The phrase "acceleration detection" is correct and usable in written English.
It can be used in contexts related to physics, engineering, or technology, particularly when discussing the measurement or identification of acceleration in various systems.
Example: "The new device features advanced acceleration detection capabilities, allowing for precise monitoring of movement."
Alternatives: "acceleration measurement" or "acceleration sensing".
In passing, acceleration detection is also straightforward to explain: split the output from a motion-detector, delay one signal, and compare.
In order to enhance the accuracy of three-component seismic acceleration detection, a novel three-component micro-optoelectronic mechanical systems (MOEMS) accelerometer based on photoelastic effect has been designed.
We report findings from several variants of a psychophysical experiment using an acceleration detection task in which we tested predictions derived from recent neurophysiological data obtained from monkey area MT. The task was designed as a Posner paradigm and required subjects to detect the speed-up of a moving bar, cued with 75% validity.
TENGs with different working modes and rationally designed structures have been developed as self-powered active sensors for a variety of mechanical motions, including pressure change, physical touching, vibrations, acoustic waves, linear displacement, rotation, tracking of moving objects, and acceleration detection.
Establishing that acceleration detection thresholds would be lower than the 0.25 or 0.20 suggested by Brouwer et al. (2002) and Babler and Dannemiller, respectively, could be a goal for subsequent research.
The second algorithm, called Comfort Index with Acceleration Threshold Detection (CI-ATD), is based on the detection of acceleration values out of comfort range and the average ride comfort.
Toshiba built quite a few features into the robot, for example two CPUs (details unknown), a camera, and a set of 38 sensors (gyro, acceleration, range detection etc).
Toshiba built quite a few features into the robot, for example two CPUs (details unknown), a camera, and a set of 38 sensors (gyro, acceleration, range detection etc.).
Comparing hardwares, GPGPU contributes to acceleration of collision detection especially in large number of source nodes.
Lesser source nodes lead to acceleration of collision detection in all conditions.
The controller receives the object velocity and acceleration and the detection of incipient slippage and adjusts the fingers motion.
