Patents by Inventor Thomas D. Franklin
Thomas D. Franklin 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: 11902182Abstract: The present disclosure describes a patent management system and method for remediating insufficiency of input data for a machine learning system. A plurality of data vectors using data are extracted from a plurality of data sources. A user input with respect to an input data context is received, the input data context correspond to a subset of the plurality of data elements. An input vector based on the user input is generated and a set of matching data vectors are determined from the plurality of data vectors based on the input vector. An insufficiency of the input data is determined based on a comparison of a number of matching data vectors with a first pre-determined threshold, and/or a variance with a second pre-determined threshold. Further, the set of matching data vectors are expanded by modifying the input vector when the input data is determined to be insufficient.Type: GrantFiled: February 25, 2022Date of Patent: February 13, 2024Assignee: Triangle IPInventor: Thomas D. Franklin
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Publication number: 20220283921Abstract: A compliance testing system for generating a compliance prediction for a test target. Determinate factors and indeterminate factors associated with a current testing stage of the test target are identified. A test vector for each of the indeterminate factors is generated. A set of matching test vectors for each of the indeterminate factors is determined based on the test vector. The set of matching test vectors are determined using data extracted from at least one profile model. A cumulative factor value is determined for each of the indeterminate factors based on the set of matching test vectors. A first outcome is generated for each of the determinate factors. A second outcome is generated for each of the indeterminate factors, based on the cumulative factor value and the set of matching test vectors. A compliance prediction is generated for the test target based on the first outcome and the second outcome.Type: ApplicationFiled: February 24, 2021Publication date: September 8, 2022Applicant: Triangle IP, Inc.Inventor: Thomas D. FRANKLIN
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Publication number: 20220255881Abstract: The present disclosure describes a patent management system and method for remediating insufficiency of input data for a machine learning system. A plurality of data vectors using data are extracted from a plurality of data sources. A user input with respect to an input data context is received, the input data context correspond to a subset of the plurality of data elements. An input vector based on the user input is generated and a set of matching data vectors are determined from the plurality of data vectors based on the input vector. An insufficiency of the input data is determined based on a comparison of a number of matching data vectors with a first pre-determined threshold, and/or a variance with a second pre-determined threshold. Further, the set of matching data vectors are expanded by modifying the input vector when the input data is determined to be insufficient.Type: ApplicationFiled: February 25, 2022Publication date: August 11, 2022Inventor: Thomas D. FRANKLIN
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Patent number: 11323388Abstract: The present disclosure receives input signals from different sources to fill gaps in a desired heat score signal. Received input signals are categorized to match to a desired category of the desired signal. The various signals are represented in vector format using category tags. There are different latencies for each input signal that are aligned in time with the desired signal. The match to the desired signal varies from the input signals so that each desired signal's contribution during the gap is weighted accordingly. A composite signal is formulated from the time-adjusted and weighted input signals to fill the gap in the desired signal. Over time, the weighting and time-adjustment for each input signal can be modified with a machine learning algorithm that takes the approximation during the gap and compares it later with the actual data once the gap is filled.Type: GrantFiled: September 29, 2020Date of Patent: May 3, 2022Assignee: Triangle IP, Inc.Inventor: Thomas D. Franklin
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Patent number: 11283727Abstract: The present disclosure describes a patent management system and method for remediating insufficiency of input data for a machine learning system. A plurality of data vectors using data are extracted from a plurality of data sources. A user input with respect to an input data context is received, the input data context correspond to a subset of the plurality of data elements. An input vector based on the user input is generated and a set of matching data vectors are determined from the plurality of data vectors based on the input vector. An insufficiency of the input data is determined based on a comparison of a number of matching data vectors with a first pre-determined threshold, and/or a variance with a second pre-determined threshold. Further, the set of matching data vectors are expanded by modifying the input vector when the input data is determined to be insufficient.Type: GrantFiled: November 16, 2020Date of Patent: March 22, 2022Assignee: Triangle IP, Inc.Inventor: Thomas D. Franklin
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Publication number: 20210263818Abstract: A compliance testing system for generating a compliance prediction for a test target. Determinate factors and indeterminate factors associated with a current testing stage of the test target are identified. A test vector for each of the indeterminate factors is generated. A set of matching test vectors for each of the indeterminate factors is determined based on the test vector. The set of matching test vectors are determined using data extracted from at least one profile model. A cumulative factor value is determined for each of the indeterminate factors based on the set of matching test vectors. A first outcome is generated for each of the determinate factors. A second outcome is generated for each of the indeterminate factors, based on the cumulative factor value and the set of matching test vectors. A compliance prediction is generated for the test target based on the first outcome and the second outcome.Type: ApplicationFiled: February 24, 2021Publication date: August 26, 2021Applicant: Triangle IP, Inc.Inventor: Thomas D. FRANKLIN
