Abstract: A system for determining a labor flexibility level for a document management system that meets a performance level of a full-flexibility level and is within one or more threshold limits includes a document management system having a plurality of print production devices, an electronic device in communication with the document management system, and a computer-readable storage medium having one or more programming instructions. The document management system is associated with a plurality of operators who each possess one or more skill sets for operating one or more of the print production devices.

Abstract: Systems and methods of modeling irregularly sampled time series signals with unknown temporal dynamics are disclosed wherein a temporal difference variable (TDV) is introduced to model irregular time differences between subsequent measurements. A hierarchical model is designed comprising two linear dynamical systems that model the effects of evolving TDV on temporal observations. All the parameters of the model, including the temporal dynamics, are statistically estimated using historical data.

Abstract: A dialog device comprises a natural language interfacing device (chat interface or a telephonic device), and a natural language output device (the chat interface, a display device, or a speech synthesizer outputting to the telephonic device). A computer stores natural language dialog conducted via the interfacing device and constructs a current utterance word-by-word. Each word is chosen by applying a plurality of language models to a context comprising concatenation of the stored dialog and the current utterance thus far. Each language model outputs a distribution over the words of a vocabulary. A recurrent neural network (RNN) is applied to the distributions to generate a mixture distribution. The next word is chosen using the mixture distribution. The output device outputs the current natural language utterance after it has been constructed by the computer.

Abstract: A method and system are disclosed for dynamically estimating an origin-destination matrix. An origin-destination matrix is initialized with a set of origin stops and destination stops. Validation sequences are acquired for a set of travelers on a transportation system which include a plurality of the origin stops and respective timestamps. Corresponding destination stops may be known or inferred. For each validation sequence, a set of subsequences is generated, each including a respective one of the origin stops and the associated timestamp. Subsequences which, in combination, constitute a valid transfer trip are identified. For a combination of subsequences constituting a valid transfer trip, the method includes determining whether the valid transfer trip is a multi-goal trip for which there is least a first destination stop with an intermediate goal and a second destination stop with a final goal. The origin-destination matrix is updated, based on the determination.

Abstract: The present disclosure discloses methods and systems for enhancing shopping experience in physical stores. The method includes receiving at least one persona associated with a user based on one or more of: ethnographic data obtained from a user, demographic data associated with the user, buying behavioral data associated with the user, and social networking data associated with the user. After this, one or more historical activities of the user inside one or more physical stores are received. Also, one or more constraints associated with the user are received. Once received, the at least one persona, the one or more constraints, and the one or more historical activities are analyzed to generate a pre-defined number of personalized recommendations. Finally, the personalized recommendations are displayed to the user within a window of a user interface.

Abstract: According to exemplary methods, automated image processing of images from order locations of a multi-lane drive-thru system is continually performed using an automated ordering system. It is automatically determined if a vehicle is present at any of the order locations based on the automated image processing. It is automatically determined if an order has been initiated into the automated ordering system. When the order has been initiated while the vehicle is present at any of the order locations, an automated sequencing processing is automatically begun. The automated sequencing processing determines an order pick-up sequence for picking up orders at pickup windows of the multi-lane drive-thru system. When the order has been initiated while the vehicle is not present at any of the order locations, a potential out-of-sequence warning is automatically associated with the order and output from the automated ordering system.

Abstract: A method and a system are provided for identifying one or more locations for placement of one or more replenishment stations for one or more vehicles. The method comprises receiving a historical demand data at a plurality of existing replenishment stations within a pre-defined area. The method identifies one or more point of interest locations within the pre-defined area based on a map data. Further, the method receives traffic information between a plurality of road intersections within the pre-defined area. Based on an aggregation of a first demand prediction, a second demand prediction, and a third demand prediction, the method predicts a replenishment demand at a plurality of locations. The method further identifies the one or more locations from the plurality of locations for placement of the one or more replenishment stations based on the predicted replenishment demand at the plurality of locations and a pre-defined threshold.

Abstract: The disclosed embodiments illustrate methods and systems for predicting requirements of a user for resources. The method includes transforming a message posted by the user into a first message vector. The method further includes categorizing one or more first message vectors into one or more categories. The method further includes transforming each of the categorized first message vectors into one or more second message vectors using a wavelet transform technique. The method further includes determining, for each of the categorized first message vectors, a first score based on at least a probability distribution of one or more coefficients associated with each associated feature. The method further includes selecting a predefined number of features based on at least the first score. The method further includes training one or more classifiers on the selected predefined number of features to identify at least the one or more needs of the user.

Abstract: A computer-implemented system and method for providing multi-locational curbside valet parking service is provided. A multiplicity of motor vehicle parking spaces are managed by a server. A plurality of smart parking devices and vehicle occupancy sensors are interfaced with the server. Use of a plurality of the parking spaces is reserved for a valet service. A reservation request for the use of the plurality of the parking spaces is accepted for use by the valet service for a period of time. Occupancy of the reserved parking spaces by a motor vehicle is sensed through the vehicle occupancy sensor. A valet drop-off location of at least one of the parking spaces that is reserved for the use of the valet service and is not occupied by a motor vehicle is identified. The valet drop-off location and a location of a lock box are provided to the motorist through a user interface.

