Patents by Inventor Jonathan DALY
Jonathan DALY 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: 20240078781Abstract: A method for determining a region for safe placement of a device in a medical image includes receiving a medical image, detecting at least one anatomic landmark in the medical image using at least one deep convolutional neural network, determining the region for safe placement of the device based on the detected at least one anatomic region using a semantic network, and displaying the region for safe placement of a device on the medical image using a display.Type: ApplicationFiled: October 12, 2020Publication date: March 7, 2024Inventors: Matthew S. Brown, Dieter R. Enzmann, Koon-Pong Wong, Jonathan G. Goldin, Fereidoun Abtin, Morgan Daly, Liza Shrestha
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Publication number: 20220132837Abstract: Methods and vitrification systems for biological samples are provided. The vitrification system has a rotatable cryowheel (210) with a facing surface (220). Droplets of a composition that includes a biological sample are released onto the facing surface. Droplets are rapidly pulled beneath the surface of the cryogenic coolant (160) to generate vitrified samples (180). Methods and cryopreservation devices are also provided that incorporate the vitrification systems.Type: ApplicationFiled: February 25, 2020Publication date: May 5, 2022Inventors: Nikolas Zuchowicz, Mary Hagedorn, Jonathan Daly, Li Zhan, Kanav Khosla, John Bischof
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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: 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: 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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Patent number: 10448846Abstract: Haemodynamic parameters such as the amplitude and phase of a pulse wave passing through a region of interest can be obtained from a video image of the exposed skin of a patient by processing of the reflectance photoplethysmographic signal using signal averaging. The region of interest is defined and a reflectance photoplethysmographic signal obtained by finding the mean pixel intensity across the region of interest for each video frame. Signal averaging is performed on the resulting pulsatile waveform by detecting peaks in the waveform, selecting those parts of the waveform which lie within a window centered on the peaks, and summing the selected parts of the waveform to find an average pulse waveform. The region of interest is then divided into sub-regions and an average pulse waveform for the video sequence is found for each of the sub-regions in the same way.Type: GrantFiled: December 14, 2015Date of Patent: October 22, 2019Assignee: OXFORD UNIVERSITY INNOVATION LIMITEDInventors: Lionel Tarassenko, Jonathan Daly
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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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Patent number: 9848041Abstract: 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: May 1, 2015Date of Patent: December 19, 2017Assignee: Amazon Technologies, Inc.Inventors: Jonathan Daly Einkauf, Luca Natali, Bhargava Ram Kalathuru, Saurabh Dileep Baji, Abhishek Rajnikant Sinha
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Publication number: 20170354334Abstract: Haemodynamic parameters such as the amplitude and phase of a pulse wave passing through a region of interest can be obtained from a video image of the exposed skin of a patient by processing of the reflectance photoplethysmographic signal using signal averaging. The region of interest is defined and a reflectance photoplethysmographic signal obtained by finding the mean pixel intensity across the region of interest for each video frame. Signal averaging is performed on the resulting pulsatile waveform by detecting peaks in the waveform, selecting those parts of the waveform which lie within a window centred on the peaks, and summing the selected parts of the waveform to find an average pulse waveform. The region of interest is then divided into sub-regions and an average pulse waveform for the video sequence is found for each of the sub-regions in the same way.Type: ApplicationFiled: December 14, 2015Publication date: December 14, 2017Applicant: OXFORD UNIVERSITY INNOVATION LIMITEDInventors: Lionel TARASSENKO, Jonathan DALY
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Publication number: 20160323377Abstract: 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: May 1, 2015Publication date: November 3, 2016Applicant: AMAZON TECHNOLOGIES, INC.Inventors: JONATHAN DALY EINKAUF, LUCA NATALI, BHARGAVA RAM KALATHURU, SAURABH DILEEP BAJI, ABHISHEK RAJNIKANT SINHA