International Business Machines Corporation

Other

Rohan R Arora

Seema Nagar

Amitkumar Manoharrao Paradkar

Pooja Aggarwal

Sinem Guven

Christian Eggenberger

Jens Rathgeber

Noah Zheutlin

Dipanwita Guhathakurta

Mudhakar Srivatsa

Ruchi Mahindru

John Alan Bivens

Larisa Shwartz

Harshit Kumar

Joshua M Rosenkranz

Sinem Guven Kaya

Ian Manning

Matthew Richard James Thornhill

Bing Zhou

Stephen James Hussey

Prasan Chari

Caroline Maloney

Grace Maloney

Satya Paruchuri

Connor Patterson

Samantha Steadman

Gerard Randolph Vanloo

Franco Forti

Karan Bhukar

Rahul Busayavalasa

Techniques are provided for dynamic alert suppression policy management. In one embodiment, the techniques involve receiving an event stream, wherein the event stream includes metric values comprising at least one of: log anomaly data and metric anomaly data, determining an anomalous event based on the event stream, determining a persistent region of the anomalous event, determining a quantum representation of the persistent region, determining X-Y values of the persistent region based on the quantum representation, and generating a policy based on a set of the X-Y values.

Dynamic alert suppression policy management

A computer-implemented method and a computer system for identifying persistent anomalies for failure prediction. The computer system receives a time series data stream. The computer system received a predetermined number N and a predetermined number M which is a fraction of N. The computer system segments the time series data stream into N consecutive sliding windows. The computer system performs supervised persistent anomaly detection to determine whether anomalies across the N consecutive sliding windows are persistent, by using a binary classification model. The computer system performs unsupervised persistent anomaly detection to determine whether the anomalies across the N consecutive sliding windows are persistent. The computer system combines results of the supervised persistent anomaly detection and results of the unsupervised persistent anomaly detection to determine persistent anomalies.

Identifying persistent anomalies for failure prediction

An embodiment includes detecting a set of anomalies recorded during a first predefined window of time in log entries for a computer environment. The embodiment also includes generating cluster data representative of a cluster of anomalies from among the set of anomalies, where the cluster is formed using a lattice clustering algorithm that spatially distinguishes the cluster of anomalies from other anomalies in the set of anomalies. The embodiment also includes composing an explanation using log templates generated from log entries associated with the cluster of anomalies.

Generating incident explanations using spatio-temporal log clustering

Detecting system log anomalies by receiving multivariate time-series system log data an multivariate metric data, inferring system metrics from the system log data and metric data, receiving a metric causal graph including causal relationships between system metrics, determining a univariate variation score for the system metrics, determining a causal variation score for the multivariate time series system metric data, according to the causal graph, determining an overall activity score according to the univariate variation score, and causal variation score, and altering a review window duration according to the activity score.

Dynamic window-size selection for anomaly detection

Embodiments relate to an intelligent computer platform to multi-dimensionally optimize device operation. Static hardware device data are acquired and dynamic hardware characteristic data are tracked over one or more temporal segments. A neural model (NM) is trained with corresponding device and network data. The acquired static and dynamic data are input into the NM, and locale processing patterns corresponding to the inputted data are identified. One or more data points and corresponding measurements of the tracked dynamic hardware characteristic data are temporally analyzed. A processing locale corresponding to the temporal analysis is identified and returned as output data, and one or more encoded actions in compliance with the identified processing locale are selectively implemented.

Optimization framework for real-time rendering of media using machine learning techniques

A component of an environment having available bandwidth for performing a task is located. Authorization to connect a device associated with the task to the component is granted. In response to determining that a set of one or more conditions are met, the device is connected to the component. The connection provides network connectivity to the device via the component.

Leveraging a regulated network to enable device connectivity in a restricted zone

Embodiments of the present invention provide methods for generating an augmented reality experience based on Knowledge Media. One method can include receiving one or more Knowledge Media. Transforming the one or more Knowledge Media into consumable steps. Extracting hardware information from the one or more Knowledge Media. Generating a three-dimensional point cloud model of the hardware based on the one or more Knowledge Media, and outputting an augmented reality experience based on an annotated three-dimensional point cloud model.

Dynamic content generation for augmented reality assisted technology support

A daily-use garment that is substantially normal in appearance includes a head portion corresponding to a head region of a person, and a body portion corresponding to a torso of the person. The head region is configured to cover the head region of the person with a first flexible chamber positioned in the head portion. A second flexible chamber is positioned in the body portion. A fluid supply device of the daily-use garment includes a container configured to hold a fluid under pressure, a first activation member configured to open the container, and one of a conduit and a nozzle that supplies the fluid from the container. The fluid supply device opens the container and supplies the fluid to at least one of the first flexible chamber and the second flexible chamber, and the daily-use garment is converted from a first state to a second state.

Daily-use garment that converts into a personal flotation device

Growing community of inventors

Chappaqua, NY, United States of America

Rohan R Arora