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Classical mechanics is mainly based on Newton's laws of motion and gravitation. Initially, it was thought that Newton's second law of motion was valid and applicable at all speeds. But new experimental evidence showed that Newton's second law of motion is valid and applicable at low speeds and invalid when the object is moving at high speeds comparable to the velocity of light. This failure of classical mechanics led to the development of the special theory of relativity by young physicist Albert Einstein in 1905, which showed everything in the universe is relative and nothing is absolute. Relativity connects space and time, matter and energy, electricity and magnetism, which are useful and remarkable to our understanding of the physical universe.
The special theory of relativity is applicable to all branches of modern physics, high-energy physics, optics, quantum mechanics, semiconductor devices, atomic theory, nanotechnology, and many other branches of science and technology.
The theory of relativity has two parts: the special theory of relativity and the general theory of relativity. The special theory of relativity deals with the inertial frame of references, while the general theory of relativity deals with the accelerated frame of references. Some common technical terms that are frequently used in relativistic mechanics are as follows:
1. Particle:A particle is a tiny bit of matter with almost no linear dimensions and is considered to be located at a single place. Its mass and charge define it. Examples include the electron, proton, and photon, among others.
Analog electronic circuits are generally offered as a core subject during the third or fourth semester of the second year in a four-year course in the electronics and communication, instrumentation and control, and computer engineering branches. It is an important subject and may be slightly toned down in the electrical, civil, chemical, and information technology branches of engineering. Design of discrete and linear integrated circuits (ICs), digital electronic modules, and electronic instrumentation are some of the obvious areas where knowledge of microelectronic circuits becomes essential. Therefore, it becomes important for students at this level of study to be proficient in electronic circuit analysis and their usage in relevant areas.
There are many fine books on electronic (devices and) circuits. Many of them have combined “devices” and “circuits”; a good practice, but sometimes resulting in the book becoming bulky. The idea here is to provide a text that deals with the fundamentals of analog electronic circuits for those who already have a basic knowledge of electronic devices, like semiconductor diodes, bipolar junction transistors (BJTs), and metal oxide semiconductor transistors (MOSFETs), either as full subject or as an introductory subject. Serious effort has been made in preparing the text so that it is not only as study material for examinations but also emphasizes fundamental concepts without being overly voluminous.
When transistors are used as switches, they operate either in cut off or in saturation mode. Whereas, when transistors are used to amplify small signals, a quiescent operating point is selected somewhere in the middle of the conduction range. The region of the location of a quiescent point depends on the kind of amplifier. For example, an amplifier may be used for maximum voltage and/or current gain, or high input resistance, or power gain. In some applications, an amplifier ought to consume minimum power, especially when it is used with a battery-operated device. After selecting the quiescent operating point, it is also required that it remains stable. If there is some change in the operating temperature or variation in supply voltage, the operating point may change its location. Variations due to the manufacturing tolerance in component values and in transistor parameters also affect the quiescent point. Irrespective of the reason, it is required that the quiescent point should remain located within specified limits.
Three amplifier configurations are commonly used while employing either BJT or FET amplification. The configuration depends on the terminals, out of the three, that is common to the input and the output of the amplifier. These configurations are studied on the basis of their characteristics, such as voltage gain, current gain, input and output resistance, and bandwidth, i.e., the frequency range within which the amplifier operates without any significant reduction in the output waveform. The operating frequency range becomes limited as the voltage gain drops at low and high operating frequencies. Hence, the study of frequency response becomes important.
A current mirror is a transistor-based circuit that the current level is controlled in an adjacent transistor, and the adjacent transistor essentially acts as a current source. Such circuits are now considered a commonly used building block in a number of analog integrated circuits (IC). Operational amplifiers, operational transconductance amplifiers, and biasing networks are examples of such circuits that essentially use current mirrors. Analog IC implementation techniques such as current-mode and switched-current circuits use current mirrors as basic circuit elements.
A significant advantage associated with the current mirrors is that they act as a near-ideal current source while fabricated using transistors and can replace large-value passive resistances in analog circuits, saving large chip area.
The later part of the chapter discusses another important analog circuit, namely, differential amplifier. As the name suggests, differential amplifiers amplify the difference between two signals that are applied to their two inputs. In addition to the differential amplification, it is also required that differential amplifiers suppress unwanted signal, which is present on the two input signals in the form of a common-mode signal. A differential amplifier is a particularly very useful and essential part of operational amplifiers. A differential pair is the basic building block of a differential amplifier that comprises of two transistors in a special form of connection.
Emphasizing how and why machine learning algorithms work, this introductory textbook bridges the gap between the theoretical foundations of machine learning and its practical algorithmic and code-level implementation. Over 85 thorough worked examples, in both Matlab and Python, demonstrate how algorithms are implemented and applied whilst illustrating the end result. Over 75 end-of-chapter problems empower students to develop their own code to implement these algorithms, equipping them with hands-on experience. Matlab coding examples demonstrate how a mathematical idea is converted from equations to code, and provide a jumping off point for students, supported by in-depth coverage of essential mathematics including multivariable calculus, linear algebra, probability and statistics, numerical methods, and optimization. Accompanied online by instructor lecture slides, downloadable Python code and additional appendices, this is an excellent introduction to machine learning for senior undergraduate and graduate students in Engineering and Computer Science.
