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Applied scanning probe methods IX : Characterization
The success of the Springer Series Applied Scanning Probe Methods I–VII and the rapidly expanding activities in scanning probe development and applications worldwide made it a natural step to collect further speci c results in the elds of development of scanning probe microscopy techniques (Vol. VIII), characterization (Vol. IX), and biomimetics and industrial applications (Vol. X). These three volumes complement the previous set of volumes under the subject topics and give insight into the recent work of leading specialists in their respective elds. Following the tradition of the series, the chapters are arranged around techniques, characterization and biomimetics and industrial applications. Volume VIII focuses on novel scanning probe techniques and the understanding of tip/sample interactions. Topics include near eld imaging, advanced AFM, s- cializedscanningprobemethodsinlifesciencesincludingnewselfsensingcantilever systems, combinations of AFM sensors and scanning electron and ion microscopes, calibration methods, frequency modulation AFM for application in liquids, Kelvin probe force microscopy, scanning capacitance microscopy, and the measurement of electrical transport properties at the nanometer scale.
Applied scanning probe methods IV : Industrial applications
The sc- ning probes emerged as a new - strument for imaging with a p- cision suf?cient to delineate single atoms. At first there were two – the Scanning Tunneling Microscope, or STM, and the Atomic Force Mic- scope, or AFM. The STM relies on electrons tunneling between tip and sample whereas the AFM depends on the force acting on the tip when it was placed near the sample. These were quickly followed by the M- netic Force Microscope, MFM, and the Electrostatic Force Microscope, EFM. The MFM will image a single magnetic bit with features as small as 10nm. With the EFM one can monitor the charge of a single electron.
Applied scanning probe methods III : Characterization
The sc- ning probes emerged as a new - strument for imaging with a p- cision suf?cient to delineate single atoms. At first there were two – the Scanning Tunneling Microscope, or STM, and the Atomic Force Mic- scope, or AFM. The STM relies on electrons tunneling between tip and sample whereas the AFM depends on the force acting on the tip when it was placed near the sample. These were quickly followed by the M- netic Force Microscope, MFM, and the Electrostatic Force Microscope, EFM. The MFM will image a single magnetic bit with features as small as 10nm. With the EFM one can monitor the charge of a single electron.
Applied scanning probe methods II : Scanning probe microscopy techniques
The sc- ning probes emerged as a new - strument for imaging with a p- cision suf?cient to delineate single atoms. At first there were two – the Scanning Tunneling Microscope, or STM, and the Atomic Force Mic- scope, or AFM. The STM relies on electrons tunneling between tip and sample whereas the AFM depends on the force acting on the tip when it was placed near the sample. These were quickly followed by the M- netic Force Microscope, MFM, and the Electrostatic Force Microscope, EFM. The MFM will image a single magnetic bit with features as small as 10nm. With the EFM one can monitor the charge of a single electron.
Applied Research in Uncertainty Modeling and Analysis
For a long time uncertainty has been considered synonymous with random, stochastic, statistic, or probabilistic. Since the early sixties views on uncertainty have become more heterogeneous. In the past forty years numerous tools that model uncertainty, above and beyond statistics, have been proposed by several engineers and scientists. The tool/method to model uncertainty in a specific context should really be chosen by considering the features of the phenomenon under consideration, not independent of what is known about the system and what causes uncertainty. In this fascinating overview of the field, the authors provide broad coverage of uncertainty analysis/modeling and its application. Applied Research in Uncertainty Modeling and Analysis presents the perspectives of various researchers and practitioners on uncertainty analysis and modeling outside their own fields and domain expertise. Rather than focusing explicitly on theory, the authors use real-world examples to demonstrate the strength of the chosen methodology. Applied Research in Uncertainty Modeling and Analysis concentrates on general aspects of uncertainty, modeling, and methods, and focuses on various applications, included Biomedical Engineering, Chemical Engineering, Structural Engineering, and Transportation Engineering.
