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Puzzle and Proof: A Decade of Problems from the Utah Math Olympiad (AK Peters/CRC Recreational Mathematics Series)
by Samuel Dittmer Hiram Golze Grant Molnar Caleb StanfordPuzzle and Proof: A Decade of Problems from the Utah Math Olympiad is a compilation of the problems and solutions for the first 10 years of the Utah Math Olympiad. The problems are challenging but should be understandable at a high school level. Besides putting all problems in one place (70 in total), which have not previously appeared in print, the book provides additional inspiration for many of the problems and will contain the first published solutions for 10 problems that were originally published on the contest flyer. The book will be a fantastic resource for anyone who enjoys mathematical and/or logic puzzles or is interested in studying for mathematics competitions.Features 70 carefully designed, high-quality high-school level math proof problems, with full solutions Detailed pictures and diagrams throughout to aid understanding Suitable for anyone with high school-level mathematics skills with an interest in furthering their understanding, or just enjoying the puzzles Solutions in the back of the book, sorting the problems by difficulty and topic.
Uncertainty Quantification with R: Bayesian Methods (International Series in Operations Research & Management Science #352)
by Eduardo Souza de CursiThis book is a rigorous but practical presentation of the Bayesian techniques of uncertainty quantification, with applications in R. This volume includes mathematical arguments at the level necessary to make the presentation rigorous and the assumptions clearly established, while maintaining a focus on practical applications of Bayesian uncertainty quantification methods. Practical aspects of applied probability are also discussed, making the content accessible to students. The introduction of R allows the reader to solve more complex problems involving a more significant number of variables. Users will be able to use examples laid out in the text to solve medium-sized problems.The list of topics covered in this volume includes basic Bayesian probabilities, entropy, Bayesian estimation and decision, sequential Bayesian estimation, and numerical methods. Blending theoretical rigor and practical applications, this volume will be of interest to professionals, researchers, graduate and undergraduate students interested in the use of Bayesian uncertainty quantification techniques within the framework of operations research and mathematical programming, for applications in management and planning.
An Invitation to Mathematical Logic (Graduate Texts in Mathematics #301)
by David MarkerIn addition to covering the essentials, the author’s intention in writing this text is to entice the reader to further study mathematical logic. There is no current “standard text” for a first graduate course in mathematical logic and this book will fill that gap. While there is more material than could be covered in a traditional one semester course, an instructor can cover the basics and still have the flexibility to choose several weeks’ worth of interesting advanced topics that have been introduced. The text can and will be used by people in various courses with different sorts of perspectives. This versatility is one of the many appealing aspects of this book. A list of suggested portions to be covered in a single course is provided as well as a useful chart which maps chapter dependencies. Additionally, a motivated student will have ample material for further reading. New definitions, formalism, and syntax have been streamlined to engage thereader quickly into the heart of logic and to more sophisticated topics. Part I and Part IV center on foundational questions, while Part III establishes the fundamentals of computability. Part II develops model theory, highlighting the model theory of the fields of real and complex numbers. The interplay between logic and other areas of mathematics, notably algebra, number theory, and combinatorics, are illustrated in Chapters 5, 6, 8, 14, and 16. For most of the text, the only prerequisite is mathematical maturity. The material should be accessible to first year graduate students or advanced undergraduates in mathematics, graduate students in philosophy with a solid math background, or students in computer science who want a mathematical introduction to logic. Prior exposure to logic is helpful but not assumed.
Scientific Method: How Science Works, Fails to Work, and Pretends to Work
by John StaddonThis expanded second edition of Scientific Method shows how science works, fails to work or pretends to work by looking at examples from physics, biomedicine, psychology, sociology and economics.Scientific Method aims to help curious readers understand the idea of science, not by learning a list of techniques but through examples both historical and contemporary. Staddon affirms that if the reader can understand successful studies as well as studies that appear to be scientific but are not, they will become a better judge of the “science” in circulation today. To this end, this new edition includes a new chapter, What is Science?, which points out that science, like any human activity, has its own set of values, with truth being the core. Other new chapters focus on the emergence of AI and machine learning, science and diversity, and behavioral economics. The book also includes textual features such as bullet-points and text boxes on topical issues.Scientific Method is essential reading for students and professionals trying to make sense of the role of science in society, and of the meaning, value and limitations of scientific methodology.
