AT&T Intellectual Property I, LP

Michigan State University

University of California

At+t Corp.

The University of Texas System

Wisconsin Alumni Research Foundation

University of Michigan

At&t Mobility II LLC

Purdue Research Foundation

Medical University of South Carolina

Jia Wang

Lusheng Ji

Zihui Ge

Ajay Mahimkar

Jennifer Yates

Dan Pei

Yin Sheng Zhang

Aman M Shaikh

Robert Raymond Miller, Ii

Balachander Krishnamurthy

Muhammad Zubair Shafiq

Jun Xu

Joanne Emmons

Tongqing Qiu

Oliver Spatscheck

Nemmara K Shankaranarayanan

Alexandre Gerber

Albert Gordon Greenberg

Zhuoqing Morley Mao

Jeffrey Pang

Adam Louis Buchsbaum

Glenn Stephen Fowler

Matthew Osinski

Xiang-Yang Alexander Liu

Ashwin Lall

Amit Kumar Sheoran

Xing Xu

Qi Zhao

Sarat Puthenpura

Seungjoon Lee

He Yan

Leonid Razoumov

Ioannis Broustis

R Michael Van Dam

Ying Zhang

Shobha Venkataraman

Xiang-Yang Alex Liu

Xiaofeng Shi

Chen Qian

Hai Paul Liu

Hao Wang

Y Richard Yang

Andrea Basso

Hisao M Chang

Jeffrey Erman

Lili Qiu

Shuai Hao

Suman Banerjee

Michael J Merritt

Kiem-Phong Vo

Feng Chi Wang

David Lee Applegate

Cheng Ee

Howard Karloff

Hongbo Jiang

Hendrik Hofman

Ramesh Govindan

Han Hee Song

Chia-Wei Chang

Min-Hsuan Chen

Anthony Caracciolo

Qunfeng Dong

David Johnson

Sonia Fahmy

Bill Lin

Subrata Acharya

Gruia Calinescu

Katrina Ligett

Lixin Gao

Benjamin Grizzle

Mitsunori Ogihara

Haiquan Zhao

Eric Bonitz

Alejandra Rios

Tongquing Qiu

Chunyi Peng

Bruno Ribeiro

Tonqing Qiu

Chandra Thompson

Shudong Jin

Andrew W Moore

Aspects of the subject disclosure may include, for example, receiving, from a machine learning model, information about an event causing a service degradation in a cellular network, wherein the event is external to the cellular network, determining one or more event categories associated with the event causing the service degradation, determining, based on the one or more event categories, likely affected customers, the likely affected customers being likely to experience the service degradation, determining, by the machine learning model, proper resources for resolution of the service degradation, wherein the determining proper resources is based on the one or more event categories, and dispatching the proper resources for resolution of the service degradation. Other embodiments are disclosed.

Automated AI/ML event management system

Aspects of the subject disclosure may include, for example, training a cell-level machine learning model to predict a likelihood of a cell site in a cellular network having service issues that impact customers of the cellular network, training a user equipment (UE) level machine learning model using output information from the cell-level machine learning model and historical information about UE-level performance metrics, receiving, from a customer associated with a UE device operating on the cellular network, information about a service degradation experienced by the customer on the UE device, providing the information about the service degradation to the UE-level machine learning model; and receiving, from the UE-level machine learning model, information identifying a source of the service degradation. Other embodiments are disclosed.

Automatic troubleshooting system for user-level performance degradation in cellular services

A method of performing high-throughput radio thin layer chromatography (radio-TLC) includes spotting a plurality of locations on one or more TLC plates with samples containing a radiochemical or a radiopharmaceutical, each location defining an individual lane on the one or more TLC plates for the respective samples. The one or more TLC plates are developed with a developing solution and dried. The TLC plates are imaged with an imaging device comprising a camera, wherein the image obtained from the camera comprises a field of view that contains regions of interest (ROIs) from the plurality of lanes. The ROIs in the images obtained from the camera may then be analyzed by the user. The ROIs may be used, for example, reaction optimization or for quality control check of the production of radiotracers.

System and method for high-throughput radio thin layer chromatography analysis

Aspects of the subject disclosure may include, for example, automatically detecting a service issue of a telecommunication system that may impact a customer of a telecommunication service provider of the telecommunication system, predicting, by the processing system, a future customer care interaction by the customer as a result of the service issue, initiating a resolution action of the telecommunication system for the service issue before the customer contacts a customer care agent of the telecommunication service provider, wherein the initiating is responsive to the predicting the future customer care interaction and modifying a component of the telecommunication system to improve efficiency of operation of the telecommunication system by reducing a number of customer care contacts by customers of the telecommunication service provider. Other embodiments are disclosed.

