- Table View
- List View
Analytical and Experimental Methods in Mechanical and Civil Engineering: Contributions of the 1st Olympiad in Engineering Science (OES 2023) (Structural Integrity #28)
by Gerhard Ersdal Jayantha P. Liyanage Dimitrios Pavlou Jose A. F. O. Correia Tiago Fazeres-Ferradosa Ove Tobias Gudmestad Sudath C. Siriwardane Hirpa Lemu Vidar Hansen Mona Wetrhus Minde Chandima Ratnayake Andreas Delimitis Idriss El-Thalji Nirosha Adasooriya Samindi Samarakoon Tor HemmingsenThis book publishes contributions of the 1st Olympiad in Engineering Science (OES 2023), an international congress and contest aiming to disseminate and evaluate the recent advances in Engineering Science. The book is divided in several parts. In 'Materials Science,' readers delve into nanostructural correlations in thermochromic VO2 thin films for smart windows, as well as microstructural observations of super duplex stainless steel. The 'Marine Technology' part explores riverbed scour, wave reflection, and innovative nature-based solutions for coastal protection. 'Additive Manufacturing and Welding Technology' delves into studies on carbon fiber-reinforced polymers and fatigue properties of 3D-printed specimens. 'Structural Integrity and Structural Health Monitoring' offers insights into offshore pipeline fatigue life prediction and risk-informed decision-making for existing structures. The 'Non-destructive Testing and Evaluation' part encompasses stress monitoring, rail profile measurement, and health-monitoring approaches for debonding diagnosis. 'Dynamics and Vibrations' ventures into investigations on combined viscous and Coulomb damped systems and seismic signal analysis for landslides. 'Materials Engineering' delves into strengthening reinforced concrete members and dynamic properties of carbon fiber-reinforced polymers. 'Building Materials and Concrete Structures' cover topics like minibar reinforced concrete, impact response of reinforced columns, and residual strength of cement-based composites. 'Electronic Sensors and Intelligent Systems' showcase simulations under high voltage transmission lines, synthesis of BaxSr(1-x)TiO3, and antenna catheter modeling. 'Asset Integrity' discusses analytical and experimental analyses of buckling in aluminum columns and I-beams, lateral-torsional buckling capacity, and modulation of fluid streams. Finally, 'Climate Change and Circular Economy' addresses climate-adaptive design, circular economy integration, and eco-innovative concrete applications with recycled materials. This book provides a comprehensive overview of cutting-edge research and advancements in mechanical and civil engineering, offering valuable insights for researchers, practitioners, and enthusiasts in the field.
Analytical and Experimental Modal Analysis
by Subodh V. ModakThis book covers the fundamentals and basic concepts of analytical and experimental approaches to modal analysis. In practice, the analytical approach based on lumped parameter and finite element models is widely used for modal analysis and simulation, and experimental modal analysis is widely used for modal identification and model validation. This book is inspired by this consideration and is written to give a complete picture of modal analysis. Features: Presents a systematic development of the relevant concepts and methods of the analytical and experimental modal analyses. Covers phase resonance testing and operational modal analysis. Provides the relevant signal processing concepts. Includes applications like model validation and updating, force identification and structural modification. Contains simulations, examples, and MATLAB® programs to enhance understanding. This book is aimed at senior undergraduates/graduates, researchers, and engineers from mechanical, aerospace, automotive, civil, and structural engineering disciplines.
Analytical and Hybrid Methods in the Theory of Slot-Hole Coupling of Electrodynamic Volumes
by Victor A. Katrich Yuriy M. Penkin Sergey L. BerdnikThis book provides the reader with the possibility of rapid study and application of methods of computer analysis of electrodynamic problems. The authors address the development of analytical methods to solve the problems of diffraction of waveguide electromagnetic waves on slot coupling holes. All the authors have experience in the field and the topics addressed are based on their original research results. The book is written in a laconic style and is visually accessible.
