Patents by Inventor Luca Natali
Luca Natali 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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Publication number: 20230031707Abstract: A method is provided to crimp a sheet having, before crimping, a thickness, a moisture, a composition, and a width, the method including: obtaining one pre-crimping sheet characteristic among the thickness of the sheet, the moisture of the sheet, the composition of the sheet, and the width of the sheet; crimping the sheet to form a plurality of corrugations on the sheet, the crimping including providing a pair of crimping rollers defining a nip therebetween, the nip having a nip size, and inserting the sheet in the nip; evaluating a post-crimping characteristic of the sheet after crimping; and varying the nip size on the basis of the obtained one of the pre-crimping sheet characteristic, and on the basis of the evaluated post-crimping sheet characteristic. An apparatus to crimp a sheet is also provided.Type: ApplicationFiled: November 11, 2020Publication date: February 2, 2023Applicant: Philip Morris Products S.A.Inventors: Massimiliano BERTOLDO, Matteo FRANCESCHI, Enrico GUIDOTTI, Luca NATALI, Ivan PRESTIA, Jerome UTHURRY, Dirk Guenter REIMANN
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Publication number: 20230011982Abstract: The invention relates to a method for optical analysis of a component of an aerosol generating article, the method comprising:—providing a component of an aerosol generating article defining a first end and a second end, the component comprising: o an aerosol forming substrate; o a susceptor in thermal contact with the aerosol forming substrate;—providing a first polarized camera including a sensor to detect polarization information of electromagnetic radiation;—illuminating the component by electromagnetic radiation;—detecting transmitted, infected or refracted electromagnetic radiation from the component by the first polarized camera; —generating a first image of the first end of the component by the first polarized camera, the first image being formed by a plurality of pixels, each pixel of the plurality of pixels containing polarization information about the detected electromagnetic radiation; and—detecting in the first image a position of the susceptor.Type: ApplicationFiled: November 11, 2020Publication date: January 12, 2023Inventors: Ricardo Cali, Andreas Löb, Luca Natali
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Patent number: 11461329Abstract: Query execution status may be tracked to selectively route queries to resources for execution. The completion of queries executing at computing resources obtained from a pool of computing resources configured to execute queries may be detected. Instead of returning the computing resources to the pool, the computing resources may be identified as available in resource management data. When another query is received, the resource management data may be evaluated to select an available computing resource. The query may then be routed to the selected computing resource for execution.Type: GrantFiled: August 28, 2020Date of Patent: October 4, 2022Assignee: Amazon Technologies, Inc.Inventors: Xing Wu, Bhargava Ram Kalathuru, Jian Fang, Yuanyuan Yue, Pratik Bhagwat Gawande, Turkay Mert Hocanin, Jason Douglas Denton, Luca Natali, Rahul Sharma Pathak, Abhishek Rajnikant Sinha, Sumeetkumar Veniklal Maru, Armen Tangamyan, Yufeng Jiang
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Patent number: 11461330Abstract: Queries may be received and executed by a managed query service. A query directed to data sets that are separately stored in a remote data store may be received. Computing resources to execute the query may be provisioned from a pool of computing resources that are configured to execute queries. The query may be routed to the provisioned computing resources to execute the query. Results may be obtained from the computing resource and provided to a submitter of the query.Type: GrantFiled: October 9, 2020Date of Patent: October 4, 2022Assignee: Amazon Technologies, Inc.Inventors: Bhargava Ram Kalathuru, Jian Fang, Xing Wu, Yuanyuan Yue, Pratik Bhagwat Gawande, Turkay Mert Hocanin, Jason Douglas Denton, Luca Natali, Rahul Sharma Pathak, Abhishek Rajnikant Sinha, Sumeetkumar Veniklal Maru, Armen Tangamyan, Yufeng Jiang
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Publication number: 20220248761Abstract: An aerosol-generating device for heating an aerosol-forming substrate to generate an aerosol is provided, the aerosol-generating device including: a substrate cavity configured to receive an aerosol-forming substrate; and an electromagnetic field generator including a solid state radio frequency (RF) transistor and being configured to generate a RF electromagnetic field in the substrate cavity. A method for generating an aerosol from an aerosol-forming substrate is also provided. An aerosol-generating article is also provided.Type: ApplicationFiled: June 29, 2020Publication date: August 11, 2022Applicant: Philip Morris Products S.A.Inventors: Robert EMMETT, Ana Isabel Gonzalez FLOREZ, Luca NATALI
