Abstract: The present disclosure relates to devices, methods, and systems for subscriber identification module (SIM) management for a private mobile network. The methods and systems may include a private mobile network service on a cloud computing system. Users of the cloud computing system may use the private mobile network service to create a private mobile network. The private mobile network service may facilitate the creation of the private mobile network by providing interfaces for secure communications with the users of the cloud computing system, the SIM service partners, and the packet core partners. The mobile network service may also manage the SIM cards for the private mobile networks by coordinating the transmission of the SIM operation details for the SIM cards.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for updating a molecular database. In one aspect, a method comprises: receiving a request to update a target molecule component stored in the molecular database; updating the data defining a target molecule represented by the target molecule component; identifying a set of target component links that reference the target molecule component; identifying, for each of the target component links, a respective validation criterion associated with the target component link; determining, for each of the target component links, a new validation status for the target component link by evaluating the validation criterion associated with the target component link; and updating the current validation status of each target component link to the new validation status for the target component link.

Abstract: The present disclosure pertains generally to image feature extraction. Both transfer-learning and multi-task training approaches are considered. In one example, a machine learning model is trained to perform a geographic classification task of distinguishing between images captured in different geographic regions based on their visual content. In another example, a machine learning model is trained to perform an order recognition task of determining information about the order of an image sequence based on its visual content, where the order of the image sequence may be different than the order in which its constituent images were captured. A further example combines the two approaches. The knowledge gained by the ML model in learning one or more such tasks can be applied to a desired image recognition task, such as image segmentation, structure detection or image classification, e.g. with a pre-training/fine-tuning framework or a multi-task learning framework.

Abstract: At an artificial intelligence based service to detect violations of resource usage policies, an indication of a first data set comprising a plurality of network traffic flow records associated with at least a first device of a set of devices may be obtained. Using the first data set, a machine learning model may be trained to predict whether resource usage of a particular device of a particular network violates a first resource usage acceptability criterion. In response to determining, using a trained version of the model, that the probability that a second device has violated the acceptability criterion exceeds a threshold, one or more actions responsive to the violation may be initiated.

Abstract: In implementations of segmenting objects in vector graphics images, an object segmentation system can obtain points that identify an object in a vector graphics image, and determine a region of interest in the image that includes the object based on the points that identify the object. The object segmentation system can generate a heat map from the points that identify the object in the image, and a rasterized region from rasterizing the region of interest. The object segmentation system can generate a mask from the rasterized region and the heat map, the mask identifying pixels of the object in the rasterized region, and determine, from the mask, paths of the vector graphics corresponding to the object.

Abstract: The present disclosure describes a method and a system for determining a 3-dimensional data structure of an audio file, and a playback position in the audio file for synchronization of media playbacks. In many circumstances the media files while displayed in a theater, TV or mobile display comprise an audio track which may not be comfortable to minority of the audiences. According to some embodiments, the methods and the systems discloses in present invention determines the 3-Dimensional data structure of an audio file and based on which the playback position of the audio file from a media source is determined. In another embodiment of the invention, the method and the system of the present invention also provides synchronization of the playback to ensure that the alternate audio file runs in sync with the original audio file or video file. FIG. 1 is the representative figure.

Abstract: Embodiments of the present invention provide systems, methods, and computer storage media directed to optimizing the accuracy of local feature detection in a variety of physical environments. Homographic adaptation for facilitating personalization of local feature models to specific target environments is formulated in a bilevel optimization framework instead of relying on conventional randomization techniques. Models for extraction of local image features can be adapted according to homography transformations that are determined to be most relevant or optimal for a user's target environment.

Abstract: A cloud-based storage architecture provides for the isolation of client data in a distributed manner using a hub-and-spoke account mechanism within the cloud. Individual client data is securely isolated while still providing a master account with access to all data, including providing access from common applications to all of the data. Thus complete client isolation is achieved while simultaneously sharing the code necessary to process the data in the cloud. A separate client account may be maintained for data stored at separate physical locations, such as may be required under various privacy laws and regulations; in this manner, no data is required to leave a specified geopolitical location in order for processing to occur.

Abstract: Performing a built-in self-test (BIST) on a memory macro includes generating a plurality of input vectors such that at least one input vector of the plurality of input vectors is transmitted to the memory macro in each of a plurality of cycles, receiving in each of the plurality of cycles, an output data from the memory macro. The output data is generated by the memory macro in response to processing the at least one input vector. The BIST also includes comparing the output data in each of the plurality of cycles with a signature value and determining whether the memory macro is normal or faulty based upon the comparison.

