Abstract: Methods, systems, and computer readable medium for improving opt-out compliance are disclosed. A method includes identifying an opportunity to transmit a digital component to a client device that is identified by a given unique identifier, accessing a database, identifying, within the database and based on the accessing, an opt-out timestamp specifying when a given user corresponding to the given unique identifier was presented the opt-out opportunity, determining, whether the timestamp indicates that the user was presented with the opportunity within a specified amount of time, and processing the opportunity by submitting the opportunity to transmit the digital component to third party digital component sources in response to determining that the given user was presented with the opportunity within the specified amount of time, or refraining from submitting the opportunity in response to determining that the given user was not presented with the opportunity within the specified amount of time.

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: In some examples, incident prediction and prevention may include ascertaining a plurality of past incidents, clustering the plurality of past incidents to generate a plurality of incidents clusters, and identifying, for each past incident of the plurality of past incidents that is in a respective incidents cluster of the plurality of incidents clusters, a time of occurrence. Incident prediction and prevention may include ascertaining a new incident, assigning the new incident to an incidents cluster of the plurality of incidents clusters, and determining, for the assigned incidents cluster, at least one further predicted incident associated with at least one further corresponding incidents cluster. Further, incident prediction and prevention may include determining a resolution to the at least one further predicted incident, and preventing occurrence of the at least one further predicted incident by executing the determined resolution to the at least one further predicted incident.

Abstract: Monitoring method and a monitoring device of a deep learning processor, which can effectively monitor running of the deep learning processor, capture an abnormal status in an arbitrary working state, and make the deep learning processor return to a normal state in time is presented. The monitoring method comprises: initializing standard data and storing a standard calculation result corresponding to the standard data, sending the standard data to the deep learning processor, receiving a calculation result returned by the deep learning processor, comparing the received calculation result with the stored standard calculation result, and judging the state of the deep learning processor in accordance with the result of the comparison, judging that the state of the deep learning processor is normal when the compared results are consistent, and judging that the deep learning processor is abnormal when the compared results are inconsistent.

Abstract: A computer-implemented method for detecting faults and events related to a system includes receiving sensor data from a plurality of sensors associated with the system. A hierarchical failure model of the system is constructed using (i) the sensor data, (ii) fault detector data, (iii) prior knowledge about system variables and states, and (iii) one or more statistical descriptions of the system. The failure model comprises a plurality of diagnostic variables related to the system and their relationships. Probabilistic reasoning is performed for diagnostic or prognostic purposes on the system using the failure model to derive knowledge related to potential or actual system failures.

Abstract: The application relates to a multi-operating system (multi-OS) device and a notification device. The multi-OS device comprises a processor, a transceiver, and an output device. The processor is configured to host a first operating system (OS1) in a foreground and a second operating system (OS2) in a background, or vice versa. The output device is configured to be controlled by an operating system hosted in the foreground. The transceiver is configured to receive a first signal (S1) from a notification device over a communication system, where the S1 indicates a notification associated to the OS2. The output device is further configured to output the notification associated to the OS2 when the OS1 is hosted in the foreground.

Abstract: In response to a posting of a negative review of an information technology item, external environmental context data is collected that comprehends processing environment attributes of an external process that interacts with the item in a reviewed performance of the item. An attribute of the item criticized in the review is correlated with an attribute of the external environmental context data as a function of contemporaneous time of occurrence. Degrees of likelihood as the principal cause of the negative review are determined for the attributes of the information technology item and for the correlated external environmental context data attribute. The negative review is determined to be a false negative review if the degree of likelihood that the correlated attribute of the external environmental context data is the principal cause is higher than the degree of likelihood that the criticized attribute of the information technology item is the principal cause.

Abstract: An apparatus operates to provide default services or functionality. The apparatus authenticates replaceable resources by determining whether the replaceable resources originate from a desired source. The apparatus provides an auxiliary service or functionality in addition to the default services or functionality when each of the replaceable resources originates from the desired source, and precludes the auxiliary service or functionality when any of the replaceable resources do not originate from the desired source.

