Dell Products Inc.

Emc IP Holding Company LLC

Madhuri Dwarakanath

Parminder Singh Sethi

Shelesh Chopra

Bing Liu

Lakshmi Saroja Nalam

Avinash Vishwanath

Chandroma Ghose

Parmnder Singh Sethi

Manjunath Patil

Selvaraja Subburaja

Srinath Kappgal

Methods, apparatus, and processor-readable storage media for predicting component lifespan information by processing user install base data and environment-related data using machine learning techniques are provided herein. An example computer-implemented method includes obtaining install base data associated with at least one system component and environment-related data associated with usage of the at least one system component; performing feature analysis on at least a portion of the obtained data using a first set of machine learning techniques; clustering, based on the feature analysis, at least a portion of the install base data and at least a portion of the environment-related data into one or more groups using a second set of machine learning techniques; generating at least one lifespan information prediction attributed to the at least one system component based on the clustering; and performing at least one automated action based on the at least one lifespan information prediction.

Predicting component lifespan information by processing user install base data and environment-related data using machine learning techniques

Embodiments described herein relate to methods, systems, and non-transitory computer readable mediums storing instructions for creating and executing migration workflows to replicate or migrate data (collectively referred to herein as 'migration') from one device or set of devices to another device or set of devices (e.g., from one computing environment to another). The method of migration involves obtaining relationship information with regards to the applications that will be migrated from one device to another device or set of devices, and classifying the applications based on their relationships such as HAS-A and IS-A. Based on these classifications, one or more embodiments of the invention generate a relationship matrix in order to assign priority to the migration of each individual application. The applications are then migrated based on the matrix and assigned priorities.

Context-driven framework to migrate the applications and its dependencies by analyzing the relationships

Techniques for prediction of remaining life and failure of disks are disclosed. For example, a method comprises collecting operational data of a plurality of disks, and identifying at least one disk of the plurality of disks as failing based at least in part on a portion of the operational data associated with the at least one disk. Using one or more machine learning algorithms, a time period when the at least one disk will remain operational is predicted based at least in part on the portion of the operational data associated with the at least one disk. An operation to write contents of the at least one disk on at least one replacement disk is executed, wherein the operation is initiated at a time based at least in part on the predicted time period.

Disk failure prediction using machine learning

A method includes identifying relationships between containers on a first device, where each container includes at least one relationship that includes a HAS-A relationship or an IS-A relationship. The method also includes creating, on a second device, a first set of twin containers, where each container in the first set of twin containers corresponds to a container that includes only the HAS-A relationships. In addition, the method includes creating, on the second device and in response to creating the first set of twin containers, a second set of twin containers where each container in the second set of twin containers corresponds to a container that includes at least one IS-A relationship. Moreover, the method includes determining and performing a twin container start-up sequence for the first set and the second set of twin containers.

System and method for instantiating twin applications

One example method, includes checking, by an intelligent time detector service running on a computing system, a trial period duration of software on the computing system, starting, by the intelligent time detector service, a counter for the software, and the counter is operable to generate a counter value based on a clock of the computing system, storing, by the intelligent time detector service, a counter value of the counter, and decommissioning, by the intelligent time detector service, the software after the trial period has expired.

Anti-piracy protection service-based software license management system to prevent usage of unlicensed software after the trial period

An information handling system receives information from an input pointer, obtains a first coordinate from the information with respect to a first direction of a display, obtains a second coordinate from the information with respect to a second direction of a display screen, and obtains a third coordinate from a scrolling value representative of an amount of scrolling of a contiguous presentation of displayable information for display of a portion of the contiguous presentation of displayable information within the display. The system also obtains a fourth coordinate representative of a time at which the first coordinate and the second coordinate are obtained, and provides an unambiguous record of a user's navigation of the contiguous presentation of displayable information based on the first coordinate, the second coordinate, the third coordinate, and the fourth coordinate.

System and method for identifying user intent using four-dimensional coordinates of an input pointer

Aspects of the disclosure include an escalated authentication system based on user behavior patterns. A user's behavior pattern on a device is collected and/or learned. The collected or learned pattern can be compared to subsequent behavior patterns to determine whether the current user is genuine or suspicious. Users deemed suspicious are subject to increased authentication requirements, often on-the-fly.

Escalated authentication system to perform an integrity-check based on behavior patterns

Methods, apparatus, and processor-readable storage media for automated detection of unauthorized access to device screens using machine learning facial recognition techniques are provided herein. An example computer-implemented method includes automatically detecting, using one or more machine learning facial recognition techniques, at least a portion of at least one face within a given proximity of a user device; automatically performing a comparison, using one or more machine learning facial recognition techniques, of the detected portion of the at least one face with facial images attributed to a set of trusted individuals; and automatically performing security-related actions with respect to the user device upon determining, based at least in part on the comparison, that the detected portion of the at least one face exhibits at least a threshold level of distinctiveness relative to each of the facial images attributed to the set of trusted individuals.

Automated detection of unauthorized access to device screens using machine learning facial recognition techniques

An information handling system (IHS) includes spatially diverse IHS components and temperature sensors disposed with respect to the spatially diverse IHS components. A fan controller defines cooling sections of the IHS for spatially diverse fans based on topological information as to locations of the spatially diverse IHS components, and selectively controls the spatially diverse fans according to component temperatures obtained from the temperature sensors and according to the cooling sections.

Method and apparatus for selective fan control in an information handling system

A system capacitively senses a swiping motion to a touch sensitive display, determines a length associated with the swiping motion to the touch sensitive display, and displays a menu of options based on the length associated with the swiping motion. The system capacitively senses inputs to the touch sensitive display that correspond to selections from the menu, determines probabilities associated with the options, and modifies the menu based on the probabilities.

Growing community of inventors

Bengaluru, India

Madhuri Dwarakanath