Bøger udgivet af now publishers Inc

Provides an overview of Efficiency and Productivity Analysis, a very important field of research and practice, spanning over and engaging with many disciplines, most prominently Economics (theoretical and applied), Statistics (and therefore Econometrics), Operations Research and Management Science.

Minimum-Distortion Embedding describes the theory behind and practical use of a cutting-edge artificial intelligence technique. Accompanied by an open-source software package, PyMDE, it illustrates applying these AI techniques in areas such as images, co- networks, demographics, genetics, and biology.

Surveys the stream developments in the regulation and standard setting that have set the requirements for companies' financial reporting in the US capital market. Attention is given to instances in which the SEC has either been in disagreement with the private-sector accounting standard setter, or where they have partnered in a solution.

Examines the evolution of the social purpose of the corporation. This development has taken place against the background of changing regulations and globalization. Consequently, international regulations, codes of conduct and standards have impinged upon corporate strategy.

Offers a detailed description of the successful technology transfer of an invention originating in intramural research within the US National Institutes of Health. The history of the commercialization of the invention is used to illustrate a new policy for the payment of royalties on the sales of biomedical products developed with public funding.

Provides evidence that over the period 2000 through 2018 nominal aggregate advertising spending in the US as a share of nominal GDP has been falling. The authors further show that nominal aggregate advertising spending has become more responsive to changes in real GDP and GDP price inflation.

Presents the case that electronic voting can improve accessibility, leading to some positive outcomes. The authors document the various problems with centralized electronic voting systems and show how the blockchain can potentially overcome these problems.

Provides an in-depth overview and practical examples of how robots can be deployed during a disaster. As such it should prove useful for roboticists, researchers in various fields related to robotics as well as industry professionals who are responsible for saving lives and mitigating societal impacts in times of disaster.

Introduces the latest trends and deep-learning-based techniques for multimedia forensics in both architectural and data-processing. Different techniques used to manipulate content are presented, followed by image and video forgery techniques. Deep learning methods for source identification and solutions for deepfake detection are covered.

Provides a review of technologies, techniques and systems for trusted, ethical, and secure AI in manufacturing. Topics covered include systems and technologies for industrial data reliability, responsible and transparent AI systems, human centred manufacturing systems, cyber-defence in AI systems, and simulated reality systems.

Questions the varied set of organisational forms collected under the label of 'collaborative' or 'sharing' economy - ranging from grassroots peer-to-peer solidarity initiatives to corporate owned platforms - from the perspective of what is known as the European social values: respect for human dignity and human rights.

Describes in detail the research on fault diagnosis, opacity analysis and enhancement, and cyber security analysis and enforcement, within suitable discrete event system modelling frameworks. In each case, the authors describe basic problem statements and key concepts, and then point out the key challenges in each research area.

Focuses on the inclusion of security in robotics from the earliest design phases onward and with a special focus on the cost-benefit tradeoff that can otherwise be an inhibitor for the fast development of affordable systems. The authors advocate for quantitative methods of security management and design.

Describes the use of principles of reinforcement learning (RL) to design feedback policies for continuous-time dynamical systems that combine features of adaptive control and optimal control. The authors give an insightful introduction to reinforcement learning techniques that can address various control problems.

Covers five areas related to the mining of user interests from social media: the foundations of social user interest modeling; techniques that have been adopted; evaluation methodologies and benchmark datasets; applications that have been taking advantage of user interest mining; and challenges, research questions, and opportunities.

Surveys two important components of modern information access: information retrieval (IR) and knowledge graphs (KGs). The authors provide an overview of the literature on KGs in the context of IR and the components required when building IR systems that leverage KGs.

Labour income risk is key to the welfare of most people and this risk is mainly insured 'within the firm' and by public institutions, rather than by financial markets. This book asks why such insurance is provided within the firm, and what determines its boundaries. It also explores the connection between risk sharing and firms' capital structure.

Presents a summary of challenges to deliver desired solutions and a presentation of efforts to be undertaken to ensure that US will continue to be a leader in robotics, both in terms of research innovation, adoption of the latest technology, and adoption of policy frameworks that ensure that the technology is utilized in a responsible fashion.

Provides an overview of existing work in explanation support for data-driven processes. The book classifies explainability requirements across three dimensions: the target of the explanation ('What'), the audience of the explanation ('Who'), and the purpose of the explanation ('Why').

Differential privacy is a promising approach to formalizing privacy - that is, for writing down what privacy means as a mathematical equation. This book serves as an overview of the state-of-the-art in techniques for differential privacy.

Reviews the academic literature on market outcomes, reporting practices and the political economy behind the global use of International Financial Reporting Standards. Starting with a conceptual discussion of expected benefits and costs, the authors explain why predictions on possible outcomes are ambiguous.

Presents a thorough review of the state of the art of recommender systems that leverage psychological constructs and theories to model and predict user behaviour and improve the recommendation process - so-called psychology-informed recommender systems.

Provides a thorough introduction to Graphical Processing Unit (GPU) optimized database systems especially in online analytical processing. The authors emphasis is on the breadth of the subject and cover as many publications as possible, with necessary details in some key GPU-optimized designs.

Provides a review of recent theoretical and practical progress on systems that employ erasure codes for distributed storage. Starting with coverage of the key challenges and research problems, the authors give an overview of different models and approaches that have been developed to quantify latency of erasure-coded storage.

Surveys fundamental concepts and practical methods for creating and curating large knowledge bases. The book covers models and methods for discovering and curating large knowledge bases from online content, with emphasis on semi-structured web pages and unstructured text sources.

Provides both historical background and a comprehensive overview of the recent advances in the field. In particular, the authors lay out all the components needed in the design of a privacy-centric email search engine.

Defines and describes the research field at the interface of Finance, Operations, and Risk Management (iFORM), provides examples where operations and finance overlap in meaningful ways, outlines promising research directions, and reduces the entry cost for anyone who would like to explore this new and exciting research field.

The term Federated Learning was coined as recently as 2016 to describe a machine learning setting where multiple entities collaborate in solving a machine learning problem, under the coordination of a central server or service provider. This book describes the latest state-of-the art.

Presents a condensed summary of research efforts investigating post-WIMP interaction techniques in visualization systems. The authors discuss the main challenges faced, lessons learned, and reflect on how their perspectives and viewpoints on post-WIMP for InfoVis have evolved.

Provides an overview and background of the various developments of single-slope analog-to-digital converters (SS-ADC). Background information is given about the general CIS architecture, the CIS pixels and the noise sources present in a CIS. The book also describes the various architectures used in an SS-ADC.