Abstract: Described herein are oral care compositions having a surfactant system comprising four or more surfactants individually selected from a non-sulfate based anionic surfactant, an amphoteric surfactant, a nonionic surfactant, and an amino acid surfactant; a stannous ion source; a nitrate ion source; and a phosphate source. Methods of making and using these compositions are also described.

Abstract: A steering system for a medical device may include a first drive member having a central longitudinal axis; a central shaft extending through the first drive member; a control knob coupled to the first drive member; a braking knob coupled to the central shaft and including a first protrusion; and a brake shoe member coupled to the central shaft between the control knob and the braking knob. The first protrusion may be positioned within a first channel of the brake shoe member; the first protrusion may be configured to engage the brake shoe member to move a first arm of the brake shoe member radially outward towards a wall of the control knob when the braking knob is rotated in a first direction; and the first arm may be configured to move away from the wall when the braking knob is rotated in a second direction.

Abstract: One or more computer processors create a binary cluster of events by bootstrapping a set of ground truths contained with a rule engine applied to a set of high-dimensional datapoints, wherein the binary cluster contains two clusters each containing a plurality of high-dimensional datapoints; determine one or more peer groups for a set of unknown high-dimensional datapoints utilizing a trained multiclass classifier, wherein the high-dimensional datapoints are assigned to one or more peer groups by the trained multiclass classifier using an incremental learning algorithm in order to reduce system resources; create an activity distribution for each unknown high-dimensional datapoint associated with a user in the set of unknown high-dimensional datapoints and each peer group; calculate a deviation percentage between the activity distribution of the user and each peer group associated with the user; and responsive to exceeding a deviation threshold, classify the user or associated high-dimensional datapoints as ri

Abstract: An object detection system includes a first camera having a first field of view and a second camera having a second field of view that overlaps with the first field of view. The object detection system includes object detection logic configured to receive a first image from the first camera and a second image from the second camera and identify an object in both the first and second image. The object detection system further includes object mapping logic configured to identify a location of the object based on the first and second image. The object detection system also includes display logic configured to display the location of the object.

Abstract: An acetabular cup removal device and method. The removal device can include a mounting ring attachable to an acetabular cup, a rotor rotatably coupled to the mounting ring and rotatable about a first axis, an arm pivotably coupled to the rotor and pivotable about a second axis orthogonal to the first axis, an oscillator assembly slidably disposed in a first slit of the arm, and a blade slidably disposed in a second slit of the arm. A rotation of the oscillator assembly causes an oscillation of the blade within the second slit. The removal method includes coupling the device to an acetabular cup, positioning the arm and blade at an initial location, oscillating the blade so as to perform a cut, repositioning the arm at a subsequent adjacent location, repeating the repositioning and oscillating steps until a 360° circumference is cut around the acetabular cup, and removing the acetabular cup.

Abstract: Methods and systems for artificially intelligent security incident and event management using an attention-based deep neural network and transfer learning are disclosed. A method includes: collecting, by a computing device, system and network activity events in bulk; forming, by the computing device, a corpus using the collected system and network activity events; correlating, by the computing device, discrete events of the system and network activity events into offenses; adding, by the computing device, additional features to the corpus representing the offenses and disposition decisions regarding the offenses; training, by the computing device, a deep neural network using the corpus; and tuning, by the computing device, the deep neural network for a monitored computing environment using transfer learning.

Abstract: One or more computer processors create a binary cluster of events by bootstrapping a set of ground truths contained with a rule engine applied to a set of high-dimensional datapoints, wherein the binary cluster contains two clusters each containing a plurality of high-dimensional datapoints; determine one or more peer groups for a set of unknown high-dimensional datapoints utilizing a trained multiclass classifier, wherein the high-dimensional datapoints are assigned to one or more peer groups by the trained multiclass classifier using an incremental learning algorithm in order to reduce system resources; create an activity distribution for each unknown high-dimensional datapoint associated with a user in the set of unknown high-dimensional datapoints and each peer group; calculate a deviation percentage between the activity distribution of the user and each peer group associated with the user; and responsive to exceeding a deviation threshold, classify the user or associated high-dimensional datapoints as ri

Abstract: A document analysis system (100) for use by legal or business users is described. The system (100) includes a number of user devices 102 that communicate with a processing platform (104) to upload documents and receive reports concerning the documents. The illustrated platform (104) includes a processor (112), a document database (114), a preprocessing module (115), a machine learning module (116), a repository for analytics (118), and a report generator (120). A user can upload contracts or other documents to the platform (104) and receive scoring and ratings information for the contract.

