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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.
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.
The Nuclear Dawn HUD (largely in yellow) displays the character's health, weapon ammunition, and compass heading, while also including a map of the area in the top-right corner, and a circular marker pointing to the player's destination.
The sensitivity of a microphone is usually expressed as the sound field strength in decibels (dB) relative to 1 V/Pa (Pa = N/m 2) or as the transfer factor in millivolts per pascal (mV/Pa) into an open circuit or into a 1 kiloohm load. [citation needed] The sensitivity of a loudspeaker is usually expressed as dB / 2.83 V RMS at 1 metre.
Sensitivity first definition: the ratio between output and input signal, or the slope of the output versus input response curve of a transducer, microphone or sensor; Sensitivity second definition: the minimum magnitude of input signal required to produce an output signal with a specified signal-to-noise ratio of an instrument or sensor
A command language is a language for job control in computing. [1] It is a domain-specific and interpreted language ; common examples of a command language are shell or batch programming languages .
It accepted command-line parameters for the cm (cursor addressing) capability, and recognized terminfo capability names. System V Release 3 provided an improved version which combined the different initialization capabilities as a new option init , and the reset capabilities as reset , thereby simplifying use of tput for initializing or ...
In a classification task, the precision for a class is the number of true positives (i.e. the number of items correctly labelled as belonging to the positive class) divided by the total number of elements labelled as belonging to the positive class (i.e. the sum of true positives and false positives, which are items incorrectly labelled as belonging to the class).