Abstract: Systems and techniques are disclosed for improvement of machine learning systems based on enhanced training data. An example method includes generating an interactive classification user interface concurrently displaying a first group of medical images and a second group of medical images, each group depicting objects associated with a respective classification. User input indicating movement of medical images from the first group to the second group is detected. The moved medical images are classified according to the second group. The re-classified medical images are provided to a machine learning system, with the machine learning system updating based on analysis of object characteristics of the re-classified medical images to increase accuracies associated with automated assignment of classifications.

Abstract: A method and system for determining user security is provided. The method includes registering a first user associated with a service provider system by retrieving identification information for the first user and a first user communication device. In response, Internet of things (IOT) devices belonging to the first user are detected. A second user associated with the service provider system is registered by retrieving identification information for the second user and a second user communication device. In response, IOT devices belonging to the second user are detected. A request for a service provided by the service provider system is received from the first user via the first user communication device belonging to the first user.

Abstract: A method, system and computer program product, the method comprising: receiving a partial description of a combinatorial model defining a test space and comprising a set of attributes, a respective domain for each attribute defining possible values for the attribute, and restrictions, each comprising an attribute, a respective value and a logical operator, the partial description comprising an attribute and a value thereof; computing a similarity measurement between the partial description and each model in a corpus, based on similarity of attributes and domains, and not on a test space defined by compared models, whereby similarity between models is indifferent to a size of the test space of the models; selecting models from the corpus according to the computed similarity measurements; determining elements from the selected models to be suggested for modifying the partial description; and outputting the suggestions to modify the partial description useful for completing the combinatorial model.

Abstract: A method, apparatus and product for utilizing semantic clusters to predict software defects. The method comprising: obtaining a plurality of software elements that are associated with a version of a System Under Test (SUT), wherein the plurality of software elements comprise defective software elements which are associated with a defect in the version of the SUT; defining, by a processor, a plurality of clusters, wherein each cluster of the plurality of clusters comprises software elements having an attribute, wherein the attribute is associated with a functionality of the SUT; and determining a score of each cluster of the plurality of clusters, wherein the score of a cluster is based on a relation between a number of defect software elements in the cluster and a number of software elements in the cluster.

Abstract: A method and system for determining user security is provided. The method includes registering a first user associated with a service provider system by retrieving identification information for the first user and a first user communication device. In response, Internet of things (IOT) devices belonging to the first user are detected. A second user associated with the service provider system is registered by retrieving identification information for the second user and a second user communication device. In response, IOT devices belonging to the second user are detected. A request for a service provided by the service provider system is received from the first user via the first user communication device belonging to the first user.

Abstract: A method and system for determining user security is provided. The method includes registering a first user associated with a service provider system by retrieving identification information for the first user and a first user communication device. In response, Internet of things (IOT) devices belonging to the first user are detected. A second user associated with the service provider system is registered by retrieving identification information for the second user and a second user communication device. In response, IOT devices belonging to the second user are detected. A request for a service provided by the service provider system is received from the first user via the first user communication device belonging to the first user.

Abstract: A method, system and computer program product, the method comprising: receiving a user document describing at least a part of a system to be tested; computing a similarity measurement between the user document and documents in a document corpus, each describing at least part of a system and associated with a combinatorial model representing the at least part of the system, wherein the combinatorial model comprises a set of attributes, a respective domain for each attribute defining possible values for the attribute, and restrictions, wherein each restriction comprises at least one attribute, a respective value and a logical operator, based upon the similarity measurement, selecting selected documents from the document corpus; obtaining one or more combinatorial models corresponding to the selected documents; selecting elements from the combinatorial models; generating an initial combinatorial model for the user document, wherein said generating comprises adding the elements to the initial combinatorial model.

Abstract: Systems and techniques are disclosed for improvement of machine learning systems based on enhanced training data. An example method includes accessing a database storing associations between objects included in medical images and classifications of the objects. A risk assessment model adapted to determine a risk condition for an object is accessed, the assessment based on features of the object. Risk conditions associated with respective objects are determined based on the risk assessment model. A group of objects associated with a first risk condition is identified. An interactive user interface is generated for display, the user interface concurrently displaying images of the group of objects. The interactive user interface enables a user to select subsets of images to be concurrently assigned a user-selected classification. User selected classifications are provided to a machine learning system adapted to update the risk assessment model based on the classifications to increase accuracy of the model.

Abstract: Systems and techniques are disclosed for improvement of machine learning systems based on enhanced training data. An example method includes generating an interactive classification user interface concurrently displaying a first group of medical images and a second group of medical images, each group depicting objects associated with a respective classification. User input indicating movement of medical images from the first group to the second group is detected. The moved medical images are classified according to the second group. The re-classified medical images are provided to a machine learning system, with the machine learning system updating based on analysis of object characteristics of the re-classified medical images to increase accuracies associated with automated assignment of classifications.

