Sources of Uncertainty in The Tropical Pacific Warming Pattern Under Global Warming Projected by Coupled Oceanatmosphere Models

This book discusses the sources of uncertainty in future model projections of the tropical Pacific SST warming pattern under global warming. It mainly focuses on cloud radiation feedback and ocean dynamical effect, which reveal to be the two greatest sources of uncertainty in the tropical Pacific SST warming pattern. Moreover, the book presents a correction for model projections of the tropical Pacific SST warming pattern based on the concept of “observational constraints”; the corrected projection exhibits a more El Niño-like warming pattern.

This book summarizes years of research in the field of fuzzy relational programming, with a special emphasis on geometric models. It discusses the state-of-the-art in fuzzy relational geometric problems, together with key open issues that must be resolved to achieve a more efficient application of this method. Though chiefly based on research conducted by the authors, who were the first to introduce fuzzy geometric problems, it also covers important findings obtained in the field of linear and non-linear programming. Thanks to its balance of basic and advanced concepts, and its wealth of practical examples, the book offers a valuable guide for both newcomers and experienced researcher in the fields of soft computing and mathematical optimization.

The Irish Rovers were one of the more popular folk-based singing groups to come out of Ireland in the mid-'60s, although they had to do it by way of Canada. As teenagers, founders George Millar (guitar, vocals, banjo) and Jimmy Ferguson (vocals) were former residents of Northern Ireland, living in Toronto, when they started singing together in 1963, originally for cigarette and beer money. It was Millar's mother who suggested, on hearing the duo rehearse, that they use the name the Irish Rovers, from the song "The Irish Rover."

Understanding the stochastic enviornment is as much important to the manager as to the economist. From production and marketing to financial management, a manager has to assess various costs imposed by uncertainty. The economist analyzes the role of incomplete and too often imperfect information structures on the optimal decisions made by a firm. The need for understanding the role of uncertainty in quantitative decision models, both in economics and management science provide the basic motivation of this monograph. The stochastic environment is analyzed here in terms of the following specific models of optimization: linear and quadratic models, linear programming, control theory and dynamic programming. Uncertainty is introduced here through the para­ meters, the constraints, and the objective function and its impact evaluated. Specifically recent developments in applied research are emphasized, so that they can help the decision-maker arrive at a solution which has some desirable charac­ teristics like robustness, stability and cautiousness. Mathematical treatment is kept at a fairly elementary level and applied as­ pects are emphasized much more than theory. Moreover, an attempt is made to in­ corporate the economic theory of uncertainty into the stochastic theory of opera­ tions research. Methods of optimal decision rules illustrated he re are applicable in three broad areas: (a) applied economic models in resource allocation and economic planning, (b) operations research models involving portfolio analysis and stochastic linear programming and © systems science models in stochastic control and adaptive behavior.

The Drop is an analog modelled resonant filter plug-in based on classic analog synth filters, as well as completely new designs. There is a huge level of detail in the models, which gives them amazing drive and tone, as well as smooth audio rate modulation behaviour. The original structure of the circuits is preserved in the model, as is the location and shape of all major non-linearities.