Revised and updated throughout, the second edition of this succinct textbook provides the perfect introduction to biomaterials, linking the fundamental properties of metals, polymers, ceramics and natural biomaterials to the unique advantages and limitations surrounding their biomedical applications. New chapters on protein chemistry and interactions, immunology and tissue response, and biocompatibility round out student understanding. Clinical concerns such as sterilization, surface modification, cell-biomaterial interactions, drug delivery systems and tissue engineering are discussed, giving students insight into real-world challenges associated with biomaterials engineering. Key concepts are summarized alongside the text, allowing students to identify the most vital information. The final chapter discusses clinical applications, challenging students to consider future industrial possibilities. Concise enough to be taught in one semester, requiring only a basic understanding of biology, accompanied by over 180 end-of-chapter problems, and featuring color figures throughout, this accessible textbook continues to be ideal for students of engineering, materials science and medicine.
Written by experts in the field, this text provides a modern introduction to three-dimensional dynamics for multibody systems. It covers rotation matrices, the twist-wrench formalism for multibody dynamics and Lagrangian dynamics, an approach that is often overlooked at the undergraduate level. The only prerequisites are differential equations and linear algebra as covered in a first-year engineering mathematics course. The text focuses on obtaining and understanding the equations of motion, featuring a rich set of examples and exercises that are drawn from real-world scenarios. Readers develop a reliable physical intuition that can then be used to apply dynamic analysis software tools, and to develop simplified approximate models. With this foundation, they will be able to confidently use the equations of motion in a variety of applications, ranging from simulation and design to motion planning and control.
Master the art of data converter design with this definitive textbook, a detailed and accessible introduction ideal for students and practicing engineers. Razavi's distinctive and intuitive pedagogical approach, building up from elementary components to complex systems. Step-by-step transistor-level designs and simulations offer a practical hands-on understanding of key design concepts. Comprehensive coverage of essential topics including sampling circuits, comparator design, digital-to-analog converters, flash topologies, SAR and pipelined architectures, time-interleaved converters, and oversampling systems. Over 250 examples pose thought-provoking questions, reinforcing core concepts and helping students develop confidence. Over 350 end-of-chapter homework problems to test student understanding, with solutions available for course instructors. Developed by leading author Behzad Razavi, and addressing all the principles and design concepts essential to today's engineers, this is the ideal text for senior undergraduate and graduate-level students and professional engineers who aspire to excel in data converter analysis and design.
While an understanding of electronic principles is vitally important for scientists and engineers working across many disciplines, the breadth of the subject can make it daunting. This textbook offers a concise and practical introduction to electronics, suitable for a one-semester undergraduate course as well as self-guided students. Beginning with the basics of general circuit laws and resistor circuits to ease students into the subject, the textbook then covers a wide range of topics, from passive circuits to semiconductor-based analog circuits and basic digital circuits. Exercises are provided at the end of each chapter, and answers to select questions are included at the end of the book. The complete solutions manual is available for instructors to download, together with eight laboratory exercises that parallel the text. Now in its second edition, the text has been updated and expanded with additional topic coverage and exercises.
Confidently analyze, interpret and act on financial data with this practical introduction to the fundamentals of financial data science. Master the fundamentals with step-by-step introductions to core topics will equip you with a solid foundation for applying data science techniques to real-world complex financial problems. Extract meaningful insights as you learn how to use data to lead informed, data-driven decisions, with over 50 examples and case studies and hands-on Matlab and Python code. Explore cutting-edge techniques and tools in machine learning for financial data analysis, including deep learning and natural language processing. Accessible to readers without a specialized background in finance or machine learning, and including coverage of data representation and visualization, data models and estimation, principal component analysis, clustering methods, optimization tools, mean/variance portfolio optimization and financial networks, this is the ideal introduction for financial services professionals, and graduate students in finance and data science.
Build a firm foundation for studying statistical modelling, data science, and machine learning with this practical introduction to statistics, written with chemical engineers in mind. It introduces a data–model–decision approach to applying statistical methods to real-world chemical engineering challenges, establishes links between statistics, probability, linear algebra, calculus, and optimization, and covers classical and modern topics such as uncertainty quantification, risk modelling, and decision-making under uncertainty. Over 100 worked examples using Matlab and Python demonstrate how to apply theory to practice, with over 70 end-of-chapter problems to reinforce student learning, and key topics are introduced using a modular structure, which supports learning at a range of paces and levels. Requiring only a basic understanding of calculus and linear algebra, this textbook is the ideal introduction for undergraduate students in chemical engineering, and a valuable preparatory text for advanced courses in data science and machine learning with chemical engineering applications.
Applications of cryptography are plenty in everyday life. This guidebook is about the security analysis or 'cryptanalysis' of the basic building blocks on which these applications rely. Rather than covering a variety of techniques at an introductory level, this book provides a comprehensive and in-depth treatment of linear cryptanalysis. The subject is introduced from a mathematical point of view, providing an overview of the most influential papers on linear cryptanalysis and placing them in a consistent framework based on linear algebra. A large number of examples and exercises are included, drawing upon practice as well as theory. The book is accessible to students with no prior knowledge of cryptography. It covers linear cryptanalysis starting from the basics, including linear approximations and trails, correlation matrices, automatic search, key-recovery techniques, up to advanced topics, such as multiple and multidimensional linear cryptanalysis, zero-correlation approximations, and the geometric approach.
Roberto Verzicco, Università degli Studi di Roma ‘Tor Vergata’, Gran Sasso Science Institute, L’Aquila, and University of Twente, Enschede,Marco D. de Tullio, Politecnico di Bari,Francesco Viola, Gran Sasso Science Institute, L’Aquila
In this chapter, the coupling of IBMs with turbulence and wall models is discussed to provide the reader with a guideline to apply these methods to high Reynolds number flows. In fact, is this context, the small thickness of the flow boundary layer, combined with the impossibility to benefit from a wall-normal mesh refinement, challenges the use of IBMs unless additional models are used at the wall.
The possibility to resort to adaptive wall refinement is presented, although it is also shown that it can be combined only with RANS models.