993 resultados para Ferrovia Milano-Como.


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University of Illinois bookplate: "From the library of Conte Antonio Cavagna Sangiuliani di Gualdana Lazelada di Bereguardo purchased 1921".

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University of Illinois bookplate: "From the library of Conte Antonio Cavagna Sangiuliani di Gualdana Lazelada di Bereguardo purchased 1921".

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University of Illinois bookplate: "From the library of Conte Antonio Cavagna Sangiuliani di Gualdana Lazelada di Bereguardo, purchased 1921".

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University of Illinois bookplate: "From the library of Conte Antonio Cavagna Sangiuliani di Gualdana Lazelada di Bereguardo purchased 1921".

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University of Illinois bookplate: "From the library of Conte Antonio Cavagna Sangiuliani di Gualdana Lazelada di Bereguardo purchased 1921".

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University of Illinois bookplate: "From the library of Conte Antonio Cavagna Sangiuliani di Gualdana Lazelada di Bereguardo, purchased 1921".

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Oggetto della trattazione è il recupero di energia da parte di una valvola idraulica durante il processo di regolazione del flusso di corrente in un impianto. Questa valvola di regolazione, detta GreenValve, è un brevetto del Politecnico di Milano, ad opera del Prof. Ing. Stefano Malavasi coadiuvato da un gruppo di ricercatori e tesisti, tra i quali spicca il nome di Cecilia Paris. Cecilia ha incentrato il proprio lavoro sull’analisi teorica e sperimentale della “Valvola Verde”, ed è dalla sua Tesi che il suddetto elaborato trae ispirazione.

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This study aimed to detect and analyse regular patterns of play in fast attack of football teams, through the combination of the sequential analysis technique and semi-structured interviews to experienced first League Portuguese coaches. The sample included 36 games (12 games of the respective national leagues per team) of the F.C. Barcelona, Inter Milan, and Manchester United teams that were coded with the observational instrument tool developed by Sarmento et al. (2010) and the data analysed through sequential analysis with the software SDIS-GSEQ 5.0. Based on the detected patterns, semi-structured interviews were carried out to 8 expert high-performance football coaches and data were analysed through the content analysis technique using the software NVivo 10. The detected patterns of play revealed specific characteristics of the teams under study. The combination of the results of sequential analysis with the qualitative interviews to the professional coaches proved to be very fruitful in this game the analysis of scope, allowing reconcile scientific knowledge with practical interpretation of coaches who develop their tasks in the field.

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An informed citizenry is essential to the effective functioning of democracy. In most modern liberal democracies, citizens have traditionally looked to the media as the primary source of information about socio-political matters. In our increasingly mediated world, it is critical that audiences be able to effectively and accurately use the media to meet their information needs. Media literacy, the ability to access, understand, evaluate and create media content is therefore a vital skill for a healthy democracy. The past three decades have seen the rapid expansion of the information environment, particularly through Internet technologies. It is obvious that media usage patterns have changed dramatically as a result. Blogs and websites are now popular sources of news and information, and are for some sections of the population likely to be the first, and possibly only, information source accessed when information is required. What are the implications for media literacy in such a diverse and changing information environment? The Alexandria Manifesto stresses the link between libraries, a well informed citizenry and effective governance, so how do these changes impact on libraries? This paper considers the role libraries can play in developing media literate communities, and explores the ways in which traditional media literacy training may be expanded to better equip citizens for new media technologies. Drawing on original empirical research, this paper highlights a key shortcoming of existing media literacy approaches: that of overlooking the importance of needs identification as an initial step in media selection. Self-awareness of one’s actual information need is not automatic, as can be witnessed daily at reference desks in libraries the world over. Citizens very often do not know what it is that they need when it comes to information. Without this knowledge, selecting the most appropriate information source from the vast range available becomes an uncertain, possibly even random, enterprise. Incorporating reference interview-type training into media literacy education, whereby the individual will develop the skills to interrogate themselves regarding their underlying information needs, will enhance media literacy approaches. This increased focus on the needs of the individual will also push media literacy education into a more constructivist methodology. The paper also stresses the importance of media literacy training for adults. Media literacy education received in school or even university cannot be expected to retain its relevance over time in our rapidly evolving information environment. Further, constructivist teaching approaches highlight the importance of context to the learning process, thus it may be more effective to offer media literacy education relating to news media use to adults, whilst school-based approaches focus on types of media more relevant to young people, such as entertainment media. Librarians are ideally placed to offer such community-based media literacy education for adults. They already understand, through their training and practice of the reference interview, how to identify underlying information needs. Further, libraries are placed within community contexts, where the everyday practice of media literacy occurs. The Alexandria Manifesto stresses the link between libraries, a well informed citizenry and effective governance. It is clear that libraries have a role to play in fostering media literacy within their communities.

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It is a big challenge to clearly identify the boundary between positive and negative streams. Several attempts have used negative feedback to solve this challenge; however, there are two issues for using negative relevance feedback to improve the effectiveness of information filtering. The first one is how to select constructive negative samples in order to reduce the space of negative documents. The second issue is how to decide noisy extracted features that should be updated based on the selected negative samples. This paper proposes a pattern mining based approach to select some offenders from the negative documents, where an offender can be used to reduce the side effects of noisy features. It also classifies extracted features (i.e., terms) into three categories: positive specific terms, general terms, and negative specific terms. In this way, multiple revising strategies can be used to update extracted features. An iterative learning algorithm is also proposed to implement this approach on RCV1, and substantial experiments show that the proposed approach achieves encouraging performance.

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We argue that web service discovery technology should help the user navigate a complex problem space by providing suggestions for services which they may not be able to formulate themselves as (s)he lacks the epistemic resources to do so. Free text documents in service environments provide an untapped source of information for augmenting the epistemic state of the user and hence their ability to search effectively for services. A quantitative approach to semantic knowledge representation is adopted in the form of semantic space models computed from these free text documents. Knowledge of the user’s agenda is promoted by associational inferences computed from the semantic space. The inferences are suggestive and aim to promote human abductive reasoning to guide the user from fuzzy search goals into a better understanding of the problem space surrounding the given agenda. Experimental results are discussed based on a complex and realistic planning activity.

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The social tags in web 2.0 are becoming another important information source to profile users' interests and preferences to make personalized recommendations. To solve the problem of low information sharing caused by the free-style vocabulary of tags and the long tails of the distribution of tags and items, this paper proposes an approach to integrate the social tags given by users and the item taxonomy with standard vocabulary and hierarchical structure provided by experts to make personalized recommendations. The experimental results show that the proposed approach can effectively improve the information sharing and recommendation accuracy.

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With the size and state of the Internet today, a good quality approach to organizing this mass of information is of great importance. Clustering web pages into groups of similar documents is one approach, but relies heavily on good feature extraction and document representation as well as a good clustering approach and algorithm. Due to the changing nature of the Internet, resulting in a dynamic dataset, an incremental approach is preferred. In this work we propose an enhanced incremental clustering approach to develop a better clustering algorithm that can help to better organize the information available on the Internet in an incremental fashion. Experiments show that the enhanced algorithm outperforms the original histogram based algorithm by up to 7.5%.