Abstract: An adaptive action recognizer for video that performs multiscale spatiotemporal decomposition of video to generate lower complexity video. The adaptive action recognizer has a number of processing pathways, one for each level of video complexity with each processing pathway having a different computational cost. The adaptive action recognizer applies a decision making scheme that encourages using low average computational costs while retaining high accuracy.

Abstract: System and method of analyzing a video, comprising dividing the video into a set of successive basic units; generating semantic tags for the basic units using a set of hierarchical classifier nodes that comprise a parent classifier node and a plurality of child classifier nodes, wherein the basic units are each routed through selected child classifier nodes based on classification of the basic units by the parent classifier node; and generating a semantic topic for the video based on the semantic tags generated for the basic units.

Abstract: Provided herein are hybrid capture-based methods to extract single-stranded DNA or RNA directly from non-treated biospecimens. The methods allow for the detection and analysis of unexplored short single-stranded DNA (sssDNA, mean length 50 nt) and ultrashort single-stranded DNA (ussDNA, mean length 15 nt) of human origin present in the biospecimen. The methods allow the discovery of unexplored short single-stranded DNA (sssDNA) in isolated red blood cells, which were believed to be deprived of nucleic acids because of the lack of a nucleus in mature red blood cells. The DNA or RNA extracted using the disclosed methods can be used as disease prognostic biomarkers and treatment predictive biomarkers.

Abstract: Methods and systems for gesture-based control of a device are described. An input frame is processed to determine a location of a distinguishing anatomical feature in the input frame. A virtual gesture-space is defined based on the location of the distinguishing anatomical feature, the virtual gesture-space being a defined space for detecting a gesture input. The input frame is processed in only the virtual gesture-space, to detect and track a hand. Using information generated from detecting and tracking the at least one hand, a gesture class is determined for the at least one hand. The device may be a smart television, a smart phone, a tablet, etc.

Abstract: This disclosure provides a training method and apparatus, and relates to the artificial intelligence field. The method includes feeding a primary video segment, representative of a concatenation of a first and a second nonadjacent video segments obtained from a video source, to a deep learning backbone network. The method further includes embedding, via the deep learning backbone network, the primary video segment into a first feature output. The method further includes providing the first feature output to a first perception network to generate a first set of probability distribution outputs indicating a temporal location of a discontinuous point associated with the primary video segment. The method further includes generating a first loss function based on the first set of probability distribution outputs. The method further includes optimizing the deep learning backbone network, by backpropagation of the first loss function.

Abstract: A method of enhancing security in object based datastores is provided. The method mounts first and second datastores identified, respectively, by first and second datastore identifiers. The first and second datastores include, respectively, first and second namespace objects that are mapped to first and second subfolders in the first and second datastores. A first file within the first subfolder references a first object via a first object identifier, while a second file within the second subfolder references a second object via a second object identifier. The first and second objects are tagged with the first and second datastores' identifiers. The first and second datastores share an underlying storage and may be configured to have separate access permissions. The method receives a command to access the first object via a datastore identifier, compares the datastore identifier with the first datastore identifier, and if they match, allows access to the first object.

Abstract: A positioning and rescue device for an unmanned underwater vehicle, comprising a battery (1), a switch (2), a protective resistor (3), an electromagnetic relay (4), a master control chip (5), a GPS positioning system (6), an igniter (7), a partition (8), an air bag (9), a shell (10), and a rope (11). The battery (1), the switch (2), the protective resistor (3), the electromagnetic relay (4) and the master control chip (5) are sequentially connected by means of wires to form a series circuit, and the igniter (7) and the GPS positioning system (6) are separately connected to the master control chip (5) by means of wires; two normally open contacts of a control loop of the electromagnetic relay (4) are respectively connected to two ends of a general power supply (15).

Abstract: The present invention provides compounds represented by Formula I, or pharmaceutically acceptable salts, stereoisomers, solvates, hydrates or combination thereof, The invention also provides pharmaceutical compositions comprising these compounds and methods of using this compounds for treating FXR-mediated or TGR5-mediated diseases or conditions.

Abstract: Methods, systems, and media for image searching are described. Images comprising one query image and a plurality of candidate images are received. For each candidate image, a first model similarity measure from an output of a first model configured for scene classification to perceive scenes in the images is determined. Further, for each candidate image of the plurality of candidate images, a second model similarity measure from the output of a second model configured for attribute classification to perceive attributes in the images is determined. For each candidate image of the plurality of candidate images, a similarity agglomerate index of a weighted aggregate of the first model similarity measure and the second model similarity measure is computed. The plurality of candidate images based on the respective similarity agglomerate index of each candidate image are ranked and a first ranked candidate images corresponding to the searched images are generated.

Abstract: A method for dynamic storage object configuration in a datacenter is provided. Embodiments include determining a number of fault domains in a storage cluster that have sufficient storage capacity for creating a storage object. Embodiments include applying a dynamic fault tolerance policy to the number of fault domains that have sufficient capacity for creating the storage object in order to determine a number of host failures to tolerate for the storage object, the dynamic fault tolerance policy specifying a manner of determining, for any respective storage object, a respective number of host failures to tolerate for storing the respective storage object in a respective storage cluster based on at least a respective number of fault domains of the respective storage cluster. Embodiments include implementing the storage object on the storage cluster based on the number of host failures to tolerate for the storage object.

