Products related to Quantification:
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Fluorescence Imaging and Biological Quantification
This comprehensive reference work details the latest developments in fluorescence imaging and related biological quantification.It explores the most recent techniques in this imaging technology through the utilization and incorporation of quantification analysis which makes this book unique.It also covers super resolution microscopy with the introduction of 3D imaging and high resolution fluorescence.Many of the chapter authors are world class experts in this medical imaging technology.
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Science, Technology And Innovation Indicators : Lessons from the Development Experience in Africa
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Verification, Validation, and Uncertainty Quantification in Scientific Computing
Can you trust results from modeling and simulation?This text provides a framework for assessing the reliability of and uncertainty included in the results used by decision makers and policy makers in industry and government.The emphasis is on models described by PDEs and their numerical solution.Procedures and results from all aspects of verification and validation are integrated with modern methods in uncertainty quantification and stochastic simulation.Methods for combining numerical approximation errors, uncertainty in model input parameters, and model form uncertainty are presented in order to estimate the uncertain response of a system in the presence of stochastic inputs and lack of knowledge uncertainty.This new edition has been extensively updated, including a fresh look at model accuracy assessment and the responsibilities of management for modeling and simulation activities.Extra homework problems and worked examples have been added to each chapter, suitable for course use or self-study.
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Fundamentals of Uncertainty Quantification for Engineers : Methods and Models
Fundamentals of Uncertainty Quantification for Engineers: Methods and Models provides a comprehensive introduction to uncertainty quantification (UQ) accompanied by a wide variety of applied examples, implementation details, and practical exercises to reinforce the concepts outlined in the book.Sections start with a review of the history of probability theory and recent developments of UQ methods in the domains of applied mathematics and data science.Major concepts of probability axioms, conditional probability, and Bayes’ rule are discussed and examples of probability distributions in parametric data analysis, reliability, risk analysis, and materials informatics are included. Random processes, sampling methods, and surrogate modeling techniques including multivariate polynomial regression, Gaussian process regression, multi-fidelity surrogate, support-vector machine, and decision tress are also covered.Methods for model selection, calibration, and validation are introduced next, followed by chapters on sensitivity analysis, stochastic expansion methods, Markov models, and non-probabilistic methods.The book concludes with a chapter describing the methods that can be used to predict UQ in systems, such as Monte Carlo, stochastic expansion, upscaling, Langevin dynamics, and inverse problems, with example applications in multiscale modeling, simulations, and materials design.
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How is the quantification of mathematical statements done?
Quantification of mathematical statements is done using quantifiers such as "for all" (∀) and "there exists" (∃). The symbol ∀ is used to indicate that a statement is true for all elements in a set, while the symbol ∃ is used to indicate that there exists at least one element in a set for which the statement is true. These quantifiers help to make precise and formal statements about mathematical properties and relationships. By using quantifiers, mathematicians can express universal and existential statements in a clear and unambiguous way.
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What is the detection limit or limit of quantification?
The detection limit is the lowest concentration of a substance that can be reliably detected but not necessarily quantified. It is typically defined as the concentration at which the signal is distinguishable from the background noise. The limit of quantification, on the other hand, is the lowest concentration of a substance that can be accurately measured and quantified with a known level of certainty. It is usually higher than the detection limit and is determined by the precision and accuracy of the analytical method being used.
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Does market research hinder innovation in business administration?
Market research does not necessarily hinder innovation in business administration. In fact, it can provide valuable insights into consumer needs and preferences, helping businesses to develop innovative products and services that meet market demands. By understanding market trends and customer behavior, businesses can identify opportunities for innovation and stay ahead of competitors. However, relying too heavily on market research without allowing room for creativity and risk-taking can limit the potential for groundbreaking innovations. It is important for businesses to strike a balance between leveraging market research and fostering a culture of innovation to drive success in business administration.
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What is the difference between electrical engineering, computer science, and network technology?
Electrical engineering focuses on the study and application of electricity, electromagnetism, and electronics to design and develop electrical systems and devices. Computer science, on the other hand, deals with the theory, design, development, and application of computer systems and software. Network technology involves the design, implementation, and management of computer networks to facilitate communication and data exchange between devices. While electrical engineering and computer science have some overlap in areas like digital systems and hardware design, network technology specifically focuses on the networking aspects of computer systems.