Analytical and Numerical Methods for Nonlinear Fluid Flow Problems in Porous Media
by Weiyao Zhu Jun Yao Wenchao LiuThis book investigates in detail the mathematical methods and computation methods in efficient solution of some open nonlinear seepage flow problems involved in engineering problems. Developed engineering technologies and some relevant practical field applications are also provided. The introduced open nonlinear problems include nonlinear quadratic pressure gradient term problem, compressible gas seepage flow problem and low-velocity non-Darcy seepage flow problem. Studies on these nonlinear seepage flow problems have attracted engineers and scientists from various disciplines, such as geo-energy engineering, civil and environmental engineering, fluid mechanics, applied mathematics and computation. In particular, the book systematically establishes a fundamental theory for a strongly nonlinear problem of low-velocity non-Darcy seepage flow from a new perspective of moving boundary, while emphasizing the usage of mathematical linearization transformation methods and computational methods into the analytical and numerical solution of the strongly nonlinear partial differential equations. Sufficient knowledge of mathematics is always introduced ahead of model solution to assist readers. And the procedure of strict formula deduction in the model solution process is provided in detail. High-solution figures and tables from model solution are rich in the book. Therefore, it is very helpful for the readers to master the nonlinear model solution methods and engineering technologies. The book is intended for upper undergraduate students and graduate students who are interested in engineering technology, fluid mechanics and applied mathematics, researchers and engineers working on geo-energy science and engineering and field applications.
Analytical and Numerical Methods for Vibration Analyses
by Jong-Shyong WuIllustrates theories and associated mathematical expressions with numerical examples using various methods, leading to exact solutions, more accurate results, and more computationally efficient techniques This book presents the derivations of the equations of motion for all structure foundations using either the continuous model or the discrete model. This mathematical display is a strong feature of the book as it helps to explain in full detail how calculations are reached and interpreted. In addition to the simple 'uniform' and 'straight' beams, the book introduces solution techniques for the complicated ‘non uniform’ beams (including linear or non-linear tapered beams), and curved beams. Most of the beams are analyzed by taking account of the effects of shear deformation and rotary inertia of the beams themselves as well as the eccentricities and mass moments of inertia of the attachments. Demonstrates approaches which dramatically cut CPU times to a fraction of conventional FEM Presents "mode shapes" in addition to natural frequencies, which are critical for designers Gives detailed derivations for continuous and discrete model equations of motions Summarizes the analytical and numerical methods for the natural frequencies, mode shapes, and time histories of straight structures rods shafts Euler beams strings Timoshenko beams membranes/thin plates Conical rods and shafts Tapered beams Curved beams Has applications for students taking courses including vibration mechanics, dynamics of structures, and finite element analyses of structures, the transfer matrix method, and Jacobi method This book is ideal for graduate students in mechanical, civil, marine, aeronautical engineering courses as well as advanced undergraduates with a background in General Physics, Calculus, and Mechanics of Material. The book is also a handy reference for researchers and professional engineers.
Analytical and Practical Aspects of Drug Testing in Hair (International Forensic Science and Investigation)
by Pascal KintzWritten by well-known, international authors, this comprehensive reference provides practical coverage of the best hair drug testing techniques and examines the drugs themselves. The authors review all new developments, the validation of analytical procedures, and the interpretation of data. Some of the applications discussed include doping, drug-facilitated crime investigating, workplace testing, and the granting of drivers' licenses. The authors describe specific drugs, such as opiates, cocaine, and cannabis, and discuss the different testing methods of them. The book also covers postmortem toxicology, pitfalls created by passive exposure, and testing for metals, including inductively coupled plasma spectrometry (ICP-MS), hair multielemen
Analytical and Preparative Separation Methods of Biomacromolecules
by Hassan Y. Aboul-EneinReports up-to-date research developments on purifying and isolation large organic molecules. The text provides information on high-performance liquid chromatography and capillary electrophoresis (CE) as tools for analyzing biomacromolecules and developing new biochemical and medicinal compounds. It applies biochemical separation technology to the study of macromolecules such as proteins, polysaccharides, nucleic acids and more.
Analytical and Stochastic Modelling Techniques and Applications: 23rd International Conference, ASMTA 2016, Cardiff, UK, August 24-26, 2016, Proceedings (Lecture Notes in Computer Science #9845)
by Sabine Wittevrongel Tuan Phung-DucThis book constitutes the refereed proceedings of the 23rd International Conference on Analytical and Stochastic Modelling Techniques and Applications, ASMTA 2016, held in Cardiff, UK, in August 2016. The 21 full papers presented in this book were carefully reviewed and selected from 30 submissions. The papers discuss the latest developments in analytical, numerical and simulation algorithms for stochastic systems, including Markov processes, queueing networks, stochastic Petri nets, process algebras, game theory, etc.
