31 Days provides a month of thoughts, tips and traps to help you better process and enjoy your month and year. In over 10 years of blogging, Wayne has curated his best posts to help you get and enjoy where you want to go, be and do.
Japanese difficult? Study boring? No way! Not with this "real manga, real Japanese" approach to learning. Presenting all spoken Japanese as a variation of three basic sentence types, Japanese the Manga Way shows how to build complex constructions step by step. Every grammar point is illustrated by an actual manga published in Japan to show how the language is used in real life, an approach that is entertaining and memorable. As an introduction, as a jump-start for struggling students, or (with its index) as a reference and review for veterans, Japanese the Manga Way is perfect for all learners at all levels. Wayne P. Lammers has taught Japanese at the college level and is an award-winning literary and commercial translator. He lives in Portland, Oregon.
Editors Fred M. Nordhauser and Wayne P. Olson have gathered a team of 18 experts from multi-national and leading edge companies to explore the advantages and disadvantages of current sterilization technologies. They cover the theory behind the technology, the practical concerns of installation from engineering and product development perspectives, the "how to validate" concern, and the pragmatics of implementation in a manner that will satisfy the regulatory agencies. The broad range of in-depth information on numerous technologies will help readers design sterile manufacturing processes cost effectively and efficiently.
A hands-on guide to making valuable decisions from data using advanced data mining methods and techniques This second installment in the Making Sense of Data series continues to explore a diverse range of commonly used approaches to making and communicating decisions from data. Delving into more technical topics, this book equips readers with advanced data mining methods that are needed to successfully translate raw data into smart decisions across various fields of research including business, engineering, finance, and the social sciences. Following a comprehensive introduction that details how to define a problem, perform an analysis, and deploy the results, Making Sense of Data II addresses the following key techniques for advanced data analysis: Data Visualization reviews principles and methods for understanding and communicating data through the use of visualization including single variables, the relationship between two or more variables, groupings in data, and dynamic approaches to interacting with data through graphical user interfaces. Clustering outlines common approaches to clustering data sets and provides detailed explanations of methods for determining the distance between observations and procedures for clustering observations. Agglomerative hierarchical clustering, partitioned-based clustering, and fuzzy clustering are also discussed. Predictive Analytics presents a discussion on how to build and assess models, along with a series of predictive analytics that can be used in a variety of situations including principal component analysis, multiple linear regression, discriminate analysis, logistic regression, and Naïve Bayes. Applications demonstrates the current uses of data mining across a wide range of industries and features case studies that illustrate the related applications in real-world scenarios. Each method is discussed within the context of a data mining process including defining the problem and deploying the results, and readers are provided with guidance on when and how each method should be used. The related Web site for the series (www.makingsenseofdata.com) provides a hands-on data analysis and data mining experience. Readers wishing to gain more practical experience will benefit from the tutorial section of the book in conjunction with the TraceisTM software, which is freely available online. With its comprehensive collection of advanced data mining methods coupled with tutorials for applications in a range of fields, Making Sense of Data II is an indispensable book for courses on data analysis and data mining at the upper-undergraduate and graduate levels. It also serves as a valuable reference for researchers and professionals who are interested in learning how to accomplish effective decision making from data and understanding if data analysis and data mining methods could help their organization.
