Abstract: A method, system and computer program for categorizing heart diseases is presented. An example method includes receiving a series of cardiac images of a heart, the cardiac images including a myocardium, and interior fibrous muscles of the heart. Cardiac images are segmented, into a myocardium segmentation showing an anatomical shape and a motion of the myocardium, and an interior fibrous muscles segmentation showing an anatomical shape and a motion of the interior fibrous muscles. The myocardium segmentation is converted into a regional characterization of the anatomical shape and motion of the myocardium. The interior fibrous muscles segmentation is converted to a regional characterization of the anatomical shape and motion of the interior fibrous muscles. Heart conditions are characterized based on the regional characterizations of the anatomical shape and the motion of the myocardium and the interior fibrous muscles.

Abstract: Methods, systems, and computer program products for category oversampling for imbalanced machine learning are provided herein. A method includes identifying an anchor data point in a given class of data points underrepresented among multiple classes in a data set of multiple data points, wherein each data point represent a vector; determining a number of data points in the given class that neighbor the anchor data point, wherein the number comprises two or more; applying a weight to (i) each of the number of data points to create a number of weighted neighboring data points, and (ii) the anchor data point to create a weighted anchor data point, wherein the sum of all weights is equal to one; performing a vector summation by summing the number of weighted neighboring data points and the weighted anchor data point; and generating a synthetic data point based on said vector summation.

Abstract: Systems and articles of manufacture for image segmentation are provided herein, and include creating an anatomical model from training data comprising one or more imaging modalities, generating one or more simulated images in a target modality based on the anatomical model and one or more principles of physics pertaining to image contrast generation, and comparing the one or more simulated images to an unlabeled input image of a given imaging modality to determine a simulated image of the one or more simulated images to represent the unlabeled input image.

Abstract: Techniques for generating cross-modality semantic classifiers and using those cross-modality semantic classifiers for ground level photo geo-location using digital elevation are provided. In one aspect, a method for generating cross-modality semantic classifiers is provided. The method includes the steps of: (a) using Geographic Information Service (GIS) data to label satellite images; (b) using the satellite images labeled with the GIS data as training data to generate semantic classifiers for a satellite modality; (c) using the GIS data to label Global Positioning System (GPS) tagged ground level photos; (d) using the GPS tagged ground level photos labeled with the GIS data as training data to generate semantic classifiers for a ground level photo modality, wherein the semantic classifiers for the satellite modality and the ground level photo modality are the cross-modality semantic classifiers.

Abstract: Methods for image segmentation are provided herein. A method includes creating an anatomical model from training data comprising one or more imaging modalities, generating one or more simulated images in a target modality based on the anatomical model and one or more principles of physics pertaining to image contrast generation, and comparing the one or more simulated images to an unlabeled input image of a given imaging modality to determine a simulated image of the one or more simulated images to represent the unlabeled input image.

Abstract: Techniques for spatial semantic attribute matching on image regions for location identification based on a reference dataset are provided. In one aspect, a method for matching images from heterogeneous sources is provided. The method includes the steps of: (a) parsing the images into different semantic labeled regions; (b) creating a list of potential matches by matching the images based on two or more of the images having same semantic labeled regions; and (c) pruning the list of potential matches created in step (b) by taking into consideration spatial arrangements of the semantic labeled regions in the images.

Abstract: Techniques for spatial semantic attribute matching on image regions for location identification based on a reference dataset are provided. In one aspect, a method for matching images from heterogeneous sources is provided. The method includes the steps of: (a) parsing the images into different semantic labeled regions; (b) creating a list of potential matches by matching the images based on two or more of the images having same semantic labeled regions; and (c) pruning the list of potential matches created in step (b) by taking into consideration spatial arrangements of the semantic labeled regions in the images.

Abstract: Methods for removing sulfur dioxide front a gas stream are disclosed. A method may include passing a gas stream comprising SO2 through a gas scrubbing apparatus. A scrubbing liquor comprising hydroxide ions and at least one oxidation catalyst may be flowed into the gas scrubbing apparatus, thereby contacting the gas stream with the scrubbing liquor. In response to the contacting, at least 90 wt. % of the sulfur dioxide may be removed from the gas stream. Concomitant to the contacting, at least some of the sulfur dioxide may react with at least some of the hydroxide ions, thereby forming sulfite ions in the scrubbing liquor. Some of the sulfite ions may be oxidized, via the oxidation catalyst, thereby forming sulfate ions in the scrubbing liquor. A used scrubbing liquor may be discharged from the scrubbing apparatus.

Abstract: The instant disclosure is directed towards methods of treating wastewater and related systems, where the system includes: an aerated zone comprising media (e.g. with sufficient surface area and porosity to sustain microbial growth and retain bacteria) and a non-aerated zone comprising compost, wherein the system is configured to remove emulsified oil (e.g. and grease) from a wastewater stream.

