Microsoft Technology Licensing, LLC

Amazon Technologies, Inc.

Sharp Laboratories of America, Inc

Other

Boe Technology Group Co., Ltd.

Beijing Boe Energy Technology Co., Ltd.

Beijing Shenogen Pharma Group Ltd.

Beijing Normal University

Greentech Environment Co., Ltd.

Academy of Military Medical Sciences

Institute of Pharmacology and Toxicology Academy of Military Medical Science P.l.a. China

Beijing Minhai Biotechnology Co., Ltd.

Beijing Orbiepharm Co., Ltd.

Institute of Pharmacology and Toxicology Academy of Military Science P.l.a. China

Jin Li

Cheng Huang

Sudipta Sengupta

Philip Andrew Chou

Sanjeev Mehrotra

Cha Zhang

Yunnan Wu

Rajesh Hegde

Shaw-min Lei

Minghua Chen

Zhengyou Zhang

Michel Pahud

Leo Parker Dirac

Biplob Kumar Debnath

Paul Adrian Oltean

Xingang Guo

Aaron William Ogus

Xian-Sheng Hua

Ran Kalach

Keith W Ross

Ronakkumar N Desai

Christian F Huitema

Qian Zhang

Zicheng Liu

Shao-Wen Yang

Sriram Krishnan

Sergey M Yekhanin

Hu Li

William A S Buxton

Kaushik Mani

Wenjun Zeng

Aleksandr Mikhaylovich Ingerman

Liuhong Yun

Bradley Gene Calder

Dan Teodosiu

Hui Zhu

Craig Henry Wittenberg

James Robert Benton

Tong L Wynn

Kun Meng

Alexandra K Heron

Ahmet Can Musabeyoglu

Xiaoyan Han

Eyal Schwartz

Parikshit Santhan Gopalan

Chao Zhang

Huseyin Simitci

John T Spivey

Eric J Horvitz

Jie Jerry Liu

Eyal Ofek

Lei Chen

Ramarathnam R Venkatesan

Xuedong D Huang

Desney S Tan

James David Johnston

Albert Gordon Greenberg

Timothy Mark Moore

Patrice Y Simard

Abhishek Gupta

Guang Yang

Ya-Qin Zhang

Ming Zhang

Paul A Viola

Lin Luo

Kai Sun

David A Maltz

Jyh-Han Lin

Tin Qian

Roy Peter D'Souza

Li-wei He

Cheng Zhang

Xin Wu

Juan Wang

Hao Chen

Jian Liang

Hua Chen

Humayun Mukhtar Khan

William David Sproule

Jeffrey Darren Couckuyt

Jiannan Zheng

Liang Lu

Aleksandar Kuzmanovic

Andrew Shaun Ivory

Shao Liu

David C Steere

Dinei Afonso Ferreira Florencio

Omkant Pandey

Nitin Suri

Kori Inkpen Quinn

Guo-Wei Shieh

Aravind Seshadri

Li-Wei He

Zehua Li

Mu Liu

Huiming Han

Yingqiang Su

Mengyuan Duan

Udaya Kumar Bhaskara

Joseph Schwartz

This disclosure describes an electronic device that can be installed within an access control system in parallel with a legacy interface device. The electronic device may perform steps of determining a set of configuration settings associated with an access control system to which the electronic device is electrically connected, receiving, by the electronic device, a first signal in a format associated with the access control system, configuring, based on the set of configuration settings, one or more signal pathways within the electronic device, generating, by routing the first signal through the one or more signal pathways, a second signal in a second format, and providing the second signal to at least one second electronic device.

Interface device for intercom access control systems

A machine learning service implements programmatic interfaces for a variety of operations on several entity types, such as data sources, statistics, feature processing recipes, models, and aliases. A first request to perform an operation on an instance of a particular entity type is received, and a first job corresponding to the requested operation is inserted in a job queue. Prior to the completion of the first job, a second request to perform another operation is received, where the second operation depends on a result of the operation represented by the first job. A second job, indicating a dependency on the first job, is stored in the job queue. The second job is initiated when the first job completes.

Machine learning service

A circuit board can be configured to access features and controls associated with a third-party circuit board. One or more spring-loaded pins or other connectors can contact one or more interaction points of the third-party circuit boards and form a connection. The circuit board can include a common or generic interface that the connections with the third-party circuit board are routed through by the circuit board. The generic interface can then connect the circuit board and third-party circuit board to external power sources, telecommunication devices, and connection ports. Based on the connection between the circuit board and the third-party circuit board, a user device can be assigned to and remotely access the features and controls of the third-party circuit board.

Configurable circuit board for abstracting third-party controls

A total nitrogen (TN) removal device for sewage and its operation method. The TN removal device includes a denitrification tank, a supplementary reaction zone filled with aerobic granular sludge and a sedimentation and separation zone. The supplementary reaction zone and the sedimentation and separation zone are arranged inside the denitrification tank, and communicated through a three-phase separator. The sedimentation and separation zone is located above the supplementary reaction zone. A top of the sedimentation and separation zone is greater than its bottom. A membrane aerated biofilm reactor (MABR) assembly is arranged in a space formed by outer walls of the sedimentation and separation zone and supplementary reaction zone and an inner chamber of the denitrification tank. A side wall of the denitrification tank is provided with a chemical oxygen demand (COD) detector and a nitrate nitrogen detector.