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Interpretive Quantification : Methodological Explorations for Critical and Constructivist IR
Countering the growing divide between positivists who embrace quantitative, numerical approaches and post-positivist scholars who favor qualitative, interpretive approaches, J.Samuel Barkin and Laura Sjoberg argue that both methods are more widely adaptable than is commonly assumed by either camp. In Interpretive Quantification, ten highly regarded scholars in the field of International Relations apply quantitative methods and formal models to specific constructivist and critical research questions.In this way, each chapter serves not only as evidence that methods can productively be applied across paradigms, but also as a guide as to how this may be done.In sum, the contributors make a compelling case that when researchers cordon off particular methods for merely ideological reasons, they circumscribe their own paradigms and hinder their own research agenda.
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The Complexity of Human Rights : From Vernacularization to Quantification
This book provides the first systematic assessment from a human rights law perspective of the landmark contributions of the renowned legal anthropologist, Sally Engle Merry. What impact does over-simplification have on human rights debates?The understandable tendency to present them as a single, universal, and immutable concept ignores their complexity and by extension only serves to weaken them. Merry and her colleagues transformed human rights thinking by highlighting the process of ‘vernacularization’, which sees rights discourse as being unavoidably dependent upon translation and interpretation.She also warned of the pitfalls of excessive reliance upon statistical and other indicators, through the process of quantification.Here the leading voices in the field assess the significance of these contributions.
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Uncertainty Quantification in Variational Inequalities : Theory, Numerics, and Applications
Uncertainty Quantification (UQ) is an emerging and extremely active research discipline which aims to quantitatively treat any uncertainty in applied models.The primary objective of Uncertainty Quantification in Variational Inequalities: Theory, Numerics, and Applications is to present a comprehensive treatment of UQ in variational inequalities and some of its generalizations emerging from various network, economic, and engineering models.Some of the developed techniques also apply to machine learning, neural networks, and related fields. Features First book on UQ in variational inequalities emerging from various network, economic, and engineering models Completely self-contained and lucid in style Aimed for a diverse audience including applied mathematicians, engineers, economists, and professionals from academia Includes the most recent developments on the subject which so far have only been available in the research literature
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The Metric Society : On the Quantification of the Social
In today’s world, numbers are in the ascendancy. Societies dominated by star ratings, scores, likes and lists are rapidly emerging, as data are collected on virtually every aspect of our lives.From annual university rankings, ratings agencies and fitness tracking technologies to our credit score and health status, everything and everybody is measured and evaluated. In this important new book, Steffen Mau offers a critical analysis of this increasingly pervasive phenomenon.While the original intention behind the drive to quantify may have been to build trust and transparency, Mau shows how metrics have in fact become a form of social conditioning.The ubiquitous language of ranking and scoring has changed profoundly our perception of value and status.What is more, through quantification, our capacity for competition and comparison has expanded significantly – we can now measure ourselves against others in practically every area.The rise of quantification has created and strengthened social hierarchies, transforming qualitative differences into quantitative inequalities that play a decisive role in shaping the life chances of individuals. This timely analysis of the pernicious impact of quantification will appeal to students and scholars across the social sciences, as well as anyone concerned by the cult of numbers and its impact on our lives and societies today.
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What is the difference between electrical engineering, electronics, information technology, and technical computer science?
Electrical engineering focuses on the generation, transmission, and distribution of electrical power, as well as the design of electrical systems. Electronics deals with the study of electronic components, circuits, and systems, including semiconductors and transistors. Information technology involves the use of computer systems to store, retrieve, transmit, and manipulate data. Technical computer science focuses on the design and development of software and hardware systems, including programming languages and algorithms. Each field has its own specialized focus within the broader realm of technology and engineering.
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What is the research question for a mechanical engineering dual study program with a focus on vehicle system engineering or production technology?
The research question for a mechanical engineering dual study program with a focus on vehicle system engineering or production technology could be: "How can advancements in vehicle system engineering improve the efficiency and performance of modern vehicles?" This question would involve exploring innovative technologies and design principles to enhance the functionality and sustainability of vehicles. Additionally, the research could investigate the integration of production technology to streamline manufacturing processes and optimize the production of vehicles.
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Will the development of technology ever stop?
It is unlikely that the development of technology will ever stop. As long as there are new problems to solve and new opportunities to explore, there will be a need for technological innovation. Additionally, the pace of technological advancement has been accelerating in recent years, with new breakthroughs and discoveries constantly pushing the boundaries of what is possible. While the specific direction and focus of technological development may change over time, it is likely that the overall trend of progress will continue.
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Could science fiction technology become real?
Yes, science fiction technology could become real in the future. Many of the technological advancements that were once considered science fiction, such as video calling, self-driving cars, and virtual reality, have already become a reality. With continued advancements in science and technology, it is possible that other futuristic technologies, such as teleportation or advanced artificial intelligence, could also become a reality in the future. While some science fiction technologies may still be far-fetched, it is important to remember that many of today's realities were once considered impossible in the past.
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