Analytical and Stochastic Modelling Techniques and Applications: 24th International Conference, ASMTA 2017, Newcastle-upon-Tyne, UK, July 10-11, 2017, Proceedings (Lecture Notes in Computer Science #10378)
by Nigel Thomas Matthew ForshawThis book constitutes the refereed proceedings of the 24th International Conference on Analytical and Stochastic Modelling Techniques and Applications, ASMTA 2017, held in Newcastle-upon-Tyne UK, in July 2017.The 14 full papers presented in this book were carefully reviewed and selected from 27 submissions. The scope of the conference is on following topics: analytical, numerical and simulation algorithms for stochastic systems, including Markov processes, queueing networks, stochastic Petri nets, process algebras, game theoretical models.
Analytical and Stochastic Modelling Techniques and Applications: 25th International Conference, ASMTA 2019, Moscow, Russia, October 21–25, 2019, Proceedings (Lecture Notes in Computer Science #12023)
by Marco Gribaudo Eduard Sopin Irina KochetkovaThis book constitutes the refereed proceedings of the 25th International Conference on Analytical and Stochastic Modelling Techniques and Applications, ASMTA 2019, held in Moscow, Russia, in October 2019. Methods of analytical and stochastic modelling are widely used in engineering to assess and design various complex systems, like computer and communication networks, and manufacturing systems. The 13 full papers presented in this book were carefully reviewed and selected from 22 submissions. The papers detail a diverse range of analysis techniques, including Markov processes, queueing theoretical results, reliability of stochastic systems, stochastic network calculus, and wide variety of applications.
Analytical and Stochastic Modelling Techniques and Applications: 28th International Conference, ASMTA 2024, Venice, Italy, June 14, 2024, Proceedings (Lecture Notes in Computer Science #14826)
by András Horváth Arnaud Devos Sabina RossiThis book constitutes the refereed proceedings of the 28th International Conference on Analytical and Stochastic Modelling Techniques and Applications, ASMTA 2024, held in Venice, Italy, on June 14, 2024. The 10 full papers presented were carefully reviewed and selected from 14 submissions. These papers covered a wide range of topics in analytical and stochastic modeling techniques and their applications.
Analytical or Semi-analytical Solutions of Functionally Graded Material Structures
by Zheng Zhong Guojun NieThis book provides a comprehensive introduction to the analysis of functionally graded materials and structures. Functionally graded materials (FGMs), in which the volume fractions of two or more constituent materials are designed to vary continuously as a function of position along certain direction(s), have been developed and studied over the past three decades. The major advantage of FGMs is that no distinct internal boundaries exist, and failures from interfacial stress concentrations developed in conventional components can be avoided. The gradual change of material properties can be tailored to different applications and working environments. As these materials’ range of application expands, new methodologies have to be developed to characterize them, and to design and analyze structural components made of them.Despite a number of existing papers on the analysis of functionally graded materials and structures, there is no single book that is devoted entirely to the analysis of functionally graded beams, plates and shells using different methods, e.g.,analytical or semi-analytical methods.Filling this gap in the literature, the book offers a valuable reference resource for senior undergraduates, graduate students, researchers, and engineers in this field. The results presented here can be used as a benchmark for checking the validity and accuracy of other numerical solutions. They can also be used directly in the design of functionally graded materials and structures.
Analyticity (New Problems of Philosophy)
by Cory Juhl Eric LoomisAnalyticity, or the 'analytic/synthetic' distinction is one of the most important and controversial problems in contemporary philosophy. It is also essential to understanding many developments in logic, philosophy of language, epistemology and metaphysics. In this outstanding introduction to analyticity Cory Juhl and Eric Loomis cover the following key topics: The origins of analyticity in the philosophy of Hume and Kant Carnap's arguments concerning analyticity in the early twentieth century Quine's famous objections to analyticity in his classic 'Two Dogmas of Empiricism' essay The relationship between analyticity and central issues in metaphysics, such as ontology The relationship between analyticity and epistemology Analyticity in the context of the current debates in philosophy, including mathematics and ontology Throughout the book the authors show how many philosophical controversies hinge on the problem of analyticity. Additional features include chapter summaries, annotated further reading and a glossary of technical terms making the book ideal to those coming to the problem for the first time.
