Follow in the footsteps of the giants of success! Andrew Carnegie. Thomas Edison. Henry Ford. You´ve probably experienced fewer failures in life than these famous achievers. Surprising, but true. Each faced repeated setbacks. Yet each became enormously successful. How? Napoleon Hill devoted his life to studying this question, analyzing the success of more than 500 of the 20th Century´s greatest achievers. His exhaustive research proved that the essence of success lies within 17 simple principles that, when used together, serve as an infallible formula for achievement. These 17 key principles are the foundation of The Science of Personal Achievement, a comprehensive course in success that empowers you to convert any adversity into advantage. And it all starts with a thought. With Napoleon Hill´s guidance, you will achieve a level of mental self-mastery that will enable you consistently to: Overcome fears to reach your achievements. Maintain self-discipline and self-confidence. Develop strong personal initiative. Focus your thoughts into clear plans of action. The Science of Personal Achievement gives you the mental skills needed to meet the challenge of transforming your ideas into realized accomplishments. Consistently attain your goals as you incorporate the 17 principles at the heart of this course into your daily life. Become the architect of your destiny, capable of building a lifetime of accomplishment. Whether you are striving for success in your career or in your personal life, Napoleon Hill´s unique, universal philosophies will lead you directly to the source of all life´s riches. PLEASE NOTE: When you purchase this title, the accompanying reference material will be available in your My Library section along with the audio. Language: English. Narrator: Napoleon Hill. Audio sample: http://samples.audible.de/bk/ntgl/000027de/bk_rhde_002536_sample.mp3. Digital audiobook in aax.
This study develops a methodology for rapidly obtaining approximate estimates of the economic consequences from numerous natural, man-made and technological threats. This software tool is intended for use by various decision makers and analysts to obtain estimates rapidly. It is programmed in Excel and Visual Basic for Applications (VBA) to facilitate its use. This tool is called E-CAT (Economic Consequence Analysis Tool) and accounts for the cumulative direct and indirect impacts (including resilience and behavioral factors that significantly affect base estimates) on the U.S. economy. E-CAT is intended to be a major step toward advancing the current state of economic consequence analysis (ECA) and also contributing to and developing interest in further research into complex but rapid turnaround approaches. The essence of the methodology involves running numerous simulations in a computable general equilibrium (CGE) model for each threat, yielding synthetic data for the estimation of a single regression equation based on the identification of key explanatory variables (threat characteristics and background conditions). This transforms the results of a complex model, which is beyond the reach of most users, into a reduced form model that is readily comprehensible. Functionality has been built into E-CAT so that its users can switch various consequence categories on and off in order to create customized profiles of economic consequences of numerous risk events. E-CAT incorporates uncertainty on both the input and output side in the course of the analysis. Adam Rose: Price School of Public Policy and Center for Risk and Economic Analysis of Terrorism Events (CREATE), University of Southern California Fynnwin Prager: College of Business Administration and Public Policy, California State University, Dominguez Hills Zhenhua Chen: Center for Risk and Economic Analysis of Terrorism Events (CREATE), University of Southern California Samrat Chatterjee: Applied Statistics and Computational Modeling, Pacific Northwest National Laboratory Dan Wei: Price School of Public Policy and Center for Risk and Economic Analysis of Terrorism Events (CREATE), University of Southern California Nathaniel Heatwole: Acumen, LLC Eric Warren: Center for Risk and Economic Analysis of Terrorism Events (CREATE), University of Southern California
This book presents methods for investigating whether relationships are linear or nonlinear and for adaptively fitting appropriate models when they are nonlinear. Data analysts will learn how to incorporate nonlinearity in one or more predictor variables into regression models for different types of outcome variables. Such nonlinear dependence is often not considered in applied research, yet nonlinear relationships are common and so need to be addressed. A standard linear analysis can produce misleading conclusions, while a nonlinear analysis can provide novel insights into data, not otherwise possible. A variety of examples of the benefits of modeling nonlinear relationships are presented throughout the book. Methods are covered using what are called fractional polynomials based on real-valued power transformations of primary predictor variables combined with model selection based on likelihood cross-validation. The book covers how to formulate and conduct such adaptive fractional polynomial modeling in the standard, logistic, and Poisson regression contexts with continuous, discrete, and counts outcomes, respectively, either univariate or multivariate. The book also provides a comparison of adaptive modeling to generalized additive modeling (GAM) and multiple adaptive regression splines (MARS) for univariate outcomes. The authors have created customized SAS macros for use in conducting adaptive regression modeling. These macros and code for conducting the analyses discussed in the book are available through the first authors website and online via the books Springer website. Detailed descriptions of how to use these macros and interpret their output appear throughout the book. These methods can be implemented using other programs. George Knafl is Professor and Biostatistician in the School of Nursing of the University of North Carolina at Chapel Hill where he teaches statistics courses to doctoral nursing students, consults with graduate students and faculty on their research, and conducts his own research. He has over 35 years of experience in teaching, consulting, and research in statistics. His research involves development of methods for searching through alternative models for data to identify an effective choice for modeling those data and the application of those methods to the analysis of health science data sets. He is also Professor Emeritus in the College of Computing and Digital Media at DePaul University and has also taught in Schools of Nursing at Yale University and the Oregon Health and Sciences University. Kai Ding is Assistant Professor, Department of Biostatistics and Epidemiology at the University of Oklahoma (OU) Health Sciences Center. He is also Associated Member of the Peggy and Charles Stephenson Cancer Center (SCC) of OU Medicine. Dr. Ding received his Ph.D. in Biostatistics from the University of North Carolina at Chapel Hill in 2010. His research has focuses on survival analysis and semiparametric inference. He has been involved in the design and analysis of numerous research studies in cancer and ophthalmology and currently serves on the Scientific Review Committee and the Protocol Monitoring Committee of the SCC.
