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The role of law in managing public health challenges such as influenza pandemics poses special challenges. This article reviews Australian plans in the context of the H1N1 09 experience to assess whether risk management was facilitated or inhibited by the "number" of levels or phases of management, the degree of prescriptive detail for particular phases, the number of plans, the clarity of the relationship between them, and the role of the media. Despite differences in the content and form of the plans at the time of the H1N1 09 emerging pandemic, the article argues that in practice, the plans proved to be responsive and robust bases for managing pandemic risks. It is suggested that this was because the plans proved to be frameworks for coordination rather than prescriptive straitjackets, to be only one component of the regulatory response, and to offer the varied tool box of possible responses, as called for by the theory of responsive regulation. Consistent with the principle of subsidiarity, it is argued that the plans did not inhibit localised responses such as selective school closures or rapid responses to selected populations such as cruise ship passengers.
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The interest in utilising multiple heterogeneous Unmanned Aerial Vehicles (UAVs) in close proximity is growing rapidly. As such, many challenges are presented in the effective coordination and management of these UAVs; converting the current n-to-1 paradigm (n operators operating a single UAV) to the 1-to-n paradigm (one operator managing n UAVs). This paper introduces an Information Abstraction methodology used to produce the functional capability framework initially proposed by Chen et al. and its Level Of Detail (LOD) indexing scale. This framework was validated through comparing the operator workload and Situation Awareness (SA) of three experiment scenarios involving multiple autonomously heterogeneous UAVs. The first scenario was set in a high LOD configuration with highly abstracted UAV functional information; the second scenario was set in a mixed LOD configuration; and the final scenario was set in a low LOD configuration with maximal UAV functional information. Results show that there is a significant statistical decrease in operator workload when a UAV’s functional information is displayed at its physical form (low LOD - maximal information) when comparing to the mixed LOD configuration.
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Introduction This study investigated the sensitivity of calculated stereotactic radiotherapy and radiosurgery doses to the accuracy of the beam data used by the treatment planning system. Methods Two sets of field output factors were acquired using fields smaller than approximately 1 cm2, for inclusion in beam data used by the iPlan treatment planning system (Brainlab, Feldkirchen, Germany). One set of output factors were measured using an Exradin A16 ion chamber (Standard Imaging, Middleton, USA). Although this chamber has a relatively small collecting volume (0.007 cm3), measurements made in small fields using this chamber are subject to the effects of volume averaging, electronic disequilibrium and chamber perturbations. The second, more accurate, set of measurements were obtained by applying perturbation correction factors, calculated using Monte Carlo simulations according to a method recommended by Cranmer-Sargison et al. [1] to measurements made using a 60017 unshielded electron diode (PTW, Freiburg, Germany). A series of 12 sample patient treatments were used to investigate the effects of beam data accuracy on resulting planned dose. These treatments, which involved 135 fields, were planned for delivery via static conformal arcs and 3DCRT techniques, to targets ranging from prostates (up to 8 cm across) to meningiomas (usually more than 2 cm across) to arterioveinous malformations, acoustic neuromas and brain metastases (often less than 2 cm across). Isocentre doses were calculated for all of these fields using iPlan, and the results of using the two different sets of beam data were evaluated. Results While the isocentre doses for many fields are identical (difference = 0.0 %), there is a general trend for the doses calculated using the data obtained from corrected diode measurements to exceed the doses calculated using the less-accurate Exradin ion chamber measurements (difference\0.0 %). There are several alarming outliers (circled in the Fig. 1) where doses differ by more than 3 %, in beams from sample treatments planned for volumes up to 2 cm across. Discussion and conclusions These results demonstrate that treatment planning dose calculations for SRT/SRS treatments can be substantially affected when beam data for fields smaller than approximately 1 cm2 are measured inaccurately, even when treatment volumes are up to 2 cm across.
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Mutations in the genes encoding for either the biosynthetic or transcriptional regulation of the anthocyanin pathway have been linked to color phenotypes. Generally, this is a loss of function resulting in a reduction or a change in the distribution of anthocyanin. Here, we describe a rearrangement in the upstream regulatory region of the gene encoding an apple (Malus x domestica) anthocyanin-regulating transcription factor, MYB10. We show that this modification is responsible for increasing the level of anthocyanin throughout the plant to produce a striking phenotype that includes red foliage and red fruit flesh. This rearrangement is a series of multiple repeats, forming a minisatellite-like structure that comprises five direct tandem repeats of a 23-bp sequence. This MYB10 rearrangement is present in all the red foliage apple varieties and species tested but in none of the white fleshed varieties. Transient assays demonstrated that the 23-bp sequence motif is a target of the MYB10 protein itself, and the number of repeat units correlates with an increase in transactivation by MYB10 protein. We show that the repeat motif is capable of binding MYB10 protein in electrophoretic mobility shift assays. Taken together, these results indicate that an allelic rearrangement in the promoter of MYB10 has generated an autoregulatory locus, and this autoregulation is sufficient to account for the increase in MYB10 transcript levels and subsequent ectopic accumulation of anthocyanins throughout the plant.
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This paper presents a novel framework to further advance the recent trend of using query decomposition and high-order term relationships in query language modeling, which takes into account terms implicitly associated with different subsets of query terms. Existing approaches, most remarkably the language model based on the Information Flow method are however unable to capture multiple levels of associations and also suffer from a high computational overhead. In this paper, we propose to compute association rules from pseudo feedback documents that are segmented into variable length chunks via multiple sliding windows of different sizes. Extensive experiments have been conducted on various TREC collections and our approach significantly outperforms a baseline Query Likelihood language model, the Relevance Model and the Information Flow model.