In some examples, an electronic device includes a plurality of network interfaces to communicate over respective different networks, and a storage medium to store information associating a first application of the electronic device with a first profile, and associating a second application of the electronic device with a second profile. The first profile selects a first network interface of the plurality of network interfaces to use for communications, and the second profile selects a second network interface of the plurality of network interfaces to use for communications.

Methods and systems are disclosed for coordinating content selection across devices. A user device may transmit a request for webpage content and in response, may receive response communications that include the webpage content, embedded content, and a script. The user device may retrieve a device identifier initially generated by a remote system from a locally stored data object. The user device can detect, using the script, whether at least part of the embedded content is being presented within a portion of the webpage that is displayed on a screen of the user device. The user device may then transmit a report communication to a remote ID-graph system that includes the device identifier and an indication as to whether the at least part of the embedded content was presented within the portion of the webpage that was displayed on the screen of the user device.

A method for providing a location-specific machine learning model from a harbor operating system to an on-board processing system of a vessel is provided. The method includes predetermining a geographical area of an area of a harbor, creating communication between the harbor operating system and the on-board processing system of the vessel, receiving a specification of the vessel from the on-board processing system of the vessel, at the harbor operating system. The received specification is used for preparing and providing at least one software container according to the received specification of the vessel, wherein the at least one software container includes the location-specific machine learning model. The at least one software container received by the on-board processing system of the vessel is activated by using the at least one provided software container activation means.

The disclosure discloses a method and apparatus for mutual authentication between two smart security media for bundle transfer between the security media. According to an embodiment of the disclosure, a first device for providing a bundle for the second device includes a transceiver; and at least one processor, wherein the at least one processor is configured to obtain information about a bundle to be transmitted to the second device, control the transceiver to transmit identification information of the bundle to the second device, control the transceiver to receive, from the second device, authentication information relating to bundle transfer of a second smart secure platform (SSP) of the second device, determine whether a second secondary platform bundle loader (SPBL) of the second SSP is a Spbl which is able to receive the bundle based on the authentication information relating to bundle transfer of the second SSP, and control the transceiver to transmit the bundle to the second device based on a result of the determining.

A system and method are provided to inform travelers of nearby pet relief areas. At least one remote server manages at least one user account. The user account is associated with a corresponding PC device. The remote server includes a plurality of terminal profiles, and each terminal profile includes a plurality of nearby service animal relief area (SARA) locations. The remote server retrieves travel information for the user account and compares the travel information with the plurality of terminal profiles. After comparing the travel information with the plurality of terminal profiles, the remote server identifies at least one closest departure SARA location and at least one closest arrival SARA location for the user account. The closest departure SARA location and one closest arrival SARA location can then be displayed to the user through the corresponding PC device.

An electronic device is provided. The electronic device includes a communication circuit and a processor. The processor may be configured to obtain information on the number of predicted abnormal terminals, allocate different resources respectively to a plurality of terminal groups, wherein the number of the plurality of terminal groups is greater than the number of predicted abnormal terminals, obtain learning data of each of the plurality of terminal groups, and identify a final terminal group among the plurality of terminal groups, based on the learning data.

A system and method are provided for controlling operations of devices in an IoT environment based on a correlation between devices. The controlled operations include identifying a first device in response to a user pointing the electronic device toward the first device, determining at least one second device contextually related to the first device, and recommending at least one suggestion to control at least one operation of at least one of the first device or the at least one second device, based on a correlation between capabilities of the first device and a current operating context of the at least one second device.

A system and method for creating priority-based regulated network interlinks between electronic devices is disclosed. The system receives a communication request from a first device to communicate with a second device and identifies whether the first device is comprised within a primary affinity group associated with the second device. If the first device is not found in the primary affinity group one or more secondary affinity groups are identified, each secondary affinity group associated with an electronic device different than the first and second devices. Based on scoring of each secondary affinity group, handling criteria for the communication object is determined and used to create a network interlink between the first device and the second device.

A method receives error measurements from network elements. Groups of network elements are generated based on similarity of error measurements and a bitloading profile for each of the groups of network elements is generated based on the error measurements for each respective group. Each bitloading profile includes a modulation level determined to be sufficient for transporting content to respective groups of network elements. The method then assigns a set of bitloading profiles to each network element based on the groups of network elements and the bitloading profile generated for each of the groups. The bitloading profile for each of the groups of network elements and the assigned set of bitloading profiles are output to a network device. The network device uses the bitloading profiles to modulate content sent to respective customer premise equipment.

A method receives error measurements from network elements. Groups of network elements are generated based on similarity of error measurements and a bitloading profile for each of the groups of network elements is generated based on the error measurements for each respective group. Each bitloading profile includes a modulation level determined to be sufficient for transporting content to respective groups of network elements. The method then assigns a set of bitloading profiles to each network element based on the groups of network elements and the bitloading profile generated for each of the groups. The bitloading profile for each of the groups of network elements and the assigned set of bitloading profiles are output to a network device. The network device uses the bitloading profiles to modulate content sent to respective customer premise equipment.