Abstract: The technologies described herein are generally directed to placing edge hub equipment for virtual radio access networks based on resource availability and performance in advanced networks, such as a fifth generation (5G) network or other next generation networks. For example, a method described herein can include receiving a request to select, for deployment of hub equipment, between site locations, with the deployment of the hub equipment being to connect, in a fronthaul segment, radio unit equipment of the network at a radio location to a backhaul connection equipment. The method can further include, based on the request, the radio location, and the backhaul location, comparing a characteristic of the site locations. Further, the method can include responding to the request with a selected site location that was selected based on a result of the comparing.

Abstract: An actuator for supplying compressed air for cleaning and drying a sensor of a vehicle, includes a compression unit configured to compress air from outside to form high-pressure compressed air, a drying unit configured to receive the compressed air compressed to a high pressure by the compression unit via a movement passage to remove moisture from the compressed air, and a storage tank connected to the drying unit via a connecting passage and configured to store the compressed air passing through the drying unit to be supplied to the vehicle, wherein the compressed air is stored in the storage tank so that high-pressure compressed air is generated and sprayed to the sensor of the vehicle, cleaning and drying the same in a short time.

Abstract: Disclosed is a neural network learning apparatus for deep learning and a method thereof. A neural network learning apparatus for deep learning according to an embodiment of the present disclosure includes an input interface, a memory, and a learning processor for applying a Gradient Descent algorithm to a neural network model, and the learning processor may transform a cumulative change function of the gradient for an error function into an inverse square root function in the Gradient Descent algorithm, and operate an inverse square root approximate value by using a Newton-Raphson method for the transformed inverse square root function. The neural network learning apparatus for deep learning of the present disclosure may be connected or converged with an Artificial Intelligence module, an Unmanned Aerial Vehicle (UAV), a robot, an Augmented Reality (AR) apparatus, a Virtual Reality (VR), or a 5G network service-related apparatus, etc.

Abstract: A framework in a cloud network that may allow for debugging at multiple vantage points at different layers (e.g., layer 2, layer 3, etc.). The methods may provide tracer or measurement services that filter, capture, or forward flows that may include packets, calls, or protocols to look for particular signatures.

Abstract: Disclosed is a neural network learning apparatus for deep learning and a method thereof. A neural network learning apparatus for deep learning according to an embodiment of the present disclosure includes an input interface, a memory, and a learning processor for applying a Gradient Descent algorithm to a neural network model, and the learning processor may transform a cumulative change function of the gradient for an error function into an inverse square root function in the Gradient Descent algorithm, and operate an inverse square root approximate value by using a Newton-Raphson method for the transformed inverse square root function. The neural network learning apparatus for deep learning of the present disclosure may be connected or converged with an Artificial Intelligence module, an Unmanned Aerial Vehicle (UAV), a robot, an Augmented Reality (AR) apparatus, a Virtual Reality (VR), or a 5G network service-related apparatus, etc.

Abstract: A framework in a cloud network that may allow for debugging at multiple vantage points at different layers (e.g., layer 2, layer 3, etc.). The methods may provide tracer or measurement services that filter, capture, or forward flows that may include packets, calls, or protocols to look for particular signatures.

Abstract: A framework in a cloud network that may allow for debugging at multiple vantage points at different layers (e.g., layer 2, layer 3, etc.). The methods may provide tracer or measurement services that filter, capture, or forward flows that may include packets, calls, or protocols to look for particular signatures.

Abstract: A framework in a cloud network that may allow for debugging at multiple vantage points at different layers (e.g., layer 2, layer 3, etc.). The methods may provide tracer or measurement services that filter, capture, or forward flows that may include packets, calls, or protocols to look for particular signatures.

Abstract: A method and apparatus for providing radio communication with an electronic object in a local environment are disclosed. For example the method receives via a mobile endpoint device of a user at least one first digital certificate associated with the local environment from a trusted source, and a second digital certificate from the electronic device deployed in the local environment via a wireless connection. The method then authenticates the electronic device using the at least one first digital certificate and the second digital certificate.

Abstract: A framework in a cloud network that may allow for debugging at multiple vantage points at different layers (e.g., layer 2, layer 3, etc.). The methods may provide tracer or measurement services that filter, capture, or forward flows that may include packets, calls, or protocols to look for particular signatures.

