Tata Consultancy Services Limited

Sonam Yashpal Sharma

Mahesh M Kshirsagar

Shailesh Shankar Deshpande

Balamuralidhar Purushothaman

Kamlesh Mhashilkar

Sanjeev Manchanda

Shivani Nigam

Nihar Ranjan Sahoo

Ajeet Phansalkar

Shashwat Shahi

Gargi Uday Kulkarni

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.

Method and system for sustainable development goal (SDG) performance assessment of an enterprise

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.

Weld quality inspection with domain knowledge infused adaptive-network-based fuzzy inference system

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.

Method and system for extracting contextual information from a knowledge base

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Mumbai, India

Sonam Yashpal Sharma