الصفحة 57
الصفحة 57
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Democracy in an Age of Globalisation

In Democracy in an Age of Globalisation, Otfried Höffe develops a comprehensive analysis of the demands, which the process of globalization exerts on the political organisations of humanity. The author starts from a diagnosis of the process of globalisation and frees its concept from its economistic narrowing: Globalisation is a comprehensive process which puts new strains on the economies and political systems of the world, the cultural and social structures of peoples. The scope of its challenges demands solutions, which transcend the powers of the classical nation-state. The question central to the book can be formulated as follows: "How can the social, moral and legal achievements of the nation-state be retained while its structure is reshaped to satisfy the requirements of a globalised world?"

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Deep learning architecture and application

As one of the fastest-growing topics in machine learning, deep learning algorithms have achieved unprecedented success in recent years. Novel paradigms (such as contrastive learning and few-shot learning) in deep learning and rising neural network architectures (e.g., transformer and masked autoencoder) are dramatically changing the field of data-driven algorithms. More importantly, deep learning models are redefining the next generation of industrial applications spanning image recognition, speech processing, language translation, healthcare, and other sciences. For example, recent advances in deep representation learning are allowing us to learn about protein 3D structures, which sheds new light on fundamental medicine and biology along with potentially bringing in billions of dollars (e.g., in the pharmaceutical market).

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Deep eutectic polvents : Synthesis, properties, and applications

Deep Eutectic Solvents contains a comprehensive review of the use of deep eutectic solvents (DESs) as an environmentally benign alternative reaction media for chemical transformations and processes. The contributors cover a range of topics including synthesis, structure, properties, toxicity and biodegradability of DESs. The book also explores myriad applications in various disciplines, such as organic synthesis and (bio)catalysis, electrochemistry, extraction, analytical chemistry, polymerizations, (nano)materials preparation, biomass processing, and gas adsorption.

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Decoupling Control

Decoupling or non-interactive control has attracted considerable research attention since the 1960s when control engineers started to deal with multivariable systems. The theory and design techniques for decoupling control have now, more or less matured for linear time-invariant systems, yet there is no single book which focuses on such an important topic. The present monograph fills this gap by presenting a fairly comprehensive and detailed treatment of decoupling theory and relevant design methods. Decoupling control under the framework of polynomial transfer function and frequency response settings, is included as well as the disturbance decoupling problem. The emphasis here is on special or relatively new compensation schemes such as (true and virtual) feedforward control and disturbance observers, rather than use of feedback control alone. The results are presented in a self-contained way and only the knowledge of basic linear systems theory is assumed of the reader.

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Decoherence and the Quantum-To-Classical Transition

This detailed but accessible text describes the concepts, formalism, interpretation, and experimental observation of decoherence and explains how decoherence is responsible for the emergence, from the realm of quantum mechanics, of the classical world of our experience.

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Declarative agent languages and technologiesV ; 5th International Workshop, DALT 2007, Honolulu, HI, USA, May 14, 2007, Revised Selected and Invited Papers

This book constitutes the thoroughly refereed post-workshop proceedings of the 5th International Workshop on Declarative Agent Languages and Technologies, DALT 2007, held in Honolulu, USA, in 2007.

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Decision science for future earth : Theory and practice

Provides a theoretical framework and case studies on decision science for regional sustainability by integrating the natural and social sciences. The cases discussed include solution-oriented transdisciplinary studies on the environment, disasters, health, governance and human cooperation.

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Decarbonizing Freight Transport: Acceptance and Policy Implications

This Book analyzes the acceptance of sustainable freight transport and suggests a new framework for policy measures to decarbonize freight transport. Despite intense political endeavors, the environmental performance of the transport system has not improved in the previous years. It seems that the existing measures are not sufficient to motivate transport users to implement sustainable freight transport strategies. The case of three different strategies for sustainable freight transport is studied: horizontal collaboration in a Physical Internet network, multimodal freight transport and liquefied natural gas (LNG) as alternative truck fuel.