Abstract: A mobile participation platform enables a wireless network operator or third party to solicit response data related to a specific time and location specific event by signaling multiple mobile device users that meet predefined qualifications. The qualifications include presence at the specific location at the specific time, and may include other characteristics, such as prior consent to receive solicitations, and particular device type or data collection functionality. The platform locates mobile devices that may qualify for participation, and generates and transmits a solicitation. Mobile devices receiving the solicitation may activate a participation client to acknowledge the solicitation and to contribute by submitting the requested response data, which may include photos, text, sensor data, audio, video and the like.

Abstract: A method and computer readable medium for encoding data onto a channel broadcasting a program are disclosed. For example, the method selects a channel that is being used to broadcast a program, generates data having characteristics in accordance with an error burst signature and transmits the data on the channel that is being used to broadcast the program.

Abstract: A method and apparatus to enable IP networking for mobile hosts without requiring changes to be made to the TCP/IP stack in the operating system installed on the mobile hosts. The apparatus is an “intelligent device” that can be installed on or connected to a mobile host, and may comprise a software-only logical module, physical hardware, or a combination of both. To a mobile host, the intelligent device emulates a network interface such as an Ethernet card or a telephone modem. The intelligent device appears to an access network just like any regular IP host connected to the access network through a physical network interface device. The intelligent device handles all mobile networking functions for the mobile host, and may control multiple different physical network interface devices to enable a connection to an access network available to the mobile user at his location.

Abstract: A mobile participation platform enables a wireless network operator or third party to solicit response data related to a specific time and location specific event by signaling multiple mobile device users that meet predefined qualifications. The qualifications include presence at the specific location at the specific time, and may include other characteristics, such as prior consent to receive solicitations, and particular device type or data collection functionality. The platform locates mobile devices that may qualify for participation, and generates and transmits a solicitation. Mobile devices receiving the solicitation may activate a participation client to acknowledge the solicitation and to contribute by submitting the requested response data, which may include photos, text, sensor data, audio, video and the like.

Abstract: A method and computer readable medium for encoding data onto a channel broadcasting a program are disclosed. For example, the method selects a channel that is being used to broadcast a program, generates data having characteristics in accordance with an error burst signature and transmits the data on the channel that is being used to broadcast the program.

Abstract: A method and apparatus for providing radio communication with an electronic object in a local environment are disclosed. For example the method receives via a mobile endpoint device of a user at least one first digital certificate associated with the local environment from a trusted source, and a second digital certificate from the electronic device deployed in the local environment via a wireless connection. The method then authenticates the electronic device using the at least one first digital certificate and the second digital certificate.

Abstract: A mobile participation platform enables a wireless network operator or third party to solicit response data related to a specific time and location specific event by signaling multiple mobile device users that meet predefined qualifications. The qualifications include presence at the specific location at the specific time, and may include other characteristics, such as prior consent to receive solicitations, and particular device type or data collection functionality. The platform locates mobile devices that may qualify for participation, and generates and transmits a solicitation. Mobile devices receiving the solicitation may activate a participation client to acknowledge the solicitation and to contribute by submitting the requested response data, which may include photos, text, sensor data, audio, video and the like.

Abstract: A method and computer readable medium for encoding data onto a channel broadcasting a program are disclosed. For example, the method selects a channel that is being used to broadcast a program, generates data having characteristics in accordance with an error burst signature and transmits the data on the channel that is being used to broadcast the program.

Abstract: A method and apparatus for providing radio communication with an electronic object in a local environment are disclosed. For example the method receives via a mobile endpoint device of a user at least one first digital certificate associated with the local environment from a trusted source, and a second digital certificate from the electronic device deployed in the local environment via a wireless connection. The method then authenticates the electronic device using the at least one first digital certificate and the second digital certificate.

Abstract: A method and apparatus to enable IP networking for mobile hosts without requiring changes to be made to the TCP/IP stack in the operating system installed on the mobile hosts. The apparatus is an “intelligent device” that can be installed on or connected to a mobile host, and may comprise a software-only logical module, physical hardware, or a combination of both. To a mobile host, the intelligent device emulates a network interface such as an Ethernet card or a telephone modem. The intelligent device appears to an access network just like any regular IP host connected to the access network through a physical network interface device. The intelligent device handles all mobile networking functions for the mobile host, and may control multiple different physical network interface devices to enable a connection to an access network available to the mobile user at his location.