Abstract: A method or apparatus for monitoring a system by detecting misbehaving components in the system is presented. A computing device receives historical data points based on a set of monitored signals of a system. The system has components that are monitored through the set of monitored signals. For each monitored component, the computing device performs unsupervised machine learning based on the historical data points to identify expected states and state transitions for the component. The computing device identifies one or more steady components based on the identified states of the monitored components. The computing device also receives real-time data points based on monitoring the set of signals from the system. For each identified steady component, the computing device examines the received real-time data points for deviation from the expected state and state transitions of the steady component. The computing device reports anomaly in the system based on the detected deviations.

Abstract: A automative management server for receiving information technology system events and wind turbine events; correlating the information technology system event with the wind turbine event to determine a cause of an event; and generating an alert reporting the cause of the event or taking action to resolve the root cause of the event.

Abstract: A log message grouping apparatus calculates a coincidence degree evaluation value E1 representing the degree of coincidence between minority words, which are relatively low occurrence frequency words, out of the words that form a log message and minority words in another log message. The log message grouping apparatus further calculates an occurrence degree evaluation value E2 representing the degree of occurrence of the combination of a classification value of a log message and the classification value of a past log message on the basis of the occurrence frequency of the combination of the classification values and calculates an association degree evaluation value E3 representing the degree of association between the log message and the past log message on the basis of the coincidence degree evaluation value E1 and the occurrence degree evaluation value E2.

Abstract: A system is provided for clustering events. A first engine is configured to receive message data from managed infrastructure that includes managed infrastructure physical hardware that supports the flow and processing of information. A second engine determines common characteristics of events and produces clusters of events relating to a failure of errors in the managed infrastructure. Membership in a cluster indicates a common factor of the events that is a failure or an actionable problem in the physical hardware managed infrastructure directed to supporting the flow and processing of information. One or more situations are created that is a collection of one or more events or alerts representative of the actionable problem in the managed infrastructure. In response to the production of the clusters one or more physical changes in the managed infrastructure hardware.

Abstract: A user interface system includes a first engine configured to receive message data from managed infrastructure that includes managed infrastructure physical hardware that supports the flow and processing of information. A second engine determines common characteristics of events and produces clusters of events relating to the failure of errors in the managed infrastructure, where membership in a cluster indicates a common factor of the events that is a failure or an actionable problem in the physical hardware managed infrastructure directed to supporting the flow and processing of information. One or more situations is created that is a collection of one or more events or alerts representative of the actionable problem in the managed infrastructure. A situation room includes a user interface (UI) for decomposing events from managed infrastructures.

Abstract: A computer-based method for generating a component fault tree for a technical system is provided, including loading a data model of a failure mode and effect analysis for the technical system, generating for each component of the technical system a component element for the component fault tree, wherein component output ports of the component elements are connected to input ports of the component elements, generating for each component of the data model a component fault tree element for the respective component element, wherein each component fault tree element is associated with the respective component element, generating for each failure effect of a failure mode of a component of the data model an output failure mode for the respective component fault tree elements, and generating for each failure mode of the component of the data model a basic event for the respective component fault tree elements.

Abstract: Embodiments of the present disclosure provide a method, system, and computer program product for certifying resiliency and recoverability level of services. The method, system and computer program product include receiving a level of testing for a target service used by an application in an ordinary course of operation. The monitoring system disrupts expected behavior of the application by adjusting one or more parameters of the application. The monitoring system determines whether the service is able to recover based on the application behavior. Upon determining that the service is able to recover based on the application behavior, reporting the level of testing as the level of testing received.

Abstract: Among other things, embodiments of the present disclosure can help improve the functionality of failure prediction systems by identifying potential future failure events in a hardware or software component based on an analysis of current and historical information for the system. Embodiments of the present disclosure may use historical data associated with past technology failures to identify causal factors identified in current event data to help predict future outages and disruptions.