Analyticity and Sparsity in Uncertainty Quantification for PDEs with Gaussian Random Field Inputs (Lecture Notes in Mathematics #2334)
by Christoph Schwab Dinh Dũng Van Kien Nguyen Jakob ZechThe present book develops the mathematical and numerical analysis of linear, elliptic and parabolic partial differential equations (PDEs) with coefficients whose logarithms are modelled as Gaussian random fields (GRFs), in polygonal and polyhedral physical domains. Both, forward and Bayesian inverse PDE problems subject to GRF priors are considered.Adopting a pathwise, affine-parametric representation of the GRFs, turns the random PDEs into equivalent, countably-parametric, deterministic PDEs, with nonuniform ellipticity constants. A detailed sparsity analysis of Wiener-Hermite polynomial chaos expansions of the corresponding parametric PDE solution families by analytic continuation into the complex domain is developed, in corner- and edge-weighted function spaces on the physical domain.The presented Algorithms and results are relevant for the mathematical analysis of many approximation methods for PDEs with GRF inputs, such as model order reduction, neural network and tensor-formatted surrogates of parametric solution families. They are expected to impact computational uncertainty quantification subject to GRF models of uncertainty in PDEs, and are of interest for researchers and graduate students in both, applied and computational mathematics, as well as in computational science and engineering.
Analytics And Modern Warfare: Dominance by the Numbers
by Michael TaillardThis book details very simply and for even the most novice of potential analysts not only how to perform analytics which describe what is happening, predict what is going to happen, and optimize responses, but also places these analytics in the context of proactive strategy development.
Analytics Enabled Decision Making
by Vinod Sharma Chandan Maheshkar Jeanne PouloseAnalytics is changing the landscape of businesses across sectors globally. This has led to the stimulation of interest of scholars and practitioners worldwide in this domain. The emergence of ‘big data’, has fanned the usages of machine learning techniques and the acceptance of ‘Analytics Enabled Decision Making’. This book provides a holistic theoretical perspective combined with the application of such theories by drawing on the experiences of industry professionals and academicians from around the world. The book discusses several paradigms including pattern mining, clustering, classification, and data analysis to name a few. The main objective of this book is to offer insight into the process of decision-making that is accelerated and made more precise with the help of analytics.
Analytics Engineering with SQL and dbt: Building Meaningful Data Models at Scale
by Rui Pedro Machado Helder RussaWith the shift from data warehouses to data lakes, data now lands in repositories before it's been transformed, enabling engineers to model raw data into clean, well-defined datasets. dbt (data build tool) helps you take data further. This practical book shows data analysts, data engineers, BI developers, and data scientists how to create a true self-service transformation platform through the use of dynamic SQL.Authors Rui Machado from Monstarlab and Hélder Russa from Jumia show you how to quickly deliver new data products by focusing more on value delivery and less on architectural and engineering aspects. If you know your business well and have the technical skills to model raw data into clean, well-defined datasets, you'll learn how to design and deliver data models without any technical influence.With this book, you'll learn:What dbt is and how a dbt project is structuredHow dbt fits into the data engineering and analytics worldsHow to collaborate on building data modelsThe main tools and architectures for building useful, functional data modelsHow to fit dbt into data warehousing and laking architectureHow to build tests for data transformations
Analytics Modeling in Reliability and Machine Learning and Its Applications (Springer Series in Reliability Engineering)
by Hoang PhamThis book presents novel research and application chapters on topics in reliability, statistics, and machine learning. It has an emphasis on analytical models and techniques and practical applications in reliability engineering, data science, manufacturing, health care, and industry using machine learning, AI, optimization, and other computational methods. Today, billions of people are connected to each other through their mobile devices. Data is being collected and analysed more than ever before. The era of big data through machine learning algorithms, statistical inference, and reliability computing in almost all applications has resulted in a dramatic shift in the past two decades. Data analytics in business, finance, and industry is vital. It helps organizations and business to achieve better results and fact-based decision-making in all aspects of life. The book offers a broad picture of current research on the analytics modeling and techniques and its applications in industry. Topics include: l Reliability modeling and methods. l Software reliability engineering. l Maintenance modeling and policies. l Statistical feature selection. l Big data modeling. l Machine learning: models and algorithms. l Data-driven models and decision-making methods. l Applications and case studies in business, health care, and industrial systems. Postgraduates, researchers, professors, scientists, engineers, and practitioners in reliability engineering and management, machine learning engineering, data science, operations research, industrial and systems engineering, statistics, computer science and engineering, mechanical engineering, and business analytics will find in this book state-of-the-art analytics, modeling and methods in reliability and machine learning.
