1,720,957 research outputs found
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe 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
Get PDF“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
Get PDFWe 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
Get PDFWe 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
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe 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
Phenomena-based process intensification methods
No full textIntenzifikacija procesa na temelju fenomena jedna je od metoda intenzifikacije procesa koja ima velik potencijal sintetiziranja novih izvedba procesa te poboljšavanje postojećih. Novi trend u holističkom pristupu intenzifikaciji procesa je tzv. pristup “odozdo prema gore“ (engl. bottom-up approach). Taj se pristup intenzifikaciji procesa razlikuje od tradicionalnog koji se temelji na jediničnim operacijama. Ovakav pristup temelji se na fizikalnim i kemijskim fenomenima koji direktno utječu na pokretačke sile povezane uz određene zadatke unutar procesa. Nadalje, kombiniranjem pojedinih fenomena u strukture postepeno se dolazi do razine jediničnih operacija, odnosno do dijagrama tokova mogućih procesa. U ovom radu dan je pregled sinteze intenzificiranih procesa na temelju fenomena koristeći metodologiju koju je razvio Garg. [1] Metodologija se sastoji od 13 koraka podijeljenih u četiri faze te od različitih algoritama i baza podataka. Metodologija je prikazana na primjeru sinteze procesa zaslađivanja prirodnog plina, odnosno izdvajanja CO2 i H2S na platformi. Izdvojene procesne izvedbe uspoređuju se s konvencionalnim procesom, koji se temelji na apsorpciji kiselih plinova (CO2 i H2S) koristeći otopine amina. [1,2,5]Phenomena-based process intensification is one of the methods of process intensification that has a great potential for synthesizing new process alternatives and improving existing ones. A recent trend in terms of holistic process intensification approaches is the use of bottom-up approach. This approach to process intensification diverts from traditional unit-operation based. These bottom-up approaches are based on the physicochemical phenomena that directly affect the driving forces associated with certain tasks within the process. Furthermore, by combining individual phenomena into structures, one gradually reaches the level of unit operations, i.e., the flowsheets of possible processes. This paper provides an overview of methodology for phenomena-based process synthesis intensification developed by Garg.[1] The methodology consists of 13 steps across four stages and different algorithms and databases. The application of methodology is presented on the synthesis of the natural gas sweetening process, that is, the separation of CO2 and H2S on a platform. Selected process alternatives are compared with the conventional natural gas sweetening process, based on the absorption of sour gases (CO2 and H2S) using amine solutions. [1,2,5
Phenomena-based process intensification methods
No full textIntenzifikacija procesa na temelju fenomena jedna je od metoda intenzifikacije procesa koja ima velik potencijal sintetiziranja novih izvedba procesa te poboljšavanje postojećih. Novi trend u holističkom pristupu intenzifikaciji procesa je tzv. pristup “odozdo prema gore“ (engl. bottom-up approach). Taj se pristup intenzifikaciji procesa razlikuje od tradicionalnog koji se temelji na jediničnim operacijama. Ovakav pristup temelji se na fizikalnim i kemijskim fenomenima koji direktno utječu na pokretačke sile povezane uz određene zadatke unutar procesa. Nadalje, kombiniranjem pojedinih fenomena u strukture postepeno se dolazi do razine jediničnih operacija, odnosno do dijagrama tokova mogućih procesa. U ovom radu dan je pregled sinteze intenzificiranih procesa na temelju fenomena koristeći metodologiju koju je razvio Garg. [1] Metodologija se sastoji od 13 koraka podijeljenih u četiri faze te od različitih algoritama i baza podataka. Metodologija je prikazana na primjeru sinteze procesa zaslađivanja prirodnog plina, odnosno izdvajanja CO2 i H2S na platformi. Izdvojene procesne izvedbe uspoređuju se s konvencionalnim procesom, koji se temelji na apsorpciji kiselih plinova (CO2 i H2S) koristeći otopine amina. [1,2,5]Phenomena-based process intensification is one of the methods of process intensification that has a great potential for synthesizing new process alternatives and improving existing ones. A recent trend in terms of holistic process intensification approaches is the use of bottom-up approach. This approach to process intensification diverts from traditional unit-operation based. These bottom-up approaches are based on the physicochemical phenomena that directly affect the driving forces associated with certain tasks within the process. Furthermore, by combining individual phenomena into structures, one gradually reaches the level of unit operations, i.e., the flowsheets of possible processes. This paper provides an overview of methodology for phenomena-based process synthesis intensification developed by Garg.