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Debating Transformations of National Citizenship

Deconomic, social and political change. It focuses on the emergence of global markets where citizenship is for sale and on how new reproduction technologies impact citizenship by descent. It also discusses the return of banishment through denationalisation of terrorist suspects, and the impact of digital technologies, such as blockchain, on the future of democratic citizenship. The book provides a wide range of views on these issues from legal scholars, political scientists, and political practitioners. It is structured as a series of four conversations in which authors respond to each other. This exchange of arguments provides unique depth to current debates about the future of citizenship.

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David Paul von Hansemann : Contributions to Oncology : Context, Comments and Translations

Presents translations of all the relevant German texts, and analyses the background and context of Hansemann's theories as well as the reasons why he was almost completely forgotten. It shows that some of Hansemann’s ideas may still be relevant to cancer research today, and that he deserves to be remembered in relation to cancer as Vordenker unter den führenden Denkern seiner Zeit - The foremost of the leading thinkers of his time.

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Data-Driven Policy Impact Evaluation : How Access to Microdata is Transforming Policy Design

Provides statistical tools for evaluating the effects of public policies advocated by governments and public institutions. Experts from academia, national statistics offices and various research centers present modern econometric methods for an efficient data-driven policy evaluation and monitoring, assess the causal effects of policy measures and report on best practices of successful data management and usage. Topics include data confidentiality, data linkage, and national practices in policy areas such as public health, education and employment. It offers scholars as well as practitioners from public administrations, consultancy firms and nongovernmental organizations insights into counterfactual impact evaluation methods and the potential of data-based policy and program evaluation.

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Data-Driven 3D Facial Animation

Data-Driven 3D Facial Animation: systematically describes the emerging data-driven techniques developed over the last ten years or so. Although data-driven 3D facial animation is used more and more in animation practice, to date there have been very few books that specifically address the techniques involved. Comprehensive in scope, the book covers not only traditional lip-sync (speech animation), but also expressive facial motion, facial gestures, facial modeling, editing and sketching, and facial animation transferring. It provides an up-to-date reference source for academic research and for professionals working in the facial animation field.

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Database systems for advanced applications ; Vol. 3453 ; 10th international conference, DASFAA 2005, Beijing, China, April 17-20, 2005, Proceedings

Data Stream Mining and Resource Adaptive Computation.- Purpose Based Access Control for Privacy Protection in Database Systems.- Complex Networks and Network Data Mining.- Bioinformatics.- Indexing DNA Sequences Using q-Grams.- PADS: Protein Structure Alignment Using Directional Shape Signatures.- LinkageTracker: A Discriminative Pattern Tracking Approach to Linkage Disequilibrium Mapping.- Watermarking and Encryption.- Query Optimization in Encrypted Database Systems.- Watermarking Spatial Trajectory Database.- Effective Approaches for Watermarking XML Data.- XML Query Processing.- A Unifying Framework for Merging and Evaluating XML Information.- Efficient Evaluation of Partial Match Queries for XML Documents Using Information Retrieval Techniques.- PathStack: A Holistic Path Join Algorithm for Path Query with Not-Predicates on XML Data.- XML Coding and Metadata Management.- An Improved Prefix Labeling Scheme: A Binary String Approach for Dynamic Ordered XML.- Efficiently Coding and Indexing XML Document.- XQuery-Based TV-Anytime Metadata Management.- Data Mining.- Effective Database Transformation and Efficient Support Computation for Mining Sequential Patterns.

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Database and XML Technologies ; Vol. 4156 ; 4th International XML Database Symposium, XSym 2006, Seoul, Korea, September 10-11, 2006, Proceedings

The theme of the XML Database Symposium (XSym) is the convergence of database technology with XML technology. Since the first International XML Symposium in 2003, XSym has continued to provide a forum for academics, practitioners, users and vendors to discuss the use of and synergy between advanced XML technologies. XSym 2006 received 32 full paper submissions. Each submitted paper underwent a rigorous review by independent referees. These proceedings represent a collection of eight excellent research papers. Their focus is on building XML repositories and covers the following topics: XML query processing, caching, indexing and navigation support, structural matching, temporal XML, and XML updates.

