Abstract: This disclosure relates to method and system for building ensemble models using competitive reinforcement learning (CRL). The method may include creating a plurality of clusters, each including a set of predictive models forming the ensemble model. For each of the plurality of clusters, the method may further include initializing each of the set of predictive models with random values for a set of first parameters to obtain a first accuracy score, categorizing each of the set of predictive models into a first associated category based on a first accuracy score, calculating a first reward for each of the set of predictive models based on the first associated category, and determining a set of second parameters for each of the set of predictive models using CRL to obtain a second accuracy score.

Abstract: A prediction manager for providing responsiveness predictions for deployments includes persistent storage and a predictor. The persistent storage stores training data and conditioned training data. The predictor is programmed to obtain training data based on: a configuration of at least one deployment of the deployments, and a measured responsiveness of the at least one deployment, perform a peak extraction analysis on the measured responsiveness to obtain conditioned training data, obtain a prediction model using: the training data, and a first untrained prediction model, obtain a confidence prediction model using: the conditioned training data, and a second untrained prediction model, obtain a combined prediction using: the prediction model, and the confidence prediction model, and perform, based on the combined prediction, an action set to prevent a responsiveness failure.

Abstract: A computer-implemented method includes receiving first inputs associated with a first modality and second inputs associated with a second modality; processing the received first and second inputs with convolutional neural networks (CNN), wherein a set of first weights are used to handle the first inputs and a second set of weights are used to handle the second inputs; determining a loss for each of the first and the second inputs based on a loss function that applies the first set of weights, the second set of weights, and a presence of a co-occurrence; generating a shared feature space as an output of the CNNs, wherein a distance between cells associated with the first inputs and the second inputs in the shared feature space is determined based on the loss associated with each of the first inputs and the second inputs; and based on the shared feature space, providing an output.

Abstract: In an approach to deriving highly accurate models, one or more computer processors train a set of machine learning models utilizing a training set and a deep learning algorithm; generate one or more feedback data sets for each model in the set of trained models; rank each model in the set of trained models based on the generated feedback data sets; dynamically adjust one or more thresholds, that initiate a retraining or deployment of one or more ranked models, based, at least in part, on one or more production environment requirements; responsive to exceeding one or more adjusted thresholds, automatically deploy one or more ranked models to one or more deployment environments based, at least in part, on the ranking of the one or more trained models; responsive to not exceeding one or more adjusted thresholds, retrain each model in the set of trained models.

Abstract: Embodiments of this application provide a charging session method and an apparatus. A control plane function entity determines to request a charging function (CHF) entity to establish a service-based interface (SBI) charging session for a 4G data connection. The control plane function entity requests, through the SBI charging session, to perform online charging and/or offline charging in the 4G data connection. According to the method, the SBI charging session that is requested by the control plane function entity to establish for the 4G data connection may support performing the online charging in the 4G data connection, and support performing the offline charging in the 4G data connection. Therefore, the disclosed embodiments simplify a procedure of charging online data and offline data in the 4G data connection by using different charging sessions.

Abstract: A data processing method is proposed, including: sensing, via at least one sensing portion, target information of a target device; receiving and processing, via an electronic device, the target information of the sensing portion to form feature information; processing, via the electronic device, the feature information into a label matrix, and establishing, via an artificial intelligence training method, a target model based on the label matrix; and after the electronic device captures real-time information of the target device, predicting, via the target model, a life limit of the target device, wherein a content of the target information is corresponding to a content of the real-time information. Thus, a good target model is constituted and is advantageous in training artificial intelligence by processing the feature information into the label matrix.

Abstract: This application discloses a roaming charging method and apparatus. A blockchain network stores information related to roaming fee settlement, to reduce a possibility that the information related to roaming fee settlement is tampered with. In addition, a digital signature algorithm is used to sign roaming service statistics to generate an abstract, to further prevent the roaming service statistics from being tampered with. In this way, when a home carrier verifies a roaming account balance by using the roaming service statistics and a roaming charging rule, accuracy of a verification result can be ensured, and the home carrier can obtain an accurate roaming fee of a user.

Abstract: System and method embodiments are provided for non-cellular wireless access. In an embodiment, a method for non-cell grid based radio access in a radio access network includes determining, by a controller, a group of transmit points (TPs) to assign to a logical entity; assigning, by the controller, a logical entity identifier (ID) to the logical entity, wherein the logical entity ID identifies the logical entity through which a user equipment (UE) communicates with the radio access network; and causing, by the controller, at least one of the TPs in the logical entity to send signals to the UE.

Abstract: A car lens offset detection method and a car lens offset detection system are provided. The first image capturing device and the second image capturing device are disposed on a car, and the method includes: capturing a first image with use of a first image capturing device and capturing a second image with use of a second image capturing device; obtaining a plurality of first feature points from the first image according to a plurality of first predetermined positions and obtaining a plurality of second feature points from the second image according to a plurality of second predetermined positions; comparing feature values of the first feature points with feature values of the second feature points and determining whether the first feature points match the second feature points; in response to the first feature points not matching the second feature points, performing a calibration and warning operation.

Abstract: There are provided measures for coordinated session charging in roaming scenarios. Such measures (of a first session management entity of a first mobile network in a roaming charging related scenario between said first mobile network and a second mobile network) exemplarily comprise transmitting a session creation request message to a second session management entity of said second mobile network, said session creation request message including information indicative of a first configuration utilized for mobile network related charging, and receiving a session creation response message from said second session management entity of said second mobile network, said session creation response message including information indicative of a second configuration utilized for mobile network related charging.