Applied Reliability and Quality : Fundamentals, Methods and Procedures
"Reliability and quality professionals need to know about each other's work activities because this may help them - directly or indirectly - to perform their tasks more effectively. Applied Reliability and Quality: Fundamentals, Methods and Procedures meets the need for a single volume that considers applied areas of both reliability and quality. Before now, there has not been one book that covers both applied reliability and quality; so to gain knowledge of each other's specialties, these people had to study various books, articles, or reports on each area."
Applied Quantitative Finance
Applied Quantitative Finance (2nd edition) provides a comprehensive and state-of-the-art treatment of cutting-edge topics and methods. It provides solutions to and presents theoretical developments in many practical problems such as risk management, pricing of credit derivatives, quantification of volatility and copula modelling. The synthesis of theory and practice supported by computational tools is reflected in the selection of topics as well as in a finely tuned balance of scientific contributions on practical implementation and theoretical concepts. This linkage between theory and practice offers theoreticians insights into considerations of applicability and, vice versa, provides practitioners comfortable access to new techniques in quantitative finance.
Applied Parallel Computing ; State of the Art in Scientific Computing
Introduction The PARA workshops in the past were devoted to parallel computing methods in science and technology. There have been seven PARA meetings to date: PARA’94, PARA’95 and PARA’96 in Lyngby, Denmark, PARA’98 in Umea, ? Sweden, PARA 2000 in Bergen, N- way, PARA 2002 in Espoo, Finland, and PARA 2004 again in Lyngby, Denmark. The ?rst six meetings featured lectures in modern numerical algorithms, computer science, en- neering, and industrial applications, all in the context of scienti?c parallel computing. This meeting in the series, the PARA 2004 Workshop with the title “State of the Art in Scienti?c Computing.
Applied Parallel Computing ; 6th International Conference, PARA 2002, Espoo, Finland, June 15-18, 2002. Proceeding
These proceedings contain the papers presented at PARA 2002, the Sixth In-ternational Conference on Applied Parallel Computing. PARA 2002 was held inEspoo, Finland, June 15–18, 2002, and hosted by CSC, the Finnish informationtechnology center for science. The general theme of the conference was advancedscientific computing.The conference demonstrated the ability of advanced scientific computing tosolve real-world problems, and highlighted methods, instruments, and trends infuture scientific computing. The conference began with a one-day tutorial sessionon Grid programming.The conference focused on an application-oriented, multi-disciplinary, andmulti-scale approach. A wide variety of scientific computing applications wereintroduced, from semiconductor processing and behavior of the human body tooceanic and atmospheric phenomena.
Applied Multivariate Statistical Analysis
This book presents the tools and concepts of multivariate data analysis in a way that is understandable for non-mathematicians and practitioners who face statistical data analysis.
Applied mathematics and machine learning
The simultaneous availability of large datasets and high-performance computing capability in recent years has enabled the rapid development of powerful machine learning algorithms. On the one hand, state-of-the-art machine learning techniques have transformed many areas of science and engineering; on the other hand, theoretical discoveries in mathematical algorithms, differential equations, and statistical inferences, to name a few, have provided the foundation for the exploration of new multidisciplinary models for solving practical problems. This Special Issue endeavors to continue the journey that started in our previous Special Issue (Applied Mathematics and Computational Physics) by providing a platform for researchers from both academia and industry, as well as government, to present their new computational methods that have engineering and physics applications.
Applied Mathematical Demography
it focus on applications of demographic models, while extending its scope to matrix models for stage-classified populations.first introduce the life table to describe age-specific mortality, and then use it to develop theory for stable populations and the rate of population increase. This theory is then revisited in the context of matrix models, for stage-classified as well as age-classified populations. Reproductive value and the stable equivalent population are introduced in both contexts, and Markov chain methods are presented to describe the movement of individuals through the life cycle. Applications of mathematical demography to population projection and forecasting, kinship, microdemography, heterogeneity, and multi-state models are considered.
