Patents by Inventor Dmitriy Bespalov
Dmitriy Bespalov 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: 20230306373Abstract: Aspects of the present disclosure relate generally to application ecosystems and, more particularly, to navigational and executional operations in an application ecosystem. In embodiments, a method includes: receiving, by a computing device, a natural language request input by a user to perform a task in an application ecosystem of a plurality of applications; determining, by the computing device, an actionable task from the natural language request to perform in the application ecosystem; generating, by the computing device, a user interface screen to perform the task with input parameters required to perform the task populated in elements of the user interface screen derived from the natural language request; and performing the task with the input parameters required in the application ecosystem of the plurality of applications.Type: ApplicationFiled: March 25, 2022Publication date: September 28, 2023Inventors: Dmitriy BESPALOV, Rohan PRASAD, Jiabo LI, Marmina ABDELMALEK, Thomas L. ROGERS, Kunal DARAL, Alexander CHAN, Gregory David HUNKINS
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Patent number: 10268962Abstract: The dynamic risk analyzer (DRA) provided by the present invention periodically assesses real-time or historic process data, or both, associated with an operations site, such as a manufacturing, production, or processing facility, including a plant's operations, and identifies hidden near-misses of such operation, when in real time the process data appears otherwise normal. DRA assesses the process data in a manner that enables operating personnel including management at a facility to have a comprehensive understanding of the risk status and changes in both alarm and non-alarm based process variables. The hidden process near-miss data may be analyzed alone or in combination with other process data and/or data resulting from prior near-miss situations to permit strategic action to be taken to reduce or avert the occurrence of adverse incidents or catastrophic failure of a facility operation.Type: GrantFiled: February 1, 2016Date of Patent: April 23, 2019Assignee: Near-Miss Management LLCInventors: Ankur Pariyani, Dmitriy Bespalov, Ulku G. Oktem, Luis Cielak
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Patent number: 9437108Abstract: Actual conditions of a roadway segment are estimated by providing roadway condition data to a processor for the roadway segment from a plurality of different types of sources of the roadway condition data, assigning a quality to each of the plurality of different types of sources of the roadway condition data, and estimating in the processor the actual conditions of the roadway segment by using the roadway condition data and the quality of each of the plurality of different types of sources of the roadway data. The quality determines weightings given to each of the plurality of different types of sources.Type: GrantFiled: February 9, 2015Date of Patent: September 6, 2016Assignee: HERE Global B.V.Inventors: Dmitriy Bespalov, James F. Carroll, I, Dean Zimmerman
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Publication number: 20160148107Abstract: The dynamic risk analyzer (DRA) provided by the present invention periodically assesses real-time or historic process data, or both, associated with an operations site, such as a manufacturing, production, or processing facility, including a plant's operations, and identifies hidden near-misses of such operation, when in real time the process data appears otherwise normal. DRA assesses the process data in a manner that enables operating personnel including management at a facility to have a comprehensive understanding of the risk status and changes in both alarm and non-alarm based process variables. The hidden process near-miss data may be analyzed alone or in combination with other process data and/or data resulting from prior near-miss situations to permit strategic action to be taken to reduce or avert the occurrence of adverse incidents or catastrophic failure of a facility operation.Type: ApplicationFiled: February 1, 2016Publication date: May 26, 2016Inventors: Ankur Pariyani, Dmitriy Bespalov, Ulku G. Oktem, Luis Cielak
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Publication number: 20150154862Abstract: Actual conditions of a roadway segment are estimated by providing roadway condition data to a processor for the roadway segment from a plurality of different types of sources of the roadway condition data, assigning a quality to each of the plurality of different types of sources of the roadway condition data, and estimating in the processor the actual conditions of the roadway segment by using the roadway condition data and the quality of each of the plurality of different types of sources of the roadway data. The quality determines weightings given to each of the plurality of different types of sources.Type: ApplicationFiled: February 9, 2015Publication date: June 4, 2015Inventors: Dmitriy Bespalov, James F. Carroll, I, Dean Zimmerman
