80 resultados para Flexible pavements
Resumo:
Age estimation from facial images is increasingly receiving attention to solve age-based access control, age-adaptive targeted marketing, amongst other applications. Since even humans can be induced in error due to the complex biological processes involved, finding a robust method remains a research challenge today. In this paper, we propose a new framework for the integration of Active Appearance Models (AAM), Local Binary Patterns (LBP), Gabor wavelets (GW) and Local Phase Quantization (LPQ) in order to obtain a highly discriminative feature representation which is able to model shape, appearance, wrinkles and skin spots. In addition, this paper proposes a novel flexible hierarchical age estimation approach consisting of a multi-class Support Vector Machine (SVM) to classify a subject into an age group followed by a Support Vector Regression (SVR) to estimate a specific age. The errors that may happen in the classification step, caused by the hard boundaries between age classes, are compensated in the specific age estimation by a flexible overlapping of the age ranges. The performance of the proposed approach was evaluated on FG-NET Aging and MORPH Album 2 datasets and a mean absolute error (MAE) of 4.50 and 5.86 years was achieved respectively. The robustness of the proposed approach was also evaluated on a merge of both datasets and a MAE of 5.20 years was achieved. Furthermore, we have also compared the age estimation made by humans with the proposed approach and it has shown that the machine outperforms humans. The proposed approach is competitive with current state-of-the-art and it provides an additional robustness to blur, lighting and expression variance brought about by the local phase features.
Resumo:
The family of location and scale mixtures of Gaussians has the ability to generate a number of flexible distributional forms. The family nests as particular cases several important asymmetric distributions like the Generalized Hyperbolic distribution. The Generalized Hyperbolic distribution in turn nests many other well known distributions such as the Normal Inverse Gaussian. In a multivariate setting, an extension of the standard location and scale mixture concept is proposed into a so called multiple scaled framework which has the advantage of allowing different tail and skewness behaviours in each dimension with arbitrary correlation between dimensions. Estimation of the parameters is provided via an EM algorithm and extended to cover the case of mixtures of such multiple scaled distributions for application to clustering. Assessments on simulated and real data confirm the gain in degrees of freedom and flexibility in modelling data of varying tail behaviour and directional shape.
Resumo:
Small, not-for-profit organisations fulfil a need in the economy that is typically not satisfied by for-profit firms. They also operate in ways that are distinct from larger organisations. While such firms employ a substantial proportion of the workforce, research addressing human resource management (HRM) practices in these settings is limited. This article used data collected from five small not-for-profit firms in Australia to examine the way one significant HRM practice – the provision and utilisation of flexible work arrangements – operates in the sector. Drawing on research from several scholarly fields, the article firstly develops a framework comprising three tensions in not-for-profits that have implications for HRM. These tensions are: (1) contradictions between an informal approach to HRM vs. a formal regulatory system; (2) employee values that favour social justice vs. external market forces; and (3) a commitment to service vs. external financial expectations. The article then empirically examines how these tensions are managed in relation to the specific case of flexible work arrangements. The study reveals that tensions around providing and accessing flexible work arrangements are managed in three ways: discretion, leadership style and distancing. These findings more broadly inform the way HRM is operationalised in this under-examined sector.
Resumo:
BACKGROUND As blood collection agencies (BCAs) face recurrent shortages of varying blood products, developing a panel comprising donors who are flexible in the product they donate based on same-time inventory demand could be an efficient, cost-effective inventory management strategy. Accounting for prior whole blood (WB) and plasmapheresis donation experience, this article explores current donors’ willingness to change their donation product and identifies the type of information required for such donation flexibility. STUDY DESIGN AND METHODS Telephone interviews (mean, 34 min; SD, 11 min) were conducted with 60 donors recruited via stratified purposive sampling representing six donor groups: no plasma, new to both WB and plasma, new to plasma, plasma, flexible (i.e., alternating between WB and plasma), and maximum (i.e., high frequency alternating between WB and plasma) donors. Participants responded to hypothetical scenarios and open-ended questions relating to their and other donors’ willingness to be flexible. Responses were transcribed and content was analyzed. RESULTS The most frequently endorsed categories varied between donor groups with more prominent differences emerging between the information and support that donors desired for themselves versus that for others. Most donors were willing to change donations but sought improved donation logistics and information regarding inventory levels to encourage flexibility. The factors perceived to facilitate the flexibility of other donors included providing donor-specific information and information regarding different donation types. CONCLUSION Regardless of donation history, donors are willing to be flexible with their donations. To foster a flexible donor panel, BCAs should continue to streamline the donation process and provide information relevant to donors’ experience.
Resumo:
This paper presents a flexible and integrated planning tool for active distribution network to maximise the benefits of having high level s of renewables, customer engagement, and new technology implementations. The tool has two main processing parts: “optimisation” and “forecast”. The “optimization” part is an automated and integrated planning framework to optimize the net present value (NPV) of investment strategy for electric distribution network augmentation over large areas and long planning horizons (e.g. 5 to 20 years) based on a modified particle swarm optimization (MPSO). The “forecast” is a flexible agent-based framework to produce load duration curves (LDCs) of load forecasts for different levels of customer engagement, energy storage controls, and electric vehicles (EVs). In addition, “forecast” connects the existing databases of utility to the proposed tool as well as outputs the load profiles and network plan in Google Earth. This integrated tool enables different divisions within a utility to analyze their programs and options in a single platform using comprehensive information.