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公开(公告)号：US20240020282A1
公开(公告)日：2024-01-18
申请号：US17865945
申请日：2022-07-15
Applicant: Microsoft Technology Licensing, LLC
Inventor： Renato Luiz DE FREITAS CUNHA , Roberto DE MOURA ESTEVÃO FILHO , Leonardo DE OLIVEIRA NUNES , Anirudh BADAM
CPC classification number: G06F16/212 , G06F16/258
Abstract: Systems and methods for authoring workflows for processing data from a large-scale dataset include defining a metadata schema for the large-scale dataset, and receiving user input defining a workflow as a plurality of operations to be performed on the data. Each of the operations includes input metadata formatted according to the metadata schema. The input metadata describes input data to be processed by the operation and identifying a location for the input data in the data storage system, programmed instructions for performing an atomic operation on the input data to generate output data; and output metadata formatted according to the metadata schema. The output metadata describes the output data and identifying a location for the output data in the data storage system.
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公开(公告)号：US20220375031A1
公开(公告)日：2022-11-24
申请号：US17323358
申请日：2021-05-18
Applicant: Microsoft Technology Licensing, LLC
Inventor： Anirudh BADAM , Ranveer CHANDRA
Abstract: A computer implemented method includes obtaining data for raw image frames captured by a moving camera. The raw image frames are indexed geographically, and a graph is created from the multiple raw image frames. The graph includes image frames as vertices and edges that represent image frames having overlapping image information. The method further includes skipping frames based on the amount of overlap, determining a frame having an interesting feature, using the graph to find additional raw image frames that have the interesting feature, combining multiple raw image frames to form a unique image frame, and transmitting the unique image frame.
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公开(公告)号：US20210136171A1
公开(公告)日：2021-05-06
申请号：US16746105
申请日：2020-01-17
Applicant: Microsoft Technology Licensing, LLC
Inventor： Anirudh BADAM , Ranveer CHANDRA , Youjie LI , Sagar Ramanand JHA
IPC: H04L29/08
Abstract: A computing device is provided, including a logic subsystem with one or more processors, and memory storing instructions executable by the logic subsystem. These instructions are executed to obtain one or more source images, segment the one or more source images to generate a plurality of segments, determine a priority order for the plurality of segments, and transmit the plurality of segments to a remote computing device in the priority order. The plurality of segments are spatial components generated by spatial decomposition of the one or more source images and/or frequency components that are generated by frequency decomposition of the one or more source images. A remote computing device may receive these components in priority order, and perform certain algorithms on individual components without waiting for the entire image to upload.
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公开(公告)号：US20220405126A1
公开(公告)日：2022-12-22
申请号：US17354200
申请日：2021-06-22
Applicant: Microsoft Technology Licensing, LLC
Inventor： Mehmet Kadri UMAY , Anirudh BADAM , Philipp Andre WITTE , Imran SIDDIQUE
Abstract: Data from data sources may be processed at an edge device. The edge device may generate a local processing result, filter the data, and/or prioritize the data. Accordingly, data is transmitted from the edge device to the data platform, where it may be processed further. For example, a local processing result may be processed at the data platform, such that processing is performed without all of the data source data. In examples, at least a part of such data may remain at an edge device. The edge device may maintain a manifest of data stored by the edge device. The data platform may generate an aggregated manifest using manifests from associated edge devices, such that it may be determined where data is stored. As a result, the data platform may redirect requests to an associated edge device when it is determined that requested data is remote from the data platform.
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公开(公告)号：US20220263921A1
公开(公告)日：2022-08-18
申请号：US17661970
申请日：2022-05-04
Applicant: Microsoft Technology Licensing, LLC
Inventor： Anirudh BADAM , Ranveer CHANDRA , Youjie LI , Sagar Ramanand JHA
Abstract: A computing device is provided, including a logic subsystem with one or more processors, and memory storing instructions executable by the logic subsystem. These instructions are executed to obtain one or more source images, segment the one or more source images to generate a plurality of segments, determine a priority order for the plurality of segments, and transmit the plurality of segments to a remote computing device in the priority order. The plurality of segments are spatial components generated by spatial decomposition of the one or more source images and/or frequency components that are generated by frequency decomposition of the one or more source images. A remote computing device may receive these components in priority order, and perform certain algorithms on individual components without waiting for the entire image to upload.
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Patent Agency Ranking
公开(公告)号：US20240055100A1
公开(公告)日：2024-02-15
申请号：US18146123
申请日：2022-12-23
Applicant: MICROSOFT TECHNOLOGY LICENSING, LLC
Inventor： Sara Malvar MAUA , Anvita Kriti Prakash BHAGAVATHULA , Ranveer CHANDRA , Maria Angels de LUIS BALAGUER , Anirudh BADAM , Roberto DE MOURA ESTEVÃO FILHO , Swati SHARMA
IPC: G16H20/60
CPC classification number: G16H20/60
Abstract: This disclosure provides a machine learning technique to predict a protein characteristic. A first training set is created that includes, for multiple proteins, a target feature, protein sequences, and other information about the proteins. A first machine learning model is trained and then used to identify which of the features are relevant as determined by feature importance or causal relationships to the target feature. A second training set is created with only the relevant features. Embeddings generated from the protein sequences are also added to the second training set. The second training set is used to train a second machine learning model. The first and second machine learning models may be any type of regressors. Once trained, the second machine learning model is used to predict a value for the target feature for an uncharacterized protein. The model of this disclosure provides 91% accuracy in predicting an ideal digestibility score.
