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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.
• Phenomenon of global warming and its connection with industrialization
• Concerns and threats of global warming and climate change
• Impact of carbon emissions on global warming
• Initiatives towards reduction of carbon emissions and preventing global warming
• Concepts of Earth Overshoot Day, sustainable development and net-zero emissions
• United Nations’ sustainable development goals.
• Link between energy demand and global warming
• How to decarbonize the energy system
Introduction
Sustainable development, in recent years, has emerged as one of the most talked-about concepts. What does this term mean, and why has it become so important? The Industrial Revolution, which gained momentum in the 19th century, was a landmark event. It represented the culmination of human efforts of thousands of years. The revolution led to great inventions, making life better and easier. The human efforts involved in day-to-day activities have decreased continuously, and automation has resulted in increased human comfort. All sectors of our life, be it agriculture, transport, and even daily routine work at our homes, have been made easier by this revolution. But these developments have extracted a significant cost, particularly on the environment.
The effect of industrial activities on the environment has been described in a poignant way by @SDGoals. It shows that if we scale down the age of the earth from its actual value of 4.6 billion years to 46 years, then on the same scale human life has been on the earth for about 4 hours only. The Industrial Revolution, on this scale, began only a minute ago, and in that time, we have destroyed more than half of the world's forests.
The UN, realizing the importance of preventing damage to the climate and warming of the planet, started working in this area more than 50 years ago. But the real transformation has come after the Paris Agreement and the adoption of SDGs. The climate change challenge was largely absent from the agenda of the countries and considerations in policy formulation in even the most advanced countries in the world. Growing evidence of the threat of global warming led to a change in the approach, with a radical change seen after the declaration of the Paris Agreement and the 17 SDGs.
The most important component of the increased concern over climate change is related to energy. Energy is the dominant contributor to climate change, accounting for a minimum around 60% of total global greenhouse gas emissions, and in fact some studies have shown this share to be more than 70%. All the related key terms in vogue these days, such as ‘low-carbon system’, ‘decarbonization’, ‘net-zero system’, and ‘carbon-neutral system’, have energy at the centre. Irrespective of the solutions adopted and the timelines set by different countries, it is agreed upon by all concerned that transition to a low-carbon climate cannot be achieved without decarbonizing the energy systems.
• Steps involved for developing sustainable organizations
• Case study on a university campus
• Integration of green sources of energy
• Implementation of energy efficiency measures
• Ensuring participation of stakeholders for energy conservation
Introduction
The achievement of SDGs defined under the Paris Agreement requires concerted efforts at the international, national, state, organization, and individual levels. The organizations which follow the principles of sustainable development can serve as a role model for others to follow.
Colleges for higher education and the universities also have an important role to play in achieving the SDGs in general and in the adoption and promotion of green sources of electricity in particular. Goal 4 of SDGs, although, is specific to the availability of quality education to all, but these institutions can play a much broader role in realizing the wide-ranging SDGs. For example, Goal 9: Industry, infrastructure and innovation; Goal 12: Responsible production and consumption; and Goal 13: Climate Action cannot possibly be achieved without the mindful and positive influence of higher education institutions.
More importantly, these institutes need to work on the creation of awareness about the need for sustainable development and SDGs, a crucial requirement for their achievement. The institutes should also make sustainable development an integral part of their future plans. Green and renewable sources of energy like solar PV should be adopted for existing buildings, and these should be made mandatory for the new buildings. The academic institutes, more importantly, should practice on their campuses what they are preaching in the class.
" Working of solar PV power plants and their benefits
" Different configurations of solar PV systems, such as grid-connected, stand-alone, and hybrid solar PV plants
" Metering mechanisms, such as net metring and gross metring
" Working and classification of different types of inverters used in solar energy generation
" Different performance evaluation parameters for solar PV power plants and effect of environmental conditions
" Components used in solar PV power plants
" Challenges related to the large-scale integration of solar PV plants with the power grid
Introduction
Solar energy is a renewable source of energy, and when electricity is produced from solar, it does not lead to any CO2 emissions. Apart from being a green and renewable source of energy, solar is the simplest system of electricity generation. As described by Professor Martin Green, ‘The whole photovoltaic technology itself is a bit magical. Sunlight just falls on this inert material and you get electricity straight out of it.’ This technology has emerged as the most powerful solution for decarbonizing the energy system.
The solar PV plants can be installed in two modes: grid-connected and off-grid system. At present, grid-connected solar PV (GCSPV) plants are the most commonly used systems. Although solar PV cells, were discovered in the year 1953, solar PV plants for generating electricity did not gain widespread acceptance primarily because of the panel cost as well as the issues with the batteries involved. GCSPV technology has removed the weak link, the battery from the system, making it an efficient, economical, and durable system with minimum maintenance requirements. These benefits have made the solar PV the fastest rising system in the world.
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.