Abstract: Systems and methods include obtaining monitored traffic from an S1 interface; detecting a Secondary Radio Access Technology (RAT) Data Usage Report (DUR) in the monitored traffic; determining whether the Secondary RAT DUR relates to a 5G Non-Standard Architecture (NSA), and, if so, determining an address of a gNodeB in the Secondary RAT DUR; and storing the address of the gNodeB in a database. The systems and methods can include, for a call, updating a Call Detail Record (CDR) to reflect one of 5G NSA and 4G based on whether an address in the CDR is in the database.

Abstract: Disclosed is an image processing apparatus and a method of operating the same. The image processing apparatus includes: a memory storing information on at least one random patch; and at least one processor configured to: obtain correlations between a pixel block included in an input image and each of a plurality of random patches obtained from the information on the at least one random patch, obtain weights respectively for the plurality of random patches on a basis of the obtained correlations and apply the weights respectively to the plurality of random patches, and obtain an output image by applying, to the pixel block, the plurality of random patches to which the weights are respectively applied.

Abstract: A learning and discrimination device configured to perform learning by gradient boosting, including: a histogram memory unit configured to store, for each value of a feature amount, a histogram obtained by integrating gradient information corresponding to the value in sample data; a category accumulated gradient calculator configured to calculate a histogram corresponding to a value of the feature amount corresponding to a threshold for the feature amount as a cumulative sum of the gradient information; a non-category accumulated gradient calculator configured to calculate, as a cumulative sum of the gradient information, a sum of a histogram corresponding to a value of the feature amount that is classified using a classification method with the threshold different from the category accumulated gradient calculator; and a cumulative sum selector configured to output the cumulative sum calculated by the category accumulated gradient calculator or the non-category accumulated gradient calculator.

Abstract: The present invention refers to a method and apparatus and computer program for detecting communities in a radio access network with a plurality of vertices (C, BBU), wherein the method comprises calculating (S11) relationship strengths (31, 41) for network connections between the vertices (C, BBU) by executing a connection strength calculation process by analyzing performance factors, decisive for network performance including cell coverage overlap, signal strength, and inter-cell interference. The method further creates (S12) a network graph with nodes, representing the vertices (C,BBU) in the network and edges, representing the network connections based on the calculated relationship strengths (31, 41) and applies (S13) an extended iterative disjoint community detection algorithm for clustering nodes into communities, wherein in each iteration imposed one or more constraints for clustering cooperating nodes into the same community are analyzed (S14).

Abstract: A network element configured to support charging for a service in a network accesses policy rules defining a rating group to be used for offline charging. While a protocol data unit (PDU) session for user equipment is being established in the network, the network element sends, to a charging function configured to send charging data records related to service usage to a billing domain, a charging data request that establishes offline charging for the PDU session and indicates the rating group. The network element also receives, from the charging function, a charging data response including one or more triggers and thresholds for the rating group for the offline charging.

Abstract: A situation recognition device (10) including a surveillance processor (1) and an AI system (3). The surveillance processor receives visual and/or acoustic surveillance signals (E) from an aircraft passenger compartment (20) via an input interface (7). The AI system (3) includes an AI processor (4), a rule set generator (5) based on self-learning algorithms, and a reference rule set memory (6). The AI system is in bidirectional data communication with the surveillance processor (1). The AI processor (4) checks, upon a request (Q) from the surveillance processor (1), data patterns in the received visual and/or acoustic surveillance signals (E) for deviations from data patterns in a reference rule set (R) stored in the reference rule set memory (6). The surveillance processor (1) outputs indicator signals (A) via the output interface (8) if deviations determined by the AI processor (4) exceed one or more predefinable deviation threshold values.

Abstract: A policy control and resource function (PCRF) is subscribed (at a network entity) to receive notifications of events for a first set of presence reporting areas (PRAs) associated with a packet data network (PDN) connection involving a user equipment. An online charging system (OCS) is subscribed (at the network entity) to receive notifications of events for a second set of PRAs associated with the PDN connection involving the user equipment. The network entity notifies an off-line charging system (OFCS) in response to a first event occurring at one or more first PRAs that are in the first set of PRAs.

Abstract: A holding apparatus and method may be used to secure and support a portable electronic device. The apparatus has a base plate that fits along the back surface of a portable electronic device. The base plate has top and bottom base plate surfaces. The apparatus has a strip that fits along the top base plate surface. The apparatus has a frame on the top base plate surface. The frame defines an aperture. The apparatus has pins and recesses that form hinged connections and secure the strip to the base plate. The strip is moveable between engaged and disengaged positions within the aperture.

Abstract: A wireless communication network charges a user for a wireless data service over an Exposure Function (EF). The EF exposes a service capability and charge to the user. The EF maps the service capability into network parameters and transfers the network parameters to a network control-plane. The control-plane receives and translates the network parameters into network signaling and transfers the network signaling to a network user-plane. The user-plane receives the network signaling and user data. The user-plane transfers the user data responsive to the network signaling and transfers session data that characterizes the user data transfer to the control-plane. The control-plane transfers the session data to the EF. The EF maps the session data into a service delivery event that that characterizes the user data transfer, service capability, and service charge. The EF exposes the service delivery event to the user.

Abstract: The present invention discloses methods and systems for sharing data usage by a plurality of SIM cards at a plurality of network devices. Each of the plurality of network devices is capable of housing at least one SIM card from the plurality of SIM cards. The method comprises the steps of determining the total data usage allowance. A remaining total data usage allowance is determined by either retrieving it from a carrier server or by subtracting aggregated data usage information from the total data usage allowance. The method further comprises restricting use of one or more of the plurality of SIM cards when the remaining total data usage allowance is below a first threshold until the remaining total data usage allowance is above the first threshold. The total data usage allowance is changed to a first value periodically or according to an administrator's instruction.