Abstract: A film tearing machine and a film tearing method are provided. The film tearing machine solves problems, such as unreasonable design. The film tearing machine includes a bottom plate; a film tearing flattening feeding mechanism fixed on the bottom plate for a flat output of a release film; a film delivering mechanism horizontally and slidably connected to the bottom plate for undertaking the flat release film output by the film tearing flattening feeding mechanism and translating the flat release film to a preset tearing position; and an upward peeling mechanism disposed above the preset tearing position for peeling the release film upward. The film tearing machine ensures flatness of the release film during feeding and stability of fixation during peeling.

Abstract: In an illustrative embodiment, systems and methods include storing, to feature vectors of real estate properties, both property attributes and at least one geospatial feature located within a predetermined distance of the property's location, evaluating, using machine learning (ML) algorithm(s), subsets of properties to identify impactful features having a significant impact on property value for each property subset, and, using an ML model trained for the impactful features of a given property subset, analyze feature data to obtain a) a set of similar properties and/or b) a property valuation for each of one or more real estate properties.

Abstract: Disclosed are systems and methods for generating a long-term signal level estimate during automatic gain control. In an example method, a computing device selects a first subset of an input signal, the input signal being a portion of a captured audio signal including at least a variable speech component. The computing device divides the first subset of the input signal into a first set of intervals. The computing device computes a first statistical measure of each interval of the first set of intervals. The computing devices generates a first statistical distribution based on the first statistical measure of at least a portion of the first set of intervals. The computing device determines the long-term signal level estimate based on one or more characteristics of the first statistical distribution. The computing device generates a first stage gain based on the long-term signal level estimate.

Abstract: Disclosed are systems and methods for generating a long-term signal level estimate during automatic gain control. In an example method, a computing device receives an input signal comprising feed data, the input signal derived from an upstream input signal. The computing device selects a first subset of the feed data and divides the first subset of the feed data into a plurality of analysis intervals. The computing device calculates a statistical average of each analysis interval and generates a first Gaussian distribution based on the statistical average of each analysis interval of the plurality of analysis intervals. Based on one or more characteristics of the first Gaussian distribution, the computing device determines the long-term signal level estimate, generates a first stage gain based on the long-term signal level estimate, and applies the first stage gain to the input signal.

Abstract: In an illustrative embodiment, an automated system engineers customized feature vectors from geospatial information system (GIS) metadata. The system may include computing systems and devices for extracting metadata for GIS features located within a predetermined distance of a property from a GIS map file and storing the extracted GIS features within a feature vector. The system can augment each of the extracted GIS features with amplifying data features extracted from external data sources. The system can calculate a distance between the property and each extracted GIS feature, which establishes a relationship between the property and each GIS feature and associated amplifying data features. Amounts of correlation between each of the extracted GIS features and associated amplifying data features within the feature vector and a market assessment of the property location can be identified using a data model trained with a data set customized to characteristics of the property.

Abstract: Disclosed are systems and methods for generating a long-term signal level estimate during automatic gain control. In an example method, a computing device receives an input signal comprising feed data, the input signal derived from an upstream input signal. The computing device selects a first subset of the feed data and divides the first subset of the feed data into a plurality of analysis intervals. The computing device calculates a statistical average of each analysis interval and generates a first Gaussian distribution based on the statistical average of each analysis interval of the plurality of analysis intervals. Based on one or more characteristics of the first Gaussian distribution, the computing device determines the long-term signal level estimate, generates a first stage gain based on the long-term signal level estimate, and applies the first stage gain to the input signal.

Abstract: Disclosed are systems and methods for automatic control of gain in audio and video conferencing applications to maintain a predetermined and stable audio level. In one embodiment, a first stage applies a first stage gain based on a long-term estimate of signal level, while a second stage gain, based on a short-term estimate of signal level assists the first stage gain to achieve a target level. Some embodiments of long-term level estimation utilize statistical analysis of a buffer to validate or arrive at a more accurate long-term signal level estimate.

