Abstract: A method for secure debugging in a multitenant cloud environment where an application server maintains a host application shared by multiple tenant users can be implemented. The method can receive a request from a tenant user to debug the host application associated with a tenant user, and responsive to the request, deploy an application runtime environment comprising an application container encapsulating the host application associated with the tenant user and a debugger container encapsulating a debugging software running on the application server. The method can set at least a breakpoint in source code of the host application through a user interface of the debugging software, run the host application associated with the tenant user in the application runtime environment, and evaluate an expression entered through the user interface of the debugging software after the host application associated with the tenant user hits the breakpoint.

Abstract: This disclosure relates to a fully software-defined, fully virtualized, and customizable mobile communication platform deployed on public cloud infrastructure. Such mobile networks allows for end to end control of automatic and programmatic deployment and configuration of the mobile network components. The implementations below effectively enables instant creation and deployment of a true private global end-to-end Software Defined Network (SDN) for 3G, 4G, LTE, and 5G mobile communication from the ground up. Users will effectively act their own mobile carrier, allowing them to customize the features available to them via a programmatic interface.

Abstract: A computer-implemented method is provided for predicting a growth rate of an aortic aneurysm. The method comprises analysing one or more geometric measures of a volumetric model of at least a portion of an aorta having an aneurysm. The method further comprises determining, from the analysis, a growth rate prediction for the aortic aneurysm. Computer-readable media and apparatuses are also described.

Abstract: Features related to systems and methods for automated generation of a machine learning model based in part on a pretrained model are described. The pretrained model is used as a starting point to augment and retrain according to client specifications. The identification of an appropriate pretrained model is based on the client specifications such as model inputs, model outputs, and similarities between the data used to train the models.

Abstract: An archival storage of data backed up from a repository storage of a primary storage is maintained. Access to data stored in archival storage is limited by one or more access policies based on whether a corresponding data restore has been authorized. A request for specific data stored in the archival storage is received. The one or more access policies are automatically managed based on status and timing of one or more data restore authorizations for the specific data stored in the archival storage.

Abstract: Systems, computer program products, and methods are described herein for implementing a data driven channel for query executions using quantum computing. The present invention is configured to receive, from a user input device, a query; parse, using a query processing engine, the query; determine a classical execution plan based on at least parsing the query; convert, using a query optimization engine, the classical execution plan into a quantum execution plan; initiate a query execution engine on the quantum execution plan; determine, using the query execution engine, a quantum circuit design for execution of the quantum execution plan; execute, using the query execution engine, the quantum execution plan; generate a query result based on at least executing the quantum execution plan; and transmit control signals configured to cause the user input device to display the query result.

Abstract: A process for document processing (e.g., automated package splitting) may involve producing, for each document page of an ordered plurality of document pages, an image of the document page and a representation of text from the document page; generating, for each document page of the ordered plurality, and based on the image of the document page and the representation of text from the document page, an embedding of the document page; and generating, for each document page among a subset of the ordered plurality, a label for the document page that indicates whether the document page is a document first page, based on the embedding of the document page, the embedding of each of at least one document page that precedes the document page in the ordered plurality, and the embedding of each of at least one document page that follows the document page in the ordered plurality.

Abstract: A method, apparatus, and computer program product are provided to determine sensor orientation. In the context of a method, the orientation of a sensor is predicted based on a predetermined dataset. The method also includes receiving information regarding a location of the sensor and information from which a gravity direction of the sensor is derivable. The method further includes determining a relative orientation of the sensor in relation to a frame of reference and the gravity direction of the sensor. The method still further includes comparing the orientation of the sensor that was predicted and the relative orientation of the sensor to determine a prediction accuracy. The method finally includes updating the predetermined dataset based on the prediction accuracy of the sensor orientation.

Abstract: There is provided a system and method for processing and storage of a time-series data stream. The method including: separating an input time-series data stream into a value array and a time array; segmenting the value array into blocks, each block including a plurality of consecutive values; performing iterations of delta encoding on the values in each block; organizing multiple delta encoded blocks in an output file structure, the output file structure further comprising the time array associated with the values in the block and a block header, the block header including: the number of values in the block; initial values for the delta encoding; and the number of iterations of delta encoding applied on the block; and outputting the multiple blocks in the output file structure.

Abstract: A process for document processing (e.g., automated package splitting) may involve producing, for each document page of an ordered plurality of document pages, an image of the document page and a representation of text from the document page; generating, for each document page of the ordered plurality, and based on the image of the document page and the representation of text from the document page, an embedding of the document page; and generating, for each document page among a subset of the ordered plurality, a label for the document page that indicates whether the document page is a document first page, based on the embedding of the document page, the embedding of each of at least one document page that precedes the document page in the ordered plurality, and the embedding of each of at least one document page that follows the document page in the ordered plurality.

Abstract: Methods described herein relate to reducing the computational intensity of vision-based localization. Methods may include: receiving sensor data from a vehicle traveling along a road; identifying one or more features of the environment from the sensor data; classifying the one or more identified features into one or more of a plurality of semantic classifications for the features; identifying map image data based on an identified location of the vehicle; identifying one or more features in the map image data; comparing one or more identified features of a first semantic classification with one or more features of the map image data of the first semantic classification; and registering a localized location of the vehicle within the environment based, at least in part, on the one or more identified features of the first semantic classification corresponding to the one or more features of the map image data of the first semantic classification.

