System and Method for Optimized Training of a Neural Network Model for Data Extraction

    公开(公告)号:US20240281664A1

    公开(公告)日:2024-08-22

    申请号:US18136985

    申请日:2023-04-20

    IPC分类号: G06N3/09 G06N3/0442

    CPC分类号: G06N3/09 G06N3/0442

    摘要: A system and method for optimized training of a neural network model for data extraction is provided. The present invention provides for generating a pre-determined format type of input document by extracting words from input document along with coordinates corresponding to each word. Further, N-grams are generated by analyzing neighboring words associated with entity text present in predetermined format type of document based on threshold measurement criterion and combining extracted neighboring words in pre-defined order. Further, generated N-grams are compared with coordinates corresponding to words for labelling N-grams with field name. Further, each word in N-gram identified by the field name is tokenized in accordance with location of each of the words relative to named entity (NE) for assigning token marker. Lastly, neural network model is trained based on tokenized words in N-gram identified by token marker. The trained neural network model is implemented for extracting data from documents.

    SYSTEM AND METHOD TO OPTIMIZE A LIGHT EMITTING DIODE POWER ALLOCATION FRAMEWORK

    公开(公告)号:US20240260162A1

    公开(公告)日:2024-08-01

    申请号:US18101739

    申请日:2023-01-26

    摘要: A system 10 to optimize a light emitting diode (LED) power allocation framework within a room is disclosed. The system 10 includes a data receiving subsystem 20, configured to receive parameters corresponding to light emitting diodes (LED), visible light communication (VLC) transmitters and visible light communication (VLC) receivers. The system 10 includes a blockage generalization subsystem 22, configured to identify location and height of one or more detected blockages within the room from the received parameters. The system 10 includes an optimal power allocation subsystem 24, configured to compute a visible light communication (VLC) channel gain for each of the one or more light emitting diodes (LED) with reference to identified location and identified height and configured to optimize the power allocation framework to achieve maximized visible light communication (VLC) data rate based on the computed visible light communication (VLC) channel gain and one or more constraints.

    System and Method for Managing Cloud Deployment Configuration Files and Container Base Images

    公开(公告)号:US20240168744A1

    公开(公告)日:2024-05-23

    申请号:US18095565

    申请日:2023-01-11

    IPC分类号: G06F8/61 G06F8/65 G06F8/75

    CPC分类号: G06F8/63 G06F8/65 G06F8/75

    摘要: A system and a method for managing cloud deployment configuration files and container base images for applications is provided. One or more application source code associated with configuration files and container images of applications are analyzed based on one or more pre-defined rule sets for determining cloud platform best-practice violations associated with the application source code. Further, impact on the application source code due to cloud platform changes is identified based on one or more search sets. Further, one or more remediation actions are executed for rectifying the determined cloud platform best-practice violations associated with the impacted application source code based on one or more remediation types. Base images of the container images are validated to be secure and without vulnerabilities. Lastly, a test run is triggered to determine that the remediation actions have not removed functionalities associated with the application source code.

    SYSTEM AND METHOD FOR IMPROVING CHATBOT TRAINING DATASET

    公开(公告)号:US20220309247A1

    公开(公告)日:2022-09-29

    申请号:US17347773

    申请日:2021-06-15

    摘要: 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.

    System and method for monitoring lab processes and predicting their outcomes

    公开(公告)号:US11449791B2

    公开(公告)日:2022-09-20

    申请号:US16244236

    申请日:2019-01-10

    摘要: A system for monitoring one or more lab processes and predicting their outcomes is provided. The system comprises a data acquisition module configured to acquire at least one of: ambient data and experimental data in real time from one or more lab resources and instruments. The system further comprises a process setup and monitoring module configured to receive the acquired data and facilitate setting-up and monitoring of one or more processes in real time utilizing the received data. The system furthermore comprises an experiment prediction module that is configured to obtain data from the data acquisition module and process setup and monitoring module. The experiment prediction module is further configured to employ one or more machine learning techniques on the obtained data to generate one or more patterns to predict outcomes of the one or more processes conducted in the lab in real time.