Abstract: A method for generating and processing bundled notification request messages includes, at a producer NF, receiving subscription request messages from consumer NFs via one or more SCPs. The method further includes obtaining and storing, from the subscription request messages validated by the producer NF, identities of SCPs within a last N hops of SCPs from the producer NF, N being an integer of at least one. The method further includes detecting an event requiring notifications to a plurality of the consumer NFs. The method further includes identifying, from the SCPs within the last N hops of SCPs from the producer NF, a group of SCPs for which the notifications can be bundled. The method further includes generating a bundled notification request message for the group of SCPs for which the notifications can be bundled. The method further includes transmitting the bundled notification request message to a first-hop SCP in the group of SCPs.

Abstract: Techniques are described to perform an automatic reset of a database session to generate an environment that resembles a brand new session without the computational cost of creating a brand new session. In an embodiment, a DBMS receives a request from a client application to execute commands within a session. The DBMS identifies that the end request boundary, the end of the logical work unit for the client application, is reached within the session. The DBMS verifies that the end request boundary is at a resettable point of a session state of the session for the session to be safely reset. If the verification is successful, the DBMS performs a reset of the session to prevent any leakage of application-related session state to the next request.

Abstract: Systems and methods are provided for supporting efficient reconfiguration of an interconnection network having a pre-existing routing. An exemplary method can provide a plurality of switches, a plurality of end nodes, and one or more subnet managers, including a master subnet manager. The method can calculate, via the master subnet manager, a first set of one or more leaf-switch to leaf-switch multipaths. The method can store this first set of one or more leaf-switch to leaf-switch multipaths at a metabase. The method can detect a reconfiguration triggering event, and call a new routing for the interconnection network. Finally, the method can reconfigure the network according to the new routing for the interconnection network.

Abstract: Techniques for determining a data tape read quality value are disclosed. A data tape system generates a value representing a quality of a data tape based on attributes of the data tape. The system calculates the data quality value using an algorithm based on: (a) a particular data tape error correction value, (b) data tape length value representing a length of data tape traversed during data-processing operations, and (c) a scaling factor. The scaling factor is based on a relationship between the particular data tape error correction value and a rate of degradation of the data tape. The scaling factor may be generated by applying a trained machine learning model to attributes of a data tape. The model generates a scaling factor for a particular data tape based on the attributes of the particular data tape.

Abstract: Techniques are disclosed for enabling attested end-to-end encryption for transporting data between devices. In one example, a destination device receives a policy profile that includes an origination key and a destination key, and the origination key corresponds to a public transfer key of a source device. The destination device verifies the policy profile based on the destination key corresponding to a public transfer key of the source device. The destination device receives a signed encrypted data encryption key from the source device. The destination device receives encrypted data from the source device. The destination device verifies the signed encrypted data encryption key originated from the source device based on the signed encrypted data key being signed with a private attestation identity key that corresponds to a public attestation identity key of the source device. The destination device decrypts encrypted data using a private transfer key of the destination device.

Abstract: Techniques are described for improving the efficiency of dialog processing by prompting and processing user feedback substantially in real time. A dialog system receives speech input from a user and processes a first portion of the speech input to determine an initial discerned intent. The dialog system causes display of a visual indication of the initial discerned intent. The visual indication of the discerned intent is used to guide the dialog so that the user can correct or confirm the initial discerned intent in a natural fashion. If the initial discerned intent is inaccurate, the user can provide feedback correcting the dialog system, and the dialog system processes a second portion of the speech input to determine a modified discerned intent. Thus, the dialog system can use the feedback to correct misunderstandings on the fly.

Abstract: According to one embodiment, a computer-implemented method for dynamically providing a tool bar in a user interface is provided. The method includes determining at least one action that is commonly performed based on data displayed on a current page of a graphical user interface of a communications device, creating a tool bar comprising at least one icon representing the at least one action, associating the tool bar with the current page of the graphical user interface, and providing the tool bar to the communications device for display on the current page of the graphical user interface.

