Abstract: Systems, methods, apparatuses, and computer program products for dependency-aware quality of service (QoS) profile provisioning. The method may include obtaining information on at least one application data flow, and dependency information between one application and at least one other application. The method may also include receiving, from a network, information on an updated quality of service profile for the at least one application, and information on another updated quality of service profile for the at least one other application.

Abstract: Disclosed is a method comprising obtaining first input data, that is image-based input data, and second input data, that is sensor-based input data, providing the first input data and the second input data to an encoder, wherein the encoder uses a machine learning model for mapping the first and second input data to encoded modulation symbols, adding a reference signal to the encoded modulation symbols, allocating transmission time interval resource units to the encoded modulation symbols with the reference signal, and transmitting the symbols with the reference signal to a transmission channel.

Abstract: An intelligent pesticide spraying robot self-adaptive to terrain of mountain land is provided. Walking mechanisms are respectively connected to both side ends of a chassis. A pesticide spraying mechanism includes rotary drive mechanisms respectively connected to both sides of the rear end of the chassis, telescopic spray boom mechanisms correspondingly connected to the rotary drive mechanisms, rotary nozzle mechanisms correspondingly connected to the telescopic spray boom mechanisms, a liquid pesticide storage box fixed to the top of the chassis, a first water pump fixed in the liquid pesticide storage box, and first water pipes in communication with the first water pump and the rotary nozzle mechanisms. A control chip of a control identification mechanism is communicatively connected to the walking mechanisms, the rotary drive mechanisms, the telescopic spray boom mechanisms, the rotary nozzle mechanisms, the first water pump, a front-end camera, side-end cameras and ultrasonic sensors respectively.

Abstract: An apparatus for use by a communication network control element or function configured to control a setting of parameters of a self-organizing communication network, the apparatus comprising at least one processing circuitry, and at least one memory for storing instructions to be executed by the processing circuitry, wherein the at least one memory and the instructions are configured to, with the at least one processing circuitry, cause the apparatus at least: to obtain a pre-trained network optimization model indicating a mapping between a communication network environment forming an input of the model, optimization actions or decisions forming an output of the model, and system performance indicators forming a reward, to cause sending, to at least one communication network element or function forming a part of the self-organizing communication network, a request for providing similarity data for a similarity analysis allowing to determine a similarity between a part of the self-organizing communication netw

Abstract: A deep transfer reinforcement learning (DTRL) method based on transfer learning within a deep reinforcement learning (DRL) framework is provided to accelerate the GoB optimization decisions when experiencing environment changes in the same source radio network agent or when being applied from a source radio network agent to a target radio network agent. The transferability of the knowledge embedded in a pre-trained neural network model as a Q-approximator is exploited, and a mechanism to transfer parameters from a source agent to a target agent is provided, where the transferability criterion is based on the similarity measure between the source and target domain.

Abstract: An apparatus, comprising: at least one processing circuitry, and at least one memory for storing instructions to be executed by the processing circuitry, wherein the at least one memory and the instructions are configured to, with the at least one processing circuitry, cause the apparatus at least to: input display data obtained from a first terminal endpoint device located in a first three-dimensional environment into a deep neural network model for terminal endpoint device pose estimation, the display data comprising at least image data of a captured image of at least part of the first three-dimensional environment acquired by the first terminal endpoint device at a first point of time and sensory data indicative of at least a motion vector of a movement of the first terminal endpoint device in the three-dimensional environment acquired by the first terminal endpoint device at a second point of time, the deep neural network model being trained with, as model input, training image data of a captured training

Abstract: An intelligent pesticide spraying robot self-adaptive to terrain of mountain land is provided. Walking mechanisms are respectively connected to both side ends of a chassis. A pesticide spraying mechanism includes rotary drive mechanisms respectively connected to both sides of the rear end of the chassis, telescopic spray boom mechanisms correspondingly connected to the rotary drive mechanisms, rotary nozzle mechanisms correspondingly connected to the telescopic spray boom mechanisms, a liquid pesticide storage box fixed to the top of the chassis, a first water pump fixed in the liquid pesticide storage box, and first water pipes in communication with the first water pump and the rotary nozzle mechanisms. A control chip of a control identification mechanism is communicatively connected to the walking mechanisms, the rotary drive mechanisms, the telescopic spray boom mechanisms, the rotary nozzle mechanisms, the first water pump, a front-end camera, side-end cameras and ultrasonic sensors respectively.

Abstract: An apparatus comprising means for performing: sending a request to a user device, wherein the user device is located in an environment; receiving, in response to the request, image information of the environment from the user device; constructing a three dimensional model of the environment based on the image information; obtaining information from the three dimensional model of the environment; and generating a radio propagation model of the environment using information obtained from the three dimensional model of the environment.

Abstract: An apparatus for use by a communication network control element or function configured to control a setting of parameters of a self-organizing communication network, the apparatus comprising at least one processing circuitry, and at least one memory for storing instructions to be executed by the processing circuitry, wherein the at least one memory and the instructions are configured to, with the at least one processing circuitry, cause the apparatus at least: to obtain a pre-trained network optimization model indicating a mapping between a communication network environment forming an input of the model, optimization actions or decisions forming an output of the model, and system performance indicators forming a reward, to cause sending, to at least one communication network element or function forming a part of the self-organizing communication network, a request for providing similarity data for a similarity analysis allowing to determine a similarity between a part of the self-organizing communication netw

Abstract: The present disclosure discloses a method and an apparatus for processing seismic data, and belongs to the field of geological surveys. The method comprises: stacking seismic trace gathers in a predetermined range among S seismic trace gathers after a Normal Move Out (NMO) correction processing to obtain a model trace, S being an integer; calculating a correlation coefficient of each seismic trace gather with the model trace, and selecting a K-th seismic trace gather with a maximum correlation coefficient; calculating an optimum point of each seismic trace gather from the K-th seismic trace gather to two sides orderly; and performing a residual NMO correction of the seismic trace gathers according to the optimum points.

