Abstract: An approach for providing flexible durability operations for a data storage application can include requests to perform logging operations of data storage application having an indication of a durability mode to use for the logging operation. The logging operation can be initiated according to the indication of the durability mode and a callback indicating log write completion can be called according to the indication of the durability mode.

Abstract: Configuring a graphical user interface according to a user's preferences is described herein. Systems and methods are provided for generating a dynamically varying themed interface for a user environment; defining appropriate color palettes associated within a brand definition of the user environment; and, providing one or more configuration settings for the rendering engine.

Abstract: Methods, systems, and computer-readable storage media for predicting a type of an event in a computer-implemented system, implementations including receiving event data including a set of features representative of an event, determining a probability for at least one feature in the set of features from a data structure that stores a plurality of feature-probability pairs, the data structure representative of a type of event, providing a joint probability based on the probability of the at least one feature, the joint probability indicating a likelihood that the event is of the type of event, comparing the joint probability to a threshold to provide a comparison, and selectively executing one or more actions based on the comparison.

Abstract: A data storage and retrieval system for a computer memory configured according to a document store adapted to contain documents. The document store includes a document data structure containing a header and a document having one or more members. The document store further includes a chain of one or more differential data structures, each having a header and at least one updated member. The updated member has a value which is updated relative to a value in a corresponding member having a same identifier in the document data structure or in a preceding differential data structure in the chain. A header of each of the differential data structures includes a pointer to the document data structure or the preceding differential data structure in the chain, and a flag indicating that each of the differential data structures contains less than all of the members of the document data structure.

Abstract: A method clusters each character on a document into one of a plurality of clusters based on widths of at least a portion of the characters on the document and measures distances between characters on the document. A threshold for each of the plurality of clusters is calculated based on at least a portion of the distances between characters in each cluster. The method then segments characters into units using the thresholds for the plurality of clusters. A distance between two characters in the document is compared to a threshold for a cluster to classify the two characters as being part of a unit when the distance is less than the threshold and not being part of the unit when the distance is greater than the threshold. Then, the method performs a recognition process on the document using the units.

Abstract: Some embodiments provide a program that receives a query for records in a table having a value in a column of the table that is included in a set of values. The program further iterates though a hierarchical tree structure in order to identify a set of leaf nodes of the hierarchical tree structure based on the set of values. Each leaf node in the hierarchical tree structure includes data describing a superset of values in the column of the block of records associated with the leaf node. Each non-leaf node includes data describing a superset of the values described by the data in child nodes of the non-leaf node. The program also processes the query on a set of block of records in the table associated with the set of leaf nodes. The program further generates results for the query based on the processing.

Abstract: A method of enhancing one or more fields of a master database record based on a consumption of one or more data points provided via a third-party data subscription service is disclosed. An aggregated view corresponding to a master database record is accessed. The aggregated view identifies correspondences between the one or more fields of the master database record and the one or more data points provided via the third-party data subscription service. Based on a determination that one or more consumption criteria are met, the one or more data points are consumed and stored in a central database. The one or more fields of the master database record are updated based on the one or more consumed data points. The enhanced master database record is provided via a network to one or more computerized processes associated with one or more consumers of the enhanced master database record.

Abstract: Disclosed herein are system, method, and computer program product embodiments for building a stateless connector to a stateful backend system. The stateless connector allows developers to deploy mobile applications that interact with the stateful backend system without refurbishing the backend system to accommodate stateless design methodologies and access functions. The stateless connector thus provides a bridge between a stateless application and a stateful backend system without requiring any risky and potentially disruptive updates the backend system. The stateless connector may be generated and deployed automatically based on a recording of user interactions with stateful application server. This saves an enormous amount of time and effort in the application development process and allows application developers to focus their time and efforts on the presentation components and business logic of the mobile application.

Abstract: A converter system for multi-component systems, comprising a multi-component system adjustment module, includes: an input/output unit, an adjustment unit configured to adjust at least one primary component of a primary multi-component system for each of the at least one primary component given as a probability distribution, a certainty evaluation unit configured to evaluate a certainty parameter of the primary multi-component system, and compare the certainty parameter with a certainty threshold, and a prompt selection unit configured to, if the certainty parameter of the primary multi-component system does not meet the certainty threshold, select a further primary component prompt of the plurality of primary component prompts and instructing the multi-component system adjustment module to perform the above steps on the basis of the further primary component prompt; wherein the converter system further comprises a multi-component system converter module, comprising: a converter unit configured to generate a p

Abstract: Various embodiments of systems and methods for decentralized image management are described herein. The method includes generating, distributing, and retrieving images on peer-to-peer network. Request for generating an image is received. Multiple components/layers of a to-be-generated image is identified. A layer is stored as a file. Files corresponding to the layers are packaged as an image file representing the image. The packaged image file and/or files of respective layers are distributed across the network, e.g., across a plurality of available nodes upon receiving a distribution command/request. When a request for retrieving the image is received, the nodes storing the multiple layers of the image are identified. The layers are retrieved from the identified multiple nodes. Using the retrieved multiple layers, the image is recreated/generated.