Abstract: Methods, systems, and computer program products for static image segmentation are provided herein. A method includes segmenting a static image containing a target object into multiple regions based on one or more visual features of the static image; analyzing video content containing the target object to determine a similarity metric across the multiple segmented regions based on motion information associated with each of the multiple segmented regions; and applying the similarity metric to the static image to identify two or more of the multiple segmented regions as being portions of the target object.

Abstract: The instant disclosure relates to methods, systems, and apparatus for polishing wastewater (i.e. non-potable water) using filtration media. More particularly, the instant disclosure relates to wastewater polishing using a bed of mixed metal oxides under certain operating conditions to remove a plurality of contaminants from a wastewater stream.

Abstract: A method, system and computer program for categorizing heart diseases is presented. An example method includes receiving a series of cardiac images of a heart, the cardiac images including a myocardium, and interior fibrous muscles of the heart. Cardiac images are segmented, into a myocardium segmentation showing an anatomical shape and a motion of the myocardium, and an interior fibrous muscles segmentation showing an anatomical shape and a motion of the interior fibrous muscles. The myocardium segmentation is converted into a regional characterization of the anatomical shape and motion of the myocardium. The interior fibrous muscles segmentation is converted to a regional characterization of the anatomical shape and motion of the interior fibrous muscles. Heart, conditions are characterized based on the regional characterizations of the anatomical shape and the motion of the myocardium and the interior fibrous muscles.

Abstract: A computer implemented method, apparatus, and computer program product code for temporal, event-based video fingerprinting. In one embodiment, events in video content are detected. The video content comprises a plurality of video frames. An event represents discrete points of interest in the video content. A set of temporal, event-based segments are generated using the events. Each temporal, event-based segment is a segment of the video content covering a set of events. A time series signal is derived from each temporal, event-based segment using temporal tracking of content-based features of a set of frames associated with the each temporal, event-based segment. A temporal segment based fingerprint is extracted based on the time series signal for the each temporal, event-based segment to form a set of temporal segment based fingerprints associated with the video content.

Abstract: Techniques for generating cross-modality semantic classifiers and using those cross-modality semantic classifiers for ground level photo geo-location using digital elevation are provided. In one aspect, a method for generating cross-modality semantic classifiers is provided. The method includes the steps of: (a) using Geographic Information Service (GIS) data to label satellite images; (b) using the satellite images labeled with the GIS data as training data to generate semantic classifiers for a satellite modality; (c) using the GIS data to label Global Positioning System (GPS) tagged ground level photos; (d) using the GPS tagged ground level photos labeled with the GIS data as training data to generate semantic classifiers for a ground level photo modality, wherein the semantic classifiers for the satellite modality and the ground level photo modality are the cross-modality semantic classifiers.

Abstract: A system, method and computer program product for relating corresponding points in images with an overlapping scene. An example method includes generating transformed images of a target image using different image transformations for each of transformed images. Texture descriptors are extracted for feature points in the transformed images and a reference image. Matched feature points are identified and inliers from matched feature points are selected. An aligning transformation is generated using the inliers for at least one of the transformed images. A panorama image is created with the target image and reference image after the images are aligned.

Abstract: Fertilizer compositions are provided, where a fertilizer composition includes: an inner portion including a nitrogen containing material; and an outer portion covering the inner portion, the outer portion including a release agent (e.g. HTC, BR).

Abstract: Techniques for detecting an event via social media content. A method includes obtaining multiple images from at least one social media source; extracting at least one visual semantic concept from the multiple images; differentiating an event semantic concept signal from a background semantic concept signal to detect an event in the multiple images; retrieving one or more images associated with the event semantic concept signal; grouping the one or more images associated with the event semantic concept signal; annotating the group of one or more images with user feedback; and displaying the annotated group of one or more images as a visual description of the detected event.

Abstract: Techniques for detecting an event via social media content. A method includes obtaining multiple images from at least one social media source, extracting at least one visual semantic concept from the multiple images, differentiating an event semantic concept signal from a background semantic concept signal to detect an event in the multiple images, and retrieving one or more images associated with the event semantic concept signal for presentation as a visual description of the detected event.

Abstract: Interoperability is enabled between participants in a network by determining values associated with a value metric defined for at least a portion of the network. Information flow is directed between two or more of the participants based at least in part on semantic models corresponding to the participants and on the values associated with the value metric. The semantic models may define interactions between the participants and define at least a portion of information produced or consumed by the participants. The determination of the values and the direction of the information flow may be performed multiple times in order to modify the one or more value metrics. The direction of information flow may allow participants to be deleted from the network, may allow participants to be added to the network, or may allow behavior of the participants to be modified.

Abstract: A system and article of manufacture for social media event detection and content-based retrieval include obtaining multiple images from at least one social media source, extracting at least one visual semantic concept from the multiple images, differentiating an event semantic concept signal from a background semantic concept signal to detect an event in the multiple images, and retrieving one or more images associated with the event semantic concept signal for presentation as a visual description of the detected event.