Abstract: A visual lens system is described that identifies, automatically and without user intervention, digital tool parameters for achieving a visual appearance of an image region in raster image data. To do so, the visual lens system processes raster image data using a tool region detection network trained to output a mask indicating whether the digital tool is useable to achieve a visual appearance of each pixel in the raster image data. The mask is then processed by a tool parameter estimation network trained to generate a probability distribution indicating an estimation of discrete parameter configurations applicable to the digital tool to achieve the visual appearance. The visual lens system generates an image tool description for the parameter configuration and incorporates the image tool description into an interactive image for the raster image data. The image tool description enables transfer of the digital tool parameter configuration to different image data.

Abstract: An apparatus to: analyze a data set to identify a candidate topic not in a set of topics; determine whether the prominence of the candidate topic within the data set meets a threshold; in response to meeting the threshold, retrieve a rate of increase in frequency of the candidate topic in online searches; in response to meeting a threshold rate of increase, retrieve the keyword most frequently used in online searches for the candidate topic, use the keyword to retrieve a supplemental data set, and analyze input data extracted from the supplemental data set to determine whether the candidate topic can change the accuracy of a forecast model; and in response to determining that the candidate topic can change the accuracy, add the candidate topic to the set of topics and replace the forecast model with a forecast model trained for the set of topics augmented with the candidate topic.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training a convolutional neural network using a regularization scheme. One of the methods includes repeatedly performing the following operations: obtaining a kernel of a particular convolutional layer; applying a Fourier transform to the kernel; generating a decomposition using singular-value decomposition (SVD); generating a regularized diagonal matrix; generating a recomposition; applying an inverse Fourier transform to the recomposition; and training the convolutional neural network on training inputs.

Abstract: Photoactive compounds are disclosed. The disclosed photoactive compounds include metal complexes with dipyrromethene-based ligands, which can be substituted with a variety of different side chains or groups or can include various fused ring configurations, such as including aromatic or heteroaromatic groups. The metal complexes may include two dipyrromethene-based ligands, which can be the same or different. The photoactive compounds can be used as photoactive materials in organic photovoltaic devices, such as visibly transparent or opaque photovoltaic devices.

Abstract: Photoactive compounds are disclosed. The disclosed compounds can include a structural motif of A-D-A, A-pi-D-A, or A-pi-D-pi-A, with A being an electron acceptor moiety, pi being a ?-bridging moiety, and D being an electron donor moiety comprising a fused heteroaromatic group. The disclosed photoactive compounds can be used in organic photovoltaic devices, such as visibly transparent or opaque photovoltaic devices.

Abstract: The invention relates to a sternal closure device for temporarily closing and stabilizing a sternum in between surgeries of the thoracic cavity wherein a C-shaped hook attaches to the outside of the portion of one side of a dissected sternum which is connected to an opposing C-shaped hook by a wire which may be readily cut with surgical scissors to allow physicians quick access to the thoracic cavity for surgical treatment. The device includes a stress measurement dial that allows physicians to evaluate the force needed for permanent closure fixation. The new and unique aspect of this invention is that it gives surgeons easy access to the thoracic cavity without worrying about the sternal bones fusing together between operations.

Abstract: Provided are compounds of Formula (I), pharmaceutical compositions comprising such compounds, and their use as menin/MLL protein/protein interaction inhibitors, useful for treating diseases such as cancer, myelodysplastic syndrome (MDS) and diabetes.

Abstract: The present invention relates to pharmaceutical agents useful for therapy and/or prophylaxis in a mammal, and in particular to spiro bicyclic compounds, pharmaceutical composition comprising such compounds, and their use as menin/MLL protein/protein interaction inhibitors, useful for treating diseases such as cancer, myelodysplastic syndrome (MDS) and diabetes.

Abstract: A method, computer program product, and a system where a processor(s) obtains, via a web interface, from a client, over a public network connection, a request to register for a financial transaction; a smart contract comprises the requested financial transaction. The processor(s) maps the client to a pre-defined security profile based on a security level associated with the security profile. The processor(s) selects, based on the security level, encryption keys from a repository and security codes. The processor(s) executes an encryption script, to automatically encrypt the contents of the smart contract utilizing the encryption keys and the security codes and by embedding SafeMath library codes in the smart contract.

Abstract: There is a need for more effective and efficient performing classification-based predictive data analysis on named data collections. This need can be addressed by, for example, solutions for performing classification-based predictive data analysis on named data collections that utilize at least one of techniques for generating column classification machine learning models to perform column classification, techniques for generating column classification machine learning models to perform anomaly detection, techniques for utilizing trained column classification machine learning models to perform column classification, and techniques for utilizing trained column classification machine learning models to perform anomaly detection.

Abstract: There is a need for more effective and efficient performing classification-based predictive data analysis on named data collections. This need can be addressed by, for example, solutions for performing classification-based predictive data analysis on named data collections that utilize at least one of techniques for generating column classification machine learning models to perform column classification, techniques for generating column classification machine learning models to perform anomaly detection, techniques for utilizing trained column classification machine learning models to perform column classification, and techniques for utilizing trained column classification machine learning models to perform anomaly detection.