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Author | Title | Accn# | Year | Item Type | Claims |
| 1 |
Cacuci, Dan Gabriel |
The nth-Order Comprehensive Adjoint Sensitivity Analysis Methodology, Volume I |
I12435 |
2022 |
Book |
|
| 2 |
Bonamente, Massimiliano |
Statistics and Analysis of Scientific Data |
I12430 |
2022 |
Book |
|
| 3 |
Mustapha, Aida Binti |
Proceedings of the 7th International Conference on the Applications of Science and Mathematics 2021 |
I12419 |
2022 |
Book |
|
| 4 |
Taylor, Alexander John |
Analysis of Quantised Vortex Tangle |
I10040 |
2017 |
eBook |
|
| 5 |
Vitali, Ettore |
Theory and Simulation of Random Phenomena |
I09810 |
2018 |
eBook |
|
| 6 |
Eliazar, Iddo |
Power Laws |
I08903 |
2020 |
eBook |
|
| 7 |
Sharp, Kim |
Entropy and the Tao of Counting |
I08704 |
2019 |
eBook |
|
| 8 |
Harney, Hanns L |
Bayesian Inference |
I11266 |
2003 |
eBook |
|
| 9 |
Feigelson, Eric D |
Statistical Challenges in Astronomy |
I10925 |
2003 |
eBook |
|
| 10 |
Starck, J.-L |
Astronomical Image and Data Analysis |
I07208 |
2006 |
eBook |
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1.
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| Title | The nth-Order Comprehensive Adjoint Sensitivity Analysis Methodology, Volume I : Overcoming the Curse of Dimensionality: Linear Systems |
| Author(s) | Cacuci, Dan Gabriel |
| Publication | Cham, 1. Imprint: Springer
2. Springer International Publishing, 2022. |
| Description | XII, 362 p : online resource |
| Abstract Note | The computational models of physical systems comprise parameters, independent and dependent variables. Since the physical processes themselves are seldom known precisely and since most of the model parameters stem from experimental procedures which are also subject to imprecisions, the results predicted by these models are also imprecise, being affected by the uncertainties underlying the respective model. The functional derivatives (also called ???sensitivities???) of results (also called ???responses???) produced by mathematical/computational models are needed for many purposes, including: (i) understanding the model by ranking the importance of the various model parameters; (ii) performing ???reduced-order modeling??? by eliminating unimportant parameters and/or processes; (iii) quantifying the uncertainties induced in a model response due to model parameter uncertainties; (iv) performing ???model validation,??? by comparing computations to experiments to address the question ???does the model represent reality???? (v) prioritizing improvements in the model; (vi) performing data assimilation and model calibration as part of forward ???predictive modeling??? to obtain best-estimate predicted results with reduced predicted uncertainties; (vii) performing inverse ???predictive modeling???; (viii) designing and optimizing the system. This 3-Volume monograph describes a comprehensive adjoint sensitivity analysis methodology, developed by the author, which enables the efficient and exact computation of arbitrarily high-order sensitivities of model responses in large-scale systems comprising many model parameters. The qualifier ???comprehensive??? is employed to highlight that the model parameters considered within the framework of this methodology also include the system???s uncertain boundaries and internal interfaces in phase-space. The model???s responses can be either scalar-valued functionals of the model???s parameters and state variables (e.g., as customarily encountered in optimization problems) or general function-valued responses. Since linear operators admit bona-fide adjoint operators, responses of models that are linear in the state functions (i.e., dependent variables) can depend simultaneously on both the forward and the adjoint state functions. Hence, the sensitivity analysis of such responses warrants the treatment of linear systems in their own right, rather than treating them as particular cases of nonlinear systems. This is in contradistinction to responses for nonlinear systems, which can depend only on the forward state functions, since nonlinear operators do not admit bona-fide adjoint operators (only a linearized form of a nonlinear operator may admit an adjoint operator). Thus, Volume 1 of this book presents the mathematical framework of the nth-Order Comprehensive Adjoint Sensitivity Analysis Methodology for Response-Coupled Forward/Adjoint Linear Systems (abbreviated as ???nth-CASAM-L???), which is conceived for the most efficient computation of exactly obtained mathematical expressions of arbitrarily-high-order (nth-order) sensitivities of a generic system response with respect to all of the parameters underlying the respective forward/adjoint systems. Volume 2 of this book presents the application of the nth-CASAM-L to perform a fourth-order