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Document Analysis and Recognition – ICDAR 2024 Workshops: Athens, Greece, August 30–31, 2024, Proceedings, Part I (Lecture Notes in Computer Science #14935)
by Harold Mouchère Anna ZhuThis two-volume set LNCS 14935-14936 constitutes the proceedings of International Workshops co-located with the 18th International Conference on Document Analysis and Recognition, ICDAR 2024, held in Athens, Greece, during August 30–31, 2024. The total of 30 regular papers presented in these proceedings were carefully selected from 46 submissions. Part I contains 16 regular papers that stem from the following workshops: ICDAR 2024 Workshop on Automatically Domain-Adapted and Personalized Document Analysis (ADAPDA); ICDAR 2024 Workshop on Advanced Analysis and Recognition of Parliamentary Corpora (ARPC); ICDAR 2024 Workshop on coMics ANalysis, Processing and Understanding (MANPU). Part II contains 14 regular papers that stem from the following workshops: ICDAR 2024 Workshop on Computational Paleography (IWCP); ICDAR 2024 Workshop on Machine Vision and NLP for Document Analysis (VINALDO).
Document Analysis and Recognition - ICDAR 2024: 18th International Conference, Athens, Greece, August 30–September 4, 2024, Proceedings, Part II (Lecture Notes in Computer Science #14805)
by Elisa H. Barney Smith Marcus Liwicki Liangrui PengThis six-volume set LNCS 14804-14809 constitutes the proceedings of the 18th International Conference on Document Analysis and Recognition, ICDAR 2024, held in Athens, Greece, during August 30–September 4, 2024. The total of 144 full papers presented in these proceedings were carefully selected from 263 submissions. The papers reflect topics such as: document image processing; physical and logical layout analysis; text and symbol recognition; handwriting recognition; document analysis systems; document classification; indexing and retrieval of documents; document synthesis; extracting document semantics; NLP for document understanding; office automation; graphics recognition; human document interaction; document representation modeling and much more.
Document Analysis and Recognition - ICDAR 2024: 18th International Conference, Athens, Greece, August 30–September 4, 2024, Proceedings, Part I (Lecture Notes in Computer Science #14804)
by Elisa H. Barney Smith Marcus Liwicki Liangrui PengThis six-volume set LNCS 14804-14809 constitutes the proceedings of the 18th International Conference on Document Analysis and Recognition, ICDAR 2024, held in Athens, Greece, during August 30–September 4, 2024. The total of 144 full papers presented in these proceedings were carefully selected from 263 submissions. The papers reflect topics such as: Document image processing; physical and logical layout analysis; text and symbol recognition; handwriting recognition; document analysis systems; document classification; indexing and retrieval of documents; document synthesis; extracting document semantics; NLP for document understanding; office automation; graphics recognition; human document interaction; document representation modeling and much more.
Document Analysis and Recognition - ICDAR 2024: 18th International Conference, Athens, Greece, August 30–September 4, 2024, Proceedings, Part V (Lecture Notes in Computer Science #14808)
by Elisa H. Barney Smith Marcus Liwicki Liangrui PengThis six-volume set LNCS 14804-14809 constitutes the proceedings of the 18th International Conference on Document Analysis and Recognition, ICDAR 2024, held in Athens, Greece, during August 30–September 4, 2024. The total of 144 full papers presented in these proceedings were carefully selected from 263 submissions. The papers reflect topics such as: document image processing; physical and logical layout analysis; text and symbol recognition; handwriting recognition; document analysis systems; document classification; indexing and retrieval of documents; document synthesis; extracting document semantics; NLP for document understanding; office automation; graphics recognition; human document interaction; document representation modeling and much more.
Document Analysis and Recognition - ICDAR 2024: 18th International Conference, Athens, Greece, August 30 – September 4, 2024, Proceedings, Part III (Lecture Notes in Computer Science #14806)
by Elisa H. Barney Smith Marcus Liwicki Liangrui PengThis six-volume set LNCS 14804-14809 constitutes the proceedings of the 18th International Conference on Document Analysis and Recognition, ICDAR 2024, held in Athens, Greece, during August 30–September 4, 2024. The total of 144 full papers presented in these proceedings were carefully selected from 263 submissions. The papers reflect topics such as: document image processing; physical and logical layout analysis; text and symbol recognition; handwriting recognition; document analysis systems; document classification; indexing and retrieval of documents; document synthesis; extracting document semantics; NLP for document understanding; office automation; graphics recognition; human document interaction; document representation modeling and much more.
