1,721,096 research outputs found
Fast and effective classification of plastic waste by pushbroom hyperspectral sensor coupled with hierarchical modelling and variable selection
No full textPlastic waste management represents a global challenge in the framework of sustainable production and consumption of resources. One of the most critical issues in plastic recycling is polymer separation, necessary to obtain high-quality secondary raw material flow streams. The aim of this work was to build a classification strategy, based on pushbroom hyperspectral imaging, able to recognize the most common polymers found in mixed plastic waste to be applied at recycling plant scale. After exploring polymer spectral differences by principal component analysis, a hierarchical partial least squares-discriminant analysis, based on the acquired full spectra, and a hierarchical interval partial least squares-discriminant analysis, based on selected variables, were tested and their performances were evaluated and compared. High quality classification results were obtained in both cases, demonstrating that the developed multi-class models can be utilized in a flexible way for quality control and/or for on-line sorting actions in recycling plants
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
Investigating the COVID-19 vaccine discussions on Twitter through a multilayer network-based approach
No full textModeling discussions on social networks is a challenging task, especially if we consider sensitive topics, such as politics or healthcare. However, the knowledge hidden in these debates helps to investigate trends and opinions and to identify the cohesion of users when they deal with a specific topic. To this end, we propose a general multilayer network approach to investigate discussions on a social network. In order to prove the validity of our model, we apply it on a Twitter dataset containing tweets concerning opinions on COVID-19 vaccines. We extract a set of relevant hashtags (i.e., gold-standard hashtags) for each line of thought (i.e., pro-vaxxer, neutral, and anti-vaxxer). Then, thanks to our multilayer network model, we figure out that the anti-vaxxers tend to have ego networks denser (+14.39%) and more cohesive (+64.2%) than the ones of pro-vaxxer, which leads to a higher number of interactions among anti-vaxxers than pro-vaxxers (+393.89%). Finally, we report a comparison between our approach and one based on single networks analysis. We prove the effectiveness of our model to extract influencers having ego networks with more nodes (+40.46%), edges (+39.36%), and interactions with their neighbors (+28.56%) with respect to the other approach. As a result, these influential users are much more important to analyze and can provide more valuable information
Detection of asbestos containing material in post-earthquake building waste through hyperspectral imaging and micro-x-ray fluorescence
No full textDuring an earthquake, a large amount of waste was generated, and many Asbes-tos-Containing Materials (ACM) were unintentionally destroyed. ACM is a mixture of cement matrix and asbestos fiber, widely used in construction materials, that causes serious diseases such as lung cancer, mesothelioma and asbestosis, as a conse-quence of inhalation of the asbestos fiber. In order to reuse and recycle Post -earth- quake Building Waste (PBW) as secondary raw material, ACM must be separately collected and deposited from other wastes during the recycling process. The work aimed to develop a non-destructive, accurate and rapid method to detect ACM and recognize different types of PBW to obtain the best method to correctly identify and separate different types of material. The proposed approach is based on Hyper -spectral Imaging (HSI) working in the short-wave infrared range (SWIR, 1000-2500 nm), followed by the implementation of a classification model based on hierarchical Partial Least Square Discriminant Analysis (hierarchical-PLS-DA). Micro-X-ray fluo- rescence (micro-XRF) analyses were carried out on the same samples in order to evaluate the reliability, robustness and analytical correctness of the proposed HSI approach. The results showed that the applied technology is a valid solution that can be implemented at the industrial level
Hyperspectral imaging as powerful technique for investigating the stability of painting samples
No full textThe aim of this work is to present the utilization of Hyperspectral Imaging for studying the stability of painting samples to simulated solar radiation, in order to evaluate their use in the restoration field. In particular, ready-to-use commercial watercolours and powder pigments were tested, with these last ones being prepared for the experimental by gum Arabic in order to propose a possible substitute for traditional reintegration materials. Samples were investigated through Hyperspectral Imaging in the short wave infrared range before and after artificial ageing procedure performed in Solar Box chamber under controlled conditions. Data were treated and elaborated in order to evaluate the sensitivity of the Hyperspectral Imaging technique to identify the variations on paint layers, induced by photo-degradation, before they could be detected by eye. Furthermore, a supervised classification method for monitoring the painted surface changes, adopting a multivariate approach was successfully applied
Evaluation of elements distribution in printed circuit boards from mobile phones by micro x-ray fluorescence
Full text linkA micro X-ray fluorescence-based approach for the chemical characterization of spent printed circuit boards (PCBSPCBSS) from mobile phones was applied. More in detail, twelve spent mobile phones were grouped into three clusters according to brands, models and year of release, and a study to evaluate the technological evolution of PCBSs over time was carried out. Precious metals and hazardous elements were investigated, revealing a few differences between samples from the different groups. For instance, the distribution of gold on PCBS layers was more widespread for the older analyzed samples, and smaller quantities of bromine and lead were detected in the more recent models in accordance with the Restriction of Hazardous Substances Directive 2002/95/EC. Analysis of PCBS composition should contribute towards correctly managing such a complex waste, maximizing the recovery of base, critical and precious metals and considering the possible presence of harmful elements requiring careful management. The experimental results showed how, using the proposed approach, distribution maps for chemical elements present in PCBSs could be obtained, thus allowing the definition of optimal strategies for further handling (i.e. classification) and processing (i.e. critical/precious metal recovery)
Near infrared hyperspectral imaging-based approach for end-of-life flat monitors recycling. Nahinfrarot-Hyperspektralbild-basierter Ansatz zum Recycling alter Flachbildschirme
No full textThe technological innovation and the relentless marketing of new electronic products with improved performance generate increasing quantities of Waste from Electrical and Electronic Equipment (WEEE). In this scenario, End-Of-Life (EOL) flat monitors and screens represent a category generating, as a consequence of the rapid change in technology, an important amount of waste. Considering future estimations, the implementation of an adequate recycling infrastructure is necessary. An efficient, reliable and low-cost analytical tool is thus needed to perform detection/control actions in order to assess: i) waste composition and ii) physical-chemical attributes of the resulting materials. The knowledge of these information is a requirement to set-up and to implement correct recycling actions. In this study, a cascade identification approach, based on Near InfraRed (NIR) - HyperSpectral Imaging (HSI), was carried out. More in detail, a four-steps classification was designed, implemented and set-up in order to recognize different materials occurring in a specific WEEE stream: EOL milled monitors and flat screens. Adopting the proposed approach, different material categories are correctly recognized and classified. Obtained results can be useful not only to set-up a quality control system, but also to improve sorting actions in this specific recycling sector
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