Abstract: A collaborative diagnostic system monitors events in a system and identifies a causality chain from a detected performance issue to the root cause of that performance issue. The collaborative diagnostic system includes multiple issue detectors, multiple analysis core modules, and multiple scenario modules that work together to identify the causality chain and root cause. Each issue detector is a module or component that includes logic to detect known behaviors in the system, such as performance issues in the system. Each analysis core module includes logic to analyze and correlate low level system behavior within a conceptual area. Within each analysis core module are one or more diagnostic modules that are specific to that analysis core module to help determine what is happening in the system. Each scenario module includes logic to take an appropriate responsive action in response to the root cause of a performance issue being determined.

Abstract: A new and/or improved method, apparatus and/or system is disclosed which aids in extending correct behavioral models to include fault modes and in fault mode analysis of components and/or systems in simulated model environments, including, e.g., FMEA and FMECA and diagnostic fault tree generation.

Abstract: A system management apparatus includes a storing unit that stores structured identification information indicating physical and logical inclusion relations of configuration elements which configure a system by a tree structure, and correlation information indicating information on a correlation between the configuration elements, and a control unit that manages a range relating to a failure which is generated in the system, based on the structured identification information and the correlation information, in which the control unit designates a subset of the structured identification information as a predetermined management range in the structured identification information, and transmits failure information which is generated in the system to a terminal that displays the management range, in a case where the structured identification information indicating the failure information which is generated in the system corresponds to the subset of the structured identification information which is designated as a

Abstract: Described herein is a technology that facilitates the production of and the use of automated datagens for event-based systems. A datagen (i.e., data-generator or data generation system) is a component, module, or subsystem of computer systems that searches, monitors, and analyzes machine data. Existing datagens are not capable of detecting an anomaly in machine data. An anomaly is a variance in the input data stream that exceeds some acceptable amount of deviation from the norm (i.e., standard, expectation, etc.). An embodiment of datagen, in accordance with the technology described herein, detects anomalies in the input machine data.

Abstract: The present disclosure discloses a fault scenario information collecting method and system for an information system, which regularly acquire information of each parameter of a first preset parameter set in the information system at a preset time interval, monitor operating states of the information system to judge whether a fault occurs in the operating states of the information system, and acquire information of each parameter of a second preset parameter set in the information system when the fault occurs in the operating states of the information system.

Abstract: Various embodiments are provided that enable a controller of a storage device having storage media to perform one or more error recovery operations on the storage media, and to convey, while performing the one or more error recovery operations, a message indicating a status of the one or more error recovery operations to a host processor in communication with the storage device. Storage devices implementing embodiments of the present invention include hard disk drives and solid state disk drives comprising a disk head having a magnetoresistive (MR) element configured to read and write data to and from the storage media, and coupled to an analog/digital (A/D) converter, and the error recovery operations are selected from a list of changing an automatic gain control of the A/D converter, positioning the disk head off-track in order to read the data, and adjusting a bias value of the MR element.

Abstract: Method and system are provided for event relationship analysis in fault management. The method includes: providing a history of a plurality of event instances relating to multiple events identified by event identifiers, where an event instance has one or more event occurrences referencing an event identifier, the history including the event occurrences and resolution event information; analyzing the event occurrences relating to each event identifier to identify a first occurrence(s) of an event instance; analyzing the resolution event information relating to each event identifier to identify any event resolution time for an event instance; comparing two event identifiers to obtain a relationship score between the two event identifiers, wherein the comparing is based on a combination of first occurrences of event instances relating to the two event identifiers and resolution times of the event instances; and creating a group of events that are related based on the relationship scores.

Abstract: A system is provided for integrating failure data for different failure analysis layouts. The system includes a data validator and layout engine. The data validator is configured to validate failure analysis data for a complex system including a plurality of systems. The failure analysis data includes failure data identifying failed systems, and design data describing the complex system and possible failures of at least some of its systems. In this regard, the data validator is configured to perform one or more consistency checks between the failure data and design data to thereby integrate the failure data for a plurality of different failure analysis layouts. The layout engine is in turn configured to selectively generate and communicate any one or more of the plurality of different layouts of the failure analysis data, with at least some of the failure analysis data being shared between at least some of the different layouts.

