137 resultados para distributed constraint satisfaction


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Flash floods pose a significant danger for life and property. Unfortunately, in arid and semiarid environment the runoff generation shows a complex non-linear behavior with a strong spatial and temporal non-uniformity. As a result, the predictions made by physically-based simulations in semiarid areas are subject to great uncertainty, and a failure in the predictive behavior of existing models is common. Thus better descriptions of physical processes at the watershed scale need to be incorporated into the hydrological model structures. For example, terrain relief has been systematically considered static in flood modelling at the watershed scale. Here, we show that the integrated effect of small distributed relief variations originated through concurrent hydrological processes within a storm event was significant on the watershed scale hydrograph. We model these observations by introducing dynamic formulations of two relief-related parameters at diverse scales: maximum depression storage, and roughness coefficient in channels. In the final (a posteriori) model structure these parameters are allowed to be both time-constant or time-varying. The case under study is a convective storm in a semiarid Mediterranean watershed with ephemeral channels and high agricultural pressures (the Rambla del Albujón watershed; 556 km 2 ), which showed a complex multi-peak response. First, to obtain quasi-sensible simulations in the (a priori) model with time-constant relief-related parameters, a spatially distributed parameterization was strictly required. Second, a generalized likelihood uncertainty estimation (GLUE) inference applied to the improved model structure, and conditioned to observed nested hydrographs, showed that accounting for dynamic relief-related parameters led to improved simulations. The discussion is finally broadened by considering the use of the calibrated model both to analyze the sensitivity of the watershed to storm motion and to attempt the flood forecasting of a stratiform event with highly different behavior.

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This paper aims to consider whether there is a link between youth happiness levels and adult life satisfaction. Our results are unequivocal that such a link exists both because demographic and socio-economic conditions are persistent over a lifetime and also because there is a persistence in personality effects. To test this link, we estimate a model of happiness for a sample of young people. This model provides us with a range of variables measuring socio-economic effects and personality effects amongst young people. These variables are then included in the adult life satisfaction model. The model is estimated using data from the British Household Panel Survey for 1994–2008. In addition to childhood happiness levels influencing adult life satisfaction significantly, we also find that the youthful personality trait for happiness has a larger effect on adult life satisfaction than demographic and socio-economic conditions.

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Highly heterogeneous mountain snow distributions strongly affect soil moisture patterns; local ecology; and, ultimately, the timing, magnitude, and chemistry of stream runoff. Capturing these vital heterogeneities in a physically based distributed snow model requires appropriately scaled model structures. This work looks at how model scale—particularly the resolutions at which the forcing processes are represented—affects simulated snow distributions and melt. The research area is in the Reynolds Creek Experimental Watershed in southwestern Idaho. In this region, where there is a negative correlation between snow accumulation and melt rates, overall scale degradation pushed simulated melt to earlier in the season. The processes mainly responsible for snow distribution heterogeneity in this region—wind speed, wind-affected snow accumulations, thermal radiation, and solar radiation—were also independently rescaled to test process-specific spatiotemporal sensitivities. It was found that in order to accurately simulate snowmelt in this catchment, the snow cover needed to be resolved to 100 m. Wind and wind-affected precipitation—the primary influence on snow distribution—required similar resolution. Thermal radiation scaled with the vegetation structure (~100 m), while solar radiation was adequately modeled with 100–250-m resolution. Spatiotemporal sensitivities to model scale were found that allowed for further reductions in computational costs through the winter months with limited losses in accuracy. It was also shown that these modeling-based scale breaks could be associated with physiographic and vegetation structures to aid a priori modeling decisions.

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In this paper, we develop an energy-efficient resource-allocation scheme with proportional fairness for downlink multiuser orthogonal frequency-division multiplexing (OFDM) systems with distributed antennas. Our aim is to maximize energy efficiency (EE) under the constraints of the overall transmit power of each remote access unit (RAU), proportional fairness data rates, and bit error rates (BERs). Because of the nonconvex nature of the optimization problem, obtaining the optimal solution is extremely computationally complex. Therefore, we develop a low-complexity suboptimal algorithm, which separates subcarrier allocation and power allocation. For the low-complexity algorithm, we first allocate subcarriers by assuming equal power distribution. Then, by exploiting the properties of fractional programming, we transform the nonconvex optimization problem in fractional form into an equivalent optimization problem in subtractive form, which includes a tractable solution. Next, an optimal energy-efficient power-allocation algorithm is developed to maximize EE while maintaining proportional fairness. Through computer simulation, we demonstrate the effectiveness of the proposed low-complexity algorithm and illustrate the fundamental trade off between energy and spectral-efficient transmission designs.