Abstract: A system, apparatus, method, and non-transitory computer readable medium for haptic augmented reality (AR) based feedback for user-centric wireless network may include a mobile device including a display device configured to display an AR user interface of a user's physical location, a location sensor configured to obtain real-time physical location information related to the mobile device, at least one wireless transceiver configured to determine characteristics of at least one wireless network, a camera configured to obtain at least one image of the user's physical location, a memory having computer readable instructions stored thereon, and at least one processor configured to execute the computer readable instructions to provide haptic AR based feedback for user-centric wireless networks.

Abstract: The present disclosure discloses a method and an apparatus for processing seismic data, and belongs to the field of geological surveys. The method comprises: stacking seismic trace gathers in a predetermined range among S seismic trace gathers after a Normal Move Out (NMO) correction processing to obtain a model trace, S being an integer; calculating a correlation coefficient of each seismic trace gather with the model trace, and selecting a K-th seismic trace gather with a maximum correlation coefficient; calculating an optimum point of each seismic trace gather from the K-th seismic trace gather to two sides orderly; and performing a residual NMO correction of the seismic trace gathers according to the optimum points.

Abstract: A method for a radio communication network is provided. The method includes displaying, to a user, a real-world environment view which is augmented with information about at least one access point of the radio communication network located in the real-world. Further, the method includes receiving a user input which indicates a desired interaction between the user and the access point. The method also includes transmitting information about the desired interaction to a management node of the radio communication network.

Abstract: A server receives signals indicating an alert condition for a location that is defined by a set of location attributes and identifies one or more base stations that serve one or more cells that overlap with the location, which encompasses less than all of the cells. The server transmits a message to the one or more base stations identifying the alert condition and including the set of location attributes. A user equipment receives the message identifying the alert condition and including the set of location attributes that define the location of the alert condition. The user equipment compares a location of the user equipment to the set of location attributes and generates an alert in response to the location of the user equipment being within the location of the alert condition.

Abstract: An application type of a bearer is classified by computing statistics vectors of bearer metrics and locating points on a label map corresponding to the statistics vectors to obtain application type information. The application type information is exported to a network node to control an operation of application. The bearer metrics include bearer identifier information and bearer condition information, where the bearer condition information includes channel condition information and cell congestion level information. The bearers are paired, such that uplink and downlink bearers for a same application are identified, so that paired bearers are classified together. The label map is produced using previously classified bearer information to calculate cluster centroids and cluster regions that define portions of the map for particular application types.

Abstract: Fast congestion detection is implemented in a wireless radio access network (RAN) to mitigate congestion by classifying bearers into bearer types using bearer metrics and monitoring bearers for type specific anomalies to obtain anomaly data. Congestion is detected based on the anomaly data to obtain congestion information that is exported to a network node to mitigate network congestion. Bearer metrics include radio link protocol (RLC) buffer size information, physical resource block (PRB) utilization information, and transmission burst interval information. The transmission burst interval information includes information on time intervals between successive time periods when a RLC buffer is empty. The bearers are classified into Type I and Type II bearers. Type I bearers are bearers displaying bursty data transfer behavior, and Type II bearers are bearers displaying a continuous stream of data transfer behavior.

Abstract: A smoothed transport block size is forecasted by predicting future value information based on historical time series data obtained at an e-Node B. The historical time series data includes historical transport block size information and historical modulation and coding scheme information. A mapping function is used to correlate the future value information with historical transport block size information. Once the mapping function is determined, the mapping function forecasts the average transport block sizes by inputting the future value information into the mapping function. The smoothed transport block sizes and the future value information is then transmitted to an application server and/or an application client at a user equipment to control an operation of an application.

Abstract: An application type of a bearer is classified by computing statistics vectors of bearer metrics and locating points on a label map corresponding to the statistics vectors to obtain application type information. The application type information is exported to a network node to control an operation of application. The bearer metrics include bearer identifier information and bearer condition information, where the bearer condition information includes channel condition information and cell congestion level information. The bearers are paired, such that uplink and downlink bearers for a same application are identified, so that paired bearers are classified together. The label map is produced using previously classified bearer information to calculate cluster centroids and cluster regions that define portions of the map for particular application types.

Abstract: Fast congestion detection is implemented in a wireless radio access network (RAN) to mitigate congestion by classifying bearers into bearer types using bearer metrics and monitoring bearers for type specific anomalies to obtain anomaly data. Congestion is detected based on the anomaly data to obtain congestion information that is exported to a network node to mitigate network congestion. Bearer metrics include radio link protocol (RLC) buffer size information, physical resource block (PRB) utilization information, and transmission burst interval information. The transmission burst interval information includes information on time intervals between successive time periods when a RLC buffer is empty. The bearers are classified into Type I and Type II bearers. Type I bearers are bearers displaying bursty data transfer behavior, and Type II bearers are bearers displaying a continuous stream of data transfer behavior.

Abstract: A smoothed transport block size is forecasted by predicting future value information based on historical time series data obtained at an e-Node B. The historical time series data includes historical transport block size information and historical modulation and coding scheme information. A mapping function is used to correlate the future value information with historical transport block size information. Once the mapping function is determined, the mapping function forecasts the average transport block sizes by inputting the future value information into the mapping function. The smoothed transport block sizes and the future value information is then transmitted to an application server and/or an application client at a user equipment to control an operation of an application.