Tata Consultancy Services Patente

Performance and lifespan of batteries deteriorate with time due to various factors. Existing systems for battery management use different approaches for the battery management, and also rely on static value of parameters for State of Health (SOH) and Remaining Useful Life (RUL) estimation, thereby failing to consider current condition of the battery. The disclosure herein generally relates to battery management, and, more particularly, to a method and system for online battery management involving real-time estimation of State of Health (SOH) and Remaining Useful Life (RUL) of a battery, based on real-time data collected from the battery. The system determines state of the battery as one of charging, discharging, and rest. Further, corresponding to the determined state, the system determines values of one or more parameters, and processes the determined values with a battery performance model for online determination of the SOH and RUL.

This disclosure relates to field of cryptography and digital signatures. The constant theft of cryptocurrencies is due to compromise of the secret signing key inherently stored in a single location. Also, one of challenges in the existing ECDSA signature is single point failure, wherein the signing key (private key) is prone to theft. The disclosed technique overcomes the challenging in the existing techniques by party distributed signature that ensures the safety of the private key. The disclosed techniques slits the key in two parts and saves at two different locations/machines. Further based on a ECDSA based technique, the digital signature is obtained securely using several steps that includes generation of first two parts of digital signature at one party, generation of the second two parts of digital signature at second party, finally decrypting a complete digital signature at the first party.

Zusammenfassung wird geladen …

Owing to their stochastic nature, Distributed Energy Resources (DERs) are more suited to participate in short-term or intraday electricity markets. However, it is very difficult for an asset owner to manage their operation when interacting with markets and create operation schedules. Present disclosure provides systems and methods that for the trades/bids placed earlier to be corrected based on the revised forecasts of demand and generation in the DER pool. The system models an optimal bidding problem of aggregators in an intraday market as a mixed-integer non-linear programming (MINLP) problem. The MINLP problem is converted to an NLP problem by an optimization model and integer variables are relaxed to solve the NLP problem and obtain (i) an optimal intraday operating schedule for one or more DERs, and (ii) an intraday bid associated with the DERs for a plurality of delivery slots to be traded in an intraday market.

Zusammenfassung wird geladen …

Zusammenfassung wird geladen …

Zusammenfassung wird geladen …

Zusammenfassung wird geladen …

Zusammenfassung wird geladen …

Zusammenfassung wird geladen …

Zusammenfassung wird geladen …

Zusammenfassung wird geladen …

Zusammenfassung wird geladen …

Zusammenfassung wird geladen …

Zusammenfassung wird geladen …

Zusammenfassung wird geladen …

Zusammenfassung wird geladen …

Zusammenfassung wird geladen …

Zusammenfassung wird geladen …

This disclosure relates to a system and method for custom made medical devices life cycle management. the life cycle management of the medical devices include tracking of material and procedure to be used in additive manufacturing of the medical device and analyzing design risk as per the raw material and the design specification. Further, it includes to identify potential hazards based upon the materials, their interactions and effect on process to be followed. An artificial intelligence (AI) enabled model is trained with one or more sample datasets pertaining to a plurality of materials to be used in the additive manufacturing to audit design, to determine materials to be used, and to generate a unique code to be used to label the manufactured medical device. A smart contract of blockchain is configured to record received input and update with new points for regulatory compliance.

Zusammenfassung wird geladen …

Zusammenfassung wird geladen …

Zusammenfassung wird geladen …

Conventional systems fail to recommend covenants in processes at financial institutions, and such systems rely on an underwriter who decides the covenants based on his experience without considering experience of other underwriters and similar type of customers historical records. Embodiments of the present disclosure provides systems and methods that implement data exploration analysis on received input data for categorizing covenants into various categories and training various machine learning models. The trained machine learning models are applied on test data for predicting covenants along with a probability score (e.g., also referred as optimized, unbiased set of covenants). The predicted covenants of various categories are then sorted to obtain a prioritized list of covenants for recommendation.

State of art techniques for color regeneration are complex and fail to provide color control. Embodiments of the present disclosure provide a method and system for generating color variants for fashion apparels by providing a Fashion Apparel Regeneration - Generative Adversarial Network (FAR-GAN) to generate color variants of the fashion apparels. The FAR-GAN utilizes a two-step encoding process to encapsulate both an input image and an edge-map information along with a target color embedding branch to manipulate the color information present in the fashion apparel present in the input image that is to be changed to a desired target color. Furthermore, the color and structural information is disentangled by controlling them using a color consistency loss. The FAR-GAN can be trained end-to-end without incorporating complex multi-step process.

A method and a system for capacitive touch panel based bio-signal measurement sense a change in raw capacitance value of a capacitive touch panel. However, unlike existing methods and systems that directly utilize the raw signal for bio-signal measurements, a normalized signal is derived by normalizing a raw signal corresponding to the change in raw capacitance of the capacitive touch panel. The normalization considers interrelationships between a plurality of variables that affect the raw capacitance value such as a set of device specific parameters associated with the capacitive touch panel of the device, a set of ethnographic parameters, and metadata associated with the subject. Thus, higher accuracy in bio-signal measurement using capacitive touch panel based devices by personalizing the bio-signal measurements is provided.

Zusammenfassung wird geladen …

Zusammenfassung wird geladen …

Zusammenfassung wird geladen …

Zusammenfassung wird geladen …

Zusammenfassung wird geladen …

Zusammenfassung wird geladen …

Zusammenfassung wird geladen …

Zusammenfassung wird geladen …

Zusammenfassung wird geladen …

Zusammenfassung wird geladen …

Zusammenfassung wird geladen …

Natural language elements are present in both the executable lines and non-executable lines of the code. Rich information hidden within them are often ignored in code analysis as extraction of meaningful insights from its raw form is not straight forward. A system and method extracting natural language elements from an application source code is provided. The disclosure provides a method for performing detailed analytics on the natural language elements, classify those using deep learning networks and create meaningful insights. The system understands the different type of natural language elements, comment patterns present in the application source code and segregates the authentic comments having valuable insights, version comments, data element level comments from other non-value adding comments. The embedded intelligence finally takes care of mapping the extracted natural language elements with the code blocks, thus making it consumable and opening a range of applications in domain contextualization, code documentation and maintenance.

Zusammenfassung wird geladen …

Zusammenfassung wird geladen …