Abstract: This disclosure provides a method of detecting and deterring a target animal from a target area. A target area is positioned within the field of vision of a video camera connected to a computer processing system. An animal identification computer program using convolution neural networks and deep learning computer programs and camera images rapidly detects a target animal. The animal identification computer program is trained to identify target animals accurately using a learning algorithm and related machine learning technology. The time to deploy a deterrent against a target animal from the instant of detection is 2 seconds or less so that little or no time is available to the target animal to damage the target area.

Abstract: A stretchable net cover for a mobile electronic device that provides multiple grasp points and configurations, providing a user with a plurality of ways to hold and use their devices. A user may slide one or more fingers through openings in the netting material to grasp the device, may slide the netting over a forearm, or may hook the device to a purse, belt loop, carabiner, lanyard, retractable or static leash via the netting material. The cover may be provided as an add-on, i.e., designed for use over a mobile electronic device alone or a device enclosed within a case, or may be provided as part of a case for a mobile electronic device.

Abstract: Methods, a policy node and a charging node for enabling spending limit control for a user equipment in a telecommunication network. The policy node obtains an identifier related to the user equipment, an identifier of a policy counter and a set of policy counter statuses to be monitored by the policy node. The set of policy counter statuses are related to the identifier of the policy counter. The policy node sends, a request for reporting of policy counter statuses related to the user equipment for the policy counter. The request includes the identifier related to the user equipment, the identifier of the policy counter and the set of policy counter statuses. A policy counter status of the set of policy counter statuses is determined. The policy counter status has changed as determined by the charging node. A response to the request is sent and includes the policy counter status that has changed.

Abstract: A method and system for determining a geographical location and orientation of a vehicle (200, 300) travelling through a road network is disclosed. The method comprises obtaining, from one or more cameras (202, 302) associated with the vehicle (200, 300) travelling through the road network, a sequence of images (500) reflecting the environment of the road network on which the vehicle (200, 300) is travelling, wherein each of the images has an associated camera location at which the image was recorded. A local map representation representing an area of the road network on which the vehicle (200, 300) is travelling is then generated using at least some of the obtained images and the associated camera locations.

Abstract: A wireless communication network charges a user for a wireless network slice over a Network Exposure Function (NEF). A network user-plane transfers user data over the wireless network slice. In response, the network user-plane generates session data that characterizes the user data transfer over the wireless network slice. The network user-plane transfers the session data to the NEF. The NEF receives the session data and generates a service charge for the wireless network slice based on the session data. The NEF transfers the service charge for the wireless network slice and at least a portion of the session data to a distributed ledger associated with the user.

Abstract: Dimensioning a policy and charging rules function (PCRF) of a communication system comprises: determining a number of processing nodes of the PCRF at a time; determining a first transaction parameter indicating a number of transactions per second exchanged by the nodes at the time; determining a load parameter indicating processing load of the nodes at the time; based on the first transaction parameter, the load parameter, the number of nodes, and allowable processing load that the nodes are set, determining a second transaction parameter indicating a number of transactions per second expected for exchange at the time by the nodes set at the allowable processing load; forecasting the first and second transaction parameters for a following time thereby obtaining forecasted first and second transaction parameters; and determining a number of nodes required at the following time according to the forecasted first and second transaction parameters.

Abstract: A computing device operating on a Linux or Android platform for adding features to an in-vehicle infotainment system of a vehicle; it has an input/output interface; a power source input; a processor; and memory storing program code that, when executed by the processor, causes the processor to receive an Android-based smartphone infotainment application program; scan program code of the Android-based smartphone infotainment application program using a predefined pattern to locate a base certificate in the program code of the Android-based smartphone infotainment application program; generate a certificate-key pair from the base certificate; transmit the certificate of the certificate-key pair to the infotainment system for authentication and to enable communication with an Android protocol between the computing device and the infotainment system; and cause a display of information associated with a feature application program for display on the infotainment system; methods of use thereof.

Abstract: A personal help button and the administrator part of a personal emergency response system are provided, in which verbal audio is converted into a low bandwidth format signal. A conversation algorithm is used which comprises a trained neural network. The low bandwidth format has a bandwidth below 500 bits/second.

Abstract: There is provided a portable electronic device including a backlight module, an ambient light sensor, a proximity sensor and a processing unit. The backlight module illuminates with backlight brightness. The ambient light sensor is configured to detect ambient light intensity. The proximity sensor is configured to detect an object. The processing unit is configured to activate the proximity sensor when the ambient light intensity detected by the ambient light sensor is lower than a predetermined value or decreases more than a predetermined range, and to maintain or reduce the backlight brightness according to a detection result of the proximity sensor. There is further provided an automatic detection method.

Abstract: This application sets forth techniques for managing phone number-based user accounts. According to some embodiments, a server computing device can be configured to carry out the steps of (1) receiving, from a first client computing device, a request to create a user account based on a phone number, (2) in response to authenticating that the first client computing device is associated with the phone number: creating the user account based on the phone number, creating a hidden contact address based on the phone number, and assigning the hidden contact address to the user account, and (3) in response to receiving a notification that a second client computing device is associated with the phone number: requiring the user account to be updated to be based on a different phone number, or assigning, to the user account, a visible contact address based on the phone number.

