Abstract:
Embodiments of a dynamic pricing system for determining an optimal commission rate based on a service request being served are disclosed. The dynamic pricing system comprises at least one service device that can communicate with a request device, wherein the at least one service device provides a response for a service request; and a dynamic pricing device interfacing with the at least one service device, wherein the dynamic pricing device determines an optimal commission rate corresponding to a request type for the at least one service device, wherein the optimal commission rate maximizes revenue from the service request.
Abstract:
Disclosed are the methods for scheduling a task including at least one sub-task, on one or more computing devices in a distributed computing environment. A set of computing devices are identified from the one or more computing devices, based on an availability of a set of computational resources on the set of computing devices. Each computing device in the set of computing devices is ranked based on at least one of a monetary cost or a network cost, associated with the execution of the at least one sub-task on the each computing device. The at least one sub-task is allocated to at least one computing device from the set of computing devices for execution based on at least one of the ranking or an acceptable success probability associated with the execution of the at least one sub-task.
Abstract:
Embodiments of a method are disclosed for computing trust index among multiple entities associated with a resource marketplace. The method includes receiving multiple inputs including interaction attributes, attribute importance factors, references to databases, and multiple entities associated with the resource marketplace. The method also includes creating a weighted-interaction graph based on the received inputs. The weighted-interaction graph includes multiple vertices representing the entities. The method further includes performing a topology-specific analysis of the weighted-interaction graph. The method furthermore includes computing Euclidean distances for each pair of vertices in the weighted-interaction graph based on the performed analysis. The method also includes determining a trust index for a first entity in the received multiple entities based on the computed Euclidean distances. The trust index includes ranking of at least one of the multiple entities with respect to the first entity. The ranking is inversely proportional to the computed Euclidean distances.
Abstract:
Disclosed are the methods for scheduling a task including at least one sub-task, on one or more computing devices in a distributed computing environment. A set of computing devices are identified from the one or more computing devices, based on an availability of a set of computational resources on the set of computing devices. Each computing device in the set of computing devices is ranked based on at least one of a monetary cost or a network cost, associated with the execution of the at least one sub-task on the each computing device. The at least one sub-task is allocated to at least one computing device from the set of computing devices for execution based on at least one of the ranking or an acceptable success probability associated with the execution of the at least one sub-task.
Abstract:
According to embodiments illustrated herein, there is provided a method for staffing one or more employees on a project. The method includes selecting a first set of employees from the one or more employees for a skill required to process the project, based on at least a first score and a second score. The method further includes receiving an input from a computing device deterministic of at least cost of the project, wherein the input is received through a graphical user interface (GUI) presented on the computing device. The method further includes selecting a second set of employees from the first set of employees based on at least one of a cost of each employee in the first set of employees, a time duration of the project, and the cost of the project.
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:
Embodiments of a method are disclosed for computing trust index among multiple entities associated with a resource marketplace. The method includes receiving multiple inputs including interaction attributes, attribute importance factors, references to databases, and multiple entities associated with the resource marketplace. The method also includes creating a weighted-interaction graph based on the received inputs. The weighted-interaction graph includes multiple vertices representing the entities. The method further includes performing a topology-specific analysis of the weighted-interaction graph. The method furthermore includes computing Euclidean distances for each pair of vertices in the weighted-interaction graph based on the performed analysis. The method also includes determining a trust index for a first entity in the received multiple entities based on the computed Euclidean distances. The trust index includes ranking of at least one of the multiple entities with respect to the first entity. The ranking is inversely proportional to the computed Euclidean distances.
Abstract:
Embodiments of a method are disclosed for transmitting one or more videos provided by one or more video cameras disposed at a mobile object traveling along a pre-defined route. The method includes receiving the videos, bandwidth map data for multiple communication channels, travel time data for the mobile object, and service level agreement (SLA) parameters. The received video is transformed into multiple video layers. For each video layer, a transmission cost over the multiple communication channels is computed based on the bandwidth map data, the travel time data and the SLA parameters. Out of the multiple communication channels, a particular communication channel is selected for each video layer, which has the minimum transmission cost over the selected communication channel. The video layers are scheduled for transmission over the respective selected communication channels. The scheduled video layers are transmitted with respect to at least one of the SLA parameters.
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:
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.