[1] The methodology consists of 13 steps across four stages and different algorithms and databases. The application of methodology is presented on the synthesis of the natural gas sweetening process, that is, the separation of CO2 and H2S on a platform. Selected process alternatives are compared with the conventional natural gas sweetening process, based on the absorption of sour gases (CO2 and H2S) using amine solutions. [1,2,5
Prediction of fouling formation in an industrial heat exchanger using machine learning methods
No full textNastajanje naslaga u industrijskim izmjenjivačima topline smanjuje učinkovitost izmjenjivača, povećava operativne troškove, dovodi do veće potrošnje energenata i posljedično povećane emisije CO2. Naslage predstavljaju jedan od najvećih problema u rafinerijskim postrojenjima, a njihovo nastajanje posebno je izraženo u sekciji za predgrijavanje sirove nafte. Kako bi se optimiziralo održavanje izmjenjivača topline i postigle financijske uštede, potrebno je kontinuirano pratiti nastajanje naslaga u izmjenjivačima topline. Zbog složenog sastava sirove nafte, nepoznatog mehanizma nastajanja naslaga i promjenjivih procesnih uvjeta ne postoji opće prihvaćeni empirijski ili polu-emipirijski model za praćenje nastajanja naslaga u izmjenjivačima topline u sekciji za predgrijavanje. Stoga se sve češće koriste modeli temeljeni na podacima. U ovom diplomskom radu, razvijeni su modeli umjetnih neuronskih mreža i modeli ekstremnog gradijentnog pojačavanja za predviđanje izlazne temperature tople i hladne struje čistog izmjenjivača topline. Modeli su razvijeni koristeći fizikalno-kemijska svojstva sirove nafte i kontinuirane praćene procesne varijable iz rafinerijskog postrojenja. Postupna razlika između predviđenih i stvarnih temperatura ukazuje na smanjenje učinkovitosti izmjenjivača topline zbog prisutnosti naslaga. Najbolji modeli detaljnije su analizirani, a njihove izlazne temperature korištene su za izračun fouling faktora, koji pruža kvantitativan uvid u proces nastajanja naslaga. Koristeći ovu metodologiju može se dobiti uvid u trend nastajanja naslaga. Primjena razvijenih modela na rafinerijskom postrojenju omogućila bi kontinuirano praćenje nastajanja naslaga u izmjenjivačima topline, čime bi se postigle značajne financijske uštede i osiguralo pravovremeno čišćenje izmjenjivača.Fouling formation in industrial heat exchangers reduces their efficiency, increases operational costs, leads to higher energy consumption which consequently raises CO2 emissions. Fouling is one of the biggest problems in refineries, particularly pronounced in crude oil preheating plant. To optimize the maintenance of heat exchangers and achieve financial savings, it is essential to continuously monitor fouling formation in heat exchangers. Due to the complex composition of crude oil, the unknown mechanisms of fouling formation, and variable process conditions, there is no generally accepted empirical or semi-empirical model for monitoring fouling in heat exchangers within the preheat train. Therefore, it has become a common practice to use data-driven models. In this master's thesis, artificial neural network and Extreme Gradient Boosting models have been developed to predict the outlet temperatures of the hot and cold streams of the clean heat exchanger. These models were developed using the physicochemical properties of crude oil and continuously monitored process variables from the refinery. The gradual difference between the predicted and actual temperatures indicates a reduction in the efficiency of the heat exchanger due to the presence of fouling. The best models were analyzed in detail, and their outlet temperatures where used to calculate the fouling factor, which provides quantitative insight into the fouling formation process. Using this methodology, it is possible to gain insight into the trend of fouling formation. The application of the developed models in the refinery would enable continuous monitoring of fouling in heat exchangers, resulting in significant financial savings and ensuring timely cleaning of the exchangers
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