Products related to Scientific-computing:
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MATLAB and Simulink in Action : Programming, Scientific Computing and Simulation
The textbook is intended for teaching MATLAB language and its applications.The book is composed of three parts: MATLAB programming, scientific computing with MATLAB, and system simulation with Simulink.Since MATLAB is widely used in all fields of science and engineering, a good introduction to the language can not only help students learn how to use it to solve practical problems, but also provide them with the skills to use MATLAB independently in their later courses and research.The three parts of the book are well-balanced and tailored to the needs of engineering students, and the mathematical problems commonly encountered in engineering can be easily solved using MATLAB.This textbook is suitable for undergraduate and graduate students majoring in science and engineering. The study guide of this textbook could be accessed via: http://sn.pub/thGR7v.This website provides links to recorded teaching videos, MATLAB toolbox for the book, interactive slide decks files in Powerpoint documents, and solution manuals by the authors.
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A Gentle Introduction to Scientific Computing
Scientific Computation has established itself as a stand-alone area of knowledge at the borderline between computer science and applied mathematics.Nonetheless, its interdisciplinary character cannot be denied: its methodologies are increasingly used in a wide variety of branches of science and engineering. A Gentle Introduction to Scientific Computing intends to serve a very broad audience of college students across a variety of disciplines.It aims to expose its readers to some of the basic tools and techniques used in computational science, with a view to helping them understand what happens "behind the scenes" when simple tools such as solving equations, plotting and interpolation are used. To make the book as practical as possible, the authors explore their subject both from a theoretical, mathematical perspective and from an implementation-driven, programming perspective. FeaturesMiddle-ground approach between theory and implementation. Suitable reading for a broad range of students in STEM disciplines.Could be used as the primary text for a first course in scientific computing. Introduces mathematics majors, without any prior computer science exposure, to numerical methods. All mathematical knowledge needed beyond Calculus (together with the most widely used Calculus notation and concepts) is introduced in the text to make it self-contained. The erratum document for A Gentle Introduction to Scientific Computing can be accessed here.
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Scientific Computing : For Scientists and Engineers
Scientific Computing for Scientists and Engineers is designed to teach undergraduate students relevant numerical methods and required fundamentals in scientific computing. Most problems in science and engineering require the solution of mathematical problems, most of which can only be done on a computer.Accurately approximating those problems requires solving differential equations and linear systems with millions of unknowns, and smart algorithms can be used on computers to reduce calculation times from years to minutes or even seconds.This book explains: How can we approximate these important mathematical processes?How accurate are our approximations? How efficient are our approximations? Scientific Computing for Scientists and Engineers covers: An introduction to a wide range of numerical methods for linear systems, eigenvalue problems, differential equations, numerical integration, and nonlinear problems; Scientific computing fundamentals like floating point representation of numbers and convergence; Analysis of accuracy and efficiency; Simple programming examples in MATLAB to illustrate the algorithms and to solve real life problems; Exercises to reinforce all topics.
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Python for Scientific Computing and Artificial Intelligence
Python for Scientific Computing and Artificial Intelligence is split into 3 parts: in Section 1, the reader is introduced to the Python programming language and shown how Python can aid in the understanding of advanced High School Mathematics.In Section 2, the reader is shown how Python can be used to solve real-world problems from a broad range of scientific disciplines.Finally, in Section 3, the reader is introduced to neural networks and shown how TensorFlow (written in Python) can be used to solve a large array of problems in Artificial Intelligence (AI). This book was developed from a series of national and international workshops that the author has been delivering for over twenty years.The book is beginner friendly and has a strong practical emphasis on programming and computational modelling. Features:No prior experience of programming is requiredOnline GitHub repository available with codes for readers to practiceCovers applications and examples from biology, chemistry, computer science, data science, electrical and mechanical engineering, economics, mathematics, physics, statistics and binary oscillator computingFull solutions to exercises are available as Jupyter notebooks on the WebSupport MaterialGitHub Repository of Python Files and Notebooks: https://github.com/proflynch/CRC-Press/Solutions to All Exercises:Section 1: An Introduction to Python: https://drstephenlynch.github.io/webpages/Solutions_Section_1.htmlSection 2: Python for Scientific Computing: https://drstephenlynch.github.io/webpages/Solutions_Section_2.htmlSection 3: Artificial Intelligence: https://drstephenlynch.github.io/webpages/Solutions_Section_3.html
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How can I outsource computing power?
You can outsource computing power by utilizing cloud computing services offered by companies such as Amazon Web Services (AWS), Microsoft Azure, or Google Cloud Platform. These services allow you to rent computing resources on a pay-as-you-go basis, giving you access to scalable computing power without the need to invest in expensive hardware. By leveraging these cloud services, you can easily scale your computing resources up or down based on your needs, making it a cost-effective and flexible solution for outsourcing computing power.
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What is a brief definition of computing technology and could you provide an example?
Computing technology refers to the use of computers and software to process, store, and manage information. It involves the use of hardware, software, and networks to perform various tasks such as data analysis, communication, and automation. An example of computing technology is cloud computing, which allows users to access and store data and applications over the internet instead of on their local computer.
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How can the computing power be improved?
Computing power can be improved through advancements in hardware and software technologies. This includes the development of faster and more efficient processors, increased memory and storage capacities, and improved cooling systems to prevent overheating. Additionally, optimizing software algorithms and programming techniques can also enhance computing power by making better use of available resources. Furthermore, advancements in parallel processing and distributed computing can also contribute to improved computing power by allowing tasks to be divided and processed simultaneously across multiple processors or systems.
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What is the difference between web development and software development?