Abstract: A target set of texts, for training and/or evaluating a text classification model, is augmented using insertions into a base text within the original target set. In an embodiment, an expanded text, including the base text and an insertion word, must satisfy one or more inclusion criteria in order to be added to the target set. The inclusion criteria may require that the expanded text constitutes a successful attack on the classification model, the expanded text has a satisfactory perplexity score, and/or the expanded text is verified as being valid. In an embodiment, if a number of expanded texts added into the target set is below a threshold number, insertions are made into an expanded text (which was generated based on the base text). Inclusion criteria are evaluated against the doubly-expanded text to determine whether to add the doubly-expanded text to the target set.

Abstract: A system and method for use with a cloud computing environment, for determining a cloud score associated with a resource configuration, limits, or shape, for example that of a virtual machine or host provided within the environment. The described approach provides a set of infrastructure workloads, for use in assessing a cloud infrastructure and resources provided thereby, so that a full spectrum of aspects of the cloud infrastructure can be covered by workload testing. The workloads can be used to generate metrics associated with resource usage. The system can then consider one or more metrics that are associated with performance of a particular resource configuration or shape, for example that of a virtual machine or (e.g., bare metal) host hosted by a cloud provider, and determine a score that is indicative of the relative performance of that configuration or shape for a particular workload configuration.

Abstract: A method of efficiently extracting large data sets from a database may include receiving a first result set from a first query executed on one or more data sources. The one or more data sources may use a first schema when the first query was executed. The method may also include receiving a second result set from a second query executed on the one or more data sources. The one or more data sources may use a second schema when the second query was executed. The method may further include generating a view that combines the first result set and the second result set. The view may resolve differences between the first schema and the second schema.

Abstract: A method for processing NF discovery requests using prioritized lists of preferred locations includes maintaining an NF profiles database including NF profiles of producer NFs registered to provide service to other NFs and a preferred locality attribute mappings database including mappings between preferred locality attributes and prioritized lists of preferred locations. The method includes receiving, from an NF, an NF discovery request including query parameters and a preferred locality attribute. The method further includes accessing the preferred locality attribute mappings database using the preferred locality attribute and obtaining a prioritized list of preferred locations corresponding to the preferred locality attribute, accessing the NF profiles database using the query parameters and identifying NF profiles of producer NFs capable of providing a service indicated by the query parameters, and prioritizing the NF profiles according to the prioritized list of preferred locations.

Abstract: Techniques for identifying one or more missing fragments within input text are disclosed. A discourse tree (DT) is generated for the input text (IT) received, the IT having any suitable number of sentence fragments. An indication that the IT is likely missing one or more sentence fragments may be identified based on determining that one or more rhetorical relationships of the DT matches one of a set of predefined rhetorical relationships. A query is generated one or more sentence fragments of the IT and executed against a knowledge base to obtain a set of search results. A most-relevance search result can be utilized to identify a set of candidate sentence fragments. A subset of those candidate sentence fragments can be identified based on comparing them to the sentence fragments provided in the IT, each candidate sentence fragment of the subset being implied but excluded from the IT.

Abstract: Techniques are described for automatically detecting and accommodating state changes in a computer-generated forecast. In one or more embodiments, a representation of a time-series signal is generated within volatile and/or non-volatile storage of a computing device. The representation may be generated in such a way as to approximate the behavior of the time-series signal across one or more seasonal periods. Once generated, a set of one or more state changes within the representation of the time-series signal is identified. Based at least in part on at least one state change in the set of one or more state changes, a subset of values from the sequence of values is selected to train a model. An analytical output is then generated, within volatile and/or non-volatile storage of the computing device, using the trained model.

Abstract: A method of detecting anomalous user behavior in a cloud environment includes calculating a first vector that is representative of actions taken during a plurality of previous time intervals; calculating a similarity between the first vector and a second vector that comprises counts of actions taken by the user during a current time interval; comparing the similarity to a baseline threshold to determine whether one or more anomalous actions have occurred; and generating an alert based at least in part on a determination that the one or more anomalous actions have occurred in the cloud environment.

