1,720,979 research outputs found

    A tuning methodology of Model Predictive Control design for energy efficient building thermal control

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    The Model Predictive Control (MPC) approach is based on the prediction of indoor and outdoor thermal loads in order to counter the deviation of the indoor temperature from the occupants' preference in advance. The minimization of temperature alteration allows for efficient energy use and improvement of indoor thermal environment. Unlike the classical reactive control, MPC is able to act in advance and to explicitly handle constraints on building variables when selecting the best scenario. This peculiarity makes MPC particularly suitable for the optimal energy management of buildings but, despite the increasing research activity in the field, the commercial technologies are lagging behind. Among the reasons are the lack of a well established design approach easily applicable to the buildings domain and the lack of a design optimization. In this paper a tuning methodology of MPC design for energy efficient building thermal control is presented. The tuning is performed on the controller parameters, and aims at identifying the best parameter set in terms of energy saving and temperature deviation from the chosen setpoint. To demonstrate the effectiveness of the methodology, a simulation based analysis using a model estimated on a real case study is presented. The methodology shows that by improving the control parameters it is possible to reduce energy consumption and improve thermal comfort for the final user

    Development of digital twin models supporting ambient assisted living

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    World population aging requires finding solutions to improve independent living options. Ambient Assisted Living (AAL) is making step forward developing services supporting the elderly, but the implementation of predictive environments is still far away. Besides, the emerging Digital Twin (DT) concept has begun to shape the first cognitive environments that integrate users into assessments, improving efficiency, prevention, and prediction of likely events through realtime AI computing. This paper aims to provide a prototype of a Cognitive Building framework based on DT models that develop high-level knowledge to achieve real-time Scenario Awareness and offer appropriate AAL services once anomalies are detected

    Going Beyond Counting First Authors in Author Co-citation Analysis

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    The 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

    Stability analysis tool for tuning unconstrained decentralized model predicitive controllers

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    Some processes are naturally suitable to be controlled in a decentralized framework: centralized control solutions are often infeasible in dealing with large scale plants and they are technologically prohibitive when the processes are too fast for the available computational resources. In these cases, the resulting control problem is usually split in many smaller subproblems and the global requirements are guaranteed by means of a proper coordination. The unconstrained decentralized case is here considered and a coordination strategy is proposed for improving the global control performances. This paper present a tool for setting up and tuning a nominally stable decentralized Model Predictive Controller. Numerical examples are proposed for testing and validating the developed technique

    Variations on the Author

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    “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

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    We 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

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    We 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

    Author Index

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    koamabayili/VECTRON-author-checklist: VECTRON author checklist

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    We have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
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