Document Analysis and Recognition - ICDAR 2024: 18th International Conference, Athens, Greece, August 30–September 4, 2024, Proceedings, Part IV (Lecture Notes in Computer Science #14807)
by Elisa H. Barney Smith Marcus Liwicki Liangrui PengThis six-volume set LNCS 14804-14809 constitutes the proceedings of the 18th International Conference on Document Analysis and Recognition, ICDAR 2024, held in Athens, Greece, during August 30–September 4, 2024. The total of 144 full papers presented in these proceedings were carefully selected from 263 submissions. The papers reflect topics such as: document image processing; physical and logical layout analysis; text and symbol recognition; handwriting recognition; document analysis systems; document classification; indexing and retrieval of documents; document synthesis; extracting document semantics; NLP for document understanding; office automation; graphics recognition; human document interaction; document representation modeling and much more.
Document Analysis and Recognition - ICDAR 2024: 18th International Conference, Athens, Greece, August 30–September 4, 2024, Proceedings, Part VI (Lecture Notes in Computer Science #14809)
by Elisa H. Barney Smith Marcus Liwicki Liangrui PengThis six-volume set LNCS 14804-14809 constitutes the proceedings of the 18th International Conference on Document Analysis and Recognition, ICDAR 2024, held in Athens, Greece, during August 30–September 4, 2024. The total of 144 full papers presented in these proceedings were carefully selected from 263 submissions. The papers reflect topics such as: document image processing; physical and logical layout analysis; text and symbol recognition; handwriting recognition; document analysis systems; document classification; indexing and retrieval of documents; document synthesis; extracting document semantics; NLP for document understanding; office automation; graphics recognition; human document interaction; document representation modeling and much more.
Document Analysis Systems: 16th IAPR International Workshop, DAS 2024, Athens, Greece, August 30–31, 2024, Proceedings (Lecture Notes in Computer Science #14994)
by Giorgos Sfikas George RetsinasThis book constitutes the refereed proceedings of the 16th IAPR International Workshop on Document Analysis Systems, DAS 2024, held in Athens, Greece, during August 30-31, 2024. The 27 full papers presented were carefully reviewed and selected from 43 submissions addressing topics like: document analysis and understanding; retrieval and VQA; layout analysis; document classification; OCR correction and NLP; recognition systems; and historical documents.
Document Analysis Systems: 15th IAPR International Workshop, DAS 2022, La Rochelle, France, May 22–25, 2022, Proceedings (Lecture Notes in Computer Science #13237)
by Seiichi Uchida Elisa Barney Véronique EglinThis book constitutes the refereed proceedings of the 15th IAPR International Workshop on Document Analysis Systems, DAS 2022, held in La Rochelle, France, in May 2022.The full papers presented were carefully reviewed and selected from numerous submissions addressing key techniques of document analysis.
Does God Play Dice?: The New Mathematics of Chaos
by Ian StewartSince the dramatic discovery of the mathematical concept of chaos in 1989, the controversy of its contents has settled down. This revised edition of Does God Play Dice? takes a fresh look at its achievements and potential. With a new preface and three completely new chapters, it includes the latest practical applications of chaos theory, such as developing intelligent heart pacemakers. All this provides a fascinating new answer to Einstien's question which provided the title of this book.