Abstract: Efficiently implemented herein is a deterministic semantic for property updates by graph queries. Mechanisms of determinism herein ensure data consistency for graph mutation. These mechanisms facilitate optimistic execution of graph access despite a potential data access conflict. This approach may include various combinations of special activities such as detecting potential conflicts during query compile time, applying query transformations to eliminate those conflicts during code generation where possible, and executing updates in an optimistic way that safely fails if determinism cannot be guaranteed. In an embodiment, a computer receives a request to modify a graph. The request to modify the graph is optimistically executed after preparation and according to safety precautions as presented herein. Based on optimistically executing the request, a data access conflict actually occurs and is automatically detected.

Abstract: Techniques are described to determine whether an input utterance is unrelated to a set of skill bots associated with a master bot. In some embodiments, a system described herein includes a training system and a master bot. The training system trains a classifier of the master bot. The training includes accessing training utterances associated with the skill bots and generating training feature vectors from the training utterances. The training further includes generating multiple set representations of the training feature vectors, where each set representation corresponds to a subset of the training feature vectors, and configuring the classifier with the set representations. The master bot accesses an input utterance and generates an input feature vector. The master bot uses the classifier to compare the input feature vector to the multiple set representations so as to determine whether the input feature falls outside and, thus, cannot be handled by the skill bots.

Abstract: Systems and methods for supporting efficient virtualization in a lossless interconnection network. An exemplary method can provide, one or more switches, including at least a leaf switch, a plurality of host channel adapters, wherein each of the host channel adapters comprise at least one virtual function, at least one virtual switch, and at least one physical function, a plurality of hypervisors, and a plurality of virtual machines, wherein each of the plurality of virtual machines are associated with at least one virtual function. The method can arrange the plurality of host channel adapters with one or more of a virtual switch with prepopulated local identifiers (LIDs) architecture or a virtual switch with dynamic LID assignment architecture. The method can assign each virtual switch with a LID. The method can calculate one or more linear forwarding tables based at least upon the LIDs assigned to each of the virtual switches.

Abstract: Routines are used to connect bot queries entered via a bot interface and database queries executed on a database. Each routine is associated with routine configurations, including (a) query attributes associated with bot queries that trigger the routine, (2) a database query executed or to be executed for the routine, and/or (3) display settings for displaying information returned from the database query in a bot response. Each routine is configured to generate an output structured data object (SDO) indicating information returned from the database query and the display settings applicable to the information. The output SDOs from the various routines are transmitted to the bot application via a single API endpoint. The routine configurations are entered by a design user through one or more design user interfaces rendered by an integrative configuration application module.

Abstract: Systems and methods for a virtual network routing gateway that supports address translation for data plane as well as dynamic routing protocols are disclosed herein. The method can include coupling a gateway with a plurality of ports to a network having a plurality of first IP addresses in a private address space, generating a Network Address Translation (“NAT”) function in the gateway, inputting translation information into the NAT function, advertising routes based on the translation information, populating a unified routing table in the gateway based on the plurality of first IP addresses in the private address space and on translated route advertisements, receive an inbound network packet at the gateway, translating an inbound address of the inbound network packet with the NAT function, and delivering the network packet according to the routing table and based on the translated inbound address.

Abstract: A parametric constant resolves to different values in different contexts, but a single value within a particular context. An anchor constant is a parametric constant that allows for a degree of parametricity for an API point. The context for the anchor constant is provided by a caller to the API point. The anchor constant resolves to an anchor value that records specialization decisions for the API point within the provided context. Specialization decisions may include type restrictions, memory layout, and/or memory size. The anchor value together with an unspecialized type of the API point result in a specialized type of the API point. A class object representing the specialized type is created. The class object may be accessible to the caller, but the full value of the anchor value is not accessible to the caller. The API point is executed based on the specialization decisions embodied in the anchor value.

Abstract: Embodiments forecast demand of an item by receiving historical sales data for the item for a plurality of past time periods including a plurality of features that define one or more feature sets. Embodiments use the feature sets as inputs to one or more different algorithms to generate a plurality of different models. Embodiments train each of the different models. Embodiments use each of the trained models to generate a plurality of past demand forecasts for each of some or all of the past time periods. Embodiments determine a root-mean-square error (“RMSE”) for each of the past demand forecasts and, based on the RMSE, determine a weight for each of the trained models and normalize each weight. Embodiments then generate a final demand forecast for the item for each future time period by combining a weighted value for each trained model.

