Abstract: A system for generating at least a question, similar to a given question and generating their step-by-step solution is disclosed. The system includes a template creation module for creating a template representing the given question, wherein the template is created by implementing NLP techniques and performing steps of identification of one or more entities and recognition of relationships between them, identification of one or more attributes of each of the one or more entities, and identification of one or more values of each of the identified attributes. The system includes a similar question generation module for generating at least one question similar to the given question, using the template created and by replacing at least one value of at least one attribute in the template. The system also includes a solution generation module for generating the step-by-step solution for the given question and the at least one similar question.

Abstract: Disclosed herein a neurosurgical simulator for training of various tasks involved in Endoscopic Endonasal Transsphenoidal Surgery, composed of a human head model comprising an anterior portion including a nose part, and a posterior portion detachably mounted on an inclined base part; a plurality of apertures on the nose part for insertion of an endoscope and an instrument for manipulation; said inclined base part placed at an inclination to mimic a patient position during endo-nasal surgery; wherein said base part comprises a protruded platform having slots to create male-female connection with corresponding a plurality of protrusions provided under one or more activity plates; wherein said activity plates are so designed to train various tasks including pick-place, drilling, incising, punching/grasping and precision movements around the anatomical structures.

Abstract: A system for generating at least a question, similar to a given question and generating their step-by-step solution is disclosed. The system includes a template creation module for creating a template representing the given question, wherein the template is created by implementing NLP techniques and performing steps of identification of one or more entities and recognition of relationships between them, identification of one or more attributes of each of the one or more entities, and identification of one or more values of each of the identified attributes. The system includes a similar question generation module for generating at least one question similar to the given question, using the template created and by replacing at least one value of at least one attribute in the template. The system also includes a solution generation module for generating the step-by-step solution for the given question and the at least one similar question.

Abstract: A method and system to conduct an audit for control and maintain the quality of a digital facility. The system executes instructions to causes one or more processors to perform a method. The method includes a first step of collecting a first set of data and a second step of creating one or more tasks. The method includes a third step of receiving a second set of data. The method includes a fourth step of analyzing the first set of data and the second set of data and a fifth step of assigning the one or more tasks. The method includes a sixth step of obtaining the third set of data. The method includes a seventh step of determining the deviation in the first set of data and the third set of data and an eighth step of rating a plurality of auditors.

Abstract: A method and system for quality control of a digital facility based on machine learning. The system connects a plurality of elements associated with a plurality of regions of the digital facility. The system allocates a unique identity to the plurality of elements. The system receives a set of data associated with the plurality of regions. The system collects a set of data associated with a plurality of micro descriptors. The system processes the second set of data to discover a plurality of patterns. The system predicts issues associated with the plurality of elements. The system assigns high severity issue to the one or more severe issues. The system stores information associated with the digital facility. The system updates the patterns associated with the plurality of elements. The system recommends characteristic parameters to the plurality of elements. The system notifies manpower associated with the digital facility.

Abstract: A method and system for quality control of a facility based on Internet of things. The system obtains data of the facility from plurality of architectural sources. The system creates a digital replica of the facility and defines plurality of control point levels for each region of the plurality of regions. The system allocates plurality of smart devices based on plurality of micro-descriptors. The system collects data associated with the facility and deciphers the data into one or more matrix. The system analyzes data with the pre-defined standard quality matrix in real time. The system assigns a degree of severity of the identified one or more issues. The system apprises one or more workforces associated with the facility to resolve the one or more issues including high degree of severity and the plurality of smart devices to take action to resolve the one or more issues.

Abstract: A system for quality control of a facility based on feedback from multiple sources. The system receives data of the facility from plurality of data sources. The system creates one or more digital replica of the facility and classifies each region of the plurality of regions into plurality of checkpoint levels. The system assigns a plurality of micro-descriptors to the last level of the plurality of checkpoint levels and collects a feedback for the plurality of micro-descriptors from plurality of sources. The system collects data associated with the facility including facility-specific matrix and manpower specific matrix. The system maps the facility specific matrix with pre-defined quality specific matrix and evaluates deviation of the mapped data to identify one or more issues associated with the facility. The system assigns degree of severity to the identified issue and alerts if degree of severity is high.