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 computer-implemented method generates a trigger registration for a selected triggering type. The generated trigger registration is stored in a triggering persistency. A received event from an event persistency is analyzed and data associated with the analyzed event is compared with the triggering persistency. Based on the comparison and using a pattern execution framework, an enterprise threat detection (ETD) pattern is processed to perform actions responsive to the received event.

Abstract: A method for execution by an integrity processing unit includes detecting a storage error associated with storage of at least one encoded data slice in at least one memory of an associated storage unit of a set of storage units. Error parameters associated with the storage error are determined and a plurality of recovery alternatives to abate the storage error are identified based on the error parameters. A plurality of cost-benefit factors that correspond the plurality of recovery alternatives are determined. One of the plurality of recovery alternatives is selected based on the plurality of cost-benefit factors, and execution of the one of the plurality of recovery alternatives is facilitated to abate the storage error.

Abstract: In some examples, continuous integration and continuous deployment (CI/CD) system failure analysis and resolution may include analyzing data for a CI/CD system to identify anomalous tests related to the CI/CD system. A plurality of hypotheses on a cause of failure associated with the CI/CD system may be determined based on a further analysis of the analyzed data. The determined hypotheses may be prioritized based on a confidence level analysis. Failure resolution to prevent failure associated with the CI/CD system may be determine based on a response to one of the prioritized hypotheses. Further, the determined failure resolution may be implemented.

Abstract: A flaw classifier model classifies a computing system as one which contains or does not contain one or more flaws that affect a performance of the computing system. Inputs to the flaw classifier model may include an actual utilization of a resource of the computing system and an expected utilization of the resource of the computing system. The expected utilization of the resource may be determined by an expected resource utilization model. Inputs to the expected resource utilization model may include workload description parameter values and hardware description parameter values.

Abstract: Disclosed is a system and method for the analysis of event data that enables analysts to create user specified datasets in a dynamic fashion. Performance, equipment and system safety, reliability, and significant event analysis utilizes failure or performance data that are composed in part of time-based records. These data identify the temporal occurrence of performance changes that may necessitate scheduled or unscheduled intervention like maintenance events, trades, purchases, or other actions to take advantage of mitigate or compensate for the observed changes. The criteria used to prompt a failure or performance record can range from complete loss of function to subtle changes in performance parameters that are known to be precursors of more severe events. These specific criteria applied to any explicit specific application and this invention is relevant to this type of data taxonomy and can be applied across all areas in which event data may be collected.

Abstract: The present application discloses a method and a system for detecting malicious code. The method comprises receiving a testing sample; testing the sample with a plurality of malicious code detectors to obtain a plurality of testing results; determining a credibility scale and a reputation value of each of the testing results, wherein the credibility scale indicates whether the testing result is malicious or safe, and the reputation value indicates a quantified trust level corresponding to the credibility scale; and determining a final detection result of the testing sample based on the determined credibility scales and the reputation values of the testing results. According to the technical solution of the present application, the testing results obtained from various malicious code detectors are rationally utilized to improve the testing accuracy for the malicious code.

Abstract: Systems and methods for monitoring a local environment for abnormal conditions (e.g., burglary, intrusion, fire, or flooding) are disclosed. Sensors of a smartphone, tablet computer, or other computing device may be used to obtain sensor data regarding the environment. Such sensor data may relate to sounds, temperatures, lighting, or other conditions within the environment. The observed environmental conditions may be compared against reference levels or patterns to determine abnormal conditions. When abnormal conditions are identified, a response may be determined and implemented, such as alerting a user or contacting an emergency service (e.g., police or fire services). In some circumstances, a training period may be used to determine baseline or threshold levels of normal environmental conditions. Different modes or profiles may be used, which may be associated with different environments (e.g., home, hotel, etc.).