Abstract: The embodiments of the present invention disclose a layering method and apparatus for point cloud data, a device, a medium and a vehicle, where the layering method includes: determining, for various frames of point cloud data corresponding to a to-be-processed trajectory, vehicle pitch angles relative to a horizontal plane in the case of a target vehicle collecting the various frames of point cloud data; dividing the to-be-processed trajectory into a ramp region and a non-ramp region according to a size relationship between the vehicle pitch angles corresponding to the various frames of point cloud data; and layering the non-ramp region according to height information. By using the above technical solution, the problem of dividing the point cloud data at different layers into the point cloud data in a same layer is solved; and the accuracy of a layering result of the point cloud data is improved.

Abstract: A film tearing machine and a film tearing method are provided. The film tearing machine solves problems, such as unreasonable design. The film tearing machine includes a bottom plate; a film tearing flattening feeding mechanism fixed on the bottom plate for a flat output of a release film; a film delivering mechanism horizontally and slidably connected to the bottom plate for undertaking the flat release film output by the film tearing flattening feeding mechanism and translating the flat release film to a preset tearing position; and an upward peeling mechanism disposed above the preset tearing position for peeling the release film upward. The film tearing machine ensures flatness of the release film during feeding and stability of fixation during peeling.

Abstract: A base material, a formation method, and an electronic device are provided in the present disclosure. The base material includes a transparent substrate, including a first surface and a second surface which are opposite to each other; a first film layer disposed over the first surface of the transparent substrate, where the first film layer includes a first light transmittance and includes a hollowed region and a non-hollowed region; and the hollowed region is used as a first graphic mark; and further includes a second film layer disposed over the first film layer, where the second film layer includes a second light transmittance and a set color, where the first light transmittance is less than the second light transmittance.

Abstract: In an illustrative embodiment, an automated system engineers customized feature vectors from geospatial information system (GIS) metadata. The system may include computing systems and devices for extracting metadata for GIS features located within a predetermined distance of a property from a GIS map file and storing the extracted GIS features within a feature vector. The system can augment each of the extracted GIS features with amplifying data features extracted from external data sources. The system can calculate a distance between the property and each extracted GIS feature, which establishes a relationship between the property and each GIS feature and associated amplifying data features. Amounts of correlation between each of the extracted GIS features and associated amplifying data features within the feature vector and a market assessment of the property location can be identified using a data model trained with a data set customized to characteristics of the property.

Abstract: Disclosed are systems and methods for automatic control of gain in audio and video conferencing applications to maintain a predetermined and stable audio level. In one embodiment, a first stage applies a first stage gain based on a long-term estimate of signal level, while a second stage gain, based on a short-term estimate of signal level assists the first stage gain to achieve a target level. Some embodiments of long-term level estimation utilize statistical analysis of a buffer to validate or arrive at a more accurate long-term signal level estimate.

Abstract: Disclosed are systems and methods for automatic control of gain in audio and video conferencing applications to maintain a predetermined and stable audio level. In one embodiment, a first stage applies a first stage gain based on a long-term estimate of signal level, while a second stage gain, based on a short-term estimate of signal level assists the first stage gain to achieve a target level. Some embodiments of long-term level estimation utilize statistical analysis of a buffer to validate or arrive at a more accurate long-term signal level estimate.

Abstract: Provided are a MEMS microphone chip and an MEMS microphone. The MEMS microphone chip comprises a substrate, a backplate and a vibration diaphragm, the backplate and the vibration diaphragm constituting two electrodes of a capacitor respectively, the backplate and the vibration diaphragm being suspended above the substrate, the backplate being located between the substrate and the vibration diaphragm, and the substrate being provided with a back chamber and a support column, the support column being connected to a side wall of the back chamber via a connection portion, a through hole or a notch being formed in the connection portion through its thickness direction, to allow spaces at opposite sides of the connection portion to communicate with each other; and the support column being configured to support the backplate.

Abstract: Provided are a MEMS microphone chip and an MEMS microphone. The MEMS microphone chip comprises a substrate, a backplate and a vibration diaphragm, the backplate and the vibration diaphragm constituting two electrodes of a capacitor respectively, the backplate and the vibration diaphragm being suspended above the substrate, the backplate being located between the substrate and the vibration diaphragm, and the substrate being provided with a back chamber and a support column, the support column being connected to a side wall of the back chamber via a connection portion, a through hole or a notch being formed in the connection portion through its thickness direction, to allow spaces at opposite sides of the connection portion to communicate with each other; and the support column being configured to support the backplate.