Scientific Method: How Science Works, Fails to Work, and Pretends to Work
by John StaddonThis expanded second edition of Scientific Method shows how science works, fails to work or pretends to work by looking at examples from physics, biomedicine, psychology, sociology and economics.Scientific Method aims to help curious readers understand the idea of science, not by learning a list of techniques but through examples both historical and contemporary. Staddon affirms that if the reader can understand successful studies as well as studies that appear to be scientific but are not, they will become a better judge of the “science” in circulation today. To this end, this new edition includes a new chapter, What is Science?, which points out that science, like any human activity, has its own set of values, with truth being the core. Other new chapters focus on the emergence of AI and machine learning, science and diversity, and behavioral economics. The book also includes textual features such as bullet-points and text boxes on topical issues.Scientific Method is essential reading for students and professionals trying to make sense of the role of science in society, and of the meaning, value and limitations of scientific methodology.
Linear Partial Differential and Difference Equations and Simultaneous Systems with Constant or Homogeneous Coefficients (Mathematics and Physics for Science and Technology)
by Luis Manuel Braga da Costa Campos Luís António Raio VilelaLinear Partial Differential and Difference Equations and Simultaneous Systems: With Constant or Homogeneous Coefficients is part of the series "Mathematics and Physics for Science and Technology," which combines rigorous mathematics with general physical principles to model practical engineering systems with a detailed derivation and interpretation of results. Volume V presents the mathematical theory of partial differential equations and methods of solution satisfying initial and boundary conditions, and includes applications to: acoustic, elastic, water, electromagnetic and other waves; the diffusion of heat, mass, and electricity; and their interactions. This is the third book of the volume.The book starts with six different methods of solution of linear partial differential equations (p.d.e.) with constant coefficients. One of the methods, namely characteristic polynomial, is then extended to a further five classes, including linear p.d.e. with homogeneous power coefficients and finite difference equations and simultaneous systems of both (simultaneous partial differential equations [s.p.d.e.] and simultaneous finite difference equations [s.f.d.e.]). The applications include detailed solutions of the most important p.d.e. in physics and engineering, including the Laplace, heat, diffusion, telegraph, bar, and beam equations. The free and forced solutions are considered together with boundary, initial, asymptotic, starting, and other conditions.The book is intended for graduate students and engineers working with mathematical models and can be applied to problems in mechanical, aerospace, electrical, and other branches of engineering dealing with advanced technology, and also in the physical sciences and applied mathematics.
Linear Partial Differential and Difference Equations and Simultaneous Systems with Constant or Homogeneous Coefficients (Mathematics and Physics for Science and Technology)
by Luis Manuel Braga da Costa Campos Luís António Raio VilelaLinear Partial Differential and Difference Equations and Simultaneous Systems: With Constant or Homogeneous Coefficients is part of the series "Mathematics and Physics for Science and Technology," which combines rigorous mathematics with general physical principles to model practical engineering systems with a detailed derivation and interpretation of results. Volume V presents the mathematical theory of partial differential equations and methods of solution satisfying initial and boundary conditions, and includes applications to: acoustic, elastic, water, electromagnetic and other waves; the diffusion of heat, mass, and electricity; and their interactions. This is the third book of the volume.The book starts with six different methods of solution of linear partial differential equations (p.d.e.) with constant coefficients. One of the methods, namely characteristic polynomial, is then extended to a further five classes, including linear p.d.e. with homogeneous power coefficients and finite difference equations and simultaneous systems of both (simultaneous partial differential equations [s.p.d.e.] and simultaneous finite difference equations [s.f.d.e.]). The applications include detailed solutions of the most important p.d.e. in physics and engineering, including the Laplace, heat, diffusion, telegraph, bar, and beam equations. The free and forced solutions are considered together with boundary, initial, asymptotic, starting, and other conditions.The book is intended for graduate students and engineers working with mathematical models and can be applied to problems in mechanical, aerospace, electrical, and other branches of engineering dealing with advanced technology, and also in the physical sciences and applied mathematics.
Dynamical Behaviors of Fractional-Order Complex Dynamical Networks
by Jin-Liang WangThis book benefits researchers, engineers, and graduate students in the field of fractional-order complex dynamical networks. Recently, the dynamical behaviors (e.g., passivity, finite-time passivity, synchronization, and finite-time synchronization, etc.) for fractional-order complex networks (FOCNs) have attracted considerable research attention in a wide range of fields, and a variety of valuable results have been reported. In particular, passivity has been extensively used to address the synchronization of FOCNs.
