Hewlett-packard Development Company, L.P.

Hewlett Packard Enterprise Development LP

Entit Software LLC

Micro Focus Lcc

Craig Peter Sayers

Bernard Burg

Prakash D Reddy

Rajan Mathew Lukose

Martin B Scholz

Shyam Sundar Rajaram

Alan Hersh Karp

Ian N Robinson

Alkiviadis Simitsis

Meichun Hsu

Wei T Huang

Chetan Kumar Gupta

Gary Joseph Dispoto

William Kevin Wilkinson

Hiroshi Horii

John Ludd Recker

Ignacio Zendejas

David Alan Tamez Cantu

Ning Ge

Umeshwar Dayal

Salil Pradhan

Harumi Kuno

Alan Andrew McReynolds

Vinay K Deolalikar

Rafael A Ballagas

Mithra Vankipuram

Riddhiman Ghosh

Krishnamurthy Viswanathan

Georgia Koutrika

Shyamsundar Rajaram

Alexander Thayer

Wei Huang

Jordi Morillo Peres

Terrance J O'Shea

Martin L Griss

Tyler Close

Mathieu Thouvenin

Shama Pagarkar

Prabodh Tiwari

Salll Pradhan

David I Bell

Patrick Daney De Marcillac

Junrui Yang

Alejandro Guerrero Gonzalez

Ralph A Morales, Iii

Thomas E Pearson

Jayakumar Suthira

In an example, a method includes operating, by a processor, on object model data and operating, on a processor, on pattern data. The object model data describes at least part of an object to be generated in additive manufacturing and the pattern data describes an object pattern intended to be formed on at least a portion of the part of the object to be generated in additive manufacturing. The method includes determining, by a processor, control data to control a print agent applicator to apply a pattern of fusing agent onto a part of a layer of build material. The pattern of fusing agent comprises a fusing agent area and a gap area that lacks fusing agent. The gap area corresponds to the object pattern such that no fusing agent is applied to a part of the layer of build material that corresponds to the object pattern.

Patterns on objects in additive manufacturing

In example implementations, a method is provided. The method includes printing a three-dimensional (3D) object that includes a secondary structure. The secondary structure is removed. A representation of a surface of the 3D object where the secondary structure was removed is captured. The 3D object is authenticated based on the representation of the surface.

Identification of 3D printed objects

A system for providing input to a computer, the system including: a stylus with a first end, the first end to provide position information to the computer; and a plurality of divots, wherein when the first end of the stylus is in a divot, the system detects an orientation of the stylus.

Divots for enhanced interaction with styluses

In an example method, a target object is detected via a camera in a mobile device based on an embedded identifier on the target object. Sensor data of the mobile device is tracked to estimate a relative location or a relative orientation of the mobile device in relation to the target object. A relative gesture is detected via the mobile device based on the relative location or the relative orientation of the mobile device. One or more actions are performed in response to detecting the relative gesture.

Relative gestures

An enhanced reality system, in an example, includes an input device, the input device including a first arm and a second arm configured to be held together by a user; a sensor to sense, at least, a relative position of at least a portion of the first and second arms; wherein sensing, at least, the relative position of the first and second arms comprises a haptic retargeting process that simulates a touching of ends of the first and second arms to the outer surface of a virtual object presented in the enhanced reality environment.

Enhanced reality system with haptic retargeting

Examples disclosed herein relate to determining 3D print part placement. In one implementation, a processor generates a user interface to receive user input related to multiple divisions of 3D print parts and a relative ordering between the divisions. The processor may determine part placement information for the parts in the divisions in a 3D print build area based on user input to the user interface. The processor may translate the determined part placement information into 3D printer instructions.

3D print part placement

An input device includes a sensor and a housing. The sensor is adapted to provide cursor control on a display based on relative movement between the sensor and a reference surface. The housing at least partially contains the sensor and is adapted to be selectively manipulable relative to the reference surface into a first position to cause operation of the sensor at a first precision level and into a second position to cause operation of the sensor at a second precision level different from the first precision level.

Input device with precision control

A timepiece includes at least one time-of-day hand rotatable relative to a first dial and a first pair of temporal calendar mechanical elements independently rotatable relative to each other, and relative to the at least one time-of-day hand. Controlled rotation of the respective temporal calendar mechanical elements is synchronizable relative to temporal calendar information on an external device.

Temporal calendar timepiece

In one example, an executable program on a computer-readable storage medium that instructs a processor to predict a characteristic of at least some parts in plural orders from a corresponding computer model of the part. The program also instructs the processor to assign, based on the predicted characteristics, models of at least some similar parts from different orders to different build trays usable to fabricate the parts. The program further instructs the processor to, for each build tray, sort the fabricated parts into the plural orders by matching a measured characteristic of a part to a predicted characteristic of unsorted parts from the build tray.

Build tray model assignment and fabricated part sorting

In one example implementation, a system for ranking target dimensions includes a model engine to generate a three-dimensional (3D) model of an object from a scan of the object, an analysis engine to analyze the 3D model of the object and determine target dimensions of the object, a ranking engine to rank the target dimensions based on target dimension characteristics, historical scan information related to the target dimension characteristics, or a combination thereof, and a display engine to display information relating to the ranked target dimensions of the object.

Ranking target dimensions

Described herein are techniques for generating a visualization relating to execution of a workload. Multiple measurements of a plurality of metrics relating to execution of the workload may be aggregated at multiple levels of execution. A visualization may be generated that comprises a representation of the measurements of a metric at one of the levels of execution.

Generating a visualization of a metric at one or multiple levels of execution of a database workload

In a method for managing a plurality of data entities, data pertaining to transactions by a plurality of users with respect to the data entities is collected and a collaborative filtering operation is applied on the data entities to determine similarity levels of the data entities with respect to each other. In addition, for at least one of the data entities, remaining ones of the data entities are ranked according to the determined similarities while discounting for popularities of the data entities. Moreover, identifications of at least another one of the data entities having the highest rankings to the at least one of the data entities are presented to a first user to recommend the at least another one of the data entities for use by the first user.

Managing data entities using collaborative filtering

The disclosure relates to methods and systems for generating application retention metrics. In one aspect, a method for generating coupled application retention metrics is disclosed. First and second reference application identifiers are selected (), and a coupled application retention metric between the first and second reference application identifiers is generated (). The coupled retention metric is generated by querying () an application database including a plurality of application records, where each record includes an application identifier, a user identifier, and retention information. Retention metrics in the application database are compared for application identifiers corresponding to the first or second reference application identifier and having a common user identifier. An application of interest is selected by and its identifier is received () from a user of a remote application, where the selected application corresponds to the first reference application identifier. The coupled application retention metric is transmitted () to the user.

Application retention metrics

A method for event correlation includes capturing events and arranging the events sequentially in at least one dimension. An event correlator implemented by a computational device convolves a kernel density function with each of the events to produce a convolved function for each event. Co-occurrences between events are found by calculating overlap between convolved functions.

Event correlation

Growing community of inventors

Menlo Park, CA, United States of America

Craig Peter Sayers