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Patent number: 11403297Abstract: The configuration of computing resources for executing queries may be selected. A comparison of the configuration of computing resources that executed previous queries may be made to select the configuration of computing resources for a received query. A historical query execution model maybe applied, in some embodiments, to determine a resource configuration for computing resources to execute a query. The computing resources may be selected from available computing resources according to the determined resource configuration.Type: GrantFiled: April 3, 2020Date of Patent: August 2, 2022Assignee: Amazon Technologies, Inc.Inventors: Pratik Bhagwat Gawande, Sumeetkumar Veniklal Maru, Bhargava Ram Kalathuru, Jian Fang, Xing Wu, Yuanyuan Yue, Turkay Mert Hocanin, Jason Douglas Denton, Luca Natali, Rahul Sharma Pathak, Abhishek Rajnikant Sinha, Armen Tangamyan, Yufeng Jiang, Marc Howard Beitchman, Andrew Edward Caldwell
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Publication number: 20210392185Abstract: A service provider may apply customer-selected or customer-defined auto-scaling policies to a cluster of resources (e.g., virtualized computing resource instances or storage resource instances in a MapReduce cluster). Different policies may be applied to different subsets of cluster resources (e.g., different instance groups containing nodes of different types or having different roles). Each policy may define an expression to be evaluated during execution of a distributed application, a scaling action to take if the expression evaluates true, and an amount by which capacity should be increased or decreased. The expression may be dependent on metrics emitted by the application, cluster, or resource instances by default, metrics defined by the client and emitted by the application, or metrics created through aggregation. Metric collection, aggregation and rules evaluation may be performed by a separate service or by cluster components. An API may support auto-scaling policy definition.Type: ApplicationFiled: June 18, 2021Publication date: December 16, 2021Applicant: Amazon Technologies, Inc.Inventors: Jonathan Daly Einkauf, Luca Natali, Bhargava Ram Kalathuru, Saurabh Dileep Baji, Abhishek Rajnikant Sinha
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Patent number: 11044310Abstract: A service provider may apply customer-selected or customer-defined auto-scaling policies to a cluster of resources (e.g., virtualized computing resource instances or storage resource instances in a MapReduce cluster). Different policies may be applied to different subsets of cluster resources (e.g., different instance groups containing nodes of different types or having different roles). Each policy may define an expression to be evaluated during execution of a distributed application, a scaling action to take if the expression evaluates true, and an amount by which capacity should be increased or decreased. The expression may be dependent on metrics emitted by the application, cluster, or resource instances by default, metrics defined by the client and emitted by the application, or metrics created through aggregation. Metric collection, aggregation and rules evaluation may be performed by a separate service or by cluster components. An API may support auto-scaling policy definition.Type: GrantFiled: February 28, 2020Date of Patent: June 22, 2021Assignee: Amazon Technologies, Inc.Inventors: Jonathan Daly Einkauf, Luca Natali, Bhargava Ram Kalathuru, Saurabh Dileep Baji, Abhishek Rajnikant Sinha
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Publication number: 20210097080Abstract: Queries may be received and executed by a managed query service. A query directed to data sets that are separately stored in a remote data store may be received. Computing resources to execute the query may be provisioned from a pool of computing resources that are configured to execute queries. The query may be routed to the provisioned computing resources to execute the query. Results may be obtained from the computing resource and provided to a submitter of the query.Type: ApplicationFiled: October 9, 2020Publication date: April 1, 2021Applicant: Amazon Technologies, Inc.Inventors: Bhargava Ram Kalathuru, Jian Fang, Xing Wu, Yuanyuan Yue, Pratik Bhagwat Gawande, Turkay Mert Hocanin, Jason Douglas Denton, Luca Natali, Rahul Sharma Pathak, Abhishek Rajnikant Sinha, Sumeetkumar Veniklal Maru, Armen Tangamyan, Yufeng Jiang
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Publication number: 20210049175Abstract: Query execution status may be tracked to selectively route queries to resources for execution. The completion of queries executing at computing resources obtained from a pool of computing resources configured to execute queries may be detected. Instead of returning the computing resources to the pool, the computing resources may be identified as available in resource management data. When another query is received, the resource management data may be evaluated to select an available computing resource. The query may then be routed to the selected computing resource for execution.Type: ApplicationFiled: August 28, 2020Publication date: February 18, 2021Applicant: Amazon Technologies, Inc.Inventors: Xing Wu, Bhargava Ram Kalathuru, Jian Fang, Yuanyuan Yue, Pratik Bhagwat Gawande, Turkay Mert Hocanin, Jason Douglas Denton, Luca Natali, Rahul Sharma Pathak, Abhishek Rajnikant Sinha, Sumeetkumar Veniklal Maru, Armen Tangamyan, Yufeng Jiang