sensitivity and uncertainty analysis of an OECD/NEA reactor physics benchmark which is representative of a large-scale model comprises many (21,976) uncertain parameters, thereby amply illustrating the unique potential of the nth-CASAM-L to enable the exact and efficient computation of chosen high-order response sensitivities to model parameters. Volume 3 of this book presents the ???nth-Order Comprehensive Adjoint Sensitivity Analysis Methodology for Nonlinear Systems??? (abbreviation: nth-CASAM-N) for the practical, efficient, and exact computation of arbitrarily-high order sensitivities of responses to model parameters for systems that are also nonlinear in their underlying state functions. Such computations are not feasible with any other methodology. The application of the nth-CASAM-L and the nth-CASAM-N overcomes the so-called ???curse of dimensionality??? in sensitivity and uncertainty analysis, thus revolutionizing all of the fields of activities which require accurate computation of response sensitivities. Since this monograph includes many illustrative, fully worked-out, paradigm problems, it can serve as a textbook or as supplementary reading for graduate courses in academic departments in the natural sciences and engineering |
| ISBN,Price | 9783030963644 |
| Keyword(s) | 1. Computational Physics and Simulations
2. COMPUTER SIMULATION
3. EBOOK
4. EBOOK - SPRINGER
5. Energy and state
6. Energy policy
7. Energy Policy, Economics and Management
8. ENGINEERING MATHEMATICS
9. Engineering???Data processing
10. Mathematical and Computational Engineering Applications
11. Mathematical Modeling and Industrial Mathematics
12. MATHEMATICAL MODELS
13. MATHEMATICAL PHYSICS
14. NUCLEAR PHYSICS
15. Statistical Theory and Methods
16. Statistics??
|
| Item Type | Book |
Multi-Media Links
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| Accession# | |
Call# | Status | Issued To | Return Due On | Physical Location |
| I12435 |
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On Shelf |
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2.
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| Title | Statistics and Analysis of Scientific Data |
| Author(s) | Bonamente, Massimiliano |
| Publication | Singapore, 1. Imprint: Springer
2. Springer Nature Singapore, 2022. |
| Description | XXIII, 488 p. 58 illus., 48 illus. in color : online resource |
| Abstract Note | This book is the third edition of a successful textbook for upper-undergraduate and early graduate students, which offers a solid foundation in probability theory and statistics and their application to physical sciences, engineering, biomedical sciences and related disciplines. It provides broad coverage ranging from conventional textbook content of probability theory, random variables, and their statistics, regression, and parameter estimation, to modern methods including Monte-Carlo Markov chains, resampling methods and low-count statistics. In addition to minor corrections and adjusting structure of the content, particular features in this new edition include: Python codes and machine-readable data for all examples, classic experiments, and exercises, which are now more accessible to students and instructors New chapters on low-count statistics including the Poisson-based Cash statistic for regression in the low-count regime, and on contingency tables and diagnostic testing. An additional example of classic experiments based on testing data for SARS-COV-2 to demonstrate practical applications of the described statistical methods. This edition inherits the main pedagogical method of earlier versions???a theory-then-application approach???where emphasis is placed first on a sound understanding of the underlying theory of a topic, which becomes the basis for an efficient and practical application of the materials. Basic calculus is used in some of the derivations, and no previous background in probability and statistics is required. The book includes many numerical tables of data as well as exercises and examples to aid the readers' understanding of the topic |
| ISBN,Price | 9789811903656 |
| Keyword(s) | 1. Applied Statistics
2. Data Analysis and Big Data
3. EBOOK
4. EBOOK - SPRINGER
5. ENGINEERING MATHEMATICS
6. Engineering???Data processing
7. Mathematical and Computational Engineering Applications
8. Mathematical Methods in Physics
9. MATHEMATICAL PHYSICS
10. Mathematical statistics???Data processing
11. Quantitative research
12. Statistical Theory and Methods
13. Statistics and Computing
14. Statistics??
|
| Item Type | Book |
Multi-Media Links
Please Click here for eBook
Circulation Data
| Accession# | |
Call# | Status | Issued To | Return Due On | Physical Location |
| I12430 |
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On Shelf |
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3.
