1,720,979 research outputs found
Integrating Spatio-Temporal Predictions in Web-GIS Based on a Relational Database Model
No full textGeostatistics and geographic information systems (indicated with the acronym GIS) provide useful tools to manage environmental spatio-temporal data. They often represent a valid support for actions addressed to favor sustainable development of a territory. In this paper, the potential use of a GIS with a web interface as well as the possibility of enhancing its performance by recalling spatio- temporal geostatistical techniques for analyzing environmental data are discussed. After introducing a georelational database model designed to store and analyze both pollutants and atmospheric variables collected from different monitoring stations located in the Salento region, the construction of a GIS project together with the associated Web-GIS is proposed. Environmental data and spatio-temporal geostatistical predictions are integrated and interactive maps with various functionalities are provided
Identifying spatial patterns with the Bootstrap ClustGeo technique
No full textBuilding clusters for pattern recognition and analysis of geographical areas can be a useful way to provide relevant information for economic and social decisions. In this paper, we introduce a novel spatial clustering technique, called Bootstrap ClustGeo (BCG), which is a hierarchical approach, based on bootstrap techniques with spatial constraints. We evaluate the performance of the proposed approach BCG through some real case studies and simulations studies with different complexity, by computing Clustering Validation Measures (CVM) and then we compare the approach with the recently proposed ClustGeo (CG). These analyses exhibit the accuracy of BCG, also with respect to CG, in the presented applications, and highlight the great potentiality of this new clustering technique to provide meaningful information for spatial analysis. (C) 2020 Elsevier B.V. All rights reserved
Classes of Colors and Timbres: A Clustering Approach
No full textSimilarities between different sensory dimensions can be addressed consid-ering common "movements" as causes, and emotional responses as effects. An imaginary movement toward the "dark" produces "dark sounds" and "dark colors," or, toward the "bright," "brighter colors" and "brighter sounds." Following this line of research, we draw upon the confluence of mathematics and cognition, extending to colors and timbres the gestural similarity conjec-ture, a development of the mathematical theory of musical gestures. Visual "gestures" are seen here as paths in the space of colors, compared with paths in the space of orchestral timbres. We present an approach based on cluster-ing algorithm to evaluate the association between color bands and orchestral timbres. The analysis is based on 8 indicators which represent and describe participants' background and associations to be tested. The indicators in-clude socio-demographic information and color class options from the color space, to associate with each given timbre class. We clustered responders into homogeneous groups where the within-group-object dissimilarity is min-imized and the between-group-object dissimilarity is maximized. The parti-tions are obtained with k-mo des. While participants' background does have an influence in their answers, the overall behaviors confirms the existence of different space regions for different timbres, supporting our hypothesis of perceived similarities similarities between color and timbre classes. In fact, the cluster analysis confirms identifiable blocks. Our pioneering study on a small dataset may open the way toward a future and deeper comprehension of complex color-timbre perceived connections
A hybrid two-step approach for assessing the probabilit of training needs on artificial intelligence systems
No full textArtificial Intelligence (AI) represents the core of many technologies and in the last few years, it has become more and more crucial in helping and enhancing decision-making processes. A wide variety of research studies has been developed in AI, covering many different areas, from Health to Agriculture, from Industry to Information Technology. Nevertheless, only a few works have focused on the impact of applying AI on people’s confidence and their reflections on training needs. The novelty of this study concerns the introduction of a hybrid two-step approach based on machine learning and multilevel modeling to assess the effect of people’s awareness, attitude and trust in AI on the probability of training needs. In particular, the Boruta Random Forest algorithm will be applied to identify the key determinants of training needs in AI in eight European countries to be included in the multilevel logit model. Then, the probability of European citizens’ educational needs in AI will be computed and analyzed with respect to gender
BOOK OF SHORT PAPERS: IES 2023
No full textThe odor emissions generated by treatment plants imply complex environmental and economic issues. The modern instrumental odor monitoring systems based on array of several sensors, continuously record the gaseous compounds, but they are characterized by poor selectivity thus compromise the possibility to discriminate and identify the emission sources. In this paper, the ability of odor sensors to distinguish the treatment plant sections generating the gaseous compounds is evaluated by a machine learning classification approach, the Random Forest. The goodness of this method is highlighted through apt performance measures and also with respect to the classical multiple discriminant analysis
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
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