Biostatistics For Dummies
by Monika Wahi John C. PezzulloBreak down biostatistics, make sense of complex concepts, and pass your class If you're taking biostatistics, you may need or want a little extra assistance as you make your way through. Biostatistics For Dummies follows a typical biostatistics course at the college level, helping you understand even the most difficult concepts, so you can get the grade you need. Start at the beginning by learning how to read and understand mathematical equations and conduct clinical research. Then, use your knowledge to analyze and graph your data. This new edition includes more example problems with step-by-step walkthroughs on how to use statistical software to analyze large datasets. Biostatistics For Dummies is your go-to guide for making sense of it all. Review basic statistics and decode mathematical equations Learn how to analyze and graph data from clinical research studies Look for relationships with correlation and regression Use software to properly analyze large datasets Anyone studying in clinical science, public health, pharmaceutical sciences, chemistry, and epidemiology-related fields will want this book to get through that biostatistics course.
Proceedings of the 2024 5th International Conference on Big Data and Informatization Education (Advances in Intelligent Systems Research #182)
This is an open access book. Big data is a large-scale and complex data set based on modern information technology. It has the characteristics of scale and diversity, and its information processing and storage capabilities have been significantly improved. The application of big data technology is to fully mine and analyze data, build cooperation and interaction between teachers and students, encourage students to communicate and interact with teachers, and give full play to the education and teaching effect of big data. In order to improve teaching quality and efficiency as much as possible, all kinds of teaching in the new era must have strong flexibility and foresight, so as to adapt to the development of modern society. So big data will give greater flexibility to educational activities. Therefore, big data will give greater flexibility to educational activities, and more and more scholars provide new ideas for the above research directions. To sum up, we will hold an international academic conference on big data and information education. The 2024 5th International Conference on Big Data and Informatization Education (ICBDIE2024) will be held on January 19–21, 2024 in Sanya, China. ICBDIE 2024 is to bring together innovative academics and industrial experts in the field of Big Data and Informatization Education to a common forum. The primary goal of the conference is to promote research and developmental activities in Big Data and Informatization Education and another goal is to promote scientific information interchange between researchers, developers, engineers, students, and practitioners working all around the world. The conference will be held every year to make it an ideal platform for people to share views and experiences in international conference on Big Data and Informatization Education and related areas.
Sustained Simulation Performance 2022: Proceedings of the Joint Workshop on Sustained Simulation Performance, High-Performance Computing Center Stuttgart (HLRS), University of Stuttgart and Tohoku University, May and October 2022
by Michael M. Resch Wolfgang Bez Hiroaki Kobayashi Hiroyuki Takizawa Johannes GebertThis book presents the state of the art in High-Performance Computing on modern supercomputer architectures. It addresses trends in hardware and software development in general. The contributions cover a broad range of topics, from performance evaluations in context with power efficiency to Computational Fluid Dynamics and High-Performance Data Analytics. In addition, they explore new topics like the use of High-Performance Computers in the field of Artificial Intelligence and Machine Learning. All contributions are based on selected papers presented in 2022 at the 33rd Workshop on Sustained Simulation Performance, WSSP33, held at HLRS in Stuttgart, Germany, and WSSP34, held at Tohoku University in Sendai, Japan.
STEM Education by Design: Opening Horizons of Possibility
by Sharon Friesen Brent Davis Krista FrancisAn accessible text that assumes no prior knowledge, this book is grounded in the realization that "STEM" and "STEM Education" have not yet evolved into fully coherent fields of study, and fills this gap by offering an original model and strategy for developing coherences in a way that both honors the integrity of each of STEM’s constituent disciplines and explores the ways they can amplify one another when used together to address complex contemporary issues. This book demonstrates how STEM can and should be understood as more than a collection of disciplines; it is a transdisciplinary, possibility-rich domain that is much more than the sum of its parts. Building on the actual work of scientists, engineers, and other professionals, the authors disrupt preconceptions about STEM domains, and provide the tools and evidence-based approaches to create new possibilities for all learners. Covering historical influences, theoretical frameworks, and current debates and challenges, this book positions teachers and students as agents of change. Each chapter features In Brief openers to introduce the topic; Opening Anecdotes to reflect the chapter’s key themes; Sidebars to put core principles in context; Consolidating Key Points activities to summarize and highlight important details; and Challenges to build upon and extend topics explored in the chapter from different angles.
