That mistakes are made is clear. What is meant by that is not. Measuring whatever might be meant and scientifically studying it is therefore even more challenging.These lectures introduce an interdisciplinary science of mistakes to cut the Gordian knot. The key building blocks are model constructs drawn from the economic tradition, methods of measurement drawn from the psychometric tradition, and analytic methods drawn from economic theory.
Relying on economic theory where necessary, this book emphasizes translating that theory into practical applications that will help students appreciate the clear importance of understanding how countries, businesses, workers, and governments interact with each other. It offers in-depth analysis, empirical evidence, and practical examples arising from all the forms of international exchange: international trade, or the exchange of goods and services across borders; international finance, or the roles that currencies, exchange rates, prices, and monetary systems play in facilitating global investment and trade; global migration, through which workers move from lower-wage countries to higherwage countries; the international flows of capital and knowledge through multinational enterprises and global supply chains; and the global policy architecture underlying these flows. The book pays particular attention to how globalization and technological change affect economic inequality, a primary policy issue today.
Modern society is currently facing a cascade of environmental crises. Moving forward, it will be the job of current and future generations to develop sound and creative approaches to addressing them. This book attempts to provide insight into the ways in which society can confront modern agricultural, environmental, and resource challenges. In particular, it provides an economic lens with which to examine and confront these issues. The first part of the book introduces a general economic framework that can be used to analyze these issues. Subsequent chapters rely on this framework to introduce and explain specific concepts in agricultural, environmental, and resource economics, including (but not limited to) non-renewable and renewable resource management, pesticide use, and climate change. The book develops quantitative tools that the readership can use to analyze and better understand the complexities of these challenges. Each chapter includes specific applications, and an accompanying Appendix includes a longer list of practice problems that can be brought into courses as exercises.Resources are available to instructors who adopt this book. More details at www.worldscientific.com/worldscibooks/10.1142/13304-sm
This book constitutes the workshop proceedings of the 16th International Conference on Database Systems for Advanced Applications, DASFAA 2011, held in Hong Kong, China, in April 2011. The volume contains six workshops, each focusing on specific research issues that contribute to the main themes of the DASFAA conference: The First International Workshop on Graph-structured Data Bases (GDB 2011); the First International Workshop on Spatial Information Modeling, Management and Mining (SIM3 2011); the International Workshop on Flash-based Database Systems (FlashDB 2011); the Second International Workshop on Social Networks and Social Media Mining on the Web (SNSMW 2011); the First International Workshop on Data Management for Emerging Network Infrastructures (DaMEN 2011); and the Fourth International Workshop on Data Quality in Integration Systems (DQIS 2011).
This book includes high-quality papers presented at the Second International Conference on Data Science and Management (ICDSM 2021), organized by the Gandhi Institute for Education and Technology, Bhubaneswar, from 19 to 20 February 2021. It features research in which data science is used to facilitate the decision-making process in various application areas, and also covers a wide range of learning methods and their applications in a number of learning problems. The empirical studies, theoretical analyses and comparisons to psychological phenomena described contribute to the development of products to meet market demands.
This book is devoted to current problems of artificial and computational intelligence including decision-making systems. Collecting, analysis, and processing information are the current directions of modern computer science. Development of new modern information and computer technologies for data analysis and processing in various fields of data mining and machine learning creates the conditions for increasing effectiveness of the information processing by both the decrease of time and the increase of accuracy of the data processing. The book contains of 54 science papers which include the results of research concerning the current directions in the fields of data mining, machine learning, and decision making. The papers are divided in terms of their topic into three sections. The first section "Analysis and Modeling of Complex Systems and Processes" contains of 26 papers, and the second section "Theoretical and Applied Aspects of Decision-Making Systems" contains of 13 papers. There are 15 papers in the third section "Computational Intelligence and Inductive Modeling". The book is focused to scientists and developers in the fields of data mining, machine learning and decision-making systems.
The beauty of science may be pure and eternal, but the practice of science costs money. And scientists, being human, respond to incentives and costs, in money and glory. Choosing a research topic, deciding what papers to write and where to publish them, sticking with a familiar area or going into something new—the payoff may be tenure or a job at a highly ranked university or a prestigious award or a bump in salary. The risk may be not getting any of that. At a time when science is seen as an engine of economic growth, Paula Stephan brings a keen understanding of the ongoing cost-benefit calculations made by individuals and institutions as they compete for resources and reputation. She shows how universities offload risks by increasing the percentage of non-tenure-track faculty, requiring tenured faculty to pay salaries from outside grants, and staffing labs with foreign workers on temporary visas. With funding tight, investigators pursue safe projects rather than less fundable ones with uncertain but potentially path-breaking outcomes. Career prospects in science are increasingly dismal for the young because of ever-lengthening apprenticeships, scarcity of permanent academic positions, and the difficulty of getting funded. Vivid, thorough, and bold, How Economics Shapes Science highlights the growing gap between the haves and have-nots—especially the vast imbalance between the biomedical sciences and physics/engineering—and offers a persuasive vision of a more productive, more creative research system that would lead and benefit the world.
This book is designed to introduce doctoral and graduate students to the process of conducting scientific research in the social sciences, business, education, public health, and related disciplines. It is a one-stop, comprehensive, and compact source for foundational concepts in behavioral research, and can serve as a stand-alone text or as a supplement to research readings in any doctoral seminar or research methods class. This book is currently used as a research text at universities on six continents and will shortly be available in nine different languages.
This book gathers a selection of peer-reviewed papers presented at the third Big Data Analytics for Cyber-Physical System in Smart City (BDCPS 2021) conference, held in Shanghai, China, on Nov. 27, 2021. The contributions, prepared by an international team of scientists and engineers, cover the latest advances made in the field of machine learning, and big data analytics methods and approaches for the data-driven co-design of communication, computing, and control for smart cities. Given its scope, it offers a valuable resource for all researchers and professionals interested in big data, smart cities, and cyber-physical systems.
This book constitutes the refereed proceedings of the Third International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2002, held in Manchester, UK in August 2002. The 89 revised papers presented were carefully reviewed and selected from more than 150 submissions. The book offers topical sections on data mining, knowledge engineering, text and document processing, internet applications, agent technology, autonomous mining, financial engineering, bioinformatics, learning systems, and pattern recognition.
