Abstract: A computer-implemented method of generating functional safety data for a design of an electronic component includes receiving attribute data for elements in an electronic component. The attribute data include element data for the elements, wherein element data for a given element include an identity of the given element and a failure rate characteristic for the given element. The attribute data include functionality data for element functionalities, wherein functionality data for a given element functionality include an identity of a use case, an identity of an element, an identity of a fault characterization for providing information about one or more fault models and a configurable data for controlling selection and use of the given functionality data when generating the functional safety data. The method also includes generating the functional safety data using the attribute data and storing a report including the functional safety data.

Abstract: A device for determining whether a defect of a component is determinable based on results of predefined diagnostic options, including: storing, in a matrix, parameters which, for each combination of one component defect and one diagnosis result, provide a measure of whether the respective defect is possible for the respective diagnosis result, the matrix rows being assigned to one of the diagnosis results, the matrix columns being assigned to one of the defects; selecting at least two matrix rows which, for a diagnosis result consistent with the defect to be identified, include a parameter greater than a predefined first limiting value; calculating a result vector by the element-wise multiplication of the selected matrix rows; and determining whether the result vector includes at least one element not smaller than a predefined second limiting value, the result vector elements, which are smaller, not being greater than a predefined third limiting value.

Abstract: Artificial intelligence procedures are disclosed for localizing faults in corrupted messages in 5G and 6G, and for correcting those faults based on measured parameters such as backgrounds and message signals. Message faults can be caused by noise or interference from a variety of sources with a wide range of properties. An AI model with multiple adjustable variables may be “trained” using a large number of message events, including faulted messages, to determine which message elements are likely faulted, based on input parameters such as modulation quality, SNR, and other signal properties. The receiving entity can then attempt a grid search to correct the faulted message elements, or request a retransmission. For field use by base stations and user devices, an algorithm may be developed based on the AI model, and configured to predict which message elements are likely faulted.

Abstract: System and techniques for computer vision assisted item search are described herein. A composite image, including visual data and depth data, may be obtained. The composite image may be filtered to isolate a clothing article represented in the composite image. A classifier may be applied to the depth data to produce a set of clothing attributes for the clothing article. The clothing attributes may then be provided to a remote device.

Abstract: A process for analyzing an incident includes setting up an alert for a high error rate on a particular endpoint. Once the alert is triggered, a set of traces for transactions exhibiting errors on the offending endpoint is queried. All traces for other services/operations that include errors on the offending endpoint are also enumerated. A set of baseline transactions that involve the offending endpoint, but do not result in error may be utilized to determine whether the errors are always present, or are distinctive for certain offending transactions. All traces are ranked based on a statistic. Once the traces have been ranked, they may be traced down to a deepest/most terminal error. A set of transactions that correlate to the terminal error may also be analyzed to determine infrastructure causes.

Abstract: A probabilistic data structure may be queried to test whether text of a received log message is present in the probabilistic data structure. The representative log messages may be included in respective existing clusters are included in the probabilistic data structure. Based on whether the text is present, whether to create a new cluster for the received log message may be determined.

Abstract: Techniques for monitoring Voice-over-IP (VoIP) network services over the Internet are disclosed. In some embodiments, a system, process, and/or computer program product for monitoring and/or troubleshooting VoIP network services over the Internet includes performing VoIP call initiation testing using a source agent and a target agent; performing synthetic VoIP call quality testing using the source agent and the target agent over the Internet; and generating a report based on the VoIP call initiation testing and the synthetic VoIP call quality testing over the Internet.

Abstract: Examples described herein generally relate to receiving a query context for service events occurring on one or more networks, determining, based on the query context, a set of service events occurring on the one or more networks, querying multiple layers of a multiple-layer relational graph to determine one or more other service events having a defined relationship with the set of service events at one or more of the multiple layers, where the multiple layers include a configuration layer, an observation layer, and learned layer, defining relationships between services or service events, and indicating, via a user interface and in response to the query context, the one or more other service events.

