Patents by Inventor Amar P. Azad
Amar P. Azad has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
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Patent number: 11734509Abstract: Methods, systems and computer program products for multi-style text transformation are provided herein. A computer-implemented method includes selecting at least one set of style specifications for transforming at least a portion of input text. The at least one set of style specifications include one or more target writing style domains selected from a plurality of writing style domains, weights for each of the target writing style domains representing relative impact of the target writing style domains for transformation of at least a portion of the input text, and weights for each of a set of linguistic aspects for transformation of at least a portion of the input text. The computer-implemented method also includes generating one or more style-transformed output texts based at least in part on the at least one set of style specifications utilizing at least one unsupervised neural network.Type: GrantFiled: December 29, 2020Date of Patent: August 22, 2023Assignee: International Business Machines CorporationInventors: Abhijit Mishra, Parag Jain, Amar P. Azad, Karthik Sankaranarayanan
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Patent number: 11574132Abstract: Methods, systems, and computer program products for unsupervised tunable stylized text transformations are provided herein. A computer-implemented method includes identifying amendable portions of input text by processing at least a portion of the input text using at least one neural network; determining stylistic text modifications to the amendable portions of the input text, the text modifications encompassing a set of stylistic parameters, wherein said determining comprises processing at least a portion of the set of stylistic parameters using at least one neural network; generating a stylized output set of text by transforming at least a portion of the input text, wherein said transforming comprises modifying at least one of the amendable portions of the input text via at least one of the stylistic text modifications encompassed by the set of stylistic parameters; and outputting the stylized output set of text to at least one user.Type: GrantFiled: December 23, 2020Date of Patent: February 7, 2023Assignee: International Business Machines CorporationInventors: Parag Jain, Amar P. Azad, Abhijit Mishra, Karthik Sankaranarayanan
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Publication number: 20220075936Abstract: Methods, systems, and computer program products for mining multi-party collaboration platforms to create triaging trees and playbooks are provided herein. A computer-implemented method includes obtaining, from a multi-user platform, conversations related to at least one technical issue; generating a plurality of triaging trees by analyzing the conversations, wherein each of the triaging trees stores information corresponding to temporal sequences of steps related to diagnosing and resolving said at least one technical issue; and deriving a playbook for resolving said at least one technical issue at least in part by combining two or more of the plurality of triaging trees.Type: ApplicationFiled: September 10, 2020Publication date: March 10, 2022Inventors: Amitkumar Manoharrao Paradkar, Amar P. Azad, Ajay Gupta, Suranjana Samanta, Prateeti Mohapatra, Harshit Kumar, Eyal Shnarch
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Patent number: 11204591Abstract: The present invention provides a method, system, and computer program product of modeling and calculating aggregate power of a set of renewable energy source stations using power output from representative renewable energy source stations. In an embodiment, the present invention includes receiving location, power output time series, and weather time series data of renewable energy source stations in a geographic region and aggregate power output time series data for the geographic region, for each cluster of stations, normalizing the aggregate power value to a representative renewable energy source station, learning a regression model, and de-normalizing a normalized aggregate output power model with respect to a maximum possible power value, and applying a combined model to the received data and power output of representative renewable energy source stations for a particular day, resulting in a total aggregate power value of the renewable energy source stations for the particular day.Type: GrantFiled: November 17, 2017Date of Patent: December 21, 2021Assignee: International Business Machines CorporationInventors: Umamaheswari Devi, Amith Singhee, Mathieu Sinn, Vincent Lonij, Amar P. Azad
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Patent number: 10998853Abstract: Methods, systems, and computer program products are provided herein in connection with IoT-enabled solar PV health monitoring and advising related thereto.Type: GrantFiled: April 9, 2018Date of Patent: May 4, 2021Assignee: International Business Machines CorporationInventors: Amar P. Azad, Manikandan Padmanaban, Kalyan Dasgupta, Shivkumar Kalyanaraman, Jagabondhu Hazra
