Abstract: The disclosed embodiments illustrate methods and systems for managing parking violations by vehicles in parking areas in real-time. The method includes receiving parking information from one or more sensors installed at each of one or more parking spots in a plurality of parking areas at a specific time. The method includes detecting a parking violation by a vehicle at a parking spot of the one or more parking spots in a parking area. The method includes identifying one or more vehicle identification parameters of the vehicle associated with the detected parking violation. The method includes determining a penalty for the vehicle with the identified one or more vehicle identification parameters. The method includes transmitting the determined penalty to a user-computing device of a user associated with the vehicle with the identified one or more vehicle identification parameters, wherein the user is imposed with the penalty.

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: Disclosed are methods and systems for transmitting a first electronic message to an employee. The method further includes generating a first data structure based on one or more first parameters of one or more electronic messages, one or more demographic attributes associated with the employee and one or more second parameters representative of one or more feedbacks provided by the employee on each of the one or more electronic messages other than the first electronic message. The method further includes determining a priority of the first electronic message, wherein the determination of the priority comprises predicting the one or more second parameters associated with the employee for the first electronic message based on the one or more second data structures. The method further includes transmitting the first electronic message to the employee based on the determined priority of the first electronic message.

Abstract: The present disclosure is directed to systems and methods for context-aware and personalized access to data corresponding to an event. The data is related to multiple predefined parameters including a location, date, time, and a classifier representing a status or an impact intensity for the event. The method includes receiving the data and an event type for the data. The event type is selected from multiple predefined event types. The method also includes creating a hierarchical data structure configured to spatially index the data based on the selected event type. The hierarchical data structure includes a node representing the selected event type. The node is augmented using a linked list for referring to the data to be stored in a database. The node is associated with a frequency of occurrence of the selected event type.

Abstract: Disclosed are methods and systems for classifying one or more human subjects in one or more categories indicative of a health condition of the one or more human subjects. The method includes categorizing one or more parameters of each of the one or more human subjects in one or more data views based on a data type of each of the one or more parameters. A data view corresponds to a first data structure storing a set of parameters categorized in the data view, associated with each of the one or more human subjects. The one or more data views are transformed to a second data structure representative of the set of parameters across the one or more data views. Thereafter, a classifier is trained based on the second data structure, wherein the classifier classifies the one or more human subjects in the one or more categories.

Abstract: A method of planning for deployment of facilities includes modeling maximization of satisfaction of demands for service in a geographic area (packing constraint) and minimization of distance traveled from locations of interest within the geographic area to deployed facilities (covering constraint) as a mixed packing and covering problem with a service level constraint on the deployed facilities and an overall budget constraint. Additional embodiments describe an iterative process to identify an optimized solution, an incremental process to identify incremental optimized solutions in relation to release of incremental budgets for deployment of facilities, and deployment of facilities in which multiple private providers compete for sites and subsidies from an authoritative agency. Various embodiments of facility deployment planning systems associated with the method are also provided, as well as various embodiments of non-transitory computer readable medium associated with the method.

Abstract: The disclosed embodiments illustrate methods and systems for managing parking violations by vehicles in parking areas in real-time. The method includes receiving parking information from one or more sensors installed at each of one or more parking spots in a plurality of parking areas at a specific time. The method includes detecting a parking violation by a vehicle at a parking spot of the one or more parking spots in a parking area. The method includes identifying one or more vehicle identification parameters of the vehicle associated with the detected parking violation. The method includes determining a penalty for the vehicle with the identified one or more vehicle identification parameters. The method includes transmitting the determined penalty to a user-computing device of a user associated with the vehicle with the identified one or more vehicle identification parameters, wherein the user is imposed with the penalty.

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: A method for mobility demand modeling uses passenger demand data and geographical data for a transportation network. The demand data includes, for each of a plurality of stops in the transportation network, a passenger demand for each of a plurality of time intervals. The geographical data includes, for each of the plurality of stops in the transportation network, geographical features representing local points-of-interest. A dependence between the demand data and the geographical data is modeled by learning first and second mapping functions for embedding the demand data and the geographical data into the same latent space. The first and second mapping functions are learnt so as to optimize a correlation between the passenger demand data and the geographic data in the latent space. From the model, a prediction of passenger demand or of local point of interest for a proposed stop in the transport network can be generated.

Abstract: A method includes receiving multicast traffic intended for host devices; identifying a flow associated with the multicast traffic; retrieving information associated with a group of multicast trees, where the group of multicast trees includes information associated with a group of I/O units, associated with a network node; identifying a particular tree that corresponds to the identified flow, where the particular tree includes information associated with a set of I/O units; and transferring the multicast traffic to an I/O unit, of the set of I/O units, based on the identification of the particular tree, where the transferring enables the I/O unit to send a copy of the multicast traffic to other I/O units of the set of I/O units, and the set of I/O units to process the multicast traffic in a manner that utilizes bandwidth or processing resources in a controlled manner and to send a copy of the multicast traffic to each of the host devices.

Abstract: A system for facilitating filling at least one unfilled form including at least one data field is disclosed. The system includes a display module configured to display the at least one unfilled form. Further, the system includes a scanning module configured to scan at least one supporting document, a classifier module configured to classify the at least one supporting document into at least one document class, an extracting module configured to extract the information from the at least one supporting document based on the at least one document class, a questionnaire module configured to provide an adaptive questionnaire to obtain additional information, and a form-filling module configured to fill out the at least one unfilled form to obtain at least one filled form. Finally, the system includes a communication module configured to send the at least one filled form over a communication network.

