Abstract: Embodiments herein provide a method and system for a hyperspectral artificial vision for machines. The system receives a hyperspectral signal of a target material as an input to a neural network model. The system initializes by selecting the number of primitive layers to be used. The system iteratively cycles through all training data (pixels) and updating weights for each unsuccessful material class prediction. Model with two primitives serves as baseline, after which the system adds another primitive layer and repeats the training procedure. The system keeps repeating these processes until obtains convergence. Where the system come to a halt, the system obtains the optimal number of primitives for the given materials. The generated new color pixel is used as a discriminator to aid in locating the target material. The new artificial color is a mixture of weighted chromatic primitives which are optimized for sensitivity/(Spectral Response Functions) SRFs.

Abstract: Quality of weld images in with bad lighting condition and specific image color formats add constraints to existing automated weld inspection systems. Embodiments herein provide a method and system based on Domain Knowledge Infused Adaptive-Network-based Fuzzy Inference System (DKI-ANFIS) for weld quality inspection. The DKI-ANFIS inspects the quality of weld joint using domain driven quality inspection techniques. A segmentation algorithm is used to extract the weld joint in form of fractals followed by an unsupervised technique to extract useful geometrical features from the fractals. These geometrical features are used for quality index generation. A weld inspection model comprising the DKI-ANFIS is used for determining the quality of the weld joint. DKI-ANFIS modifies layers of ANFIS by infusing layer of domain knowledge to give better results even if there is a class imbalance in the data or the data is skewed or there is only a short corpus of data available.

Abstract: Assessing sustainability performance of an enterprise is a challenging task. Embodiments of present disclosure provide a method and system for SDG performance assessment of an enterprise with a conceptually simpler data model and processing pipeline. Enterprise data collected from hard and soft sensors is mapped to appropriate indicators of the SDGs. Further, a semantic network is constructed with nodes corresponding to each indicator and edges connecting nodes belonging to same SDG. Each node of the semantic network is further linked to a first layer of a neuro fuzzy network which calculates degree of impact of the indicator on Social, Economic and Environment values. Output of the first layer activates second layer of the neuro fuzzy network which determines BBV scores indicating whether the indicator is a burden, benefit, or vulnerability. The BBV scores are transformed to a colour space to generate a colour that indicates SDG performance of the enterprise.

Abstract: This disclosure relates generally to system and method for determining explainability of machine predicted decisions. Typical explainable AI (XAI) solutions are limited by type of data processed, such as structured, semi-structured and unstructured text. In addition, due to limited automation of the process of explainability, typical systems are cumbersome and time-consuming. The system and method provide an end to end solution for automating the determination of explainability of machine predicted decisions. The XAI process output an absolute relevance score indicative of relevance of the features associated with the prediction which is indicative of percentage relevance/contribution of individual feature. The system further computes relative relevance score of the features by adding up all the features and calculating how much each individual feature is contributing to the total score. The relative relevance scores are utilized for determining explainability of decisions of the prediction.

Abstract: In medical writing, manual process of creating, updating and maintaining documents is expensive, time consuming. This disclosure provides a method of an automatic medical document writing by receiving, a plurality of input documents as an input; processing, the inputted plurality of documents by extracting into an at least one section to generate a list of sections; classifying, at least one category corresponding to the at least one section to generate a summary set; generating, at least one of a local context and a global context based on the summary set; parsing, at least one sentence based on the generated local context and global context to generate at least one sequence of the plurality of sentences; processing, the at least one sequence of the plurality of sentence to generate a queue of the at least one sequence; validating, the queue of the at least one sequence to obtain a combined summary set.

Abstract: The problem of ever-increasing huge volume of unstructured data, mainly documents, and within that the scanned documents, needs to have a solution to expedite the overall turnaround time in document centric business processing. Majority of these documents often do not strictly follow a specific format or a template, and creating a generic OCR solution, which would work on any kind of document format is needed to enhance overall efficacy of processes. Embodiments of the present disclosure provide system and method that extract tabular and text information from scanned documents. More specifically, method and system are provided to extract user filled tabular data, textual information, selected radio-buttons and checked checkboxes, stamps, barcodes from scanned copies of any filled form with or without any template being pre-defined or without any prior knowledge about format of input forms. The system converts extracted information in a structured form for further for analytics and reporting.

