Abstract: A computer-implemented system and method for planning recurring events is provided. Event objects for events are stored in a database. A trigger notifying the beginning of an event is received and an event object representing the event is generated in response to the trigger. An event class is associated with a set of parameters and is assigned to the event object. A set of activity data is created for the event object and each activity data includes structured and unstructured data describing an event activity occurred during the event. At least one event object is retrieved from the database as a model and the parameter values of the model event object are displayed. At least one of the parameter values of the model event object is modified and the modification is reflected against other parameter values of the model event object that are dependent on the modified parameter value.

Abstract: Systems and methods providing access control and data privacy/security with decentralized ledger technology are disclosed. To ensure data privacy the decryption or access to data by a non-data owner requires joint orchestration of decentralized system nodes to provide partial decryption components with n-of-x required to fulfill request. Data can be encrypted, and access control policy can be decided including required number of key fragments to fulfill decryption. Access control policies can be stored in the decentralized ledger based system. Key information can be stored in the system in a decentralized manner with partial key fragments encrypted and split among system nodes. An access request can be sent to the system to fetch a data file, without disclosing the requester's identity in the system. The decentralized ledger based system can verify a legitimate request to access the data and denies access to malicious or faulty participants.

Abstract: Detecting passengers traveling through a transit gate, includes transmitting a first beam from a first optical emitter on a side of the transit gate to a first plurality of optical receivers on an opposite side of the transit gate, and transmitting a second beam from a second optical emitter on the opposite side of the transit gate to a second plurality of optical receivers on the side of the transit gate in a direction opposite the direction of the first beam. Transmit intensities are adjusted based on learned patterns or drifts in the receive intensities of light beams. Detection times are reduced based on pairing additional optical receivers with a single optical emitter.

Abstract: Methods and systems for authenticating a short-range communications HCE (Host Card Emulation) application for mobile communications devices. HCE application data can be transmitted to each registered mobile communications device among a group of mobile communications devices for storage of the HCE application data in a non-volatile memory associated with each registered mobile communications device. The HCE application data include a unique identifier, an expiry date, and an authentication key valid only for a user of each registered mobile communications device. The authentication key can then be diversified by the expiry date and the unique identifier so that the authentication key is only usable for a limited amount of time and the unique identifier is only usable for a single mobile communications device.

Abstract: Neural network systems are provided that comprise one or more neural networks. The first neural network can comprise a convolutional neural network (CNN) long short-term memory (LSTM) architecture for receiving a primary data set comprising text messages and output a primary data structure comprising a text pattern-based feature. The second neural network can comprise a CNN architecture for receiving a secondary data sets derived from the primary data set and output a plurality of secondary data structures. The third neural network can combine the data structures to produce a combined data structure, and then process it to produce a categorized data structure comprising the text messages assigned to targets. The primary data set can comprise hate speech and the categorized data structure can comprise target categories, for example, hate targets. Methods of operating neural network systems and computer program products for performing such methods are also provided.

Abstract: Systems, methods, and computer program products are provided for determining an event parameter are provided. Event data can be matched to a grid comprising gridlines and cells defined by the gridlines. The grid can be mapped to a predetermined area. Each cell can comprise a number of events per predetermined time interval. The cells can be sorted into classes based on the number of events occurring during the predetermined time interval to produce a classified data set. Features can be extracted from the classified data set. The extracted features can be processed using a classifier to determine the event parameter for a future time interval in at least one cell of the cells, for example, crime events. The classifier can comprise a neural network. Systems can comprise one or more of a processor, a neural network, and a user interface.

Abstract: Methods and systems for controlling a camera can involve automatically setting an exposure control for a camera based on data obtained from the camera and using a synchronized infrared flash for video recording by the camera with the exposure control automatically set for the camera. The exposure control can include a managed fixed exposure time controlled with automatic gain correction by the camera. The exposure time for the camera can be fixed. A gain can be monitored, and the exposure time adjusted when an average gain attains a maximum value or a minimum value with changes to ambient light.

Abstract: A method for automated booking of an on-demand service in a multimodal journey includes receiving information related to a multimodal trip plan for a commuter trip. The multimodal trip plan includes a plurality of segments, and the plurality of segments include an on-demand service segment that requires an on-demand service vehicle as the mode of transport. The method also includes receiving real-time information relating to a location of the commuter from one or more location tracking sensors, determining an estimated time of arrival of the commuter at a transfer point for transfer to the on-demand service segment by analyzing the real-time information, identifying a time of availability of an on-demand service vehicle at the transfer point (as a function of a time of booking), and determining an optimal time of booking of the on-demand service vehicle based on the estimated time of arrival and the time of availability.

Abstract: Methods and systems for forecasting in sparse data streams. In an example embodiment, steps or operations can be implemented for mapping a time series data stream to generate forecast features using a neural network, transforming the forecast features into a space with transformed forecast features thereof using metric learning, clustering the transformed forecast features in a cluster, initializing a forecast learning algorithm with a combination of the transformed forecast features in the cluster corresponding to a sparse data stream, and displaying forecasts in a GUI dashboard with information indicative of how the forecasts were achieved, wherein the mapping, the transforming, the clustering, and the initializing together lead to increases in a speed of the forecasting and computer processing thereof.

Abstract: A system and method for providing distributed on-street valet parking with the aid of a digital computer is provided. Parking spaces for valet services are reserved. One of the reserved parking spaces is designated as a valet drop-off parking space. A motor vehicle is detected in the valet drop-off parking space and a notification that the motor vehicle requires parking is provided to a valet of the detected motor vehicle. A search is conducted for the reserved parking spaces available for valet services for the motor vehicle. At least one of the reserved parking spaces available for the motor vehicle is identified and the motor vehicle is parked in the identified reserved parking space.