Abstract: An evaluation device of an embodiment includes a storage, a data generator, a class definer, a characteristic data divider, and an evaluator. The data generator is configured to generate a set of characteristic data from both a set of first data and at least a set of second data, the at least set of second data being associated in time information with the set of first data, the set of characteristic data representing a plurality of characteristics. The characteristic data divider is configured to divide the plurality of sets of characteristic data into a plurality of groups on the basis of the plurality of classes defined by the class definer and condition of operations included in the set of first data. The evaluator is configured to evaluate a operating state using a first model defined for each of the plurality of groups divided by the characteristic data divider.

Abstract: One embodiment of the present invention can provide a system for identifying a root cause of an anomaly event in operation of one or more machines is provided. During operation, the system can obtain sensor data from a set of sensors associated with the one or more machines, convert the sensor data into a set of sensor states, build an optimal DAG based on the set of sensor states to model causal dependency; determining, by using the DAG, a probability of an anomaly state of a target sensor given a state of a direct neighbor sensor, and determining a root cause of the anomaly event associated with the target sensor by back-tracking the anomaly state in the DAG.

Abstract: Techniques for monitoring Voice-over-IP (VoIP) network services over the Internet are disclosed. In some embodiments, a system, process, and/or computer program product for monitoring and/or troubleshooting VoIP network services over the Internet includes performing VoIP call initiation testing using a source agent and a target agent; performing synthetic VoIP call quality testing using the source agent and the target agent over the Internet; and generating a report based on the VoIP call initiation testing and the synthetic VoIP call quality testing over the Internet.

Abstract: A learning method detects anomalies and is implemented on a microcontroller including at least one memory, the microcontroller being configured to receive data sets coming from at least one sensor, the memory being configured to store a maximum number of categories, a category including at least a signature and an occurrence.

Abstract: According to examples, an apparatus may include a processor and a memory on which is stored machine readable instructions. The instructions may cause the processor to receive a call request for a cloud-based service and retrieve a first policy corresponding to the cloud-based service, the first policy identifying a policy reroute. The instructions may also cause the processor to determine which second policy of a plurality of second policies that corresponds to the policy reroute and retrieve the second policy that the corresponds to the policy reroute. The instructions may further cause the processor to apply the second policy on the cloud-based service and respond to the call request following the application of the second policy.

Abstract: A method for providing computer-related support to an end user is described. The method includes receiving, from a mobile device, an image of a user-readable message that is displayed by a computing device. The method also includes identifying one or more solutions using text extracted from the image of the user-readable message. The method further includes sending the one or more solutions to the mobile device for display on the mobile device.

Abstract: Systems and methods are described herein for logging system events within an electronic machine using an event log structured as a collection of tree-like cause and effect graphs. An event to be logged may be received. A new event node may be created within the event log for the received event. One or more existing event nodes within the event log may be identified as having possibly caused the received event. One or more causal links may be created within the event log between the new event node and the one or more identified existing event nodes. The new event node may be stored as an unattached root node in response to not identifying an existing event node that may have caused the received event.

Abstract: A computer-implemented method for detecting compromised automated teller machines is provided. The method includes receiving activity data from an ATM, activity data including user input data and machine data, wherein user input data includes instructions input by a user at the ATM during a transaction, and wherein machine data is associated with processes performed by the ATM; storing operating parameter rules in the memory, the operating parameter rules configured to indicate whether the received activity data is within a normal activity range for the ATM; applying the received activity data to the operating parameter rules; generating an activity score for the ATM based on the applying, wherein the activity score is configured to indicate a likelihood that the ATM is compromised; and initiating a response based on the activity score.

Abstract: An intelligent target object detection and alerting platform may be provided. The platform may receive a content stream from a content source. A target object may be designated for detection within the content stream. A target object profile associated with the designated target object may be retrieved from a database of learned target object profiles. The learned target object profiles may be associated with target objects that have been trained for detection. At least one frame associated with the content stream may be analyzed to detect the designated target object. The analysis may comprise employing a neural net, for example, to detect each target object within each frame. A parameter for communicating target object detection data may be specified. In turn, when the parameter is met, the detection data may be communicated.

Abstract: An alert management system for a configuration management database (CMDB) platform includes a client instance configured to: apply a first filter of an alert rule to CMDB alerts to select a first alert based on context of the first alert and apply a second filter of the alert rule to the CMDB alerts to select a second alert based on context of the second alert, wherein the context of the first and second alerts includes details regarding the first and second alerts and associated configuration items (CIs). The client instance is also configured to: evaluate at least one condition of the alert rule using the context of the first and/or second alert; and in response to evaluating the at least one condition of the alert rule to be true, performing at least one action of the alert rule using the context of the first and/or second alert.

