Academic literature on the topic 'Pythons – Fiction'

In this paper, python is used to obtain the data of the top 100 global movie ticket rooms, and through datavisualization, it is concluded that the global movie box office will peak in the next 10 years. Science fiction actionmovies are more popular. r-language was used to construct log-linear models, respectively. The results of therandom unit group design model showed that science fiction action movies were more favorable to the box office.Through k-means clustering analysis, it was concluded that the guidance of well-known directors had more positiveeffects on the box office. According to the above conclusions, the major cinemas and film and television companiesmake relevant suggestions.

In this paper, python is used to obtain the data of the top 100 global movie ticket rooms, and through data visualization, it is concluded that the global movie box office will peak in the next 10 years. Science fiction action movies are more popular. r-language was used to construct log-linear models, respectively. The results of the random unit group design model showed that science fiction action movies were more favorable to the box office. Through k-means clustering analysis, it was concluded that the guidance of well-known directors had more positive effects on the box office. According to the above conclusions, the major cinemas and film and television companies make relevant suggestions.

In this paper, python is used to obtain the data of the top 100 global movie ticket rooms, and through data visualization, it is concluded that the global movie box office will peak in the next 10 years. Science fiction action movies are more popular. r-language was used to construct log-linear models, respectively. The results of the random unit group design model showed that science fiction action movies were more favorable to the box office. Through k-means clustering analysis, it was concluded that the guidance of well-known directors had more positive effects on the box office. According to the above conclusions, the major cinemas and film and television companies make relevant suggestions.

The study deals with NLP procedures on the material of the fiction texts in German and in English, which are considered as strong cultural texts. The aim of the study is to develop a model of such a technical device to process, analyze and interpret a fiction text, which would reveal the full potential of popular NLP tools within the corpus approach. The general methods used in the study are analysis and synthesis. Special methods are additionally used to solve certain specific issues: descriptive method, modelling and qualitative and quantitative analysis. The scientific novelty lies in the fact that the authors apply the crucial principles of the classical theories of text interpretation according to the latest methods and tools of the applied linguistics. As a practical result, special software has been developed, which is able to process SQL based linguistic corpora, automatically built with spaCy NLP library and Python programming language. This software can be used for a fiction text interpretation, as well as for compiling learning materials in Home Reading. It is assumed that the development of special software for strong cultural texts stimulates the search for scientific solutions and at the same time allows one to understand the essential differences that exist between natural and artificial intelligence.

Abstract Augmented reality has come a long way from the concept of science fiction to science-based reality. Until recently, the cost of augmented reality was so high that designers only dreamed of working on an AR related design project. Things have changed now, and augmented reality is also available on mobile phones. An e-learning Augmented Reality application for immersive and practical based learning is proposed in this paper where any student can make use of this platform to learn concepts easily in Augmented Reality. This has been implemented by using technologies like Unity, Zappar and deploying the project on web using python and Django. By incorporating AR technology in education, students can effectively learn and understand complex concepts in a more engaging and interactive way.

Abstract: The present work aims to classify the genre of the books automatically using the Python programming language. A genre is a subset of art, literature, or music that has a distinct form, substance, and style. In many instances, a book can be classified as belonging to more than one genre. It's difficult to categorize a book or piece of literature as belonging to one genre over another. Many novels end up badly categorized or pushed under the super-genre umbrella of fiction since there is no clear criterion to determine how much of a book belongs to a given genre. Therefore, it's critical to develop a system for categorizing books and determining their relevance to a particular genre. Therefore, the current study tries to solve this challenge by combining various text categorization approaches and models to come up with the best solution

Die Geschichte der Menschheit ist voll von Entdeckungsreisen. Sie haben teilweise mythisch-erzählerischen Charakter und reichen von den sagenhaften Reisen der griechischen Argonauten, den Irrfahrten des Odysseus oder den Abenteuern Sindbad des Seefahrers aus 1001 Nacht bis hin zu Stanley Kubricks moderner filmischer Science-Fiction-Erzählung „2001: Odyssee im Weltall“ (1968) eintausend Jahre später, zu „E.T.“ und „Star Wars“. Neben diesen Geschichten gibt es auch die tatsächliche, historisch belegte Geschichte und ihre nicht minder packenden Inhalte: Die Fahrt des Griechen Pytheas schon im vierten vorchristlichen Jahrhundert bis zum Polarkreis, die Besiedlung Grönlands durch Erik den Roten und die daran anschließende erste europäische Besiedlung Amerikas um das Jahr 1000 (Leif Eriksson), im 15.