Abstract: Systems and techniques are disclosed for improvement of machine learning systems based on enhanced training data. An example method includes providing a visual concurrent display of a set of images of features, the features requiring classification by a reviewing user. The user interface is provided to enable the reviewing user to assign classifications to the images, the user interface being configured to create, read, update, and/or delete classifications. The user interface is responsive to the user, with the user response indicating at least two images with a single classification. The user interface is updated to represent the single classification.

Abstract: A method, system and computer program product, the method comprising: receiving a partial description of a combinatorial model defining a test space and comprising a set of attributes, a respective domain for each attribute defining possible values for the attribute, and restrictions, each comprising an attribute, a respective value and a logical operator, the partial description comprising an attribute and a value thereof; computing a similarity measurement between the partial description and each model in a corpus, based on similarity of attributes and domains, and not on a test space defined by compared models, whereby similarity between models is indifferent to a size of the test space of the models; selecting models from the corpus according to the computed similarity measurements; determining elements from the selected models to be suggested for modifying the partial description; and outputting the suggestions to modify the partial description useful for completing the combinatorial model.

Abstract: A method and system for determining user security is provided. The method includes registering a first user associated with a service provider system by retrieving identification information for the first user and a first user communication device. In response, Internet of things (IOT) devices belonging to the first user are detected. A second user associated with the service provider system is registered by retrieving identification information for the second user and a second user communication device. In response, IOT devices belonging to the second user are detected. A request for a service provided by the service provider system is received from the first user via the first user communication device belonging to the first user.

Abstract: A method for processing an image includes computing a plurality of binarization scores for an image using a corresponding plurality of binarization threshold values, determining a selected binarization threshold value based on the plurality of binarization scores, processing the image or another image using the selected binarization threshold value. Each binarization score of the plurality of binarization scores may be based on a transition pixel count for a binary image that is derivable from the image using a specified threshold value of the plurality of thresholding values. A computer system and computer program product corresponding to the method are also disclosed herein.

Abstract: A method and system for determining user security is provided. The method includes registering a first user associated with a service provider system by retrieving identification information for the first user and a first user communication device. In response, Internet of things (IOT) devices belonging to the first user are detected. A second user associated with the service provider system is registered by retrieving identification information for the second user and a second user communication device. In response, IOT devices belonging to the second user are detected. A request for a service provided by the service provider system is received from the first user via the first user communication device belonging to the first user.

Abstract: A method, apparatus and computer program product for program migration, the method comprising: receiving a target host and an application to be migrated to a target host; estimating a target load of the application to be migrated; generating a synthetic application which simulates a simulated load, the simulated load being smaller than the target load; loading the synthetic application to the target host; monitoring behavior of the target host, the synthetic application, or a second application executed thereon; subject to the behavior being satisfactory: if the simulated load is smaller than the target load, then repeating said generating, said loading and said monitoring, wherein said loading is repeated with increased load; and otherwise migrating the application to the target.

Abstract: Embodiments of the present invention provide automated systems and methods for segmentation of fibro-glandular (FG) tissue in digital mammography. A classifier is trained for breast density without the prior knowledge for FG tissue. The classifier is then used for feature selection, where the selected features are fed into a fuzzy logic module, and an adaptive threshold is obtained. Post-processing is performed on the image in order to reduce regions which may have been misclassified during the FG segmentation.

Abstract: A method and system for determining user security is provided. The method includes registering a first user associated with a service provider system by retrieving identification information for the first user and a first user communication device. In response, Internet of things (IOT) devices belonging to the first user are detected. A second user associated with the service provider system is registered by retrieving identification information for the second user and a second user communication device. In response, IOT devices belonging to the second user are detected. A request for a service provided by the service provider system is received from the first user via the first user communication device belonging to the first user.

Abstract: Techniques for monitoring computer program test design are described herein. The techniques include a method that specifies a subset of tuples in a combinatorial test model as supervised. At least some of the supervised tuples are confirmed using expert data. The method may include determining a metric indicating progress of the combinatorial test modeling process based on the supervised tuples and the confirmed tuples.

Abstract: Embodiments of the present invention provide automated systems and methods for segmentation of fibro-glandular (FG) tissue in digital mammography. A classifier is trained for breast density without the prior knowledge for FG tissue. The classifier is then used for feature selection, where the selected features are fed into a fuzzy logic module, and an adaptive threshold is obtained. Post-processing is performed on the image in order to reduce regions which may have been misclassified during the FG segmentation.

Abstract: A method, apparatus, and computer-implemented method for optimized instrumentation based on functional coverage, the method comprising: receiving a set of states, the set of states defining required coverage of a program under test, each state of the set of states comprising a value of one or more controllable parameters and a value of one or more incontrollable parameters; executing the program under test and obtaining one or more runtime traces; comparing a value of the incontrollable parameters in the runtime trace to a value of the incontrollable parameters in one or more of the states; and responsive to the values of the incontrollable parameters in the runtime trace being equal to the values of the incontrollable parameters in any of the states, setting a value of one or more controllable parameters to the value of the one or more controllable parameters in the state.