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Patent number: 8972192Abstract: Actual conditions of a roadway segment are estimated by providing roadway condition data to a processor for the roadway segment from a plurality of different types of sources of the roadway condition data, assigning a quality to each of the plurality of different types of sources of the roadway condition data, and estimating in the processor the actual conditions of the roadway segment by using the roadway condition data and the quality of each of the plurality of different types of sources of the roadway data. The quality determines weightings given to each of the plurality of different types of sources.Type: GrantFiled: September 25, 2007Date of Patent: March 3, 2015Assignee: HERE Global B.V.Inventors: Dmitriy Bespalov, James F. Carroll, Dean Zimmerman
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Publication number: 20130080443Abstract: A scale-Space feature extraction technique is based on recursive decomposition of polyhedral surfaces into surface patches. The experimental results show that this technique can be used to perform matching based on local model structure. Scale-space techniques can be parameterized to generate decompositions that correspond to manufacturing, assembly or surface features relevant to mechanical design. One application of these techniques is to support matching and content-based retrieval of solid models. Scale-space technique can extract features that are invariant with respect to the global structure of the model as well as small perturbations that 3D laser scanning may introduce. A new distance function defined on triangles instead of points is introduced. This technique offers a new way to control the feature decomposition process, which results in extraction of features that are more meaningful from an engineering viewpoint. The technique is computationally practical for use in indexing large models.Type: ApplicationFiled: July 25, 2012Publication date: March 28, 2013Applicant: DREXEL UNIVERSITYInventors: WILLIAM C. REGLI, ALI SHOKOUFANDEH, DMITRIY BESPALOV
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Publication number: 20120253792Abstract: A method for sentiment classification of a text document using high-order n-grams utilizes a multilevel embedding strategy to project n-grams into a low-dimensional latent semantic space where the projection parameters are trained in a supervised fashion together with the sentiment classification task. Using, for example, a deep convolutional neural network, the semantic embedding of n-grams, the bag-of-occurrence representation of text from n-grams, and the classification function from each review to the sentiment class are learned jointly in one unified discriminative framework.Type: ApplicationFiled: March 20, 2012Publication date: October 4, 2012Applicant: NEC LABORATORIES AMERICA, INC.Inventors: Dmitriy Bespalov, Bing Bai, Yanjun Qi
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Patent number: 8266079Abstract: A scale-Space feature extraction technique is based on recursive decomposition of polyhedral surfaces into surface patches. The experimental results show that this technique can be used to perform matching based on local model structure. Scale-space techniques can be parameterized to generate decompositions that correspond to manufacturing, assembly or surface features relevant to mechanical design. One application of these techniques is to support matching and content-based retrieval of solid models. Scale-space technique can extract features that are invariant with respect to the global structure of the model as well as small perturbations that 3D laser scanning may introduce. A new distance function defined on triangles instead of points is introduced. This technique offers a new way to control the feature decomposition process, which results in extraction of features that are more meaningful from an engineering viewpoint. The technique is computationally practical for use in indexing large models.Type: GrantFiled: July 19, 2011Date of Patent: September 11, 2012Assignee: Drexel UniversityInventors: William C. Regli, Ali Shokoufandeh, Dmitriy Bespalov
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Publication number: 20120136860Abstract: A scale-Space feature extraction technique is based on recursive decomposition of polyhedral surfaces into surface patches. The experimental results show that this technique can be used to perform matching based on local model structure. Scale-space techniques can be parameterized to generate decompositions that correspond to manufacturing, assembly or surface features relevant to mechanical design. One application of these techniques is to support matching and content-based retrieval of solid models. Scale-space technique can extract features that are invariant with respect to the global structure of the model as well as small perturbations that 3D laser scanning may introduce. A new distance function defined on triangles instead of points is introduced. This technique offers a new way to control the feature decomposition process, which results in extraction of features that are more meaningful from an engineering viewpoint. The technique is computationally practical for use in indexing large models.Type: ApplicationFiled: July 19, 2011Publication date: May 31, 2012Applicant: DREXEL UNIVERSITYInventors: WILLIAM C. REGLI, ALI SHOKOUFANDEH, DMITRIY BESPALOV
