Historically, nursing, in all of its missions of research/scholarship, education and practice, has not had access to large patient databases. Nursing consequently adopted qualitative methodologies with small sample sizes, clinical trials and lab research. Historically, large data methods were limited to traditional biostatical analyses. In the United States, large payer data has been amassed and structures/organizations have been created to welcome scientists to explore these large data to advance knowledge discovery. Health systems electronic health records (EHRs) have now matured to generate massive databases with longitudinal trending. This text reflects how the learning health system infrastructure is maturing, and being advanced by health information exchanges (HIEs) with multiple organizations blending their data, or enabling distributed computing. It educates the readers on the evolution of knowledge discovery methods that span qualitative as well as quantitative data mining, including the expanse of data visualization capacities, are enabling sophisticated discovery. New opportunities for nursing and call for new skills in research methodologies are being further enabled by new partnerships spanning all sectors.
Farbe: magenta, Inhalt: 3,5 ml(C13T12834011/C13T12834010)Stylus SX125/SX420W/SW425W/BX305F/BX305FW/SX130/SX440W/SX445W/SX440W/SX445WStylus Office BX535WD/BX635FWD*** Rand ist eingerissen ***
This book constitutes the thoroughly refereed post-conference proceedings of the 20th International Conference on Financial Cryptography and Data Security, FC 2016, held in Christ church, Barbados, in February 2016. The 27 revised full papers and 9 short papers were carefully selected and reviewed from 137 full papers submissions. The papers are grouped in the following topical sections: fraud and deception; payments, auctions, and e-voting; multiparty computation; mobile malware; social interaction and policy; cryptanalysis; surveillance and anonymity; Web security and data privacy; Bitcoin mining; cryptographic protocols; payment use and abuse.
Amharic is the second-most widely spoken Semitic language in the world after Arabic. Compared to other languages, it is difficult to find computational tools created for the language speakers. Question answering is the act of making a dialogue with the computers. This work is done to help the Amharic speakers find factoid information from the web easily. The targeted factoid questions are what, when, who, and where types of questions in Amharic. This work is essential for anyone who is curious about how question answering works in Amharic or wants to do a natural language processing research on the language.
This book presents a detailed review of the state of the art in deep learning approaches for semantic object detection and segmentation in medical image computing, and large-scale radiology database mining. A particular focus is placed on the application of convolutional neural networks, with the theory supported by practical examples. Features: highlights how the use of deep neural networks can address new questions and protocols, as well as improve upon existing challenges in medical image computing; discusses the insightful research experience of Dr. Ronald M. Summers; presents a comprehensive review of the latest research and literature; describes a range of different methods that make use of deep learning for object or landmark detection tasks in 2D and 3D medical imaging; examines a varied selection of techniques for semantic segmentation using deep learning principles in medical imaging; introduces a novel approach to interleaved text and image deep mining on a large-scale radiology image database.
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Speed, social change, historical inheritance and cultural gaps are the key success factors which have significant impact on global collaboration and global sourcing. The author explains how working in virtual teams in a global, multicultural environment requires a significant amount of organizational and behavioral change of people and organizations. Understanding cultural differences in working styles is important for successful global project management. Major theories of international management, company internationalization, cultural dimensions and distances will be discussed to develop cross-cultural competencies and conflict management styles for international project managers. They will understand modern theories and methods of international management and will be able to apply these to practical project management problems. They understand the benefits and challenges of international cooperation and know how to identify modes of cooperation that are relevant to the needs of international teams. Speed, social change, historical inheritance and cultural gaps are key factors which have significant impact on global collaboration and global sourcing. The author explains how working in virtual teams in a global, multicultural environment requires a significant amount of organizational and behavioral change of people and organizations. Understanding cultural differences in working styles is important for successful global project management. Major theories of international management, company internationalization, cultural dimensions and distances will be discussed to develop cross-cultural competencies and conflict management styles for international project managers. They will understand modern theories and methods of international management and will be able to apply these to practical project management problems. They understand the benefits and challenges of international cooperation and know how to identify modes of cooperation that are relevant to the needs of international teams.
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Com popularização dos sistemas de informação, a quantidade de dados armazenados tem crescido diariamente, analisar esse grande volume de dados se tornou um requisito importante de negócio. A necessidade de se obter o melhor desempenho ao menor custo está cada vez mais presente no dia a dia das organizações. Dessa forma, o grande desafio é desenvolver novas tecnologias e modelos de dados que consigam armazenar e analisar de forma eficiente a gigantesca massa de dados gerada nos dias de hoje. Tendo como base esse cenário de mudanças, este trabalho tem por objetivo modelar e implementar uma base de dados orientada à grafos, a fim de identificar suas diferenças em relação a abordagem relacional. Para isso, foi desenvolvido um estudo de caso baseado em análise social onde bases de dados foram carregadas com dados obtidos através do Facebook, a fim de verificar o desempenho dos dois modelos de dados em consultas recursivas. Os resultados apresentados pelos testes de performance foram satisfatórios fornecendo as informações necessárias sobre as principais diferenças na utilização de bases de dados relacionais e as orientadas a grafos para a análise de redes sociais e Big Data.
This book comprises nine selected works on numerical and computational methods for solving multiobjective optimization, game theory, and machine learning problems. It provides extended versions of selected papers from various fields of science such as computer science, mathematics and engineering that were presented at EVOLVE 2013 held in July 2013 at Leiden University in the Netherlands. The internationally peer-reviewed papers include original work on important topics in both theory and applications, such as the role of diversity in optimization, statistical approaches to combinatorial optimization, computational game theory, and cell mapping techniques for numerical landscape exploration. Applications focus on aspects including robustness, handling multiple objectives, and complex search spaces in engineering design and computational biology.
There have been substantial developments in meshfree methods, particle methods, and generalized finite element methods since the mid 1990s. The growing interest in these methods is in part due to the fact that they offer extremely flexible numerical tools and can be interpreted in a number of ways. For instance, meshfree methods can be viewed as a natural extension of classical finite element and finite difference methods to scattered node configurations with no fixed connectivity. Furthermore, meshfree methods have a number of advantageous features that are especially attractive when dealing with multiscale phenomena: A-priori knowledge about the solution´s particular local behavior can easily be introduced into the meshfree approximation space, and coarse scale approximations can be seamlessly refined by adding fine scale information. However, the implementation of meshfree methods and their parallelization also requires special attention, for instance with respect to numerical integration.