Abstract: Devices and methods are provided for providing software developer-driven analysis for the expected impact that a proposed software modification may have on software programs and devices. A device may receive files including a first file including indications of: (i) a feature modified by one or more software modifications, (ii) a sub-feature associated with the feature and modified by the one or more software modifications, and (iii) first information associated with the feature, and a second file including indications of: (i) the feature, (ii) the sub-feature, and (iii) second information associated with the feature. The device may determine a record including indications of: (i) the feature, (ii) the sub-feature, (iii) the first information, and (iv) the second information. The device may determine a test plan including one or more tests performed based on the record. The device may execute at least a portion of the test plan.

Abstract: A method and system for user experience event processing and analysis are provided. In one embodiment, a computing device correlates detected pre-defined user experience events with data indicating activity of a storage device over a time period and generates an analysis of the correlation. In another embodiment, a computing device compares first and second recorded videos to identify differences, wherein the first and second recorded videos are synchronized based on content rather than time, correlates the differences with the data indicating activity of a storage device of a host device, and generates an analysis of the correlation. Other embodiments are possible, and each of the embodiments can be used alone or together in combination.

Abstract: A system, method, and computer program product are provided for utilizing radio access network (RAN) information and mobile backhaul (MBH) network information to assess network site performance. In operation, a system receives information associated with a radio access network. Additionally, the system receives information associated with a mobile backhaul network corresponding to the radio access network. The system correlates the information associated with the radio access network with the information associated with the mobile backhaul network to create correlated information. Further, the system calculates scores for the correlated information. Moreover, the system calculates a score for a site associated with the mobile backhaul network utilizing the scores for the correlated information.

Abstract: A method and apparatus for generating a fault tree for a failure mode of a multi-mode system which includes a plurality of system components, the method includes the steps of providing component fault tree elements of the system components, wherein each component fault tree element includes at least one component fault tree mode element, representing a failure-relevant operation mode of the respective system component; selecting at least one component fault tree mode element representing a system state of the system; and generating the fault tree by incorporating the selected component fault tree mode elements the generated fault tree representing a failure behaviour of a system state of the system.

Abstract: A failure determination apparatus includes an electricity storage, a state sensor, a data accumulator, and a controller. The state sensor is to detect a state of the electricity storage as data. The data accumulator is to accumulate the data acquired by the state sensor as accumulated data. The controller is to determine, based on the accumulated data, whether a failure occurs in at least one of the electricity storage and the state sensor.

Abstract: Disclosed is a computer program stored in a computer readable storage medium including encoded commands. When the computer program is executed by one or more processors of a computer system, the computer program enables the one or more processors to perform operations for parsing, and the operations include: receiving, by a dispatcher thread, an event; matching, by the dispatcher thread, information on a parsing rule corresponding to the event with the event, and storing the event and the matched information on the parsing rule in an event queue; fetching, by a parser thread, the event and the information on the parsing rule from the event queue; and processing, by the parser thread, the event according to the parsing rule corresponding to the event based on the information on the parsing rule.

Abstract: A method for continuous data anomaly detection includes identifying a period of time covered by metrics data stored in a repository. The stored metrics data is categorized into a plurality of non-overlapping time segments. Statistical analysis of the stored metrics data is performed based on the identified period of time. A range of acceptable metric values is dynamically generated based on the performed statistical analysis.

Abstract: Method and system for event relationship analysis in fault management. The method includes identifying a group of related events based on a history of a plurality of event instances relating to multiple events. For each event occurrence of each event of the group of related events, there is identified: an event type; and one or more resources associated with the event occurrence. The method also comprises: identifying a set of event occurrences of the same type; and identifying event occurrences associated with the same resource.

Abstract: A device for monitoring a critical path of an integrated circuit includes a replica of the critical path formed by sequential elements mutually separated by delay circuits that are programmable though a corresponding main multiplexer. A control circuit controls delay selections made by each main multiplexer. A sequencing module operates to sequence each sequential element using a main clock signal by delivering, in response to a main clock signal, respectively to the sequential elements, secondary clock signals that are mutually time shifted in such a manner as to take into account the propagation time inherent to the main multiplexer.

