1,720,975 research outputs found
Dynamic Classification Trees for imprecise data
No full textThis paper provides a supervised classification tree-based methodology to deal with
Multivalued data, specifically predictors’ measurements can be provided by a functional
distribution or an interval of values. Main literature refers to symbolic data analysis, aiming to extend standard methods such as factorial analysis, clustering, discriminant analysis, etc., to deal with symbolic data tables. One approach is to define a suitable data pre-processing enabling the application of standard methods. A more correct approach is to define suitable methods to deal specifically with un-standard data.
In the framework of supervised classification, there are no proposal in literature for supervised classification methods to deal with both standard and multivalued data as well. There are only proposals based on data pre-processing.
This paper provides a methodology to grow the so-called Dynamic CLASSification TREE (D-CLASSTREE), upon suitable definition of both a specific splitting criterion and a tree-growing algorithm. A real world case study will be considered to show the advantages of the final output and main issues of the interpretation. A comparative study with older proposals will be also described such to demonstrate the stability and the better accuracy of the D-CLASSTREE
Walk, Look and Smell Through
No full textHuman Computer interaction is typically constrained to the use of sight, hear, and touch. This paper describes an attempt to get over these limitations. We introduce the smell in the interaction with the aim of obtaining information from scents, i.e. giving meaning to odours and understand how people would appreciate such extensions. We discuss the design and implementation of our prototype system. The system is able to represent/manage an immersive environment,
where the user interacts by means of visual, hearing and olfactory informations. We have implemented an odour emitter controlled by a presence sensor device. When the system perceives the presence of a user it activates audio/visual con-
tents to encourage engaging in interaction. Then a specic
scent is diffused in the air to augment the perceive reality of the experience. We discuss technical difficulties and initial
empirical observations
L'incertezza nelle relazioni di lavoro: Una prospettiva di analisi di comportamento organizzativo.
No full textLe relazioni di lavoro si caratterizzano per una crescente incertezza derivante dalla crisi economica e dalla conseguente crisi occupazionale. L’incertezza nelle relazioni di lavoro tende ad assumere la forma della job insecu- rity che, come sostenuto nella letteratura orga- nizzativa, esercita una significativa influenza sugli atteggiamenti degli individui sul lavoro. Nonostante le numerose ricerche sul tema, emergono risultati empirici contrastanti con riguardo al tema della job insecurity e delle reazioni psicologiche indotte sui lavoratori stabili e su quelli flessibili.
In questa ricerca sviluppiamo un modello che integra la letteratura esistente sul tema della job insecurity e del lavoro flessibile con la prospettiva teorica del contratto psicologico. Si ipotizza, infatti, che la relazione negativa tra job insecurity e commitment affettivo possa es- sere mediata dalla percezione di adempimento del contratto psicologico. Inoltre, argomentando sui tratti distintivi del contratto psicologico relazionale ed il contratto psicologico transa- zionale, ipotizziamo che significative diffe- renze possono affermarsi tra lavoratori stabili e lavoratori flessibili con riguardo alla natura
ed all’intensità della reazione psicologica in- dotta dalla job insecurity. È stata condotta un’indagine di tipo quantitativo presso un’azienda campana che opera nel settore alimentare. I risultati evidenziano che la job insecurity ha un effetto negativo sul commitment affettivo che è pienamente mediato dalla percezione di adempimento del contratto psicologico e che la reazione psicologica nei confronti della percezione di insicurezza sul lavoro risulta più accentuata per i lavoratori stabili rispetto ai lavoratori flessibili
Ternary classification trees for imprecise data
No full textThe framework of this work is the statistical learning theory of Vapnik, i.e. learn from the experience (training sample) to generalize and provide useful answers (prediction, decision) in new cases. Goal is to identify the learning machine characterized by the best functional relationships between the input and the output such to approximate the supervisor’s response minimizing the loss of discrepancy or error. Classification tree-based supervisor will be considered, consisting in a recursive partitioning of the predictor space (input) to induce a partitioning of the sample of cases into disjoint subgroups which are internally homogeneous and externally heterogeneous with respect to a categorical (often dummy) response variable (output). Predictors are usually of numerical or categorical type, with punctual measurements.
This paper provides a supervised classification tree-based methodology to deal with imprecise data, specifically predictors’ measurements can be provided by a functional distribution or an interval of values. The proposed recursive ternary partitioning algorithm discriminates in better way the ordering relationships and the imprecision of the case measurements. Typical data structures of this type occur in many real life applications,
where training data comes with intrinsic uncertainty that might be the result of imprecise measuring instruments such as in image recognition (in medicine, physics, robotics, etc.) or human judgements/observations in socio-economic fields. As a result, the proposed approach can be understood as a “subjectivistic” view of imprecision formalizing the uncertainty concerning an underlying “crisp” phenomenon
Osteopontin, a protein with cytokine-like properties: a possible involvement in pemphigus vulgaris
No full text
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
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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