A Review of: Xiao, J., & Gao, W. (2020). Connecting the dots: reader ratings, bibliographic data, and machine-learning algorithms for monograph selection. The Serials Librarian, 78(1-4), 117-122. https://doi.org/10.1080/0361526X.2020.1707599 Objective – To illustrate how machine-learning book recommender systems can help librarians make collection development decisions. Design – Data analysis of publicly available book sales rankings and reader ratings. Setting – The internet. Subjects – 192 New York Times hardcover fiction best seller titles from 2018, and 1,367 Goodreads ratings posted in 2018. Methods – Data were collected using Application Programming Interfaces. The researchers retrieved weekly hardcover fiction best seller rankings published by the New York Times in 2018 in CSV file format. All 52 files, each containing bibliographic data for 15 hardcover fiction titles, were combined and duplicate titles removed, resulting in 192 unique best seller titles. The researchers retrieved reader ratings of the 192 best seller titles from Goodreads. The ratings were limited to those posted in 2018 by the top Goodreads reviewers. A Bayes estimator produced a list of the top ten highest rated New York Times best sellers. The researchers built the recommender system using Python and employed several content-based and collaborative filtering recommender techniques (e.g., cosine similarity, term frequency-inverse document frequency, and matrix factorization algorithms) to identify novels similar to the highest rated best sellers. Main Results – Each recommender technique generated a different list of novels. Conclusion – The main finding from this study is that recommender systems can simplify collection development for librarians and facilitate greater access to relevant library materials for users. Academic libraries can use the same recommender techniques employed in the study to identify titles similar to highly circulated monographs or frequently requested interlibrary loans. There are several limitations to using recommender systems in libraries, including privacy concerns when analyzing user behaviour data and potential biases in machine-learning algorithms.

Python programme contains a question and answer system that derived from data sets that have used and implemented the chatbot in this modern era. where the data collected is in the form of corpuses containing extensive metadata-rich fictional conversations derived from extracted film scripts, commonly called cornell movie dialogue corpus. The various models have been used chatbots in python programmes, and LSTM and BiLSTM models were specifically used in this study. Where the form of accuracy will be reported as a result of the implementation of LSTM and BiLSTM models in the chatbot programme. The programme performance will be influenced by the data from the model selection, because the level of accuracy is determined by the target programme being taken. So this is the main factor that determines which model to choose. Based on considerations required for choosing the programme model, in the end the LSTM and the BiLSTM models are chosen and will be applied to the programme. Based on the LSTM and BiLSTM chatbot programmes that have been tested, it can be concluded that the best parameters come from a pair of BiLSTM chatbots using the BiLTSM model with an average accuracy value of 0.995217.