Web and Big Data. APWeb-WAIM 2023 International Workshops: KGMA 2023 and SemiBDMA 2023, Wuhan, China, October 6–8, 2023, Proceedings (Communications in Computer and Information Science #2094)
by Jianxin Li Geyong Min Xiangyu Song Ruyi Feng Yunliang ChenThis proceedings constitutes selected papers from the Workshops KGMA and SemiBDMA which were held in conjunction with APWeb-WAIM 2023 which took place in Wuhan, China, during October 6-8, 2023. The 7 full papers included in this book were carefully reviewed and selected from 15 papers submitted to these workshops. They focus on new research approaches on the theory, design, and implementation of data management systems.
Cracking the Machine Learning Code: Technicality or Innovation? (Studies in Computational Intelligence #1155)
by KC Santosh Rodrigue Rizk Siddhi K. BajracharyaEmploying off-the-shelf machine learning models is not an innovation. The journey through technicalities and innovation in the machine learning field is ongoing, and we hope this book serves as a compass, guiding the readers through the evolving landscape of artificial intelligence. It typically includes model selection, parameter tuning and optimization, use of pre-trained models and transfer learning, right use of limited data, model interpretability and explainability, feature engineering and autoML robustness and security, and computational cost – efficiency and scalability. Innovation in building machine learning models involves a continuous cycle of exploration, experimentation, and improvement, with a focus on pushing the boundaries of what is achievable while considering ethical implications and real-world applicability. The book is aimed at providing a clear guidance that one should not be limited to building pre-trained models to solve problems using the off-the-self basic building blocks. With primarily three different data types: numerical, textual, and image data, we offer practical applications such as predictive analysis for finance and housing, text mining from media/news, and abnormality screening for medical imaging informatics. To facilitate comprehension and reproducibility, authors offer GitHub source code encompassing fundamental components and advanced machine learning tools.
Generalized Linear Mixed Models: Modern Concepts, Methods and Applications (Chapman & Hall/CRC Texts in Statistical Science)
by Walter W. StroupWith numerous examples using SAS PROC GLIMMIX, this text presents an introduction to linear modeling using the generalized linear mixed model as an overarching conceptual framework. For readers new to linear models, the book helps them see the big picture. It shows how linear models fit with the rest of the core statistics curriculum and points out the major issues that statistical modelers must consider.
Event Mining: Algorithms and Applications (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series)
by Tao LiWith a focus on computing system management, this book presents a variety of event mining approaches for improving the quality and efficiency of IT service and system management. It covers different components in the data-driven framework, from system monitoring and event generation to pattern discovery and summarization. The book explores recent developments in event mining, such as new clustering-based approaches, as well as various applications of event mining, including social media.
Evolutionary Economics (Springer Texts in Business and Economics)
by Yuji ArukaThis textbook presents a new way to visualize or imagine the evolutionary architecture of economics, to judge both its practical outcomes and its ultimate value. Evolutionary economics employs an Aristotelian architecture. The cognitive value of this imagination[H1] must be directly relevant to the evolutionary theory and practice of designing the architecture of the economic system. Mainstream economics completely ignores design value in order to concentrate on the ideal, Platonic vision of the economy. The current system is no longer one that converges on a constant entity, because the system is constantly evolving. The advent of the digital economy is an indispensable next step, and computational power and algorithmic rationality are increasingly dominating the economic system—and complicating it. In today’s society, neither fault nor malice matters in the algorithmic or human system. There is little room left for the effective working of human reason. Correspondingly, the meanings of money, exchange, the market system, auctions, production, consumption, and the currency transaction system are poised to change. In most cases, there will be digital counterparts. A smart contract tied together with DLT, for example, makes it possible to design an economically well-behaved peer-to-peer (P2P) system, which ranges from the micromarket to the international currency transaction system. The introduction of this technology and its architectural design may suggest what a truly decentralized future entails. This change may also bring about a new understanding of existing social consensus and practice. Thus, the implementation of these considerations naturally leads to a new style of chapter structuring in this book, from the classical analytical approach to exploring computational methods and digital tools: in many cases, the problems presented in each chapter are combined with discussions of a respective computational method and its practical value.
