International Business Machines Corporation

Oracle International Corporation

Cisco Technology, Inc.

Adobe, Inc.

Dell Products Inc.

Toshiba Tec Kabushiki Kaisha

Citrix Systems, Inc.

Emc IP Holding Company LLC

Rahul Gupta

Rhonda L Childress

Maharaj Mukherjee

David B Kumhyr

Michael Bender

Hari Haranath Madduri

Timothy James Hahn

Joanna W Ng

Lohitashwa Thyagaraj

Santosh Kumar

Yathish Gatty

Arnaud Airy Mathieu

Santosh Kumar Singh

Prithviraj Singh

Shivakumar Vaithyanathan

Eric Hsiao

Jeffrey Mark Achtermann

Sriram Raghavan

Rajasekar Krishnamurthy

Huaiyu Zhu

Sandeep Agarwal

Vishnu Murty Karrotu

Adriano Covello Santos

Krishna Prasad Chitrapura

Leucir Marin, Jr

Janis A Morariu

Devang D Patel

Kunal Mulay

Michael Reed

Vishal Sharma

Jennifer Lee Beckmann

Leucir Marin Junior

Michael P Robertson

Jeffrey J Bonasso

Kathiresan Selvaraj

Rajesh Mullangath Sakthidharan

Sara Giordano

Kathryn Marietta-Tondin

Antonella Vaccina

Deepu Syam SreedharM

Ashwin Kumar T C

Rajan Goyal

Sachindra Joshi

Parmeshwr Prasad

Raghuram Krishnapuram

Marc Dickenson

Pere Monclus

Vijay R Kalangumvathakkal

Mukesh Garg

Shyamasundar S Kaluve

Gaurav Manglik

Naveen G Balani

Vikramjeet Singh

Shamik Ganguly

Virgil Nicolae Mihailovici

Shiladitya Bose

Ahsan Habib

Kiran Prabhakar

Paul Andrew Titheridge

Dimitri Laloue

Vivek Koni Raghuveer

Venkatesh Vellingiri

Rishabh Agarwal

Dhawal Patel

Sowmya H Dayananda

Shishir Choubey

Harrison Kurtz

Bhuvan Mital

Ashwin Kumar Tc

Amy S Purdy

Vijay Kumar Sahu

Amrutha S Shenoy

Ambalika Roy

Kirtikumar L Prabhu

Christophe J Paggen

Himanshu Pandey

Pn Prathima

Rupak Das

Divya Ranjan

Amy Purdy Hirst

Mahesh Vangapalli

Aravind Vinayak

Hanumesh Thippanna Govindappa

Sourav Sikdar

Systems and methods of managing virtual application performance in a virtual computing environment are provided. A system determines an application interaction score based on corresponding application interaction factors associated with sessions. The system determines the application interaction score for each virtual application accessed during each of the sessions. The system generates an aggregated application interaction score for each of the sessions based at least on combining the application interaction score for each of the virtual applications accessed during a corresponding session. The system performs an action based at least in part on the aggregated application interaction score to improve performance of a virtual application accessed via the virtual computing environment.

Managing virtual application performance in a virtual computing environment

An instructional design tool is provided for designing learning based applications. More specifically, the instructional design tool is configured to use captured expert knowledge for translating such knowledge into an environment used for instructional purposes. The instructional design tool includes at least one component configured to visually model a gaming scenario using recorded knowledge and graphical content defined by values associated with classes of respective models and translate the defined values into a standardized XML format.

Instructional design tool

Methods and systems for analysis of a plurality of channels that provide a remote desktop session are described herein. Channel metrics for each of a plurality of communication channels may be received. Each of the plurality of communication channels may be configured to deliver, to a computing device and via a network, different aspects of a remote desktop session. A plurality of channel scores may be determined for each communication channel of the plurality of communication channels. Based on the plurality of channel scores, an aggregate score may be determined. Based on the aggregate score satisfying a threshold, a notification may be transmitted. For example, an indication of one or more executable scripts predicted to improve a performance of one or more of the plurality of communication channels may be transmitted.

User experience analysis for multi-channel remote desktop environments

A shelving assembly is provided for a container. The shelving assembly includes a first shelf movably positioned in the container and configured to support a first stock. The shelving assembly further includes a plurality of first support members configured to support the first shelf and displace the first shelf between a first position and a second position in the container based on a weight sensed by at least one first weight sensor to maintain the first stock at an opening of the container. Additionally, the shelving assembly includes a second shelf positioned adjacent within the container and configured to support a second stock. The first shelf is configured to be removed at the second position to facilitate the first stock descending onto the second stock on the second shelf. Accordingly, the shelving assembly facilitates first in first out stock rotation.

