Advances in Applications of Data Driven Computing

This book aims to foster machine and deep learning approaches to data-driven applications, in which data governs the behaviour of applications.

Advances in Applications of Data Driven Computing


Advances in Computational Plasticity

It is important to frame Data-Driven Computing within the context of past and present efforts to automate and ... There has been extensive previous work focusing on the application of Data Science and Analytics to material data sets.

Advances in Computational Plasticity

This book brings together some 20 chapters on state-of-the-art research in the broad field of computational plasticity with applications in civil and mechanical engineering, metal forming processes, geomechanics, nonlinear structural analysis, composites, biomechanics and multi-scale analysis of materials, among others. The chapters are written by world leaders in the different fields of computational plasticity.

Recent Advances on Soft Computing and Data Mining

This book provides an introduction to data science and offers a practical overview of the concepts and techniques that readers need to get the most out of their large-scale data mining projects and research studies.

Recent Advances on Soft Computing and Data Mining

This book provides an introduction to data science and offers a practical overview of the concepts and techniques that readers need to get the most out of their large-scale data mining projects and research studies. It discusses data-analytical thinking, which is essential to extract useful knowledge and obtain commercial value from the data. Also known as data-driven science, soft computing and data mining disciplines cover a broad interdisciplinary range of scientific methods and processes. The book provides readers with sufficient knowledge to tackle a wide range of issues in complex systems, bringing together the scopes that integrate soft computing and data mining in various combinations of applications and practices, since to thrive in these data-driven ecosystems, researchers, data analysts and practitioners must understand the design choice and options of these approaches. This book helps readers to solve complex benchmark problems and to better appreciate the concepts, tools and techniques used.

Applications of Computational Intelligence in Data Driven Trading

... the new paradigm of Data-Driven trading and the application of Computational Intelligence techniques to implement it. ... within our culture that is driven by the groundbreaking technological achievements of the last decade, ...

Applications of Computational Intelligence in Data Driven Trading

“Life on earth is filled with many mysteries, but perhaps the most challenging of these is the nature of Intelligence.” – Prof. Terrence J. Sejnowski, Computational Neurobiologist The main objective of this book is to create awareness about both the promises and the formidable challenges that the era of Data-Driven Decision-Making and Machine Learning are confronted with, and especially about how these new developments may influence the future of the financial industry. The subject of Financial Machine Learning has attracted a lot of interest recently, specifically because it represents one of the most challenging problem spaces for the applicability of Machine Learning. The author has used a novel approach to introduce the reader to this topic: The first half of the book is a readable and coherent introduction to two modern topics that are not generally considered together: the data-driven paradigm and Computational Intelligence. The second half of the book illustrates a set of Case Studies that are contemporarily relevant to quantitative trading practitioners who are dealing with problems such as trade execution optimization, price dynamics forecast, portfolio management, market making, derivatives valuation, risk, and compliance. The main purpose of this book is pedagogical in nature, and it is specifically aimed at defining an adequate level of engineering and scientific clarity when it comes to the usage of the term “Artificial Intelligence,” especially as it relates to the financial industry. The message conveyed by this book is one of confidence in the possibilities offered by this new era of Data-Intensive Computation. This message is not grounded on the current hype surrounding the latest technologies, but on a deep analysis of their effectiveness and also on the author’s two decades of professional experience as a technologist, quant and academic.

Computational Science ICCS 2009

Data-driven computational science is ripe for multidisciplinary research to build applications, algorithms, measurementprocesses ... The advances that will result, including enhanced repositories of software components and applications, ...

Computational Science     ICCS 2009


Data Driven Engineering Design

Cloud-based design and manufacturing: A new paradigm in digital manufacturing and design innovation. Computer-Aided Design, 59, 1–14. 5. Suh, H. P. (2001). Axiomatic design: Advances and applications MIT-Pappalardo series in mechanical ...

Data Driven Engineering Design

This book addresses the emerging paradigm of data-driven engineering design. In the big-data era, data is becoming a strategic asset for global manufacturers. This book shows how the power of data can be leveraged to drive the engineering design process, in particular, the early-stage design. Based on novel combinations of standing design methodology and the emerging data science, the book presents a collection of theoretically sound and practically viable design frameworks, which are intended to address a variety of critical design activities including conceptual design, complexity management, smart customization, smart product design, product service integration, and so forth. In addition, it includes a number of detailed case studies to showcase the application of data-driven engineering design. The book concludes with a set of promising research questions that warrant further investigation. Given its scope, the book will appeal to a broad readership, including postgraduate students, researchers, lecturers, and practitioners in the field of engineering design.

