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Downside risk was first modeled by Roy (1952), who assumed that an investor's goal was to minimize his/her risk. This mean-semivariance, or downside risk, model is also known as “safety-first” technique, and only looks at the lower standard deviations of expected returns which are the potential losses.
Downside risk (DR) is measured by target semi-deviation (the square root of target semivariance) and is termed downside deviation. It is expressed in percentages and therefore allows for rankings in the same way as standard deviation. An intuitive way to view downside risk is the annualized standard deviation of returns below the target.
The sample information for example could be concentration of iron in soil samples, or pixel intensity on a camera. Each piece of sample information has coordinates s = ( x , y ) {\displaystyle \mathbf {s} =(x,y)} for a 2D sample space where x {\displaystyle x} and y {\displaystyle y} are geographical coordinates.
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A context diagram can also list the classifications of the external entities as one of a set of simple categories [5] (Examples: [6]), which add clarity to the level of involvement of the entity with regards to the system. These categories include: Active: Dynamic to achieve some goal or purpose (Examples: "Article readers" or "customers").
In cybernetics and control theory, a setpoint (SP; [1] also set point) is the desired or target value for an essential variable, or process value (PV) of a control system, [2] which may differ from the actual measured value of the variable.
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A system sequence diagram should be done for the main success scenario of the use case, and frequent or complex alternative scenarios. There are two kinds of sequence diagrams: Sequence Diagram (SD): A regular version of sequence diagram describes how the system operates, and every object within a system is described specifically.