Abstract: A computer-implemented system and method for providing available parking spaces is provided. Parking spaces, each associated with a hold time, are monitored. A request for parking is received from a user. Available parking spaces near the destination are identified, and a location of the user is determined. At least two different routes from the user's location to one of the available parking spaces are identified. An arrival time of the user for each route is calculated. The route with the fastest arrival time is selected for that available parking space. Those parking spaces for which the user's arrival time is less than the hold time are selected as possible parking spaces. A number of the possible parking spaces is reduced by removing those available parking spaces that fail to satisfy one or more parking preferences of the user. The remaining available parking spaces are sent to the user for selection.

Abstract: A method, non-transitory computer readable medium and apparatus for predicting mortality of a current patient are disclosed. For example, the method includes receiving data associated with a plurality of different patients with known mortality outcomes, wherein the data includes a subset of data for each one of a plurality of different measurement timepoints for each one of the plurality of different patients, calculating n number of classifiers, wherein n is equal to a number of the plurality of different measurement timepoints, receiving data associated with the current patient at an i-th measurement timepoint, predicting the current patient has a high mortality risk based on an output of the i-th classifier of the n number of classifiers and transmitting a signal to a health administration server to cause an alarm to be generated in response to the high mortality risk that is predicted.

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 personalized trust recommendation based on a dynamic trust model. In an example embodiment, a trust framework can be derived from a set of use-case specific factors. Invasive data and non-invasive data can be collected from a user (or a group of users) based on activity data and profile data associated with the user. A dynamic trust profile can be created (or learned) based on the invasive data and the non-invasive data collected from the user. A recommended level of trustworthiness can be then provided to the user respect to a particular situation and/or entity (e.g. other users) within the trust framework based on the dynamic trust profile of the user and which is personalized for the user.

Abstract: A system and method for optimization of on-demand microtransit is provided. A list of possible stops of one or more vehicles is maintained. A plurality of requests for transportation are received, each of the requests associated with at least one traveler. Travelers to be transported by one of the vehicles are selected. A set of a minimal number of the stops is selected, the set comprising at least one stop that is within a predefined walking distance of the origin location of each of the selected travelers and at least one stop within the predefined walking distance of the destination location of each of the selected travelers. Potential routes are identified for the vehicle that include the stops in the set. The potential routes are evaluated using a plurality of constraints and one of the routes is selected for fulfilling the requests of the selected travelers.

Abstract: A long-term memory network method and system for text comprehension. A recurrent neural network can be provided, which includes an external memory module and a long-short term memory unit, wherein said recurrent neural network encodes raw text information into vector representations, forms memories, finds relevant sentences to answer questions, and generates multi-word answers to said questions utilizing the long short term memory unit.

Abstract: A computer-implemented system and method for facilitating rental of a private parking space by an urban resident are provided. Motor vehicle parking spaces located in a residential area are managed through a server. Smart parking devices that are each physically proximate to least one of the parking spaces are interfaced to the server. Vehicle occupancy sensors that are also each physically proximate to least one of the parking spaces are interfaced to the server. Parking availability indicators that are each associated with at least one of the parking spaces are interfaced to the server. The parking spaces are supplemented with a private parking space under legitimate control by a resident of the residential area. Use of the private parking space is managed through the server and the smart parking device nearest to the private parking space. Parking availability the parking spaces is indicated through the nearest parking availability indicator.

Abstract: The disclosed embodiments illustrate a method for real time management of transportation services. The method includes determining a discrete control process with respect to a plurality of states of a vehicle. Each state in the plurality of states corresponds to a station and a count of vacant seats in the vehicle at the station. A set of rules is generated to maximize a key performance parameter of the vehicle, based on at least the determined discrete control process. A valuation parameter is determined, in real time, for one or more vacant seats in the vehicle at each of one or more subsequent stations based on the generated set of rules. The determined valuation parameter for the one or more vacant seats corresponding to each of the one or more subsequent stations is transmitted to a plurality of mobile computing devices associated with a plurality of commuters.

Abstract: A computer-implemented system and method identify Pareto optimal candidate paths between an origin and a destination for which no other candidate path is strictly better on one of a predefined set of criteria and at least as good on all the others. A constraint is defined for each of the criteria, based on user input. A set of Pareto optimal candidate paths is identified, from an origin to a destination, which respect these constraints. The identification may include, in a search graph composed of nodes connected by edges, iteratively advancing each of a set of possible paths from an origin node by exactly one exit node and updating labels of the exit nodes reached. The exit node labels each include a value for each of the criteria. Labels of reached exit nodes that are dominated by another label of that reached node are removed. Pareto optimal candidate path(s) is/are identified.

