Abstract: A process for optimizing loss functions includes progressively building better sets of parameters for loss functions represented as multivariate Taylor expansions in accordance with an iterative process. The optimization process is built upon CMA-ES. At each generation (i.e., each CMA-ES iteration), a new set of candidate parameter vectors is sampled. These candidate parameter vectors are sampled from a multivariate Gaussian distribution representation that is modeled by the CMA-ES covariance matrix and the current mean vector. The candidates are then each evaluated by training a model (neural network) using the candidates and determining a fitness value for each candidate against a validation data set.

Abstract: The present invention provides for generating in real-time synthetic test data comprising large volumes of data records associated with an entity for testing data processing applications. In operation, the present invention provides for generating a data structure, where the data structure is populated with predefined segments based on selected operating field. Each predefined segment comprises one or more sub-segments. The data values for each sub-segment is generated based on one or more parameters. Further, the present invention provides for evaluating combinations between data values of one or more sub-segments of one or more predefined segments. Yet further, synthetic test data comprising a plurality of data records is generated based on generated data structure and evaluated combinations, where each data record is populated with one or more sub-segments of the data structure, arranged within each data record and populated with data values based on the one or more parameters.

Abstract: System and method for prevention of counterfeiting of products using combination of packaging codes and blockchain technology is provided. Hash of a first product code is generated by encrypting scanned product data associated with a product received. Second product code is generated by encrypting first product code for combining with distinct first product code Quick Response (QR) part values. Hash of a third product code is generated by combining hash of first product code and hash of second product code. Hash of third product code is divided into a hash of a first sub-code and a hash of a second sub-code. Lastly, a comparison of a scanned third product code placed on the product is performed with requested user ID, generated hash of first product code, second product code and hash of third product code to ascertain a match therebetween for preventing counterfeiting of the product.

Abstract: An evolutionary AutoML framework called LEAF optimizes hyperparameters, network architectures and the size of the network. LEAF makes use of both evolutionary algorithms (EAs) and distributed computing frameworks. A multiobjective evolutionary algorithm is used to maximize the performance and minimize the complexity of the evolved networks simultaneously by calculating the Pareto front given a group of individuals that have been evaluated for multiple objectives.

Abstract: A system and method for developing unified digital platform based virtual power banks is provided. A second data type is derived by analyzing record types. The record types are obtained from the first data type received from multiple sources. Virtual power banks are generated by employing the first and second data types fetched from database. Dynamic actionable items relating to the virtual power banks are generated from the first data type and the second data type. One or more variables are identified that correspond to different types of dynamic actionable items for categorizing the dynamic actionable items based on the identified variables. Lastly, optimization operations are performed on values of each of the identified variables to obtain an optimized final weightage value of the virtual power banks, accessed via a unified digital platform, based on which one or more operational parameters associated with the virtual power banks are determined.

Abstract: A computing architecture includes a continuous property record (CPR) mass asset model. The CPR mass asset model includes a retirement unit field, an asset location field, and a vintage field for each mass asset. The retirement unit field stores an identifier of the mass asset, the asset location field storing a region of installation of the mass asset, and the vintage field storing a date of the mass asset. The CPR asset model is a wrapper for a corresponding master data structure of an existing asset system. The computing architecture further includes a retirement ledger for storing a postings for the mass assets. The retirement ledger stores at least one line for each transaction using the mass assets. The computing architecture further includes CPR unitization and retirement engine for adding lines to the retirement ledger.

Abstract: 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.

Abstract: The present invention provides for generating high volumes of synthetic data records for testing data processing applications associated with one or more operating fields, such as healthcare without using any confidential Information. In operation, the present invention provides for retrieving a predefined dataset. Further, the present invention provides for extracting data values associated with selected relevant data fields from the retrieved predefined dataset. Furthermore, the present invention provides for defining rules for generating data values of specific data fields out of the selected relevant data fields. Yet further, the present invention provides for evaluating a number of possible data records. Yet further, the present invention provides for generating evaluated number of synthetic data records using a predefined file format based on the extracted data values and the defined rules.

Abstract: The present invention provides for a system and a method for implementing artificial intelligence-based optimised data stewardship. The system comprises a memory for storing program instructions, a processor executing instructions stored in the memory and a digital data stewardship engine executed by the processor. One or more events are identified based on nature of the events and a sequence is determined for invoking one or more units of the digital data stewardship engine based on the identified event. Machine learning-based intelligent analysis is performed on additional information obtained through third-party websites associated with the identified event. Rules are applied on the results of the intelligent analysis for augmenting the results as per pre-defined requirements and outcome generated based on application of rules are delivered as an executable file.

