Abstract: An artificial intelligence system for identifying attributes in an image. The system may include a processor in communication with a client device; and a storage medium. The storage medium may store instructions that, when executed, configure the processor to perform operations including: extracting first features; categorizing the first images in a first group or a second group; modifying first metadata associated with each image in the first images to include a binary label; calculating a classification function; classifying a second plurality of images using the classification function; extracting second features from the second images classified in the first group; categorizing the second images in the first group by attribute; calculating an attribute identification function that identifies attributes of the second images; and identifying at least one attribute associated with a client image using the attribute identification function, the client image being received from the client device.

Abstract: The present disclosure relates to systems and methods for generating real-time quotes using machine learning algorithms. The system may include a processor in communication with a client device, and a storage medium storing instructions that, when executed, cause the processor to perform operations including: receiving an image of a vehicle from the client device, extracting one or more features from the image, based on the extracted features and using a machine learning algorithm, identifying one or more attributes of the vehicle, based on the identified attributes of the vehicle, determining a make and a model of the vehicle, obtaining comparison information based at least in part on the determined make and model, estimating a quote for the vehicle based on the comparison information; and transmitting the estimated quote for display on the client device.

Abstract: A system for monitoring a device includes, among other things, at least one sensor adjacent a device, and a controller coupled to the at least one sensor. The controller includes a comparison module operable to determine that at least one predetermined criterion is met in response to comparing one or more values sensed by the least one sensor, the at least one predetermined criterion based on a total number of cycles associated with operation of the device. A method of monitoring a device is also disclosed.

Abstract: Disclosed embodiments provide devices, methods, and computer-readable storage media for determining information of an object from a captured image. Further, the disclosed device responds to a user input by capturing, with the camera, image data representing an object. The device then transmits, via a messaging application through a network interface to a server, the image data and a request for information relating to the object. The object information is received via the messaging application through the network from the server and is displayed on the display screen.

Abstract: The present disclosure relates to interactive projection systems. In one implementation, an interactive projection system for a vehicle window may include a film having a plurality of sensors embedded therein, the plurality of sensors configured to detect local pressure disturbance on the film; a projector configured to project a user interface onto the film; and at least one processor. The at least one processor may be configured to perform operations, including receiving a detection of a local pressure disturbance from at least one of the plurality of sensors, based on a location of the detected local pressure disturbance, determining a change in the user interface, and transmitting a command to the projector to modify a projected user interface according to the determined change.

Abstract: Example super-resolution microscopy systems are described herein that are configured for relatively high throughput. The disclosed microscopy systems can be to generate an array of sub-diffraction activated areas for imaging. The microscopy systems can be to utilize imaging techniques that employ time delay integration to build up super-resolution images over time. The disclosed microscopy systems can utilize long-lived fluorophores in conjunction with wide field and patterned illumination to generate super-resolution images of a sample with relatively high throughput.

Abstract: A coupler assembly (60) for a sub-sea connector including a coupler (18) having an abutment (76) radially outwardly from the coupler body (64), and a radially inwardly extending groove (78) in the coupler body that is longitudinally spaced apart from the abutment. The abutment (76) is configured to engage the rear side of the plate when the coupler is inserted through a rearward opening in the plate. The groove (78) may be longitudinally spaced apart from the abutment such that, when the abutment is engaged with the rear of the plate, the groove is positioned forwardly of the front side of the plate sufficiently to allow a portion of a mounting ring (82) to be inserted into the groove with a portion of the mounting ring protruding radially outwardly from the body to engage an abutment surface at the front side of the plate, thereby restricting axial movement of the body relative to the plate.

Abstract: The present invention relates to a deodorant composition comprising an oxazolidine- or, a thiazolidine-carboxylic acid compound, a cosmetic carrier and optionally a fragrance. The invention also relates to a manufacturing process for the deodorant composition, a method of treating malodour and a method of screening deodorant actives as well as inhibiting a Staphylococcus hominis C-S ?-lyase.

Abstract: Systems and methods for generating realtime quotes using machine learning algorithms are provided. The system includes a processor in communication with a client device, and a storage medium storing instructions that, when executed, cause the processor to perform operations including: receiving an image of a vehicle from the client device, extracting one or more features from the image, and identifying one or more attributes of the vehicle. The operations also include: based on the identified attributes, determining a make and a model of the vehicle, obtaining comparison information based at least in part on the determined make and model, estimating and transmitting a quote for the vehicle for display on the client device, based on the comparison information.