Abstract: The present arrangements relate to analyzing a software error. At least one dump file created in response to a crash of software executing on a processing system can be accessed. Based on the dump file, a base version of at least one software module that was loaded when the crash occurred can be identified. Based on the dump file, maintenance that has been applied to the at least one software module also can be identified. A report recommending new corrective maintenance to be applied to the at least one software module can be generated.

Abstract: Computer-implemented systems, methods, and computer-readable media are provided for causing an action to be performed in response to a network communication, such as a malicious network communication. In accordance with some embodiments, a first network communication sent from a client device is received, and a protocol used in the first network communication is determined. Once the protocol is determined, the protocol may be implemented to enable a second network communication with the client device. An action to be performed based at least in part on the protocol may be identified, and an instruction may be sent to the client device in the second network communication.

Abstract: A memory system includes multiple storage devices that each include a nonvolatile memory device. A client device is configured to collect deterioration information of the nonvolatile memory devices provided from the storage devices. A server device is configured to receive the collected deterioration information and to predict a degree of deterioration of the nonvolatile memory devices in real time by performing machine learning based on the collected deterioration information and initial deterioration information. The client device determines a read level of the nonvolatile memory device based on the degree of deterioration of the nonvolatile memory devices from the server device. The storage device sets the nonvolatile memory device to operate based on the read level determined in the client device.

Abstract: A system for detecting a faulty behavior of a User Equipment (UE) in a telecommunication network is provided. A trouble report information associated with a first UE is received. The trouble report includes information uniquely identifying the first UE and information indicative of trouble affecting the first UE. One or more geographic locations for each communication session associated with the first UE for a predetermined period of time are established. Performance metrics associated with the first UE are compared with performance metrics associated with a plurality of UEs. The plurality of UEs includes UEs that handled communication sessions at similar times and locations. The first UE is characterized based on the comparison.

Abstract: A method may include receiving, by a device, an input sample of textual content. The method may include identifying, by the device, a comparison sample that is semantically similar to the input sample. The comparison sample may be identified based on a similarity score, of the comparison sample and the input sample, satisfying a semantic similarity threshold. The method may include identifying, by the device, a plurality of output samples of textual content based on acceptance information corresponding to the plurality of output samples and the comparison sample. The acceptance information may be determined based on a user input regarding similarity or relevance of the plurality of output samples and the comparison sample, and the user input may be received before the input sample is received.

Abstract: A method, a computer system, and a computer program product for clustering operational parameter values in a micro-service architecture used in a computing infrastructure. The computer system measures a plurality of operational parameter values of elements of the computing infrastructure and logs identifiers for elements having caused a problem situation and related problem resolution times. The computer system clusters the operational parameter values of the elements having caused the problem situation, according to a correlation function. The computer system orders the operational parameter values within a cluster and the elements having caused the problem situation. The computer system periodically performs the clustering and the ordering such that a sequence of the operational parameter values and the elements having caused the problem situation is indicative of a resolution time required for a new problem situation.

Abstract: Example implementations relate to escalated remediation. In an example implementation, a recovery script for addressing a security threat to the computing system may be received by a recovery service from a triggering entity. The recovery script may be processed by the recovery service to determine a security-related recovery action and a target component of the recovery action. The recovery action may be forwarded by the recovery service to a recovery agent at an abstraction layer immediately above the target component. The recovery agent may execute the recovery action on the target component. In response to a determination by the triggering entity that the recovery action did not address the security threat, the recovery service may receive a next recovery script that is more aggressive.

Abstract: An online system identifies an assignment for a computer program error indicated in an error message by applying an assignment model to token sequences identified in the error message. The error message includes a sequence of execution paths of the computer program. Each execution path indicates a function call active in computer memory when the error was generated. In other words, the error message allows tracking of the sequence of nested paths up to the point where the error was generated. In one example, the error message is a stack trace message that reports active stack frames in computer memory during the execution of the program.

Abstract: A data inconsistency is detected in a file system data block of a file system. The file system includes a set of files, each file includes a set of file system data blocks. Information regarding a file including the data inconsistency is provided to a client of the file system. Based on the information, the client is enabled to determine an action for recovering from the data inconsistency.