Abstract: Embodiments of the present disclosure include insulating devices, motor stators, and motors. The insulating device comprises at least one insulating frame and at least one insulating wrapping layer; the insulating frame has at least two support ends with the same orientation and arranged at intervals; the insulating wrapping layer is a cylindrical structure, and at least one open end of the cylindrical structure wraps the at least two support ends on the insulating frame and is supported by the support ends to form a winding space. The insulating device can balance the copper wire space factor and the manufacturing cost.

Abstract: In various examples, a single camera is used to capture two images of a scene from different locations. A trained neural network, taking the two images as inputs, outputs a scene structure map that indicates a ratio of height and depth values for pixel locations associated with the images. This ratio may indicate the presence of an object above a surface (e.g., road surface) within the scene. Object detection then can be performed on non-zero values or regions within the scene structure map.

Abstract: In various examples, a single camera is used to capture two images of a scene from different locations. A trained neural network, taking the two images as inputs, outputs a scene structure map that indicates a ratio of height and depth values for pixel locations associated with the images. This ratio may indicate the presence of an object above a surface (e.g., road surface) within the scene. Object detection then can be performed on non-zero values or regions within the scene structure map.

Abstract: In order to enable long-term stabilization of rapamycin contained in a liquid formulation, a formulation sealing vessel of the present invention includes: a sealed vessel body in which a liquid formulation containing 2% (w/w) rapamycin or a salt thereof, 94% (w/w) polyethylene glycol, and 4% (w/w) ethanol is sealed, the sealed vessel body having a volume of 0.1 mL to 1.0 mL, the liquid formulation containing no antioxidant, and the liquid formulation having a total volume of 0.02 mL to 1.0 mL.

Abstract: In various examples, a single camera is used to capture two images of a scene from different locations. A trained neural network, taking the two images as inputs, outputs a scene structure map that indicates a ratio of height and depth values for pixel locations associated with the images. This ratio may indicate the presence of an object above a surface (e.g., road surface) within the scene. Object detection then can be performed on non-zero values or regions within the scene structure map.

Abstract: In order to enable long-term stabilization of rapamycin contained in a liquid formulation, a formulation sealing vessel of the present invention includes: a sealed vessel body in which a liquid formulation containing 2% (w/w) rapamycin or a salt thereof, 94% (w/w) polyethylene glycol, and 4% (w/w) ethanol is sealed, the sealed vessel body having a volume of 0.1 mL to 1.0 mL, the liquid formulation containing no antioxidant, and the liquid formulation having a total volume of 0.02 mL to 1.0 mL.

Abstract: An example method is provided in according with one implementation of the present disclosure. The method comprises generating a base image representing a location of a wireless-enabled device with data from a plurality of wireless beacons and generating an image fingerprint for the location of the wireless-enabled device by using the base image. The method further comprises comparing the image fingerprint for the location of the wireless-enabled device with a plurality of existing image fingerprints associated with the plurality of wireless beacons, and determining a location of the wireless-enabled device based on the comparison.

Abstract: A method is disclosed of recognizing a logo of a vehicle. The method including obtaining a limited number of high resolution logos; populating a training dataset for each of the limited number of high resolution logos using gamma transformations; obtaining a low resolution image of a vehicle; and matching the low resolution image of the vehicle with the training dataset.

Abstract: Retrieval of images of objects from a large-scale database of object images, based on a query image. The database may, for example, contain images of objects such as faces, vehicles, people and luggage. Semantic attributes such as doors or windows in the case of vehicles are used as high level semantic cues to determine identities of objects in the images. Salient visual characteristics of the images are labeled with attribute information, and a transformation is learned so as to transform the labeled visual characteristics into a discrimination vector that discriminates between the labels. A similarity metric is learned using the discrimination vectors, such that different images depicting the same object are determined to be close while those having different objects are determined to be far apart. Candidates are retrieved based on a query image, and a re-ranking step may be applied to improve results. Validation experiments are described.

Abstract: An example method is provided in according with one implementation of the present disclosure. The method comprises generating a base image representing a location of a wireless-enabled device with data from a plurality of wireless beacons and generating an image fingerprint for the location of the wireless-enabled device by using the base image. The method further comprises comparing the image fingerprint for the location of the wireless-enabled device with a plurality of existing image fingerprints associated with the plurality of wireless beacons, and determining a location of the wireless-enabled device based on the comparison.

Abstract: A method is disclosed of recognizing a logo of a vehicle. The method including obtaining a limited number of high resolution logos; populating a training dataset for each of the limited number of high resolution logos using gamma transformations; obtaining a low resolution image of a vehicle; and matching the low resolution image of the vehicle with the training dataset.

Abstract: A new image-based representation and an associated reference image is disclosed called the emotion avatar image (EAI), and the avatar reference, respectively, which leverages the out-of-plane head rotation. The method is not only robust to outliers but also provides a method to aggregate dynamic information from expressions with various lengths. The approach to facial expression analysis can consist of the following steps: 1) face detection; 2) face registration of video frames with the avatar reference to form the EAI representation; 3) computation of features from EAI using both local binary patterns and local phase quantization; and 4) the classification of the feature as one of the emotion type by using a linear support vector machine classifier.

Abstract: A new image-based representation and an associated reference image is disclosed called the emotion avatar image (EAI), and the avatar reference, respectively, which leverages the out-of-plane head rotation. The method is not only robust to outliers but also provides a method to aggregate dynamic information from expressions with various lengths. The approach to facial expression analysis can consist of the following steps: 1) face detection; 2) face registration of video frames with the avatar reference to form the EAI representation; 3) computation of features from EAI using both local binary patterns and local phase quantization; and 4) the classification of the feature as one of the emotion type by using a linear support vector machine classifier.

Abstract: Retrieval of images of objects from a large-scale database of object images, based on a query image. The database may, for example, contain images of objects such as faces, vehicles, people and luggage. Semantic attributes such as doors or windows in the case of vehicles are used as high level semantic cues to determine identities of objects in the images. Salient visual characteristics of the images are labeled with attribute information, and a transformation is learned so as to transform the labeled visual characteristics into a discrimination vector that discriminates between the labels. A similarity metric is learned using the discrimination vectors, such that different images depicting the same object are determined to be close while those having different objects are determined to be far apart. Candidates are retrieved based on a query image, and a re-ranking step may be applied to improve results. Validation experiments are described.

Abstract: Aspects of the invention include methods of generating models for scoring patient notes. The methods include receiving a sample of patient notes, extracting a plurality of ngrams from the sample of patient notes, clustering the plurality of extracted ngrams that meet a similarity threshold into a plurality of lists, identifying a feature associated with each of the plurality of lists based on the ngrams in that list and designating at least one ngram in each list as evidence of the feature associated with that list. The identified features and designated ngram are stored in models for scoring patient notes.