Analytics Optimization with Columnstore Indexes in Microsoft SQL Server: Optimizing OLAP Workloads
by Edward PollackMeet the challenge of storing and accessing analytic data in SQL Server in a fast and performant manner. This book illustrates how columnstore indexes can provide an ideal solution for storing analytic data that leads to faster performing analytic queries and the ability to ask and answer business intelligence questions with alacrity. The book provides a complete walk through of columnstore indexing that encompasses an introduction, best practices, hands-on demonstrations, explanations of common mistakes, and presents a detailed architecture that is suitable for professionals of all skill levels. With little or no knowledge of columnstore indexing you can become proficient with columnstore indexes as used in SQL Server, and apply that knowledge in development, test, and production environments. This book serves as a comprehensive guide to the use of columnstore indexes and provides definitive guidelines. You will learn when columnstore indexes should be used, and the performance gains that you can expect. You will also become familiar with best practices around architecture, implementation, and maintenance. Finally, you will know the limitations and common pitfalls to be aware of and avoid.As analytic data can become quite large, the expense to manage it or migrate it can be high. This book shows that columnstore indexing represents an effective storage solution that saves time, money, and improves performance for any applications that use it. You will see that columnstore indexes are an effective performance solution that is included in all versions of SQL Server, with no additional costs or licensing required. What You Will LearnImplement columnstore indexes in SQL ServerKnow best practices for the use and maintenance of analytic data in SQL ServerUse metadata to fully understand the size and shape of data stored in columnstore indexesEmploy optimal ways to load, maintain, and delete data from large analytic tablesKnow how columnstore compression saves storage, memory, and timeUnderstand when a columnstore index should be used instead of a rowstore indexBe familiar with advanced features and analyticsWho This Book Is ForDatabase developers, administrators, and architects who are responsible for analytic data, especially for those working with very large data sets who are looking for new ways to achieve high performance in their queries, and those with immediate or future challenges to analytic data and query performance who want a methodical and effective solution
Analytics Stories: Using Data to Make Good Things Happen
by Wayne L. WinstonInform your own analyses by seeing how one of the best data analysts in the world approaches analytics problems Analytics Stories: How to Make Good Things Happen is a thoughtful, incisive, and entertaining exploration of the application of analytics to real-world problems and situations. Covering fields as diverse as sports, finance, politics, healthcare, and business, Analytics Stories bridges the gap between the oft inscrutable world of data analytics and the concrete problems it solves. Distinguished professor and author Wayne L. Winston answers questions like: Was Liverpool over Barcelona the greatest upset in sports history? Was Derek Jeter a great infielder What's wrong with the NFL QB rating? How did Madoff keep his fund going? Does a mutual fund’s past performance predict future performance? What caused the Crash of 2008? Can we predict where crimes are likely to occur? Is the lot of the American worker improving? How can analytics save the US Republic? The birth of evidence-based medicine: How did James Lind know citrus fruits cured scurvy? How can I objectively compare hospitals? How can we predict heart attacks in real time? How does a retail store know if you're pregnant? How can I use A/B testing to improve sales from my website? How can analytics help me write a hit song? Perfect for anyone with the word “analyst” in their job title, Analytics Stories illuminates the process of applying analytic principles to practical problems and highlights the potential pitfalls that await careless analysts.