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Data science, AI, and machine learning in drug development

The confluence of big data, AI, and machine learning has led to a paradigm shift in how innovative medicines are developed and healthcare delivered. To fully capitalize on these technological advances, it is essential to systematically harness data from diverse sources and leverage digital technologies and advanced analytics to enable data-driven decisions. Data science stands at a unique moment of opportunity to lead such a transformative change. Intended to be a single source of information, Data Science, AI, and Machine Learning in Drug Research and Development covers a wide range of topics on the changing landscape of drug R&D, emerging applications of big data, AI and machine learning in drug development, and the build of robust data science organizations to drive biopharmaceutical digital transformations

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Data science on the Google cloud platform : Implementing end-to-end real-time data pipelines : From ingest to machine learning

Learn how easy it is to apply sophisticated statistical and machine learning methods to real-world problems when you build using Google Cloud Platform (GCP). This hands-on guide shows data engineers and data scientists how to implement an end-to-end data pipeline with cloud native tools on GCP. You'll work through a sample business decision by employing a variety of data science approaches. Follow along by building a data pipeline in your own project on GCP, and discover how to solve data science problems in a transformative and more collaborative way. Employ best practices in building highly scalable data and ML pipelines on Google Cloud Automate and schedule data ingest using Cloud Run Create and populate a dashboard in Data Studio Build a real-time analytics pipeline using Pub/Sub, Dataflow, and BigQuery Conduct interactive data exploration with BigQuery Create a Bayesian model with Spark on Cloud Dataproc Forecast time series and do anomaly detection with BigQuery ML Aggregate within time windows with Dataflow Train explainable machine learning models with Vertex AI Operationalize ML with Vertex AI Pipelines

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Data science in theory and practice : Techniques for big data analytics and complex data sets

Delivers a comprehensive treatment of the mathematical and statistical models useful for analyzing data sets arising in various disciplines, like banking, finance, health care, bioinformatics, security, education, and social services. Written in five parts, the book examines some of the most commonly used and fundamental mathematical and statistical concepts that form the basis of data science. The authors go on to analyze various data transformation techniques useful for extracting information from raw data, long memory behavior, and predictive modeling. Readers will also learn from topics like: Analyses of foundational theoretical subjects, including the history of data science, matrix algebra and random vectors, and multivariate analysis A comprehensive examination of time series forecasting, including the different components of time series and transformations to achieve stationarity Introductions to both the R and Python programming languages, including basic data types and sample manipulations for both languages An exploration of algorithms, including how to write one and how to perform an asymptotic analysis A comprehensive discussion of several techniques for analyzing and predicting complex data sets

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Data Science for Civil Engineering : A Beginner's Guide

Explains use of data science-based techniques for modeling and providing optimal solutions to complex problems in civil engineering. It discusses civil engineering problems like air, water and land pollution, climate crisis, transportation infrastructures, traffic and travel modes, mobility services, and so forth. Divided into two sections, the first one deals with the basics of data science and essential mathematics while the second section covers pertinent applications in structural and environmental engineering, construction management, and transportation.

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Data rights in transition

Maps the development of data rights that formed and reformed in response to the socio-technical transformations of the postwar twentieth century. The authors situate these rights, with their early pragmatic emphasis on fair information processing, as different from and less symbolically powerful than utopian human rights of older centuries

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Data management in a connected world : Essays dedicated to Hartmut Wedekind on the occasion of his 70th birthday

Data management systems play the most crucial role in building large application s- tems. Since modern applications are no longer single monolithic software blocks but highly flexible and configurable collections of cooperative services, the data mana- ment layer also has to adapt to these new requirements. Therefore, within recent years, data management systems have faced a tremendous shift from the central management of individual records in a transactional way to a platform for data integration, fede- tion, search services, and data analysis. This book addresses these new issues in the area of data management from multiple perspectives, in the form of individual contributions, and it outlines future challenges in the context of data management.

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