Abstract: This disclosure relates generally to method and system for extracting contextual information from a knowledge base. The method receives a user query comprising a request to extract contextual information from the user query. Further, the user query is analyzed based on a plurality of predefined parameters to determine sufficiency of information comprised in the user query. The received user query identifies relevant sources of the structured data, the unstructured data or the semi-structured data storage repositories. The user query is processed using a fine grain approach, where a dictionary of one or more keywords with weights are created through the domain ontology builder from the one or more knowledge articles. Furthermore, an appropriate contextual information related to the user query is extracted using the fine grain approach, based on the knowledge articles associated with the trained knowledge base comprising information required by the user query extracted from the knowledge articles.

Abstract: In medical writing, manual process of creating, updating and maintaining documents is expensive, time consuming. This disclosure provides a method of an automatic medical document writing by receiving, a plurality of input documents as an input; processing, the inputted plurality of documents by extracting into an at least one section to generate a list of sections; classifying, at least one category corresponding to the at least one section to generate a summary set; generating, at least one of a local context and a global context based on the summary set; parsing, at least one sentence based on the generated local context and global context to generate at least one sequence of the plurality of sentences; processing, the at least one sequence of the plurality of sentence to generate a queue of the at least one sequence; validating, the queue of the at least one sequence to obtain a combined summary set.

Abstract: Method and system for enabling dynamic capacity planning are disclosed. In an embodiment, a plurality of operational inputs are configured to forecast a demand volume and generate a dynamic capacity planning schedule. For example, said plurality of operational inputs include raw data received from a server. Further, historical data is processed based on said plurality of operational inputs to create a plurality of contextual data elements. Furthermore, said demand volume is forecasted and said dynamic capacity planning schedule is generated using at least a part of the historical data and a current capacity planning requirement, said current capacity planning requirement is being generated dynamically by said server. In addition, said dynamic capacity planning schedule is rendered based on said forecasted demand volume and said rendered dynamic capacity planning schedule is clustered into a plurality of work reports associated with said plurality of contextual data elements.

Abstract: A system and a method for process transaction visibility of one or more steps in a process lifecycle. The method includes identifying a current status of one or more process transactions at a first step of a process lifecycle and determining a change in the status of the one or more process transactions at the first step based the complete of a milestone of the one or more process transaction at the first step. A one or more Key Performance Indicators (KPIs) information is calculated for the current status and the changed status of the one or more process transactions to generate a KPIs report. A unified view of the current status and changed status of the one or more process transactions is displayed on a digital dashboard.

Abstract: This disclosure relates generally to transaction processing, and more particularly to method and system for transaction processing in an application. In one embodiment, the method includes facilitating selection of an overlay application corresponding to the application. The application includes at least one window having a plurality of fields and is rendered in a first UI. At least one field of the plurality of fields is masked to obtain at least one masked field in the first UI. A second UI corresponding to the at least one window is rendered. The second UI is associated with the overlay application and includes at least one field blank field corresponding to the at least one field masked field in the first UI. Entering data is enabled in the at least one blank field in the second UI, and the data entered is compared with a prepopulated data to determine validity of the transaction.

Abstract: Disclosed is a system and method for cross enterprise collaboration for processing a transaction request. The method includes a mechanism for collaboration to resolve context specific tasks in a structured manner requiring inputs from various stakeholders situated in different enterprises. The metadata associated with each of the activities in the workflow is collected to create a workflow. The method further allows the role-based users to extend the workflow by authoring customized activities and share context specific information and artifacts. The method includes memory efficient version of doubly linked list using one address field for every node to process one or more transaction requests at a given point of time.

Abstract: The present disclosure in particular relates to data processing, and more particularly, to systems and methods for identifying and extracting an informative segment from data objects. In one embodiment, a system for facilitating identification of an informative segment from a data is provided. The system includes one or more processors; and a memory storing processor-executable instructions comprising instructions to generate a customized search query based on one or more input parameters, process the data to obtain a plurality of machine-readable data objects, obtain one or more approximate results corresponding to the informative segment based on the customize search query and the plurality of data objects, validate the one or more approximate results based on a comparison of the one or more approximate results and the data, and provide the validated one or more approximate result to identify the informative segment.

