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41.发明授权公开(公告)号：US12014195B2
公开(公告)日：2024-06-18
申请号：US17553972
申请日：2021-12-17
Inventor： Parasu Pillai Iyappan Velammal , Kumaresan Ramachandran , Karthikeyan Mohan , Jeyashree Pandian Duraipandian , Madhusudhan Venkatesan
CPC classification number: G06F9/45516 , G06F8/423 , G06F9/44505 , G06F11/0772 , G06F11/3604
Abstract: A system and a method for application transformation to cloud by conversion of an application source code to a cloud native code is provided. First and second transformation recommendation paths are received and remediation tem plates based on the same are applied. A pre-defined transformation process flow is applied on application source code based on first and second transformation recommendation paths including a pre-processing stage involving analysis of source code and target framework. A plugin unit is provided which provides an adaptable plugin framework for creating multiple plugin types. The adaptable plugin framework allows addition of semi-automated workflow that applies functionality to accelerate application development or application to cloud transformation or addition of semi-automated steps to accelerate greenfield application development and application source code transformation to cloud native code. The functionality may include assessment of application source code and generation of application source code.
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公开(公告)号：US11893354B2
公开(公告)日：2024-02-06
申请号：US17347773
申请日：2021-06-15
Inventor： Jithu R Jacob , Siddhartha Das
IPC: G06F40/30 , G06F40/232 , G06F40/117 , G10L25/30
CPC classification number: G06F40/30 , G06F40/117 , G06F40/232 , G10L25/30
Abstract: The present invention provides for improving training dataset by identifying errors in training dataset and generating improvement recommendations. In operation, the present invention provides for identifying and correcting duplicate utterances in training dataset comprising utterances-intent pairs. Further, a plurality of Natural Language ML models are trained with the corrected training dataset to obtain diverse set of trained ML models. Each utterance of training dataset are fed as input to trained ML models, and a probability of error associated with each utterances-intent pairs of training dataset are evaluated based on analysis of respective intent predictions received from each of the trained ML models. Furthermore, spelling errors in the dataset are identified and data-imbalances in the training dataset are evaluated. Finally, a set of improvement recommendations for each utterances-intent pair is generated based on evaluated probability of errors, spelling errors, duplicate utterances and data imbalances.
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公开(公告)号：US20230419195A1
公开(公告)日：2023-12-28
申请号：US18083654
申请日：2022-12-19
Inventor： Mrityunjoy Panday
IPC: G06Q10/04 , G06Q10/0631
CPC classification number: G06Q10/04 , G06Q10/06313
Abstract: The present invention provides for a system and a method for optimised time series forecasting. A time-series dataset is converted corresponding to a system, for which forecast data is to be determined, into data embeddings in the form of a distance vector. A hierarchical clustering of values of the distance vector is performed, wherein the hierarchical clustering comprises creating a high-level cluster by combining two or more local clusters. A hierarchical tree is created based on the hierarchical clustering, wherein the hierarchical tree represents a first level cluster and a second level cluster. A plurality of factors is extracted from each node of the tree and a gaussian process decomposition is applied on the extracted factors from each node of the tree to determine decomposed factors. The decomposed factors represent interpretable components of the extracted factors and a forecast data is determined for system based on decomposed factors.
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公开(公告)号：US11741194B2
公开(公告)日：2023-08-29
申请号：US17130756
申请日：2020-12-22
Inventor： Srinivasan Thiagarajan , Saritha Panapparambil Abubacker , Surendranathan Ardhanari , Vinoth Kumar Devarajan , Yuvarajan Mani , Suganya Thirumalaisamy , Saranya Nedumaran , Vijayalakshmi Senthilkumar , Manikandan Namasivayam , Radha Ponram , Monalisa Behera
Abstract: The present invention relates to a system and method for application debt management with zero maintenance strategy that make the applications “fit for use” and “fit for purpose”. The objective is to ensure that applications run at the lowest cost, deliver maximum performance and serve the purpose for which it was developed. The machine learning enabled debt engine of present system reads the unstructured ticket data or debts, eliminates noise, and classify the debts into one of predefined categories. This is followed by remediation of debt via either of automation or healing workbench based on predetermined priorities.
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公开(公告)号：US20230188613A1
公开(公告)日：2023-06-15
申请号：US17674014
申请日：2022-02-17
Inventor： Parasu Pillai Iyappan Velammal , Karthikeyan Mohan , Rangarajan Ramadass , Selvaraj Natarajan
IPC: H04L67/00 , H04L67/148 , H04L67/01 , G06F8/72 , G06F8/60
CPC classification number: H04L67/34 , H04L67/148 , H04L67/42 , G06F8/72 , G06F8/60
Abstract: The present invention provides for migration of application running on source cloud platform to target cloud platform. In operation, the present invention provides for retrieving analysis-data including source code of application to be migrated, hereinafter referred to as application M, a runtime data of application M, and target cloud platform data. The present invention further provides for identifying migration parameters based on analysis-data. Further, migration readiness of application M to target cloud platform is assessed based on migration parameters. Furthermore, a migration readiness report is generated based on the migration parameters, migration readiness assessment and the runtime data. Yet further, deployment configurations for the application M are generated as per the target cloud platform based on the migration readiness report. Yet further, the application is migrated to the target cloud platform based on the generated deployment configurations by creating Continuous Integration/Continuous Deployment (CI/CD) pipeline.
