Abstract: A method and system of detecting abnormalities captured in a medical image are provided. A medical image is received having one or more lesions and one or more interferences. One or more convolution layers are applied to the medical image to create one or more feature maps, respectively. A region proposal network (RPN) is applied to each of the one or more feature maps to create a bounding box around each lesion and interference. For each bounding box, an object in the bounding box is classified as a lesion, an interference, or a background. Each object that is incorrectly classified as a lesion but determined to be an interference, is stored as a hard-negative example to be part of a training set for a next application of the RPN.

Abstract: The present disclosure relates to a method and system for generating a road network. An embodiment of the present invention provides a method comprising: identifying a target area to be refined in a road network skeleton; and refining the target area using at least one trajectory associated with the target area to generate the road network. Another embodiment of the present invention provides a corresponding system.

Abstract: A method, system, and computer program product, include receiving a plurality of requests for dynamic context information from a plurality of road segments, determining whether the plurality of road segments are included in a same cluster of road segments in a road network generated by clustering road segments in the road network based on connectivity of the road network; and consolidating the plurality of requests to generate a consolidated request in response to determining that the plurality of road segments are included in the same cluster.

Abstract: Techniques facilitating object classification based on decoupling a background from a foreground of an image are provided. A system can comprise a memory that stores computer executable components and a processor that executes the computer executable components stored in the memory. The computer executable components can comprise a model that is trained on images that comprise respective backgrounds and respective foregrounds that are interleaved. The model can be trained to detect the respective backgrounds with a defined confidence level. The computer executable components can also comprise an extraction component that employs the model to identify a background of a received image based on the defined confidence level and to decouple a foreground object of the received image based on identification of the background of the received image.

Abstract: A method of generating a predictor to classify data includes: training each of a plurality of first classifiers arranged in a first level on current training data; operating each classifier of the first level on the training data to generate a plurality of predictions; combining the current training data with the predictions to generated new training data; and training each of a plurality of second classifiers arranged in a second level on the new training data. The first classifiers are classifiers of different classifier types, respectively and the second classifiers are classifiers of the different classifier types, respectively.

Abstract: A system for tracking cumulative motor vehicle risk includes a satellite navigation system receiver disposed within a motor vehicle and configured to determine a present location of the motor vehicle. A computer processor receives the determined present location of the motor vehicle from the satellite navigation system receiver and generates a traveled route therefrom. A first computer server receives a plurality of motor vehicle claims records, determines a plurality of motor vehicle accident locations from the plurality of motor vehicle claims records, and generates a motor vehicle accident heat map from the plurality of motor vehicle accident locations. A second computer server determines a cumulative risk exposure of the motor vehicle based on the generated traveled route and the generated motor vehicle accident heat map.

Abstract: Techniques facilitating attention based sequential image processing are provided. A system can comprise a memory that stores computer executable components and a processor that executes the computer executable components stored in the memory. The computer executable components can comprise an initialization component that can perform self-attention based training on a model that comprises context information associated with a sequence of images. Images of the sequence of images can be selected during the self-attention based training. The computer executable components can also comprise a localization component that can extract local information from the images selected during the self-attention based training based on the context information. In addition, the computer executable components can also comprise an integration component that can update the model based on an end-to-end integrated attention training framework comprising the context information and the local information.

Abstract: In one embodiment, a computer-implemented method includes receiving training data including a plurality of records, each record having a plurality of attributes. The training data is horizontally parallelized across two or more processing elements. This horizontal parallelizing includes dividing the training data into two or more subsets of records; assigning each subset of records to a corresponding processing element of the two or more processing elements; transmitting each subset of records to its assigned processing element; and sorting, at the two or more processing elements, the two or more subsets of records to two or more candidate leaves of a decision tree. The output from horizontally parallelizing is converted into input for vertically parallelizing the training data. The training data is vertically parallelized across the two or more processing elements. The decision tree is grown based at least in part on the horizontally parallelizing, the converting, and the vertically parallelizing.

Abstract: In one embodiment, a computer-implemented method includes receiving training data including a plurality of records, each record having a plurality of attributes. The training data is horizontally parallelized across two or more processing elements. This horizontal parallelizing includes dividing the training data into two or more subsets of records; assigning each subset of records to a corresponding processing element of the two or more processing elements; transmitting each subset of records to its assigned processing element; and sorting, at the two or more processing elements, the two or more subsets of records to two or more candidate leaves of a decision tree. The output from horizontally parallelizing is converted into input for vertically parallelizing the training data. The training data is vertically parallelized across the two or more processing elements. The decision tree is grown based at least in part on the horizontally parallelizing, the converting, and the vertically parallelizing.

Abstract: Techniques facilitating attention based sequential image processing are provided. A system can comprise a memory that stores computer executable components and a processor that executes the computer executable components stored in the memory. The computer executable components can comprise an initialization component that can perform self-attention based training on a model that comprises context information associated with a sequence of images. Images of the sequence of images can be selected during the self-attention based training. The computer executable components can also comprise a localization component that can extract local information from the images selected during the self-attention based training based on the context information. In addition, the computer executable components can also comprise an integration component that can update the model based on an end-to-end integrated attention training framework comprising the context information and the local information.