Abstract: An association metric for record attributes associated with cardinalities that are not necessarily the same is used for training and/or applying an entity resolution (ER) model. A pair of records includes (a) a first record indicating a first set of values for a first attribute and (b) a second record indicating a second set of values for a second attribute. Each of the first set of values and each of the second set of values are compared to determine individual association metrics. A first-level reduction operation is applied to subsets of the individual association metrics to determine reduced association metrics. A second-level reduction operation is applied to the reduced association metrics to determine an association metric, for the pair of records, for training and/or applying an ER model.

Abstract: Techniques for generating and presenting graph data structures representing patient visit paths and physician referral networks are disclosed. A system generates one or more graph data structures representing one or more referred visit paths and/or inferred visit paths. Based on the graph data structures representing the visit paths, the system generates another graph data structure representing a physician network. A user interface presents a graph representing the physician network. Based on the presented graph, a user may thereby determine influential levels of different physicians for referring one or more patients to a particular physician.

Abstract: An image error identification system retrieves an image associated with a vehicle listing and uses various machine learning models to classify the image and generate identification data that may include a vehicle make, model, trim level, and/or various features of the vehicle present in the image. The identification data is compared to the rest of the vehicle listing to detect a mismatch between the image and the vehicle listing. An alert is generated, when a mismatch is detected, indicating the one of the image or the data in the vehicle listing is incorrect.

Abstract: A method of manufacturing a hypoid gear includes face hobbing a gear blank and forming a green hypoid gear with gear teeth, heat treating the green hypoid gear to form a heat treated hypoid gear with heat treated gear teeth, and hard hobbing the heat treated gear teeth to form a hard finished hypoid gear. Critical non-tooth features on the heat treated hypoid gear are hard finished. Also, the critical non-tooth features on the heat treated hypoid gear can be hard finished prior to hard hobbing the heat treated gear teeth. The heat treating includes at least one of carburizing and induction hardening the green hypoid gear, a surface of the heat treated gear teeth has a hardness greater than or equal to 58 HRC, and the hard hobbing removes heat distortion from the heat treated gear teeth.

Abstract: An image information overlay system retrieves an image associated with a vehicle listing and uses machine learning models to classify the image, generating identification data that may comprise a vehicle make and model, a feature or part of the vehicle present in the image, and a location of the vehicle feature or part. The identification data or an individual identifier of the vehicle, such as a Vehicle Identification Number (VIN), may be used to retrieve overlay information related to the vehicle make and model, such as recalls or known maintenance issues or information specific to the vehicle, such as mileage, accident reports, or ownership history. The overlay information is displayed on the image as an overlay at the location of the vehicle feature or part corresponding to the overlay information.

Abstract: Systems and methods for processing an image using machine learning are provided. The system includes a processor in communication with a client device, and a storage medium storing instructions that, when executed, cause the processor to perform operations including: receiving an image of a vehicle from the client device; extracting one or more features from the image; determining a make and a model of the vehicle based on the extracted features and using a machine learning algorithm. The operations also include: obtaining user information relating to a financing request for the vehicle; determining and transmitting to the client device a real-time quote for the vehicle based on the make, the model, and the user information.

Abstract: The present invention relates to an extendable folding saw that is lightweight and compact when retracted yet rigid when extended. In one embodiment, the extendable folding saw can have a folding saw and a removably attached extension. The folding saw can have a grip and a pivotally attached saw. The extension can comprise several members that are compactable to a length not much greater than the length of the longest individual member. The members of the extension can have a generally I shaped profile. The extension rod can be attached to the folding saw in a snap-fitting manner for use. A retracted folding saw can be snapped side-by-side to a retracted to extension rod for storage.

Abstract: The present invention relates to products and methods for the prevention and amelioration of bacterial contamination and degradation (spoiling) of biological material, particularly foodstuffs. In particular, the invention provides a product comprising an envelope of material defining a lumen wherein the lumen contains bacteriophage covalently attached to a surface.

Abstract: A computer system receives a request to locate a vehicle within a facility. The computer system parses the request to identify one or more characteristics of the vehicle. The computer system identifies a sensor corresponding to the vehicle based on the one or more characteristics of the vehicle. The computer system identifies a most recent location of the vehicle based on the last registered position of the vehicle within the facility. The computer system transmits a signal to a parking spot sensor at the most recent location of the vehicle in the facility. The computer system receives the unique identification. The computer system determines that the unique identification of the vehicle sensor co-located with the parking spot sensor matches the sensor of the requested vehicle. The computer system reports to the user a current location of the vehicle within the facility based on a location of the parking spot sensor.