1,720,958 research outputs found
A carbon footprint calculator for the municipal waste collection system of Bari
No full textThe concept of smart city is being receiving wide consideration as a guiding principle of European public policy. Providing "smartness" to modern society is emerging as a strategy to coordinate sets of interventions aiming at make city more sustainable. Following the principle that what is not measured cannot be managed, the authors propose a Carbon Footprint Calculator (CFC) to evaluate and monitor emissions resulting from the collection of municipal solid waste system. This user-friendly tool has been developed in the frame of European project "RES NOVAE" with the aim of providing the city with a 'smart governance'. Smart governance is a cornerstone of smart city: it means stakeholders cooperating in decision making process and public or social service. Indeed, the calculator is suitable for both public decision makers and citizens. Policy maker can use the CFC proposed to support greenhouse gases monitoring as well as to provide an estimation of a potential change in emissions associated with management and technological changes in waste collection. 'Smart' citizens will use the carbon footprint calculator to glean consciousness about personal behaviours affecting green house gas emissions. The tool stands as a formative instrument to involve citizens in societal challenges and increase their public participation
A carbon footprint calculator for the municipal waste collection system of Bari
No full textThe concept of smart city is being receiving wide consideration as a guiding principle of European public policy. Providing "smartness" to modern society is emerging as a strategy to coordinate sets of interventions aiming at make city more sustainable. Following the principle that what is not measured cannot be managed, the authors propose a Carbon Footprint Calculator (CFC) to evaluate and monitor emissions resulting from the collection of municipal solid waste system. This user-friendly tool has been developed in the frame of European project "RES NOVAE" with the aim of providing the city with a 'smart governance'. Smart governance is a cornerstone of smart city: it means stakeholders cooperating in decision making process and public or social service. Indeed, the calculator is suitable for both public decision makers and citizens. Policy maker can use the CFC proposed to support greenhouse gases monitoring as well as to provide an estimation of a potential change in emissions associated with management and technological changes in waste collection. 'Smart' citizens will use the carbon footprint calculator to glean consciousness about personal behaviours affecting green house gas emissions. The tool stands as a formative instrument to involve citizens in societal challenges and increase their public participation
Minimizing Carbon-footprint of Municipal Waste Integrated Management Systems
No full textSustainability in urban development, economic growth and human well-being are critical issues faced all over the world. In the last decade urban planning and management had accomplished, or will do it, innovations in order to meet the challenges posed by sustainable development. Reduction of 20% of GHG emission, the achievement of 20% energy demand by renewable energy together with an increase of 20% of energy efficiency are targets foreseen by EU. In this scenario a strategic role is played by municipal waste integrated management system (MWIMS). The matter is becoming increasingly important as a results of the growth of urbanization rate: the raising complexity of a MWIMS relies on the high number of design and management variables and relationships pertaining to collection, treatments and disposal phases. Waste management practices can sway greenhouse gas emission by affecting energy consumption, methane generation, carbon sequestration and non-energy related manufacturing emission. In this context, a sustainable waste management system allows a reduction of negative impacts on environment. The purpose of such a study is to propose a decision-making framework aiming to minimize the carbon footprint of a MWIMS. The model goes beyond the existing technical and organizational solutions outlining the different options in a much broader view concerning both waste collection and treatments. A mixed integer linear programming model , has been applied to a full case study concerning Bari. The study is carried out within the research project RES NOVAE (Reti, Edifici, Strade ‐ Nuovi Obiettivi Virtuosi per l’Ambiente e l’Energia). The strength of the framework results in supporting public decision-making, a complex process due to the number of decision variables and their implications on economic performance. Results exhibit the effectiveness of the model also in pointing out opportunities non yet evaluated
Minimizing Carbon-footprint of Municipal Waste Integrated Management Systems
No full textSustainability in urban development, economic growth and human well-being are critical issues faced all over the world. In the last decade urban planning and management had accomplished, or will do it, innovations in order to meet the challenges posed by sustainable development. Reduction of 20% of GHG emission, the achievement of 20% energy demand by renewable energy together with an increase of 20% of energy efficiency are targets foreseen by EU. In this scenario a strategic role is played by municipal waste integrated management system (MWIMS). The matter is becoming increasingly important as a results of the growth of urbanization rate: the raising complexity of a MWIMS relies on the high number of design and management variables and relationships pertaining to collection, treatments and disposal phases. Waste management practices can sway greenhouse gas emission by affecting energy consumption, methane generation, carbon sequestration and non-energy related manufacturing emission. In this context, a sustainable waste management system allows a reduction of negative impacts on environment. The purpose of such a study is to propose a decision-making framework aiming to minimize the carbon footprint of a MWIMS. The model goes beyond the existing technical and organizational solutions outlining the different options in a much broader view concerning both waste collection and treatments. A mixed integer linear programming model , has been applied to a full case study concerning Bari. The study is carried out within the research project RES NOVAE (Reti, Edifici, Strade ‐ Nuovi Obiettivi Virtuosi per l’Ambiente e l’Energia). The strength of the framework results in supporting public decision-making, a complex process due to the number of decision variables and their implications on economic performance. Results exhibit the effectiveness of the model also in pointing out opportunities non yet evaluated
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
An ANN-based Decision Support Tool for the Sustainable Performance Prediction of the Waste Management Systems
No full textAssessment and prediction of environmental and economic performance of waste management systems
should be jointly considered in a sustainable planning of such a system. Complexity of the economic and the
environmental evaluation of waste management system limits the adoption of analytical tools by policy makers.
Consistently, the authors propose an Artificial Neural Network (ANN)-based decision support tool for the
prediction of the optimized sustainable performance of an integrated waste management system. It stands as a userfriendly
dashboard designed for a local-policy maker who seeks to have insights into potential effects of different
waste management policy mainly on greenhouse gases (GHGs) emissions and monetary savings. Indeed, starting
from both demographic and urban fabric features, the tool predicts the most suitable collection configuration, the
flows managed as well as the amount of CO2eq emitted/avoided and relative financial flows. The ANN developed is
trained through data deriving from an analytical optimization model. The modeling code is developed by Alyuda
NeuroIntelligenceTM. Results show the good reliability of the ANN in the prediction of the optimized sustainable
performance for the waste management syste
An ANN-based Decision Support Tool for the Sustainable Performance Prediction of the Waste Management Systems
No full textAssessment and prediction of environmental and economic performance of waste management systems
should be jointly considered in a sustainable planning of such a system. Complexity of the economic and the
environmental evaluation of waste management system limits the adoption of analytical tools by policy makers.
Consistently, the authors propose an Artificial Neural Network (ANN)-based decision support tool for the
prediction of the optimized sustainable performance of an integrated waste management system. It stands as a userfriendly
dashboard designed for a local-policy maker who seeks to have insights into potential effects of different
waste management policy mainly on greenhouse gases (GHGs) emissions and monetary savings. Indeed, starting
from both demographic and urban fabric features, the tool predicts the most suitable collection configuration, the
flows managed as well as the amount of CO2eq emitted/avoided and relative financial flows. The ANN developed is
trained through data deriving from an analytical optimization model. The modeling code is developed by Alyuda
NeuroIntelligenceTM. Results show the good reliability of the ANN in the prediction of the optimized sustainable
performance for the waste management syste
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
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