Abstract

A system receives a plurality of scientific documents for inclusion in an extended knowledge graph. For each respective scientific document of the plurality of scientific documents, the system classifies the respective scientific document with a theoretical framework of a plurality of theoretical frameworks each comprising terms and principles associated with a particular scientific topic, extracts metainformation of the respective scientific document, structures the metainformation in a document-specific ontology model that further comprises an indication of the theoretical framework, generates a plurality of text chunks from the respective scientific document of a given size, and generates, using a first ML model, one or more concepts from each of the plurality of text chunks. The system generates, using a second ML model, the extended knowledge graph using each of the plurality of text chunks, each concept, and the metainformation, and stores the extended knowledge graph in a graph document database.

IPC Classes  ?

• G06F 16/34 - BrowsingVisualisation therefor
• G06F 16/35 - ClusteringClassification
• G06F 16/36 - Creation of semantic tools, e.g. ontology or thesauri
• G06F 40/20 - Natural language analysis

Abstract

A system receives a user query requesting a testable hypothesis about a scientific topic. The system classifies the user query into a first theoretical framework of a plurality of theoretical frameworks each comprising of terms and principles related to a particular scientific topic. The system generates the testable hypothesis by a first machine learning (ML) model that is configured to: receive as inputs: the user query, the first theoretical framework, and information from a graph document database comprising data associated with scientific documents, generate, as an output, the testable hypothesis that can be evaluated using the first theoretical framework and that does not reiterate a hypothesis or findings from the scientific documents in the graph document database. The system outputs the testable hypothesis via a user interface in response to the user query.

IPC Classes  ?

• G06F 16/332 - Query formulation
• G06F 16/338 - Presentation of query results
• G06F 16/353 - ClusteringClassification into predefined classes

Abstract

A system includes a performance optimization module of an autonomous vehicle configured to: (1) receive a first and second set of real-time parameter values of the autonomous vehicle; (2) identify instability of the autonomous vehicle in response to detecting one or more errors between a control command given by a controller unit to the autonomous vehicle and an execution of the control command by the autonomous vehicle based on the first set of real-time parameter values and the second set of real-time parameter values; (3) generate additional information associated with the autonomous vehicle and an environment in which the autonomous vehicle is driving based on the one or more errors; generate a corrective course of action for reducing a duration needed to drive a given route by the autonomous vehicle; and feed back the additional information and the corrective course of action to the controller unit for execution.

IPC Classes  ?

• B60W 30/02 - Control of vehicle driving stability
• B60W 60/00 - Drive control systems specially adapted for autonomous road vehicles

Abstract

A multi-layer path-planning system and method calculates trajectories for autonomous vehicles using a global planner, a fast local planner, and an optimizing local planner. The calculated trajectories are used to guide the autonomous vehicle along a bounded path between a starting point and a destination.

IPC Classes  ?

• B60W 60/00 - Drive control systems specially adapted for autonomous road vehicles

Abstract

A multi-layer path-planning system and method calculates trajectories for autonomous vehicles using a global planner, a fast local planner, and an optimizing local planner. The calculated trajectories are used to guide the autonomous vehicle along a bounded path between a starting point and a destination.

IPC Classes  ?

• B60W 60/00 - Drive control systems specially adapted for autonomous road vehicles
• G01C 21/34 - Route searchingRoute guidance

Abstract

Systems and methods for conducting a synchronized student-lecturer session on an e-learning server in a computer network. The method includes obtaining a lesson material template from the lecturer computing system; logging a lecturer and one or more students in the e-learning application by verifying respective credentials to access the lesson material template, presenting the lesson material template on a session screen of the e-learning application corresponding to the lecturer and the one or more student users; generating a lecturer session; generating a student session log; tracking the lecturer session log, wherein the lecturer activity as recorded in the lecturer session log is monitored by one or more student users, and tracking the student session log, wherein the student activity as recorded in the student session log is monitored by the lecturer user.

IPC Classes  ?

• G09B 5/02 - Electrically-operated educational appliances with visual presentation of the material to be studied, e.g. using film strip

Abstract

A system and method for optimizing the performance of an autonomous race car in real-time during a race event are disclosed. An autonomous race car controller unit is pre-fed with a first set of initial parameter values and a second set of initial parameter values. A set of sensors is configured for measuring a first and a second set of real-time parameter values after the starting of the race event. A performance optimization module is configured to generate a corrective course by receiving the first and second sets of real-time parameters and detecting the presence of errors between a control command given by the controller unit and its execution.

IPC Classes  ?

• B60W 30/02 - Control of vehicle driving stability
• B60W 60/00 - Drive control systems specially adapted for autonomous road vehicles

Abstract

A multi-layer path-planning system and method calculates trajectories for autonomous vehicles using a global planner, a fast local planner, and an optimizing local planner. The calculated trajectories are used to guide the autonomous vehicle along a bounded path between a starting point and a destination.

IPC Classes  ?

• B60W 60/00 - Drive control systems specially adapted for autonomous road vehicles
• B60W 30/18 - Propelling the vehicle
• B60W 40/064 - Degree of grip
• H04W 4/44 - Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P] for communication between vehicles and infrastructures, e.g. vehicle-to-cloud [V2C] or vehicle-to-home [V2H]

Abstract

A method for the computer-assisted learning of orthography, the method includes executing by a data processing system the steps of retrieving a main set of words from a data storage; retrieving an error data set associated with said main set of words from the data storage and repeatedly executing the steps of selecting a word to prompt the user with, by computing, for each word from the error data set, a statistic measure related to the probability of an error occurring in the word, and selecting the word which has the maximum value of the statistic measure; prompting the user with the word; accepting a user input specifying a sequence of symbols; comparing the user input with the word and updating and storing the error data set.

IPC Classes  ?

• G09B 1/00 - Manually- or mechanically-operated educational appliances using elements forming or bearing symbols, signs, pictures, or the like which are arranged or adapted to be arranged in one or more particular ways

Abstract

updating (17, 18) and storing the error data set.

IPC Classes  ?

• G09B 1/00 - Manually- or mechanically-operated educational appliances using elements forming or bearing symbols, signs, pictures, or the like which are arranged or adapted to be arranged in one or more particular ways

Abstract

A method encodes a word or words. A sequential input string of symbols representing a word or a plurality of words is parsed into segments. A graph is constructed having spatial levels, each level including nodes. The segments of the input string are mapped to the nodes according to the levels and attributes are assigned to the nodes according to the segments, where an entropy of the word or plurality of words is a constant times an entropy of the graph and of the nodal attributes.

IPC Classes  ?

• G09B 5/00 - Electrically-operated educational appliances