Abstract: A capacitive touch sensor is disclosed for use with input signal. The capacitive touch sensor includes a number n of input/output lines. Each of the number n of input/output lines is electrically disconnected from every other of the number n of input/output lines. Each of the number n of input/output lines is arranged to cross every other of the number n of input/output lines. Each of a number ? of positions includes one of the number n of input/output lines crossing another of the number n of input/output lines.

Abstract: A method and detector for detecting anomalies among media event sequences are disclosed. One method includes obtaining a first profile of media event data over a first time period, where the first profile is a first distribution of different media event sequences. Each sequence is associated with a number of occurrences of the sequence and the first profile having a first profile vector. The method further includes obtaining a second profile of media event data over a second time period less than the first time period. The second profile is a second distribution of the different media sequences and the second profile having a second profile vector. The method also includes comparing the first profile vector and the second profile vector, and determining one of a presence and absence of at least one anomaly in the second profile vector of media event data based on the comparison.

Abstract: The present disclosure relates generally to facilitating routing of communications across external systems. More specifically, techniques are provided to dynamically route issue tracking tickets to disparate endpoints based on the content of the ticket.

Abstract: A processor-readable storage device storing instructions that cause a processor to perform operations including, subsequent to determining, at a first device based on a first file attribute associated with a file, that a classification for the file is unavailable at the first device, sending the first file attribute from the first device to a second device to determine whether the classification for the file is available at the second device. The operations include receiving a notification at the first device from the second device that the classification for the file is unavailable at the second device. The operations include, determining the classification for the file by performing, at the first device, an analysis of a second file attribute based on a trained file classification model. The operations include sending the classification from the first device to the second device and to a third device.

Abstract: An infrastructure backup system includes an infrastructure manager system coupled to infrastructure devices via a network. A first infrastructure device includes a management controller database storing component dependency information identifying dependenc(ies) between a first component in the first infrastructure device and a second component in a second infrastructure device. A management controller device in the first infrastructure device receives a predicted failure for the first component from the infrastructure manager system and performs first backup operations to generate first component backup data based on the identification of the predicted failure for the first component. Based on the component dependency information that identifies the dependency between the first component and the second component, the management controller device also performs second backup operations to generate second component backup data.

Abstract: For incident management, parsing, responsive to an incident ticket being opened relative to a first application. The parsing identifying a set of incident data. Identifying, using a dependency graph, a set of applications, wherein each application in the set of applications is dependent on the first application through at least one dependency relationship. Notifying, responsive to the incident ticket, a subset of a set of users of a second application about the incident ticket related to the first application, the second application being a member of the set of applications, the subset of the set of users of the second application performing a type of transaction with the second application wherein the type of transaction is indicated in a dependency relationship between the first application and the second application. Preventing a user in the subset of users from creating a second incident ticket.

Abstract: A computer-implemented method performed in a computerized system incorporating a central processing unit, a localization signal receiver, a plurality of sensors, separate and distinct from the localization signal receiver, and a memory, the computer-implemented method involving: using the central processing unit to initialize a plurality of particles based on an information on a map graph; using the central processing unit to repeatedly execute a particle filter loop, wherein the particle filter loop includes: using the central processing unit to perform a motion update of the plurality of particles; using the central processing unit to perform a measurement update of the plurality of particles; and using the central processing unit to perform a resampling of the plurality of particles based on particle importance weights and the map graph information. The location of the computerized system is subsequently determined based on the plurality of particles.

Abstract: A machine learning module is trained by receiving inputs comprising attributes of a computing environment, where the attributes affect a likelihood of failure in the computing environment. In response to an event occurring in the computing environment, a risk score that indicates a predicted likelihood of failure in the computing environment is generated via forward propagation through a plurality of layers of the machine learning module. A margin of error is calculated based on comparing the generated risk score to an expected risk score, where the expected risk score indicates an expected likelihood of failure in the computing environment corresponding to the event. An adjustment is made of weights of links that interconnect nodes of the plurality of layers via back propagation to reduce the margin of error, to improve the predicted likelihood of failure in the computing environment.