Validity, Reliability, and Significance: Empirical Methods for NLP and Data Science (Synthesis Lectures on Human Language Technologies)
by Stefan Riezler Michael HagmannThis book introduces empirical methods for machine learning with a special focus on applications in natural language processing (NLP) and data science. The authors present problems of validity, reliability, and significance and provide common solutions based on statistical methodology to solve them. The book focuses on model-based empirical methods where data annotations and model predictions are treated as training data for interpretable probabilistic models from the well-understood families of generalized additive models (GAMs) and linear mixed effects models (LMEMs). Based on the interpretable parameters of the trained GAMs or LMEMs, the book presents model-based statistical tests such as a validity test that allows for the detection of circular features that circumvent learning. Furthermore, the book discusses a reliability coefficient using variance decomposition based on random effect parameters of LMEMs. Lastly, a significance test based on the likelihood ratios of nested LMEMs trained on the performance scores of two machine learning models is shown to naturally allow the inclusion of variations in meta-parameter settings into hypothesis testing, and further facilitates a refined system comparison conditional on properties of input data. The book is self-contained with an appendix on the mathematical background of generalized additive models and linear mixed effects models as well as an accompanying webpage with the related R and Python code to replicate the presented experiments. The second edition also features a new hands-on chapter that illustrates how to use the included tools in practical applications.
Exercises in Applied Mathematics: With a View toward Information Theory, Machine Learning, Wavelets, and Statistical Physics (Chapman Mathematical Notes)
by Daniel AlpayThis text presents a collection of mathematical exercises with the aim of guiding readers to study topics in statistical physics, equilibrium thermodynamics, information theory, and their various connections. It explores essential tools from linear algebra, elementary functional analysis, and probability theory in detail and demonstrates their applications in topics such as entropy, machine learning, error-correcting codes, and quantum channels. The theory of communication and signal theory are also in the background, and many exercises have been chosen from the theory of wavelets and machine learning. Exercises are selected from a number of different domains, both theoretical and more applied. Notes and other remarks provide motivation for the exercises, and hints and full solutions are given for many. For senior undergraduate and beginning graduate students majoring in mathematics, physics, or engineering, this text will serve as a valuable guide as theymove on to more advanced work.
Communication and Intelligent Systems: Proceedings of ICCIS 2023, Volume 2 (Lecture Notes in Networks and Systems #968)
by Lipo Wang Harish Sharma Vivek Shrivastava Ashish Kumar TripathiThis book gathers selected research papers presented at the Fifth International Conference on Communication and Intelligent Systems (ICCIS 2023), organized by Malaviya National Institute of Technology Jaipur, India, during December 16–17, 2023. This book presents a collection of state-of-the-art research work involving cutting-edge technologies for communication and intelligent systems. Over the past few years, advances in artificial intelligence and machine learning have sparked new research efforts around the globe, which explore novel ways of developing intelligent systems and smart communication technologies. The book presents single- and multi-disciplinary research on these themes to make the latest results available in a single, readily accessible source. The work is presented in three volumes.
Family Ties and Psychosocial Processes in an Ageing Society: Comparative Perspectives (International Perspectives on Aging #42)
by Alejandro KleinThis book contributes to the discussion on the ageing society by addressing the new psycho-social structures of the ageing society, the problems around family bonds and ties, and the structures of care and protection. The book sheds light on the new roles of grandparents and new grandparents, and the empowerment and resilience initiatives, thereby providing a broad discussion of what the ageing society implies in psychosocial terms. These issues are addressed in an interdisciplinary way, but also in an approach that is also rare, comparing different realities between Europe and Latin America. The [basis of the] English translation of this book from its Spanish original manuscript was done with the help of artificial intelligence. A subsequent human revision of the content was done by the author.
