International Business Machines Corporation

Su Liu

Eric Rozner

Inseok Hwang

Cheng Xu

Chin Ngai Sze

Yu Gu

Yaoguang Wei

Debbie A Anglin

Shunguo Yan

Kai Liu

Jun Su

Boyi Tzen

Manjunath Ravi

Si Bin Fan

Fan Yang

Zhichao Li

Chungkuk Yoo

Hamid Majdabadi

Fang Wang

Yang Liang

Yin Xia

Jeffrey Alan Calcaterra

John David Wilson

Sushain Pandit

Jinho Lee

Denise Marie Genty

Peng Hui Jiang

Fang Lu

Romelia H Flores

Howard Neil Anglin

Anita Govindjee

Qin Qiong Zhang

Itzhack Goldberg

Nadiya Kochura

Janani Janakiraman

Shi Kun Li

Zachary A Silverstein

Kanak Behari Agarwal

Wei Shan Dong

Li Li

Martin Oberhofer

Neil Sondhi

George Francis Ramsay, Iii

Jeremy R Fox

Rui Li Xu

Yu Liu

Vishal Chittranjan Aslot

Jian Li

Barton Wayne Emanuel

Zhi Li Guan

Jennifer D Mulsow

Ivan Matthew Milman

Wei T Huang

Yuan Wang

Charles Daniel Wolfson

Dan Li

Xing Xing Wang

Guang Han Sui

Susan Marie Cox

Xue Yong Zhang

Logan Bailey

Robert W Thompson

Xiao Xia Mao

Rhonda L Childress

David B Kumhyr

Jun Zhou

Zhuo Li

Yu Zhu

Ting Chen

Johnny Menh-Han Shieh

Harigovind Venkatraj Ramasamy

Wen Jun Yin

Tushar Agrawal

Andrew Jason Lavery

Yan Sun

Yu Huang

Yi Liu

Shi Lei Zhang

Miao Liu

Steven Edward Atkin

Tiberiu (Jim) Suto

Chih-Wen Su

Michael Baessler

Saritha Arunkumar

Jeffrey Alan Schmidt

Ping Xiao

Meng Wan

Rui Yang

Ying Nan Li

Riaz Yousuf Hussain

He Fang Zhang

Aruna Yedavilli

Paul Llamas Virgen

Hisham Emad Elshishiny

Fei Shen

Yuan Jin

Jill S Dhillon

Yin Qian

Xi Zhang

Etai Lev Ran

A broker capability augmenting method, system, and computer program product for increasing a capability of a Message Queuing Telemetry Transfer (MQTT) broker in an Internet-of-Things (IoT) network including obtaining data from an IoT neighborhood to detect an IoT network topology over time, collecting data from IoT devices in the IoT neighborhood, defining an input parameter to a machine learning model, and training the machine learning model on the collected data and the input parameter.

Augmenting broker capabilities on massive IoT scenarios

In an approach to improve the privacy of chat groups within a virtual world, in response to identifying a private chat group has been created between two or more users, embodiments collect, by an internet of things (IoT) sensor set, a voice for each user in the private chat group. Further, embodiments analyze, by an analysis module, the collected voice, an intonation associated with the collected voice and an original pronunciation associated with the collected voice, and generate a de-content pronunciation based on the analysis of the collected voice, the intonation, and the original pronunciation. Additionally, embodiments output, by the IoT sensor set, the intonation and the original pronunciation to the two or more users in the private chat group and output, by the IoT sensor set and a client computer, the intonation and the de-content pronunciation to one or more users outside the private chat group.

Computer-based privacy protection for chat groups in a virtual environment

Techniques are described with respect to a system, method, and computer program product for representing Internet-Of-Things (IOT) devices in a virtual environment. An associated method includes detecting a plurality of IOT devices associated with a physical space; extracting a plurality of IOT capabilities associated with the plurality of IOT devices; rendering a virtual IOT device based on the plurality of IOT capabilities; and visualizing the virtual IOT device within the virtual environment associated with the physical space.

Virtualizing internet-of-things devices in virtual environments

An embodiment for detecting the danger of an object in close proximity of a subject is provided. The embodiment may include receiving real-time data from one or more IoT devices in a surrounding environment. The embodiment may also include detecting and classifying one or more subjects and one or more objects in an image from the one or more IoT devices. The embodiment may further include identifying one or more risk factors associated with each object. The embodiment may also include correlating the one or more risk factors associated with each object with the one or more subjects in the image. The embodiment may further include identifying relative positions of the one or more subjects and the one or more objects in the image. The embodiment may also include in response to determining a current position of at least one subject is dangerous, notifying a user of the danger.

Proximity danger detection based on subject and object distance analysis

A computer implemented method compiles a source code. A computer system loads the source code into a first memory. The computer system loads a rendered source code into a second memory, wherein the rendered source code is a rendered version of the source code. The computer system determines whether a difference is present between the source code in the first memory and the rendered source code in the second memory. The computer system performs a set of actions in compiling the source code in response to determining that the difference between the source code and the rendered source code is present.

Compiler suppression of invisible trojan source code

Described are techniques for handwriting authentication. The techniques include defining handwriting characteristics for a user based on a set of handwriting authentication criteria. The techniques further include receiving, from a graphical user interface (GUI) of a user device associated with the user, a handwritten phrase. The techniques further include determining that the handwritten phrase satisfies a comparison threshold to the handwriting characteristics and authenticating the user device.