Abstract: A system and a method for process transaction visibility of one or more steps in a process lifecycle. The method includes identifying a current status of one or more process transaction at a first step of a process lifecycle and determining a change in the status of the one or more process transaction at the first step based the complete of a milestone of the one or more process transaction at the first step. A one or more Key Performance Indicators (KPIs) information is calculated for the current status and the changed status of the process transaction to generate a KPIs report. A unified view of the current status and changed status of the process transaction is displayed on a digital dashboard.

Abstract: This disclosure relates generally to transaction processing, and more particularly to method and system for transaction processing in an application. In one embodiment, the method includes facilitating selection of an overlay application corresponding to the application. The application includes at least one window having a plurality of fields and is rendered in a first UI. At least one field of the plurality of fields is masked to obtain at least one masked field in the first UI. A second UI corresponding to the at least one window is rendered. The second UI is associated with the overlay application and includes at least one field blank field corresponding to the at least one field masked field in the first UI. Entering data is enabled in the at least one blank field in the second UI, and the data entered is compared with a prepopulated data to determine validity of the transaction.

Abstract: Method and system for enabling dynamic capacity planning are disclosed. In an embodiment, a plurality of operational inputs are configured to forecast a demand volume and generate a dynamic capacity planning schedule. For example, said plurality of operational inputs include raw data received from a server. Further, historical data is processed based on said plurality of operational inputs to create a plurality of contextual data elements. Furthermore, said demand volume is forecasted and said dynamic capacity planning schedule is generated using at least a part of the historical data and a current capacity planning requirement, said current, capacity planning requirement is being generated dynamically by said server. In addition, said dynamic capacity planning schedule is rendered based on said forecasted demand volume and said rendered dynamic capacity planning schedule is clustered into a plurality of work reports associated with said plurality of contextual data elements.

Abstract: Disclosed is a system and method for cross enterprise collaboration for processing a transaction request. The method includes a mechanism for collaboration to resolve context specific tasks in a structured manner requiring inputs from various stakeholders situated in different enterprises. The metadata associated with each of the activities in the workflow is collected to create a workflow. The method further allows the role-based users to extend the workflow by authoring customized activities and share context specific information and artifacts. The method includes memory efficient version of doubly linked list using one address field for every node to process one or more transaction requests at a given point of time.

Abstract: Disclosed is a system and method for processing a transaction. The method comprises receiving an input data from a user. The input data is associated with the transaction. The method further comprises creating a decision tree or a decision table based upon the input data and pre-defined rules. The decision tree comprises a parent node and a child node. The parent node and the child node comprise a first question and a second question respectively presented to the user. The decision table comprises a plurality of criteria/conditions being presented to the user. For each criteria/condition, a conditional response is received from the user. The method further comprises processing the transaction by identifying a solution, stored in a database, based on the decision tree or the decision table.

Abstract: Disclosed is a method and system for classifying a plurality of customer accounts based on a recoverable amount from a customer account. The method includes receiving historical data of the customer account and a user input indicating a selection of a predictive analytics algorithm from a set of predictive analytics algorithms, and building a predictive data model by executing the predictive analytics algorithm on the historical data. The building includes computing a contact index for the customer account and a payment index for the customer account. The building further includes computing a recoverability index based on the contact index, the payment index, and the outstanding amount. The recoverability index denotes the recoverable amount. The method further includes classifying the customer account based on the recoverability index.

Abstract: The present disclosure in particular relates to data processing, and more particularly, to systems and methods for identifying and extracting an informative segment from data objects. In one embodiment, a system for facilitating identification of an informative segment from a data is provided. The system includes one or more processors; and a memory storing processor-executable instructions comprising instructions to generate a customized search query based on one or more input parameters, process the data to obtain a plurality of machine-readable data objects, obtain one or more approximate results corresponding to the informative segment based on the customize search query and the plurality of data objects, validate the one or more approximate results based on a comparison of the one or more approximate results and the data, and provide the validated one or more approximate result to identify the informative segment.