Abstract: Herein are techniques for dynamic aggregation of results of a database request, including concurrent grouping of result items in memory based on quasi-dense keys. Each of many computational threads concurrently performs as follows. A hash code is calculated that represents a particular natural grouping key (NGK) for an aggregate result of a database request. Based on the hash code, the thread detects that a set of distinct NGKs that are already stored in the aggregate result does not contain the particular NGK. A distinct dense grouping key for the particular NGK is statefully generated. The dense grouping key is bound to the particular NGK. Based on said binding, the particular NGK is added to the set of distinct NGKs in the aggregate result.

Abstract: Techniques for storing and processing large volumes of data by increasing the number of partitions that customers can allocate and use for their streams while minimizing the physical footprint of the partitions is disclosed. In certain examples, the stream partitions are created as different logical partitions on a physical partition in a physical storage cluster of a distributed message streaming system. The disclosed system provides an improved process for reading messages stored in different logical partitions of a physical partition by identifying partition chunks in a physical partition that comprise subsets of messages associated with a logical partition and filtering out partition chunks that do not contain messages associated with the logical partition. The disclosed system reduces the amount of the physical partition that needs to be read to retrieve messages stored in different logical partitions thereby improving the overall performance of the distributed message streaming system.

Abstract: In exemplary embodiments, a computer system detects performance anomalies for user computer services. Physical databases convert physical database KPIs into logical database KPI vectors for individual user services and individual time intervals. Physical application servers convert physical application server KPIs into logical application server KPI vectors for the individual user services and time intervals. Physical web servers convert physical web server KPIs into logical web server KPI vectors for the individual user services and time intervals. A KPI server combines the logical database KPI vectors, the logical application server KPI vectors, and the logical web server KPI vectors for individual time intervals into user service KPI vectors for the individual user services during the time intervals. The KPI server detects outlier user service KPI vectors as compared to normal user service KPI vectors and indicates corresponding computer performance anomalies for the user services.

Abstract: Described herein are systems and methods for a DAG based transaction processing system and method in a distributed ledger. In accordance with an embodiment, a DAG based transaction processing system and method in a distributed ledger can be introduced. The model can help achieve improved throughput performance. With additional weight mechanism, the final performance can be adjusted based on various business requirements. This is different from existing work that uses linear structure and can achieve better performance.

Abstract: A server system can receive an input identifying a problem to generate a solution using a machine-learning application. The method selects a machine-learning model template from a plurality of templates based at least in part on the input. The method analyzes one or more formats of the customer data to generate a customer data schema based at least in part a data ontology that applies to the identified problem. The method determines whether the customer data schema is misaligned with one or more key features of the selected machine-learning model template. Based on this determination, the method analyzes the metadata for the selected machine-learning model template to determine what additional information is required to re-align the customer data with the data expectations. The method can include gathering the addition information required to re-align the customer data with the data expectations of the selected machine-learning model template.

Abstract: In one embodiment of systems and methods described herein, a computing device is configured to generate and display a user interface including one or more selectable generic options; receive a selection of a data analysis function to perform machine learning; translate the selected function into pre-configured commands for each back-end tool that are specific to each back-end tool for performing the selected function, wherein the pre-configured commands identify and access specific schema with a compatible format for reading the specific schema from each back end tool to expose retail-specific data sets in accordance with the specific schema; execute the preconfigured commands based on the specific schema and retrieve corresponding retail-specific data from a plurality of the back-end tools based on the specific schema; and execute the selected data analysis function on the retrieved retail-specific data from the plurality of back-end tools and generate a data analysis result using Artificial Intelligence-Ena

Abstract: Techniques for automatically switching between chatbot skills in the same domain. In one particular aspect, a method is provided that includes receiving an utterance from a user within a chatbot session, where a current skill context is a first skill and a current group context is a first group, inputting the utterance into a candidate skills model for the first group, obtaining, using the candidate skills model, a ranking of skills within the first group, determining, based on the ranking of skills, a second skill is a highest ranked skill, changing the current skill context of the chatbot session to the second skill, inputting the utterance into a candidate flows model for the second skill, obtaining, using the candidate flows model, a ranking of intents within the second skill that match the utterance, and determining, based on the ranking of intents, an intent that is a highest ranked intent.