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Publication number: 20210117618Abstract: Methods, systems and computer program products for multi-style text transformation are provided herein. A computer-implemented method includes selecting at least one set of style specifications for transforming at least a portion of input text. The at least one set of style specifications include one or more target writing style domains selected from a plurality of writing style domains, weights for each of the target writing style domains representing relative impact of the target writing style domains for transformation of at least a portion of the input text, and weights for each of a set of linguistic aspects for transformation of at least a portion of the input text. The computer-implemented method also includes generating one or more style-transformed output texts based at least in part on the at least one set of style specifications utilizing at least one unsupervised neural network.Type: ApplicationFiled: December 29, 2020Publication date: April 22, 2021Inventors: Abhijit Mishra, Parag Jain, Amar P. Azad, Karthik Sankaranarayanan
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Publication number: 20210110118Abstract: Methods, systems, and computer program products for unsupervised tunable stylized text transformations are provided herein. A computer-implemented method includes identifying amendable portions of input text by processing at least a portion of the input text using at least one neural network; determining stylistic text modifications to the amendable portions of the input text, the text modifications encompassing a set of stylistic parameters, wherein said determining comprises processing at least a portion of the set of stylistic parameters using at least one neural network; generating a stylized output set of text by transforming at least a portion of the input text, wherein said transforming comprises modifying at least one of the amendable portions of the input text via at least one of the stylistic text modifications encompassed by the set of stylistic parameters; and outputting the stylized output set of text to at least one user.Type: ApplicationFiled: December 23, 2020Publication date: April 15, 2021Inventors: Parag Jain, Amar P. Azad, Abhijit Mishra, Karthik Sankaranarayanan
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Patent number: 10977439Abstract: Methods, systems and computer program products for multi-style text transformation are provided herein. A computer-implemented method includes obtaining input text and selecting a set of style specifications for transforming the input text. The set of style specifications include one or more target writing style domains selected from a plurality of writing style domains, weights for each of the target writing style domains representing relative impact of the target writing style domains for transformation of the input text, and weights for each of a set of linguistic aspects for transformation of the input text. The computer-implemented method also includes generating one or more style-transformed output texts based at least in part on the set of style specifications utilizing an unsupervised neural network.Type: GrantFiled: April 1, 2019Date of Patent: April 13, 2021Assignee: International Business Machines CorporationInventors: Abhijit Mishra, Parag Jain, Amar P. Azad, Karthik Sankaranarayanan
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Patent number: 10915712Abstract: Methods, systems, and computer program products for unsupervised tunable stylized text transformations are provided herein. A computer-implemented method includes identifying stylistically amendable portions of input text by applying at least one neural network to the input text; determining stylistic text modifications to the amendable portions of the input text, the text modifications encompassing a set of stylistic parameters, wherein the determining comprises applying at least one neural network to the set of stylistic parameters; generating a stylized output set of text by transforming the input text, wherein the transforming comprises modifying at least one of the stylistically amendable portions of the input text via at least one of the stylistic text modifications encompassed by the set of stylistic parameters; and outputting the stylized output set of text to a user.Type: GrantFiled: July 26, 2018Date of Patent: February 9, 2021Assignee: International Business Machines CorporationInventors: Parag Jain, Amar P. Azad, Abhijit Mishra, Karthik Sankaranarayanan
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Publication number: 20200311195Abstract: Methods, systems and computer program products for multi-style text transformation are provided herein. A computer-implemented method includes obtaining input text and selecting a set of style specifications for transforming the input text. The set of style specifications include one or more target writing style domains selected from a plurality of writing style domains, weights for each of the target writing style domains representing relative impact of the target writing style domains for transformation of the input text, and weights for each of a set of linguistic aspects for transformation of the input text. The computer-implemented method also includes generating one or more style-transformed output texts based at least in part on the set of style specifications utilizing an unsupervised neural network.Type: ApplicationFiled: April 1, 2019Publication date: October 1, 2020Inventors: Abhijit Mishra, Parag Jain, Amar P. Azad, Karthik Sankaranarayanan
