1,721,028 research outputs found
Public-private partnerships as a policy response to climate change
No full textThe negative impacts of climate change on the environment and economic activities are increasingly obvious and relevant. Private response to this threat often proves to be inadequate. For example, empirical evidence reveals a sub-optimal investment by firms in energy efficiency projects capable of reducing energy costs and CO2 emissions, as well as adaptation projects able to reduce the vulnerability of the ecosystem. On the other hand, past public programs that provided financial subsidies to the above-mentioned projects have proven to be not particularly cost-effective or able to enhance final performances. In this paper, as an alternative to public subsidies, we propose and assess the opportunity to implement Public-Private Partnerships (PPPs) where the public regulator plays a more active role in the investment choice. Precisely, we model the decision-making process through a Nash bargaining procedure between public and private actors. We end up with two main results: (i) compared to public subsidies, the use of PPPs leads to higher outcomes/performances and allows governments to overcome incompleteness in contracts; (ii) PPPs are optimally chosen only when there is a fair allocation of the bargaining power between the two sides and when bargaining procedures are not perceived as being too lengthy or costly
Measuring Performance Limits of Subband Adaptive Systems
No full textWe discuss a method to measure the convergence limits of general subband adaptive systems due to non-ideal filter banks. Aliasing caused in such filter banks presents a distortion to the subband adaptive system which forms a lower limit for the minimum mean squared error. The accuracy of the achievable model is given by the transfer function of the filter bank. To measure both aliasing and filter bank distortions, we employ the measurement technique by Heinle and Schuessler (1996). The presented approach is applicable to a wide range of subband adaptive filter systems. Examples for the measured limits are presented
Steady-State Performance Limitations of Subband Adaptive Filters
No full textNon-perfect filter banks used for subband adaptive filtering (SAF) are known to impose limitations on the steady-state performance of such systems. In this paper, we quantify the minimum mean-square error (MMSE) and the accuracy with which the overall SAF system can model an unknown system that it is set to identify. Firstly, in case of MMSE limits, the error is evaluated based on a power spectral density description of aliased signal components, which is accessible via a source model for the subband signals that we derive. Approximations of the MMSE can be embedded in a signal-to-alias ratio (SAR), a factor by which the error power can be reduced by adaptive filtering. With simplifications, SAR only depends on the filter banks. Secondly, in case of modelling, we link the accuracy of the SAF system to the filter bank mismatch in perfect reconstruction. When using modulated filter banks, both error limits --- MMSE and inaccuracy --- can be linked to the prototype. We explicitly derive this for generalized DFT modulated filter banks and demonstrate the validity of the analytical error limits and their approximations for a number of examples, whereby the analytically predicted limits of error quantities compare favourably with simulations
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Comprehensive study of flow boiling modeling inside helical micro-finned tubes: Empirical, non-convex optimization and deep learning predictive models
Full text linkOver the past decades, the design of evaporators has experienced improvement due to accruing experimental and numerical research on flow boiling. For micro-finned geometries that are deemed promising in augmentation of thermal performance, several empirical models have been developed. Recently, to attain higher accuracies in modeling, authors also resorted to Artificial Intelligence (AI) techniques while encouraging their further investigations. In this case, a database comprised of 1358 experimental heat transfer coefficients (HTC) and frictional pressure drops per unit length (FPD) has been considered for a holistic assessment of flow boiling modeling methods. The wide range of geometric features within the database, which includes tubes with outside diameters from 3 mm to 7 mm, helps to acquire a more reliable evaluation of the models, since the flow boiling mechanism is strongly dependent on the geometric parameters.After evaluating three empirical models for the HTC, it was confirmed that, depending on the diameter, the flow boiling mechanism undergoes alterations pertinent to a balance between convective and nucleate boiling, and the models must be modified to account for these conditions.The mean average deviation (MAD) for the models was recorded to be 11.7 %, 22.2 %, and 21.5 % for Diani et al., Mehendale, and Tang and Li, respectively. Higher accuracies were obtained after modification of the empirical models, of which the most accurate one provides a MAD of 10.13 %. Moreover, by the implementation of a novel approach, for the first time, a power function correlation has been established among dimensionless parameters for a machine learning-powered model. The MAD of 10.9 % and 15.8 % was reported for the Nusselt number and the two-phase multiplier respectively. Artificial Neural Network (ANN) was also considered for modeling, and MADs of 4.6 % and 4.2 % were recorded for the Nusselt number and two-phase multiplier, respectively
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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