Abstract:
Controlling resource access, a first device responsive to a request for access to a resource, determines whether to grant the access to the resource, based on an identity of a requestor requesting the access to the resource. The resource is provided by a second device that is separate from the first device. The first device customizes an access token with an access constraint to control the access to the resource, the access token is generated responsive to the first device determining that, based on the identity of the requestor requesting the access to the resource, the access to the resource is granted.
Abstract:
In an approach for evaluating a predictive model, a computer identifies features of training samples in a set of training samples and selects at least one evaluation metric from a set of evaluation metrics as one or more available metrics based on the identified features. The computer applies a predictive model created based on the set of training samples to a set of test samples so as to calculate values of the one or more available metrics and evaluates the predictive model by using the one or more available metrics and the values of the available metrics. With the technical solutions described with respect to the embodiments of the present invention, one or more evaluation metrics that are applicable to specific training sample features may be determined from several evaluation metrics, so that users can precisely evaluate predictive models by using the determined evaluation metrics.
Abstract:
Location based on call detail record. The method includes: acquiring handover call detail record (HCDR) data and handover (HO) data corresponding to at least one cell transfer during a call; The HCDR data can include a start time, an end time, passed cells during the call; The HO data can include the HO time for each pair of adjacent cells among the passed cells during the call. The method can further include estimating the location of the subscriber based on the HCDR data and the HO data.
Abstract:
A method to detect unauthorized beacons includes receiving position information that defines a positional pattern for a plurality of authorized beacons, receiving beacon identifiers from a plurality of beacons with a beacon receiving device, determining a movement path of the beacon receiving device relative to the positional pattern, and determining whether the movement path has an anomaly. A corresponding computer program product and computer system are also disclosed herein.
Abstract:
A method and an apparatus for determining a location of a mobile device. The location of a mobile device is determined accurately according to information which includes call data records of the mobile device. By employing a partial ellipse integral model, two physical world factors are taken into consideration in reducing the location uncertainty in call data records. The factors include: spatiotemporal constraints of the device's movement in the physical world and the telecommunication cell area's geometry information, which increase the accuracy of determining the location of a mobile device.
Abstract:
Controlling resource access, a first device responsive to a request for access to a resource, determines whether to grant the access to the resource, based on an identity of a requestor requesting the access to the resource. The resource is provided by a second device that is separate from the first device. The first device customizes an access token with an access constraint to control the access to the resource, the access token is generated responsive to the first device determining that, based on the identity of the requestor requesting the access to the resource, the access to the resource is granted.
Abstract:
A method for recognizing a primitive in an image includes recognizing at least one primitive in the image to obtain at least one candidate shape of the at least one primitive, which at least one candidate shape has a respective confidence; determining whether the recognizing of the at least one primitive has a potential error based on the confidence; obtaining auxiliary information about the at least one primitive from a user in response to determining that the recognizing has the potential error; and re-recognizing the at least one primitive at least in part based on the auxiliary information.
Abstract:
Methods and systems for monitoring interesting subjects. A method including: selecting, based on a first collection of interesting subjects, a set of critical nodes including at least one critical node which participates in one or more interesting subjects in the first collection; and monitoring contents posted by the one or more critical nodes in the set so as to find a second collection of interesting subjects. The set of critical nodes which participate in one or more interesting subjects in the first collection of interesting subjects is selected based on the first collection, as objects to be monitored, thereby reducing the number of contents posted by the nodes to be monitored as compared with monitoring all the user nodes, so that interesting subjects such as hot news or hot events can be found in real time with high efficiency and low cost.
Abstract:
A method and apparatus for estimating a wave velocity of negative pressure wave in a fluid transportation pipeline. The method including: receiving a plurality of pressure signals from a plurality of sensors; determining time differences produced by the negative pressure wave reaching the adjacent sensors based on the received pressure signals; determining a wave source sensor segment where a wave source of the negative pressure wave is located; and estimating the wave velocities of the negative pressure wave in a non-wave source sensor segment and the wave source sensor segment.
Abstract:
An approach for a computer to evaluate a predictive model includes identifying features of training samples in a set of training samples. The approach selects evaluation metrics from a set of evaluation metrics as available metrics using identified features and includes determining recommended metrics using the predictive model, the available metrics, and a predetermined set of user-preferred metrics. The approach applies the predictive model created using the set of training samples to a set of test samples to calculate values of the available metrics. The approach evaluates the predictive model by using the available metrics and the values of the available metrics to evaluate the predictive model by evaluating the predictive model using the recommended metrics and the values of the recommended metrics.