Analytics and Big Data for Accountants (AICPA)
by Jim LindellAnalytics is a new force driving business. Tools have been created to measure program effects and return on investment, visualize data and business processes, and uncover the relationship between key performance indicators—many using the unprecedented amount of data now moving into organizations. In this course, you will discuss leading-edge topics in analytics and finance in a session that is packed with useful tips and practical guidance that you can apply immediately.
Analytics and Big Data for Accountants (AICPA)
by Jim LindellWhy is big data analytics one of the hottest business topics today? This book will help accountants and financial managers better understand big data and analytics, including its history and current trends. It dives into the platforms and operating tools that will help you measure program impacts and ROI, visualize data and business processes, and uncover the relationship between key performance indicators. Key topics covered include: Evidence-based techniques for finding or generating data, selecting key performance indicators, isolating program effects Relating data to return on investment, financial values, and executive decision making Data sources including surveys, interviews, customer satisfaction, engagement, and operational data Visualizing and presenting complex results
Analytics and Big Data: The Davenport Collection
by D. J. Patil Thomas H. Davenport Jinho Kim Jeanne G. Harris Robert MorisonThe Analytics and Big Data collection offers a “greatest hits” digital compilation of ideas from world-renowned thought leader Thomas Davenport, who helped popularize the terms analytics and big data in the workplace. An agile and prolific thinker, Davenport has written or coauthored more than a dozen bestselling books. Several of these titles are offered together for the first time in this curated digital bundle, including: Big Data at Work, Competing on Analytics, Analytics at Work, and Keeping Up with the Quants. The collection also includes Davenport’s popular Harvard Business Review articles, “Data Scientist: The Sexiest Job of the 21st Century” (2012) and “Analytics 3.0” (2013). Combined, these works cover all the bases on analytics and big data: what each term means; the ramifications of each from a technical, consumer, and management perspective; and where each can have the biggest impact on your business. Whether you’re an executive, a manager, or a student wanting to learn more, Analytics and Big Data is the most comprehensive collection you’ll find on the ever-growing phenomenon of digital data and analysis—and how you can make this rising business trend work for you. Named one of the ten “Masters of the New Economy” by CIO magazine, Thomas Davenport has helped hundreds of companies revitalize their management practices. He combines his interests in research, teaching, and business management as the President’s Distinguished Professor of Information Technology & Management at Babson College. Davenport has also taught at Harvard Business School, the University of Chicago, Dartmouth’s Tuck School of Business, and the University of Texas at Austin and has directed research centers at Accenture, McKinsey & Company, Ernst & Young, and CSC.
Analytics and Business Performance: Transforming the Ability to Compete on Analytics into a Lasting Competitive Advantage
by Thomas H. Davenport Jeanne G. HarrisThis chapter explores the links between the extensive use of analytics and business performance, describing how several highly successful companies have transformed their ability to compete analytically into a key point of differentiation and long-term competitive advantage. This chapter was originally published as Chapter 3 of "Competing on Analytics."
Analytics and Data Science: Advances in Research and Pedagogy (Annals of Information Systems #21)
by Ashish Gupta Lakshmi S. Iyer Amit V. Deokar Mary C. JonesThis book explores emerging research and pedagogy in analytics and data science that have become core to many businesses as they work to derive value from data. The chapters examine the role of analytics and data science to create, spread, develop and utilize analytics applications for practice. Selected chapters provide a good balance between discussing research advances and pedagogical tools in key topic areas in analytics and data science in a systematic manner. This book also focuses on several business applications of these emerging technologies in decision making, i. e. , business analytics. The chapters in Analytics and Data Science: Advances in Research and Pedagogy are written by leading academics and practitioners that participated at the Business Analytics Congress 2015. Applications of analytics and data science technologies in various domains are still evolving. For instance, the explosive growth in big data and social media analytics requires examination of the impact of these technologies and applications on business and society. As organizations in various sectors formulate their IT strategies and investments, it is imperative to understand how various analytics and data science approaches contribute to the improvements in organizational information processing and decision making. Recent advances in computational capacities coupled by improvements in areas such as data warehousing, big data, analytics, semantics, predictive and descriptive analytics, visualization, and real-time analytics have particularly strong implications on the growth of analytics and data science.