Abstract: Implementation of an application rule for an application to be accessed by a User Equipment, UE, in a user session in a Service Based Architecture, SBA, domain in a core network of a telecommunications system is disclosed. The SBA, among others, comprises a Policy Control Function, PCF (6), an Application Function, AF (5), and a Session Management Function, SMF (9). The method comprising the steps of receiving, by the PCF (6), an application rule comprising an AF Identifier, AF-ID, identifying the application rule, an Application Identifier, App-ID, identifying the application, and at least one service requirement for processing the application in the SBA domain. The PCF (6) instructing the SMF (9) to execute the at least one service requirement to all present and future user sessions pertaining to the respective application. Complementary methods of supporting the execution of the application rule and devices are also presented.

Abstract: The disclosed embodiments provide a system for processing data. During operation, the system obtains a training dataset containing a first set of records associated with a first set of identifier (ID) values and an evaluation dataset containing a second set of records associated with a second set of ID values. Next, the system selects a random subset of ID values from the second set of ID values. The system then generates a sampled evaluation dataset comprising a first subset of records associated with the random subset of ID values in the second set of records. The system also generates a sampled training dataset comprising a second subset of records associated with the random subset of ID values in the first set of records. Finally, the system outputs the sampled training dataset and the sampled evaluation dataset for use in training and evaluating a machine learning model.

Abstract: Techniques are described for generating population counts for seed production plants based on one or more images obtained from a camera on an aerial vehicle including, but not limited to, UAVs. The image(s) is processed to identify the plurality of rows of seed production plants, classify each one of the identified rows as either male or female, and produce a count of the number of seed production plants in the male rows and produce a count of the number of seed production plants in the female rows. The seed production plants can be corn seed plants or any other type of seed production plant in which male and female seed production plants can be distinguished from one another based on one or more aerial images.

Abstract: It is provided a method, comprising monitoring if a request for granting a requested quota for a subscriber is received; calculating a quota consumption speed based on a consumption of a previous quota granted to the subscriber and a duration during which the previous quota is consumed; determining a determined quota size based on the quota consumption speed; granting a granted quota to the subscriber in response to the received request, wherein the granted quota has the determined quota size.

Abstract: A system and method for resolving an unsatisfactory quality of experience (QoE) for an application executed on a wireless device that accesses a CSP network is described. A QoE network appliance generates an integrated event stream that includes a RAN data set, a CN data set, a NWDAF data set, a QoE latency measurement, a QoE bandwidth measurement, and a QoE packet loss rate measurement. A measured QoE score is generated with the RAN data set, the CN data set, and the NWDAF data set. The measured QoE score is associated with a QoE latency measurement, a QoE bandwidth measurement, and a QoE packet loss rate measurement. A robotics process automation (RPA) module receives the integrated event stream when the measured QoE score fails to satisfy the QoE requirement. The RPA module performs one or more automated actions to improve the measured QoE based on information from the integrated event stream.

Abstract: The present disclosure provides a method and system for automated analysis of human behavior. The automated analysis of human behavior is performed to determine fraudulent behavior. The system collects a technical data and a video data from one or more data sources and one or more video sources. In addition, the system trains a fraudulent behavior detection system with the collected technical data and the video data in real-time. Further, the system receives a live video stream data from the one or more video sources. Furthermore, the system analyzes the live video stream data received from the one or more video sources installed at the facility in real-time. Moreover, the system predicts likelihood of fraudulent behavior of humans based on analyzation of the live video stream data. Also, the system performs prediction to alarm concerned authorities of the facility about likelihood of fraudulent behavior.

Abstract: A method, system, and computer-usable medium are disclosed for, comprising: examining pairs of samples in each leaf node of a plurality of decision trees and for each pair of samples, determining a neighbor frequency of each pair of samples as a frequency of how often such pair of samples are filtered into a particular leaf node of the plurality of decision trees and for each leaf node of the plurality of decision trees, determining a neighbor frequency of the leaf node as an average of the neighbor frequencies of the samples of the leaf node.

Abstract: An apparatus of a wireless system, product to be implemented at a computer process of the wireless system, and method to operate the apparatus. The apparatus includes an input; an output; and processing circuitry connected to the input and to the output, the processing circuitry to implement logic to: receive, through the input and from a first modem of the wireless system, information on a traffic attribute relating to communication in compliance with a first wireless communication protocol; determine, based on the traffic attribute, blacklisted channels to be avoided during a discovery procedure by a second modem of the wireless system, the discovery being in compliance with a second wireless communication protocol; and send, through the output, information based on the blacklisted channels to the second modem to cause the second modem to avoid the blacklisted channels during the discovery procedure.

Abstract: A method including training predictor machine learning models (MLMs) using a first data set. The trained predictor MLMs are trained to predict classifications of data items in the first data set. The method also includes training confidence MLMs using second classifications, output by the trained predictor MLMs. The method also includes generating an aggregated ranked list of classes based on third classifications output by the trained predictor MLMs and second confidences output by the trained confidence MLMs. The method also includes training an ensemble confidence MLM using the aggregated ranked list of classes to generate a trained ensemble confidence MLM. The trained ensemble confidence MLM is trained to predict a corresponding selected classification for each corresponding data item in a training data set containing second data items similar to the first data items.

Abstract: Techniques are described herein for providing radio resource ownership indicators in charging records for a charging function. In one example, a method may include determining, by a session management node of a mobile network, that a user equipment is utilizing a particular radio resource of a mobile network resource for a Protocol Data Unit (PDU) session of the user equipment, wherein the mobile network resource is capable of being utilized via a plurality of radio resources and the particular radio resources is associated with an enterprise entity; and reporting charging information for the PDU session of the user equipment to a charging function of the mobile network to facilitate storing a charging record for the user equipment that is to include an identifier of the enterprise entity that is associated with the particular radio resource.