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公开(公告)号：US20230282316A1
公开(公告)日：2023-09-07
申请号：US17807685
申请日：2022-06-17
Applicant: Microsoft Technology Licensing, LLC
Inventor： Sara MALVAR MAUA , Leonardo DE OLIVEIRA NUNES , Mirco MILLETARI' , Neera Bansal TALBERT , Yazeed Khalid ALAUDAH , Jeremy Randall REYNOLDS , Yagna Deepika ORUGANTI , Ashish BHATIA , Anirudh BADAM
Abstract: A method for source attribution comprises receiving measurements of a chemical species at a spatially distributed sensor array for a given set of spatially positioned emission sources in a physical environment using a dispersion model. Based on the received measurements, a concentration field is mapped from the emission sources to the sensor array using a forward operator. For each emission source, a likelihood data set is evaluated at least by fitting an emission rate of the chemical species using a regression model based on the mapped concentration field and real-world, runtime measurements from the sensor array. A posterior data set is evaluated based at least on the evaluated likelihood data set and historical data for the physical environment. For each sensor of the sensor array, estimated emission rates and contribution rankings for emission sources are determined and output based on the evaluation of the posterior data set.
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公开(公告)号：US20230169222A1
公开(公告)日：2023-06-01
申请号：US17726206
申请日：2022-04-21
Applicant: Microsoft Technology Licensing, LLC
Inventor： Shirui WANG , Sara MALVAR MAUA , Leonardo DE OLIVEIRA NUNES , Kim D. WHITEHALL , Yagna Deepika ORUGANTI , Yazeed ALAUDAH , Anirudh BADAM , Mirco MILLETARI
IPC: G06F30/13
CPC classification number: G06F30/13
Abstract: A method for pollutant sensor placement for pollutants from point sources is described. Data about environmental characteristics for a geographic region are received from a plurality of environmental sensors. The geographic region includes pollutant sources that emit a pollutant. The received data from one or more of the plurality of environmental sensors are transformed into common data having a common spatial and temporal discretization across the geographic region. Predicted emission plumes are generated for the pollutant sources within the geographic region that identify pollutant detection regions for the pollutant when the pollutant is emitted by the pollutant sources using the common data. Sensor locations for a plurality of pollutant sensors are greedily selected across the common spatial and temporal discretization according to a number of predicted emission plumes that are detectable by the plurality of pollutant sensors.
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公开(公告)号：US20230007082A1
公开(公告)日：2023-01-05
申请号：US17363202
申请日：2021-06-30
Applicant: Microsoft Technology Licensing, LLC
Inventor： Conor E. KELLY , Ashish BHATIA , Yagna Deepika ORUGANTI , Peeyush KUMAR , Anirudh BADAM , Leonardo DE OLIVEIRA NUNES , Shirui WANG , Yazeed ALAUDAH , Neera B. TALBERT , Xinyu CHEN , Fatemeh ZAMANIAN
Abstract: A method for pollutant sensor placement is described. Data about environmental characteristics across a geographic region is received from a plurality of environmental sensors. The geographic region includes one or more pollutant sources that emit a pollutant. The received data is transformed from one or more of the plurality of environmental sensors into common data having a common grid across the geographic region. The geographic region is divided into a plurality of sub-regions based on the common data. Locations within the geographic region are determined for placement of pollutant sensors based on estimated dispersion of the pollutant through the plurality of sub-regions.
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公开(公告)号：US20190196748A1
公开(公告)日：2019-06-27
申请号：US15850578
申请日：2017-12-21
Applicant: Microsoft Technology Licensing, LLC
Inventor： Anirudh BADAM , Badriddine KHESSIB , Laura Marie CAULFIELD , Mihail Gavril TARTA , Robin Andrew ALEXANDER , Xiaozhong XING , Zhe TAN , Jian XU
CPC classification number: G06F3/0667 , G06F3/0605 , G06F3/0613 , G06F3/0631 , G06F3/064 , G06F3/0688 , G06F9/455 , G06F9/545 , G06F12/0246 , G06F2009/45587 , G06F2009/45595 , G06F2212/7201
Abstract: A system includes reception of a request from a first application to create a virtual open-channel solid state drive associated with a first bandwidth and first capacity, association, in response to the request, of block addresses of a virtual address space of the first application with block addresses of one or more blocks of a first one of a first plurality of channels of a first open-channel solid state drive and with block addresses of one or more blocks of a second one of a second plurality of channels of a second open-channel solid state drive, reception, from the first application, of a first I/O call associated with one or more block addresses of the virtual address space, determination of block addresses of one or more blocks of the first one of the first plurality of channels which are associated with the one or more block addresses of the virtual address space, and execution of the first I/O call on the determined block addresses of one or more blocks of the first one of the first plurality of channels.
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