Awarded one of BookAuthority's best new Particle Physics books in 2019! Hands-On Accelerator Physics Using MATLAB® provides an introduction into the design and operational issues of a wide range of particle accelerators, from ion-implanters to the Large Hadron Collider at CERN. Many aspects from the design of beam optical systems and magnets, to the subsystems for acceleration, beam diagnostics, and vacuum are covered. Beam dynamics topics ranging from the beam-beam interaction to free-electron lasers are discussed. Theoretical concepts and the design of key components are explained with the help of MATLAB® code. Practical topics, such as beam size measurements, magnet construction and measurements, and radio-frequency measurements are explored in student labs without requiring access to an accelerator. This unique approach provides a look at what goes on 'under the hood' inside modern accelerators and presents readers with the tools to perform their independent investigations on the computer or in student labs. This book will be of interest to graduate students, postgraduate researchers studying accelerator physics, as well as engineers entering the field. Features: Provides insights into both synchrotron light sources and colliders Discusses technical subsystems, including magnets, radio-frequency engineering, instrumentation and diagnostics, correction of imperfections, control, and cryogenics Accompanied by MATLAB® code, including a 3D-modeler to visualize the accelerators, and additional appendices which are available on the CRC Press website

Predictive Analytics using MATLAB(R) for Biomedical Applications is a comprehensive and practical guide for biomedical engineers, data scientists, and researchers on how to use predictive analytics techniques in MATLAB(R) for solving real-world biomedical problems. The book offers a technical overview of various predictive analytics methods and covers the utilization of MATLAB(R) for implementing these techniques. It includes several case studies that demonstrate how predictive analytics can be applied to real-world biomedical problems, such as predicting disease progression, analyzing medical imaging data, and optimizing treatment outcomes.With a plethora of examples and exercises, this book is the ultimate tool for reinforcing one's knowledge and skills. - Covers various predictive analytics methods, including regression analysis, time series analysis, and machine learning algorithms, providing readers with a comprehensive understanding of the field - Provides a hands-on approach to learning predictive analytics, with a focus on practical applications in biomedical engineering - Includes several case studies that demonstrate the practical application of predictive analytics in real-world biomedical problems, such as disease progression prediction, medical imaging analysis, and treatment optimization

This book puts numerical methods in action for the purpose of solving practical problems in quantitative finance. The first part develops a toolkit in numerical methods for finance. The second part proposes twenty self-contained cases covering model simulation, asset pricing and hedging, risk management, statistical estimation and model calibration. Each case develops a detailed solution to a concrete problem arising in applied financial management and guides the user towards a computer implementation. The appendices contain "crash courses" in VBA and Matlab programming languages.

This book and MATLAB® app package will accurately convert values from one unit of measure to another using standard conversion factors. It performs conversions from and to the inch-pound system units used in the USA and the International System of Units (SI) as documented in the National Institute of Standards and Technology (NIST) publications of conversions for general use. There are 1,316 conversion factors available for bidirectional conversion from / to SI units, organized into 44 minor subsections by topic under eight major topical sections. There is also an alphabetical section comprising 445 conversion factors for unidirectional conversion to SI units. It also converts CGS and other “unacceptable” units (conversion factors not for general use, i.e. as in science, engineering, etc.). The application performs all three steps in the conversion process: application of the relevant conversion factor, selection of significant digits, and rounding of the result. Conversion factors designated as “exact” are definitions, or they have been set by agreements that define the factor value precisely. All other conversion factors, designated as “derived,” result from truncation of decimal places and/or calculation by a combination of other factors. The unit converter will run on any MacOS or Windows platform that has MATLAB R2018A or R2018B installed. FEATURES: • Performs all three steps in the conversion process: application of the relevant conversion factor, selection of significant digits, and rounding of the result. • Converts values from one unit of measure to another using standard conversion factors. It performs conversions from and to the inch-pound system units used in the USA and also the International System of Units (SI). The companion files include: --The MATLAB conversion app. The unit converter will run on any MacOS or Windows platform that has MATLAB R2018A or R2018B installed. (Files are also available by writing to the publisher at info @ merclearning.com.)

The thesis analyzes the effect that the sample size, the asymmetry in the distribution of returns and the leverage in their volatility have on the estimation and forecasting of market risk in financial assets. The goal is to compare the performance of a variety of models for the estimation and forecasting of Value at Risk (VaR) and Expected Shortfall (ES) for a set of assets of different nature: market indexes, individual stocks, bonds, exchange rates, and commodities. The three chapters of the thesis address issues of greatest interest for the measurement of risk in financial institutions and, therefore, for the supervision of risks in the financial system. They deal with technical issues related to the implementation of the Basel Committee's guidelines on some aspects of which very little is known in the academic world and in the specialized financial sector. In the first chapter, a numerical correction is proposed on the values usually estimatedwhen there is little statistical information, either because it is a financial asset (bond, investment fund...) recently created or issued, or because the nature or the structure of the asset or portfolio have recently changed. The second chapter analyzes the relevance of different aspects of risk modeling. The third and last chapter provides a characterization of the preferable methodology to comply with Basel requirements related to the backtesting of the Expected Shortfall.

Practical Biomedical Signal Analysis Using MATLAB® presents a coherent treatment of various signal processing methods and applications. The book not only covers the current techniques of biomedical signal processing, but it also offers guidance on which methods are appropriate for a given task and different types of data. The first several chapters of the text describe signal analysis techniques—including the newest and most advanced methods—in an easy and accessible way. MATLAB routines are listed when available and freely available software is discussed where appropriate. The final chapter explores the application of the methods to a broad range of biomedical signals, highlighting problems encountered in practice. A unified overview of the field, this book explains how to properly use signal processing techniques for biomedical applications and avoid misinterpretations and pitfalls. It helps readers to choose the appropriate method as well as design their own methods.

ITiB’2016 is the 5th Conference on Information Technologies in Biomedicine organized by the Department of Informatics & Medical Equipment of Silesian University of Technology every other year. The Conference is under the auspices of the Committee on Biocybernetics and Biomedical Engineering of the Polish Academy of Sciences. The meeting has become a recognized event that helps to bridge the gap between methodological achievements in engineering and clinical requirements in medical diagnosis, therapy, and rehabilitation. Mathematical information analysis, computer applications together with medical equipment and instruments have become standard tools underpinning the current rapid progress with developing Computational Intelligence. Members of academic societies of technical and medical background present their research results and clinical implementations. This proceedings (divided in 2 volumes) include the following sections: ؠ Image Processing ؠ Signal Processing ؠ Medical Information System & Database ؠ Ambient Assisted Living ؠ Bioinformatics ؠ Modeling & Simulation ؠ Biomechatronics ؠ Biomaterials