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Presenting interdisciplinary research at the forefront of present advances in information technologies and their foundations, Scientific Applications of Language Methods is a multi-author volume containing pieces of work (either original research or surveys) exemplifying the application of formal language tools in several fields, including logic and discrete mathematics, natural language processing, artificial intelligence, natural computing and bioinformatics.
Experimental Methods in Language Acquisition Research provides students and researchers interested in language acquisition with comprehensible and practical information on the most frequently used methods in language acquisition research. It includes contributions on first and child/adult second language learners, language-impaired children, and on the acquisition of both spoken and signed language. Part I discusses specific experimental methods, explaining the rationale behind each one, and providing an overview of potential participants, the procedure and data-analysis, as well as advantages and disadvantages and dos and don’ts. Part II focuses on comparisons across groups, addressing the theoretical, applied and methodological issues involved in such comparative work. This book will not only be of use to advanced undergraduate and postgraduate students, but also to any scholars wishing to learn more about a particular research method. It is suitable as a textbook in postgraduate programs in the fields of linguistics, education and psychology.
This book constitutes the refereed proceedings of the 32nd International Conference on Applications and Theory of Petri Nets and Other Models of Concurrency, PETRI NETS 2011, held in Newcastle, UK, in June 2011. The 13 regular papers and 4 tool papers presented were carefully reviewed and selected from 49 submissions. The book also contains 3 full paper length invited talks. All current issues on research and development in the area of Petri nets and related models of concurrent systems are addressed.
Let Python do the heavy lifting for you as you analyze large datasets Python for Data Science For Dummies lets you get your hands dirty with data using one of the top programming languages. This beginner’s guide takes you step by step through getting started, performing data analysis, understanding datasets and example code, working with Google Colab, sampling data, and beyond. Coding your data analysis tasks will make your life easier, make you more in-demand as an employee, and open the door to valuable knowledge and insights. This new edition is updated for the latest version of Python and includes current, relevant data examples. Get a firm background in the basics of Python coding for data analysis Learn about data science careers you can pursue with Python coding skills Integrate data analysis with multimedia and graphics Manage and organize data with cloud-based relational databases Python careers are on the rise. Grab this user-friendly Dummies guide and gain the programming skills you need to become a data pro.
This book constitutes the proceedings of the 25th International Conference on Implementation and Application of Automata, CIAA 2021, held in July 2021. Due to Covid-19 pandemic the conference was held virtually. The 13 regular papers presented in this book were carefully reviewed and selected from 20 submissions. The topics of the papers cover various fields in the application, implementation, and theory of automata and related structures.
This book constitutes the thoroughly refereed papers of the 16th International Conference on Implementation and Application of Automata, CIAA 2011, held in Blois, France, in July 2011. The 20 revised full papers together with 4 short papers were carefully selected from 38 submissions. The papers cover various topics such as applications of automata in computer-aided verification; natural language processing; pattern matching, data storage and retrieval; document engineering and bioinformatics as well as foundational work on automata theory.
Biotechnology has been labelled as one of the key technologies of the last two decades of the 20th Century, offering boundless solutions to problems ranging from food and agricultural production to pharmaceutical and medical applications, as well as environmental and bioremediation problems. Biological processes, however, are complex and the prevailing mechanisms are either unknown or poorly understood. This means that adequate techniques for data acquisition and analysis, leading to appropriate modeling and simulation packages that can be superimposed on the engineering principles, need to be routine tools for future biotechnologists. The present volume presents a masterly summary of the most recent work in the field, covering: instrumentation systems; enzyme technology; environmental biotechnology; food applications; and metabolic engineering.
Describes practical programming approaches for scientific applications on exascale computer systems Presents strategies to make applications performance portable Provides specific solutions employed in current application porting and development Illustrates domain science software development strategies based on projected trends in supercomputing technology and architectures Includes contributions from leading experts involved in the development and porting of scientific codes for current and future high performance computing resources