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Patent number: 8015125Abstract: A scale-Space feature extraction technique is based on recursive decomposition of polyhedral surfaces into surface patches. The experimental results show that this technique can be used to perform matching based on local model structure. Scale-space techniques can be parameterized to generate decompositions that correspond to manufacturing, assembly or surface features relevant to mechanical design. One application of these techniques is to support matching and content-based retrieval of solid models. Scale-space technique can extract features that are invariant with respect to the global structure of the model as well as small perturbations that 3D laser scanning may introduce. A new distance function defined on triangles instead of points is introduced. This technique offers a new way to control the feature decomposition process, which results in extraction of features that are more meaningful from an engineering viewpoint. The technique is computationally practical for use in indexing large models.Type: GrantFiled: August 30, 2007Date of Patent: September 6, 2011Assignee: Drexel UniversityInventors: William C. Regli, Ali Shokoufandeh, Dmitriy Bespalov
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Patent number: 7755509Abstract: Actual traffic conditions of a roadway segment are predicted by providing a plurality of historical roadway condition patterns of the roadway segment in a database, obtaining an electronic representation of a current roadway condition pattern of the roadway segment, identifying one or more of the historical roadway condition patterns that closely matches the current roadway condition pattern, and predicting the future actual traffic conditions of the roadway segment by using the conditions associated with the one or more identified historical patterns.Type: GrantFiled: October 9, 2007Date of Patent: July 13, 2010Assignee: Traffic.com, Inc.Inventors: Dmitriy Bespalov, Ali Shokoufandeh
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Publication number: 20090079586Abstract: Actual traffic conditions of a roadway segment are predicted by providing a plurality of historical roadway condition patterns of the roadway segment in a database, obtaining an electronic representation of a current roadway condition pattern of the roadway segment, identifying one or more of the historical roadway condition patterns that closely matches the current roadway condition pattern, and predicting the future actual traffic conditions of the roadway segment by using the conditions associated with the one or more identified historical patterns.Type: ApplicationFiled: October 9, 2007Publication date: March 26, 2009Applicant: TRAFFIC.COM, INC.Inventors: Dmitriy Bespalov, Ali Shokoufandeh
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Publication number: 20090080973Abstract: Actual conditions of a roadway segment are estimated by providing roadway condition data to a processor for the roadway segment from a plurality of different types of sources of the roadway condition data, assigning a quality to each of the plurality of different types of sources of the roadway condition data, and estimating in the processor the actual conditions of the roadway segment by using the roadway condition data and the quality of each of the plurality of different types of sources of the roadway data. The quality determines weightings given to each of the plurality of different types of sources.Type: ApplicationFiled: September 25, 2007Publication date: March 26, 2009Applicant: TRAFFIC.COM, INC.Inventors: Dmitriy Bespalov, James F. Carroll, Dean Zimmerman
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Publication number: 20080215510Abstract: A scale-Space feature extraction technique is based on recursive decomposition of polyhedral surfaces into surface patches. The experimental results show that this technique can be used to perform matching based on local model structure. Scale-space techniques can be parameterized to generate decompositions that correspond to manufacturing, assembly or surface features relevant to mechanical design. One application of these techniques is to support matching and content-based retrieval of solid models. Scale-space technique can extract features that are invariant with respect to the global structure of the model as well as small perturbations that 3D laser scanning may introduce. A new distance function defined on triangles instead of points is introduced. This technique offers a new way to control the feature decomposition process, which results in extraction of features that are more meaningful from an engineering viewpoint. The technique is computationally practical for use in indexing large models.Type: ApplicationFiled: August 30, 2007Publication date: September 4, 2008Applicant: DREXEL UNIVERSITYInventors: WILLIAM C. REGLI, ALI SHOKOUFANDEH, DMITRIY BESPALOV