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The Seurat effectHylton, Jennifer Sherlock 15 February 2013 (has links)
Seurat’s contemporaries regarded his work as cold and mechanical, in the most pejorative way. Viewers in the late nineteenth century were inclined to chastise him and his impersonal touch and mechanical figures. By the early decades of the next century that view had been almost entirely replaced, and a new understanding of Seurat had blossomed: far from representing the threat of a mechanical world, he came to embody its promise. To these critics, Seurat’s technique was perfectly suited to their own era’s embrace of technology. Yet, as the modern era has begun to take shape, a third view of the artist has become more common. Although some viewers still regard his work as mechanical or formulaic in respects, an increasing number of scholars and artists reject the idea that his work is cold and mechanical at all. The purpose of this dissertation is to explore why these varying perceptions of Seurat were formed and how each reflects on the time in which it was embraced. / text
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Helldunkel, Raum und Form : Georges Seurat als Zeichner : mit einem Anhang Seurats schriftliche Selbstzeugnisse und annotierter Bibliographie /Paquet, Peter. January 1900 (has links)
Texte remanié de: Diss.--Saarbrücken, 1997. / Bibliogr. p. 379-485. Notes bibliogr.
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Seurat and Art NouveauSolomon, Ila Joyce. January 1961 (has links)
Thesis (M.A.)--University of Wisconsin--Madison, 1961. / Typescript. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references.
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DOCUMENTING DESIGN RATIONALE TO PROMOTE LEARNINGMalloy, John William 05 May 2014 (has links)
No description available.
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Welt und Stimmung bei Puvis de Chavannes, Seurat und GauguinThomas, Kerstin January 2005 (has links)
Zugl. überarb. Fassung von: Frankfurt (Main), Univ., Diss., 2005 u.d.T.: Thomas, Kerstin: Stimmung als malerische Weltaneignung
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The Models' Morality: A Study of Seurat's Les PoseusesNowlin, Kaitlin Veronica January 2014 (has links)
Completed in 1888 Georges Seurat's monumental canvas, Les Poseuses, depicts three models in various states of undress within the artist's studio. Given the relative seclusion of this work until the Barnes Foundation's landmark move to Philadelphia in May of 2012, Les Poseuses has not received the same amount of critical attention as his other canvases of combat. Despite the fact that artists in the nineteenth century regularly used professional models, their profession and, by extension, their very being had become significantly stigmatized in Parisian society. Over time prejudices developed and resulted in the unwarranted ostracizing of these working-class women from general Parisian society. This thesis will attempt to prove Seurat was not only keenly aware of the reputation of models, but that in Les Poseuses he actively sought to recognize these preconceptions through a consideration of the influence of Orientalism and fashion and the implications of the inclusion of Un Dimanche à la Grande Jatte in the background in his depiction of three working-class women. / Art History
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Benchmarking of computational methods for Spatial Transcriptomics Data analysis / Jämförande analys av beräkningsmetoder för Spatial Transcriptomics data analyserTaherpour, Nima January 2022 (has links)
Ökningen av sekvenseringsdata har skapat ett behov av att ta fram nya och flexibla analysmetoder för att kunna analysera datan. Många sekvenseringsteknologier har utvecklats genom åren, med olika syften och de är idag mer specialiserade. Kostnaden för att sekvensera har även sjunkit kraftigt och idag är kostnaden bara en bråkdel av kostnaden för 20 år sedan. En av dessa heter Spatial Transcriptomics där mRNA kan analyseras med Spatiell upplösning. Experimenten skapar stora mängder data och analysmetoder som ursprungligen var utvecklade för scRNA-seq har nu ocksp blivit mer specialiserade mot spatial data. En analysmetod som använts länge är Seurat som utvecklades av Satija labbet under 2015. Men de senaste åren har även nya metoder utvecklats. Två av dessa, Giotto och Squidpy kommer att jämföras med Seurat som referens för att reda ut hur bra de presterar för Spatial Transcriptomics analyser. Datan som kommer användas kommer från hjärnvävnad från fyra olika möss som testades i NASAs RR3 mission. Två av mössen är av ”flight” skick och kommer jämföras med två stycken ”ground” kontroller. I data analysen kommer Quality Control, Normalization, Integration, Dimensional reduction, Clustering och Differential Expression analysis testas. Förutom de steg som testas i analysen kommer även parametrar som analysmetodernas flexibilitet, duration och prestation att testas och jämföras. Resultaten i detta projekt visade att Seurat presterar bättre än Giotto och Squidpy utifrån de parametrar som testas. / The increase in data received from sequencing has created a need for new and accurate frameworks to analyze the data. There are many sequencing technologies developed for different purposes. They have become more specialized and the cost compared to 20 years ago is just a fraction. One of the technologies is Spatial Transcriptomics, where mRNA can be analyzed with spatial resolution. The experiments has high throughput, and frameworks that was original developed for scRNA-seq has also started to be more specialised towards spatial data. Seurat has been widely used for that purpose for many years and was developed by the Satija Lab. But many more frameworks have been developed. In this project’s scope, two other frameworks, Giotto and Squidpy, will be benchmarked with Seurat as the golden standard and a referece to examine how the frameworks perform with Spatial Transcriptomics data as input. The dataset consists of four mouse brain tissue sections from the NASA RR3 mission. Two of the mouse brains are of ”flight” condition while the two others are used as ”ground” controls. The pipeline used in all three frameworks includes Quality Control, normalization, integration, dimensional reduction, clustering, and differential expression analysis. Except for the pipeline steps other parameters has been tested including: the flexibility of the frameworks, the duration of analysis, and the performance. The results showed that Seurat outperforms Giotto and Squidpy according to the tested parameters. Mainly because of more developed integration features when working with multiple data. But both Squidpy and Giotto shows great potential and has a lot of features that was not useful for this project, but however can for other projects be very promising.
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<b>Immersion in Georges Seurat’s Painting “La Grande Jatte” with VR: A Study for Art Appreciation</b>Siddhant Bal (19182175) 20 July 2024 (has links)
<p dir="ltr">The study aims to provide insight into improving the understanding and, in tandem, appreciation of a traditional art piece, the "Sunday Afternoon on the Island of La Grande Jatte" made by Georges Seurat, using virtual reality.</p>
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Defining A Character Through Voice Quality: An Analysis Of The Character "george" In Sondheim And Lapine's Sunday In The Park With George Using The Estill Voice ModelSwickard, Michael 01 January 2007 (has links)
This thesis explores the use of the Estill Voice Model, in particular six voice qualities (Speech, Twang, Falsetto, Cry/Sob, Belt and Opera) and their permutations, to define character, character traits and emotions. Traits and emotions that specific voice qualities can influence are, but are not limited to, location, age, background, socioeconomic status, genre, intelligence, nationality, class, culture, gender, promiscuity, disposition, pain and revelations. In particular, this thesis explores the use of voice qualities to show specific human qualities of the character "George" from Sondheim and Lapine's "Sunday in the Park with George" and the people he imitates in his painting by letting the characters' given circumstances (textual and subtextual), the way other actors portray the characters and the director's and musical director's input inform the choices in voice quality. By using the specific technical aspects of the Estill Voice Training System and combining them with the limi
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