205,136 research outputs found

    Evolving weighting schemes for the Bag of Visual Words

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    The Bag of Visual Words (BoVW) is an established representation in computer vision. Taking inspiration from text mining, this representation has proved to be very effective in many domains. However, in most cases, standard term-weighting schemes are adopted (e.g., term-frequency or TF-IDF). It remains open the question of whether alternative weighting schemes could boost the performance of methods based on BoVW. More importantly, it is unknown whether it is possible to automatically learn and determine effective weighting schemes from scratch. This paper brings some light into both of these unknowns. On the one hand, we report an evaluation of the most common weighting schemes used in text mining, but rarely used in computer vision tasks. Besides, we propose an evolutionary algorithm capable of automatically learning weighting schemes for computer vision problems. We report empirical results of an extensive study in several computer vision problems. Results show the usefulness of the proposed method

    How should public health professionals engage with lay epidemiology?

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    "Lay epidemiology" is a term used to describe the processes through which health risks are understood and interpreted by laypeople. It is seen as a barrier to public health when the public disbelieves or fails to act on public health messages. Two elements to lay epidemiology are proposed: (a) empirical beliefs about the nature of illness and (b) values about the place of health and risks to health in a good life. Both elements have to be dealt with by effective public health schemes or programmes, which would attempt to change the public's empirical beliefs and values. This is of concern, particularly in a context in which the lay voice is increasingly respected. Empirically, the scientific voice of standard epidemiology should be deferred to by the lay voice, provided a clear distinction exists between the measurement of risk, which is empirical, and its weighting, which is based on values. Turning to engagement with values, health is viewed to be an important value and is discussed and reflected on by most people. Public health professionals are therefore entitled and advised to participate in that process. This view is defended against some potential criticisms

    Accruals, Investment and Errors-in-Variables

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    We formulate well-known discretionary accruals models in an investment setting. Given that accruals basically consist of short-term investment, we introduce, (i) cash-flows, as a proxy for financial constraints and other financial markets imperfections, and (ii) Tobin’s q as a measure of capital return. Accounting data and Tobin’s q being measured with errors, we propose an econometric method based on a modified version of the Hausman artificial regression which features an optimal weighting matrix of higher moments instrumental variable estimators. The empirical results suggest that all the key parameters of the discretionary accruals models studied are biased systematically with measurement errors.Discretionary accruals; Earnings management; Investment; Measurement errors; Higher moments; Instrumental variable estimators.

    Power Loss Analysis of Solar Photovoltaic Integrated Model Predictive Control Based On-Grid Inverter

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    This paper presents a finite control-set model predictive control (FCS-MPC) based technique to reduce the switching loss and frequency of the on-grid PV inverter by incorporating a switching frequency term in the cost function of the model predictive control (MPC). In the proposed MPC, the control objectives (current and switching frequency) select an optimal switching state for the inverter by minimizing a predefined cost function. The two control objectives are combined with a weighting factor. A trade-off between the switching frequency (average) and total harmonic distortion (THD) of the current was utilized to determine the value of the weighting factor. The switching, conduction, and harmonic losses were determined at the selected value of the weighting factor for both the proposed and conventional FCS-MPC and compared. The system was simulated in MATLAB/Simulink, and a small-scale hardware prototype was built to realize the system and verify the proposal. Considering only 0.25% more current THD, the switching frequency and loss per phase were reduced by 20.62% and 19.78%, respectively. The instantaneous overall power loss was also reduced by 2% due to the addition of a switching frequency term in the cost function which ensures a satisfactory empirical result for an on-grid PV inverter

    Back to the basics: a quantitative analysis of statistical and graph-based term weighting schemes for keyword extraction

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    Term weighting schemes are widely used in Natural Language Processing and Information Retrieval. In particular, term weighting is the basis for keyword extraction. However, there are relatively few evaluation studies that shed light about the strengths and shortcomings of each weighting scheme. In fact, in most cases researchers and practitioners resort to the well-known tf-idf as default, despite the existence of other suitable alternatives, including graph-based models. In this paper, we perform an exhaustive and large-scale empirical comparison of both statistical and graph-based term weighting methods in the context of keyword extraction. Our analysis reveals some interesting findings such as the advantages of the less-known lexical specificity with respect to tf-idf, or the qualitative differences between statistical and graph-based methods. Finally, based on our findings we discuss and devise some suggestions for practitioner

    Improving nutritional status through behavioral change: lessons from Madagascar

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    This paper provides evidence of the effects of a large-scale intervention that focuses on the quality of nutritional and child care inputs during the early stages of life. The empirical strategy uses a combination of double-difference and weighting estimators in a longitudinal survey to address the purposive placement of participating communities and estimate the effect of the availability of the program at the community level on nutritional outcomes. The authors find that the program helped 0-5 year old children in the participating communities to bridge the gap in weight for age z-scores and the incidence of underweight. The program also had significant effects in protecting long-term nutritional outcomes (height for age z-scores and incidence of stunting) against an underlying negative trend in the absence of the program. Importantly, the effect of the program exhibits substantial heterogeneity: gains in nutritional outcomes are larger for more educated mothers and for villages with better infrastructure. The program enables the analysis to isolate responsiveness to information provision and disentangle the effect of knowledge in the education effect on nutritional outcomes. The results are suggestive of important complementarities among child care, maternal education, and community infrastructure

    Characterizing Signal Loss in the 21 cm Reionization Power Spectrum: A Revised Study of PAPER-64

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    The Epoch of Reionization (EoR) is an uncharted era in our Universe's history during which the birth of the first stars and galaxies led to the ionization of neutral hydrogen in the intergalactic medium. There are many experiments investigating the EoR by tracing the 21cm line of neutral hydrogen. Because this signal is very faint and difficult to isolate, it is crucial to develop analysis techniques that maximize sensitivity and suppress contaminants in data. It is also imperative to understand the trade-offs between different analysis methods and their effects on power spectrum estimates. Specifically, with a statistical power spectrum detection in HERA's foreseeable future, it has become increasingly important to understand how certain analysis choices can lead to the loss of the EoR signal. In this paper, we focus on signal loss associated with power spectrum estimation. We describe the origin of this loss using both toy models and data taken by the 64-element configuration of the Donald C. Backer Precision Array for Probing the Epoch of Reionization (PAPER). In particular, we highlight how detailed investigations of signal loss have led to a revised, higher 21cm power spectrum upper limit from PAPER-64. Additionally, we summarize errors associated with power spectrum error estimation that were previously unaccounted for. We focus on a subset of PAPER-64 data in this paper; revised power spectrum limits from the PAPER experiment are presented in a forthcoming paper by Kolopanis et al. (in prep.) and supersede results from previously published PAPER analyses.Comment: 25 pages, 18 figures, Accepted by Ap
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