Abstract: Disclosed are methods and systems for transmitting a first electronic message to an employee. The method further includes generating a first data structure based on one or more first parameters of one or more electronic messages, one or more demographic attributes associated with the employee and one or more second parameters representative of one or more feedbacks provided by the employee on each of the one or more electronic messages other than the first electronic message. The method further includes determining a priority of the first electronic message, wherein the determination of the priority comprises predicting the one or more second parameters associated with the employee for the first electronic message based on the one or more second data structures. The method further includes transmitting the first electronic message to the employee based on the determined priority of the first electronic message.

Abstract: The disclosed embodiments illustrate methods and systems for selecting a set of resumes for a job description (JD). The method includes extracting at least a portion in each of a plurality of resumes based on a scoping criterion received from a user. The method further includes extracting one or more first features from said portion in each of said plurality of resumes. The method further includes selecting said set of resumes from said plurality of resumes based on a comparison between said one or more first features and said scoping criterion. Thereafter, the method includes displaying, by a display device, one or more second features of said selected set of resumes on a graphical user interface to said user. The method is performed by one or more microprocessors.

Abstract: Disclosed are methods and systems for classifying one or more human subjects in one or more categories indicative of a health condition of the one or more human subjects. The method includes categorizing one or more parameters of each of the one or more human subjects in one or more data views based on a data type of each of the one or more parameters. A data view corresponds to a first data structure storing a set of parameters categorized in the data view, associated with each of the one or more human subjects. The one or more data views are transformed to a second data structure representative of the set of parameters across the one or more data views. Thereafter, a classifier is trained based on the second data structure, wherein the classifier classifies the one or more human subjects in the one or more categories.

Abstract: The disclosed embodiments illustrate methods and systems for human resource management in an organization. A graph, representative of relationships between employees, job openings, and candidates applied for the job openings, is generated. The graph is transformed to generate a graph matrix deterministic of a mapping of nodes depicted in the graph, in a predetermined dimensional space. Further, a first distance between nodes corresponding to the candidates and a node corresponding to a job opening is determined based on the graph matrix. A list of ranked candidates, based on the first distance, is presented over a display associated with a hiring manager, allowing selection of a set of candidates. Additionally, a second distance between nodes corresponding to the candidates and between each node corresponding to a candidate and each node corresponding to an employee, is determined, based on which a set of candidates for a team are selected.

Abstract: A method, a system, and a computer program product for evaluating a handwritten document comprising one or more text fields are provided. The method includes identifying a character in each of the one or more text fields in a digital image by applying a character recognition technique. The character type of the identified character is then compared with a predefined character type corresponding to the associated text field of the one or more text fields. The character type in each of the one or more text fields is then validated based on the comparison. Thereafter the identified character for each of the one or more text fields is recommended while digitalization of the handwritten document.

Abstract: Methods and systems for determining one or more routes in a navigation system. A request comprising a first set of parameters corresponding to a trip is received. The first set of parameters comprise at least one an originating node for the trip, a destination node for the trip, a start time for the trip, or a set of preferences associated with the trip. The one or more routes between the originating node and the destination node are determined based on the first set of parameters. Each of the one or more routes comprises at least one public transportation sub-trip traversed by a public vehicle and a private transportation sub-trip traversed by a private vehicle. The one or more routes are ranked based on a trip score associated with the one or more routes. The trip score is determined based on the set of preferences.

Abstract: Methods and systems for determining one or more routes in a navigation system. A request comprising a first set of parameters corresponding to a trip is received. The first set of parameters comprise at least one an originating node for the trip, a destination node for the trip, a start time for the trip, or a set of preferences associated with the trip. The one or more routes between the originating node and the destination node are determined based on the first set of parameters. Each of the one or more routes comprises at least one public transportation sub-trip traversed by a public vehicle and a private transportation sub-trip traversed by a private vehicle. The one or more routes are ranked based on a trip score associated with the one or more routes. The trip score is determined based on the set of preferences.

Abstract: The present disclosure is directed to systems and methods for context-aware and personalized access to data corresponding to an event. The data is related to multiple predefined parameters including a location, date, time, and a classifier representing a status or an impact intensity for the event. The method includes receiving the data and an event type for the data. The event type is selected from multiple predefined event types. The method also includes creating a hierarchical data structure configured to spatially index the data based on the selected event type. The hierarchical data structure includes a node representing the selected event type. The node is augmented using a linked list for referring to the data to be stored in a database. The node is associated with a frequency of occurrence of the selected event type.

Abstract: A method and system for determining real-time delay information in a transportation system. Historical operational information about the transportation system, including data related to a plurality of arrival events corresponding to one or more stops within the transportation system is received and a dependency graph is built based upon the historic information. The dependency graph defines relationships that exist in the transportation system between the plurality of arrival events, each of the relationships defining a specific dependent relationship between at least two of the arrival events. Delay dependency values are fitted into the dependency graph, each of the delay dependency values being associated with one of the plurality of relationships and defining a specific dependency value associated with that relationship. Predictive delay information is determined based upon the fitted dependency graph for one or more of the arrival events based upon current operating information.