The book explores advanced building-facade daylighting design practices based on diverse energy and human-factor performance metrics. It also defines effective daylighting by rethinking the simplified approach to glazing and facade systems to incorporate the local climate and the needs of building occupants as critical drivers of building performance, design solutions and technological innovation. It discusses state-of-the-art approaches in the context of simulation-based design workflows, innovative technologies and real project case studies, all targeting low and net-zero energy solutions that enhance occupant comfort. Readers benefit from a comprehensive approach that improves the feedback loop between design intent and performance in use. The book is intended for architects, lighting designers, facade engineers, manufacturers and building owners/operators, as well as advanced students. Kyle Konis, Ph.D, AIA is an Assistant Professor of Architecture at the University of Southern California (https://arch.usc.edu/faculty/kkonis). His courses focus on techniques and measurable methods for integrating sustainable design principles into architectural practice and urban design. Kyles research interests are centered on improving the feedback loop between design and the performance outcomes of buildings in use, with an emphasis on the experience of building occupants. In 2011, Kyle received a Ph.D in Architecture with an emphasis in Building Science from U.C. Berkeley. His Ph.D dissertation extends into the realms of engineering, physical computing, product design and social science, with the goal of leveraging rich and granular occupant feedback data as a critical instrument for evaluating and improving the design and performance of low-energy commercial buildings. While completing his Ph.D, Kyle worked for four years as a graduate research assistant with the Lawrence Berkeley National Laboratorys Windows and Daylighting Group on high performance facade research funded by the U.S. Department of Energy and the California Energy Commission. His research experience also includes examining the feasibility of net-zero energy homes and demand response (DR) enabling technology. While at Berkeley, Kyle received the Bears Breaking Boundaries Award from the U.C. Berkeley Chancellor for Science and Technology. Kyle is a registered architect in the state of Washington and has worked professionally for Bohlin Cywinski Jackson in Seattle and for Sir Michael Hopkins and Long and Kentish Architects in London. Kyle holds a Masters of Architecture degree from Yale University where he received the Multon Andrus Award for Excellence in Art and Architecture in 2004. Prior to coming to USC, Kyle held an appointment at Portland State University. Kyle is a member of the IESNA Daylighting and Daylighting Metrics Committees. His research has been published in a number of prominent journals including Energy and Buildings, Building and Environment, Solar Energy, Intelligent Buildings International, and LEUKOS. Stephen Selkowitz Stephen Selkowitz is Senior Advisor for Building Science, Lawrence Berkeley National Laboratory, now in a part-time research and strategic planning role after leading LBNLs building performance teams in research, development, and deployment of energy efficient technologies and sustainable design practices. An internationally recognized expert on window technologies, window software tools, façade systems, shading solutions, daylighting strategies, and integrated building systems solutions, he led the LBNL Windows Group for 40 years and the LBNL Building Technologies Department for 25 years, partnering with industry to develop and demonstrate new technologies, systems, processes and tools that address energy, sustainability and human factors. He serves as Scientific Advisor to several international building science programs that explore zero net energy building solutions, serves as a consultant to industry, has spoken at over 400 scientific, business and industry venues and authored over 170 publications, 4 books and holds 2 patents. He holds an AB in Physics from Harvard College and an MFA in Environmental Design from California Institute of the Arts. In 2012 he was the recipient of LBNLs first Lifetime Achievement Award for Societal Impact; in 2014 he received McGraw Hill/ENRs prestigious Award of Excellence for relentlessly working to reduce the carbon footprint of buildings and for moving the nation towards better building