A Simple Introduction to Python (Chapman & Hall/CRC The Python Series)
by Stephen LynchA Simple Introduction to Python is aimed at pre-university students and complete novices to programming. The whole book has been created using Jupyter notebooks. After introducing Python as a powerful calculator, simple programming constructs are covered, and the NumPy, MatPlotLib and SymPy modules (libraries) are introduced. Python is then used for Mathematics, Cryptography, Artificial Intelligence, Data Science and Object Oriented Programming.The reader is shown how to program using the integrated development environments: Python IDLE, Spyder, Jupyter notebooks, and through cloud computing with Google Colab.Features: No prior experience in programming is required. Demonstrates how to format Jupyter notebooks for publication on the Web. Full solutions to exercises are available as a Jupyter notebook on the Web. All Jupyter notebook solution files can be downloaded through GitHub. GitHub Repository of Data Files and a Jupyter Solution notebook: https://github.com/proflynch/A-Simple-Introduction-to-PythonJupyter Solution notebook web page: https://drstephenlynch.github.io/webpages/A-Simple-Introduction-to-Python-Solutions.html
A Simple Introduction to Python (Chapman & Hall/CRC The Python Series)
by Stephen LynchA Simple Introduction to Python is aimed at pre-university students and complete novices to programming. The whole book has been created using Jupyter notebooks. After introducing Python as a powerful calculator, simple programming constructs are covered, and the NumPy, MatPlotLib and SymPy modules (libraries) are introduced. Python is then used for Mathematics, Cryptography, Artificial Intelligence, Data Science and Object Oriented Programming.The reader is shown how to program using the integrated development environments: Python IDLE, Spyder, Jupyter notebooks, and through cloud computing with Google Colab.Features: No prior experience in programming is required. Demonstrates how to format Jupyter notebooks for publication on the Web. Full solutions to exercises are available as a Jupyter notebook on the Web. All Jupyter notebook solution files can be downloaded through GitHub. GitHub Repository of Data Files and a Jupyter Solution notebook: https://github.com/proflynch/A-Simple-Introduction-to-PythonJupyter Solution notebook web page: https://drstephenlynch.github.io/webpages/A-Simple-Introduction-to-Python-Solutions.html
Model-Based Monitoring and Statistical Control (Chapman & Hall/CRC Interdisciplinary Statistics)
by Kohei OhtsuAvailable in English for the first time, this classic and influential book by the late Kohei Ohtsu presents real examples of ships in motion under irregular ocean waves, how to understand the characteristics of fluctuations of stochastic phenomena through spectral analysis methods and statistical modeling. It also explains how to realize prediction and optimal control based on time series models.In recent years, the need to improve safety and reduce environmental impact in ship operations has been increasing, and the statistical methods presented in this book will be increasingly needed in the future. In addition, the recent development of innovative AI technology and highspeed communications will make it possible to adapt this method not only to ship monitoring and control, but also to any field that involves irregular fluctuations, and it is expected to contribute to solving issues that have been difficult to solve in the past.Part 1 describes classical spectral method for the analysis of stochastic phenomena. In Part 2, this book explains methods to construct time series models using the information criterion, to capture the characteristics of ship and engine motions using the model, to design a model-based monitoring system that informs navigators operating the ship and managers ashore. Furthermore, it explains statistical control method to design an autopilot system and the governor of a marine engine, while showing actual examples. Part 3 presents the basic knowledge necessary for understanding these topics of the book, namely, the basic theory of ship motion, probability and statistics, Kalman filter and statistical optimal control theory.
Model-Based Monitoring and Statistical Control (Chapman & Hall/CRC Interdisciplinary Statistics)
by Kohei OhtsuAvailable in English for the first time, this classic and influential book by the late Kohei Ohtsu presents real examples of ships in motion under irregular ocean waves, how to understand the characteristics of fluctuations of stochastic phenomena through spectral analysis methods and statistical modeling. It also explains how to realize prediction and optimal control based on time series models.In recent years, the need to improve safety and reduce environmental impact in ship operations has been increasing, and the statistical methods presented in this book will be increasingly needed in the future. In addition, the recent development of innovative AI technology and highspeed communications will make it possible to adapt this method not only to ship monitoring and control, but also to any field that involves irregular fluctuations, and it is expected to contribute to solving issues that have been difficult to solve in the past.Part 1 describes classical spectral method for the analysis of stochastic phenomena. In Part 2, this book explains methods to construct time series models using the information criterion, to capture the characteristics of ship and engine motions using the model, to design a model-based monitoring system that informs navigators operating the ship and managers ashore. Furthermore, it explains statistical control method to design an autopilot system and the governor of a marine engine, while showing actual examples. Part 3 presents the basic knowledge necessary for understanding these topics of the book, namely, the basic theory of ship motion, probability and statistics, Kalman filter and statistical optimal control theory.