Abstract: Methods and systems for vehicle passenger detection, can involve extracting a region of interest from one or more images of a vehicle captured by one or more cameras, image-processing of the region of interest and detecting faces in the region of interest with a pruned deep neural-network based object-detection module of a neural network comprising a pruned network, and utilizing the pruned network for inference to determine a number of passengers in the vehicle. The neural network can be pruned by identifying filter pairs in the neural network having a high correlation of weights to detect features have redundant features, and iteratively removing the filter pairs wherein the neural network is retrained after the iterative removal of the filter pairs.

Abstract: Systems and methods providing access control and data privacy/security with decentralized ledger technology are disclosed. To ensure data privacy the decryption or access to data by a non-data owner requires joint orchestration of decentralized system nodes to provide partial decryption components with n-of-x required to fulfill request. Data can be encrypted, and access control policy can be decided including required number of key fragments to fulfill decryption. Access control policies can be stored in the decentralized ledger based system. Key information can be stored in the system in a decentralized manner with partial key fragments encrypted and split among system nodes. An access request can be sent to the system to fetch a data file, without disclosing the requester's identity in the system. The decentralized ledger based system can verify a legitimate request to access the data and denies access to malicious or faulty participants.

Abstract: An autonomous automated intent mining system extracts intents from stored conversations in a text-based chat corpus for use in an AI-driven dialog system. The intent mining system includes an intelligent pre-processor for extracting the conversation data from a computer memory and operating on the conversation data to identify relevant utterances. The system additionally includes a representation processor for operating on the identified relevant utterances to create a numerical representation. The system also includes a clustering processor for generating clusters of utterances and classifying each of the identified relevant utterances into a cluster based on the numerical representation of each utterance. Each generated cluster represents a unique intent for use in the AI-driven dialog system.

Abstract: A store profile generation method includes moving a mobile base around a product facility which includes an arrangement of product display units for displaying products. Product labels are associated with the display units. The product labels display product-related data for the displayed products. With an image capture assembly mounted on the mobile base, images are acquired of the product display units at a sequence of locations of the mobile base. With a computer processor, the product-related data is extracted from the acquired images and a store profile is constructed, based on the extracted product-related data, a spatial characterization of the image capture assembly, and information on the locations of the mobile base when the images were acquired, which indicates locations of the product labels throughout the product facility.

Abstract: A method and system for dynamically visualizing a user experience, can involve tracking data indicative of an interaction and a journey taken by a customer and an agent, and selectively rendering a visualization of the interaction and the journey taken by the customer and the agent to aid in a faster resolution of an issue experienced by the customer. In addition, deviant states and routes can be identified within the data indicative of interactions and journeys taken by the customer and the agent.

Abstract: Embodiments of the present disclosure disclose methods and systems for generating operational alarms for a plurality of clients, the operational alarms being generated by a business performance system, each client being associated with a plurality of Key Performance Indicators (KPIs). An aggregate rank for each client based on ranks of each KPI is generated. For each client: the aggregate rank of the client over one or more time periods is monitored. If the aggregate rank deteriorates over the one or more time periods, a severity indicator is determined based on change of value of each KPI and change of rank of each KPI for the client over the one or more time periods. An operational alarm based on value of the severity indicator is determined. The operational alarm is displayed on a user interface, wherein the operational alarm displays one or more KPIs with highest severity values.

Abstract: A method and system is presented for dynamically predicting hotspots (predictive of a high volume of event occurrences) in a geographic location. The method calculates a hotspot probability measure for each grid within this geographic location by summing probability of predicted volume bucket with probabilities of all higher buckets (buckets are ordinal here). The method also calculates a hotspot score for each grid based on the corresponding hotspot probability measure, selects a pre-defined number of grids having the highest hotspot scores as predicted hotspots, and generates an alert indicating the predicted hotspots and displaying the alert on a predictive GUI, showing the multiple grids.

Abstract: A computer-implemented user profiling system includes a human communication retrieval component which, for an entity employing a business process management system, captures communication data in response to a given business process being implemented by the business process management system. A human task monitoring and contextual analysis component captures user behavior information associated with the business process. A profile analysis engine is also included, which receives the user behavior information and communication data and updates a user profile corresponding to at least one of the users, based on the user behavior information and communication data.

Abstract: A method and system for parking enforcement, can include graphically displaying in a graphical user interface, a mixed reality display of data including some augmented reality data including parking enforcement information and real-time navigational cues for a navigation that account for a current location of a parking enforcement officer and one or more zones allocated to the parking enforcement officer, capturing license plate information to determine compliance with curbside regulations, and integrating a payment data source and a citation issuance application to issue a citation based on the license plate information.

Abstract: Systems, methods, and processing nodes predicting and perform preventive maintenance in a transportation system. Predicting and performing preventive maintenance in a transportation system includes determining historical data for electronic devices in the transportation system. Predicting and performing preventive maintenance also includes determining dependencies of the electronic devices based on the historical data. Predicting and performing preventive maintenance includes determining a likelihood of a fault in the target electronic device during a time period based on the dependencies of the electronic devices and a mutual probability of failure of the target electronic device and parent electronic devices associated with the target electronic device. Predicting and performing preventive maintenance also includes initiating preemptive maintenance on the target electronic device based on the likelihood of the fault.