Computational Science ICCS 2005

Recent advances in Dynamic Data Driven Application Systems (DDDAS) facilitated by the present level of computational technologies, as well as advances in data-driven modeling and simulation, impose the need for a critical evaluation of ...

Computational Science    ICCS 2005

The three-volume set LNCS 3514-3516 constitutes the refereed proceedings of the 5th International Conference on Computational Science, ICCS 2005, held in Atlanta, GA, USA in May 2005. The 464 papers presented were carefully reviewed and selected from a total of 834 submissions for the main conference and its 21 topical workshops. The papers span the whole range of computational science, ranging from numerical methods, algorithms, and computational kernels to programming environments, grids, networking, and tools. These fundamental contributions dealing with computer science methodologies and techniques are complemented by papers discussing computational applications and needs in virtually all scientific disciplines applying advanced computational methods and tools to achieve new discoveries with greater accuracy and speed.

Data Driven Computational Neuroscience

Markov blanket-based approach for learning multi-dimensional Bayesian network classifiers: An application to predict the European ... Highperformance computing in neuroscience for data-driven discovery, integration, and dissemination.

Data Driven Computational Neuroscience

Data-driven computational neuroscience facilitates the transformation of data into insights into the structure and functions of the brain. This introduction for researchers and graduate students is the first in-depth, comprehensive treatment of statistical and machine learning methods for neuroscience. The methods are demonstrated through case studies of real problems to empower readers to build their own solutions. The book covers a wide variety of methods, including supervised classification with non-probabilistic models (nearest-neighbors, classification trees, rule induction, artificial neural networks and support vector machines) and probabilistic models (discriminant analysis, logistic regression and Bayesian network classifiers), meta-classifiers, multi-dimensional classifiers and feature subset selection methods. Other parts of the book are devoted to association discovery with probabilistic graphical models (Bayesian networks and Markov networks) and spatial statistics with point processes (complete spatial randomness and cluster, regular and Gibbs processes). Cellular, structural, functional, medical and behavioral neuroscience levels are considered.

Recent Advances on Soft Computing and Data Mining

This book provides an introduction to data science and offers a practical overview of the concepts and techniques that readers need to get the most out of their large-scale data mining projects and research studies.

Recent Advances on Soft Computing and Data Mining

This book provides an introduction to data science and offers a practical overview of the concepts and techniques that readers need to get the most out of their large-scale data mining projects and research studies. It discusses data-analytical thinking, which is essential to extract useful knowledge and obtain commercial value from the data. Also known as data-driven science, soft computing and data mining disciplines cover a broad interdisciplinary range of scientific methods and processes. The book provides readers with sufficient knowledge to tackle a wide range of issues in complex systems, bringing together the scopes that integrate soft computing and data mining in various combinations of applications and practices, since to thrive in these data-driven ecosystems, researchers, data analysts and practitioners must understand the design choice and options of these approaches. This book helps readers to solve complex benchmark problems and to better appreciate the concepts, tools and techniques used.

Advances in Chinese Computer Science

J. Darlington , P. Henderson and D. A. Turner , Functional Programming and its Applications ( Cambridge University Press , 1982 ) . 15. ... Data - driven and Demand - driven Computer Architecture ” , Computing Surveys , Vol . 14 No.

Advances in Chinese Computer Science

There has been significant progress in certain areas of software engineering in China during the past five years. This volume is the first in a series of reports on outstanding results by Chinese computer scientists. It consists of twelve papers contributed by leading computer scientists in China. This book is a must for all professionals engaged in software engineering research.

Advances in Computer Systems Architecture

It is capable to virtualize computing resources by partitioning an application into computation threads which are then sequentially mapped and executed ... X.P. Ling and H. Amano: WASMII: a Data Driven Computer on a Virtual Hardware.