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| Title | Proceedings of the 7th International Conference on the Applications of Science and Mathematics 2021 : Sciemathic 2021 |
| Author(s) | Mustapha, Aida Binti;Shamsuddin, Suhadir;Zuhaib Haider Rizvi, Syed;Asman, Saliza Binti;Jamaian, Siti Suhana |
| Publication | Singapore, 1. Imprint: Springer
2. Springer Nature Singapore, 2022. |
| Description | XXVI, 464 p. 212 illus., 167 illus. in color : online resource |
| Abstract Note | This book presents peer-reviewed articles and recent advances on the potential applications of Science and Mathematics for future technologies, from the 7th International Conference on the Applications of Science and Mathematics (SCIEMATHIC 2021), held in Malaysia. It provides an insight about the leading trends in sustainable Science and Technology. The world is looking for sustainable solutions to problems more than ever. The synergistic approach of mathematicians, scientists and engineers has undeniable importance for future technologies. With this viewpoint, SCIEMATHIC 2021 has the theme ???Quest for Sustainable Science and Mathematics for Future Technologies???. The conference brings together physicists, mathematicians, statisticians and data scientists, providing a platform to find sustainable solutions to major problems around us. The works presented here are suitable for professionals and researchers globally in making the world a better and sustainable place |
| ISBN,Price | 9789811689031 |
| Keyword(s) | 1. Chemistry, Physical and theoretical
2. EBOOK
3. EBOOK - SPRINGER
4. MATERIALS SCIENCE
5. Mathematical Modeling and Industrial Mathematics
6. MATHEMATICAL MODELS
7. MATHEMATICAL PHYSICS
8. Statistical Theory and Methods
9. Statistics??
10. Sustainability
11. THEORETICAL CHEMISTRY
|
| Item Type | Book |
Multi-Media Links
Please Click here for eBook
Circulation Data
| Accession# | |
Call# | Status | Issued To | Return Due On | Physical Location |
| I12419 |
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On Shelf |
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4.
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| Title | Analysis of Quantised Vortex Tangle |
| Author(s) | Taylor, Alexander John |
| Publication | Cham, Springer International Publishing, 2017. |
| Description | XVI, 197 p. 95 illus., 84 illus. in color : online resource |
| Abstract Note | In this thesis, the author develops numerical techniques for tracking and characterising the convoluted nodal lines in three-dimensional space, analysing their geometry on the small scale, as well as their global fractality and topological complexity---including knotting---on the large scale. The work is highly visual, and illustrated with many beautiful diagrams revealing this unanticipated aspect of the physics of waves. Linear superpositions of waves create interference patterns, which means in some places they strengthen one another, while in others they completely cancel each other out. This latter phenomenon occurs on 'vortex lines' in three dimensions. In general wave superpositions modelling e.g. chaotic cavity modes, these vortex lines form dense tangles that have never been visualised on the large scale before, and cannot be analysed mathematically by any known techniques. |
| ISBN,Price | 9783319485560 |
| Keyword(s) | 1. EBOOK
2. EBOOK - SPRINGER
3. MATHEMATICAL PHYSICS
4. Numerical and Computational Physics, Simulation
5. PHYSICS
6. Statistical Theory and Methods
7. Statistics??
8. TOPOLOGY
|
| Item Type | eBook |
Multi-Media Links
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| Accession# | |
Call# | Status | Issued To | Return Due On | Physical Location |
| I10040 |
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On Shelf |
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5.