Abstract: Systems, methods, and computer media of processing a video are disclosed. An example method may include: receiving a plurality of video frames of a video; generating a plurality of first input features based on the plurality of video frames; generating a plurality of second input features based on reversing a temporal order of the plurality of first input features; generating a first set of joint attention features based on the plurality of first input features; generating a second set of joint attention features based on the plurality of second input features; and concatenating the first set of joint attention features and the second set of joint attention features to generate a final set of joint attention features.

Abstract: Methods, systems, and media for training deep neural networks for cross-domain few-shot classification are described. The methods comprise an encoder and a decoder of a deep neural network. The training of the autoencoder comprises two training stages. For each iteration in the first training stage, a batch of data samples from the source dataset are sampled and fed to the encoder to generate a plurality of source feature maps, then determining a first training stage loss, which updates the autoencoder's parameters. For each iteration in the second training stage, the novel dataset is split into a support set and a query set. The support set is fed to the encoder to determine a prototype for each class label. The query set is also fed to the encoder to calculate a query set metric classification loss. The query set metric classification loss updates the autoencoder's parameters.

Abstract: The disclosure herein describes mounting a shared data store, remote from a client cluster, as a remote data store on the client cluster. An abstraction interface of the remote data store on the client cluster is configured to receive data operations that are in a local data store-based format. A control path interface is established between the server cluster and the client cluster, and network location data associated with the shared data store is received by the client cluster via the established control path interface. Based on the network location data, a data path interface is established between the client cluster and the shared data store of the server cluster, whereby data operations directed to the abstraction interface of the remote data store on the client cluster are routed to the shared data store of the server cluster via the established data path interface.

Abstract: Methods and systems for updating the weights of a set of convolution kernels of a convolutional layer of a neural network are described. A set of convolution kernels having attention-infused weights is generated by using an attention mechanism based on characteristics of the weights. For example, a set of location-based attention multipliers is applied to weights in the set of convolution kernels, a magnitude-based attention function is applied to the weights in the set of convolution kernels, or both. An output activation map is generated using the set of convolution kernels with attention-infused weights. A loss for the neural network is computed, and the gradient is back propagated to update the attention-infused weights of the convolution kernels.

Abstract: System and method of analyzing a video, comprising dividing the video into a set of successive basic units; generating semantic tags for the basic units using a set of hierarchical classifier nodes that comprise a parent classifier node and a plurality of child classifier nodes, wherein the basic units are each routed through selected child classifier nodes based on classification of the basic units by the parent classifier node; and generating a semantic topic for the video based on the semantic tags generated for the basic units.

Abstract: An expansion tool includes a housing, a collar rotatably coupled to the housing, a plurality of jaws coupled for co-rotation with the collar, a mandrel movable relative to the housing between a retracted position and an extended position to expand the jaws, and a drive mechanism including a rotatable cam. Rotation of the cam moves the mandrel between the retracted position and the extended position. The expansion tool further includes an indexing gear configured to incrementally receive torque from the drive mechanism such that continuous rotation of the drive mechanism incrementally rotates the indexing gear, and a clutch assembly including a clutch gear meshed with the indexing gear, a clutch cover surrounding the clutch gear, and a plurality of rolling elements disposed between the clutch gear and the clutch cover. The clutch cover is drivably coupled to the collar such that rotation of the clutch cover rotates the collar.

Abstract: The disclosure herein describes mounting a shared data store, remote from a client cluster, as a remote data store on the client cluster. An abstraction interface of the remote data store on the client cluster is configured to receive data operations that are in a local data store-based format. A control path interface is established between the server cluster and the client cluster, and network location data associated with the shared data store is received by the client cluster via the established control path interface. Based on the network location data, a data path interface is established between the client cluster and the shared data store of the server cluster, whereby data operations directed to the abstraction interface of the remote data store on the client cluster are routed to the shared data store of the server cluster via the established data path interface.

Abstract: Methods, processing units and media for multi-bandwidth separated feature extraction convolution in a neural network are described. A convolution block splits input channels of an activation map into multiple branches, each branch undergoing convolution at a different bandwidth by using down-sampling of the inputs. The outputs are concatenated by up-sampling the outputs of the low-bandwidth branches using pixel shuffling. The concatenation operation may be a shuffled concatenation operation that preserves separated multi-bandwidth feature information for use by subsequent layers of the neural network. Embodiments are described which apply frequency-based and magnitude-based attention to the weights of the convolution kernels based on the frequency band locations of the weights.

Abstract: Provided herein are methods of quantitative amplicon sequencing, for labeling each strand of targeted genomic loci in a DNA sample with an oligonucleotide barcode sequence by polymerase chain reaction, and amplifying the genomic region(s) for high-throughput sequencing. The methods can be used for the simultaneous detection of copy number variation (CNV) in a set of genes of interest, by quantifying the frequency of extra copies of each gene. In addition, these methods provide for the quantitation of the allele ratio of different genetic identities for targeted genomic loci using multiplexed PCR. In addition, these methods provide for the detection of mutations and quantitation of the variant allele frequency.