Does Measurement Measure Up?: How Numbers Reveal and Conceal the Truth
by John M. HenshawThere was once a time when we could not measure sound, color, blood pressure, or even time. We now find ourselves in the throes of a measurement revolution, from the laboratory to the sports arena, from the classroom to the courtroom, from a strand of DNA to the far reaches of outer space. Measurement controls our lives at work, at school, at home, and even at play. But does all this measurement really measure up? Here, John Henshaw examines the ways in which measurement makes sense or creates nonsense. Henshaw tells the controversial story of intelligence measurement from Plato to Binet to the early days of the SAT to today's super-quantified world of No Child Left Behind. He clears away the fog on issues of measurement in the environment, such as global warming, hurricanes, and tsunamis, and in the world of computers, from digital photos to MRI to the ballot systems used in Florida during the 2000 presidential election. From cycling and car racing to baseball, tennis, and track-and-field, he chronicles the ever-growing role of measurement in sports, raising important questions about performance and the folly of comparing today's athletes to yesterday's records.We can't quite measure everything, at least not yet. What could be more difficult to quantify than reasonable doubt? However, even our justice system is yielding to the measurement revolution with new forensic technologies such as DNA fingerprinting. As we evolve from unquantified ignorance to an imperfect but everpresent state of measured awareness, Henshaw gives us a critical perspective from which we can "measure up" the measurements that have come to affect our lives so greatly.
Doing Action Research in Your Own Organization (PDF)
by Teresa Brannick David CoghlanDoing Action Research in Your Own Organization is the essential resource for anyone embarking on a research project in their own organization or as part of a work placement programme whether in business, healthcare, government, education, social work or third sector organizations. The authors provide an easy-to-follow, hands-on guide to every aspect of conducting an action research project and have added in the Third Edition : more on politics and ethics to help researchers negotiate gaining access and permission, and building and maintaining support from peers and relevant subsystems within an organization more on writing an action research dissertation, and treatment of sensitive issues such as: giving feedback to one's superiors and peers, disseminating the research to the wider community, and handling interpretations or outcomes which may be perceived negatively by the organization involved more case examples and reflective exercises taken from a wide variety of organizational settings to aid students and researchers whatever their background discipline.
Doing Critical Research
by Mats Alvesson Stanley DeetzThis title builds on the success of Doing Critical Management Research which has proven to be a seminal text in the 20 years since publication. In 2020, Alvesson and Deetz have broadened their focus and updated the original book to offer relevance to critical research across all of the social sciences. In reflecting contemporary theoretical and methodological turns over the past few decades, it includes coverage of key contemporary topics such as race, gender, postmodernism and intersectionality. With examples throughout, the authors provide an authoritative and insightful framework for navigating critical theories and methods and sets out a new agenda for critical research undertaken today.
Doing Critical Research (Sage Series In Management Research Ser.)
by Mats Alvesson Stanley DeetzThis title builds on the success of Doing Critical Management Research which has proven to be a seminal text in the 20 years since publication. In 2020, Alvesson and Deetz have broadened their focus and updated the original book to offer relevance to critical research across all of the social sciences. In reflecting contemporary theoretical and methodological turns over the past few decades, it includes coverage of key contemporary topics such as race, gender, postmodernism and intersectionality. With examples throughout, the authors provide an authoritative and insightful framework for navigating critical theories and methods and sets out a new agenda for critical research undertaken today.
Doing Critical Research (Sage Series In Management Research Ser.)
by Mats Alvesson Stanley DeetzThis title builds on the success of Doing Critical Management Research which has proven to be a seminal text in the 20 years since publication. In 2020, Alvesson and Deetz have broadened their focus and updated the original book to offer relevance to critical research across all of the social sciences. In reflecting contemporary theoretical and methodological turns over the past few decades, it includes coverage of key contemporary topics such as race, gender, postmodernism and intersectionality. With examples throughout, the authors provide an authoritative and insightful framework for navigating critical theories and methods and sets out a new agenda for critical research undertaken today.
Doing Data Science in R: An Introduction for Social Scientists
by Mark AndrewsThis approachable introduction to doing data science in R provides step-by-step advice on using the tools and statistical methods to carry out data analysis. Introducing the fundamentals of data science and R before moving into more advanced topics like Multilevel Models and Probabilistic Modelling with Stan, it builds knowledge and skills gradually. This book: Focuses on providing practical guidance for all aspects, helping readers get to grips with the tools, software, and statistical methods needed to provide the right type and level of analysis their data requires Explores the foundations of data science and breaks down the processes involved, focusing on the link between data science and practical social science skills Introduces R at the outset and includes extensive worked examples and R code every step of the way, ensuring students see the value of R and its connection to methods while providing hands-on practice in the software Provides examples and datasets from different disciplines and locations demonstrate the widespread relevance, possible applications, and impact of data science across the social sciences.
