다중혈관 관상동맥 환자에서 y-문합을 이용하여 양쪽 내흉동맥만을 사용한 우회술의 조기 성적

THE DESIGN AND ANALYSIS OF EXPERIMENTS. By Oscar Kempthorne. New York, John Wiley and Sons, Inc., 1952. 631 pp. $8.50. This book by a teacher of statistics (as well as a consultant for \"experimenters\") is a comprehensive study of the philosophical background for the statistical design of experiment. It is necessary to have some facility with algebraic notation and manipulation to be able to use the volume intelligently. The problems are presented from the theoretical point of view, without such practical examples as would be helpful for those not acquainted with mathematics. The mathematical justification for the techniques is given. As a somewhat advanced treatment of the design and analysis of experiments, this volume will be interesting and helpful for many who approach statistics theoretically as well as practically. With emphasis on the \"why,\" and with description given broadly, the author relates the subject matter to the general theory of statistics and to the general problem of experimental inference. MARGARET J. ROBERTSON

The Design and Analysis of Experiments

National Institute of Standards and Technology における超伝導研究及び生活

Energy management means to optimize one of the most complex and important technical creations that we know: the energy system. While there is plenty of experience in optimizing energy generation and distribution, it is the demand side that receives increasing attention by research and industry. Demand Side Management (DSM) is a portfolio of measures to improve the energy system at the side of consumption. It ranges from improving energy efficiency by using better materials, over smart energy tariffs with incentives for certain consumption patterns, up to sophisticated real-time control of distributed energy resources. This paper gives an overview and a taxonomy for DSM, analyzes the various types of DSM, and gives an outlook on the latest demonstration projects in this domain.

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Demand Side Management: Demand Response, Intelligent Energy Systems, and Smart Loads

For 100 years, there has been no change in the basic structure of the electrical power grid. Experiences have shown that the hierarchical, centrally controlled grid of the 20th Century is ill-suited to the needs of the 21st Century. To address the challenges of the existing power grid, the new concept of smart grid has emerged. The smart grid can be considered as a modern electric power grid infrastructure for enhanced efficiency and reliability through automated control, high-power converters, modern communications infrastructure, sensing and metering technologies, and modern energy management techniques based on the optimization of demand, energy and network availability, and so on. While current power systems are based on a solid information and communication infrastructure, the new smart grid needs a different and much more complex one, as its dimension is much larger. This paper addresses critical issues on smart grid technologies primarily in terms of information and communication technology (ICT) issues and opportunities. The main objective of this paper is to provide a contemporary look at the current state of the art in smart grid communications as well as to discuss the still-open research issues in this field. It is expected that this paper will provide a better understanding of the technologies, potential advantages and research challenges of the smart grid and provoke interest among the research community to further explore this promising research area.

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Smart Grid Technologies: Communication Technologies and Standards

A novel decentralized platform for peer-to-peer energy trading market with blockchain technology

The energy system of the future is expected to be composed of a large variety of technologies and applications. However, the diverse nature of these components, their interlinked topology, and the sheer size of the system lead to an unprecedented level of complexity. Industry is confronted with severe problems in designing interoperable grid components, analyzing system stability, and improving efficiency. This paper describes the main challenges of continuous time-based and discrete event-based models of such cyber-physical energy systems. Using a characteristic test model, the scalability of the two approaches is analyzed. The results show the strengths and weaknesses of these two fundamentally different modeling principles that need to be considered when working with large scale cyber-physical energy systems.

Simulating Cyber-Physical Energy Systems: Challenges, Tools and Methods

Building automation (BA) and smart homes (SHs) have traditionally not been a unified field but varied by their origins, legal foundations, different applications, different goals, and national funding programs for basic research. Only within the last years that an international common focus appeared. The following overview gives not only an introduction into the topic of BA but also the distinction to other areas of automation, in which networks of the field level (the sensor and actuator level) play an important role. Finally, the scientific challenges will be mentioned. SHs are referred to when the differences to BA have to be explicitly stressed. This paper is an introduction for the special IEEE Transactions on Industrial Electronics section on BA and shall introduce the reader to this new topic. BA not only has a huge economic potential but also is of significant academic interest today.

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Communication and Computation in Buildings: A Short Introduction and Overview

Smart grids link various types of energy technologies-such as power electronics, machines, grids, and markets-via communication technology, which leads to a transdisciplinary, multidomain system. Simulation packages for assessing system integration of components typically cover only one subdomain, while simplifying the others. Cosimulation overcomes this by coupling subdomain models that are described and solved within their native environments, using specialized solvers and validated libraries. This article discusses the state of the art and conceptually describes the main challenges for simulating intelligent power systems. This article, part 1 of 2 on this subject, covers fundamental concepts. Part 2 will appear in a future issue of IEEE Electrification Magazine and cover applications.

Peter Palensky

Papers

Demand Side Management: Demand Response, Intelligent Energy Systems, and Smart Loads

A novel decentralized platform for peer-to-peer energy trading market with blockchain technology

Simulating Cyber-Physical Energy Systems: Challenges, Tools and Methods

Communication and Computation in Buildings: A Short Introduction and Overview

Cosimulation of Intelligent Power Systems: Fundamentals, Software Architecture, Numerics, and Coupling