Advances in Computer Systems Architecture

This book constitutes the refereed proceedings of the 8th Asia-Pacific Computer Systems Architecture Conference, ACSAC 2003, held in Aizu-Wakamatsu, Japan in September 2003. The 23 revised full papers presented together with 8 invited papers were carefully reviewed and selected from 30 submissions. The papers are organized in topical sections on processor architectures and innovative microarchitectures, parallel computer architectures and computation models, reconfigurable architectures, computer arithmetic, cache and memory architectures, and interconnection networks and network interfaces.

Advances In Chinese Computer Science Vol 1

J. Darlington, P. Henderson and D. A. Turner, Functional Programming and its Applications (Cambridge University Press, 1982). ... "Data-driven and Demand-driven Computer Architecture", Computing Surveys, Vol. 14 No. 1 (March, 1982).

Advances In Chinese Computer Science  Vol 1

There has been significant progress in certain areas of software engineering in China during the past five years. This volume is the first in a series of reports on outstanding results by Chinese computer scientists. It consists of twelve papers contributed by leading computer scientists in China. This book is a must for all professionals engaged in software engineering research.

Computational Science ICCS 2008

Several research thrusts in which advances should significantly enhance the ability of data-driven computational science to bring its tremendous benefits to a wide array of applications.

Computational Science     ICCS 2008

The three-volume set LNCS 5101-5103 constitutes the refereed proceedings of the 8th International Conference on Computational Science, ICCS 2008, held in Krakow, Poland in June 2008. The 167 revised papers of the main conference track presented together with the abstracts of 7 keynote talks and the 100 revised papers from 14 workshops were carefully reviewed and selected for inclusion in the three volumes. The main conference track was divided into approximately 20 parallel sessions addressing topics such as e-science applications and systems, scheduling and load balancing, software services and tools, new hardware and its applications, computer networks, simulation of complex systems, image processing and visualization, optimization techniques, numerical linear algebra, and numerical algorithms. The second volume contains workshop papers related to various computational research areas, e.g.: computer graphics and geometric modeling, simulation of multiphysics multiscale systems, computational chemistry and its applications, computational finance and business intelligence, physical, biological and social networks, geocomputation, and teaching computational science. The third volume is mostly related to computer science topics such as bioinformatics' challenges to computer science, tools for program development and analysis in computational science, software engineering for large-scale computing, collaborative and cooperative environments, applications of workflows in computational science, as well as intelligent agents and evolvable systems.

Recent Advances in Technology Research and Education

Further, a machine learning and intelligent optimization application, as an effective platform for developing a novel data-driven computational toolbox for materials design is proposed. The proposed platform is a simple yet powerful ...

Recent Advances in Technology Research and Education

This book presents selected contributions to the 16th International Conference on Global Research and Education Inter-Academia 2017 hosted by Alexandru Ioan Cuza University of Iași, Romania from 25 to 28 September 2017. It is the third volume in the series, following the editions from 2015 and 2016. Fundamental and applied research in natural sciences have led to crucial developments in the ongoing 4th global industrial revolution, in the course of which information technology has become deeply embedded in industrial management, research and innovation – and just as deeply in education and everyday life. Materials science and nanotechnology, plasma and solid state physics, photonics, electrical and electronic engineering, robotics and metrology, signal processing, e-learning, intelligent and soft computing have long since been central research priorities for the Inter-Academia Community (I-AC) – a body comprising 14 universities and research institutes from Japan and Central/East-European countries that agreed, in 2002, to coordinate their research and education programs so as to better address today’s challenges. The book is intended for use in academic, government, and industrial R&D departments as a reference tool in research and technology education. The 42 peer-reviewed papers were written by more than 119 leading scientists from 14 countries, most of them affiliated to the I-AC.

Advances on Computational Intelligence in Energy

Most of the emerging applications, data-driven models and techniques with the capability of operating at large scales are not yet widely known [12]. In real-time systems, the amount of energy is increasing; thus, the application of big ...

Advances on Computational Intelligence in Energy

Addressing the applications of computational intelligence algorithms in energy, this book presents a systematic procedure that illustrates the practical steps required for applying bio-inspired, meta-heuristic algorithms in energy, such as the prediction of oil consumption and other energy products. Contributions include research findings, projects, surveying work and industrial experiences that describe significant advances in the applications of computational intelligence algorithms in energy. For easy understanding, the text provides practical simulation results, convergence and learning curves as well as illustrations and tables. Providing a valuable resource for undergraduate and postgraduate students alike, it is also intended for researchers in the fields of computational intelligence and energy.

