Tata Consultancy Services Patente

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With the growing use of large-scale datasets containing participants' genomics and clinical data for research and studies purposes, it is important to ensure the privacy of the participants by generating a secure representation of genome data observations. Embodiments herein provide a system and method to perform DNA analysis on an encrypted genome without the need for decryption and to ensure users' genome privacy. Herein, a stream of input genome is divided into chunks called sketches, where each k-mer in the sketch is hashed to get a sampling level and a counter value for the k-mer in the sketch. A privacy-enhancing technique is designed over the representations using Fully Homomorphic Encryption (FHE). Genomic data is analyzed with identified efficient algorithms for real-world deployment in the encrypted domain.

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Amyloid deposition is considered a viable biomarker for Alzheimer's disease which is expensive and less used modality to study amyloid spatial distribution in brain. The present disclosure addresses problems of conventional approaches which exhibit trade-off between performance and mode collapse. This disclosure provides a system and method for subject-specific amyloid position emission tomography (PET) translation using conditioned diffusion-based generative model. The present disclosure discloses an architecture for synthesizing subject-specific amyloid images with a diffusion model. First effectiveness of a relationship between Fluorodeoxyglucose (FDG) and amyloid PET images is identified. Further, a framework is provided to synthesize Amyloid PET by utilizing its connection to FDG PET of same subject and cross-subject trends in amyloid deposition by incorporating age, gender and disease status information in learning process. In the other words, a diffusion model inspired image translation is provided to synthesize Amyloid PET from FDG PET and cross-subject amyloid deposition patterns.

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This disclosure relates generally to method and system for providing data privacy in service operations. Identifying risk arising from processing of user request in service operations is time consuming and monitoring insider threats is a difficult task. The method includes receiving a user request for a service comprising a plurality of sensitive attributes and further a vulnerability rating is assigned to each sensitive attribute. To mitigate the risk, the method estimates a disclosure proportion for the plurality of sensitive attributes and a masking operation is performed. Further, a sensitivity score is computed to allocate the user request to an agent associated with an agent registry with enabled data privacy and minimal data exposure. The agent is monitored by computing an agent mis-usability score to assess an insider threat risk. Additionally, a feedback alert is notified to autotune the plurality of privacy settings.

Electrocardiography (ECG) signals contain important markers for Coronary Heart Disease (CHD). State of the art systems and methods rely on clinically available multi-lead ECG for CHD classification which is not cost effective. Moreover the state of the art methods are applied on digital ECG time series data only. Also, discriminative HRV markers are not often present in short ECG recordings necessitating long hours of ECG data to analyze. In accordance with the present disclosure, systems and methods described hereinafter extract ECG time series from ECG images obtained from commercially available low-cost single lead ECG devices through a combination of image and signal processing steps including Histogram analysis, Morphological operation-thinning, Extraction of lines, Extraction of Reference Pulse, Extraction of ECG and interpolating missing data. Further, domain independent statistical features such as self-similarity of raw ECG time series and average Maharaj's distance along with domain specific features are used for classifying CHD.

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Currently solutions for early detection of failures in manufacturing utilize predefined threshold levels of the process variables associated with equipment in manufacturing unit/industry plants. The pre-defined threshold and levels thereof are compared with the real values obtained from the manufacturing unit to check behavior of process variables (also referred as 'process parameters') and thus are prone to error. The present disclosure provides systems and method for predicting early warning of operating mode of equipment operating in industry plants which is based on transforming conditions on process parameters into conditions on corresponding fuzzy indices based on their thresholds. The fuzzy indices (concordance index, discordance index) of individual conditions are combined into a composite fuzzy index (composite index or degree of credibility) that describes the failure scenario in the process parameter space. A fuzzy logic-based detection is useful for detecting a failure mode early and providing alerts to operators for necessary action.

Unaddressed technical problem is how to make the window manager select and update the appropriate visual design given the Just-In-Time constraint to optimize Profit/Economic Goal for a Basic Emergent User and not have a locking/permanent binding on a particular Socio Economic Cohort (SEC) or Contract Management System Companies (CMSCs). A method and system is disclosed that provides interface layout to discover and optimize economics of information exchange of digitally virtualized physical space for a Basic Emergent User (BEU). A correlation score is determined based on correlation between i) the expected profit range provided by the BEU indicating the tolerance around the SP(selling price) and ii) the buying price(BP) and the tolerance specified by the SEC or the CMSC to identify a best match for the BEU based on goal provided by the BEU in terms of expected profit range and corresponding time range within which it is to be achieved.

A computer implement format preservation based masking system and method is provided. The system obtains a first set of letters and a private key, and encrypts the first set of letters to obtain an encrypted letters list using the first set and private key. The encrypted letters list comprises a set of encrypted letters. A dynamic map is generated based on the encrypted letters, which includes one or more keys, each key being specific to a letter in the first set letters. A position of each of maskable letters in a second set of letters is calculated using the dynamic map, and performs masking of the maskable letters based on the position of each of the maskable letters to obtain masked data using the dynamic map.

The disclosure generally relates to methods and systems for crop damage assessment using semantic reasoning. Conventional techniques using only specific data either individually or in a combination may result in bias and may not accurately estimate the crop damage, due to diversity in each of the natural calamities. The present disclosure solves the technical problems in the art using domain ontologies and a semantic reasoning over the spatio-temporal data for the automatic assessment of the crop damage due to the natural calamities. The present disclosure establishes automated crop loss assessment using trigger-based analysis of plurality of sources like satellite-based earth observations, weather observations, social media posts and news articles, for obtaining a spatio-temporal data. Then the spatio-temporal data is reasoned over the domain knowledge graph, using the semantic reasoning technique, for the crop damage assessment.

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Traditional machine learning (ML) based systems used for scene recognition and object recognition have the disadvantage that they require huge quantity of labeled data to generate data models for the purpose of aiding the scene and object recognition. The disclosure herein generally relates to image processing, and, more particularly, to method and system for generating 3D mesh generation using planar and non-planar data. The system extracts planar point cloud and non-planar point cloud from each RGBD image in a sequence of RGBD images fetched as input, and then generates a planar mesh and a non-planar mesh for planar and non-planar objects in the image. A mesh representation is generated by merging the planar mesh and the non-planar mesh. Further, an incremental merging of the mesh representation is performed on the sequence of RGBD images, based on an estimated camera pose information, to generate representation of the scene.

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