By Meera Subramanian
Crowded, scorching, topic to violent swings in weather, with a central authority not able or unwilling to stand the main important demanding situations, the wealthy and terrible more and more dwelling in worlds aside; for many of the realm, this photograph is of a potential destiny. For India, it's the very genuine present.
In this lyrical exploration of existence, loss, and survival, Meera Subramanian travels looking for the normal humans and microenterprises decided to restore India’s ravaged wildlife: an engineer-turned-farmer brings natural foodstuff to Indian plates; villagers resuscitate a river run dry; prepare dinner range designers persist at the quest for a smokeless hearth; biologists carry vultures again from the threshold of extinction; and in Bihar, considered one of India’s such a lot impoverished states, a daring younger lady teaches teens the basics of sexual health and wellbeing. whereas investigating those 5 environmental demanding situations, Subramanian discovers the tales that renew wish for a kingdom with the capability to guide India and the planet right into a sustainable and wealthy destiny.
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Additional resources for A River Runs Again: India's Natural World in Crisis, from the Barren Cliffs of Rajasthan to the Farmlands of Karnataka
Miller Abstract NetWeaver is one of the foundational technologies of the Ecosystem Management Decision Support (EMDS) system. NetWeaver’s graphical interface, real time evaluations, fuzzy-logic-based measures of uncertainty, and overall ease of use led to it being chosen as a major component of EMDS. By way of background on this stand-alone knowledge engineering tool, and in order to provide enhanced perspective on EMDS and its inner workings, we first present a description of the origins of NetWeaver, and how and why it was developed.
The standard argument compares data values against an argument to return a TRUE or FALSE value (or undetermined when data are absent). An example of a standard argument is presence (TRUE) or absence (FALSE) of a particular species. The fuzzy argument compares the data values against a fuzzy set membership function that returns a level of trueness based on the degree of membership in the fuzzy set. In NetWeaver, fuzzy set membership is measured on a scale of -1 (no membership in the fuzzy set TRUE, which is equivalent to 100 % FALSE), to 0 (UNDETERMINED in the case of no data, or if there are data provided, it represents 50 % membership in the fuzzy set TRUE), to 1 (complete membership in the fuzzy set, which is equivalent to 100 % or completely TRUE).
Com K. M. Reynolds et al. 1007/978-3-642-32000-2_3, Ó Springer-Verlag Berlin Heidelberg 2014 35 36 P. J. 1 Multi-Criteria Decision Analysis Multi-criteria decision analysis is concerned with decisions amongst alternatives when decision makers have multiple, often competing criteria, that they require the alternatives to address. One of the earliest descriptions of multi-criteria decision analysis (MCDA) was provided in 1771 in a letter by Ben Franklin (Franklin 1956). A friend had asked him how to decide whether a course of action should be pursued or not.