Abstract: Aspects of the present disclosure provide a method and apparatus for maintenance recommendations. Embodiments include receiving data related to a plurality of fault codes. Embodiments include determining, for each respective fault code of the plurality of fault codes, a unique subset of parameters for the respective fault code based on frequencies of the parameters within the plurality of fault codes in the data. Embodiments include receiving a plurality of fault records and a plurality of maintenance records. Embodiments include, for each respective maintenance record of the plurality of maintenance record, identifying one or more candidate fault records of the plurality of fault records and correlating a subset of the one or more candidate fault records with the respective maintenance record based on the unique subset of the parameters for the respective fault code corresponding to each respective candidate fault record of the one or more candidate fault records.

Abstract: In one embodiment, an issue analysis service determines that an issue exists with a device in a network. The service searches a decision tree for a solution to the issue, wherein branch nodes of the decision tree comprise diagnostic checks. The service clusters, based on a determination that a solution to the issue does not exist in the decision tree, telemetry for the device with telemetry for one or more other devices that also experienced the issue. The service uses a neural network to identify a difference between the clustered telemetry and telemetry from one or more devices for which the issue was resolved. The service adds a leaf node to the decision tree with the identified difference as a solution to the issue.

Abstract: A system may include (i) a database disposed within a computational instance of a remote network management platform that manages a managed network and (ii) server device(s) associated with the computational instance. The database is configured to store records related to issues with configuration items of the managed network, each record assigned to one of a plurality of states including: a first state for newly-opened records, a second state for records undergoing assessment, a third state for records undergoing root cause analysis, a fourth state for records with a fix in progress, a fifth state for resolved records, and a sixth state for closed records. Additionally, the server device(s) are configured to generate and provide graphical user interface panes to a client device associated with the managed network, each of the graphical user interface panes corresponding to one of the plurality of states for a particular record.

Abstract: A method including receiving events from different data sources for a service automatically executing in an enterprise system. A first event is enriched by providing the first event with first metadata that associates the first event with a first application used by the service. The first event is assigned to a time slice associated with the first application. A second event is enriched in a similar manner. A correlation graph of nodes and edges is built using the enriched events, with nodes representing the events and edges indicating relationships between the edges. A third event indicating a fault in the first application associated with the first node is received. The source of the error for the third event is identified using the second updated correlation graph and the time slice. The source of error is then mitigated.

Abstract: A system retrieves cluster data for a cluster including one or more nodes and one or more pods. The system displays, on a visual interface, a cluster visualization based on the retrieved cluster data. The cluster visualization includes, for each of the one or more nodes, a node spoke graphical element. Each node spoke graphical element includes a pod region indicating pods of the node and a health region indicating one or more health metrics of the node. A particular pod of the one or more pods in the cluster data is represented in the cluster visualization by a pod graphical element at the pod region of a node graphical element of a node corresponding to the particular pod. A graphical feature of the pod graphical element is indicative of at least one of one or more health metrics of the particular pod and one or more health metrics of a pod element within the particular pod.

Abstract: A system for automated testing of functionally complex systems, comprising a test manager, a test execution module, and a correlation engine, is disclosed. The test manager module causes tests to be executed by the test execution engine, and on detection of an anomalous test result, the test manager module at least causes additional testing to be performed and causes the correlation engine module to analyze the results of at least some of the additional testing in order to isolate at least one component exhibiting anomalous behavior.

Abstract: Systems and methods for communications network failure detection and remediation utilizing link probes are disclosed. Exemplary methods include: receiving first communications from a first client; authenticating the first user of the first client; creating a registration for the first client in a registration database; establishing a connection to the first client; detecting the connection to the first client has failed, the detecting comprising using a link probe to test connectivity of the first client and utilizing a voting scheme, based on the plurality of connectivity test results, to determine that the connection to the first client has failed; receiving second communications from the second client; authenticating the first user of the second client using the telephone number and the security credential; removing the registration for the first client from the registration database; creating a registration for the second client; and establishing a connection to the second client.