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The Mobile Network Optimization (MNO) technologies have advanced at a tremendous pace in recent years. And the Dynamic Network Optimization (DNO) concept emerged years ago, aimed to continuously optimize the network in response to variations in network traffic and conditions. Yet, DNO development is still at its infancy, mainly hindered by a significant bottleneck of the lengthy optimization runtime. This paper identifies parallelism in greedy MNO algorithms and presents an advanced distributed parallel solution. The solution is designed, implemented and applied to real-life projects whose results yield a significant, highly scalable and nearly linear speedup up to 6.9 and 14.5 on distributed 8-core and 16-core systems respectively. Meanwhile, optimization outputs exhibit self-consistency and high precision compared to their sequential counterpart. This is a milestone in realizing the DNO. Further, the techniques may be applied to similar greedy optimization algorithm based applications.

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It has been years since the introduction of the Dynamic Network Optimization (DNO) concept, yet the DNO development is still at its infant stage, largely due to a lack of breakthrough in minimizing the lengthy optimization runtime. Our previous work, a distributed parallel solution, has achieved a significant speed gain. To cater for the increased optimization complexity pressed by the uptake of smartphones and tablets, however, this paper examines the potential areas for further improvement and presents a novel asynchronous distributed parallel design that minimizes the inter-process communications. The new approach is implemented and applied to real-life projects whose results demonstrate an augmented acceleration of 7.5 times on a 16-core distributed system compared to 6.1 of our previous solution. Moreover, there is no degradation in the optimization outcome. This is a solid sprint towards the realization of DNO.

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In this paper, a new paradigm is presented, to improve the performance of audio-based P300 Brain-computer interfaces (BCIs), by using spatially distributed natural sound stimuli. The new paradigm was compared to a conventional paradigm using spatially distributed sound to demonstrate the performance of this new paradigm. The results show that the new paradigm enlarged the N200 and P300 components, and yielded significantly better BCI performance than the conventional paradigm.

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4-Dimensional Variational Data Assimilation (4DVAR) assimilates observations through the minimisation of a least-squares objective function, which is constrained by the model flow. We refer to 4DVAR as strong-constraint 4DVAR (sc4DVAR) in this thesis as it assumes the model is perfect. Relaxing this assumption gives rise to weak-constraint 4DVAR (wc4DVAR), leading to a different minimisation problem with more degrees of freedom. We consider two wc4DVAR formulations in this thesis, the model error formulation and state estimation formulation. The 4DVAR objective function is traditionally solved using gradient-based iterative methods. The principle method used in Numerical Weather Prediction today is the Gauss-Newton approach. This method introduces a linearised `inner-loop' objective function, which upon convergence, updates the solution of the non-linear `outer-loop' objective function. This requires many evaluations of the objective function and its gradient, which emphasises the importance of the Hessian. The eigenvalues and eigenvectors of the Hessian provide insight into the degree of convexity of the objective function, while also indicating the difficulty one may encounter while iterative solving 4DVAR. The condition number of the Hessian is an appropriate measure for the sensitivity of the problem to input data. The condition number can also indicate the rate of convergence and solution accuracy of the minimisation algorithm. This thesis investigates the sensitivity of the solution process minimising both wc4DVAR objective functions to the internal assimilation parameters composing the problem. We gain insight into these sensitivities by bounding the condition number of the Hessians of both objective functions. We also precondition the model error objective function and show improved convergence. We show that both formulations' sensitivities are related to error variance balance, assimilation window length and correlation length-scales using the bounds. We further demonstrate this through numerical experiments on the condition number and data assimilation experiments using linear and non-linear chaotic toy models.

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This study aims to investigate the mediating effects of consumer satisfaction on the relationship between consumer-based brand equity and brand loyalty in the hotel and restaurant industry. Based on a sample of 378 customers and using structural equation modelling approach, the five dimensions of brand equity—physical quality, staff behaviour, ideal self-congruence, brand identification and lifestyle-congruence—are found to have positive effects on consumer satisfaction. The findings of the study suggest that consumer satisfaction partially mediates the effects of staff behaviour, ideal self-congruence and brand identification on brand loyalty. The effects of physical quality and lifestyle-congruence on brand loyalty are fully mediated by consumer satisfaction.