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Patent number: 10803060Abstract: Queries may be received and executed by a managed query service. A query directed to data sets that are separately stored in a remote data store may be received. Computing resources to execute the query may be provisioned from a pool of computing resources that are configured to execute queries. The query may be routed to the provisioned computing resources to execute the query. Results may be obtained from the computing resource and provided to a submitter of the query.Type: GrantFiled: March 27, 2017Date of Patent: October 13, 2020Assignee: Amazon Technologies, Inc.Inventors: Bhargava Ram Kalathuru, Jian Fang, Xing Wu, Yuanyuan Yue, Pratik Bhagwat Gawande, Turkay Mert Hocanin, Jason Douglas Denton, Luca Natali, Rahul Sharma Pathak, Abhishek Rajnikant Sinha, Sumeetkumar Veniklal Maru, Armen Tangamyan, Yufeng Jiang
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Patent number: 10762086Abstract: Query execution status may be tracked to selectively route queries to resources for execution. The completion of queries executing at computing resources obtained from a pool of computing resources configured to execute queries may be detected. Instead of returning the computing resources to the pool, the computing resources may be identified as available in resource management data. When another query is received, the resource management data may be evaluated to select an available computing resource. The query may then be routed to the selected computing resource for execution.Type: GrantFiled: March 27, 2017Date of Patent: September 1, 2020Assignee: Amazon Technologies, Inc.Inventors: Xing Wu, Bhargava Ram Kalathuru, Jian Fang, Yuanyuan Yue, Pratik Bhagwat Gawande, Turkay Mert Hocanin, Jason Douglas Denton, Luca Natali, Rahul Sharma Pathak, Abhishek Rajnikant Sinha, Sumeetkumar Veniklal Maru, Armen Tangamyan, Yufeng Jiang
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Publication number: 20200233869Abstract: The configuration of computing resources for executing queries may be selected. A comparison of the configuration of computing resources that executed previous queries may be made to select the configuration of computing resources for a received query. A historical query execution model maybe applied, in some embodiments, to determine a resource configuration for computing resources to execute a query. The computing resources may be selected from available computing resources according to the determined resource configuration.Type: ApplicationFiled: April 3, 2020Publication date: July 23, 2020Applicant: Amazon Technologies, Inc.Inventors: Pratik Bhagwat Gawande, Sumeetkumar Veniklal Maru, Bhargava Ram Kalathuru, Jian Fang, Xing Wu, Yuanyuan Yue, Turkay Mert Hocanin, Jason Douglas Denton, Luca Natali, Rahul Sharma Pathak, Abhishek Rajnikant Sinha, Armen Tangamyan, Yufeng Jiang, Marc Howard Beitchman, Andrew Edward Caldwell
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Publication number: 20200204623Abstract: A service provider may apply customer-selected or customer-defined auto-scaling policies to a cluster of resources (e.g., virtualized computing resource instances or storage resource instances in a MapReduce cluster). Different policies may be applied to different subsets of cluster resources (e.g., different instance groups containing nodes of different types or having different roles). Each policy may define an expression to be evaluated during execution of a distributed application, a scaling action to take if the expression evaluates true, and an amount by which capacity should be increased or decreased. The expression may be dependent on metrics emitted by the application, cluster, or resource instances by default, metrics defined by the client and emitted by the application, or metrics created through aggregation. Metric collection, aggregation and rules evaluation may be performed by a separate service or by cluster components. An API may support auto-scaling policy definition.Type: ApplicationFiled: February 28, 2020Publication date: June 25, 2020Applicant: Amazon Technologies, Inc.Inventors: Jonathan Daly Einkauf, Luca Natali, Bhargava Ram Kalathuru, Saurabh Dileep Baji, Abhishek Rajnikant Sinha
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Patent number: 10614066Abstract: The configuration of computing resources for executing queries may be selected. A comparison of the configuration of computing resources that executed previous queries may be made to select the configuration of computing resources for a received query. A historical query execution model maybe applied, in some embodiments, to determine a resource configuration for computing resources to execute a query. The computing resources may be selected from available computing resources according to the determined resource configuration.Type: GrantFiled: March 27, 2017Date of Patent: April 7, 2020Assignee: Amazon Technologies, Inc.Inventors: Pratik Bhagwat Gawande, Sumeetkumar Veniklal Maru, Bhargava Ram Kalathuru, Jian Fang, Xing Wu, Yuanyuan Yue, Turkay Mert Hocanin, Jason Douglas Denton, Luca Natali, Rahul Sharma Pathak, Abhishek Rajnikant Sinha, Armen Tangamyan, Yufeng Jiang, Marc Howard Beitchman, Andrew Edward Caldwell