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Publication number: 20210083990Abstract: The present disclosure describes a patent management system and method for remediating insufficiency of input data for a machine learning system. A plurality of data vectors using data are extracted from a plurality of data sources. A user input with respect to an input data context is received, the input data context correspond to a subset of the plurality of data elements. An input vector based on the user input is generated and a set of matching data vectors are determined from the plurality of data vectors based on the input vector. An insufficiency of the input data is determined based on a comparison of a number of matching data vectors with a first pre-determined threshold, and/or a variance with a second pre-determined threshold. Further, the set of matching data vectors are expanded by modifying the input vector when the input data is determined to be insufficient.Type: ApplicationFiled: November 16, 2020Publication date: March 18, 2021Applicant: Triangle IP, Inc.Inventor: Thomas D. FRANKLIN
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Patent number: 10812410Abstract: The present disclosure uses input signals from different sources to fill gaps in the desired signal, for example a heat score signal. Different input signals are categorized so that they can be matched to a desired category of the desired signal. The various signals can be represented in vector format using category tags, for example. There are different latencies for each input signal that is aligned in time with the desired signal. Also, the match to the desired signal may vary from the input signals so that each desired signal's contribution during the gap is weighted accordingly. A composite signal is formulated from the time-adjusted and weighted input signals to fill the gap in the desired signal. Over time, the weighting and time-adjustment for each input signal can be modified with a learning algorithm that takes the approximation during the gap and compares it later with the actual data once the gap is filled in one embodiment.Type: GrantFiled: September 23, 2019Date of Patent: October 20, 2020Assignee: Triangle IP, Inc.Inventor: Thomas D. Franklin
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Patent number: 10425353Abstract: A method and system for determining of timing for vector following a branched processing model is disclosed. A data source is mined to determine event vectors from a large number of cases that follow a branched processing model. Current event vectors are compared to the mined event vectors with machine learning to predict future nodes for the current event vectors. Historical temporal spacing for the mined event vectors are used to predict temporal position for the current event vector in the future.Type: GrantFiled: April 8, 2019Date of Patent: September 24, 2019Assignee: Triangle IP, Inc.Inventors: Sameer Vadera, Katherine S. Gaudry, Thomas D. Franklin
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Patent number: 10257116Abstract: A method and system for allocation of resources is disclosed. A data source is mined to determine event vectors from a large number of cases that follow a branched processing model. Current event vectors are compared to the mined event vectors with machine learning to predict future nodes for the current event vectors. Historical resource allocations for the mined event vectors are used to determine resource allocation for the current event vector over time. Current event vectors are combined to produce a resource allocation curve showing past and future resources allocated.Type: GrantFiled: August 31, 2018Date of Patent: April 9, 2019Assignee: Triangle IP, Inc.Inventors: Sameer Vadera, Katherine S. Gaudry, Thomas D. Franklin
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Patent number: 10069759Abstract: A method and system for allocation of resources is disclosed. Authenticated and unauthenticated data sources are mined to determine event vectors from a large number of cases that follow a branched processing model. A current event vector is compared to the mined event vectors with machine learning to predict future nodes for the current event vector. Historical resource allocations for the mined event vectors are used to determine resource allocation for the current event vector over time.Type: GrantFiled: January 29, 2018Date of Patent: September 4, 2018Assignee: TRIANGLE IP, INC.Inventors: Sameer Vadera, Katherine S. Gaudry, Thomas D. Franklin
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Publication number: 20100062519Abstract: An organ and tissue preservation and transport apparatus comprising a chamber, a temperature control mechanism and a system monitor. A medium bathes an organ within the chamber. The temperature control mechanism adjusts the temperature of the medium. The system monitors receiving and records the temperature of the chamber.Type: ApplicationFiled: November 12, 2009Publication date: March 11, 2010Inventors: Thomas D. Franklin, JR., Stacie L. Hyatt, Howell E. Warner, Marshall Wenrich, Marvin J. Slepian, Shell Lambert
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Publication number: 20080145919Abstract: An organ and tissue preservation and transport apparatus comprising a chamber, a temperature control mechanism and a system monitor. A medium bathes an organ within the chamber. The temperature control mechanism adjusts the temperature of the medium. The system monitor receiving and records the temperature of the chamber.Type: ApplicationFiled: December 18, 2006Publication date: June 19, 2008Inventors: Thomas D. Franklin, Stacie L. Hyatt, Howell E. Warner, Marshall Wenrich, Marvin J. Slepian, Shell Lambert