Description: Announces author's departure as Section Chair and incoming Council members.

Description: In this continuation of our July 2013 article we explore an algorithm for evaluating Hidden Markov Models in detail. A preferred method in speech recognition technology, Hidden Markov Models are a promising technique when dealing with data you suspect may be driven by a change in a unobservable state. The example in the article is provided in an Excel workbook for the reader to follow along with.

Description: 1. A simplified description of how a genetic algorithm works (requiring no knowledge of biology) and how to build your own. 2. A free Excel workbook that allows you to solve problems without doing any coding; or to let you extend the existing code for your own special needs.

Description: An introduction of predictive modeling techniques that are applicable to insurance industry, including generalized linear model (GLM) and classification and regression tree model(CART). Other models such as data clustering, neural network, and support vector machine (SVM), are also briefly discussed.

Description: A summary of the Global Trends 2030 report, the fifth such report produced every four years by the National Intelligence Council. The report is based on the research and analysis of the 17 major intelligence agencies in the US. The summary covers the highlights of the report.

Description: Summary of a LTD Profitability and Market Survery discussing growth, profits and new developments. Issue No. 34.

Description: Discussion of Alternative or Integrative Care - Fundamental themes, market demand, recent activity, developing an alternative care program, pricing benefits Issue No. 34.

Description: Discussion of several short stories by featured author Steve Mathys. Mathys was the winner of the 10th Speculative Fiction Contest Forecasting and Futurism Section prize.

Description: An introduction to Hidden Markov Models, which are used extensively in speech and facial recognition technology. They are a useful tool in forecasting time series and in developing categorizations of data based on the values of the data themselves.

Description: A general introduction about predictive modeling in insurance applications. Some basic models are discussed, such as Generalized Linear Model(GLM), Calssification and Regression Tree Model. Other models are also briefly introduced, including data clustering, neural networks and support vector machine.