Abstract: A computer-implemented method is presented for inferring passenger routes in a subway system. The method includes identifying, via an imaging device, a target passenger within the subway system, employing an exiting flow extractor to determine passenger exiting waves, employing an exiting wave identifier to mark an exiting wave of the passenger exiting waves including the target passenger, employing a supporting evidence backtracer to determine an entrance gate for each of the passengers in the marked exiting wave including the target passenger, determining a route probability for each of the passengers in the marked exiting wave including the target passenger via voting or distribution estimation processing, and employing a most probable route inferer to infer a route of the target passenger based on an aggregate route probability for all the passengers in the marked exiting wave.

Abstract: The disclosure involves a method comprising clustering a plurality of observation samples related to historical travel demands into one or more clusters; for each cluster, constructing an actual probability distribution of the historical travel demands corresponding to the observation samples in the cluster; for each cluster, inputting observation samples in the cluster into a prediction model for predicting future travel demands to produce a result of prediction; for each cluster, computing a predicted probability distribution of the historical travel demands corresponding to the observation samples in the cluster based on the result of prediction; for each cluster, evaluating a difference between the actual probability distribution and the predicted probability distribution of the cluster; and modifying the prediction model so that a statistical sum of the differences for the one or more clusters is decreased.

Abstract: A system, a computer readable storage medium, and a method for detecting insurance fraud or for comparing references use visual analytics-based techniques. The method can include identifying a scratch and a scratch location on a vehicle in a 3-dimensional rendering in comparison to a base image or in comparison to a stored image in a database, comparing one or more features of the scratch such as color features of the scratch in the scratch location in comparison to the scratch location or comparing one or more texture features of the scratch in the scratch location in comparison to the scratch location in the base image or the stored image. The method can further generate a similarity calculation based on the one or more comparisons for the scratch, the scratch location, the one or more scratch features of the scratch and presents a result in response to the similarity calculation.

Abstract: The present invention provides polymer blends that can be used in a multilayer structure and to multilayer structures comprising one or more layers formed from such blends. In one aspect, a polymer blend comprises (a) a copolymer comprising ethylene and at least one of acrylic acid and methacrylic acid having an acid content of 2 to 21 weight percent based on the weight of the copolymer, wherein the amount of copolymer (a) comprises 20-80 weight percent of the blend based on the total weight of the blend, and (b) a copolymer comprising ethylene and at least one of methyl acrylate and ethyl acrylate having an acrylate content of 5 to 30 weight percent based on the weight of the copolymer, wherein the amount of copolymer (b) comprises 10 to 50 weight percent of the blend based on the total weight of the blend, wherein the amount of copolymer (a) and copolymer (b) is at least 70 weight percent of the blend based on the total weight of the blend.

Abstract: Provided herein are compounds, derivatives thereof, composition comprising one or more of said compounds and derivatives, and methods for prevention and/or treatment of microbial infections and/or related diseases or conditions. The present compounds and/or derivatives thereof can be represented by Formula (I): The present methods include administering to a subject an effective amount of one or more compounds of Formula (I). In one embodiment, said microbial infections are bacterial infections. More specifically, said bacterial infections are staphylococcal infections.

Abstract: A mechanism is provided in a data processing system for distributed tree learning. A source processing instance distributes data record instances to a plurality of model update processing items. The plurality of model update processing items determine candidate leaf splitting actions in a decision tree in parallel based on the data record instances. The plurality of model update processing items send the candidate leaf splitting actions to a plurality of conflict resolve processing items. The plurality of conflict resolve processing items identifies conflict leaf splitting actions. The plurality of conflict resolve processing items applies tree structure changes to the decision tree in the plurality of model update processing items.

Abstract: A mechanism is provided in a data processing system for distributed tree learning. A source processing instance distributes data record instances to a plurality of model update processing items. The plurality of model update processing items determine candidate leaf splitting actions in a decision tree in parallel based on the data record instances. The plurality of model update processing items send the candidate leaf splitting actions to a plurality of conflict resolve processing items. The plurality of conflict resolve processing items identifies conflict leaf splitting actions. The plurality of conflict resolve processing items applies tree structure changes to the decision tree in the plurality of model update processing items.

Abstract: A sensor circuit that is capable of sensing of neural action potentials is disclosed. The circuit can be designed to minimize power dissipation and total silicon area so that it can be incorporated into a massively parallel sensor array and ultimately implanted in the body (e.g. into the brain) in a safe manner. The circuit can also be designed to be tunable such that it can be optimized in silico prior to fabrication, and can be optimized through the use of controllable current sources after fabrication.

Abstract: Apparatuses and methods for pipelining memory operations with error correction coding are disclosed. A method for pipelining consecutive write mask operations is disclosed wherein a second read operation of a second write mask operation occurs during error correction code calculation of a first write mask operation. The method may further including writing data from the first write mask operation during the error correction code calculation of the second write mask operation. A method for pipelining consecutive operations is disclosed where a first read operation may be cancelled if the first operation is not a write mask operation. An apparatus including a memory having separate global read and write input-output lines is disclosed.

Abstract: The invention discloses a multi-stage suspension magnetizing roasting-magnetic separation system and method for refractory iron ore, which belongs to the field of mineral processing technology. This system comprises multistage suspension preheater, multistage suspension oxidizer, multistage suspension redactor, on-line grade analyzer, ore-like splitter, magnetic separator, dust remover, roots blower and other components and connection modes. The refractory iron ore treated by the present method can be produced to homogeneous magnetite or maghemite accurately, and through magnetic separation, on-line grade analyzer detection and ore-like splitter, the concentrate powder which reach the set grade can be obtained, and the unqualified ore powder enters the next stage of oxidation-reduction-magnetic separation-split treatment.