Abstract: Various embodiments of a system and associated method for audio source separation based on generative priors trained on individual sources. Through the use of projected gradient descent optimization, the present approach simultaneously searches in the source-specific latent spaces to effectively recover the constituent sources. Though the generative priors can be defined in the time domain directly, it was found that using spectral domain loss functions leads to good-quality source estimates.

Abstract: A system for generating 2D slices of a 3D image of a target volume is provided. The system receives a target sinogram collected during a computed tomography scan of the target volume. The system inputs the target sinogram to a convolutional neural network (CNN) to generate predicted 2D slices of the 3D image. The CNN is trained using training 2D slices of training 3D images. The system initializes 2D slices to the predicted 2D slices. The system reconstructs 2D slices of the 3D image from the target sinogram and the initialized 2D slices.

Abstract: Techniques for prefetching are provided. The techniques include receiving a first prefetch command; in response to determining that a history buffer indicates that first information associated with the first prefetch command has not already been prefetched, prefetching the first information into a memory; receiving a second prefetch command; and in response to determining that the history buffer indicates that second information associated with the second prefetch command has already been prefetched, avoiding prefetching the second information into the memory.

Abstract: Systems, methods, and computer storage media are disclosed for predicting visual compatibility between a bundle of catalog items (e.g., a partial outfit) and a candidate catalog item to add to the bundle. Visual compatibility prediction may be jointly conditioned on item type, context, and style by determining a first compatibility score jointly conditioned on type (e.g., category) and context, determining a second compatibility score conditioned on outfit style, and combining the first and second compatibility scores into a unified visual compatibility score. A unified visual compatibility score may be determined for each of a plurality of candidate items, and the candidate item with the highest unified visual compatibility score may be selected to add to the bundle (e.g., fill the in blank for the partial outfit).

Abstract: Techniques for optically detecting a subject chemical species within an atmospheric environment are disclosed. Image data is obtained representing multispectral imagery of a geographic region captured through the atmospheric environment. The image data includes an array of band-specific intensity values for each of a plurality of spectral bands, including a sample spectral band having increased sensitivity to the subject chemical species as compared to a plurality of reference spectral bands. A background reflectance map is generated that includes an array of inter-band intensity values in which each inter-band intensity value represents a filtered combination of band-specific intensity values of albedo-normalized arrays for a grouped subset of the plurality of reference spectral bands. The albedo-normalized array of band-specific intensity values for the sample spectral band is compared to the background reflectance map to obtain an index array of intensity variance values for the subject chemical species.

Abstract: Embodiments of the invention are directed to a system, method, or computer program product for multimodal and distributed database system structured for dynamic latency reduction. In this regard, the invention comprises a unified data layer structured to map a plurality of data storage mechanisms to a common abstraction and a query engine structured for heterogenous domain based data extraction without requiring input of schema-based queries. In some embodiments, the invention comprises determining (i) one or more data components and (ii) one or more associated data domains associated with the first domain-based query by parsing the user input based on derived metadata from data dictionaries associated with a unified data layer system component. Moreover, the invention is configured to extract stored data from each of a plurality of databases based on the associated one or more data domains.

Abstract: An audio processing system is configured to process an audio signal representing sound waves originating from at least one vehicle system disposed on a vehicle. The audio processing system includes a controller configured to receive the audio signal from a microphone. The controller processes the audio signal to generate a frequency domain representation of the audio signal. The controller also receives a first operating signal indicating an operating state of a first said vehicle system. The controller decomposes the frequency domain representation of the audio signal in dependence on the first operating signal to identify a first audio profile associated with the operation of the first vehicle system. Aspects of the present invention also relate to a vehicle including an audio processing system.

Abstract: Techniques are described automatically determining runtime configurations used to execute recurrent neural networks (RNNs) for training or inference. One such configuration involves determining whether to execute an RNN in a looped, or “rolled,” execution pattern or in a non-looped, or “unrolled,” execution pattern. Execution of an RNN using a rolled execution pattern generally consumes less memory resources than execution using an unrolled execution pattern, whereas execution of an RNN using an unrolled execution pattern typically executes faster. The configuration choice thus involves a time-memory tradeoff that can significantly affect the performance of the RNN execution. This determination is made automatically by a machine learning (ML) runtime by analyzing various factors such as, for example, a type of RNN being executed, the network structure of the RNN, characteristics of the input data to the RNN, an amount of computing resources available, and so forth.

Abstract: A method and system for detecting deviation between invoices and receipts are disclosed. In some embodiments, the method includes receiving invoice data and receipt data. The method includes filtering the received data to generate filtered data. The method includes performing line-level matching on the filtered data based on one or more line-level attributes and one or more distance based algorithms. The method then includes determining, from the line-level matching, matched line items and unmatched line items between each pair of the invoice and receipts. The method also includes calculating one or more types of claims for both the matched line items and the unmatched line items to measure a total deviation between the invoices and receipts. The method further includes determining a level of match between the invoices and receipts and generating a recommended matching pair of invoice and receipt based on the level of match.