Abstract: User-driven exploration functionality, referred to herein as a Scratchpad, is a post-learning extension for machine learning systems. For example, in ESP, consisting of the Predictor (a surrogate model of the domain) and Prescriptor (a solution generator model), the Scratchpad allows the user to modify the suggestions of the Prescriptor, and evaluate each such modification interactively with the Predictor. Thus, the Scratchpad makes it possible for the human expert and the AI to work together in designing better solutions. This interactive exploration also allows the user to conclude that the solutions derived in this process are the best found, making the process trustworthy and transparent to the user.

Abstract: A domain-independent problem-solving system and process addresses domain-specific problems with varying dimensionality and complexity, solving different problems with little or no hyperparameter tuning, and adapting to changes in the domain, thus implementing lifelong learning.

Abstract: A transmitter device for a secure communication based on quantum cryptography, the transmitter device comprises a transmitter optical communication module for transmitting light pulses from the transmitter device to a receiver device, and the transmitter optical communication module enables exchange of a quantum key between the transmitter device and the receiver device. The transmitter device comprises transmitter data communication module for exchanging data between the transmitter device and the receiver device, the data is encrypted by the quantum key thereby ensuring a secure communication between the transmitter device and the receiver device. The transmitter device further contains a status display on a front side of the transmitter device for displaying status of the secure communication between the transmitter device and the receiver device.

Abstract: 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.

Abstract: A system and method for generating a modernization sequence for application modernization is provided. The present invention provides for generating a database of hierarchies between a plurality of technology stacks based on analysis of historic modernization data and user inputs. Further, the present invention provides for evaluating in real-time an optimal sequence for implementing modernization of two or more technologies associated with the application based on the database. A hierarchy between each of the technology stacks corresponding to the two or more technologies is derived based on the database, and the technology stacks are arranged in a chronological order based on the derived hierarchy. The modernization sequence of the two or more technologies is same as the chronological order of their corresponding technology stacks.

Abstract: A multi-task (MTL) process is adapted to the single-task learning (STL) case, i.e., when only a single task is available for training. The process is formalized as pseudo-task augmentation (PTA), in which a single task has multiple distinct decoders projecting the output of the shared structure to task predictions. By training the shared structure to solve the same problem in multiple ways, PTA simulates the effect of training towards distinct but closely-related tasks drawn from the same universe. Training dynamics with multiple pseudo-tasks strictly subsumes training with just one, and a class of algorithms is introduced for controlling pseudo-tasks in practice.

Abstract: A genetic loss function optimization (hereafter “GLO”) process uses a genetic algorithm to construct candidate loss functions as trees. The process takes the best candidate loss functions from this set and optimizes the coefficients thereof using covariance-matrix adaptation evolutionary strategy (hereafter “CMA-ES”), resulting in new loss functions showing substantial improvements in accuracy, convergence speed, and data requirements.

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.

Abstract: A computer-implemented method optimizing genetic algorithms for finding solutions to a provided problem is described. The method implements a multi-arm bandit algorithm to determine performance scores for candidate individuals from a candidate pool in dependence on successes and failures of the one or more candidates. The method evolves the candidate individuals in the candidate pool by performing evolution steps including: determining a fitness score for each of the candidate individuals in the candidate pool in dependence on the performance scores for the candidate individuals, discarding candidate individuals from the candidate pool in dependence upon their assigned performance measure, and adding, to the candidate pool, a new candidate individual procreated from candidate individuals remaining in the candidate pool after the discarding of the candidate individuals.

Abstract: The present invention provides for building a knowledgebase of dependencies between Configuration Items(CIs) associated with IT computing environment. In operation, the present invention provides for mapping a plurality of Configuration Items(CI) with respective one or more actions. The present invention further provides for tracking and capturing of one or more actions performed on one or more CIs in relation to resolving an activity related to a reported CI. Further, the present invention provides for identifying dependencies between one or more CIs and the reported CI based on the captured one or more actions. Furthermore, the present invention provides for building a knowledgebase of dependencies between CIs of the computing environment based on the identified dependencies between one or more CIs and the reported CI. Yet further, the present invention provides for generating visual representations of dependencies between CIs.

Abstract: The present invention provides for a system and a method for optimized data extraction of different document types. First digitised data is extracted from ingested documents based on extraction rules and is classified into first classified data based on pre-defined rules. Confidence score is assigned to first classified data based on comparison of first classified data with pre-defined data. A second digitised data is extracted from classified document types corresponding to first classified data via a tool selected from multiple integrated tools based on extraction rules. An extraction score is determined for second digitised data. Classified document types are validated based on pre-defined requirements. In the event the pre-determined requirements are met the confidence score and the extraction score are compared with pre-defined parameters. If the result is above a pre-determined threshold the second digitized data is transmitted as executable files to applications for execution.