Doing Data Science in R: An Introduction for Social Scientists
by Mark AndrewsThis approachable introduction to doing data science in R provides step-by-step advice on using the tools and statistical methods to carry out data analysis. Introducing the fundamentals of data science and R before moving into more advanced topics like Multilevel Models and Probabilistic Modelling with Stan, it builds knowledge and skills gradually. This book: Focuses on providing practical guidance for all aspects, helping readers get to grips with the tools, software, and statistical methods needed to provide the right type and level of analysis their data requires Explores the foundations of data science and breaks down the processes involved, focusing on the link between data science and practical social science skills Introduces R at the outset and includes extensive worked examples and R code every step of the way, ensuring students see the value of R and its connection to methods while providing hands-on practice in the software Provides examples and datasets from different disciplines and locations demonstrate the widespread relevance, possible applications, and impact of data science across the social sciences.
Doing Data Science in R: An Introduction for Social Scientists
by Mark AndrewsThis approachable introduction to doing data science in R provides step-by-step advice on using the tools and statistical methods to carry out data analysis. Introducing the fundamentals of data science and R before moving into more advanced topics like Multilevel Models and Probabilistic Modelling with Stan, it builds knowledge and skills gradually. This book: Focuses on providing practical guidance for all aspects, helping readers get to grips with the tools, software, and statistical methods needed to provide the right type and level of analysis their data requires Explores the foundations of data science and breaks down the processes involved, focusing on the link between data science and practical social science skills Introduces R at the outset and includes extensive worked examples and R code every step of the way, ensuring students see the value of R and its connection to methods while providing hands-on practice in the software Provides examples and datasets from different disciplines and locations demonstrate the widespread relevance, possible applications, and impact of data science across the social sciences.
Doing Meta-Analysis with R: A Hands-On Guide
by Mathias Harrer Pim Cuijpers Toshi A. Furukawa David D. EbertDoing Meta-Analysis with R: A Hands-On Guide serves as an accessible introduction on how meta-analyses can be conducted in R. Essential steps for meta-analysis are covered, including calculation and pooling of outcome measures, forest plots, heterogeneity diagnostics, subgroup analyses, meta-regression, methods to control for publication bias, risk of bias assessments and plotting tools. Advanced but highly relevant topics such as network meta-analysis, multi-three-level meta-analyses, Bayesian meta-analysis approaches and SEM meta-analysis are also covered. A companion R package, dmetar, is introduced at the beginning of the guide. It contains data sets and several helper functions for the meta and metafor package used in the guide. The programming and statistical background covered in the book are kept at a non-expert level, making the book widely accessible. Features• Contains two introductory chapters on how to set up an R environment and do basic imports/manipulations of meta-analysis data, including exercises• Describes statistical concepts clearly and concisely before applying them in R• Includes step-by-step guidance through the coding required to perform meta-analyses, and a companion R package for the book
Doing Meta-Analysis with R: A Hands-On Guide
by Mathias Harrer Pim Cuijpers Toshi A. Furukawa David D. EbertDoing Meta-Analysis with R: A Hands-On Guide serves as an accessible introduction on how meta-analyses can be conducted in R. Essential steps for meta-analysis are covered, including calculation and pooling of outcome measures, forest plots, heterogeneity diagnostics, subgroup analyses, meta-regression, methods to control for publication bias, risk of bias assessments and plotting tools. Advanced but highly relevant topics such as network meta-analysis, multi-three-level meta-analyses, Bayesian meta-analysis approaches and SEM meta-analysis are also covered. A companion R package, dmetar, is introduced at the beginning of the guide. It contains data sets and several helper functions for the meta and metafor package used in the guide. The programming and statistical background covered in the book are kept at a non-expert level, making the book widely accessible. Features• Contains two introductory chapters on how to set up an R environment and do basic imports/manipulations of meta-analysis data, including exercises• Describes statistical concepts clearly and concisely before applying them in R• Includes step-by-step guidance through the coding required to perform meta-analyses, and a companion R package for the book
Doing Physics with Scientific Notebook: A Problem Solving Approach
by Joseph GallantThe goal of this book is to teach undergraduate students how to use Scientific Notebook (SNB) to solve physics problems. SNB software combines word processing and mathematics in standard notation with the power of symbolic computation. As its name implies, SNB can be used as a notebook in which students set up a math or science problem, write and solve equations, and analyze and discuss their results. Written by a physics teacher with over 20 years experience, this text includes topics that have educational value, fit within the typical physics curriculum, and show the benefits of using SNB. This easy-to-read text: Provides step-by-step instructions for using Scientific Notebook (SNB) to solve physics problems Features examples in almost every section to enhance the reader's understanding of the relevant physics and to provide detailed instructions on using SNB Follows the traditional physics curriculum, so it can be used to supplement teaching at all levels of undergraduate physics Includes many problems taken from the author’s class notes and research Aimed at undergraduate physics and engineering students, this text teaches readers how to use SNB to solve some everyday physics problems.