Abstract: A computer-implemented method can receive a request from a robotic process automation engine to identify a target user interface control element in a webpage represented by a current master data frame. The current master data frame comprises a current document object model (DOM). The method can determine that a target user interface control element identifier associated with the target user interface control element is absent in the current DOM. The method can retrieve an archived version of the target user interface control element from an archived master data frame of the webpage. The method can find an equivalent user interface control element within the current master data frame based at least on the archived version of the target user interface control element, and output an equivalent user interface control element identifier associated with the equivalent user interface control element.

Abstract: Physical block numbers are assigned to pages loaded into memory of an in-memory database. Thereafter, pages having a same size are distributed to one of a plurality of helper threads executing in parallel for processing if such pages having consecutive physical block numbers. Each of these helper threads can have a corresponding small page buffer. Contents of the respective small page buffers are later flushed to physical disk persistence when such small page buffers are full.

Abstract: Technologies described herein can be used to generate and distribute neural network models and executable code using feedback data received from one or more client computing devices. A neural network model can be generated by a server computer. Executable code can also be generated by the server that, when executed by a client computing device, causes the client device to generate a prediction using the neural network model. The server can transmit the model and code to one or more client computing devices. The server can receive feedback data from the client device(s) based on predictions generated by the client device(s) using the neural network model and the executable code. The server can generate an updated version of the neural network model and/or an updated version of the executable code base on the feedback data, and can transmit the updated model and/or the updated code to the client device(s).

Abstract: Various examples described herein are directed to systems and methods for analyzing text. A computing device may train an autoencoder language model using a plurality of language model training samples. The autoencoder language mode may comprise a first convolutional layer. Also, a first language model training sample of the plurality of language model training samples may comprise a first set of ordered strings comprising a masked string, a first string preceding the masked string in the first set of ordered strings, and a second string after the masked string in the first set of ordered strings. The computing device may generate a first feature vector using an input sample and the autoencoder language model. The computing device may also generate a descriptor of the input sample using a target model, the input sample, and the first feature vector.

Abstract: A system includes determination, based on a plurality of rows of a table, where each of the plurality of rows associated with a respective row_id represents a respective a node of a hierarchy, row_id pairs of each parent node-child node pair of the hierarchy, execution, based on the row_id pairs, of a depth-first traversal of the hierarchy to sequentially add each row_id of the plurality of rows to a hierarchy index and receive a NODE value associated with the added row_id, and, for each of the plurality of rows, update of a row based on the NODE value associated with the row_id of the row.

Abstract: A method and system including receiving selection of a component at a porting module; retrieving a source code for the selected component and a component configuration file for the selected component; receiving component data associated with the component; generating metadata associated with the received component based on the received component data; modifying the component configuration file of the selected component to generate a modified configuration file; generating an integration adapter by modifying the retrieved source code for the selected component with the generated metadata and the modified configuration file; and deploying the integration adapter. Numerous other aspects are provided.

Abstract: A front end receives a request for data specifying a data type. A query handler retrieves data of the data type comprising a plurality of data records from at least one database. The query handler assigns a classification attribute to each data record using a pre-defined classification policy stored in a policy store. A discrimination detection engine statistically evaluates the classification attributes for the data to identify a mutual information metric. The query handler generates a listing of one or more discriminatory attributes and corresponding mutual information metric contributing to discriminatory data patterns based on the mutual information metric.

Abstract: Methods, systems, and computer program products for a database processing system are described. A core database comprises common procedures for processing information, at least one of the common procedures configured to provide a common functionality to an analysis application. A content import database comprises content-specific procedures, at least one of the content-specific procedures configured to provide access for at least one of the common procedures to content of the content import database that conforms to a content-specific data model.

Abstract: The present disclosure involves systems, software, and computer implemented methods for Internet of Things (IoT) end-to-end continuous monitoring. In one example, a method may include transmitting a first message by a first device to a second device in an IoT cloud system, the first message including a first timestamp indicating when the first message is transmitted, receiving a second message by the first device from the second device, the second message including the first timestamp and a second timestamp indicating when the first message was received by the second device, the second message being received at a time indicated by a third timestamp, and monitoring by the first device end-to-end communication between the first device and the second device in the IoT cloud system based on at least one of the first, second, or third timestamps.

Abstract: The present disclosure involves systems, software, and computer implemented methods for providing voice-enabled human tasks in process modeling. One example method includes receiving a deployment request for a workflow that includes a human task. The workflow is deployed to a workflow engine in response to the deployment request. An instance of the workflow is created in response to a request from a client application. The instance of the workflow is processed, including execution of the human task. The human task is added to a task inbox of an assignee of the human task. A request is received from the assignee to access the task inbox from a telecommunications system. Voice guidance is provided, to the assignee, that requests assignee input. Voice input from the assignee is processed for completion of the human task. Workflow context for the human task is updated based on the received voice input.