Abstract: A dynamic digital signage system based on measured customer behaviors through video analytics.

Abstract: Methods and systems for training a conversation-classification model are disclosed. A first set of conversations in a source domain and a second set of conversation in a target domain are received. Each of the first set of conversations has an associated predetermined tag. One or more features are extracted from the first set of conversations and from the second set of conversations. Based on the similarity of content in the first set of conversations and the second set of conversations, a first weight is assigned to each conversation of the first set of conversations. Further, a second weight is assigned to the one or more features of the first set of conversations based on the similarity of the one or more features of the first set of conversations and of the second set of conversations. A conversation-classification model is trained based on the first weight and the second weight.

Abstract: The disclosed embodiments illustrate methods and systems for generating recommendations for client process execution of one or more client processes corresponding to a plurality of clients of an organization. The method comprises retrieving an event log including event data captured during execution of one or more processes in the organization to service a plurality of clients of a predefined type. The event log is analyzed across the plurality of clients to determine cross-clientele information including a process compliance deviation between an observed and an expected client process execution of the one or more processes. Thereafter, a set of root-causes of the process compliance deviation is determined based on process models of the one or more processes and/or decision rules of the organization. Further, one or more recommendations for the client process execution of the one or more processes of the organization are generated, based on the set of root-causes.

Abstract: A method and system for performing semantic analysis for electronic communication using a lexicon is provided. A neural network model is trained with a plurality of annotated text strings, the annotations comprising characteristic tuples that indicate characteristics for the text strings. An unannotated text string is received that comprises a plurality of words from a user. A characteristic matrix for the received text string is generated using a lexicon. The determined characteristic matrix is input into the trained neural network. And a characteristic tuple that indicates a characteristic for the received text string is received as output from the trained neural network.

Abstract: Methods and systems for preventing vehicle theft. A video stream of a parking area wherein a vehicle is parked can be captured, the video stream provided by a theft notification service to which the vehicle is pre-registered. The vehicle in the video stream can be identified. The video stream is then analyzed to detect motion with respect to the vehicle. An alert can then be generated if motion is detected.

Abstract: According to exemplary methods, automated image processing of images from order locations of a multi-lane drive-thru system is continually performed using an automated ordering system. It is automatically determined if a vehicle is present at any of the order locations based on the automated image processing. It is automatically determined if an order has been initiated into the automated ordering system. When the order has been initiated while the vehicle is present at any of the order locations, an automated sequencing processing is automatically begun. The automated sequencing processing determines an order pick-up sequence for picking up orders at pickup windows of the multi-lane drive-thru system. When the order has been initiated while the vehicle is not present at any of the order locations, a potential out-of-sequence warning is automatically associated with the order and output from the automated ordering system.

Abstract: Disclosed are the embodiments for creating a model capable of identifying one or more clusters in a healthcare dataset. An input is received pertaining to a range of numbers. Each number in the range of numbers is representative of a number of clusters in the healthcare dataset. For a cluster, one or more first parameters of a distribution associated with the cluster are estimated. Thereafter, a threshold value is determined based on the one or more first parameters. An inverse cumulative distribution of each of one or more n-dimensional variables in the healthcare dataset is determined. The one or more first parameters are updated to generate one or more second parameters based on the estimated inverse cumulative distribution. A model is created for each number in the range of numbers based on the one or more second parameters.

Abstract: According to exemplary methods of training a convolutional neural network, input images are received into a computerized device having an image processor. The image processor evaluates the input images using first convolutional layers. The number of first convolutional layers is based on a first size for the input images. Each layer of the first convolutional layers receives layer input signals comprising features of the input images and generates layer output signals that include signals from the input images and ones of the layer output signals from previous layers within the first convolutional layers. Responsive to an input image being a second size larger than the first size, additional convolutional layers are added to the convolutional neural network. The number of additional convolutional layers is based on the second size in relation to the first size. The additional convolutional layers are initialized using weights from the first convolutional layers.

Abstract: Disclosed embodiments illustrate methods and systems implementable on a computing device for training a crowdworker on one or more skill sets. The crowdworker attempts a first set of tasks. The method includes determining an expertise gap between a current level of expertise possessed by the crowdworker in the one or more skill sets and a required level of expertise in the one or more skill sets. Further, the method includes determining a number of training tasks that the crowdworker has to complete to achieve the required level of expertise in the one or more skill sets. At least one training task pertaining to the one or more skill sets is assigned along with the first set of tasks such that the crowdworker gets trained on the one or more skill sets in a predetermined period without violating a service level agreement associated with the first set of tasks.

Abstract: A computer-implemented method and system enable customizing web applications within a domain includes mapping a plurality of source databases to a universal database. A webpage is generated, which includes providing for a user to incorporate at least one widget into a webpage, associating a call to the universal database for the incorporated at least one widget. The webpage, or a model of the webpage, is incorporated into a management system. When the widget is actuated, a visualization of data from at least one of the plurality of source databases that has been mapped to the universal database is incorporated into the webpage.

Abstract: A healthcare payment management system comprising a payment consolidation server configured to receive billing information from a provider for an episode of care for a member, receive benefit information from a payer for the episode of care, consolidate the billing information and the benefit information into a payment reconciliation statement, and send the payment reconciliation statement to a member.