Advances in Computers

[5] http://press.xilinx.com/2016-10-17-Baidu-Adopts-Xilinx-to-Accelerate-MachineLearning-Applications-in-the-Data-Center. ... [12] P.C. Treleaven, D.R. Brownbridge, R.P. Hopkins, Data-driven and demand-driven computer architecute, ...

Advances in Computers

Advances in Computers, Volume 106 is the latest volume in the series, which has been published since 1960. This update presents innovations in computer hardware, software, theory, design and applications, with new chapters in this volume including sections on A New Course on R&D Project Management in Computer Science and Engineering: Subjects Taught, Rationales Behind, and Lessons Learned, Advances in Dataflow Systems, Adaptation and Evaluation of the Simplex Algorithm for a Data-Flow Architecture, and Simple Operations in Memory to Reduce Data Movement. In addition, this series provides contributors with a medium to explore their subjects in greater depth than journal articles usually allow. Provides in-depth surveys and tutorials on new computer technology Presents well-known authors and researchers in the field Contains extensive bibliographies with most chapters Includes volumes that are devoted to single themes or subfields of computer science

Extracellular Matrix Proteins Advances in Research and Application 2013 Edition

... approach to its understanding and control, integratively tuning cell speed and directional persistence to achieve maximal mean free path (MFP) of migration. This approach employs data-driven computational 211 CHAPTER 1 COLLAGEN.

Extracellular Matrix Proteins   Advances in Research and Application  2013 Edition

Extracellular Matrix Proteins—Advances in Research and Application: 2013 Edition is a ScholarlyEditions™ book that delivers timely, authoritative, and comprehensive information about Tenascin. The editors have built Extracellular Matrix Proteins—Advances in Research and Application: 2013 Edition on the vast information databases of ScholarlyNews.™ You can expect the information about Tenascin in this book to be deeper than what you can access anywhere else, as well as consistently reliable, authoritative, informed, and relevant. The content of Extracellular Matrix Proteins—Advances in Research and Application: 2013 Edition has been produced by the world’s leading scientists, engineers, analysts, research institutions, and companies. All of the content is from peer-reviewed sources, and all of it is written, assembled, and edited by the editors at ScholarlyEditions™ and available exclusively from us. You now have a source you can cite with authority, confidence, and credibility. More information is available at http://www.ScholarlyEditions.com/.

Computational Science ICCS 2006

The dynamic data driven paradigm is exploited to promote application advances, application measurement systems and methods, mathematical and statistical algorithms and finally systems software infrastructure relevant to this effort.

Computational Science   ICCS 2006

This is Volume III of the four-volume set LNCS 3991-3994 constituting the refereed proceedings of the 6th International Conference on Computational Science, ICCS 2006. The 98 revised full papers and 29 revised poster papers of the main track presented together with 500 accepted workshop papers were carefully reviewed and selected for inclusion in the four volumes. The coverage spans the whole range of computational science.

Proceedings of 5th International Conference on the Industry 4 0 Model for Advanced Manufacturing

Note that process models should be used in both cloud and edge-based process monitoring applications. With the recent rise of datadriven models and advancements in computational power, process models can easily be implemented in the ...

Proceedings of 5th International Conference on the Industry 4 0 Model for Advanced Manufacturing

This book gathers the proceedings of the 5th International Conference on the Industry 4.0 Model for Advanced Manufacturing (AMP 2020), held in Belgrade, Serbia, on 1–4 June 2020. The event marks the latest in a series of high-level conferences that bring together experts from academia and industry to exchange knowledge, ideas, experiences, research findings, and information in the field of manufacturing. The book addresses a wide range of topics, including: design of smart and intelligent products, developments in CAD/CAM technologies, rapid prototyping and reverse engineering, multistage manufacturing processes, manufacturing automation in the Industry 4.0 model, cloud-based products, and cyber-physical and reconfigurable manufacturing systems. By providing updates on key issues and highlighting recent advances in manufacturing engineering and technologies, the book supports the transfer of vital knowledge to the next generation of academics and practitioners. Further, it will appeal to anyone working or conducting research in this rapidly evolving field.