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Patent number: 10673372Abstract: Methods, systems, and computer program products for cognitively predicting dust deposition on solar photovoltaic modules are provided herein. A computer-implemented method includes deriving, with respect to solar photovoltaic modules, dust parameters from image data, and estimating, for a given future time at a current module orientation, an amount of surface area of the modules that will be covered by dust and a yield loss of the modules associated with dust coverage. The method also includes forecasting, for the given future time at each of one or more modified module orientations, an amount of surface area of the modules that will be covered by dust and a yield loss of the modules associated with dust coverage. Further, the method includes generating an instruction to change the orientation of at least one of the modules, and outputting the instruction to at least one actuation system associated with the modules.Type: GrantFiled: December 8, 2017Date of Patent: June 2, 2020Assignee: International Business Machines CorporationInventors: Amar P. Azad, Rashmi Mittal, Vijay Arya
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Publication number: 20200034432Abstract: Methods, systems, and computer program products for unsupervised tunable stylized text transformations are provided herein. A computer-implemented method includes identifying stylistically amendable portions of input text by applying at least one neural network to the input text; determining stylistic text modifications to the amendable portions of the input text, the text modifications encompassing a set of stylistic parameters, wherein the determining comprises applying at least one neural network to the set of stylistic parameters; generating a stylized output set of text by transforming the input text, wherein the transforming comprises modifying at least one of the stylistically amendable portions of the input text via at least one of the stylistic text modifications encompassed by the set of stylistic parameters; and outputting the stylized output set of text to a user.Type: ApplicationFiled: July 26, 2018Publication date: January 30, 2020Inventors: Parag Jain, Amar P. Azad, Abhijit Mishra, Karthik Sankaranarayanan
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Publication number: 20190312547Abstract: Methods, systems, and computer program products are provided herein in connection with IoT-enabled solar PV health monitoring and advising related thereto.Type: ApplicationFiled: April 9, 2018Publication date: October 10, 2019Inventors: Amar P. Azad, Manikandan Padmanaban, Kalyan Dasgupta, Shivkumar Kalyanaraman, Jagabondhu Hazra
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Publication number: 20190181793Abstract: Methods, systems, and computer program products for cognitively predicting dust deposition on solar photovoltaic modules are provided herein. A computer-implemented method includes deriving, with respect to solar photovoltaic modules, dust parameters from image data, and estimating, for a given future time at a current module orientation, an amount of surface area of the modules that will be covered by dust and a yield loss of the modules associated with dust coverage. The method also includes forecasting, for the given future time at each of one or more modified module orientations, an amount of surface area of the modules that will be covered by dust and a yield loss of the modules associated with dust coverage. Further, the method includes generating an instruction to change the orientation of at least one of the modules, and outputting the instruction to at least one actuation system associated with the modules.Type: ApplicationFiled: December 8, 2017Publication date: June 13, 2019Inventors: Amar P. Azad, Rashmi Mittal, Vijay Arya
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Publication number: 20190155234Abstract: The present invention provides a method, system, and computer program product of modeling and calculating aggregate power of a set of renewable energy source stations using power output from representative renewable energy source stations. In an embodiment, the present invention includes receiving location, power output time series, and weather time series data of renewable energy source stations in a geographic region and aggregate power output time series data for the geographic region, for each cluster of stations, normalizing the aggregate power value to a representative renewable energy source station, learning a regression model, and de-normalizing a normalized aggregate output power model with respect to a maximum possible power value, and applying a combined model to the received data and power output of representative renewable energy source stations for a particular day, resulting in a total aggregate power value of the renewable energy source stations for the particular day.Type: ApplicationFiled: November 17, 2017Publication date: May 23, 2019Inventors: Umamaheswari Devi, Amith Singhee, Mathieu Sinn, Vincent Lonij, Amar P. Azad