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| Title | Theory and Simulation of Random Phenomena : Mathematical Foundations and Physical Applications |
| Author(s) | Vitali, Ettore;Motta, Mario;Galli, Davide Emilio |
| Publication | Cham, Springer International Publishing, 2018. |
| Description | XIII, 235 p. 5 illus : online resource |
| Abstract Note | The purpose of this book is twofold: first, it sets out to equip the reader with a sound understanding of the foundations of probability theory and stochastic processes, offering step-by-step guidance from basic probability theory to advanced topics, such as stochastic differential equations, which typically are presented in textbooks that require a very strong mathematical background. Second, while leading the reader on this journey, it aims to impart the knowledge needed in order to develop algorithms that simulate realistic physical systems. Connections with several fields of pure and applied physics, from quantum mechanics to econophysics, are provided. Furthermore, the inclusion of fully solved exercises will enable the reader to learn quickly and to explore topics not covered in the main text. The book will appeal especially to graduate students wishing to learn how to simulate physical systems and to deepen their knowledge of the mathematical framework, which has very deep connections with modern quantum field theory |
| ISBN,Price | 9783319905150 |
| Keyword(s) | 1. EBOOK
2. EBOOK - SPRINGER
3. Mathematical Applications in the Physical Sciences
4. Mathematical Methods in Physics
5. MATHEMATICAL PHYSICS
6. Numerical and Computational Physics, Simulation
7. PHYSICS
8. PROBABILITIES
9. Probability Theory and Stochastic Processes
10. Statistical Theory and Methods
11. Statistics??
|
| Item Type | eBook |
Multi-Media Links
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| Accession# | |
Call# | Status | Issued To | Return Due On | Physical Location |
| I09810 |
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On Shelf |
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6.
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| Title | Power Laws : A Statistical Trek |
| Author(s) | Eliazar, Iddo |
| Publication | Cham, Springer International Publishing, 2020. |
| Description | XX, 203 p. 1 illus : online resource |
| Abstract Note | This monograph is a comprehensive and cohesive exposition of power-law statistics. Following a bottom-up construction from a foundational bedrock ??? the power Poisson process ??? this monograph presents a unified study of an assortment of power-law statistics including: Pareto laws, Zipf laws, Weibull and Fr??chet laws, power Lorenz curves, L??vy laws, power Newcomb-Benford laws, sub-diffusion and super-diffusion, and 1/f and flicker noises. The bedrock power Poisson process, as well as the assortment of power-law statistics, are investigated via diverse perspectives: structural, stochastic, fractal, dynamical, and socioeconomic. This monograph is poised to serve researchers and practitioners ??? from various fields of science and engineering ??? that are engaged in analyses of power-law statistics |
| ISBN,Price | 9783030332358 |
| Keyword(s) | 1. COMPLEX SYSTEMS
2. COMPLEXITY
3. COMPUTATIONAL COMPLEXITY
4. EBOOK
5. EBOOK - SPRINGER
6. STATISTICAL PHYSICS
7. Statistical Physics and Dynamical Systems
8. Statistical Theory and Methods
9. Statistics??
10. SYSTEM THEORY
|
| Item Type | eBook |
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| Accession# | |
Call# | Status | Issued To | Return Due On | Physical Location |
| I08903 |
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On Shelf |
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8.
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| Title | Bayesian Inference : Parameter Estimation and Decisions |
| Author(s) | Harney, Hanns L |
| Publication | Berlin, Heidelberg, Springer Berlin Heidelberg, 2003. |
| Description | XIII, 263 p : online resource |
| Abstract Note | The book provides a generalization of Gaussian error intervals to situations where the data follow non-Gaussian distributions. This usually occurs in frontier science, where the observed parameter is just above background or the histogram of multiparametric data contains empty bins. Then the validity of a theory cannot be decided by the chi-squared-criterion, but this long-standing problem is solved here. The book is based on Bayes' theorem, symmetry and differential geometry. In addition to solutions of practical problems, the text provides an epistemic insight: The logic of quantum mechanics is obtained as the logic of unbiased inference from counting data. However, no knowledge of quantum mechanics is required. The text, examples and exercises are written at an introductory level |
| ISBN,Price | 9783662060063 |
| Keyword(s) | 1. COMPLEX SYSTEMS
2. Computational Mathematics and Numerical Analysis
3. Computer mathematics
4. DYNAMICAL SYSTEMS
5. EBOOK
6. EBOOK - SPRINGER
7. PROBABILITIES
8. Probability Theory and Stochastic Processes
9. QUANTUM COMPUTERS
10. Quantum Information Technology, Spintronics
11. QUANTUM PHYSICS
12. SPINTRONICS
13. STATISTICAL PHYSICS
14. Statistical Theory and Methods
15. Statistics??
|
| Item Type | eBook |
Multi-Media Links
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Circulation Data
| Accession# | |
Call# | Status | Issued To | Return Due On | Physical Location |
| I11266 |
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On Shelf |
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9.
