Abstract: A system for automatic ordering of products comprises a receiver to receive stock parameters including a number of products sold till a point in time, an expiration duration for usage of products, or a number of products available in an inventory at the time. The system also includes a stock analyzer to determine a stock-out probability factor based on the number of products sold and estimated short term sales, determine a disposal probability factor based on the number of products sold, the expiration duration and estimated long term sales, ascertain a risk balance factor indicative of a ratio of the disposal probability factor to the stock-out probability factor, determine a number of products to replenish the inventory, based on the stock-out probability factor, the disposal probability factor, and the risk balance factor, and place a purchase order to a vendor for acquiring the number of products for replenishing the inventory.

Abstract: An intelligent VR (IVR) system receives a VR content item and automatically augments the VR content item with additional or ancillary content. The intelligent VR system initially identifies within the VR content item, valid textual and non-textual objects that have ancillary content associated therewith. The IVR system provides hotspots that signify presence of the ancillary content for the valid objects during a display of the VR content item. The hotspots and the ancillary content are positioned for display corresponding to pixel blocks including the valid objects. The ancillary content is selected for the hotspots based on a spatial and temporal extent of display of the valid objects. The hotspots with respective ancillary content items and the VR content item are streamed to a head mounted display (HMD) for display to a viewer.

Abstract: In some examples, image content moderation may include classifying, based on a learning model, an object displayed in an image into a category. Further, image content moderation may include detecting, based on another learning model, the object, refining the detected object based on a label, and determining, based on the another learning model, a category for the refined detected object. Further, image content moderation may include identifying, based on the label, a keyword associated with the object, and determining, based on the identified keyword, a category for the object. Further, image content moderation may include categorizing, based on a set of rules, the object into a category, and moderating image content by categorizing, based on aforementioned analysis the object into a category. Yet further, image content moderation may include tagging, based on fusion-based tagging, the object with a category and a color associated with the object.

Abstract: A solution generation and planning system uses Artificial Intelligence (AI) techniques such as machine learning (ML) data models, predictive analytics and natural language processing (NLP) techniques for generating outputs to aid decision making in the domain of public infrastructure development. The problem statement is analyzed using the NLP techniques to generate word tokens which are employed in identifying issues that aid in selection of appropriate data sources from a plurality of discrete data sources. In addition, data models trained to produce probable solutions for the issue are also selected. The probable solutions are presented to the user who selects one of the probable solutions for implementation. Feedback from the implementation is also incorporated so that the data models are updated per the latest information obtained from the implementation of the user-selected solution.

Abstract: A server node may receive a token creation message including an authorization parameter. The server node may acquire, from a blockchain synchronized across a plurality of network nodes, a token factory in response to receipt of the token creation message. The token factory may include token factory logic configured to generate an authorization token based on the authorization parameter. The server node may generate, based on execution of the token factory logic with the token creation parameter, the authorization token. The authorization token may include authorization logic configured to validate an access event corresponding to an executable component configured on a remote device. The server node may append a datablock to the blockchain. The datablock may include the authorization token. The server node may control access to the executable component configured on the remote device by execution of the authorization token included in the blockchain.

Abstract: A system may parse a group of manuscripts to extract manuscript properties and textual data included in each respective manuscript. The system may perform computer based identification of a predetermined category in which each respective manuscript resides and generate a categorized inventory of log entries, which include the manuscript properties and the textual data as respective field values. Each of the log entries may be representative of one of the manuscripts and may be categorized in the categorized inventory of log entries according to the predetermined category. The system may generate derived field values in at least some of the log entries. The derived field values may be indicative of at least some of the respective field values. The system may generate an architectural computer based dimensional mapping of a categorized inventory of log entries based on the relational association among the respective field values and the derived field values.

Abstract: In some examples, natural language unification based robotic agent control may include ascertaining, by a robotic agent, an image of an object or an environment, and ascertaining a plurality of natural language insights for the image. A semantic relatedness may be determined between each insight of the plurality of insights, and a semantic relatedness graph may be generated for the plurality of insights. For each insight of the plurality of insights, at least one central concept may be identified. Based on the semantic relatedness graph and the identified at least one central concept, the plurality of insights may be clustered to generate at least one insights cluster. For insights included in the least one insights cluster, a unified insight may be generated. Further, an operation associated with the robotic agent, the object, or the environment may be controlled by the robotic agent and based on the unified insight.

Abstract: A document processing system receives an electronic document including component documents generated from various sources in different formats. Plain text data can be extracted from the electronic document in addition to formatting and structuring information. The plain text data is segmented into sections and various entities are extracted and linked from the sections. An interactive graphical user interface (GUI) that displays content including the plain text data is formatted according to the styling information and annotated entity relationships are determined from the linked entities. The GUI enables user edits to the annotated entity relationships.

Abstract: In some examples, natural language eminence based robotic agent control may include ascertaining, by a robotic agent, an image of an object or an environment, and ascertaining a plurality of natural language insights for the image. For each insight of the plurality of insights, an eminence score may be generated, and each insight of the plurality of insights may be ranked according to the eminence scores. An operation associated with the robotic agent, the object, or the environment may be controlled by the robotic agent and based on a highest ranked insight.

Abstract: According to an example of the present disclosure, a software testing system is operable to test functionalities of a web application across different platforms. The software testing system can interact with different platforms via different drivers to facilitate multiplatform testing of the functionalities. Also, multiplatform test result views may be generated.