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Patent Agency Ranking
公开(公告)号：US20220156173A1
公开(公告)日：2022-05-19
申请号：US17157101
申请日：2021-01-25
Inventor： Rajkumar Chandrasekaran , Karthikeyan Vedagiri , Vishwajit Mankar
Abstract: The present invention relates to a system and method for assessing performance of a software release in a production environment. The attempt is to measure impact of delivered features and correlate with cost incurred in building those features to calculate a return on investment made. The disclosure, thus, provides for fetching relevant details from plurality of tools or data sources, correlating the fetched information and linking it with milestone data. This milestone data is labeled with a milestone id to enable querying of data sources and determine impact delivered. The determined impact is linked with calculated cost identifier to finally assess the release performance.
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公开(公告)号：US20220101164A1
公开(公告)日：2022-03-31
申请号：US17096380
申请日：2020-11-12
Inventor： Ashish Majumdar
Abstract: A system and a method for providing data computation using quantum computing is disclosed. In particular, the present invention enables client computing devices to readily access quantum computers and perform complex computational tasks using quantum computing. In operation, a computational problem is defined based on one or more inputs received from the client device. The one or more inputs include an objective, and one or more parameters associated with the objective. Further, a category associated with the computational problem is identified. Furthermore, one or more predefined machine learning codes are determined based on the identified category of the computational problem. Finally, the computational problem is encoded into a format interpretable by the quantum computers, and processed by the quantum computers based on the selected one or more machine learning codes to obtain an optimal solution to the computational problem.
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公开(公告)号：US11232189B2
公开(公告)日：2022-01-25
申请号：US16114395
申请日：2018-08-28
Inventor： Rajkumar Chandrasekaran , Karthikeyan Vedagiri
Abstract: A system and method for tracking and authenticating software code transition during various phases of software development and deployment in a DevOps platform is provided. The present invention provides for creating, modifying and deleting one or more code authentication elements including respective policies within a distributed ledger. The code authentication elements are mapped with one or more event types in respective one or more tools of a DevOps platform. Information associated with occurrence of an event in one or more tools of the DevOps platform are retrieved. The retrieved event information is parsed to extract event type and a code authentication element is invoked based on the identified event type. The invoked code authentication element authenticates software code transition to appropriate tool of DevOps platform based on one more defined policies. A result representative of authentication success or failure is stored in the distributed ledger for tracking and auditing.
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公开(公告)号：US11151483B2
公开(公告)日：2021-10-19
申请号：US16400499
申请日：2019-05-01
Inventor： Mrityunjoy Panday , Nagarajan Kumar
IPC: G06F16/242 , G06Q10/06 , G06F16/2458
Abstract: A System and a Method for Assessing Data for Analytics A system and a method for assessing readiness of data for data science and analytics is disclosed. The present invention quantifies readiness of data by providing a data insight quotient (DIQ). In particular, a nucleus of a dataset retrieved from an enterprise database is derived. The dataset is representative of data collected for a predefined objective over a period of time and includes a plurality of features and records. Further, a plurality of time-ordered datasets are generated by dividing the retrieved dataset based on a selected time series. A nucleus is derived for each of the time-ordered dataset. Furthermore, relevancy and redundancy of each of the plurality of time-ordered datasets is evaluated. The present invention, further computes the complexity and noise associated with each of the time-ordered datasets. Finally, a DIQ value for each time-ordered dataset is evaluated as a function of relevancy, complexity, noise and redundancy.
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公开(公告)号：US11087153B2
公开(公告)日：2021-08-10
申请号：US16559104
申请日：2019-09-03
Inventor： Kumar Vishal , Arvind Channarayapatna Srinivasa , Ritesh Mishra , Venugopal Gundimeda
Abstract: The present disclosure is directed to a traffic light recognition system and method for advanced driver assistance systems (ADAS) and robust to variations in illumination, partial occlusion, climate, shape and angle at which traffic light is viewed. The solution performs a real time recognition of traffic light by detecting the region of interest, where extracting the region of interest is achieved by projecting the sequence of frames into a kernel space, binarizing the linearly separated sequence of frames, identifying and classifying the region of interest as a candidate representative of traffic light. With the aforesaid combination of techniques used, traffic light can be conveniently recognized from amidst closely similar appearing objects such as vehicle headlights, tail or rear lights, lamp posts, reflections, street lights etc. with enhanced accuracy in real time.
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