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Context sensitivity is ubiquitous in current graphical user interfaces, often in context menus. A user-interface may also provide context sensitive feedback , such as changing the appearance of the mouse pointer or cursor, changing the menu color, or with auditory or tactile feedback.
For instance, certain games employ a "health bar" which empties as the player becomes hurt such as Tekken, Street Fighter, and many others. Armour levels are also commonly monitored, either through a separate readout, or as part of the health system. For example, some Halo games use one recharging shield bar, acting as the health level. [2]
The low CUSUM value, detecting a negative anomaly, + = (, +) where ω {\displaystyle \omega } is a critical level parameter (tunable, same as threshold T) that's used to adjust the sensitivity of change detection: larger ω {\displaystyle \omega } makes CUSUM less sensitive to the change and vice versa.
A sensitivity guarantees that the distance from the critical point to the Nyquist curve is always greater than and the Nyquist curve of the loop transfer function is always outside a circle around the critical point + with the radius , known as the sensitivity circle.
In more dynamic action games, it is important to quickly restore a character's health, while role-playing games feature slower-paced methods of health restoration to achieve realism. [26] A number of games incorporate a regeneration system that automatically replenishes health if the character does not take damage.
Context-sensitive meaning, where meaning depends on context (language use) Context-sensitive grammar , a formal grammar in which the left-hand sides and right-hand sides of any production rules may be surrounded by a context of terminal and nonterminal symbols
In signal processing, sensitivity also relates to bandwidth and noise floor as is explained in more detail below. In the field of electronics different definitions are used for sensitivity. The IEEE dictionary [2] [3] states: "Definitions of sensitivity fall into two contrasting categories." It also provides multiple definitions relevant to ...
The sensitivity is therefore 32 / 35 = 91.4%. Using the same method, we get TN = 40 - 3 = 37, and the number of healthy people 37 + 8 = 45, which results in a specificity of 37 / 45 = 82.2 %. For the figure that shows low sensitivity and high specificity, there are 8 FN and 3 FP. Using the same method as the previous figure, we get TP = 40 - 3 ...