A driving control apparatus, a device, an optical module, and a driving control method will be provided, the driving control apparatus including: an acquiring unit to acquire a detection signal depending on a detection result of sensing a position of a driving target object; a driving control unit to generate a driving signal to move the driving target object to a target position based on the detection signal; an oscillation detecting unit to detect oscillation in a signal at a predetermined object point on a signal path from the detection signal to the driving signal; and an oscillation suppressing unit to suppress oscillation of the signal path according to detection of the oscillation.

A method for calculating real-time immission values at locations within an area of interest. The method comprises providing an emission dispersion model with real-time information on one or more mobile emitters, for example vehicles. The one or more mobile emitters are within an area of interest. The method further comprises providing the emission dispersion model with respective emission characteristics of the one or more mobile emitters. The method further comprises providing the emission dispersion model with information comprising influencing environmental factors on emission dispersion for an environment within the area of interest. The method further comprises calculating real-time immission values at locations within the area of interest based on the emission dispersion model. Further, a system for calculating real-time immission values at locations within an area of interest is provided.

A rack server noise monitoring method and system. The system includes a sound pressure obtaining device, which includes a semi-anechoic room with a 4U jig at the center thereof and microphones over the 4U jig, and a noise monitoring device which includes a server rack and a rack server management module RMC. The microphone is configured to measure sound pressure values of the 4U jig controlled by PWM input signals with different duty ratios. Node middle boards are provided in the server rack, each of which is connected to a fan control panel, the fan control panel is connected to a fan unit, the fan unit includes fans, and each node middle board is connected to the RMC. The RMC obtains a real-time duty ratio of a PWM input signal for the fan, and calculates a real-time sound pressure value based on the duty ratio of the PWM input signal.

An audio system and methods for detecting proximity between or engagement between a removable open-ear acoustic module and a host device. Upon detection of proximity or engagement, the audio system may adjust at least one device setting of the devices in the system. In some examples, the devices of the audio system are capable of obtaining specific identifying information about the other devices, and can be configured to adjust the at least one device setting based on device identity. For example, adjusting the device settings can include an adjustment to power state of the open-ear acoustic module, an audio equalization (EQ) setting, a volume setting, a bass level setting, a treble level setting, an Active Noise Reduction (ANR) setting, a user profile setting, selection of an algorithm of a plurality of algorithms related to data collection, a sensor calibration setting, and a user interface control setting.

An audio system and methods for detecting proximity between or engagement between a removable open-ear acoustic module and a host device. Upon detection of proximity or engagement, the audio system may adjust at least one device setting of the devices in the system. In some examples, the devices of the audio system are capable of obtaining specific identifying information about the other devices, and can be configured to adjust the at least one device setting based on device identity. For example, adjusting the device settings can include an adjustment to power state of the open-ear acoustic module, an audio equalization (EQ) setting, a volume setting, a bass level setting, a treble level setting, an Active Noise Reduction (ANR) setting, a user profile setting, selection of an algorithm of a plurality of algorithms related to data collection, a sensor calibration setting, and a user interface control setting.

A device includes a gas-measuring unit and a sound-measuring unit. The gas-measuring unit has a gas sensor detecting a first measured variable, and a gas analysis module determining a gas concentration from the first variable and comparing the concentration with a first threshold value, to output a first signal based thereon. The sound-measuring unit has a sound detection unit detecting a second measured variable, and a sound analysis module determining a status variable, from the second variable, indicating a noise exposure, and comparing the status variable with a second threshold value to determine a first parameter indicating a current sound level and/or determining a second parameter indicating a sound exposure accumulated over a time interval. The sound analysis module may determine the status variable, the first parameter and/or the second parameter as a function of the comparison of the gas concentration and the first threshold value.

In an abnormal noise evaluation system, running noise of a vehicle is acquired, and the running noise is analyzed to generate analysis data. A rotational order component of the running noise of the vehicle is then extracted from the analysis data, and features for each rotational order of the running noise of the vehicle is generated based on the extracted rotational order component. Subsequently, a learning model is generated using as training data a combination of the features for each rotational order generated for a learning object that is of the same type as an object to be evaluated and an evaluation result given in advance to the learning object. Whether there is abnormal noise from the object to be evaluated is evaluated by applying the features for each rotational order generated for the object to be evaluated to the learning model, and an evaluation result is output.

An airborne acoustic vector sensor for simultaneously measuring triaxial particle acceleration in three dimensions and pressure includes a triaxial MEMS accelerometer sensitive to an Earth gravitational field. The airborne acoustic vector sensor includes one or multiple MEMS microphones sensitive to sound pressure and overlapping the accelerometer in frequency. The airborne acoustic vector sensor includes a solid body having a density approximating a density of air. The accelerometer is mounted in or upon the solid body. The airborne acoustic vector sensor includes a suspension system supporting the accelerometer and solid body within a framework.

A device has one or more loudspeakers housed in a rigid loudspeaker frame and a back cover, affixed to the rigid loudspeaker frame, with a base layer and a raised layer fitted against a back side of the rigid loudspeaker frame, and the base layer has a uniform layer thickness and the raised layer is a non-uniform grid of raised supports which extend beyond a height of the uniform layer thickness to create a plurality of enclosed portions having the uniform layer thickness.

An assessment system includes a sound data acquiring unit configured to acquire sound data collected by a sound insulation device, the sound insulation device being fitted into a wearer's ears; and an assessment unit configured to assess noise to which the wearer is exposed, based on the sound data acquired by the sound data acquiring unit and time information associated with the sound data.