Total nitrogen removal device for sewage and method for operating the same

With respect to a package delivery system configured to optimize efficiencies associated with package delivery, a server computing device may monitor locations and conditions associated with a fleet of vehicles. A vehicle including a first delivery person may be dispatched with packages for delivery. The server computing device may provide updated delivery routes based on traffic and/or other conditions in the environment. At the completion of a work shift associated with the first delivery person, the vehicle may be parked at a location proximate the delivery route. The server computing device may dispatch a second delivery person to the location. Based on an indication that the second delivery person is proximate the vehicle, the server computing device may cause a user interface to surface on a computing device of the second delivery person, enabling the second delivery person to unlock the vehicle and continue delivering the packages.

Optimized package delivery

Embodiments herein describe a beacon that is used to verify a location of a user and provide access to a secure location (e.g., a locked building). The beacon includes a radio frequency reader which communicates with a tag (e.g., an NFC or RFID tag) disposed on a same surface as the beacon. For example, the beacon may cover the tag on the surface (e.g., a wall next to a locked door or access point into the secure location). The reader in the beacon can periodically perform a read cycle to identify the presence of the tag to ensure the beacon has not been removed. If during one or more cycles the reader does not detect the tag, the beacon can deactivate the beacon and no longer transmit the location verification code.

Tamper detection for beacons using radio frequency tags

Disclosed are various embodiments for anonymously validating the identities of multiple parties participating a transaction. In one embodiment, a system is configured to determine a location of the system is within a proximity threshold of a location and transmit an arrival indication to a remote computing device. The system is also configured to receive an encryption key from the remote computing device and detect a client device located at the location. The encryption key can be transmitted to the client device for validation that the location of the computing device is the location.

Privacy-preserving identity-validated transactions

Consistency metadata, including a parameter for a pseudo-random number source, are determined for training-and-evaluation iterations of a machine learning model. Using the metadata, a first training set comprising records of at least a first chunk is identified from a plurality of chunks of a data set. The first training set is used to train a machine learning model during a first training-and-evaluation iteration. A first test set comprising records of at least a second chunk is identified using the metadata, and is used to evaluate the model during the first training-and-evaluation iteration.

Consistent filtering of machine learning data

A delivery confirmation of a package at a delivery location may be determined based on a communication protocol between a user device and a package device associated with the package. A user can order an item and anticipate a delivery of the item to a delivery location associated with the user. A delivery device can determine that it has entered a geographic region associated with the delivery location. The delivery device and/or a user device associated with the delivery location can determine, using the communication protocol, that the delivery device is within a range of the user device. Then, the user device can receive a package device identifier associated with the package device, determine that the package device is within the range of the user device, and determine a delivery confirmation of the package.

Beacon-based delivery confirmation

In various embodiments, methods and systems for implementing distributed data object management are provided. The distributed data object management system includes a distributed storage system having a local metadata-consensus information store in and one or more remote metadata-consensus information stores. A metadata-consensus information store is configured to store metadata-consensus information. The metadata-consensus information corresponds to erasure coded fragments of a data object and instruct on how to manage the erasure coded fragments. The distributed storage system further includes a local data store and one or more remote data stores for the erasure coded fragments. The distributed data object management system includes a distributed data object manager for operations including, interface operations, configuration operations, write operations, read operations, delete operations, garbage collection operations and failure recovery operations. The distributed data object management system is operates based on metadata paths and data paths, operating in parallel, for write operations and read operations.

Distributed data object management system

A record extraction request for a data set is received at a machine learning service. A plan to perform one or more chunk-level operations (such as sampling, shuffling, splitting or partitioning for parallel computation) on chunks of the data set is generated. A set of data transfers that results in a particular chunk being stored in a particular server's memory is initiated to implement the first chunk-level operation of the sequence. A second operation such as another filtering operation or a feature processing operation is performed on a result set of the first chunk-level operation.

Input processing for machine learning

Described is using flash memory (or other secondary storage), RAM-based data structures and mechanisms to access key-value pairs stored in the flash memory using only a low RAM space footprint. A mapping (e.g. hash) function maps key-value pairs to a slot in a RAM-based index. The slot includes a pointer that points to a bucket of records on flash memory that each had keys that mapped to the slot. The bucket of records is arranged as a linear-chained linked list, e.g., with pointers from the most-recently written record to the earliest written record. Also described are compacting non-contiguous records of a bucket onto a single flash page, and garbage collection. Still further described is load balancing to reduce variation in bucket sizes, using a bloom filter per slot to avoid unnecessary searching, and splitting a slot into sub-slots.

Low RAM space, high-throughput persistent key value store using secondary memory

In various embodiments, methods and systems for implementing distributed data object management are provided. The distributed data object management system includes a local metadata-consensus information store and one or more remote metadata-consensus information stores for metadata-consensus information and a local data store and one or more remote data stores for erasure coded fragments. For a write operation, corresponding metadata writes and data writes are performed in parallel using a metadata write path and a data write path, respectively, when writing to the local metadata-consensus information store and the one or more remote metadata-consensus information stores and the local data store and the one or more remote data stores. And, for a read operation, corresponding metadata reads and data reads are performed in parallel using a metadata read path and a data read path, respectively, when reading from the metadata-consensus information stores and the data stores.

Distributed data object management system operations

The present invention provides a method for purifying an EV71 virus-like particle and a method for preparing a vaccine thereof. The virus-like particle is obtained by performing high density fermentation cultivation on recombinantly engineered bacteria; inducing expression of the EV71 virus-like particle protein expression using methanol; collecting the bacteria by centrifugation and performing high-pressure homogenization for disruption; performing precipitation on the supernatant with ammonium sulfate; and purifying by redissolution, ultrafiltration, ion exchange chromatography, molecular sieve chromatography, hydroxyapatite chromatography, etc.

Purification of recombinant EV71 virus-like particle and method for preparing vaccine thereof

Growing community of inventors

Sammamish, WA, United States of America

Jin Li