Автор: Daniel J. Velleman Название: How to Prove It : A Structured Approach ISBN: 1108439535 ISBN-13(EAN): 9781108439534 Издательство: Cambridge Academ Рейтинг: Цена: 5861.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Proofs play a central role in advanced mathematics and theoretical computer science, and this bestselling text`s third edition will help students transition from solving problems to proving theorems by teaching them the techniques needed to read and write proofs, with a new chapter on number theory and over 150 new exercises.
Автор: Trevor Hastie; Robert Tibshirani; Jerome Friedman Название: The Elements of Statistical Learning ISBN: 0387848576 ISBN-13(EAN): 9780387848570 Издательство: Springer Рейтинг: Цена: 10061.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This major new edition features many topics not covered in the original, including graphical models, random forests, and ensemble methods. As before, it covers the conceptual framework for statistical data in our rapidly expanding computerized world.
Автор: Bradley Efron , Trevor Hastie Название: Computer Age Statistical Inference, Student Edition ISBN: 1108823416 ISBN-13(EAN): 9781108823418 Издательство: Cambridge Academ Рейтинг: Цена: 5069.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Computing power has revolutionized the theory and practice of statistical inference. Now in paperback, and fortified with 130 class-tested exercises, this book explains modern statistical thinking from classical theories to state-of-the-art prediction algorithms. Anyone who applies statistical methods to data will value this landmark text.
Автор: Velliangiri Sarveshwaran, Joy Iong-Zong Chen, Danilo Pelusi Название: Artificial intelligence and cyber security in industry 4.0 ISBN: 9819921147 ISBN-13(EAN): 9789819921140 Издательство: Springer Рейтинг: Цена: 6097.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book provides theoretical background and state-of-the-art findings in artificial intelligence and cybersecurity for industry 4.0 and helps in implementing AI-based cybersecurity applications. Machine learning-based security approaches are vulnerable to poison datasets which can be caused by a legitimate defender's misclassification or attackers aiming to evade detection by contaminating the training data set. There also exist gaps between the test environment and the real world. Therefore, it is critical to check the potentials and limitations of AI-based security technologies in terms of metrics such as security, performance, cost, time, and consider how to incorporate them into the real world by addressing the gaps appropriately. This book focuses on state-of-the-art findings from both academia and industry in big data security relevant sciences, technologies, and applications.
Описание: This book contains thirty-five selected papers presented at the International Conference on Evolutionary and Deterministic Methods for Design, Optimization and Control with Applications to Industrial and Societal Problems (EUROGEN 2017). This was one of the Thematic Conferences of the European Community on Computational Methods in Applied Sciences (ECCOMAS).Topics treated in the various chapters reflect the state of the art in theoretical and numerical methods and tools for optimization, and engineering design and societal applications. The volume focuses particularly on intelligent systems for multidisciplinary design optimization (mdo) problems based on multi-hybridized software, adjoint-based and one-shot methods, uncertainty quantification and optimization, multidisciplinary design optimization, applications of game theory to industrial optimization problems, applications in structural and civil engineering optimum design and surrogate models based optimization methods in aerodynamic design.
Описание: Social robots not only work with humans in collaborative workspaces - we meet them in shopping malls and even more personal settings like health and care. Especially for developments with a high societal impact like robots in health and care settings, the authors discuss not only technology, design and usage but also ethical aspects.
Автор: Rautaray Название: Data Science in Societal Applications ISBN: 9811951535 ISBN-13(EAN): 9789811951534 Издательство: Springer Рейтинг: Цена: 12196.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The book provides an insight into the practical applications and theoretical foundation of data science. The book discusses new ways of embracing agile approaches to various facets of data science, including machine learning and artificial intelligence, data mining, data visualization, and communication. The book includes contributions from academia and industry experts detailing the shortfalls of current tools and techniques used and generating the blueprint of the new technologies. The topics covered in the book range from theoretical and foundational research, platforms, methods, applications, and tools in data science. The chapters in the book add a social, geographical, and temporal dimension to data science research. The papers included are application-oriented that prepare and use data in discovery research. This book will provide researchers and practitioners with a detailed snapshot of current progress in data science. Moreover, it will stimulate new study, research, and the development of new applications.
Описание: This book provides an understanding of the evolution of digitization in our day to day life and how it has become a part of our social system. The obvious challenges faced during this process and how these challenges were overcome have been discussed. The discussions revolve around the solutions to these challenges by leveraging the use of various advanced technologies. The book mainly covers the use of these technologies in variety of areas such as smart cities, healthcare informatics, transportation automation, digital transformation of education. The book intends to be treated as a source to provide the systematic discussion to the bouquet of areas that are essential part of digitized societies. In light of this, the book accommodates theoretical, methodological, well-established, and validated empirical work dealing with various related topics.
Автор: Garcia Diaz Название: Confidential Computing ISBN: 9811930473 ISBN-13(EAN): 9789811930478 Издательство: Springer Рейтинг: Цена: 12196.00 р. Наличие на складе: Нет в наличии.