Doing Physics with Scientific Notebook: A Problem Solving Approach
by Joseph GallantThe goal of this book is to teach undergraduate students how to use Scientific Notebook (SNB) to solve physics problems. SNB software combines word processing and mathematics in standard notation with the power of symbolic computation. As its name implies, SNB can be used as a notebook in which students set up a math or science problem, write and solve equations, and analyze and discuss their results. Written by a physics teacher with over 20 years experience, this text includes topics that have educational value, fit within the typical physics curriculum, and show the benefits of using SNB. This easy-to-read text: Provides step-by-step instructions for using Scientific Notebook (SNB) to solve physics problems Features examples in almost every section to enhance the reader's understanding of the relevant physics and to provide detailed instructions on using SNB Follows the traditional physics curriculum, so it can be used to supplement teaching at all levels of undergraduate physics Includes many problems taken from the author’s class notes and research Aimed at undergraduate physics and engineering students, this text teaches readers how to use SNB to solve some everyday physics problems.
Doing Qualitative Research (PDF)
by David SilvermanWritten in a lively, accessible style, Doing Qualitative Research, 3rd Edition, provides a step-by-step guide to all the questions students ask when beginning their first research project. Silverman demonstrates how to learn the craft of qualitative research by applying knowledge about different methods to actual data. He provides practical advice on key issues such as: defining 'originality' and narrowing down a topic; keeping a research diary and writing a research report;and presenting research to different audiences. Doing Qualitative Research, 3rd Edition, is substantially updated and revised. Among its new, attractive features are: problem-based format, making extensive use of statements and queries by recent research students two new chapters on data-gathering and ethical issues in student research material relevant for both Masters and PhD students examples from many social science disciplines and from Asia, Africa, the United States and Europe detailed discussion of different analytical models used in research additional material on the treatment of visual data an updated chapter on computer-aided qualitative data analysis boxed tips and links to websites throughout the text an expanded index and glossary a companion website which includes further readings and exercises Each stage in the research process is grounded in worked examples based on the experiences of real students, with exercises designed both to test readers' knowledge and to encourage the development of practical skills.nbsp;
Doing Quantitative Research in Education with IBM SPSS Statistics
by Daniel MuijsThis essential guide for education students and researchers explains how to use quantitative methods for analysing educational data using IBM SPSS Statistics. By using datasets from real-life educational research, it demonstrates key statistical techniques that you will need to know, explaining how each procedure can by run on IBM SPSS Statistics. Datasets discussed in the book are downloadable, allowing you to hone your skills as you read. In this third edition, explanations have been updated with figures and screenshots from SPSS version 28, alongside a range of new research examples and updated further reading. Daniel Muijs is Dean of the Faculty of Education and Society at Academica University of Applied Sciences in Amsterdam.
Doing Quantitative Research in Education with IBM SPSS Statistics
by Daniel MuijsThis essential guide for education students and researchers explains how to use quantitative methods for analysing educational data using IBM SPSS Statistics. By using datasets from real-life educational research, it demonstrates key statistical techniques that you will need to know, explaining how each procedure can by run on IBM SPSS Statistics. Datasets discussed in the book are downloadable, allowing you to hone your skills as you read. In this third edition, explanations have been updated with figures and screenshots from SPSS version 28, alongside a range of new research examples and updated further reading. Daniel Muijs is Dean of the Faculty of Education and Society at Academica University of Applied Sciences in Amsterdam.