Abstract: Additional background information is used with a trained neural network based model to help classify whether text is a subtly and/or ambiguously offensive. This additional background information can come from different sources such as the article on which the comment was made, world knowledge about the external entities (e.g., Wikipedia, Urban Dictionary), phrases referenced in the text being classified, and, the context of the previous comments/text in the thread. The background information is retrieved based on key entities (e.g., people, places things) and/or key phrases in the comment. Sentence matrix encodings are built for both the comment and the background information. The background information encoding is used to condition the comment encoding. The background information encoding, and the conditioned comment encoding are fed to a trained multi-level perceptron to classify the comment as hate speech or non-hate speech.

Abstract: A blended communication engine helps bridge a gap amongst users in the blended ecosystem by allowing a multi-channel platform for shared, real-time interaction amongst the users, system, and environment. This engine can provide three different forms of interaction between the user and the ecosystem: Share and Alert—The ability to alert another user or group by sharing an information block; Instruct and Assign—The ability to highlight segments of interest within an information block and direct the corresponding instructions to specific people; Converse and Collaborate—The involved members' ability to have contextual discussions about shared information blocks and instructions. Users interact with each other in virtual reality and augmented reality platforms over communication links using annotations on real objects in an environment thereby enabling efficient information tagging of real-world objects, and communication between personnel managing the objects.

Abstract: A crime analysis system, method, and apparatus comprising at least one processor and a storage device communicatively coupled to the at least one processor, the storage device storing instructions which, when executed by the at least one processor, cause the processor to perform operations comprising receiving information provided by one or more data collection source, storing the information, wherein the stored information is formatted, processing the information to generate crime clustering data associated with at least one region and at least one crime, processing the crime clustering data associated with at least one region and at least one crime to generate benchmarking of the at least one region with at least one other region, and providing crime clustering data associated with at least one region and at least one crime, and benchmarking of the at least one region with at least one other region for presentation through a user interface.

Abstract: A system and method for performing vehicle-velocity aware image enhancement. Embodiments generally include a video capture module configured to receive image data of the scene being monitored, an image extraction module configured to extract still images from incoming video data, a vehicle detection module that detects the approximate location of a target vehicle in the scene being monitored, a velocity determination module configured to determine the amplitude and direction of a vector that describes the velocity of the target vehicle in image pixel coordinates, and a velocity-aware enhancing module configured to enhance the image(s) of the target vehicle extracted from the video feed based on the vehicle's velocity. Embodiments may also include an infraction detection module configured to detect the occurrence of a violation of traffic law(s) by a target vehicle.

Abstract: The disclosed embodiments illustrate methods and systems for searching for a first user. The one or more inputs pertaining to one or more first attributes of the first user are received. Further, the one or more first attributes of the first user are ranked based on at least a presence of the one or more first attributes among one or more second attributes pertaining to one or more second users. Thereafter, one or more search strings comprising at least one attribute selected from the ranked one or more first attributes are generated, wherein the one or more search strings are utilizable to search for the first user. Finally, a list of third users is obtained from one or more search engines in response to the one or more search strings.

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: 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: A method of selecting an intervention includes, based on user content submitted to a platform, determining whether the content includes objectionable content. Based on the objectionable content, a content persona classification is associated with the objectionable content. Based on the content persona classification, an intervention is selected. The objectionable content may include, for example, content that has one or more characterizations as: subjective, misaligned, trigger, misguided, expressive, non-owner, offensive, prohibited, trigger product, trigger description, expired/invalid, and/or otherwise objectionable.

Abstract: According to embodiments illustrated herein, there is provided a system for predicting a health condition of a first patient. The system includes a document processor configured to extract one or more headings from one or more medical records of the first patient based on one or more predefined rules. The document processor is further configured to extract one or more words from one or more phrases written under each of the extracted one or more headings, wherein the one or more phrases correspond to documentation of the observation of the first patient by a medical attender. The system further includes one or more processors configured to predict the health condition of the first patient based on a count of the one or more words in historical medical records and the one or more medical records.

Abstract: A method, non-transitory computer readable medium, and apparatus for recommending a topic-cohesive and interactive implicit community are disclosed. For example, the method receives a request for customer care, selects an implicit community identified from a plurality of individual users of a social media website based upon a relevance score related to a topic of the request for customer care and recommends the implicit community in response to the request for customer care.

Abstract: A system and method to identify the leader of a group in a retail, restaurant, or queue-type setting (or virtually any setting) through recognition of payment gestures. The method comprises acquiring initial video of a group, developing feature models for members of the group, acquiring video at a payment location, identifying a payment gesture in the acquired video, defining the person making the gesture as the leader of the group, and forwarding/backtracking through the video to identify timings associated with leader events (e.g., entering, exiting, ordering, etc.).