Abstract: A device may receive a set of first samples of textual content. A device may identify a set of clusters of first samples of the set of first samples. A device may identify a pattern of occurrence based on the set of clusters. The pattern of occurrence to identify two or more clusters, of the set of clusters, based on an order in which first samples associated with the two or more clusters were generated or received. A device may receive one or more second samples of textual content. A device may determine that the one or more second samples are semantically similar to one or more corresponding clusters associated with the pattern of occurrence. A device may identify a predicted sample based on the pattern of occurrence and the one or more corresponding clusters. A device may perform an action based on identifying the predicted sample.

Abstract: Systems and methods for orchestrating a process are disclosed. In an implementation, a system is configured to extract process information associated with the process. Based on the process information, the system is configured to determine a current model of performing the process based on the process information. The system is further configured to retrieve regulatory information associated with the process, wherein the regulatory information is indicative of at least one of a predefined policy, a predefined rule, and a predefined regulation associated with the process. Further, the system is configured to update the current model based on at least one of the process information and the regulatory information for obtaining a predefined outcome of the process.

Abstract: Data extraction and automatic validation from digitized documents in non-editable formats is disclosed. Paper documents are digitized or converted into formats suitable for storage on computers or other digital devices. The digitized documents are classified into one of a plurality of document types and based on the document type, document processing rules are selected for analyzing the digitized documents to enable data extraction and automatic validation. The positions and values of the data fields in the digitized documents are obtained using machine learning techniques. The data field values are automatically validated and assigned confidence scores. Data fields with low confidence scores are flagged for manual review.

Abstract: Techniques for providing information security threat assessment and amelioration are disclosed. The techniques may include obtaining fundamental data, obtaining document data, preparing fundamental instance nodes from the fundamental data, preparing document nodes from the document data, preparing edges between at least some of the nodes, storing the nodes and the edges in a manner that reflects a graph structure, and causing to be displayed at least a portion of a graph defined by at least one node and at least one edge.

Abstract: A device may obtain text to be processed to identify a trend associated with a topic included in the text. The text may include a plurality of text sections, associated with the topic, that may be associated with a plurality of temporal intervals. The device may determine a respective context for the topic in each of the plurality of text sections. The device may calculate a first specificity score based on the respective context for the topic for one or more text sections associated with the first temporal interval. The device may calculate a second specificity score based on the respective context for the topic for one or more text sections associated with the second temporal interval. The device may identify a trend associated with the topic based on the first specificity score and the second specificity score, and may provide information that identifies the trend.

Abstract: A device to execute an application design plugin associated with a user interface. The device may analyze, using the application design plugin, a set of historical applications to identify one or more dependencies included in the set of historical applications. The device may provide, to a storage device, historical application metadata relating to the one or more dependencies. The device may receive, via the user interface, a request to generate an application design. The device may update the user interface with design information that includes design feature metadata identifying the one or more dependencies. The device may determine that the application design is ready for validation. The device may validate the application design based on determining that the application design is ready for validation.

Abstract: A device receives training data and an ontology for the training data, where the training data includes information associated with a subject of the ontology. The device generates a knowledge graph based on the training data and the ontology, and converts the knowledge graph into knowledge graph embeddings, where the knowledge graph embeddings include points in a k-dimensional metric space. The device receives a new entity that is not present in the knowledge graph embeddings, and generates a new embedding of the new entity. The device adds the new embedding to the knowledge graph embeddings, and utilizes the knowledge graph embeddings, with the new embedding, to perform an action.

Abstract: An extensible single point orchestration system receives service requests from applications. In dependence upon the service request a single third party provider service or multiple third party provider services is identified. When the single third party provider service is identified, the system dynamically adapts a core capability service, using a stored configuration entity, so as to set an appropriate message format and transmit a service call message to an external API of the identified single third party provider service. When multiple third party provider services are identified, the system dynamically adapts the core capability service, using another stored configuration entity, so as to set a respective appropriate message format for parallel data transmission of service call messages to each of the respective identified third party provider services and transmits the service call messages to respective external APIs of each of the third party provider services.

Abstract: An identification and management system for log entries may filter historical data and generate closed log entries as a reference dataset. A dynamic learning engine may perform statistical modelling using the reference dataset to assign predetermined categories to each of a number of open log entries. An automation index may be generated for each of the open log entries. The automation index is indicative of accuracy of the assigned categories. Some of the open log entries may be identified as priority log entries which are representative of a group of the open log entries. The assigned category of the priority log entries may be analyzed for accuracy and the results of the analysis may be used to train the statistical model so that the open log entries may be iteratively assigned and re-assigned a category until the category of each open log entry reaches a desired accuracy.

Abstract: Techniques are described for metadata-driven code generation to generate code for analyzing data from clinical trial(s). A code generation engine may generate program code based on metadata that is input to the engine. The metadata may describe the data to be input to the generated code, and one or more artifacts to be output by the generated code on execution. The metadata may also describe one or more operations to be performed on the input data and/or intermediate data. The metadata may include one or more of the following: inline code to be included in the generated code; references to stored code to be included in the generated code; and/or instructions to be run to generate the code. Artifact(s) may include, but are not limited to, reports such as tables, figures, and/or listings that describe the results of analyzing or otherwise processing the data by the generated program code.