Cette recherche porte sur The Hitchhiker’s Guide to the Galaxy, une série de science-fiction humoristique britannique créée pour la BBC Radio 4 en 1978. Sur la période étudiée (1978 – 2009), la série a été déclinée sur tous les supports que peut offrir la culture de masse. Dans les premières années, la série trouve un écho important auprès des adolescents, des étudiants et des jeunes adultes. L’auteur de la série - Douglas Adams - a gardé la main sur toutes les incarnations de Hitchhiker’s. Au cours de sa vie, l’auteur de cette science-fiction qui veut faire rire a progressivement été qualifié de « gourou de la technologie » par la presse. Les grandes passions de Douglas Adams étaient effectivement au nombre de quatre : les ordinateurs, l’évolution des espèces, les Beatles et les Monty Pythons. Cette recherche s’attache donc à comprendre comme ces quatre éléments se sont articulés dans la vie de Douglas Adams, l’influence qu’ils ont eu sur Hitchhiker’s et ce que le succès de la série dit des évolutions de la société britannique. The Hitchhiker’s Guide to the Galaxy arrive à un moment où les attentes changent en matière de comédie, comme le montre l’essor de l’Alternative Comedy. La percée de Hitchhiker’s se déroule aussi dans un contexte où la technologie prend de l’importance dans la vie quotidienne et où la culture geek prend forme, à la croisée des mondes imaginaires et de l’informatique. Le retentissement de la série peut aussi se voir comme un témoignage de l’existence de ce que le sociologue Mike Savage a appelé la classe moyenne technique. Par ailleurs, en voulant créer un album de rock pour la radio, Douglas Adams a produit une fiction en adéquation avec l’univers sonore de la jeunesse des années 1970. La technologie du studio stimule la créativité, tout comme l’ordinateur personnel le fera dans les années 1980
This research focuses on The Hitchhiker’s Guide to the Galaxy, a British science-fiction comedy series created for BBC Radio 4 in 1978. Over the study period (1978-2009), the series was provided to the public in all possible formats that mass culture can offer. In its first years the series attracted a strong audience among teenagers, students and young adults. Douglas Adams, the series’ author, maintained control over all the incarnations of The Hitchhiker’s Guide to the Galaxy. Over the course of his life, the author of this science fiction series, made to make people laugh, gradually became known as a ‘‘technology guru” by the press. Indeed, Douglas Adams had four great passions : computers, evolution of species, the Beatles and the Pythons. Therefore, this research endeavours to understand how these four topics were expressed in Douglas Adams’ life, the influence they had on Hitchhiker’s and how this series’ success shows the evolution of British society. The Hitchhiker’s Guide to the Galaxy occurs at a time when expectations towards comedy were changing, as shown by the rise of Alternative Comedy. Hitchhiker’s breakthrough also takes place at a time when technology was gaining importance in daily life and geek culture was developing, at the crossroads of imaginary worlds and computer science. The series’ impact can also be considered as evidence of what the sociologist Mike Savage called the technical middle class. In addition, by creating a rock album for the radio, Douglas Adams created a fantasy consistent with the musical universe of the 1970s youth. The technology used in the radio studio stimulates creativity, just like the personal computer will do in the 1980s

In this chapter, we present the dataset used in the course of this book. Our case study is built upon fictional data. This process implied “collecting” data, and we will explain each of the chosen variables with more detail.

Boy vocalists in children’s company plays by Richard Edwards, John Marston, and Ben Jonson were portrayed as ideal vehicles for poetry, as though their charming, dainty music would provide a means of perfect transmission. Yet children’s singing was also understood to be highly sensuous and erotic—bringing out some of the most licentious dimensions of theatrical experience. This mismatch between ideal communication and embodied performance was often represented in terms of sexual violence, with boy servants graphically punished for altering the messages they were bound to convey. Plays including Edwards’s Damon and Pythias, Marston’s What You Will, and Jonson’s Epicene celebrate child singers’ virtuosity, including their capacity to reimagine their scripts and expose patterns of subjection to critical scrutiny. Song becomes a means of redirecting audiences to the extra-fictional boundaries of theatrical experience, and articulating new registers of poetic meaning grounded in the perspectives of boy performers.