Dynamic handwriting authentication

One or more processors to add identification information of a device to an initialized augmented device retrieval assistance (ADRA) data structure. Received data from ADRA clients monitoring the device within a location includes a network connection status and a time-based position of the device. The ADRA clients dynamically update the ADRA data structure with the location, a current position of the device, and a timeframe of the data from the monitoring by the ADRA clients. A request for ADR assistance is received that includes an identification of a target device, the timeframe, and a location. Location images are generated that include a location layout or floor plan. A time-spatial axis is rendered and sent to an ADRA client and includes location images and target device position within the respective images associated with a specific timeframe on the time-spatial axis.

Augmented device retrieval assistance

Aspects of the present disclosure relate to augmentation for web conference participants. An augmentation rule set defining mappings between augmentations and participant characteristics can be received, where the augmentation rule set is implemented for a web conference to determine augmentations to apply onto participant video feeds within the web conference. A plurality of participants within the web conference can be identified. The web conference can be analyzed to determine participant characteristics of each participant of the plurality within the web conference. Augmentation can be applied on respective video feeds of each participant according to the augmentation rule set based on the determined characteristics of each participant.

Augmentation for web conference participants

A computer-implemented method to send targeted messages based on a driver's intent. The method includes identifying, by a sending vehicle, one or more additional vehicles in the vicinity of the sending vehicle, including a first vehicle. Monitoring a set of data related to a current scenario for the sending vehicle and determining, based on a current scenario, an intent score for the sending vehicle. The method includes activating a horn device associated with the sending vehicle. The method further includes determining, in response to the activating, the intent score is above an intent threshold for the first vehicle. The method includes generating, in response to the intent score being above the intent threshold, a message; and sending, to a target vehicle, the message. Further aspects of the present disclosure are directed to systems and computer program products containing functionality consistent with the method described above.

Intelligent vehicle horn

A computer-implemented method, in accordance with one embodiment, includes detecting cultural context and accents of speakers portrayed in a video stream and/or an audience of the video stream. Accent tags are selected for the speakers according to the cultural context and accents of the speakers and/or the audience of the video stream. A textual representation of spoken words of the speakers is translated from a source language to a target language. The accent tags are applied to the textual representation of the spoken words in the target language according to the speakers corresponding to the textual representation of the spoken words in the target language. Speech lip movements of the speakers portrayed in the video stream are modified to match the target language and the locale accent tags. A translated video stream having the speakers appearing to speak in the target language with the modified lip movements is output.

Generation of video stream having localized lip-syncing with personalized characteristics

A method for configuring beamforming for a network device is disclosed. In one embodiment, such a method includes creating a map of an area in which a network device that supports beamforming is placed. The method shows, on an interactive display device, the network device on the map. The method shows, on the interactive display device, one or more beams emanating from the network device on the map. The method enables a user to manipulate the beams on the interactive display device to create a desired beamforming pattern that takes into account the map and receiving devices located in the area. The claimed method is advantageous in that it may enable a user to establish or modify a beamforming pattern in a more intuitive, visual way. A corresponding system and computer program product are also disclosed.

Augmented configuration interface for visualizing and optimizing beamforming

A computer-implemented method, a computer system and a computer program product control access to streaming media content. The method includes identifying the streaming media content on a content server for transmission to a user. The method also includes acquiring a biometric marker from the user using a computer vision system. The method further includes obtaining a profile for the user from a server, where the profile of the user includes a biometric signature and permissible content. In addition, the method includes determining that the biometric marker matches the biometric signature in the profile for the user. The method also includes determining that the streaming media content matches the permissible content in the profile for the user. Lastly, the method includes transmitting the streaming media content to a device, where the device is associated with the user.

Biometric authentication of streaming content

Aspects of the present disclosure relate to gaze-based active device identification and management. At a first time, at least one reference gaze image of a user while the user is gazing at a first user device of a plurality of user devices in an environment of the user can be collected. At a second time, a current gaze image of the user can be collected. The at least one reference gaze image can be compared with the current gaze image to determine that the user is gazing at the first user device of the plurality of user devices.

Gaze-based active device identification and management

Methods and systems for provisioning resources includes classifying a request for a virtual server instance (VSI) according to resources specified in the request. Dependent resources that the VSI will use are predicted based on the specified resources. A provisioning plan is generated, including timing and configuration information, based on the specified resources and the dependent resources. Resources for the VSI are provisioned according to the provisioning plan, including allocating hardware resources on a computing system.

Dynamic provisioning for virtual server instances

In an approach to improve manual and autonomous operations of a vehicle embodiments predict a moving intention of a first vehicle. Based on the predicted moving intention embodiments broadcast and share the predicted vehicle moving intention of the first with a set of key vector data through a predefined network to a second vehicle. Further, embodiments receive the broadcasting signal embedded with the set of key vector data related to vehicle moving intention nearby and map the received vehicle moving intentions to two-dimensional (2d) or three-dimensional (3D) spatial map. Additionally, embodiments render the 2D or 3D spatial map with the mapped vehicle moving intentions in a virtual display.

Computer-based vehicle control and predicted vehicle operation

Growing community of inventors

Austin, TX, United States of America

Su Liu