Applied Hydrogeophysics
This book focuses on how hydrogeophysical methods can be applied to solve problems facing environmental engineers, geophysicists, agronomists, hydrologists, soil scientists and hydrogeologists. We present applications of hydrogeophysical methods to the understanding of hydrological processes and environmental problems dealing with the flow of water and the transport of solutes and contaminants. The majority of the book is organized as a series of process-driven chapters, each authored by leading experts. Areas covered include: infiltration and solute transport processes, biogeochemical functioning of soil-water systems, coastal groundwater interactions, cold region hydrology, engineered barriers and landfill processes. In addition, the book offers insight into the development of new data fusion methodologies, of value to many hydrogeophysical investigations, and provides an account how the rapidly developing self-potential technique can give valuable information about water fluxes and hydrochemical states within the subsurface.
Applied Graph Theory in Computer Vision and Pattern Recognition
It presents the application of graph theory to low-level processing of digital images, presents graph-theoretic learning algorithms for high-level computer vision and pattern recognition applications, and provides detailed descriptions of several applications of graph-based methods to real-world pattern recognition tasks.
Applied geotechnics for construction projects ; Vol. 3 : Behavior and Design of Project Foundations and Eurocode Validation
Applied Geotechnics for Construction Projects 3 first presents the basic theoretical principles and rules governing the designing and validation of foundations; shallow, semi-deep and deep, then presents real foundation projects with a detailed comparison of the approaches and methods of calculating foundations in relation to the reference systems and rules in force, closely compared to and validated by the Eurocodes. The third chapter presents examples of foundation projects, covering high-side building rafts, strip footings, piles and embankments, enriched by an unprecedented level of experience in the field of foundations for civil and industrial construction projects.
Applied geotechnics for construction projects ; Vol. 1 : Soil and Experimental Data
Applied Geotechnics for Construction Projects 1 first defines, identifies and classifies soils, exploring their complexities and weaknesses, and then outlines the basic principles of stresses and strains that establish and develop within soils. The third chapter of the book introduces and develops methods of soil investigation in order to experimentally determine the geotechnical parameters that are useful in the design stage of construction projects.
Applied computational materials modeling : Theory, simulation and experiment
this book provides the average person working in the materials field with a more balanced perspective of the role that computational modeling can play in every day research and development efforts. This is done by presenting a series of examples of the successful application of various computational modeling procedures (everything from first principles to quantum approximate to CALPHAD methods) to real life surface and bulk alloy problems.This book should have a large appeal in the materials community, both for experimentalists who would greatly benefit from adding computational methods to their everyday research regimes, as well as for those scientists/engineers familiar with a particular computational method who would like to add complementary techniques to their arsenal of research and development tools
Applied Civil Engineering Risk Analysis
Povides readers with the tools needed to determine the probability of failure, and when multiplied by the consequences of failure, illustrates how to assess the risk of civil engineering problems. Presenting methods for quantifying uncertainty that exists in engineering analysis and design, with an emphasis on fostering more accurate analysis and design.
Applied biophysics for drug discovery
It is a guide to new techniques and approaches to identifying and characterizing small molecules in early drug discovery. Biophysical methods are reasserting their utility in drug discovery and through a combination of the rise of fragment-based drug discovery and an increased focus on more nuanced characterisation of small molecule binding, these methods are playing an increasing role in discovery campaigns.
Applied and computational mathematics for digital environments
Contains the 11 papers that were accepted and published in the Special Issue “Applied and Computational Mathematics for Digital Environments” of the MDPI Mathematics journal. The topics of interest include, among others, scientific research, applied tasks, and problems in the following areas: The construction of mathematical and information models of intelligent computer systems for monitoring and controlling the parameters of digital environments; The development of intelligent optimization algorithms that search for optimal parameter values of mathematical and information models in digital environments; Software and mathematical technologies in the implementation of intelligent monitoring and computer control of the parameters of digital environments; The development and application of mathematical and information models, machine learning methods, and artificial intelligence for the analysis and processing of big data in digital environments.