Abstract: A first set and a second set are identified as operands for a set operation of a similarity analysis task iteration. Using respective minimum hash information arrays and contributor count arrays of the two sets, a minimum hash information array and contributor count array of a derived set resulting from the set operation is generated. An entry in the contributor count array of the derived set indicates the number of child sets of the derived set that meet a criterion with respect to a corresponding entry in the minimum hash information array of the derived set. The generated minimum hash information array and the contributor count array are stored as part of input for a subsequent iteration. After a termination criterion of the task is met, output of the task is stored.

Abstract: Techniques described herein allow a user of an RDBMS to specify a graph algorithm function (GAF) declaration, which defines a graph algorithm that takes a graph object as input and returns a logical graph object as output. A database dictionary stores the GAF declaration, which allows addition of GAFs without changing the RDBMS kernel. GAFs are used within graph queries to compute output properties of property graph objects. Output properties are accessible in the enclosing graph pattern matching query, and are live for the duration of the query cursor execution. According to various embodiments, the declaration of a GAF includes a DESCRIBE function, used for semantic analysis of the GAF, and an EXECUTE function, which defines the operations performed by the GAF. Furthermore, composition of GAFs in a graph query is done by supplying, as the input graph argument of an outer GAF, the result of an inner GAF.

Abstract: Techniques are disclosed for cryptographically secure shuffling processes for generating and utilizing secrets in an infrastructure-as-a-service (IaaS) environment. In an embodiment, a method comprises generating a source list and a destination list, the source list and destination list association with a sequential format and the source list comprising a plurality of elements in the sequential format; generating a first random number and a second random number; determining a first element in the source list, the first element corresponding to a position in the sequential format of the source list based on the first random number; determining a first destination position in the destination list, the first destination position corresponding to a position in the sequential format of the destination list based on the second random number; and updating the destination list to include the first element in the source list at the first destination position.

Abstract: The disclosed systems, methods and computer readable media relate to managing Non-Volatile Memory Express (NVMe) over Transmission Control Protocol (TCP) (NVMeOTCP) connections between a smart network interface card (smartNIC) and a block storage data plane (BSDP) of a cloud computing environment. A software agent (“agent”) executing at the smartNIC may manage a number of network paths (active and, in some cases, passive network paths). The agent may monitor the network traffic (e.g., input/output operations (IOPS)) through the paths (e.g., using established NVMeOTCP connections corresponding to the paths). If a condition is met relating to a performance threshold associated with the monitored paths, the agent may increase or decrease the number established NVMeOTCP connections to match real time network conditions.

Abstract: Techniques for a database management system to predict when in the future a materialized view will have a quiet period during which the materialized view will not be stale. This is a followed by an approach that uses the quiet period prediction to determine an optimized schedule for refreshing the materialized view. The approach combines the quiet period prediction with a query rewrite pattern prediction for the materialized view and an estimated refresh duration for the materialized view to determine the optimized refresh schedule for the materialized view.

Abstract: The disclosed embodiments relate to a system that characterizes susceptibility of an inferential model to follow signal degradation. During operation, the system receives a set of time-series signals associated with sensors in a monitored system during normal fault-free operation. Next, the system trains the inferential model using the set of time-series signals. The system then characterizes susceptibility of the inferential model to follow signal degradation. During this process, the system adds degradation to a signal in the set of time-series signals to produce a degraded signal. Next, the system uses the inferential model to perform prognostic-surveillance operations on the set of time-series signals with the degraded signal. Finally, the system characterizes susceptibility of the inferential model to follow degradation in the signal based on results of the prognostic-surveillance operations.

Abstract: In accordance with an embodiment, described herein is a system and method for dependency analysis for a calculation script in a multidimensional database computing environment. A multidimensional database cube aggregation can be represented as a lattice of blocks or cube, arranged according to a database outline (e.g., intra-dimensional or member hierarchy). When the multidimensional database system performs computations in parallel for a given calculation script, portions of the cube that can be computed concurrently are identified.