Proactive customer care in a communication system

A microfluidic synthesis platform includes a microfluidic chip holder that has a computer controlled heating element and cooling element therein. A microfluidic chip is mountable in the microfluidic chip holder. The microfluidic chip is formed by a hydrophobic substrate having patterned thereon a hydrophilic reaction site and a plurality of hydrophilic channels or pathways extending outward from the hydrophilic reaction site and terminating at respective loading sites on the substrate, wherein the hydrophilic channels or pathways are tapered with an increasing width in an inward direction toward the hydrophilic reaction site. A fixture is provided for holding a plurality of non-contact reagent dispensing devices above the microfluidic chip at locations corresponding to the loading sites of the plurality of hydrophilic channels or pathways, the fixture further holding a moveable collection tube disposed above the hydrophilic reaction site of the microfluidic chip for removing droplets containing reaction products.

Device and method for microscale chemical reactions

Aspects of the subject disclosure may include, for example, a method in which a processing system installs on a controlling device user interface automation software provided by a customer care server separated from the controlling device; the controlling device communicates with the customer care server over a communication network. The system receives information from equipment of a customer care agent regarding a customer care issue associated with a communication device coupled to the controlling device by a communication link separate from the communication network. The method includes effecting, responsive to the information and without action by a user of the communication device, an input to the user interface via the communication link to initiate a resolution procedure for the customer care issue; the resolution procedure can include resetting network settings, enabling a network service, collecting information regarding the network settings, and/or providing new network settings. Other embodiments are disclosed.

Method and system to automate troubleshooting and resolution of customer device issues

Aspects of the subject disclosure may include, for example, allocating, by a processing system including a processor, a first subset of resources to a first plurality of applications and a second subset of the resources to a second plurality of applications, wherein the allocating is based on respective statuses associated with the first plurality of applications and the second plurality of applications, and assigning, by the processing system, a respective bitrate to each application of the first plurality of applications, wherein the assigning of the respective bitrate to each application of the first plurality of applications is based on: a first threshold associated with a re-buffering of content, and a second threshold associated with the statuses. Other embodiments are disclosed.

Method and apparatus for streaming video applications in cellular networks

A system that incorporates teachings of the present disclosure may include, for example, a coordinator device having a memory, and a controller. The memory can have computer instructions, which when executed by the controller, causes the controller to facilitate establishing a first virtual personal area network with a first sensor by executing computer instructions associated with a first application profile, and facilitate establishing a second virtual personal area network with a second sensor by executing computer instructions associated a second application profile. The first application profile can be defined by a first protocol specification, while the second application profile can be defined by a second protocol specification. The first protocol specification can also be operationally distinct from the second protocol specification. Other embodiments are disclosed.

Facilitating virtual personal area networks

A mechanism is provided for predicting video engagement from network measurements for a user device connected to a wireless network. Wireless network measurements are retrieved from a wireless network device in the wireless network. The wireless network measurements are related to the user device of a user. It is determined that the user device is engaged in a video streaming session. A computer classifies the video streaming session as one of a plurality of classes, in which the plurality of classes predict an outcome of the video streaming session for the user device.

Predicting video engagement from wireless network measurements

A method, a computer readable medium and an apparatus for optimizing a cellular network architecture are disclosed. For example, the method obtains network traffic data for a plurality of different endpoint device types, wherein the network traffic data comprises network traffic data for each of the plurality of different endpoint device types, and predicts a future traffic pattern for one of the plurality of different endpoint device types based on the network traffic data. The method then adjusts a parameter of the cellular network architecture in response to the future traffic pattern predicted for the one of the plurality of different endpoint device types.

Optimization of cellular network architecture based on device type-specific traffic dynamics

Techniques for sharing a cellular network connection amongst multiple devices over a local area network are provided that reduce cellular network load during crowded events. In an aspect, a devices is configure to perform operations that include scanning an area for another device that has established a first wireless cellular connection with a cellular network device of a cellular network and that enables an indirect connection of the device to the cellular network device via a direct connection of the device to the other device via a local network device. The operations further include, in response to identifying the other device as a result of the scanning, sending a request to the other device to connect to the other device via the local network device and to receive the indirect connection to the cellular network device.

Cellular connection sharing

A system and method identify a network upgrade from a data set including a plurality of configuration sessions. The system performs the method by receiving a plurality of configuration sessions. Each of the configuration sessions comprises a plurality of configuration commands. The configuration commands are generated by a same user identifier and within a time threshold. The method further includes identifying one of the configuration sessions as a network upgrade session. The identification is based on a rareness of the configuration session or a skewness of the configuration session.

Method and system for detecting network upgrades

Growing community of inventors

Randolph, NJ, United States of America

Jia Wang