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Complex products such as manufacturing equipment have always needed maintenance and repair services. Increasingly, leading manufacturers are integrating products and services to generate increased revenues and achieve customer satisfaction. Designing integrated products and services requires a different approach to new product development and a clear understanding of how customers perceive the value they obtain from actual usage of products and services—so-called value-in-use. However, there is a lack of research on integrated products and services and how they impact customer satisfaction. An exploratory study was undertaken to understand customers’ views on integrated products and services and the value-in-use derived from such offerings. As value-in-use and its impacts are complicated concepts, a technique from psychology—Repertory Grid Technique—was used to gather data in 33 interviews. The interviews allowed a deep understanding of customer views on integrated products and services to be obtained, and a systematic analysis identified the key attributes of value-in-use. In order to probe further, the data were then analyzed using Honey’s procedure, which identified the impact of the attributes of value-in-use on customer satisfaction. Two key attributes—relational dynamic and access—were found to have the most influence on customer satisfaction. This paper contributes to the innovation field by identifying customer needs for integrated products and services and how these impact customer satisfaction. These are key points and need to be fully considered by managers during new product and service development. Similarly, the paper identifies a number of important areas for further research.

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Purpose – Corporate Occupiers require offices and services which meet their business needs, whilst landlords must attract and retain occupiers in order to maximise occupancy and rental income. The purpose of this research is to help landlords and corporate occupiers understand each other better, in order to achieve a mutually beneficial relationship. Design/methodology/approach - This paper analyses interviews with 1334 office tenants in the UK, conducted over an 11-year period, to investigate determinants of occupier satisfaction, loyalty and advocacy. Structural equation modelling and regressions are performed using respondents’ ratings of satisfaction with many aspects of occupancy as explanatory variables. The dependent variables include satisfaction with property management, value for money, overall occupier satisfaction, lease renewal intentions and occupiers’ willingness to recommend their landlord. Findings - The aspects with most impact on occupiers’ satisfaction are the office building itself, its location and amenities, and also communication with their property manager, a belief that their business needs are understood and the property manager’s responsiveness to occupiers’ requests. Occupiers’ loyalty depends mainly upon feeling that their rent and service charges provide value for money, an amicable leasing process, the professionalism of their property manager and the Corporate Social Responsibility of the Landlord. ‘Empathy’ is crucial to occupiers’ willingness to recommend their landlord, and clear documentation and efficient legal process improve occupiers’ perception of receiving ‘Value for Money’. Research Limitations - The sample is skewed towards occupiers of prime office buildings in the UK, owned by landlords who care sufficiently about their tenants to commission studies into occupier satisfaction. Practical implications - This research should help to improve the landlord – tenant relationship, benefitting the businesses that rent property and helping building managers understand where to focus their efforts to achieve maximum effect on occupier satisfaction, loyalty and advocacy. Originality/value - There has been little academic research into the determinants of satisfaction of occupiers of UK commercial property. This large-scale study enables the most influential factors to be identified and prioritised.

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We present one of the first studies of the use of Distributed Temperature Sensing (DTS) along fibre-optic cables to purposely monitor spatial and temporal variations in ground surface temperature (GST) and soil temperature, and provide an estimate of the heat flux at the base of the canopy layer and in the soil. Our field site was at a groundwater-fed wet meadow in the Netherlands covered by a canopy layer (between 0-0.5 m thickness) consisting of grass and sedges. At this site, we ran a single cable across the surface in parallel 40 m sections spaced by 2 m, to create a 40×40 m monitoring field for GST. We also buried a short length (≈10 m) of cable to depth of 0.1±0.02 m to measure soil temperature. We monitored the temperature along the entire cable continuously over a two-day period and captured the diurnal course of GST, and how it was affected by rainfall and canopy structure. The diurnal GST range, as observed by the DTS system, varied between 20.94 and 35.08◦C; precipitation events acted to suppress the range of GST. The spatial distribution of GST correlated with canopy vegetation height during both day and night. Using estimates of thermal inertia, combined with a harmonic analysis of GST and soil temperature, substrate and soil-heat fluxes were determined. Our observations demonstrate how the use of DTS shows great promise in better characterising area-average substrate/soil heat flux, their spatiotemporal variability, and how this variability is affected by canopy structure. The DTS system is able to provide a much richer data set than could be obtained from point temperature sensors. Furthermore, substrate heat fluxes derived from GST measurements may be able to provide improved closure of the land surface energy balance in micrometeorological field studies. This will enhance our understanding of how hydrometeorological processes interact with near-surface heat fluxes.