Abstract: Systems, devices, and methods of the present invention involve discourse trees. In an example, a method involves generating a discourse tree. The method includes identifying, from the discourse tree, a central entity that is associated with a rhetorical relation of type elaboration and corresponds to a topic node that identifies a central entity of the text. The method includes determining a subset of elementary discourse units of the discourse tree that are associated with the central entity. The method includes forming generalized phrases from the subset of elementary discourse units. The method includes forming tuples from the generalized phrases, where a tuple is an ordered set of words in normal form. The method involves responsive to successfully converting an elementary discourse unit associated with an identified tuple into a logical representation, updating the ontology with an entity from the identified tuple.

Abstract: The present disclosure relates generally to determining intent based upon speech input using a dialog system. More particularly, techniques are described using matching-based machine learning techniques to identify an intent corresponding to speech input in a dialog system. These procedures do not require training when intents are added or removed from the set of possible intents.

Abstract: Systems that determine relationships between network components of a cluster using packet filters are disclosed. A system can identify objects that implement services of a cluster and network connections associated with respective pairs of the objects. The system can also filter out network connections from the identified network connections. The filtering can remove connections between source objects and destination objects based on the destination objects lacking any components that implement a service in cluster. The filtering can also retain network connections between source objects and destination objects based on the source objects including components that each implement at least one service, and based on the second destination object including components that each implement at least one service. Additionally, the system can generate relationship maps and network topologies using the determined relationships.

Abstract: Methods, systems, and computer readable media for enabling forwarding of subsequent network function subscription updates. A method includes forwarding, from a bootstrapped network function repository function (NRF) in a first region, a subscription creation request from a consumer network function to a target NRF in a second region. The method includes creating, at the target NRF, a subscription for the consumer network function. The method includes generating, at the target NRF, a hint comprising data indicating one or more alternate NRFs each sharing subscription state data with the target NRF. The method includes sending, from the target NRF to the consumer network function, a subscription response message including the hint.

Abstract: Systems and methods for using InfiniBand routing algorithms for Ethernet fabrics in a high performance computing environment. The method can provide, at a computer comprising one or more microprocessors, a plurality of switches, a plurality of hosts, a topology provider (TP) module, a routing engine (RE) module, and a switch initializer (SI) module. The method can perform a discovery sweep, by the TP, of the plurality of hosts and the plurality of switches and assigns an address to each of the plurality of hosts and the plurality of switches. The method can calculate, by the routing engine, a routing map, based upon a routing scheme, for the plurality of hosts and the plurality of switches, the routing map comprising a plurality of forwarding tables. The method can configure, each of the plurality of switches with a forwarding table of the plurality of forwarding tables calculated by the routing engine.

Abstract: Methods, systems, and computer readable media for processing binding requests in a telecommunications network. A method includes receiving, at a binding support function (BSF), a first request to create a first binding between a protocol data unit (PDU) session and a first policy and control function (PCF). The method includes creating, at the BSF, the first binding between the PDU session and the first PCF and storing, with the first binding, a first PCF session acceptance timestamp from a first header of the first request. The method includes receiving, at the BSF, a second request to create a second binding between the PDU session and a second PCF. The method includes determining, at the BSF, whether to accept or reject the second request based on a difference between the first PCF session acceptance timestamp and a second PCF session acceptance timestamp from a second header of the second request.

Abstract: A tool may provide a real-time analysis of potential bottlenecks while threads wait on locks held by other threads. For each job currently operating on the server instance, the tool may access a list of threads and retrieve call stacks associated with those threads. The call stacks may then be analyzed to identify threads that are holding a lock, along with any corresponding threads that are waiting on the lock. The locks may be held on memory resources or any other type of computing resource. These bottlenecks may be identified and an adjustment of the configuration of the server instance may be triggered in response that is configured to reduce the likelihood that these types of bottlenecks may occur in the future.

Abstract: Techniques discussed herein are directed to identifying health assessment data of a set of computing instances of a distributed computing system. The health assessment data may be collected from the computing instances and stored in a first distributed cache. When a request for health assessment data for one or more computing instances is received, the health assessment data may be retrieved from the first distributed cache, provided to the requesting entity, and stored in a second distributed cache. A subsequent request may cause new health assessment data to be retrieved from the first distributed cache and compared to the stored data of the second distributed cache. Changes in the health assessment data may be identified and data indicating those changes may be provided in response to the subsequent request. One or more remedial actions may be performed in response to the health assessment data obtained.