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| Title | Statistical Challenges in Astronomy |
| Author(s) | Feigelson, Eric D;Babu, Jogesh |
| Publication | New York, NY, Springer New York, 2003. |
| Description | XXII, 506 p : online resource |
| Abstract Note | Digital sky surveys, high-precision astrometry from satellite data, deep-space data from orbiting telescopes, and the like have all increased the quantity and quality of astronomical data by orders of magnitude per year for several years. Making sense of this wealth of data requires sophisticated statistical techniques. Fortunately, statistical methodologies have similarly made great strides in recent years. Powerful synergies thus emerge when astronomers and statisticians join in examining astrostatistical problems and approaches. The book begins with an historical overview and tutorial articles on basic cosmology for statisticians and the principles of Bayesian analysis for astronomers. As in earlier volumes in this series, research contributions discussing topics in one field are joined with commentary from scholars in the other. Thus, for example, an overview of Bayesian methods for Poissonian data is joined by discussions of planning astronomical observations with optimal efficiency and nested models to deal with instrumental effects. The principal theme for the volume is the statistical methods needed to model fundamental characteristics of the early universe on its largest scales |
| ISBN,Price | 9780387215297 |
| Keyword(s) | 1. Astronomy, Observations and Techniques
2. Astronomy???Observations
3. COSMOLOGY
4. EBOOK
5. EBOOK - SPRINGER
6. Observations, Astronomical
7. SPACE SCIENCES
8. Space Sciences (including Extraterrestrial Physics, Space Exploration and Astronautics)
9. Statistical Theory and Methods
10. Statistics??
|
| Item Type | eBook |
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| Accession# | |
Call# | Status | Issued To | Return Due On | Physical Location |
| I10925 |
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On Shelf |
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10.
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| Title | Astronomical Image and Data Analysis |
| Author(s) | Starck, J.-L;Murtagh, F |
| Publication | Berlin, Heidelberg, Springer Berlin Heidelberg, 2006. |
| Description | XIV, 338 p : online resource |
| Abstract Note | With information and scale as central themes, this comprehensive survey explains how to handle real problems in astronomical data analysis using a modern arsenal of powerful techniques. It treats those innovative methods of image, signal, and data processing that are proving to be both effective and widely relevant. The authors are leaders in this rapidly developing field and draw upon decades of experience. They have been playing leading roles in international projects such as the Virtual Observatory and the Grid. The book addresses not only students and professional astronomers and astrophysicists, but also serious amateur astronomers and specialists in earth observation, medical imaging, and data mining. The coverage includes chapters or appendices on: detection and filtering; image compression; multichannel, multiscale, and catalog data analytical methods; wavelets transforms, Picard iteration, and software tools. This second edition of Starck and Murtagh's highly appreciated reference again deals with topics that are at or beyond the state of the art. It presents material which is more algorithmically oriented than most alternatives and broaches new areas like ridgelet and curvelet transforms. Throughout the book various additions and updates have been made |
| ISBN,Price | 9783540330257 |
| Keyword(s) | 1. Astronomy, Observations and Techniques
2. Astronomy???Observations
3. DATABASE MANAGEMENT
4. EBOOK
5. EBOOK - SPRINGER
6. Information storage and retrieval
7. Observations, Astronomical
8. Statistical Theory and Methods
9. Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences
10. Statistics??
|
| Item Type | eBook |
Multi-Media Links
Please Click here for eBook
Circulation Data
| Accession# | |
Call# | Status | Issued To | Return Due On | Physical Location |
| I07208 |
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On Shelf |
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