Shelving assembly of a container

An event processing system for distributing a geospatial computation, and processing events in an event stream, is disclosed. The disclosed system and methods can apply a spatial function, such as distance, within Distance, and proximity, in parallel to a stream comprising event locations. The disclosed system improves over existing geospatial computations by providing an efficient parallel implementation that can handle a large number of moving objects in real time with little latency. A computing device receives an event stream comprising locations and can geohash the locations to obtain geohashes identifying geo grid cells containing the locations. The computing device can determine respective sets of neighboring geohashes identifying neighboring cells in the geo grid. The computing device then partitions the geospatial computation by mapping, based on the respective geo hash and the respective set of neighboring geo hashes, the events to processors.

Geo-hashing for proximity computation in a stream of a distributed system

Systems, methods, and computer readable storage mediums are disclosed for the management of rejected traffic in a WCCP protocol. A request is received from a switch to redirect traffic from a client device to a cache engine. The cache engine determines that it cannot process traffic from the client device, and in response to the determination, sends a command to the switch to suspend traffic to the cache engine. The command includes instructions for one or more of removing a particular rule regarding routing of the traffic to the cache engine or modifying an access control list rule to exclude the cache engine.

Effective handling of WCCP reject traffic

Continuance in quality level of an input timing signal may be provided. Clock source reference timing information may be receive by a first node from a second node as an input. The first node may be downstream from the second node. Then the first node may receive an event message associated with a future event associated with the second node. The first node may then refrain, for a period of time in response to receiving the event message, from switching the input for clock source reference timing information to a source other than the second node.

Continuance in quality level of an input timing signal

Provided are techniques for authenticating a device. Accepted communication patterns representing accepted modes of communication between devices in an internet of things network are stored. In response to receiving a new communication from a requesting device of the devices, it is determined whether the new communication matches at least one of the accepted communication patterns. In response to determining that the new communication matches, there is a response to the new communication. In response to determining that the new communication does not match, flagging the new communication as an anomaly and determining how to process the new communication based on the flagging.

Authenticating a device based on communication patterns in a group of devices

Methods, apparatus, and processor-readable storage media for machine learning techniques for automated processing of workflow approval requests are provided herein. An example computer-implemented method includes generating a machine learning model for workflow approval requests, wherein generating the machine learning model comprises automatically learning temporal-based patterns from historical data related to previous workflow approval requests; generating, in response to an additional workflow approval request, an output value by applying the machine learning model to input data related to the additional workflow approval request; comparing the output value to at least one predefined threshold value; and automatically rejecting the additional workflow approval request responsive to a result of the comparing of the output value to the at least one predefined threshold value.

Machine learning techniques for automated processing of workflow approval requests

Provided are techniques for grouping devices as a virtual device for providing better quality of device data. A group of devices in an Internet of Things (IoT) network is identified based on one or more attributes of each of the devices. The group of devices is provided as a single virtual device by: collecting data from each of the devices in the group, transforming the data, and using the transformed data to modify a device.

Grouping devices as a virtual device for providing better quality of device data

A security apparatus and a method for detecting illegal carrying of items at a check-out are provided. The security apparatus includes a first set of sensors for measuring a number of parameters associated with a number of items purchased by a customer, and a second set of sensors to measure a number of physiological parameters of the customer. A communication unit in the security apparatus obtains information regarding a purchase of the number of items. A computing unit of the security apparatus compares reference parameters with the measured number of parameters. Based on a difference in the comparison, the computing unit receives the number of micro-expressions of the customer and determines one or more emotions of the customer. The one or more emotions and the number of parameters associated with the number of items are used to detect illegal carrying of at least one item.

Security apparatus in a shopping environment, and a method thereof

Methods and apparatus, including computer program products, implementing and using techniques for chain of custody tracking for an object. Several sets of Internet of Things (IoT) sensors are organized in a network. Each set of sensors is configured to record one or more events relating to the object. Each event includes an event time, an event location, and an entity that is a custodian for the object at the time of the event. When the object changes custodians, proper custodianship is verified based on input from at least one set of IoT sensors.

Tracking products with chain of custody using IOT devices

Methods for chain of custody tracking for an object are described. Several sets of Internet of Things (IoT) sensors are organized in a network. Each set of sensors is configured to record one or more events relating to the object. Each event includes an event time, an event location, and an entity that is a custodian for the object at the time of the event. When the object changes custodians, proper custodianship is verified based on input from at least one set of IoT sensors.

Tracking products with chain of custody using IoT devices

A method, computer program product, and system includes a processor(s) intercepting an instruction, upon receipt on the instruction, by the one or more processors in the computing device on a communications network, prior to execution of the instruction by the processor(s) in the computing device. The processor(s) determines a state of the computing device and based on the state of the computing device and a portion of the instruction, the processor(s) determines that the instruction is precluded from executing on the computing device.

Internet of things device state and instruction execution

A blockchain may include various transactions which are identified and which require processing. The order of processing such transactions may be optimized by examining content of the transactions. One example operation may include one or more of identifying blockchain transactions, designating each of the blockchain transactions as an independent transaction type or a dependent transaction type, and determining an order to process the blockchain transactions based on the independent transaction type or the dependent transaction type.

Limiting blockchain size to optimize performance

Growing community of inventors

Bengaluru, India

Rahul Gupta