Abstract: Methods, apparatus, and processor-readable storage media for determining server issues related to software versions using artificial intelligence techniques are provided herein. An example computer-implemented method includes determining one or more server issues, among multiple reported server issues, as being related to one or more software version states; labeling, using at least one clustering algorithm, each of at least a subset of the servers as being associated with at least one of the determined server issues; generating, by processing data pertaining to at least a portion of the labeled servers using artificial intelligence techniques, at least one knowledge base identifying automated actions to be carried out in response to observed data related to the one or more server issues; monitoring metrics across at least a portion of the one or more servers; and performing one or more automated actions based on the monitoring and the at least one knowledge base.

Abstract: A log transmission apparatus is a log transmission apparatus connected to a log collection apparatus via a communication network, and includes an application execution unit which outputs a log, an environment change management unit which generates an environment code as information indicating a change in a state of the log transmission apparatus, and a transmission unit which transmits the log and the environment code to the log collection apparatus, in which the environment change management unit generates the environment code indicating a change in the state during a period from a previous output to present output of the log by the application execution unit.

Abstract: A method for cause analysis of a configuration exception occurred during the execution of a computer program on a programmable computer. The method includes executing the program on the computer. Exception information associated with the configuration exception may be extracted. The method may use context information and circumstances under which the configuration exception occurred. The method may also use data indicative of experiences of other developers that had a similar exception. A set of possible causes may be looked up from a knowledge base; wherein looking up the set of possible causes is based on context information related to the computer program.

Abstract: First-order anomaly scores are received from related anomaly detectors. Each first-order anomaly score indicates a likelihood of an anomaly at a target system. A relatedness measure of the related anomaly detectors is determined, based on the first-order anomaly scores that have been received. A higher-order anomaly score is determined based on the relatedness measure that has been determined. The higher-order anomaly score indicates a likelihood of an anomaly at the target system. An anomaly at the target system is detected based on the higher-order anomaly score.

Abstract: A method of root cause diagnosis of fault data from a vehicle includes identifying a first vehicle fault and selecting from field repair data a vehicle feature corresponding to the identified first vehicle fault. The method also includes identifying from the field repair data an effective repair of the identified first vehicle fault. The method additionally includes training and testing via a machine learning algorithm, a labor code classifier using the identified effective repair of the first vehicle fault and the selected vehicle feature corresponding to the identified first vehicle fault. The method also includes identifying and classifying, using the trained classifier, indistinguishable labor codes. Furthermore, the method includes communicating the identified and classified indistinguishable labor codes for diagnosing a root cause of real time first vehicle fault data.

Abstract: In the field of Internet of Things understanding need of applications and translating them to network parameters and protocol parameters is a major challenge. This disclosure addresses problem of enabling network services by cognitive sense-analyze-decide-respond framework. A processor implemented method is provided for enabling network aware applications and applications aware networks by a sense analyze decide respond (SADR) framework.

Abstract: Methods, systems, and computer-readable storage media for receiving, by an auto-pilot platform, one or more log files from an in-memory system, determining, by the auto-pilot platform, occurrence of a first error within the in-memory system based on the one or more logs, wherein the first error is indicated by a first error code within the one or more log files, identifying, by the auto-pilot platform, a first resolution from a resolution repository based on the first error code, the resolution repository including one or more mappings associating error codes to resolutions including associating the first error code with the first resolution, initiating, by the auto-pilot platform, execution of the first resolution, and updating, by the auto-pilot platform, the resolution repository based on execution of the first resolution.

Abstract: An application performance management system is disclosed. Operational elements are dynamically discovered and extended when changes occur. Programmatic knowledge is captured. Particular instances of operational elements are recognized after changes have been made using a fingerprint/signature process. Metrics and metadata associated with a monitored operational element are sent in a compressed form to a backend for analysis. Metrics and metadata from multiple similar systems may be used to adjust/create expert rules to be used in the analysis of the state of an operational element. A 3-D user interface with both physical and logical representations may be used to display the results of the performance management system.

Abstract: A system for handling errors in a neural network includes a neural network processor for executing a neural network associated with use of a vehicle. The neural network processor includes an error detector configured to detect a data error associated with execution of the neural network and a neural network controller configured to receive a report of the data error from the error detector. In response to receiving the report, the neural network controller is further configured to signal that a pending result of the neural network is tainted without terminating execution of the neural network.

