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ikelle l introduction multidisciplinary science ai 2024

Type:: E-books
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Uploaded On:: May 19, 2024, 4:38 p.m.
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Textbook in PDF format The book is about multidisciplinary science education. The challenges of our time, such as improving the length and quality of lives on Earth and short- and long-distance communication and transportation. In this book, we provide readers with the multidisciplinary education necessary to meet the scientific and technological challenges of our time while optimizing the college experience for students. The fundamental notions addressed in this book include gravitational forces and energy; dark matter and dark energy; heat transfer in solid Earth, stars’ interiors, and human bodies; electromagnetic radiation and spectroscopy; quantum entanglement and computing; accretion disks; matter in plasma state; and exoplanets. We illustrate the importance of these notions with applications across disciplines, including monitoring the deformation of the solid Earth’s surface using satellite measurements, unusual gravity anomalies in Antarctica, a view and characterization of the far side of our Moon, Earth’s climate, Titan’s anti-greenhouse effect, long-distance communication between Earth and the planets and exoplanets, etc. Finally, the book contains analytical and computational problems, including MatLAB software developed especially for the classes associated with this book. With the huge progress being made in the ?eld of Arti?cial Intelligence (AI), the new jobs are about innovation. Broadly speaking, AI is a set of techniques that are aimed at approximating some aspects of human or animal cognition by inserting computer software into robots and other related systems. AI systems can nowadays perform many traditionally human tasks with high e?ciency and without errors. Yet they are very far from being able to create. Very soon AI systems will become central to all science disciplines and the central platform of multidisciplinary studies. They are modern versions of computers, which extend beyond programming a set of scienti?c rules for a discipline-speci?c dataset. The AI systems can automatically learn these rules, improve them, and even create new ones. We can easily input di?erent kinds of datasets to them and even introduce the rules for outcomes. So, while specialization and expertise are especially critical in graduate schools and adult life, a broad horizon is critical for expertise and innovation and to command and create AI systems. Moreover, how can one teach AI without having a background in the biology of life, chemistry, and physics? Likewise, how can one teach the biology of life, chemistry, or physics without incorporating AI? One of the major applications of quantum entanglement is in the so-called quantum computing. Quantum computing has two schools of thought. One school aims to address current bottleneck applications in classical physics. These include weather predictions, climate modeling, optimizing radiotherapy treatments, energy exploration, seismic survey optimization, reservoir optimization, and reserve and spot trading optimization. Compared to traditional digital computing, quantum computing dramatically reduces computation time and energy consumption. Key Features • Contains multiple analytic and computational (MatLAB) exercises • Explores applications related to space programs' discoveries • Provides an accessible introduction and response to growing Multidisciplinary Science programs Preface Gravitational Forces and Geodesy Heat Radiation, Conduction, and Convection Electromagnetic Radiation and Spectroscopy A View of our Universe from Quantum Computing Spontaneous Technology Plasma, Magnetohydrodynamics, Accretion, and Exoplanets A Advanced Numerical Modeling B Answers to Some of the Quizzes and Exercises

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Ikelle L. Introduction to Multidisciplinary Science with AI...2024.pdf 52.9 MB

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ikelle l introduction multidisciplinary science ai 2024

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