Описание: This book highlights the three pillars of data security, viz protecting data at rest, in transit, and in use. Protecting data at rest means using methods such as encryption or tokenization so that even if data is copied from a server or database, a thief cannot access the information. Protecting data in transit means making sure unauthorized parties cannot see information as it moves between servers and applications. There are well-established ways to provide both kinds of protection. Protecting data while in use, though, is especially tough because applications need to have data in the clear—not encrypted or otherwise protected—in order to compute. But that means malware can dump the contents of memory to steal information. It does not really matter if the data was encrypted on a server’s hard drive if it is stolen while exposed in memory. As computing moves to span multiple environments—from on-premise to public cloud to edge—organizations need protection controls that help safeguard sensitive IP and workload data wherever the data resides. Many organizations have declined to migrate some of their most sensitive applications to the cloud because of concerns about potential data exposure. Confidential computing makes it possible for different organizations to combine data sets for analysis without accessing each other’s data.
Novel strategies for data-driven evolutionary optimization
Machine learning using distance-based methods
Counting cells and predicting immunoscore using gradient boosted convolutional neural networks
Kubelka-Munk model and stochastic model comparison in skin physical parameter retrieval using neural networks
A combined approach of neural networks and graphical models in skin cancer inference using spectral imaging
Using wave propagation simulations and convolutional neural networks to retrieve thin coating's thickness from hyperspectral images
Predicting future overweight and obesity from childhood growth data: A case study
Variable selection under a value acquisition budget
Stochastic approximation by successive piecewise linearization
Non-convex robust low-rank matrix recovery
Neural network learning via successive piecewise linearization
Learning for scientific computing purposes
Computational intelligence in design of new nanomaterials
Modeling flow, reactive transport and geomechanics in porous media
Physics constrained machine learning for industrial applications
Parameter and type identification in partial differential equations using deep neural networks
Stability maximization for layered moving web with total mass constraint
Similarity solutions for condensation on a non-isothermal vertical plate
Enhanced topology optimization approach using moving morphable components coupled with NURBS curves
Combined model order reduction and artificial neural network for data assimilation and damage detection in structures
Towards the optimization of fuzzy pattern trees by abs - linearization
Support vector machines in clusterwise linear regression
A Second-order method with enriched hessian information for composite sparse optimization problems
Missing value imputation via nonsmooth optimization and clusterwise linear regression
Parsimonious neural networks
Nobody can stop advancing artificial intelligence (AI) where developing
Computational sciences, physics field theories and geometry
Mini-symposium on ethics in AI
Essentializing software engineering practices for ethically designing and developing artificial intelligence systems 30 Ethics is important, but how can we implement it? Survey on software developers' views on AI ethics
Industrial IoT capabilities in reducing the LCOE of offshore wind energy: A review
High-Performance data analysis with the Helmholtz Analytics Toolkit (HeAT)
Dynamic data-driven application systems based on tensor factorization: learning the physics of model evolution
Predicting customer experience
Puhti-AI: Finland's new AI supercomputer
Using Artificial Intelligence to Classify Textual Applications for Reporting Purposes Application of machine learning methods to error control of approximate solutions
Iterative data selection strategy in offline data-driven evolutionary multiobjective optimization
On surrogate management in interactive multiobjective building energy system design
A modified deep neural network for the rapid inversion of geo-physical resistivity measurements
Using agents for automatic meta-modelling algorithm selection in data-driven multiobjective optimization problems
Future cooperation between Computational Science and AI in Industrial and Societal Applications - challenges, impact and expectations?
Artificial Intelligence, Deep Lea
Автор: Garg Lalit, Basterrech Sebastian, Banerjee Chitresh Название: Artificial Intelligence in Healthcare ISBN: 9811662649 ISBN-13(EAN): 9789811662645 Издательство: Springer Рейтинг: Цена: 26711.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book highlights the analytics and optimization issues in healthcare systems, proposes new approaches, and presents applications of innovative approaches in real facilities. In the past few decades, there has been an exponential rise in the application of swarm intelligence techniques for solving complex and intricate problems arising in healthcare. The versatility of these techniques has made them a favorite among scientists and researchers working in diverse areas. The primary objective of this book is to bring forward thorough, in-depth, and well-focused developments of hybrid variants of swarm intelligence algorithms and their applications in healthcare systems.
Описание: This book offers concepts related to communication engineering principles to fight the current Covid situation, by developing contactless need-based solutions. COVID-19, a global pandemic makes us rethink how governments, organizations, and societies around the world can work with minimum or without physical contact. Technologies like artificial intelligence and big data are playing an essential role in responding to the COVID-19 pandemic. This book is a combination of chapters related to imaging and detective technologies used by the experts to fight the COVID-19 pandemic and a combination of interesting content covering the need of hour solutions generated through cutting edge technologies. In the absence of a proper medicine or vaccine, it is quite evident that nutrition plays an important role in the quick recovery of covid patients which must be very carefully planned with proper diagnostics. Data analysis and X-Ray/CT Image analysis by next-generation techniques like deep sensing, machine learning is interesting and useful for research and applied healthcare professionals. Research findings with a focus on diagnostics and reports generated through important data analysis in the book are quite useful and can be referred to by researchers and professionals working in the area of cutting-edge technologies against COVID 19.
ООО "Логосфера " Тел:+7(495) 980-12-10 www.logobook.ru