O GMA é o Grupo de Modelagem Avançada da Universidade Federal de Santa Catarina (UFSC), formalizado por meio de um Programa de Extensão universitária e tem como propósito promover eventos e cursos de extensão em temas variados, incluindo modelagem BIM, paramétrica, simulação e automatização na arquitetura. O grupo é formado por professores do Departamento de Arquitetura e Urbanismo e Design, estudantes de graduação e pós-graduação da Universidade Federal de Santa Catarina e profissionais. O Ciclo de Oficinas GMA é um evento semestral promovido por este grupo, ocorrendo no início do semestre letivo de ensino da graduação. Este Ciclo promove cursos de formação complementar sobre ferramentas BIM e de modelagem paramétrica, além de outros cursos que incentivam a adoção de tecnologia da informação e automatização de processos de projeto no campo da Arquitetura e Urbanismo. O Ciclo de Oficinas GMA aborda assuntos não contemplados no rol de conteúdos do currículo do curso de Graduação em Arquitetura e Urbanismo da Universidade Federal de Santa Catarina e realiza-se de forma aberta à comunidade. No semestre 2020.1 foi realizado o “I Ciclo de Oficinas GMA” durante os meses de Fevereiro e Março de 2020, de forma presencial antes da suspensão das atividades devido à pandemia do Covid-19. No semestre 2020.2 ocorreu o “II Ciclo de Oficinas GMA” de forma remota entre os dias 25 de Janeiro e 12 de Fevereiro de 2021. O “I Ciclo de Oficinas GMA” contemplou seis cursos de extensão: (1) Digitalização da construção e Modelagem no ArchiCAD; (2) Introdução à parametrização com Grasshopper; (3) Introdução a maquetes de papel com prototipagem digital; (4) Oficina de arquitetura performativa; (5) Oficina de auTETEmação com Arduino e (6) Oficina de paisagismo: a utilização de aplicativos de reconhecimento de vegetação. Os instrutores dos cursos foram 2 estudantes da graduação em Arquitetura e Urbanismo, 4 estudantes da Pós-Graduação em Arquitetura e Urbanismo, 1 estudante de Pós-Graduação em Engenharia e Gestão do Conhecimento e duas profissionais em Arquitetura e Urbanismo, além de dois professores do Departamento de Arquitetura e Urbanismo da Universidade Federal de Santa Catarina. Foram 99 inscrições realizadas e homologadas por meio do Sistema “Inscrições UFSC”, de 12/02/2020 a 22/02/2020. O “II Ciclo de Oficinas GMA” contemplou um evento de extensão de abertura realizado por meio de uma mesa redonda com o tema “Inovação e Arquitetura”, além de 12 Cursos de Extensão, todos gratuitos e realizados de forma remota pela ferramenta Google Meet. Foram 212 inscrições realizadas e homologadas por meio do Sistema “Inscrições UFSC”, de 18/01/2021 a 22/01/2021. No evento de abertura foi debatido como ocorre a inovação na área da arquitetura, além da aplicação de tecnologias de projeto e de construção, mostrando novas formas de se pensar a arquitetura nos campos social e econômico. O evento foi organizado em parceria com a startup Think&Make e contou com a presença de três convidados externos à Instituição de Ensino Superior e uma integrante da startup como mediadora. Os doze cursos de extensão realizados contemplam os seguintes temas e cargas horárias: (a) A geração de formas na composição paisagística: composição em lógica criativa (8hrs); (b) Introdução à ferramenta BIM Graphisoft Archicad (8-16hrs); (c) Introdução à ferramenta BIM Autodesk Revit (8-16hrs); (d) Ateliê Pescarte - Cultura, Projeto & Paisagem: A pesca artesanal estruturando espaços (4hrs); (e) Introdução à modelagem paramétrica com Grasshopper (8hrs); (f) Introdução à análise do clima e componentes de simulação com Grasshopper (8hrs); (g) Introdução à programação com Python em ambiente de modelagem paramétrica (8hrs); (h) Introdução à programação com C# em ambiente de modelagem paramétrica (8hrs); (i) Avaliando Espaços Criativos: avaliação de parâmetros de bem-estar e produtividade no espaço de trabalho; (j) Introdução à maquetes de papel com processos automatizados (8hrs); (k) Running Drawing - Mídias digitais e a percepção urbana (8hrs); e (l) Design Fiction para Arquitetura e Urbanismo (20hrs). Todos os cursos foram divulgados nas redes sociais (https://www.instagram.com/gma.ufsc/) e sites do GMA (https://www.gmaufsc.com.br/ciclo-de-oficinas-2021). Os instrutores dos cursos são 4 estudantes da graduação em Arquitetura e Urbanismo, 5 estudantes da Pós-Graduação em Arquitetura e Urbanismo, 1 estudante de Pós-Mestrado no Programa de Pós-Graduação em Engenharia Civil, 1 estudante de Pós-Graduação em Engenharia do Conhecimento e três profissionais em Arquitetura e Urbanismo, além de dois professores do Departamento de Arquitetura e Urbanismo da Universidade Federal de Santa Catarina. Quanto à adaptação às áreas de difusão BIM propostas por Succar (2015), essa experiência enquadra-se principalmente nas políticas de integração e colaboração entre diferentes áreas da educação superior e no desenvolvimento de competências individuais básicas níveis operacional, técnico e pesquisa e desenvolvimento. Esta ação de extensão promove a interdisciplinaridade pela organização envolvendo estudantes de diferentes Departamentos desta Universidade e níveis de formação (Graduação e Pós), além de envolver profissionais da área, contribuindo para a formação dos estudantes. Além disso, a realização destes cursos para a comunidade envolve a articulação com o ensino e a pesquisa. Apresentação no YouTube: https://youtu.be/itFFVQEwsYc