Abstract: An object detection system includes a first camera having a first field of view and a second camera having a second field of view that overlaps with the first field of view. The object detection system includes object detection logic configured to receive a first image from the first camera and a second image from the second camera and identify an object in both the first and second image. The object detection system further includes object mapping logic configured to identify a location of the object based on the first and second image. The object detection system also includes display logic configured to display the location of the object.

Abstract: Methods and systems for artificially intelligent security incident and event management using an attention-based deep neural network and transfer learning are disclosed. A method includes: collecting, by a computing device, system and network activity events in bulk; forming, by the computing device, a corpus using the collected system and network activity events; correlating, by the computing device, discrete events of the system and network activity events into offenses; adding, by the computing device, additional features to the corpus representing the offenses and disposition decisions regarding the offenses; training, by the computing device, a deep neural network using the corpus; and tuning, by the computing device, the deep neural network for a monitored computing environment using transfer learning.

Abstract: Methods and apparatuses for environmental control systems are described. In one example, a method includes monitoring a voice communications call between a local call participant located in a building space and a remote call participant. The method includes detecting a change in a user state of the local call participant from the voice communications call. The method further includes adjusting an environmental parameter in the building space responsive to detecting the change in the user state of the local call participant.

Abstract: Methods and apparatuses for addressing open space noise are disclosed. In one example, a method for masking open space noise includes optimizing a recorded naturally occurring sound signal. The method also includes outputting the optimized recorded naturally occurring sound signal from a plurality of speakers distributed in the open space. Further, the method includes displaying a natural system complementing the optimized recorded naturally occurring sound signal.

Abstract: Methods and apparatuses for visualizing distractions are described. In one example, audio data is received from microphones in an open space. A human speech distractor presence is identified by one or more of: (a) detecting voice activity from the audio data, (b) receiving motion sensor data from motion sensors in the open space and detecting motion activity from the motion sensor data, or (c) receiving video sensor data from video sensors in the open space and detecting a human presence from the video data. A source location of the human speech distractor presence within the open space is identified utilizing one or more of the audio data, the motion sensor data, or the video data. A distraction index parameter is generated from the audio data. The distraction index parameter is visually indicated on an open space map at the source location of the human speech distractor presence.

Abstract: Methods and apparatuses for addressing open space noise are disclosed. In one example, a method for masking open space noise includes optimizing a recorded naturally occurring sound signal. The method also includes outputting the optimized recorded naturally occurring sound signal from a plurality of speakers distributed in the open space. Further, the method includes displaying a natural system complementing the optimized recorded naturally occurring sound signal.

Abstract: Methods and apparatuses for noise management are disclosed. In one example, a method includes receiving a plurality of noise level measurements. The method includes receiving a plurality of location data. In one example, the method further includes adjusting an environmental parameter utilizing the noise level measurements. In one example, the method further includes providing location services to a user directing the user to a geographical area having a lower noise level.

Abstract: Methods and apparatuses for visualizing distractions are described. In one example, audio data is received from microphones in an open space. A human speech distractor presence is identified by one or more of: (a) detecting voice activity from the audio data, (b) receiving motion sensor data from motion sensors in the open space and detecting motion activity from the motion sensor data, or (c) receiving video sensor data from video sensors in the open space and detecting a human presence from the video data. A source location of the human speech distractor presence within the open space is identified utilizing one or more of the audio data, the motion sensor data, or the video data. A distraction index parameter is generated from the audio data. The distraction index parameter is visually indicated on an open space map at the source location of the human speech distractor presence.

Abstract: Methods and apparatuses for addressing open space noise are disclosed. In one example, a method for masking open space noise includes outputting from a speaker a speaker sound corresponding to a flow of water, and displaying a water element system, the water element system generating a sound of flowing water.

Abstract: Methods and apparatuses for environmental control systems are described. In one example, a method includes monitoring a voice communications call between a local call participant located in a building space and a remote call participant. The method includes detecting a change in a user state of the local call participant from the voice communications call. The method further includes adjusting an environmental parameter in the building space responsive to detecting the change in the user state of the local call participant.

Abstract: Methods and apparatuses for noise management are disclosed. In one example, a method includes receiving a plurality of noise level measurements taken at a plurality of headsets. The method includes receiving a plurality of location data, including receiving a location data associated with each headset in the plurality of headsets. In one example, the method further includes adjusting an environmental parameter utilizing the noise level measurements. In one example, the method further includes providing location services to a user directing the user to a geographical area having a lower noise level.

Abstract: Methods and apparatuses for addressing open space noise are disclosed. In one example, a method for masking open space noise includes outputting from a speaker a speaker sound corresponding to a flow of water, and displaying a water element system, the water element system generating a sound of flowing water.