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Patent number: 10581964Abstract: A service provider may apply customer-selected or customer-defined auto-scaling policies to a cluster of resources (e.g., virtualized computing resource instances or storage resource instances in a MapReduce cluster). Different policies may be applied to different subsets of cluster resources (e.g., different instance groups containing nodes of different types or having different roles). Each policy may define an expression to be evaluated during execution of a distributed application, a scaling action to take if the expression evaluates true, and an amount by which capacity should be increased or decreased. The expression may be dependent on metrics emitted by the application, cluster, or resource instances by default, metrics defined by the client and emitted by the application, or metrics created through aggregation. Metric collection, aggregation and rules evaluation may be performed by a separate service or by cluster components. An API may support auto-scaling policy definition.Type: GrantFiled: December 18, 2017Date of Patent: March 3, 2020Assignee: Amazon Technologies, Inc.Inventors: Jonathan Daly Einkauf, Luca Natali, Bhargava Ram Kalathuru, Saurabh Dileep Baji, Abhishek Rajnikant Sinha
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Publication number: 20180109610Abstract: A service provider may apply customer-selected or customer-defined auto-scaling policies to a cluster of resources (e.g., virtualized computing resource instances or storage resource instances in a MapReduce cluster). Different policies may be applied to different subsets of cluster resources (e.g., different instance groups containing nodes of different types or having different roles). Each policy may define an expression to be evaluated during execution of a distributed application, a scaling action to take if the expression evaluates true, and an amount by which capacity should be increased or decreased. The expression may be dependent on metrics emitted by the application, cluster, or resource instances by default, metrics defined by the client and emitted by the application, or metrics created through aggregation. Metric collection, aggregation and rules evaluation may be performed by a separate service or by cluster components. An API may support auto-scaling policy definition.Type: ApplicationFiled: December 18, 2017Publication date: April 19, 2018Applicant: Amazon Technologies, Inc.Inventors: JONATHAN DALY EINKAUF, LUCA NATALI, BHARGAVA RAM KALATHURU, SAURABH DILEEP BAJI, ABHISHEK RAJNIKANT SINHA
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Publication number: 20180060393Abstract: Queries may be received and executed by a managed query service. A query directed to data sets that are separately stored in a remote data store may be received. Computing resources to execute the query may be provisioned from a pool of computing resources that are configured to execute queries. The query may be routed to the provisioned computing resources to execute the query. Results may be obtained from the computing resource and provided to a submitter of the query.Type: ApplicationFiled: March 27, 2017Publication date: March 1, 2018Applicant: Amazon Technologies, Inc.Inventors: Bhargava Ram Kalathuru, Jian Fang, Xing Wu, Yuanyuan Yue, Pratik Bhagwat Gawande, Turkay Mert Hocanin, Jason Douglas Denton, Luca Natali, Rahul Sharma Pathak, Abhishek Rajnikant Sinha, Sumeetkumar Veniklal Maru, Armen Tangamyan, Yufeng Jiang
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Publication number: 20180060400Abstract: Query execution status may be tracked to selectively route queries to resources for execution. The completion of queries executing at computing resources obtained from a pool of computing resources configured to execute queries may be detected. Instead of returning the computing resources to the pool, the computing resources may be identified as available in resource management data. When another query is received, the resource management data may be evaluated to select an available computing resource. The query may then be routed to the selected computing resource for execution.Type: ApplicationFiled: March 27, 2017Publication date: March 1, 2018Applicant: Amazon Technologies, Inc.Inventors: Xing Wu, Bhargava Ram Kalathuru, Jian Fang, Yuanyuan Yue, Pratik Bhagwat Gawande, Turkay Mert Hocanin, Jason Douglas Denton, Luca Natali, Rahul Sharma Pathak, Abhishek Rajnikant Sinha, Sumeetkumar Veniklal Maru, Armen Tangamyan, Yufeng Jiang
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Publication number: 20180060133Abstract: Event-driven management may be implemented for resource pools. Pool management events may be detected at computing resources in a resource pool. Operations based on the pool management events may then be performed at the computing resources. In some embodiments, pool management events may trigger operations to a recycle a computing resource for reuse in a resource pool or perform other resource lifecycle operations.Type: ApplicationFiled: March 27, 2017Publication date: March 1, 2018Applicant: Amazon Technologies, Inc.Inventors: Jian Fang, Xing Wu, Bhargava Ram Kalathuru, Yuanyuan Yue, Pratik Bhagwat Gawande, Turkay Mert Hocanin, Jason Douglas Denton, Luca Natali, Rahul Sharma Pathak, Abhishek Rajnikant Sinha, Sumeetkumar Veniklal Maru, Armen Tangamyan, Yufeng Jiang