A comprehensive yet concise history of the English language, this accessible textbook helps those studying the subject to understand the formation of English. It tells the story of the language from its remote ancestry to the present day, especially the effects of globalisation and the spread of, and subsequent changes to, English. Now in its third edition, it has been substantially revised and updated in light of new research, with an extended chapter on World Englishes, and a completely updated final chapter, which concentrate on changes to English in the twenty-first century. It makes difficult concepts very easy to understand, and the chapters are set out to make the most of the wide range of topics covered, using dozens of familiar texts, including the English of King Alfred, Chaucer, Shakespeare, and Addison. It is accompanied by a website with exercises for each chapter, and a range of extra resources.
Students will develop a practical understanding of data science with this hands-on textbook for introductory courses. This new edition is fully revised and updated, with numerous exercises and examples in the popular data science tool Python, a new chapter on using Python for statistical analysis, and a new chapter that demonstrates how to use Python within a range of cloud platforms. The many practice examples, drawn from real-life applications, range from small to big data and come to life in a new end-to-end project in Chapter 11. New 'Data Science in Practice' boxes highlight how concepts introduced work within an industry context and many chapters include new sections on AI and Generative AI. A suite of online material for instructors provides a strong supplement to the book, including lecture slides, solutions, additional assessment material and curriculum suggestions. Datasets and code are available for students online. This entry-level textbook is ideal for readers from a range of disciplines wishing to build a practical, working knowledge of data science.
Historical Sociolinguistics is the study of the relationship between language and society in its historical dimension. This is the first textbook to introduce this vibrant field, based on examples and case studies taken from a variety of languages. Chapters begin with clear explanations of core concepts, which are then applied to historical contexts from different languages, such as English, French, Hindi and Mandarin. The volume uses several pedagogical methods, allowing readers to gain a deeper understanding of the theory and of examples. A list of key terms is provided, covering the main theoretical and methodological issues discussed. The book also includes a range of exercises and short further reading sections for students. It is ideal for students of sociolinguistics and historical linguistics, as well as providing a basic introduction to historical sociolinguistics for anyone with an interest in linguistics or social history.
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.
This leading textbook introduces students and practitioners to the identification and analysis of animal remains at archaeology sites. The authors use global examples from the Pleistocene era into the present to explain how zooarchaeology allows us to form insights about relationships among people and their natural and social environments, especially site-formation processes, economic strategies, domestication, and paleoenvironments. This new edition reflects the significant technological developments in zooarchaeology that have occurred in the past two decades, notably ancient DNA, proteomics, and isotope geochemistry. Substantially revised to reflect these trends, the volume also highlights novel applications, current issues in the field, the growth of international zooarchaeology, and the increased role of interdisciplinary collaborations. In view of the growing importance of legacy collections, voucher specimens, and access to research materials, it also includes a substantially revised chapter that addresses management of zooarchaeological collections and curation of data.
Students have an almost insurmountable task in understanding statistics in the psychological sciences and applying them to a research study. This textbook tackles this source of stress by guiding students through the research process, start to finish, from writing a proposal and performing the study, to analysing the results and creating a report and presentation. This truly practical textbook explains psychology research methods in a conversational style, with additional material of interest placed in focus boxes alongside, so that students don't lose their way through the steps. Every step is detailed visually with processes paralleled in both SPSS and R, allowing instructors and students to learn both statistical packages or to bridge from one to the other. Students perform hands-on statistical exercises using real data, and both qualitative and mixed-methods research are covered. They learn effective ways to present information visually, and about free tools to collect and analyse data.
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.
Teaching fundamental design concepts and the challenges of emerging technology, this textbook prepares students for a career designing the computer systems of the future. Self-contained yet concise, the material can be taught in a single semester, making it perfect for use in senior undergraduate and graduate computer architecture courses. This edition has a more streamlined structure, with the reliability and other technology background sections now included in the appendix. New material includes a chapter on GPUs, providing a comprehensive overview of their microarchitectures; sections focusing on new memory technologies and memory interfaces, which are key to unlocking the potential of parallel computing systems; deeper coverage of memory hierarchies including DRAM architectures, compression in memory hierarchies and an up-to-date coverage of prefetching. Practical examples demonstrate concrete applications of definitions, while the simple models and codes used throughout ensure the material is accessible to a broad range of computer engineering/science students.
Only when we fully appreciate the origins and foundations of child and adolescent behaviors will we succeed in uncovering why they do what they do. By emphasizing evolutionary viewpoints of human psychological development, this textbook explains the fundamental underpinnings of young minds and how they grow. New chapters on the biological basis and cultural context of development introduce students to dynamic new debates in the field. The integrative, topical approach incorporates the perspectives that guide today's practitioners and gives students a holistic and up-to-date understanding of development. Box features highlight key debates, Section Reviews reinforce essential points, and “Ask Yourself” questions and end-of-chapter exercises encourage engagement and extend learning, supporting and enhancing student understanding. Revised and updated throughout, this comprehensive, topical textbook uniquely integrates the central themes of modern developmental theory – developmental contextualism, sociocultural perspective, and evolutionary theory – in a strong, theoretical introduction to child and adolescent development.