Web development primarily focuses on creating websites and web applications that are accessed through a web browser, using technologies such as HTML, CSS, and JavaScript. Software development, on the other hand, involves creating applications that can run on various platforms, including desktop computers, mobile devices, and servers. While web development is a subset of software development, software development encompasses a broader range of applications beyond just web-based ones.
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Introduction to Bioinformatics and Clinical Scientific Computing
This textbook provides an introduction to computer science theory, informatics best practice, and the standards and legislation that apply to computing in a healthcare environment.It delivers an accessible discussion of databases (construction, interrogation and maintenance); networking (design and low-level application); programming (best practice rather than the specifics of any one language – design, maintenance, safety).It can be used to accompany the NHS Modernising Scientific Careers syllabus.It is also targeted towards those creating software rather than those using it, particularly computer scientists working in healthcare, specifically those in or close to the Physical Sciences, including radiotherapy, nuclear medicine, and equipment management and those working with genomics and health informatics.Features Combines all topics into one comprehensive introduction. Explores practical applications of theory to healthcare. Can be used to accompany the NHS Modernising Scientific Careers syllabus.
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Verification, Validation, and Uncertainty Quantification in Scientific Computing
Can you trust results from modeling and simulation?This text provides a framework for assessing the reliability of and uncertainty included in the results used by decision makers and policy makers in industry and government.The emphasis is on models described by PDEs and their numerical solution.Procedures and results from all aspects of verification and validation are integrated with modern methods in uncertainty quantification and stochastic simulation.Methods for combining numerical approximation errors, uncertainty in model input parameters, and model form uncertainty are presented in order to estimate the uncertain response of a system in the presence of stochastic inputs and lack of knowledge uncertainty.This new edition has been extensively updated, including a fresh look at model accuracy assessment and the responsibilities of management for modeling and simulation activities.Extra homework problems and worked examples have been added to each chapter, suitable for course use or self-study.
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Introduction to Engineering and Scientific Computing with Python
As more and more engineering departments and companies choose to use Python, this book provides an essential introduction to this open-source, free-to-use language.Expressly designed to support first-year engineering students, this book covers engineering and scientific calculations, Python basics, and structured programming. Based on extensive teaching experience, the text uses practical problem solving as a vehicle to teach Python as a programming language.By learning computing fundamentals in an engaging and hands-on manner, it enables the reader to apply engineering and scientific methods with Python, focusing this general language to the needs of engineers and the problems they are required to solve on a daily basis.Rather than inundating students with complex terminology, this book is designed with a leveling approach in mind, enabling students at all levels to gain experience and understanding of Python.It covers such topics as structured programming, graphics, matrix operations, algebraic equations, differential equations, and applied statistics.A comprehensive chapter on working with data brings this book to a close. This book is an essential guide to Python, which will be relevant to all engineers, particularly undergraduate students in their first year.It will also be of interest to professionals and graduate students looking to hone their programming skills, and apply Python to engineering and scientific contexts.
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Principles of Parallel Scientific Computing : A First Guide to Numerical Concepts and Programming Methods
New insight in many scientific and engineering fields is unthinkable without the use of numerical simulations running efficiently on modern computers.The faster we get new results, the bigger and accurate are the problems that we can solve.It is the combination of mathematical ideas plus efficient programming that drives the progress in many disciplines.Future champions in the area thus will have to be qualified in their application domain, they will need a profound understanding of some mathematical ideas, and they need the skills to deliver fast code. The present textbook targets students which have programming skills already and do not shy away from mathematics, though they might be educated in computer science or an application domain.It introduces the basic concepts and ideas behind applied mathematics and parallel programming that we need to write numerical simulations for today’s multicore workstations.Our intention is not to dive into one particular applicationdomain or to introduce a new programming language – we lay the generic foundations for future courses and projects in the area. The text is written in an accessible style which is easy to digest for students without years and years of mathematics education.It values clarity and intuition over formalism, and uses a simple N-body simulation setup to illustrate basic ideas that are of relevance in various different subdomains of scientific computing.Its primary goal is to make theoretical and paradigmatic ideas accessible to undergraduate students and to bring the fascination of the field across.
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How can one earn money with computing power?
One way to earn money with computing power is through cryptocurrency mining. By using your computer's processing power to solve complex mathematical equations, you can earn cryptocurrency as a reward. Another way is by participating in distributed computing projects, where you can lend your computing power to help solve scientific research problems in exchange for payment. Additionally, you can offer your computing skills and services on freelance platforms or by starting your own tech consulting business to earn money.
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What is the computing power of the blender?
The computing power of a blender is not typically measured in the same way as a computer or other electronic device. Instead, the performance of a blender is often evaluated based on its motor power, which is measured in watts. The higher the wattage, the more powerful the blender is likely to be, and the more efficiently it can blend ingredients. Additionally, some blenders may also have advanced features such as variable speed settings and preset programs that can affect their overall performance.
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What training opportunities are available for IT specialists to specialize in web development and general programming, such as software development?
There are various training opportunities available for IT specialists looking to specialize in web development and general programming. Online platforms like Coursera, Udemy, and Codecademy offer courses and certifications in programming languages such as Python, Java, and JavaScript. Additionally, coding bootcamps like General Assembly and Flatiron School provide intensive, hands-on training in software development. IT specialists can also pursue advanced degrees in computer science or related fields to deepen their knowledge and skills in web development and programming.
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What training options are available for IT specialists to specialize in web development and general programming, such as software development?
IT specialists looking to specialize in web development and general programming have a variety of training options available to them. They can pursue formal education through degree programs in computer science or related fields, attend coding bootcamps that offer intensive training in programming languages and frameworks, or take online courses and tutorials to learn specific skills. Additionally, IT specialists can participate in workshops, seminars, and conferences to stay updated on the latest trends and technologies in web development and software development. Continuous learning and practice are essential for IT specialists to excel in these specialized areas.
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