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Insight Through Computing
This introduction to computer-based problem-solving using the MATLAB environment is highly recommended for students wishing to learn the concepts and develop the programming skills that are fundamental to computational science and engineering (CSE). Through a 'teaching by examples' approach, the authors pose strategically chosen problems to help first-time programmers learn these necessary concepts and skills. Each section formulates a problem and then introduces those new MATLAB language features that are necessary to solve it. This approach puts problem-solving and algorithmic thinking first and syntactical details second. Each solution is followed by a 'talking point' that concerns some related, larger issue associated with CSE. Collectively, the worked examples, talking points, and 300+ homework problems build intuition for the process of discretization and an appreciation for dimension, inexactitude, visualization, randomness, and complexity. This sets the stage for further coursework in CSE areas.
Introduction to Elementary Computational Modeling
With an emphasis on problem solving, this book introduces the basic principles and fundamental concepts of computational modeling. It emphasizes reasoning and conceptualizing problems, the elementary mathematical modeling, and the implementation using computing concepts and principles. Examples are included that demonstrate the computation and visu
Introduction to Computational Models with Python
Introduction to Computational Models with Python explains how to implement computational models using the flexible and easy-to-use Python programming language. The book uses the Python programming language interpreter and several packages from the huge Python Library that improve the performance of numerical computing, such as the Numpy and Scipy m
Introduction to Computational Modeling Using C and Open-Source Tools
Introduction to Computational Modeling Using C and Open-Source Tools presents the fundamental principles of computational models from a computer science perspective. It explains how to implement these models using the C programming language. The software tools used in the book include the Gnu Scientific Library (GSL), which is a free software libra
Best! Letters from Asian Americans in the Arts
This collection of seventy-three letters written in 2020 captures an unprecedented moment in politics and society through the experiences of Asian-American artists, curators, educators, art historians, editors, writers, and designers. The form of the letter offers readers intimate insights into the complexities of Asian American experiences, moving beyond the model-minority myth. Chronicling everyday lives, dreams, rage, family histories, and cultural politics, these letters ignite new ways of being, and modes of creating, at a moment of racial reckoning.
Seven Myths About Education
In this controversial new book, Daisy Christodoulou offers a thought-provoking critique of educational orthodoxy. Drawing on her recent experience of teaching in challenging schools, she shows through a wide range of examples and case studies just how much classroom practice contradicts basic scientific principles. She examines seven widely-held beliefs which are holding back pupils and teachers: Facts prevent understanding Teacher-led instruction is passive The 21st century fundamentally changes everything You can always just look it up We should teach transferable skills Projects and activities are the best way to learn Teaching knowledge is indoctrination In each accessible and engaging c...
Memoirs of the Scientific Sections of the Academy of the Socialist Republic of Romania
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Pattern Recognition and Computer Vision
The four-volume set LNCS 11256, 11257, 11258, and 11259 constitutes the refereed proceedings of the First Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2018, held in Guangzhou, China, in November 2018. The 179 revised full papers presented were carefully reviewed and selected from 399 submissions. The papers have been organized in the following topical sections: Part I: Biometrics, Computer Vision Application. Part II: Deep Learning. Part III: Document Analysis, Face Recognition and Analysis, Feature Extraction and Selection, Machine Learning. Part IV: Object Detection and Tracking, Performance Evaluation and Database, Remote Sensing.