Abstract: An embodiment of the present invention is directed to generating a branch health index. The innovative method is directed to generating a Branch Health Index (BHI) designed to provide a comprehensive measurement for ATM performance. According to an embodiment of the present invention, BHI takes into account ATM availability, service response/repair times and customer impacts to score every ATM on a predetermined scale. The method applies a weighted scoring algorithm designed to take into account a multitude of attributes. The score may then be used to determine graphical status, such as a red/amber/green status of the ATM.

Abstract: In one implementation, a computer-implemented method includes receiving information that describes an issue with a building; accessing data that identifies (i) a plurality of components that are included in the building and (ii) features of the plurality of components; identifying one or more candidate components that have at least a threshold likelihood of being a cause of the issue; selecting a candidate service provider from among a plurality of service providers based on a comparison of (i) the one or more candidate components and (ii) information identifying technical qualifications for the plurality of service providers; transmitting a service request for the issue to the candidate service provider; receiving a response from the candidate service provider; and scheduling, based on the response, a service appointment with the candidate service provider to resolve the issue.

Abstract: A method for detecting repairable boards requiring repair amongst many boards which may or may not require repair applies a board detection model based on training features of many sample repairable boards. The method obtains repair-relevant information of all the sample repairable boards, extracts predetermined features from the repair-relevant information, and analyzes the predetermined features to obtain the training features. The board detection model is established and trained based on the training features, and receives repair-relevant information of each repairable board to obtain a result of detection repairable board according to the board detection model. A device for detecting repairable boards is also provided.

Abstract: A conversational bot system uses a set of conversations that have been annotated to identify speech acts, wherein a speech act is a labeled grouping of utterances. To facilitate processing, a data model associated with a multi-turn conversation is received. The data model comprises an observation history. Upon receipt of query that includes a sequence of at least two or more utterances, an utterance ranking algorithm is applied. The algorithm selectively reorders the utterances in the sequence into a ranked order of importance that reflects a lowest to highest priority of response. In response to applying the utterance ranking algorithm, the data model is then updated to reflect the ranked order. In one embodiment, updating the data model positions the highest priority utterance as a most recent utterance in the observation history. The updated data model is then used to attempt to generate a coherent response to the query.

Abstract: A plurality of log messages may be clustered into a plurality of clusters. For each of the plurality of log messages, the log message may be partitioned into a series of substrings. At least two of the plurality of clusters may be selected. For each one of the at least two selected clusters, a parsing rule may be generated corresponding to a plurality of substrings each of which are at a given location of a respective one of the log messages of the plurality of log messages in the one of the selected cluster.

Abstract: Monitoring health of associated, but separated storage clusters can be done at both a node scope and a cluster scope. Monitoring the storage clusters at the cluster scope includes monitoring the network elements that support the storage clusters and connect the storage clusters. Initially, a fabric monitor in each cluster discovers cluster topology. This cluster topology is communicated and maintained throughout the managing storage elements of the storage clusters. After the storage cluster topologies have been discovered, the fabric monitors of each cluster can periodically determine status of network elements of the storage clusters. This allows the storage clusters to maintain awareness of interconnect status, and react to changes in status. In addition, each managing storage element monitors its own health. This information is aggregated to determine when to trigger corrective actions, alerts, and/or storage features in accordance with rules defined at the managing storage elements.

Abstract: A support engine for managing computing clusters includes a persistent storage and a processor. The persistent storage includes monitoring policies. The processor monitors a computing cluster of the computing clusters and identifies a potential component failure of the computing cluster based on the monitoring and the monitoring policies. In response to identifying the potential component failure the processor identifies an error state of the computing cluster; obtains solution level state information from the computing cluster based on the identified error state; generates a support package comprising the solution level state information; and initiates a support session by sending the generated support package to a support manager.

Abstract: A fault model representation of a computer network is generated, wherein the computer network includes a set of connected computer network elements that was at least in part configured based on a specified declarative intent in forming the computer network. A symptom representation for the computer network is determined based on telemetry data of one or more elements of the set of connected computer network elements and a behavior specification repository identifying symptoms and their associated root causes. The fault model representation and the symptom representation are provided to a root cause analysis to determine one or more root causes of one or more detected symptoms of the computer network.