Abstract: A computer comprising one or more processors and memory may implement multiple threads that perform a lock operation using a data structure comprising an allocation field and a grant field. Upon entry to a lock operation, a thread allocates a ticket by atomically copying a ticket value contained in the allocation field and incrementing the allocation field. The thread compares the allocated ticket to the grant field. If they are unequal, the thread determines a number of waiting threads. If the number is above the threshold, the thread enters a long term wait operation comprising determining a location for long term wait value and waiting on changes to that value. If the number is below the threshold or the long term wait operation is complete, the thread waits for the grant value to equal the ticket to indicate that the lock is allocated.

Abstract: In accordance with an embodiment, described herein is a system and method for aggregating values through risk dimension hierarchies to create risk models in a multidimensional database. The system can include a cube that stores a plurality of standard risk measures organized into different risk dimension hierarchies, and a pluggable calculation engine executing a plurality of scripts to dynamically operate on any value in the cube. The system can aggregate values through the plurality of risk dimensional hierarchies, and either store an aggregated value against a dimension member, or dynamically calculate the aggregated value on demand. By aggregating values through the risk dimension hierarchies, a plurality of risk models can be built to measure a variety of risks.

Abstract: Techniques for managing a software build using a machine learning model are disclosed. A system obtains historical data associated with historical software builds. The historical data includes attribute data for a plurality of development stages associated with a historical software build and labels indicating success or failure for the plurality of development stages. The system trains a machine learning model using the historical data associated with the historical software builds to generate predictions of success or failure of the plurality of development stages. The system receives attributes of a target software build and a selection of a first target development stage of the target software build. The system applies the machine learning model to the target software build to generate a first prediction of success or failure of the first target development stage.

Abstract: New data structures for analyzing a log are generated. A hierarchical data structure includes a plurality of hierarchical nodes. Each node is associated with data and metadata. Each node may also be associated with analysis data. Information (data, metadata, and/or analysis data) of an ancestor node is imputed to a descendant node; a descendant node inherits the information of an ancestor node. When determining analysis data for a particular hierarchical node, information from any ancestor node to the particular hierarchical node may be used; however, information from non-ancestor nodes is not necessarily used. A timeline data structure includes a reference to a hierarchical node within a hierarchical data structure and a reference to an event type. The timeline data structure is thereby associated with the information of the referenced hierarchical node and information of any ancestor nodes to the referenced hierarchical node.

Abstract: The present disclosure relates to systems and methods that use an artificial intelligence (AI) model to generate outputs that can be evaluated to predict which logged entry items match entry request record line items of an entry request record. Additionally, the present disclosure relates to systems and methods for intelligently detecting anomalies within data sets.

Abstract: Techniques for generating text content arranged in a consistent read order from a source document including text corresponding to different read orders are disclosed. A system parses a binary file representing an electronic document to identify characters and metadata associated with the characters. The system pre-sorts a character order of characters in each line of the electronic document to generate an ordered list of characters arranged according to the right-to-left reading order. The system performs a layout-mirroring operation to change a position of characters within the modified document relative to a right edge of the document and a left edge of the document. Subsequent to performing layout-mirroring, the system identifies native left-to-right reading-order text in-line with the native right-to-left reading-order text.

Abstract: Techniques discussed herein relate to provisioning one or more virtual cloud-computing edge devices at a physical cloud-computing edge device. A manifest may be generated/utilized to specify various attributes of the virtual cloud-computing edge devices to be executed at a physical cloud-computing edge device. A first set of resources corresponding to a first virtual cloud-computing edge device may be obtained from memory of a centralized cloud-environment and provisioned at the first virtual cloud-computing edge device. Similar operations may be performed with respect to a second virtual cloud-computing edge device. The techniques described herein split the physical edge device into multiple virtual device resources that can be utilized in combination or separately to extend the functionality and versatility of the physical edge device.